OVERVIEW OF EPA'S HUMAN EXPOSURE AND SOURCE-TO-DOSE MODELING PROGRAM: HEADSUP

EPA Science Inventory

EPA's human exposure and source-to-dose modeling program is designed to provide a scientifically sound approach to understanding how people are actually exposed to pollutants and the magnitude of predicted exposures and dose. The objective of this research project is to develo...

Active Rack Isolation System Program and Technical Status

NASA Technical Reports Server (NTRS)

Bushnell, Glenn; Fialho, Ian; Allen, James; Quraishi, Naveed

2000-01-01

The Boeing Active Rack Isolation System (ARIS) is one of the means used to isolate acceleration-sensitive scientific experiments from structurally transmitted disturbances aboard the International Space Station. The presentation provides an overview of ARIS and technical issues associated with the development of the active control system. An overview of ARIS analytical models is presented along with recent isolation performance predictions made using these models. Issues associated with commanding and capturing ARIS data are discussed and possible future options based on the ARIS ISS Characterization Experiment (ICE) Payload On-orbit Processor (POP) are outlined. An overview of the ARIS-ICE experiment scheduled to fly on ISS Flight 6A is presented. The presentation concludes with a discussion of recent- developmental work that includes passive rack damping, umbilical redesigns and advanced multivariable control design methods.

Empirical approaches to the study of language evolution.

PubMed

Fitch, W Tecumseh

2017-02-01

The study of language evolution, and human cognitive evolution more generally, has often been ridiculed as unscientific, but in fact it differs little from many other disciplines that investigate past events, such as geology or cosmology. Well-crafted models of language evolution make numerous testable hypotheses, and if the principles of strong inference (simultaneous testing of multiple plausible hypotheses) are adopted, there is an increasing amount of relevant data allowing empirical evaluation of such models. The articles in this special issue provide a concise overview of current models of language evolution, emphasizing the testable predictions that they make, along with overviews of the many sources of data available to test them (emphasizing comparative, neural, and genetic data). The key challenge facing the study of language evolution is not a lack of data, but rather a weak commitment to hypothesis-testing approaches and strong inference, exacerbated by the broad and highly interdisciplinary nature of the relevant data. This introduction offers an overview of the field, and a summary of what needed to evolve to provide our species with language-ready brains. It then briefly discusses different contemporary models of language evolution, followed by an overview of different sources of data to test these models. I conclude with my own multistage model of how different components of language could have evolved.

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Zipf, Mark E.

1989-01-01

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

Overview of meteorological measurements for aerial spray modeling.

PubMed

Rafferty, J E; Biltoft, C A; Bowers, J F

1996-06-01

The routine meteorological observations made by the National Weather Service have a spatial resolution on the order of 1,000 km, whereas the resolution needed to conduct or model aerial spray applications is on the order of 1-10 km. Routinely available observations also do not include the detailed information on the turbulence and thermal structure of the boundary layer that is needed to predict the transport, dispersion, and deposition of aerial spray releases. This paper provides an overview of the information needed to develop the meteorological inputs for an aerial spray model such as the FSCBG and discusses the different types of instruments that are available to make the necessary measurements.

Language Model Applications to Spelling with Brain-Computer Interfaces

PubMed Central

Mora-Cortes, Anderson; Manyakov, Nikolay V.; Chumerin, Nikolay; Van Hulle, Marc M.

2014-01-01

Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies. PMID:24675760

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Overview of the 1986--1987 atomic mass predictions

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

Haustein, P.E.

1988-07-01

The need for a comprehensive update of earlier sets of atomic mass predictions is documented. A project that grew from this need and which resulted in the preparation of the 1986--1987 Atomic Mass Predictions is summarized. Ten sets of new mass predictions and expository text from a variety of types of mass models are combined with the latest evaluation of experimentally determined atomic masses. The methodology employed in constructing these mass predictions is outlined. The models are compared with regard to their reproduction of the experimental mass surface and their use of varying numbers of adjustable parameters. Plots are presented,more » for each set of predictions, of differences between model calculations and the measured masses. These plots may be used to estimate the reliability of the new mass predictions in unmeasured regions that border the experimetally known mass surface. copyright 1988 Academic Press, Inc.« less

Event-driven simulation in SELMON: An overview of EDSE

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; Chien, Steve A.; Charest, Leonard, Jr.

1992-01-01

EDSE (event-driven simulation engine), a model-based event-driven simulator implemented for SELMON, a tool for sensor selection and anomaly detection in real-time monitoring is described. The simulator is used in conjunction with a causal model to predict future behavior of the model from observed data. The behavior of the causal model is interpreted as equivalent to the behavior of the physical system being modeled. An overview of the functionality of the simulator and the model-based event-driven simulation paradigm on which it is based is provided. Included are high-level descriptions of the following key properties: event consumption and event creation, iterative simulation, synchronization and filtering of monitoring data from the physical system. Finally, how EDSE stands with respect to the relevant open issues of discrete-event and model-based simulation is discussed.

Computational intelligence in earth sciences and environmental applications: issues and challenges.

PubMed

Cherkassky, V; Krasnopolsky, V; Solomatine, D P; Valdes, J

2006-03-01

This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The issues of data quality, selection of the error function, incorporation of the predictive learning methods into the existing modeling frameworks, expert knowledge, model uncertainty, and other application-domain specific problems are discussed. A brief overview of the papers in the Special Issue is provided, followed by discussion of open issues and directions for future research.

Care 3 model overview and user's guide, first revision

NASA Technical Reports Server (NTRS)

Bavuso, S. J.; Petersen, P. L.

1985-01-01

A manual was written to introduce the CARE III (Computer-Aided Reliability Estimation) capability to reliability and design engineers who are interested in predicting the reliability of highly reliable fault-tolerant systems. It was also structured to serve as a quick-look reference manual for more experienced users. The guide covers CARE III modeling and reliability predictions for execution in the CDC CYber 170 series computers, DEC VAX-11/700 series computer, and most machines that compile ANSI Standard FORTRAN 77.

The High-Throughput Stochastic Human Exposure and Dose Simulation Model (SHEDS-HT) & The Chemical and Products Database (CPDat)

EPA Science Inventory

The Stochastic Human Exposure and Dose Simulation Model – High-Throughput (SHEDS-HT) is a U.S. Environmental Protection Agency research tool for predicting screening-level (low-tier) exposures to chemicals in consumer products. This course will present an overview of this m...

Uncertainty analysis in ecological studies: an overview

Treesearch

Harbin Li; Jianguo Wu

2006-01-01

Large-scale simulation models are essential tools for scientific research and environmental decision-making because they can be used to synthesize knowledge, predict consequences of potential scenarios, and develop optimal solutions (Clark et al. 2001, Berk et al. 2002, Katz 2002). Modeling is often the only means of addressing complex environmental problems that occur...

Long-term predictive capability of erosion models

NASA Technical Reports Server (NTRS)

Veerabhadra, P.; Buckley, D. H.

1983-01-01

A brief overview of long-term cavitation and liquid impingement erosion and modeling methods proposed by different investigators, including the curve-fit approach is presented. A table was prepared to highlight the number of variables necessary for each model in order to compute the erosion-versus-time curves. A power law relation based on the average erosion rate is suggested which may solve several modeling problems.

An overview of the evaluation of oxygen interaction with materials-third phase (EOIM-III) experiment - Space Shuttle Mission 46

NASA Technical Reports Server (NTRS)

Leger, Lubert J.; Koontz, Steven L.; Visentine, James T.; Hunton, Donald

1993-01-01

An overview of EOIM-III, designed to produce benchmark atomic oxygen reactivity data is presented. Ambient density measurements are conducted using a quadrupole mass spectrometer calibrated for atomic oxygen measurements in a unique ground-based test facility. The combination of these data with the predictions of ambient density models permits an assessment of the accuracy of measured reaction rates on a variety of materials, many of which have never been tested in LEO previously.

Fundamental Mechanisms, Predictive Modeling, and Novel Aerospace Applications of Plasma Assisted Combustion. Overview of OSU Research Plan

DTIC Science & Technology

2009-11-04

air, low-temperature plasma chemistry kinetic model Nonequilibrium Thermodynamics Laboratories The Ohio State University • Air plasma model...problems require separate analysis: • Nsec pulse plasma / sheath models cannot incorporate detailed reactive plasma chemistry : too many species ( 100...and reactions ( 1 000)~ ~ , • Detailed plasma chemistry models (quasi-neutral) cannot incorporate repetitive, nsec time scale sheath dynamics and plasma

Operational Dust Prediction

NASA Technical Reports Server (NTRS)

Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas;

An Overview of the NASA Aviation Safety Program (AVSP) Systemwide Accident Prevention (SWAP) Human Performance Modeling (HPM) Element

NASA Technical Reports Server (NTRS)

Foyle, David C.; Goodman, Allen; Hooley, Becky L.

2003-01-01

An overview is provided of the Human Performance Modeling (HPM) element within the NASA Aviation Safety Program (AvSP). Two separate model development tracks for performance modeling of real-world aviation environments are described: the first focuses on the advancement of cognitive modeling tools for system design, while the second centers on a prescriptive engineering model of activity tracking for error detection and analysis. A progressive implementation strategy for both tracks is discussed in which increasingly more complex, safety-relevant applications are undertaken to extend the state-of-the-art, as well as to reveal potential human-system vulnerabilities in the aviation domain. Of particular interest is the ability to predict the precursors to error and to assess potential mitigation strategies associated with the operational use of future flight deck technologies.

Conformational Sampling in Template-Free Protein Loop Structure Modeling: An Overview

PubMed Central

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a “mini protein folding problem” under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized. PMID:24688696

Conformational sampling in template-free protein loop structure modeling: an overview.

PubMed

Li, Yaohang

2013-01-01

Accurately modeling protein loops is an important step to predict three-dimensional structures as well as to understand functions of many proteins. Because of their high flexibility, modeling the three-dimensional structures of loops is difficult and is usually treated as a "mini protein folding problem" under geometric constraints. In the past decade, there has been remarkable progress in template-free loop structure modeling due to advances of computational methods as well as stably increasing number of known structures available in PDB. This mini review provides an overview on the recent computational approaches for loop structure modeling. In particular, we focus on the approaches of sampling loop conformation space, which is a critical step to obtain high resolution models in template-free methods. We review the potential energy functions for loop modeling, loop buildup mechanisms to satisfy geometric constraints, and loop conformation sampling algorithms. The recent loop modeling results are also summarized.

OVERVIEW OF THE OZARK ISOPRENE EXPERIMENT (OZIE)

EPA Science Inventory

Ozone modeling studies, such as those performed for the Ozone Transport Advisory Group (OTAG), have raised concerns about extremely high isoprene concentrations (. 50ppbv) that have been predicted over the Ozark Plateau in southern Missouri. In response to these concerns, a col...

An Overview of Atmospheric Composition OSSE Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

daSilva, Arlinda

2012-01-01

A model-based Observing System Simulation Experiment (OSSE) is a framework for numerical experimentation in which observables are simulated from fields generated by an earth system model, including a parameterized description of observational error characteristics. Simulated observations can be used for sampling studies, quantifying errors in analysis or retrieval algorithms, and ultimately being a planning tool for designing new observing missions. While this framework has traditionally been used to assess the impact of observations on numerical weather prediction, it has a much broader applicability, in particular to aerosols and chemical constituents. In this talk we will give a general overview of Observing System Simulation Experiments (OSSE) activities at NASA's Global Modeling and Assimilation Office, with focus on its emerging atmospheric composition component.

Bayesics

NASA Astrophysics Data System (ADS)

Skilling, John

2005-11-01

This tutorial gives a basic overview of Bayesian methodology, from its axiomatic foundation through the conventional development of data analysis and model selection to its rôle in quantum mechanics, and ending with some comments on inference in general human affairs. The central theme is that probability calculus is the unique language within which we can develop models of our surroundings that have predictive capability. These models are patterns of belief; there is no need to claim external reality. 1. Logic and probability 2. Probability and inference 3. Probability and model selection 4. Prior probabilities 5. Probability and frequency 6. Probability and quantum mechanics 7. Probability and fundamentalism 8. Probability and deception 9. Prediction and truth

Methods for exploring uncertainty in groundwater management predictions

USGS Publications Warehouse

Guillaume, Joseph H. A.; Hunt, Randall J.; Comunian, Alessandro; Fu, Baihua; Blakers, Rachel S; Jakeman, Anthony J.; Barreteau, Olivier; Hunt, Randall J.; Rinaudo, Jean-Daniel; Ross, Andrew

2016-01-01

Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

Microphysiological models of the developing nervous system (SOT workshop session overview)

EPA Science Inventory

Recent advances using human stem cells and other cells that can be ushered through differentiation and developmental maturation offer an unprecedented opportunity to develop predictive systems for toxicological assessment. The use of human cells is an advantage because there is n...

Modeling the transition region

NASA Technical Reports Server (NTRS)

Singer, Bart A.

1993-01-01

The current status of transition-region models is reviewed in this report. To understand modeling problems, various flow features that influence the transition process are discussed first. Then an overview of the different approaches to transition-region modeling is given. This is followed by a detailed discussion of turbulence models and the specific modifications that are needed to predict flows undergoing laminar-turbulent transition. Methods for determining the usefulness of the models are presented, and an outlook for the future of transition-region modeling is suggested.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

NASA Space Radiation Risk Project: Overview and Recent Results

NASA Technical Reports Server (NTRS)

Blattnig, Steve R.; Chappell, Lori J.; George, Kerry A.; Hada, Megumi; Hu, Shaowen; Kidane, Yared H.; Kim, Myung-Hee Y.; Kovyrshina, Tatiana; Norman, Ryan B.; Nounu, Hatem N.;

Reducing the number of laboratory animals used in tissue engineering research by restricting the variety of animal models. Articular cartilage tissue engineering as a case study.

PubMed

de Vries, Rob B M; Buma, Pieter; Leenaars, Marlies; Ritskes-Hoitinga, Merel; Gordijn, Bert

2012-12-01

The use of laboratory animals in tissue engineering research is an important underexposed ethical issue. Several ethical questions may be raised about this use of animals. This article focuses on the possibilities of reducing the number of animals used. Given that there is considerable debate about the adequacy of the current animal models in tissue engineering research, we investigate whether it is possible to reduce the number of laboratory animals by selecting and using only those models that have greatest predictive value for future clinical application of the tissue engineered product. The field of articular cartilage tissue engineering is used as a case study. Based on a study of the scientific literature and interviews with leading experts in the field, an overview is provided of the animal models used and the advantages and disadvantages of each model, particularly in terms of extrapolation to the human situation. Starting from this overview, it is shown that, by skipping the small models and using only one large preclinical model, it is indeed possible to restrict the number of animal models, thereby reducing the number of laboratory animals used. Moreover, it is argued that the selection of animal models should become more evidence based and that researchers should seize more opportunities to choose or create characteristics in the animal models that increase their predictive value.

Supercomputer applications in molecular modeling.

PubMed

Gund, T M

1988-01-01

An overview of the functions performed by molecular modeling is given. Molecular modeling techniques benefiting from supercomputing are described, namely, conformation, search, deriving bioactive conformations, pharmacophoric pattern searching, receptor mapping, and electrostatic properties. The use of supercomputers for problems that are computationally intensive, such as protein structure prediction, protein dynamics and reactivity, protein conformations, and energetics of binding is also examined. The current status of supercomputing and supercomputer resources are discussed.

Integrated Optical Design Analysis (IODA): New Test Data and Modeling Features

NASA Technical Reports Server (NTRS)

Moore, Jim; Troy, Ed; Patrick, Brian

2003-01-01

A general overview of the capabilities of the IODA ("Integrated Optical Design Analysis") exchange of data and modeling results between thermal, structures, optical design, and testing engineering disciplines. This presentation focuses on new features added to the software that allow measured test data to be imported into the IODA environment for post processing or comparisons with pretest model predictions. software is presented. IODA promotes efficient

Turbulent Dispersion Modelling in a Complex Urban Environment - Data Analysis and Model Development

DTIC Science & Technology

2010-02-01

Technology Laboratory (Dstl) is used as a benchmark for comparison. Comparisons are also made with some more practically oriented computational fluid dynamics...predictions. To achieve clarity in the range of approaches available for practical models of con- taminant dispersion in urban areas, an overview of...complexity of those methods is simplified to a degree that allows straightforward practical implementation and application. Using these results as a

Systematic review and overview of health economic evaluation models in obesity prevention and therapy.

PubMed

Schwander, Bjoern; Hiligsmann, Mickaël; Nuijten, Mark; Evers, Silvia

2016-10-01

Given the increasing clinical and economic burden of obesity, it is of major importance to identify cost-effective approaches for obesity management. Areas covered: This study aims to systematically review and compile an overview of published decision models for health economic assessments (HEA) in obesity, in order to summarize and compare their key characteristics as well as to identify, inform and guide future research. Of the 4,293 abstracts identified, 87 papers met our inclusion criteria. A wide range of different methodological approaches have been identified. Of the 87 papers, 69 (79%) applied unique /distinctive modelling approaches. Expert commentary: This wide range of approaches suggests the need to develop recommendations /minimal requirements for model-based HEA of obesity. In order to reach this long-term goal, further research is required. Valuable future research steps would be to investigate the predictiveness, validity and quality of the identified modelling approaches.

On various metrics used for validation of predictive QSAR models with applications in virtual screening and focused library design.

PubMed

Roy, Kunal; Mitra, Indrani

2011-07-01

Quantitative structure-activity relationships (QSARs) have important applications in drug discovery research, environmental fate modeling, property prediction, etc. Validation has been recognized as a very important step for QSAR model development. As one of the important objectives of QSAR modeling is to predict activity/property/toxicity of new chemicals falling within the domain of applicability of the developed models and QSARs are being used for regulatory decisions, checking reliability of the models and confidence of their predictions is a very important aspect, which can be judged during the validation process. One prime application of a statistically significant QSAR model is virtual screening for molecules with improved potency based on the pharmacophoric features and the descriptors appearing in the QSAR model. Validated QSAR models may also be utilized for design of focused libraries which may be subsequently screened for the selection of hits. The present review focuses on various metrics used for validation of predictive QSAR models together with an overview of the application of QSAR models in the fields of virtual screening and focused library design for diverse series of compounds with citation of some recent examples.

Ocean modelling for aquaculture and fisheries in Irish waters

NASA Astrophysics Data System (ADS)

Dabrowski, T.; Lyons, K.; Cusack, C.; Casal, G.; Berry, A.; Nolan, G. D.

2016-01-01

The Marine Institute, Ireland, runs a suite of operational regional and coastal ocean models. Recent developments include several tailored products that focus on the key needs of the Irish aquaculture sector. In this article, an overview of the products and services derived from the models are presented. The authors give an overview of a shellfish model developed in-house and that was designed to predict the growth, the physiological interactions with the ecosystem, and the level of coliform contamination of the blue mussel. As such, this model is applicable in studies on the carrying capacity of embayments, assessment of the impacts of pollution on aquaculture grounds, and the determination of shellfish water classes. Further services include the assimilation of the model-predicted shelf water movement into a new harmful algal bloom alert system used to inform end users of potential toxic shellfish events and high biomass blooms that include fish-killing species. Models are also used to identify potential sites for offshore aquaculture, to inform studies of potential cross-contamination in farms from the dispersal of planktonic sea lice larvae and other pathogens that can infect finfish, and to provide modelled products that underpin the assessment and advisory services on the sustainable exploitation of the resources of marine fisheries. This paper demonstrates that ocean models can provide an invaluable contribution to the sustainable blue growth of aquaculture and fisheries.

Nonlinear and progressive failure aspects of transport composite fuselage damage tolerance

NASA Technical Reports Server (NTRS)

Walker, Tom; Ilcewicz, L.; Murphy, Dan; Dopker, Bernhard

1993-01-01

The purpose is to provide an end-user's perspective on the state of the art in life prediction and failure analysis by focusing on subsonic transport fuselage issues being addressed in the NASA/Boeing Advanced Technology Composite Aircraft Structure (ATCAS) contract and a related task-order contract. First, some discrepancies between the ATCAS tension-fracture test database and classical prediction methods is discussed, followed by an overview of material modeling work aimed at explaining some of these discrepancies. Finally, analysis efforts associated with a pressure-box test fixture are addressed, as an illustration of modeling complexities required to model and interpret tests.

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

NASA Technical Reports Server (NTRS)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Avalanches and plastic flow in crystal plasticity: an overview

NASA Astrophysics Data System (ADS)

Papanikolaou, Stefanos; Cui, Yinan; Ghoniem, Nasr

2018-01-01

Crystal plasticity is mediated through dislocations, which form knotted configurations in a complex energy landscape. Once they disentangle and move, they may also be impeded by permanent obstacles with finite energy barriers or frustrating long-range interactions. The outcome of such complexity is the emergence of dislocation avalanches as the basic mechanism of plastic flow in solids at the nanoscale. While the deformation behavior of bulk materials appears smooth, a predictive model should clearly be based upon the character of these dislocation avalanches and their associated strain bursts. We provide here a comprehensive overview of experimental observations, theoretical models and computational approaches that have been developed to unravel the multiple aspects of dislocation avalanche physics and the phenomena leading to strain bursts in crystal plasticity.

CDEP Consortium on Ocean Data Assimilation for Seasonal-to-Interannual Prediction (ODASI)

NASA Technical Reports Server (NTRS)

Rienecker, Michele; Zebiak, Stephen; Kinter, James; Behringer, David; Rosati, Antonio; Kaplan, Alexey

2005-01-01

The ODASI consortium is focused activity of the NOAA/OGP/Climate Diagnostics and Experimental Prediction Program with the goal of improving ocean data assimilation methods and their implementations in support of seasonal forecasts with coupled general circulation models. The consortium is undertaking coordinated assimilation experiments, with common forcing data sets and common input data streams. With different assimilation systems and different models, we aim to understand what approach works best in improving forecast skill in the equatorial Pacific. The presentation will provide an overview of the consortium goals and plans and recent results focused towards evaluating data impacts.

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

ANSYS tools in modeling tires

NASA Technical Reports Server (NTRS)

Ali, Ashraf; Lovell, Michael

1995-01-01

This presentation summarizes the capabilities in the ANSYS program that relate to the computational modeling of tires. The power and the difficulties associated with modeling nearly incompressible rubber-like materials using hyperelastic constitutive relationships are highlighted from a developer's point of view. The topics covered include a hyperelastic material constitutive model for rubber-like materials, a general overview of contact-friction capabilities, and the acoustic fluid-structure interaction problem for noise prediction. Brief theoretical development and example problems are presented for each topic.

Solar Dynamics Observatory (SDO) HGAS Induced Jitter

NASA Technical Reports Server (NTRS)

Liu, Alice; Blaurock, Carl; Liu, Kuo-Chia; Mule, Peter

2008-01-01

This paper presents the results of a comprehensive assessment of High Gain Antenna System induced jitter on the Solar Dynamics Observatory. The jitter prediction is created using a coupled model of the structural dynamics, optical response, control systems, and stepper motor actuator electromechanical dynamics. The paper gives an overview of the model components, presents the verification processes used to evaluate the models, describes validation and calibration tests and model-to-measurement comparison results, and presents the jitter analysis methodology and results.

General overview on structure prediction of twilight-zone proteins.

PubMed

Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

2015-09-04

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

Cryogenic Model Materials

NASA Technical Reports Server (NTRS)

Kimmel, W. M.; Kuhn, N. S.; Berry, R. F.; Newman, J. A.

2001-01-01

An overview and status of current activities seeking alternatives to 200 grade 18Ni Steel CVM alloy for cryogenic wind tunnel models is presented. Specific improvements in material selection have been researched including availability, strength, fracture toughness and potential for use in transonic wind tunnel testing. Potential benefits from utilizing damage tolerant life-prediction methods, recently developed fatigue crack growth codes and upgraded NDE methods are also investigated. Two candidate alloys are identified and accepted for cryogenic/transonic wind tunnel models and hardware.

Progress in sensor performance testing, modeling and range prediction using the TOD method: an overview

NASA Astrophysics Data System (ADS)

Bijl, Piet; Hogervorst, Maarten A.; Toet, Alexander

2017-05-01

The Triangle Orientation Discrimination (TOD) methodology includes i) a widely applicable, accurate end-to-end EO/IR sensor test, ii) an image-based sensor system model and iii) a Target Acquisition (TA) range model. The method has been extensively validated against TA field performance for a wide variety of well- and under-sampled imagers, systems with advanced image processing techniques such as dynamic super resolution and local adaptive contrast enhancement, and sensors showing smear or noise drift, for both static and dynamic test stimuli and as a function of target contrast. Recently, significant progress has been made in various directions. Dedicated visual and NIR test charts for lab and field testing are available and thermal test benches are on the market. Automated sensor testing using an objective synthetic human observer is within reach. Both an analytical and an image-based TOD model have recently been developed and are being implemented in the European Target Acquisition model ECOMOS and in the EOSTAR TDA. Further, the methodology is being applied for design optimization of high-end security camera systems. Finally, results from a recent perception study suggest that DRI ranges for real targets can be predicted by replacing the relevant distinctive target features by TOD test patterns of the same characteristic size and contrast, enabling a new TA modeling approach. This paper provides an overview.

Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties.

PubMed

Salahinejad, Maryam

2015-01-01

Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

Proceedings of the Workshop on High Altitude Data Assimilation and Modeling

DTIC Science & Technology

2015-06-24

Masha  Kuznetsova,  NASA  GSFC)   1330-­‐1400    Upper  Atmospheric  Data...prediction.       The  Community  Coordinated  Modeling  Center:  Overview  of  Activities   Masha  Kuznetsova  (Space...Division,  Naval  Research  Laboratory,  Washington  DC     Masha  Kuznetsov      Community  Coordinated

Applying Risk Prediction Models to Optimize Lung Cancer Screening: Current Knowledge, Challenges, and Future Directions.

PubMed

Sakoda, Lori C; Henderson, Louise M; Caverly, Tanner J; Wernli, Karen J; Katki, Hormuzd A

2017-12-01

Risk prediction models may be useful for facilitating effective and high-quality decision-making at critical steps in the lung cancer screening process. This review provides a current overview of published lung cancer risk prediction models and their applications to lung cancer screening and highlights both challenges and strategies for improving their predictive performance and use in clinical practice. Since the 2011 publication of the National Lung Screening Trial results, numerous prediction models have been proposed to estimate the probability of developing or dying from lung cancer or the probability that a pulmonary nodule is malignant. Respective models appear to exhibit high discriminatory accuracy in identifying individuals at highest risk of lung cancer or differentiating malignant from benign pulmonary nodules. However, validation and critical comparison of the performance of these models in independent populations are limited. Little is also known about the extent to which risk prediction models are being applied in clinical practice and influencing decision-making processes and outcomes related to lung cancer screening. Current evidence is insufficient to determine which lung cancer risk prediction models are most clinically useful and how to best implement their use to optimize screening effectiveness and quality. To address these knowledge gaps, future research should be directed toward validating and enhancing existing risk prediction models for lung cancer and evaluating the application of model-based risk calculators and its corresponding impact on screening processes and outcomes.

An Overview of Spray Modeling With OpenNCC and its Application to Emissions Predictions of a LDI Combustor at High Pressure

NASA Technical Reports Server (NTRS)

Raju, M. S.

2016-01-01

The open national combustion code (Open- NCC) is developed with the aim of advancing the current multi-dimensional computational tools used in the design of advanced technology combustors. In this paper we provide an overview of the spray module, LSPRAY-V, developed as a part of this effort. The spray solver is mainly designed to predict the flow, thermal, and transport properties of a rapidly evaporating multi-component liquid spray. The modeling approach is applicable over a wide-range of evaporating conditions (normal, superheat, and supercritical). The modeling approach is based on several well-established atomization, vaporization, and wall/droplet impingement models. It facilitates large-scale combustor computations through the use of massively parallel computers with the ability to perform the computations on either structured & unstructured grids. The spray module has a multi-liquid and multi-injector capability, and can be used in the calculation of both steady and unsteady computations. We conclude the paper by providing the results for a reacting spray generated by a single injector element with 600 axially swept swirler vanes. It is a configuration based on the next-generation lean-direct injection (LDI) combustor concept. The results include comparisons for both combustor exit temperature and EINOX at three different fuel/air ratios.

A data base approach for prediction of deforestation-induced mass wasting events

NASA Technical Reports Server (NTRS)

Logan, T. L.

1981-01-01

A major topic of concern in timber management is determining the impact of clear-cutting on slope stability. Deforestation treatments on steep mountain slopes have often resulted in a high frequency of major mass wasting events. The Geographic Information System (GIS) is a potentially useful tool for predicting the location of mass wasting sites. With a raster-based GIS, digitally encoded maps of slide hazard parameters can be overlayed and modeled to produce new maps depicting high probability slide areas. The present investigation has the objective to examine the raster-based information system as a tool for predicting the location of the clear-cut mountain slopes which are most likely to experience shallow soil debris avalanches. A literature overview is conducted, taking into account vegetation, roads, precipitation, soil type, slope-angle and aspect, and models predicting mass soil movements. Attention is given to a data base approach and aspects of slide prediction.

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

PubMed

Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk

2015-05-01

To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Validation metrics for turbulent plasma transport

DOE PAGES

Holland, C.

2016-06-22

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. Furthermore, the utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak, as part of a multi-year transport model validation activity.« less

Validation metrics for turbulent plasma transport

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

Holland, C.

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. Furthermore, the utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak, as part of a multi-year transport model validation activity.« less

Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi-automated metrics.

PubMed

Abriata, Luciano A; Kinch, Lisa N; Tamò, Giorgio E; Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Dal Peraro, Matteo

2018-03-01

For assessment purposes, CASP targets are split into evaluation units. We herein present the official definition of CASP12 evaluation units (EUs) and their classification into difficulty categories. Each target can be evaluated as one EU (the whole target) or/and several EUs (separate structural domains or groups of structural domains). The specific scenario for a target split is determined by the domain organization of available templates, the difference in server performance on separate domains versus combination of the domains, and visual inspection. In the end, 71 targets were split into 96 EUs. Classification of the EUs into difficulty categories was done semi-automatically with the assistance of metrics provided by the Prediction Center. These metrics account for sequence and structural similarities of the EUs to potential structural templates from the Protein Data Bank, and for the baseline performance of automated server predictions. The metrics readily separate the 96 EUs into 38 EUs that should be straightforward for template-based modeling (TBM) and 39 that are expected to be hard for homology modeling and are thus left for free modeling (FM). The remaining 19 borderline evaluation units were dubbed FM/TBM, and were inspected case by case. The article also overviews structural and evolutionary features of selected targets relevant to our accompanying article presenting the assessment of FM and FM/TBM predictions, and overviews structural features of the hardest evaluation units from the FM category. We finally suggest improvements for the EU definition and classification procedures. © 2017 Wiley Periodicals, Inc.

Prediction models for successful external cephalic version: a systematic review.

PubMed

Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

2015-12-01

To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

PubMed

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Overview: Parity Violation and Fundamental Symmetries

NASA Astrophysics Data System (ADS)

Carlini, Roger

2017-09-01

The fields of nuclear and particle physics have undertaken extensive programs of research to search for evidence of new phenomena via the precision measurement of observables that are well predicted within the standard model of electroweak interaction. It is already known that the standard model is incomplete as it does not include gravity and dark matter/energy and therefore likely the low energy approximation of a more complex theory. This talk will be an overview of the motivation, experimental methods and status of some of these efforts (past and future) related to precision in-direct searches that are complementary to the direct searches underway at the Large Hadron Collider. This abstract is for the invited talk associated with the Mini-symposium titled ``Electro-weak Physics and Fundamental Symmetries'' organized by Julie Roche.

Overview of the Meso-NH model version 5.4 and its applications

NASA Astrophysics Data System (ADS)

Lac, Christine; Chaboureau, Jean-Pierre; Masson, Valéry; Pinty, Jean-Pierre; Tulet, Pierre; Escobar, Juan; Leriche, Maud; Barthe, Christelle; Aouizerats, Benjamin; Augros, Clotilde; Aumond, Pierre; Auguste, Franck; Bechtold, Peter; Berthet, Sarah; Bielli, Soline; Bosseur, Frédéric; Caumont, Olivier; Cohard, Jean-Martial; Colin, Jeanne; Couvreux, Fleur; Cuxart, Joan; Delautier, Gaëlle; Dauhut, Thibaut; Ducrocq, Véronique; Filippi, Jean-Baptiste; Gazen, Didier; Geoffroy, Olivier; Gheusi, François; Honnert, Rachel; Lafore, Jean-Philippe; Lebeaupin Brossier, Cindy; Libois, Quentin; Lunet, Thibaut; Mari, Céline; Maric, Tomislav; Mascart, Patrick; Mogé, Maxime; Molinié, Gilles; Nuissier, Olivier; Pantillon, Florian; Peyrillé, Philippe; Pergaud, Julien; Perraud, Emilie; Pianezze, Joris; Redelsperger, Jean-Luc; Ricard, Didier; Richard, Evelyne; Riette, Sébastien; Rodier, Quentin; Schoetter, Robert; Seyfried, Léo; Stein, Joël; Suhre, Karsten; Taufour, Marie; Thouron, Odile; Turner, Sandra; Verrelle, Antoine; Vié, Benoît; Visentin, Florian; Vionnet, Vincent; Wautelet, Philippe

2018-05-01

This paper presents the Meso-NH model version 5.4. Meso-NH is an atmospheric non hydrostatic research model that is applied to a broad range of resolutions, from synoptic to turbulent scales, and is designed for studies of physics and chemistry. It is a limited-area model employing advanced numerical techniques, including monotonic advection schemes for scalar transport and fourth-order centered or odd-order WENO advection schemes for momentum. The model includes state-of-the-art physics parameterization schemes that are important to represent convective-scale phenomena and turbulent eddies, as well as flows at larger scales. In addition, Meso-NH has been expanded to provide capabilities for a range of Earth system prediction applications such as chemistry and aerosols, electricity and lightning, hydrology, wildland fires, volcanic eruptions, and cyclones with ocean coupling. Here, we present the main innovations to the dynamics and physics of the code since the pioneer paper of Lafore et al. (1998) and provide an overview of recent applications and couplings.

Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale

NASA Astrophysics Data System (ADS)

Blokker, Mirjam; Agudelo-Vera, Claudia; Moerman, Andreas; van Thienen, Peter; Pieterse-Quirijns, Ilse

2017-04-01

Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models is available at a temporal scale of 1 s and a spatial scale of a single home. The reasons for building these models were described in the papers in which the models were introduced, along with a discussion on their potential applications. However, the predicted applications are seldom re-examined. SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed. We are therefore re-examining its applications in this paper. SIMDEUM's original purpose was to calculate maximum demands in order to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application for SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of the requirements for demand models in various applications.

The string prediction models as invariants of time series in the forex market

NASA Astrophysics Data System (ADS)

Pincak, R.

2013-12-01

In this paper we apply a new approach of string theory to the real financial market. The models are constructed with an idea of prediction models based on the string invariants (PMBSI). The performance of PMBSI is compared to support vector machines (SVM) and artificial neural networks (ANN) on an artificial and a financial time series. A brief overview of the results and analysis is given. The first model is based on the correlation function as invariant and the second one is an application based on the deviations from the closed string/pattern form (PMBCS). We found the difference between these two approaches. The first model cannot predict the behavior of the forex market with good efficiency in comparison with the second one which is, in addition, able to make relevant profit per year. The presented string models could be useful for portfolio creation and financial risk management in the banking sector as well as for a nonlinear statistical approach to data optimization.

Designing synthetic RNA for delivery by nanoparticles

NASA Astrophysics Data System (ADS)

Jedrzejczyk, Dominika; Gendaszewska-Darmach, Edyta; Pawlowska, Roza; Chworos, Arkadiusz

2017-03-01

The rapid development of synthetic biology and nanobiotechnology has led to the construction of various synthetic RNA nanoparticles of different functionalities and potential applications. As they occur naturally, nucleic acids are an attractive construction material for biocompatible nanoscaffold and nanomachine design. In this review, we provide an overview of the types of RNA and nucleic acid’s nanoparticle design, with the focus on relevant nanostructures utilized for gene-expression regulation in cellular models. Structural analysis and modeling is addressed along with the tools available for RNA structural prediction. The functionalization of RNA-based nanoparticles leading to prospective applications of such constructs in potential therapies is shown. The route from the nanoparticle design and modeling through synthesis and functionalization to cellular application is also described. For a better understanding of the fate of targeted RNA after delivery, an overview of RNA processing inside the cell is also provided.

Goal-oriented Site Characterization in Hydrogeological Applications: An Overview

NASA Astrophysics Data System (ADS)

Nowak, W.; de Barros, F.; Rubin, Y.

2011-12-01

In this study, we address the importance of goal-oriented site characterization. Given the multiple sources of uncertainty in hydrogeological applications, information needs of modeling, prediction and decision support should be satisfied with efficient and rational field campaigns. In this work, we provide an overview of an optimal sampling design framework based on Bayesian decision theory, statistical parameter inference and Bayesian model averaging. It optimizes the field sampling campaign around decisions on environmental performance metrics (e.g., risk, arrival times, etc.) while accounting for parametric and model uncertainty in the geostatistical characterization, in forcing terms, and measurement error. The appealing aspects of the framework lie on its goal-oriented character and that it is directly linked to the confidence in a specified decision. We illustrate how these concepts could be applied in a human health risk problem where uncertainty from both hydrogeological and health parameters are accounted.

ANALYTICAL MODELING OF ELECTRON BACK-BOMBARDMENT INDUCED CURRENT INCREASE IN UN-GATED THERMIONIC CATHODE RF GUNS

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

Edelen, J. P.; Sun, Y.; Harris, J. R.

In this paper we derive analytical expressions for the output current of an un-gated thermionic cathode RF gun in the presence of back-bombardment heating. We provide a brief overview of back-bombardment theory and discuss comparisons between the analytical back-bombardment predictions and simulation models. We then derive an expression for the output current as a function of the RF repetition rate and discuss relationships between back-bombardment, fieldenhancement, and output current. We discuss in detail the relevant approximations and then provide predictions about how the output current should vary as a function of repetition rate for some given system configurations.

Integrated Modeling Activities for the James Webb Space Telescope (JWST): Structural-Thermal-Optical Analysis

NASA Technical Reports Server (NTRS)

Johnston, John D.; Parrish, Keith; Howard, Joseph M.; Mosier, Gary E.; McGinnis, Mark; Bluth, Marcel; Kim, Kevin; Ha, Hong Q.

2004-01-01

This is a continuation of a series of papers on modeling activities for JWST. The structural-thermal- optical, often referred to as "STOP", analysis process is used to predict the effect of thermal distortion on optical performance. The benchmark STOP analysis for JWST assesses the effect of an observatory slew on wavefront error. The paper begins an overview of multi-disciplinary engineering analysis, or integrated modeling, which is a critical element of the JWST mission. The STOP analysis process is then described. This process consists of the following steps: thermal analysis, structural analysis, and optical analysis. Temperatures predicted using geometric and thermal math models are mapped to the structural finite element model in order to predict thermally-induced deformations. Motions and deformations at optical surfaces are input to optical models and optical performance is predicted using either an optical ray trace or WFE estimation techniques based on prior ray traces or first order optics. Following the discussion of the analysis process, results based on models representing the design at the time of the System Requirements Review. In addition to baseline performance predictions, sensitivity studies are performed to assess modeling uncertainties. Of particular interest is the sensitivity of optical performance to uncertainties in temperature predictions and variations in metal properties. The paper concludes with a discussion of modeling uncertainty as it pertains to STOP analysis.

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

NASA Technical Reports Server (NTRS)

West, Jeff; Strutzenberg, Louise L.; Putnam, Gabriel C.; Liever, Peter A.; Williams, Brandon R.

2012-01-01

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

Medicinal Chemistry and Molecular Modeling: An Integration to Teach Drug Structure-Activity Relationship and the Molecular Basis of Drug Action

ERIC Educational Resources Information Center

Carvalho, Ivone; Borges, Aurea D. L.; Bernardes, Lilian S. C.

2005-01-01

The use of computational chemistry and the protein data bank (PDB) to understand and predict the chemical and molecular basis involved in the drug-receptor interactions is discussed. A geometrical and chemical overview of the great structural similarity in the substrate and inhibitor is provided.

Data Assimilation - Advances and Applications

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

Williams, Brian J.

2014-07-30

This presentation provides an overview of data assimilation (model calibration) for complex computer experiments. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Utilization of surrogate models and empirical adjustment for model form error in code calibration form the basis for the statistical methodology considered. The role of probabilistic code calibration in supporting code validation is discussed. Incorporation of model form uncertainty in rigorous uncertainty quantification (UQ) analyses is also addressed. Design criteria used within a batchmore » sequential design algorithm are introduced for efficiently achieving predictive maturity and improved code calibration. Predictive maturity refers to obtaining stable predictive inference with calibrated computer codes. These approaches allow for augmentation of initial experiment designs for collecting new physical data. A standard framework for data assimilation is presented and techniques for updating the posterior distribution of the state variables based on particle filtering and the ensemble Kalman filter are introduced.« less

Avian models for toxicity testing

USGS Publications Warehouse

Hill, E.F.; Hoffman, D.J.

1984-01-01

The use of birds as test models in experimental and environmental toxicology as related to health effects is reviewed, and an overview of descriptive tests routinely used in wildlife toxicology is provided. Toxicologic research on birds may be applicable to human health both directly by their use as models for mechanistic and descriptive studies and indirectly as monitors of environmental quality. Topics include the use of birds as models for study of teratogenesis and embryotoxicity, neurotoxicity, behavior, trends of environmental pollution, and for use in predictive wildlife toxicology. Uses of domestic and wild-captured birds are discussed.

Validation of Metrics as Error Predictors

NASA Astrophysics Data System (ADS)

Mendling, Jan

In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

Modeling and Simulation of Nanoindentation

NASA Astrophysics Data System (ADS)

Huang, Sixie; Zhou, Caizhi

2017-11-01

Nanoindentation is a hardness test method applied to small volumes of material which can provide some unique effects and spark many related research activities. To fully understand the phenomena observed during nanoindentation tests, modeling and simulation methods have been developed to predict the mechanical response of materials during nanoindentation. However, challenges remain with those computational approaches, because of their length scale, predictive capability, and accuracy. This article reviews recent progress and challenges for modeling and simulation of nanoindentation, including an overview of molecular dynamics, the quasicontinuum method, discrete dislocation dynamics, and the crystal plasticity finite element method, and discusses how to integrate multiscale modeling approaches seamlessly with experimental studies to understand the length-scale effects and microstructure evolution during nanoindentation tests, creating a unique opportunity to establish new calibration procedures for the nanoindentation technique.

Whole-genome regression and prediction methods applied to plant and animal breeding.

PubMed

de Los Campos, Gustavo; Hickey, John M; Pong-Wong, Ricardo; Daetwyler, Hans D; Calus, Mario P L

2013-02-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade.

Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding

PubMed Central

de los Campos, Gustavo; Hickey, John M.; Pong-Wong, Ricardo; Daetwyler, Hans D.; Calus, Mario P. L.

2013-01-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade. PMID:22745228

In Silico Approaches for Predicting Adme Properties

NASA Astrophysics Data System (ADS)

Madden, Judith C.

A drug requires a suitable pharmacokinetic profile to be efficacious in vivo in humans. The relevant pharmacokinetic properties include the absorption, distribution, metabolism, and excretion (ADME) profile of the drug. This chapter provides an overview of the definition and meaning of key ADME properties, recent models developed to predict these properties, and a guide as to how to select the most appropriate model(s) for a given query. Many tools using the state-of-the-art in silico methodology are now available to users, and it is anticipated that the continual evolution of these tools will provide greater ability to predict ADME properties in the future. However, caution must be exercised in applying these tools as data are generally available only for "successful" drugs, i.e., those that reach the marketplace, and little supplementary information, such as that for drugs that have a poor pharmacokinetic profile, is available. The possibilities of using these methods and possible integration into toxicity prediction are explored.

Structural modeling of G-protein coupled receptors: An overview on automatic web-servers.

PubMed

Busato, Mirko; Giorgetti, Alejandro

2016-08-01

Despite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

Perspectives for geographically oriented management of fusarium mycotoxins in the cereal supply chain.

PubMed

van der Fels-Klerx, H J; Booij, C J H

2010-06-01

This article provides an overview of available systems for management of Fusarium mycotoxins in the cereal grain supply chain, with an emphasis on the use of predictive mathematical modeling. From the state of the art, it proposes future developments in modeling and management and their challenges. Mycotoxin contamination in cereal grain-based feed and food products is currently managed and controlled by good agricultural practices, good manufacturing practices, hazard analysis critical control points, and by checking and more recently by notification systems and predictive mathematical models. Most of the predictive models for Fusarium mycotoxins in cereal grains focus on deoxynivalenol in wheat and aim to help growers make decisions about the application of fungicides during cultivation. Future developments in managing Fusarium mycotoxins should include the linkage between predictive mathematical models and geographical information systems, resulting into region-specific predictions for mycotoxin occurrence. The envisioned geographically oriented decision support system may incorporate various underlying models for specific users' demands and regions and various related databases to feed the particular models with (geographically oriented) input data. Depending on the user requirements, the system selects the best fitting model and available input information. Future research areas include organizing data management in the cereal grain supply chain, developing predictive models for other stakeholders (taking into account the period up to harvest), other Fusarium mycotoxins, and cereal grain types, and understanding the underlying effects of the regional component in the models.

Stratospheric ozone - Fragile shield. [SST exhausts and Freons impact

NASA Technical Reports Server (NTRS)

Hoffert, M. I.; Stewart, R. W.

1975-01-01

Atmospheric models that have been used in major studies on the possible impact of SST exhausts and Freons on stratospheric ozone are discussed and compared. An overview is given of ozone-reduction estimates that they produce, together with an assessment of possible effects of atmospheric testing of thermonuclear bombs in an attempt to find direct observational evidence for ozone depletion resulting from human activities. It is concluded that clear validation of atmospheric-model predictions is lacking.

Modeling the Earth system in the Mission to Planet Earth era

NASA Technical Reports Server (NTRS)

Unninayar, Sushel; Bergman, Kenneth H.

1993-01-01

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

Validation metrics for turbulent plasma transport

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

Holland, C., E-mail: chholland@ucsd.edu

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.« less

One-fiftieth scale model studies of 40-by 80-foot and 80-by 120-foot wind tunnel complex at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Schmidt, Gene I.; Rossow, Vernon J.; Vanaken, Johannes M.; Parrish, Cynthia L.

1987-01-01

The features of a 1/50-scale model of the National Full-Scale Aerodynamics Complex are first described. An overview is then given of some results from the various tests conducted with the model to aid in the design of the full-scale facility. It was found that the model tunnel simulated accurately many of the operational characteristics of the full-scale circuits. Some characteristics predicted by the model were, however, noted to differ from previous full-scale results by about 10%.

Modeling High-Resolution Coastal Ocean Dynamics with COAMPS: System Overview, Applications and Future Directions

NASA Astrophysics Data System (ADS)

Allard, R. A.; Campbell, T. J.; Edwards, K. L.; Smith, T.; Martin, P.; Hebert, D. A.; Rogers, W.; Dykes, J. D.; Jacobs, G. A.; Spence, P. L.; Bartels, B.

2014-12-01

The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®) is an atmosphere-ocean-wave modeling system developed by the Naval Research Laboratory which can be configured to cycle regional forecasts/analysis models in single-model (atmosphere, ocean, and wave) or coupled-model (atmosphere-ocean, ocean-wave, and atmosphere-ocean-wave) modes. The model coupling is performed using the Earth System Modeling Framework (ESMF). The ocean component is the Navy Coastal Ocean Model (NCOM), and the wave components include Simulating WAves Nearshore (SWAN) and WaveWatch-III. NCOM has been modified to include wetting and drying, the effects of Stokes drift current, wave radiation stresses due to horizontal gradients of the momentum flux of surface waves, enhancement of bottom drag in shallow water, and enhanced vertical mixing due to Langmuir turbulence. An overview of the modeling system including ocean data assimilation and specification of boundary conditions will be presented. Results from a high-resolution (10-250m) modeling study from the Surfzone Coastal Oil Pathways Experiment (SCOPE) near Ft. Walton Beach, Florida in December 2013 will be presented. ®COAMPS is a registered trademark of the Naval Research Laboratory

Evaluating Antarctic sea ice predictability at seasonal to interannual timescales in global climate models

NASA Astrophysics Data System (ADS)

Marchi, Sylvain; Fichefet, Thierry; Goosse, Hugues; Zunz, Violette; Tietsche, Steffen; Day, Jonny; Hawkins, Ed

2016-04-01

Unlike the rapid sea ice losses reported in the Arctic, satellite observations show an overall increase in Antarctic sea ice extent over recent decades. Although many processes have already been suggested to explain this positive trend, it remains the subject of current investigations. Understanding the evolution of the Antarctic sea ice turns out to be more complicated than for the Arctic for two reasons: the lack of observations and the well-known biases of climate models in the Southern Ocean. Irrespective of those issues, another one is to determine whether the positive trend in sea ice extent would have been predictable if adequate observations and models were available some decades ago. This study of Antarctic sea ice predictability is carried out using 6 global climate models (HadGEM1.2, MPI-ESM-LR, GFDL CM3, EC-Earth V2, MIROC 5.2 and ECHAM 6-FESOM) which are all part of the APPOSITE project. These models are used to perform hindcast simulations in a perfect model approach. The predictive skill is estimated thanks to the PPP (Potential Prognostic Predictability) and the ACC (Anomaly Correlation Coefficient). The former is a measure of the uncertainty of the ensemble while the latter assesses the accuracy of the prediction. These two indicators are applied to different variables related to sea ice, in particular the total sea ice extent and the ice edge location. This first model intercomparison study about sea ice predictability in the Southern Ocean aims at giving a general overview of Antarctic sea ice predictability in current global climate models.

Overview of aerothermodynamic loads definition study

NASA Technical Reports Server (NTRS)

Gaugler, Raymond E.

1991-01-01

The objective of the Aerothermodynamic Loads Definition Study is to develop methods of accurately predicting the operating environment in advanced Earth-to-Orbit (ETO) propulsion systems, such as the Space Shuttle Main Engine (SSME) powerhead. Development of time averaged and time dependent three dimensional viscous computer codes as well as experimental verification and engine diagnostic testing are considered to be essential in achieving that objective. Time-averaged, nonsteady, and transient operating loads must all be well defined in order to accurately predict powerhead life. Described here is work in unsteady heat flow analysis, improved modeling of preburner flow, turbulence modeling for turbomachinery, computation of three dimensional flow with heat transfer, and unsteady viscous multi-blade row turbine analysis.

NOAA SWPC / NASA CCMC Space Weather Modeling Assessment Project: Toward the Validation of Advancements in Heliospheric Space Weather Prediction Within WSA-Enlil

NASA Astrophysics Data System (ADS)

Adamson, E. T.; Pizzo, V. J.; Biesecker, D. A.; Mays, M. L.; MacNeice, P. J.; Taktakishvili, A.; Viereck, R. A.

2017-12-01

In 2011, NOAA's Space Weather Prediction Center (SWPC) transitioned the world's first operational space weather model into use at the National Weather Service's Weather and Climate Operational Supercomputing System (WCOSS). This operational forecasting tool is comprised of the Wang-Sheeley-Arge (WSA) solar wind model coupled with the Enlil heliospheric MHD model. Relying on daily-updated photospheric magnetograms produced by the National Solar Observatory's Global Oscillation Network Group (GONG), this tool provides critical predictive knowledge of heliospheric dynamics such as high speed streams and coronal mass ejections. With the goal of advancing this predictive model and quantifying progress, SWPC and NASA's Community Coordinated Modeling Center (CCMC) have initiated a collaborative effort to assess improvements in space weather forecasts at Earth by moving from a single daily-updated magnetogram to a sequence of time-dependent magnetograms to drive the ambient inputs for the WSA-Enlil model as well as incorporating the newly developed Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model. We will provide a detailed overview of the scope of this effort and discuss preliminary results from the first phase focusing on the impact of time-dependent magnetogram inputs to the WSA-Enlil model.

StreamCat and LakeCat: An overview of algorithms, data, and models developed at the US EPA Western Ecology Division to facilitate and advance watershed prediction in the conterminous US.

EPA Science Inventory

Geospatial data and techniques have long been critical to advancing the analysis and management of freshwater ecosystems. However, these data and techniques have often been limited to specific sample sites or regional analyses because of the difficulty associated with generating ...

The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; De La Beaujardiere, J.-F.; Fan, Yuhong; Leka, K. D.; Mcclymont, A. N.; Metcalf, Thomas R.; Mickey, Donald L.; Wuelser, Jean-Pierre; Lites, Bruce W.

1993-01-01

Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.

Highway traffic noise prediction based on GIS

NASA Astrophysics Data System (ADS)

Zhao, Jianghua; Qin, Qiming

2014-05-01

Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

Status of the \\varvec{Λ (1405)}

NASA Astrophysics Data System (ADS)

Mai, Maxim

2018-07-01

I give an overview of the current status of the lowest s-wave baryon resonance in the strangeness (S=-1) channel, the Λ (1405). Recent results from Lattice QCD calculations and new high-precision data from photoproduction experiments are highlighted in this talk. On the theoretical side various directions have been explored over the last two decades on the basis of coupled-channel chiral unitary models. New photoproduction data can be used to reduce statistical uncertainty of the predictions of such models. As for the systematic uncertainties, a recent comparative analysis of modern approaches exhibits many similarities but also large ambiguities in some of the predicted properties of the antikaon-nucleon scattering amplitudes. Some possible ways to reduce such a model dependence are discussed at the end of this manuscript.

Major challenges for correlational ecological niche model projections to future climate conditions.

PubMed

Peterson, A Townsend; Cobos, Marlon E; Jiménez-García, Daniel

2018-06-20

Species-level forecasts of distributional potential and likely distributional shifts, in the face of changing climates, have become popular in the literature in the past 20 years. Many refinements have been made to the methodology over the years, and the result has been an approach that considers multiple sources of variation in geographic predictions, and how that variation translates into both specific predictions and uncertainty in those predictions. Although numerous previous reviews and overviews of this field have pointed out a series of assumptions and caveats associated with the methodology, three aspects of the methodology have important impacts but have not been treated previously in detail. Here, we assess those three aspects: (1) effects of niche truncation on model transfers to future climate conditions, (2) effects of model selection procedures on future-climate transfers of ecological niche models, and (3) relative contributions of several factors (replicate samples of point data, general circulation models, representative concentration pathways, and alternative model parameterizations) to overall variance in model outcomes. Overall, the view is one of caution: although resulting predictions are fascinating and attractive, this paradigm has pitfalls that may bias and limit confidence in niche model outputs as regards the implications of climate change for species' geographic distributions. © 2018 New York Academy of Sciences.

An update on the potential role of intestinal first-pass metabolism for the prediction of drug-drug interactions: the role of PBPK modeling.

PubMed

Alqahtani, Saeed; Bukhari, Ishfaq; Albassam, Ahmed; Alenazi, Maha

2018-05-28

The intestinal absorption process is a combination of several events that are governed by various factors. Several transport mechanisms are involved in drug absorption through enterocytes via active and/or passive processes. The transported molecules then undergo intestinal metabolism, which together with intestinal transport may affect the systemic availability of drugs. Many studies have provided clear evidence on the significant role of intestinal first-pass metabolism on drug bioavailability and degree of drug-drug interactions (DDIs). Areas covered: This review provides an update on the role of intestinal first-pass metabolism in the oral bioavailability of drugs and prediction of drug-drug interactions. It also provides a comprehensive overview and summary of the latest update in the role of PBPK modeling in prediction of intestinal metabolism and DDIs in humans. Expert opinion: The contribution of intestinal first-pass metabolism in the oral bioavailability of drugs and prediction of DDIs has become more evident over the last few years. Several in vitro, in situ, and in vivo models have been developed to evaluate the role of first-pass metabolism and to predict DDIs. Currently, physiologically based pharmacokinetic modeling is considered the most valuable tool for the prediction of intestinal first-pass metabolism and DDIs.

Current target acquisition methodology in force on force simulations

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Miller, Brian; Mazz, John P.

2017-05-01

The U.S. Army RDECOM CERDEC NVESD MSD's target acquisition models have been used for many years by the military community in force on force simulations for training, testing, and analysis. There have been significant improvements to these models over the past few years. The significant improvements are the transition of ACQUIRE TTP-TAS (ACQUIRE Targeting Task Performance Target Angular Size) methodology for all imaging sensors and the development of new discrimination criteria for urban environments and humans. This paper is intended to provide an overview of the current target acquisition modeling approach and provide data for the new discrimination tasks. This paper will discuss advances and changes to the models and methodologies used to: (1) design and compare sensors' performance, (2) predict expected target acquisition performance in the field, (3) predict target acquisition performance for combat simulations, and (4) how to conduct model data validation for combat simulations.

Circadian rhythms of performance: new trends

NASA Technical Reports Server (NTRS)

Carrier, J.; Monk, T. H.

2000-01-01

This brief review is concerned with how human performance efficiency changes as a function of time of day. It presents an overview of some of the research paradigms and conceptual models that have been used to investigate circadian performance rhythms. The influence of homeostatic and circadian processes on performance regulation is discussed. The review also briefly presents recent mathematical models of alertness that have been used to predict cognitive performance. Related topics such as interindividual differences and the postlunch dip are presented.

Design and application of implicit solvent models in biomolecular simulations.

PubMed

Kleinjung, Jens; Fraternali, Franca

2014-04-01

We review implicit solvent models and their parametrisation by introducing the concepts and recent devlopments of the most popular models with a focus on parametrisation via force matching. An overview of recent applications of the solvation energy term in protein dynamics, modelling, design and prediction is given to illustrate the usability and versatility of implicit solvation in reproducing the physical behaviour of biomolecular systems. Limitations of implicit modes are discussed through the example of more challenging systems like nucleic acids and membranes. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Overview of LANL's New Hurricane Lightning Project (Invited)

NASA Astrophysics Data System (ADS)

Jeffery, C. A.; Shao, X.; Reisner, J.; Kao, C. J.; Brockwell, M.; Chylek, P.; Fierro, A.; Galassi, M.; Godinez, H. C.; Guimond, S.; Hamlin, T.; Henderson, B. G.; Ho, C.; Holden, D.; Light, T. E.; O'Connor, N.; Suszcynsky, D. M.

2009-12-01

For the last two years, Los Alamos National Laboratory has sponsored an internal hurricane lightning project with four main goals: (1) To develop and deploy a new dual VLF/VHF lightning mapping array in the Mississippi River Delta south of New Orleans. (2) To develop a new hurricane forecast capability with fully prognostic cloud electrification and lightning discharge physics, based on a model framework developed at Oklahoma University. (3) To develop a new data assimilation approach for ingesting LANL lightning data into our forecast model that exploits the phenomenological relationship between lightning occurrence and intense convection. (4) To demonstrate that the assimilation of lightning data from the new LANL Gulf array into the hurricane forecast model improves the prediction of rapid intensification (RI), when RI is driven by eyewall adjustment (axisymmetrization) triggered by intense convective events (hot towers). In this talk, I present an overview of LANL's new hurricane lighting project, and the progress we have made to-date in achieving the project's four main goals.

Allostery: An Overview of Its History, Concepts, Methods, and Applications.

PubMed

Liu, Jin; Nussinov, Ruth

2016-06-01

The concept of allostery has evolved in the past century. In this Editorial, we briefly overview the history of allostery, from the pre-allostery nomenclature era starting with the Bohr effect (1904) to the birth of allostery by Monod and Jacob (1961). We describe the evolution of the allostery concept, from a conformational change in a two-state model (1965, 1966) to dynamic allostery in the ensemble model (1999); from multi-subunit (1965) proteins to all proteins (2004). We highlight the current available methods to study allostery and their applications in studies of conformational mechanisms, disease, and allosteric drug discovery. We outline the challenges and future directions that we foresee. Altogether, this Editorial narrates the history of this fundamental concept in the life sciences, its significance, methodologies to detect and predict it, and its application in a broad range of living systems.

A Simulation Model of Carbon Cycling and Methane Emissions in Amazon Wetlands

NASA Technical Reports Server (NTRS)

Potter, Christopher; Melack, John; Hess, Laura; Forsberg, Bruce; Novo, Evlyn Moraes; Klooster, Steven

2004-01-01

An integrative carbon study is investigating the hypothesis that measured fluxes of methane from wetlands in the Amazon region can be predicted accurately using a combination of process modeling of ecosystem carbon cycles and remote sensing of regional floodplain dynamics. A new simulation model has been build using the NASA- CASA concept for predicting methane production and emission fluxes in Amazon river and floodplain ecosystems. Numerous innovations area being made to model Amazon wetland ecosystems, including: (1) prediction of wetland net primary production (NPP) as the source for plant litter decomposition and accumulation of sediment organic matter in two major vegetation classes - flooded forests (varzea or igapo) and floating macrophytes, (2) representation of controls on carbon processing and methane evasion at the diffusive boundary layer, through the lake water column, and in wetland sediments as a function of changes in floodplain water level, (3) inclusion of surface emissions controls on wetland methane fluxes, including variations in daily surface temperature and of hydrostatic pressure linked to water level fluctuations. A model design overview and early simulation results are presented.

Comprehensive summary--Predict-IV: A systems toxicology approach to improve pharmaceutical drug safety testing.

PubMed

Mueller, Stefan O; Dekant, Wolfgang; Jennings, Paul; Testai, Emanuela; Bois, Frederic

2015-12-25

This special issue of Toxicology in Vitro is dedicated to disseminating the results of the EU-funded collaborative project "Profiling the toxicity of new drugs: a non animal-based approach integrating toxicodynamics and biokinetics" (Predict-IV; Grant 202222). The project's overall aim was to develop strategies to improve the assessment of drug safety in the early stage of development and late discovery phase, by an intelligent combination of non animal-based test systems, cell biology, mechanistic toxicology and in silico modeling, in a rapid and cost effective manner. This overview introduces the scope and overall achievements of Predict-IV. Copyright © 2014 Elsevier Ltd. All rights reserved.

Food allergy animal models: an overview.

PubMed

Helm, Ricki M

2002-05-01

Specific food allergy is characterized by sensitization to innocuous food proteins with production of allergen-specific IgE that binds to receptors on basophils and mast cells. Upon recurrent exposure to the same allergen, an allergic response is induced by mediator release following cross-linking of cell-bound allergen-specific IgE. The determination of what makes an innocuous food protein an allergen in predisposed individuals is unknown; however, mechanistic and protein allergen predictive models are being actively investigated in a number of animal models. Currently, there is no animal model that will actively profile known food allergens, predict the allergic potential of novel food proteins, or demonstrate clinically the human food allergic sensitization/allergic response. Animal models under investigation include mice, rats, the guinea pig, atopic dog, and neonatal swine. These models are being assessed for production of IgE, clinical responses to re-exposure, and a ranking of food allergens (based on potency) including a nonfood allergen protein source. A selection of animal models actively being investigated that will contribute to our understanding of what makes a protein an allergen and future predictive models for assessing the allergenicity of novel proteins is presented in this review.

Symposium overview the Shell Conference on computer-aided molecular modelling

NASA Astrophysics Data System (ADS)

Hays, G. R.; de Bruijn, D. P.

1988-10-01

The `Shell Conference on ...' series began in 1985 and meetings are held approximately twice a year. The idea behind the conferences is to bring together invited scientists from both universities and industry, and representatives from different Shell Research laboratories, to create a forum to discuss the future directions of the chosen research area. These meetings have embraced a wide range of topics of interest to Shell Research as a whole. This particular conference, organised by the Analytical Department of the Koninklijke/ShellLaboratorium, Amsterdam (KSLA), was held on 4-6 October, 1987 at Hoenderloo in the Netherlands. The aim was to review the state-of-the-art and to discuss the future of molecular modelling and design. The programme itself consisted of a series of presentations on prescribed topics, panel discussions, and software and hardware demonstrations. Many of the presentations given consisted of overviews, experiences, advice and predictions for the future. The panel sessions, which involved the speakers within that session and a discussion leader who summarised some of the points made in an introduction, encouraged even further discussion and speculation. This overview attempts to catch the flavour of the meeting and convey some personal views that were expressed and conclusions drawn.

Surface protection overview

NASA Technical Reports Server (NTRS)

Levine, S. R.

1982-01-01

A first-cut integrated environmental attack life prediction methodology for hot section components is addressed. The HOST program is concerned with oxidation and hot corrosion attack of metallic coatings as well as their degradation by interdiffusion with the substrate. The effects of the environment and coatings on creep/fatigue behavior are being addressed through a joint effort with the Fatigue sub-project. An initial effort will attempt to scope the problem of thermal barrier coating life prediction. Verification of models will be carried out through benchmark rig tests including a 4 atm. replaceable blade turbine and a 50 atm. pressurized burner rig.

Global Ocean Prediction with the HYbrid Coordinate Ocean Model, HYCOM

NASA Astrophysics Data System (ADS)

Chassignet, E.

A broad partnership of institutions is collaborating in developing and demonstrating the performance and application of eddy-resolving, real-time global and Atlantic ocean prediction systems using the the HYbrid Coordinate Ocean Model (HYCOM). These systems will be transitioned for operational use by both the U.S. Navy at the Naval Oceanographic Office (NAVOCEANO), Stennis Space Center, MS, and the Fleet Numerical Meteorology and Oceanography Centre (FNMOC), Monterey, CA, and by NOAA at the National Centers for Environmental Prediction (NCEP), Washington, D.C. These systems will run efficiently on a variety of massively parallel computers and will include sophisticated data assimilation techniques for assimilation of satellite altimeter sea surface height and sea surface temperature as well as in situ temperature, salinity, and float displacement. The Partnership addresses the Global Ocean Data Assimilation Experiment (GODAE) goals of three-dimensional (3D) depiction of the ocean state at fine resolution in real-time and provision of boundary conditions for coastal and regional models. An overview of the effort will be presented.

Theories of Giant Planet Formation

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1998-01-01

An overview of current theories of planetary formation, with emphasis on giant planets, is presented. The most detailed models are based upon observations of our own Solar System and of young stars and their environments. While these models predict that rocky planets should form around most single stars, 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 as do terrestrial planets, but they become massive enough that they are able to accumulate substantial amounts of gas before the protoplanetary disk dissipates. Most models for extrasolar giant planets suggest that they formed as did Jupiter and Saturn (in nearly circular orbits, far enough from the star that ice could), and subsequently migrated to their current positions, although some models suggest in situ formation.

Predicting Electrostatic Forces in RNA Folding

PubMed Central

Tan, Zhi-Jie; Chen, Shi-Jie

2016-01-01

Metal ion-mediated electrostatic interactions are critical to RNA folding. Although considerable progress has been made in mechanistic studies, the problem of accurate predictions for the ion effects in RNA folding remains unsolved, mainly due to the complexity of several potentially important issues such as ion correlation and dehydration effects. In this chapter, after giving a brief overview of the experimental findings and theoretical approaches, we focus on a recently developed new model, the tightly bound ion (TBI) model, for ion electrostatics in RNA folding. The model is unique because it can treat ion correlation and fluctuation effects for realistic RNA 3D structures. For monovalent ion (such as Na+) solutions, where ion correlation is weak, TBI and the Poisson–Boltzmann (PB) theory give the same results and the results agree with the experimental data. For multivalent ion (such as Mg2+) solutions, where ion correlation can be strong, however, TBI gives much improved predictions than the PB. Moreover, the model suggests an ion correlation- induced mechanism for the unusual efficiency of Mg2+ ions in the stabilization of RNA tertiary folds. In this chapter, after introducing the theoretical framework of the TBI model, we will describe how to apply the model to predict ion-binding properties and ion-dependent folding stabilities. PMID:20946803

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

NASA Astrophysics Data System (ADS)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

1986-87 atomic mass predictions

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

Haustein, P.E.

A project to perform a comprehensive update of the atomic mass predictions has recently been concluded and will be published shortly in Atomic Data and Nuclear Data Tables. The project evolved from an ongoing comparison between available mass predictions and reports of newly measured masses of isotopes throughout the mass surface. These comparisons have highlighted a variety of features in current mass models which are responsible for predictions that diverge from masses determined experimentally. The need for a comprehensive update of the atomic mass predictions was therefore apparent and the project was organized and began at the last mass conferencemore » (AMCO-VII). Project participants included: Pape and Anthony; Dussel, Caurier and Zuker; Moeller and Nix; Moeller, Myers, Swiatecki and Treiner; Comay, Kelson, and Zidon; Satpathy and Nayak; Tachibana, Uno, Yamada and Yamada; Spanier and Johansson; Jaenecke and Masson; and Wapstra, Audi and Hoekstra. An overview of the new atomic mass predictions may be obtained by written request.« less

The 1986-87 atomic mass predictions

NASA Astrophysics Data System (ADS)

Haustein, P. E.

1987-12-01

A project to perform a comprehensive update of the atomic mass predictions has recently been concluded and will be published shortly in Atomic Data and Nuclear Data Tables. The project evolved from an ongoing comparison between available mass predictions and reports of newly measured masses of isotopes throughout the mass surface. These comparisons have highlighted a variety of features in current mass models which are responsible for predictions that diverge from masses determined experimentally. The need for a comprehensive update of the atomic mass predictions was therefore apparent and the project was organized and began at the last mass conference (AMCO-VII). Project participants included: Pape and Anthony; Dussel, Caurier and Zuker; Möller and Nix; Möller, Myers, Swiatecki and Treiner; Comay, Kelson, and Zidon; Satpathy and Nayak; Tachibana, Uno, Yamada and Yamada; Spanier and Johansson; Jänecke and Masson; and Wapstra, Audi and Hoekstra. An overview of the new atomic mass predictions may be obtained by written request.

Job stress models for predicting burnout syndrome: a review.

PubMed

Chirico, Francesco

2016-01-01

In Europe, the Council Directive 89/391 for improvement of workers' safety and health has emphasized the importance of addressing all occupational risk factors, and hence also psychosocial and organizational risk factors. Nevertheless, the construct of "work-related stress" elaborated from EU-OSHA is not totally corresponding with the "psychosocial" risk, that is a broader category of risk, comprising various and different psychosocial risk factors. The term "burnout", without any binding definition, tries to integrate symptoms as well as cause of the burnout process. In Europe, the most important methods developed for the work related stress risk assessment are based on the Cox's transactional model of job stress. Nevertheless, there are more specific models for predicting burnout syndrome. This literature review provides an overview of job burnout, highlighting the most important models of job burnout, such as the Job Strain, the Effort/Reward Imbalance and the Job Demands-Resources models. The difference between these models and the Cox's model of job stress is explored.

A Practical Philosophy of Complex Climate Modelling

NASA Technical Reports Server (NTRS)

Schmidt, Gavin A.; Sherwood, Steven

2014-01-01

We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP).We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naive predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Application of indoor noise prediction in the real world

NASA Astrophysics Data System (ADS)

Lewis, David N.

2002-11-01

Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

Understanding jet noise.

PubMed

Karabasov, S A

2010-08-13

Jets are one of the most fascinating topics in fluid mechanics. For aeronautics, turbulent jet-noise modelling is particularly challenging, not only because of the poor understanding of high Reynolds number turbulence, but also because of the extremely low acoustic efficiency of high-speed jets. Turbulent jet-noise models starting from the classical Lighthill acoustic analogy to state-of-the art models were considered. No attempt was made to present any complete overview of jet-noise theories. Instead, the aim was to emphasize the importance of sound generation and mean-flow propagation effects, as well as their interference, for the understanding and prediction of jet noise.

Embedded Model Error Representation and Propagation in Climate Models

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Thornton, P. E.

2017-12-01

Over the last decade, parametric uncertainty quantification (UQ) methods have reached a level of maturity, while the same can not be said about representation and quantification of structural or model errors. Lack of characterization of model errors, induced by physical assumptions, phenomenological parameterizations or constitutive laws, is a major handicap in predictive science. In particular, e.g. in climate models, significant computational resources are dedicated to model calibration without gaining improvement in predictive skill. Neglecting model errors during calibration/tuning will lead to overconfident and biased model parameters. At the same time, the most advanced methods accounting for model error merely correct output biases, augmenting model outputs with statistical error terms that can potentially violate physical laws, or make the calibrated model ineffective for extrapolative scenarios. This work will overview a principled path for representing and quantifying model errors, as well as propagating them together with the rest of the predictive uncertainty budget, including data noise, parametric uncertainties and surrogate-related errors. Namely, the model error terms will be embedded in select model components rather than as external corrections. Such embedding ensures consistency with physical constraints on model predictions, and renders calibrated model predictions meaningful and robust with respect to model errors. Besides, in the presence of observational data, the approach can effectively differentiate model structural deficiencies from those of data acquisition. The methodology is implemented in UQ Toolkit (www.sandia.gov/uqtoolkit), relying on a host of available forward and inverse UQ tools. We will demonstrate the application of the technique on few application of interest, including ACME Land Model calibration via a wide range of measurements obtained at select sites.

An overview of selected NASP aeroelastic studies at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Spain, Charles V.; Soistmann, David L.; Parker, Ellen C.; Gibbons, Michael D.; Gilbert, Michael G.

1990-01-01

Following an initial discussion of the NASP flight environment, the results of recent aeroelastic testing of NASP-type highly swept delta-wing models in Langley's Transonic Dynamics Tunnel (TDT) are summarized. Subsonic and transonic flutter characteristics of a variety of these models are described, and several analytical codes used to predict flutter of these models are evaluated. These codes generally provide good, but conservative predictions of subsonic and transonic flutter. Also, test results are presented on a nonlinear transonic phenomena known as aileron buzz which occurred in the wind tunnel on highly swept delta wings with full-span ailerons. An analytical procedure which assesses the effects of hypersonic heating on aeroelastic instabilities (aerothermoelasticity) is also described. This procedure accurately predicted flutter of a heated aluminum wing on which experimental data exists. Results are presented on the application of this method to calculate the flutter characteristics of a fine-element model of a generic NASP configuration. Finally, it is demonstrated analytically that active controls can be employed to improve the aeroelastic stability and ride quality of a generic NASP vehicle flying at hypersonic speeds.

In praise of mechanistically-rich models

USGS Publications Warehouse

DeAngelis, Donald L.; Mooij, Wolf M.; Canham, Charles D.; Cole, Jonathan J.; Lauenroth, William K.

2003-01-01

The book opens with an overview of the status and role of modeling in ecosystem science, including perspectives on the long-running debate over the appropriate level of complexity in models. This is followed by eight chapters that address the critical issue of evaluating ecosystem models, including methods of addressing uncertainty. Next come several case studies of the role of models in environmental policy and management. A section on the future of modeling in ecosystem science focuses on increasing the use of modeling in undergraduate education and the modeling skills of professionals within the field. The benefits and limitations of predictive (versus observational) models are also considered in detail. Written by stellar contributors, this book grants access to the state of the art and science of ecosystem modeling.

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Eigenspace perturbations for structural uncertainty estimation of turbulence closure models

NASA Astrophysics Data System (ADS)

Jofre, Lluis; Mishra, Aashwin; Iaccarino, Gianluca

2017-11-01

With the present state of computational resources, a purely numerical resolution of turbulent flows encountered in engineering applications is not viable. Consequently, investigations into turbulence rely on various degrees of modeling. Archetypal amongst these variable resolution approaches would be RANS models in two-equation closures, and subgrid-scale models in LES. However, owing to the simplifications introduced during model formulation, the fidelity of all such models is limited, and therefore the explicit quantification of the predictive uncertainty is essential. In such scenario, the ideal uncertainty estimation procedure must be agnostic to modeling resolution, methodology, and the nature or level of the model filter. The procedure should be able to give reliable prediction intervals for different Quantities of Interest, over varied flows and flow conditions, and at diametric levels of modeling resolution. In this talk, we present and substantiate the Eigenspace perturbation framework as an uncertainty estimation paradigm that meets these criteria. Commencing from a broad overview, we outline the details of this framework at different modeling resolution. Thence, using benchmark flows, along with engineering problems, the efficacy of this procedure is established. This research was partially supported by NNSA under the Predictive Science Academic Alliance Program (PSAAP) II, and by DARPA under the Enabling Quantification of Uncertainty in Physical Systems (EQUiPS) project (technical monitor: Dr Fariba Fahroo).

Using neural networks for prediction of air pollution index in industrial city

NASA Astrophysics Data System (ADS)

Rahman, P. A.; Panchenko, A. A.; Safarov, A. M.

2017-10-01

This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.

Man-Machine Communication in Remote Manipulation: Task-Oriented Supervisory Command Language (TOSC).

DTIC Science & Technology

1980-03-01

ORIENTED SUPERVISORY CONTROL SYSTEM METHODOLOGY 3-1 3.1 Overview 3-1 3.2 Background 3-3 3.2.1 General 3-3 3.2.2 Preliminary Principles of Command Language...Design 3-4 3.2.3 Preliminary Principles of Feedback Display Design 3-9 3.3 Man-Machine Communication Models 3-12 3.3.1 Background 3-12 3.3.2 Adapted...and feedback mode. The work ends with the presentation of a performance prediction model and a set of principles and guidelines, applicable to the

Oculomotor prediction: a window into the psychotic mind

PubMed Central

Thakkar, Katharine N.; Diwadkar, Vaibhav A.; Rolfs, Martin

2017-01-01

Psychosis—an impaired contact with reality—is a hallmark of schizophrenia. Many psychotic symptoms are associated with disruptions in agency—the sense that I cause my actions. A failure to predict sensory consequences of one’s own actions may underlie agency disturbances. Such predictions rely on corollary discharge (CD) signals, “copies” of movement commands sent to sensory regions prior to action execution. Here, we make a case that the oculomotor system is a promising model for understanding CD in psychosis, building on advances in our understanding of the behavioral and neurophysiological correlates of CD associated with eye movements. We provide an overview of recent evidence for disturbed oculomotor CD in schizophrenia, potentially linking bizarre and disturbing psychotic experiences with basic physiological processes. PMID:28292639

Boundary Layer Transition Flight Experiment Overview and In-Situ Measurements

NASA Technical Reports Server (NTRS)

Berger, Karen T.; Anderson, Brian P.; Campbell, Charles H.; Garske, Michael T.; Saucedo, Luis A.; Kinder, Gerald R.

2010-01-01

In support of the Boundary Layer Transition Flight Experiment (BLT FE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for the flights of STS-119, STS-128 and STS-131. Additional instrumentation was installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLT FE Project. Significant efforts were made to place the protuberance at an appropriate location on the Orbiter and to design the protuberance to withstand the expected environments. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that predictions for boundary layer transition onset time closely match the flight data, while predicted temperatures were significantly higher than observed flight temperatures.

NASA Iced Aerodynamics and Controls Current Research

NASA Technical Reports Server (NTRS)

Addy, Gene

2009-01-01

This slide presentation reviews the state of current research in the area of aerodynamics and aircraft control with ice conditions by the Aviation Safety Program, part of the Integrated Resilient Aircraft Controls Project (IRAC). Included in the presentation is a overview of the modeling efforts. The objective of the modeling is to develop experimental and computational methods to model and predict aircraft response during adverse flight conditions, including icing. The Aircraft icing modeling efforts includes the Ice-Contaminated Aerodynamics Modeling, which examines the effects of ice contamination on aircraft aerodynamics, and CFD modeling of ice-contaminated aircraft aerodynamics, and Advanced Ice Accretion Process Modeling which examines the physics of ice accretion, and works on computational modeling of ice accretions. The IRAC testbed, a Generic Transport Model (GTM) and its use in the investigation of the effects of icing on its aerodynamics is also reviewed. This has led to a more thorough understanding and models, both theoretical and empirical of icing physics and ice accretion for airframes, advanced 3D ice accretion prediction codes, CFD methods for iced aerodynamics and better understanding of aircraft iced aerodynamics and its effects on control surface effectiveness.

Classification and disease prediction via mathematical programming

NASA Astrophysics Data System (ADS)

Lee, Eva K.; Wu, Tsung-Lin

2007-11-01

In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80% to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Overview of Recent Radiation Transport Code Comparisons for Space Applications

NASA Astrophysics Data System (ADS)

Townsend, Lawrence

Recent advances in radiation transport code development for space applications have resulted in various comparisons of code predictions for a variety of scenarios and codes. Comparisons among both Monte Carlo and deterministic codes have been made and published by vari-ous groups and collaborations, including comparisons involving, but not limited to HZETRN, HETC-HEDS, FLUKA, GEANT, PHITS, and MCNPX. In this work, an overview of recent code prediction inter-comparisons, including comparisons to available experimental data, is presented and discussed, with emphases on those areas of agreement and disagreement among the various code predictions and published data.

Calculating system reliability with SRFYDO

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

Morzinski, Jerome; Anderson - Cook, Christine M; Klamann, Richard M

2010-01-01

SRFYDO is a process for estimating reliability of complex systems. Using information from all applicable sources, including full-system (flight) data, component test data, and expert (engineering) judgment, SRFYDO produces reliability estimates and predictions. It is appropriate for series systems with possibly several versions of the system which share some common components. It models reliability as a function of age and up to 2 other lifecycle (usage) covariates. Initial output from its Exploratory Data Analysis mode consists of plots and numerical summaries so that the user can check data entry and model assumptions, and help determine a final form for themore » system model. The System Reliability mode runs a complete reliability calculation using Bayesian methodology. This mode produces results that estimate reliability at the component, sub-system, and system level. The results include estimates of uncertainty, and can predict reliability at some not-too-distant time in the future. This paper presents an overview of the underlying statistical model for the analysis, discusses model assumptions, and demonstrates usage of SRFYDO.« less

Overview of physical models of liquid entrainment in annular gas-liquid flow

NASA Astrophysics Data System (ADS)

Cherdantsev, Andrey V.

2018-03-01

A number of recent papers devoted to development of physically-based models for prediction of liquid entrainment in annular regime of two-phase flow are analyzed. In these models shearing-off the crests of disturbance waves by the gas drag force is supposed to be the physical mechanism of entrainment phenomenon. The models are based on a number of assumptions on wavy structure, including inception of disturbance waves due to Kelvin-Helmholtz instability, linear velocity profile inside liquid film and high degree of three-dimensionality of disturbance waves. Validity of the assumptions is analyzed by comparison to modern experimental observations. It was shown that nearly every assumption is in strong qualitative and quantitative disagreement with experiments, which leads to massive discrepancies between the modeled and real properties of the disturbance waves. As a result, such models over-predict the entrained fraction by several orders of magnitude. The discrepancy is usually reduced using various kinds of empirical corrections. This, combined with empiricism already included in the models, turns the models into another kind of empirical correlations rather than physically-based models.

An Overview of Different Approaches for Battery Lifetime Prediction

NASA Astrophysics Data System (ADS)

Zhang, Peng; Liang, Jun; Zhang, Feng

2017-05-01

With the rapid development of renewable energy and the continuous improvement of the power supply reliability, battery energy storage technology has been wildly used in power system. Battery degradation is a nonnegligible issue when battery energy storage system participates in system design and operation strategies optimization. The health assessment and remaining cycle life estimation of battery gradually become a challenge and research hotspot in many engineering areas. In this paper, the battery capacity falling and internal resistance increase are presented on the basis of chemical reactions inside the battery. The general life prediction models are analysed from several aspects. The characteristics of them as well as their application scenarios are discussed in the survey. In addition, a novel weighted Ah ageing model with the introduction of the Ragone curve is proposed to provide a detailed understanding of the ageing processes. A rigorous proof of the mathematical theory about the proposed model is given in the paper.

Dynamic thermal signature prediction for real-time scene generation

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Deep learning for computational chemistry.

PubMed

Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

2017-06-15

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

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

Brown, C. W.; Hood, Raleigh R.; Long, Wen

The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat modelsmore » of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.« less

Bioprinted three dimensional human tissues for toxicology and disease modeling.

PubMed

Nguyen, Deborah G; Pentoney, Stephen L

2017-03-01

The high rate of attrition among clinical-stage therapies, due largely to an inability to predict human toxicity and/or efficacy, underscores the need for in vitro models that better recapitulate in vivo human biology. In much the same way that additive manufacturing has revolutionized the production of solid objects, three-dimensional (3D) bioprinting is enabling the automated production of more architecturally and functionally accurate in vitro tissue culture models. Here, we provide an overview of the most commonly used bioprinting approaches and how they are being used to generate complex in vitro tissues for use in toxicology and disease modeling research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Atmosphere-Wave-Ocean Coupling from Regional to Global Earth System Models for High-Impact Extreme Weather Prediction

NASA Astrophysics Data System (ADS)

Chen, S. S.; Curcic, M.

2017-12-01

The need for acurrate and integrated impact forecasts of extreme wind, rain, waves, and storm surge is growing as coastal population and built environment expand worldwide. A key limiting factor in forecasting impacts of extreme weather events associated with tropical cycle and winter storms is fully coupled atmosphere-wave-ocean model interface with explicit momentum and energy exchange. It is not only critical for accurate prediction of storm intensity, but also provides coherent wind, rian, ocean waves and currents forecasts for forcing for storm surge. The Unified Wave INterface (UWIN) has been developed for coupling of the atmosphere-wave-ocean models. UWIN couples the atmosphere, wave, and ocean models using the Earth System Modeling Framework (ESMF). It is a physically based and computationally efficient coupling sytem that is flexible to use in a multi-model system and portable for transition to the next generation global Earth system prediction mdoels. This standardized coupling framework allows researchers to develop and test air-sea coupling parameterizations and coupled data assimilation, and to better facilitate research-to-operation activities. It has been used and extensively tested and verified in regional coupled model forecasts of tropical cycles and winter storms (Chen and Curcic 2016, Curcic et al. 2016, and Judt et al. 2016). We will present 1) an overview of UWIN and its applications in fully coupled atmosphere-wave-ocean model predictions of hurricanes and coastal winter storms, and 2) implenmentation of UWIN in the NASA GMAO GEOS-5.

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

NASA Astrophysics Data System (ADS)

Pulkkinen, A.

2012-12-01

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

Methods and Applications of the Audibility Index in Hearing Aid Selection and Fitting

PubMed Central

Amlani, Amyn M.; Punch, Jerry L.; Ching, Teresa Y. C.

2002-01-01

During the first half of the 20th century, communications engineers at Bell Telephone Laboratories developed the articulation model for predicting speech intelligibility transmitted through different telecommunication devices under varying electroacoustic conditions. The profession of audiology adopted this model and its quantitative aspects, known as the Articulation Index and Speech Intelligibility Index, and applied these indices to the prediction of unaided and aided speech intelligibility in hearing-impaired listeners. Over time, the calculation methods of these indices—referred to collectively in this paper as the Audibility Index—have been continually refined and simplified for clinical use. This article provides (1) an overview of the basic principles and the calculation methods of the Audibility Index, the Speech Transmission Index and related indices, as well as the Speech Recognition Sensitivity Model, (2) a review of the literature on using the Audibility Index to predict speech intelligibility of hearing-impaired listeners, (3) a review of the literature on the applicability of the Audibility Index to the selection and fitting of hearing aids, and (4) a discussion of future scientific needs and clinical applications of the Audibility Index. PMID:25425917

An Overview of Human Figure Modeling for Army Aviation Systems

DTIC Science & Technology

2010-04-01

An Overview of Human Figure Modeling for Army Aviation Systems by Jamison S. Hicks, David B. Durbin, and Richard W. Kozycki ARL-TR-5154...April 2010 An Overview of Human Figure Modeling for Army Aviation Systems Jamison S. Hicks, David B. Durbin, and Richard W. Kozycki...TYPE Final 3. DATES COVERED (From - To) May 2009–August 2009 4. TITLE AND SUBTITLE An Overview of Human Figure Modeling for Army Aviation Systems

Development of new geoinformation methods for modelling and prediction of sea level change over different timescales - overview of the project

NASA Astrophysics Data System (ADS)

Niedzielski, T.; Włosińska, M.; Miziński, B.; Hewelt, M.; Migoń, P.; Kosek, W.; Priede, I. G.

2012-04-01

The poster aims to provide a broad scientific audience with a general overview of a project on sea level change modelling and prediction that has just commenced at the University of Wrocław, Poland. The initiative that the project fits, called the Homing Plus programme, is organised by the Foundation for Polish Science and financially supported by the European Union through the European Regional Development Fund and the Innovative Economy Programme. There are two key research objectives of the project that complement each other. First, emphasis is put on modern satellite altimetric gridded time series from the Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO) repository. Daily sea level anomaly maps, access to which in near-real time is courtesy of AVISO, are being steadily downloaded every day to our local server in Wroclaw, Poland. These data will be processed within a general framework of modelling and prediction of sea level change in short, medium and long term. Secondly, sea level change over geological time is scrutinised in order to cover very long time scales that go far beyond a history of altimetric and tide-gauge measurements. The aforementioned approaches comprise a few tasks that aim to solve the following detailed problems. Within the first one, our objective is to seek spatio-temporal dependencies in the gridded sea level anomaly time series. Subsequently, predictions that make use of such cross-correlations shall be derived, and near-real time service for automatic update with validation will be implemented. Concurrently, (i.e. apart from spatio-temporal dependencies and their use in the process of forecasting variable sea level topography), threshold models shall be utilised for predicting the El Niño/Southern Oscillation (ENSO) signal that is normally present in sea level anomaly time series of the equatorial Pacific. Within the second approach, however, the entirely different methods are proposed. Links between sea floor topography and sea level change will be quantified, with a particular emphasis placed on the hypsometric curve and its semi-empirical modelling. Very long-term projections of sea level change will be based on testing statistical hypotheses and trend analyses, but input data will be calculated from theoretical models. Slightly apart from this topic is a notion of nonlinearity that was earlier shown to be present in gridded sea level anomaly time series. Thus, the list of intermediate tasks concludes with a need for a comprehensive interpretation of such irregularities.

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

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

Song, Hyun-Seob; Cannon, William R.; Beliaev, Alex S.

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can bemore » potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.« less

Overview of T.E.S.T. (Toxicity Estimation Software Tool)

EPA Science Inventory

This talk provides an overview of T.E.S.T. (Toxicity Estimation Software Tool). T.E.S.T. predicts toxicity values and physical properties using a variety of different QSAR (quantitative structure activity relationship) approaches including hierarchical clustering, group contribut...

An overview of the on-orbit contamination of the Long Duration Exposure Facility (LDEF)

NASA Technical Reports Server (NTRS)

Stuckey, W. K.

1993-01-01

Contamination that leads to degradation of critical surfaces becomes a vital design issue for many spacecraft programs. One of the processes that must be considered is the on-orbit accumulation of contaminants. The Long Duration Exposure Facility (LDEF) has presented an opportunity to examine the deposits on surfaces returned from orbit in order to help in understanding the deposition processes and the current models used to predict spacecraft contamination levels. The results from various investigators on the contamination of LDEF have implications for material selection, contamination models, and contamination control plans for the design of future spacecraft.

3D Simulations of Convection: From the Sun Toward Evolved Stars

NASA Astrophysics Data System (ADS)

Höfner, Susanne

2018-04-01

Basic physical considerations and detailed numerical simulations predict a dramatic increase in the sizes of convection cells during late phases of stellar evolution. The recent progress in high-angular-resolution techniques has made it possible to observe surface structures on several nearby giants and supergiants for a wide range of wavelengths. Such observations provide much-needed checkpoints for convection theory, in addition to the detailed comparisons of models and observations for the sun. In this talk I will give an overview of current 3D convection models for different types of stars and discuss related observable phenomena.

Recent advances of nanotechnology in medicine and engineering

NASA Astrophysics Data System (ADS)

Nobile, Lucio; Nobile, Stefano

2016-05-01

The aim of this paper is to give an overview of some advances of nanotechnology in medicine and engineering, exploring typical applications of these emerging technologies. The mechanical properties of such small structures determine their utility and are therefore of considerable interest. Based on nanometer scale tests, a theoretical model to predict the bending strength of a nanobeam is proposed. A fracture approach which takes into account imperfections on the beam surface and crack growth is employed.

Predicting and Mitigating Outbreaks of Vector-Borne Disease Utilizing Satellite Remote Sensing Technology and Models

NASA Technical Reports Server (NTRS)

Estes, Sue; Haynes, John; Kiang, Richard; Brown, Molly; Reisen, William

2008-01-01

Satellite earth observations present a unique vantage point of the earth's environment from space which offers a wealth of health applications for the imaginative investigator. The session will present research results of the remote sensing environmental observations of earth and health applications. This session will an overview of many of the NASA public health applications using Remote Sensing Data and will also discuss opportunities to become a research collaborator with NASA.

Fuzzy inductive reasoning: a consolidated approach to data-driven construction of complex dynamical systems

NASA Astrophysics Data System (ADS)

Nebot, Àngela; Mugica, Francisco

2012-10-01

Fuzzy inductive reasoning (FIR) is a modelling and simulation methodology derived from the General Systems Problem Solver. It compares favourably with other soft computing methodologies, such as neural networks, genetic or neuro-fuzzy systems, and with hard computing methodologies, such as AR, ARIMA, or NARMAX, when it is used to predict future behaviour of different kinds of systems. This paper contains an overview of the FIR methodology, its historical background, and its evolution.

Pretest predictions of surface strain and fluid pressures in mercury targets undergoing thermal shock

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

Taleyarkhan, R.P.; Kim, S.H.; Haines, J.

The authors provide a perspective overview of pretest modeling and analysis work related to thermal shock effects in spallation neutron source targets that were designed for conducting thermal shock experiments at the Los Alamos Neutron Science Center (LANSCE). Data to be derived are to be used for benchmarking computational tools as well as to assess the efficacy of optical gauges for monitoring dynamic fluid pressures and phenomena such as the onset of cavitation.

Recent advances of nanotechnology in medicine and engineering

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

Nobile, Lucio; Nobile, Stefano

The aim of this paper is to give an overview of some advances of nanotechnology in medicine and engineering, exploring typical applications of these emerging technologies. The mechanical properties of such small structures determine their utility and are therefore of considerable interest. Based on nanometer scale tests, a theoretical model to predict the bending strength of a nanobeam is proposed. A fracture approach which takes into account imperfections on the beam surface and crack growth is employed.

Flight-determined engine exhaust characteristics of an F404 engine in an F-18 airplane

NASA Technical Reports Server (NTRS)

Ennix, Kimberly A.; Burcham, Frank W., Jr.; Webb, Lannie D.

1993-01-01

The exhaust characteristics of the F-18 aircraft with an F404 engine are examined with reference to the results of an acoustic flight testing program. The discussion covers an overview of the flight test planning, instrumentation, test procedures, data analysis, engine modeling codes, and results. In addition, the paper presents the exhaust velocity and Mach number data for the climb-to-cruise, Aircraft Noise Prediction Program validation, and ground tests.

Improved Foundry Castings Utilizing CAD/CAM (Computer Aided Design/ Computer Aided Manufacture). Volume 1. Overview

DTIC Science & Technology

1988-06-30

casting. 68 Figure 1-9: Line printer representation of roll solidification. 69 Figure I1-1: Test casting model. 76 Figure 11-2: Division of test casting...writing new casting analysis and design routines. The new routines would take advantage of advanced criteria for predicting casting soundness and cast...properties and technical advances in computer hardware and software. 11 2. CONCLUSIONS UPCAST, a comprehensive software package, has been developed for

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

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

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

SEISMIC DIAGNOSTICS OF RED GIANTS: FIRST COMPARISON WITH STELLAR MODELS

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

Montalban, J.; Miglio, A.; Noels, A.

2010-10-01

The clear detection with CoRoT and KEPLER of radial and non-radial solar-like oscillations in many red giants paves the way for seismic inferences on the structure of such stars. We present an overview of the properties of the adiabatic frequencies and frequency separations of radial and non-radial oscillation modes for an extended grid of models. We highlight how their detection allows a deeper insight into the internal structure and evolutionary state of red giants. In particular, we find that the properties of dipole modes constitute a promising seismic diagnostic tool of the evolutionary state of red giant stars. We comparemore » our theoretical predictions with the first 34 days of KEPLER data and predict the frequency diagram expected for red giants in the CoRoT exofield in the galactic center direction.« less

Improved Aerodynamic Analysis for Hybrid Wing Body Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2012-01-01

This paper provides an overview of ongoing efforts to develop, evaluate, and validate different tools for improved aerodynamic modeling and systems analysis of Hybrid Wing Body (HWB) aircraft configurations. Results are being presented for the evaluation of different aerodynamic tools including panel methods, enhanced panel methods with viscous drag prediction, and computational fluid dynamics. Emphasis is placed on proper prediction of aerodynamic loads for structural sizing as well as viscous drag prediction to develop drag polars for HWB conceptual design optimization. Data from transonic wind tunnel tests at the Arnold Engineering Development Center s 16-Foot Transonic Tunnel was used as a reference data set in order to evaluate the accuracy of the aerodynamic tools. Triangularized surface data and Vehicle Sketch Pad (VSP) models of an X-48B 2% scale wind tunnel model were used to generate input and model files for the different analysis tools. In support of ongoing HWB scaling studies within the NASA Environmentally Responsible Aviation (ERA) program, an improved finite element based structural analysis and weight estimation tool for HWB center bodies is currently under development. Aerodynamic results from these analyses are used to provide additional aerodynamic validation data.

An overview of service lifetime prediction (SLP)

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

Jorgensen, G.

This report describes the need for service life prediction for photovoltaic cells and associated devices, coatings, and other related technologies. Information regarding outdoor exposure tests is given.

Need for Affect and Attitudes Toward Drugs: The Mediating Role of Values.

PubMed

Lins de Holanda Coelho, Gabriel; H P Hanel, Paul; Vilar, Roosevelt; P Monteiro, Renan; Gouveia, Valdiney V; R Maio, Gregory

2018-05-04

Human values and affective traits were found to predict attitudes toward the use of different types of drugs (e.g., alcohol, marijuana, and other illegal drugs). In this study (N = 196, M age = 23.09), we aimed to gain a more comprehensive understanding of those predictors of attitudes toward drug use in a mediated structural equation model, providing a better overview of a possible motivational path that drives to such a risky behavior. Specifically, we predicted and found that the relations between need for affect and attitudes toward drug use were mediated by excitement values. Also, results showed that excitement values and need for affect positively predicted attitudes toward the use of drugs, whereas normative values predicted it negatively. The pattern of results remained the same when we investigated attitudes toward alcohol, marijuana, or illegal drugs separately. Overall, the findings indicate that emotions operate via excitement and normative values to influence risk behavior.

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Dichotomy between the band and hopping transport in organic crystals: insights from experiments.

PubMed

Yavuz, I

2017-10-04

The molecular understanding of charge-transport in organic crystals has often been tangled with identifying the true dynamical origin. While in two distinct cases where complete delocalization and localization of charge-carriers are associated with band-like and hopping-like transports, respectively, their possible coalescence poses some mystery. Moreover, the existing models are still controversial at ambient temperatures. Here, we review the issues in charge-transport theories of organic materials and then provide an overview of prominent transport models. We explored ∼60 organic crystals, the single-crystal hole/electron mobilities of which have been predicted by band-like and hopping-like transport models, separately. Our comparative results show that at room-temperature neither of the models are exclusively capable of accurately predicting mobilities in a very broad range. Hopping-like models well-predict experimental mobilities around μ ∼ 1 cm 2 V -1 s -1 but systematically diverge at high mobilities. Similarly, band-like models are good at μ > ∼50 cm 2 V -1 s -1 but systematically diverge at lower mobilities. These results suggest the development of a unique and robust room-temperature transport model incorporating a mixture of these two extreme cases, whose relative importance is associated with their predominant regions. We deduce that while band models are beneficial for rationally designing high mobility organic-semiconductors, hopping models are good to elucidate the charge-transport of most organic-semiconductors.

An overview of aeroelasticity studies for the National Aero-Space Plane

NASA Technical Reports Server (NTRS)

Ricketts, Rodney H.; Noll, Thomas E.; Whitlow, Woodrow, Jr.; Huttsell, Lawrence J.

1993-01-01

The National Aero-Space Plane (NASP), or X-30, is a single-stage-to-orbit vehicle that is designed to takeoff and land on conventional runways. Research in aeroelasticity was conducted by the NASA and the Wright Laboratory to support the design of a flight vehicle by the national contractor team. This research includes the development of new computational codes for predicting unsteady aerodynamic pressures. In addition, studies were conducted to determine the aerodynamic heating effects on vehicle aeroelasticity and to determine the effects of fuselage flexibility on the stability of the control systems. It also includes the testing of scale models to better understand the aeroelastic behavior of the X-30 and to obtain data for code validation and correlation. This paper presents an overview of the aeroelastic research which has been conducted to support the airframe design.

Array Simulations Platform (ASP) predicts NASA Data Link Module (NDLM) performance

NASA Technical Reports Server (NTRS)

Snook, Allen David

1993-01-01

Through a variety of imbedded theoretical and actual antenna patterns, the array simulation platform (ASP) enhanced analysis of the array antenna pattern effects for the KTx (Ku-Band Transmit) service of the NDLM (NASA Data Link Module). The ASP utilizes internally stored models of the NDLM antennas and can develop the overall pattern of antenna arrays through common array calculation techniques. ASP expertly assisted in the diagnosing of element phase shifter errors during KTx testing and was able to accurately predict the overall array pattern from combinations of the four internally held element patterns. This paper provides an overview of the use of the ASP software in the solving of array mis-phasing problems.

Strategies to predict metal mobility in surficial mining environments

USGS Publications Warehouse

Smith, Kathleen S.

2007-01-01

This report presents some strategies to predict metal mobility at mining sites. These strategies are based on chemical, physical, and geochemical information about metals and their interactions with the environment. An overview of conceptual models, metal sources, and relative mobility of metals under different geochemical conditions is presented, followed by a discussion of some important physical and chemical properties of metals that affect their mobility, bioavailability, and toxicity. The physical and chemical properties lead into a discussion of the importance of the chemical speciation of metals. Finally, environmental and geochemical processes and geochemical barriers that affect metal speciation are discussed. Some additional concepts and applications are briefly presented at the end of this report.

ROTONET Primer

NASA Technical Reports Server (NTRS)

Prichard, Devon S.

1996-01-01

This document provides a brief overview of use of the ROTONET rotorcraft system noise prediction capability within the Aircraft Noise Program (ANOPP). Reviews are given on rotorcraft noise, the state-of-the-art of system noise prediction, and methods for using the various ROTONET prediction modules.

Computational Modeling of Space Physiology for Informing Spaceflight Countermeasure Design and Predictions of Efficacy

NASA Technical Reports Server (NTRS)

Lewandowski, B. E.; DeWitt, J. K.; Gallo, C. A.; Gilkey, K. M.; Godfrey, A. P.; Humphreys, B. T.; Jagodnik, K. M.; Kassemi, M.; Myers, J. G.; Nelson, E. S.;

Xanthine oxidase inhibitors beyond allopurinol and febuxostat; an overview and selection of potential leads based on in silico calculated physico-chemical properties, predicted pharmacokinetics and toxicity.

PubMed

Šmelcerović, Andrija; Tomović, Katarina; Šmelcerović, Žaklina; Petronijević, Živomir; Kocić, Gordana; Tomašič, Tihomir; Jakopin, Žiga; Anderluh, Marko

2017-07-28

Xanthine oxidase (XO), a versatile metalloflavoprotein enzyme, catalyzes the oxidative hydroxylation of hypoxanthine and xanthine to uric acid in purine catabolism while simultaneously producing reactive oxygen species. Both lead to the gout-causing hyperuricemia and oxidative damage of the tissues where overactivity of XO is present. Over the past years, significant progress and efforts towards the discovery and development of new XO inhibitors have been made and we believe that not only experts in the field, but also general readership would benefit from a review that addresses this topic. Accordingly, the aim of this article was to overview and select the most potent recently reported XO inhibitors and to compare their structures, mechanisms of action, potency and effectiveness of their inhibitory activity, in silico calculated physico-chemical properties as well as predicted pharmacokinetics and toxicity. Derivatives of imidazole, 1,3-thiazole and pyrimidine proved to be more potent than febuxostat while also displaying/possessing favorable predicted physico-chemical, pharmacokinetic and toxicological properties. Although being structurally similar to febuxostat, these optimized inhibitors bear some structural freshness and could be adopted as hits for hit-to-lead development and further evaluation by in vivo studies towards novel drug candidates, and represent valuable model structures for design of novel XO inhibitors. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction

NASA Astrophysics Data System (ADS)

McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.

2017-12-01

Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used for driving meteorology. The NWP models will be evaluated against standard and mesonet fields averaged for various regions during the summer 2017. An evaluation of meteorological fields important to air quality modeling (eg: near surface winds, temperatures, moisture and boundary layer heights, cloud cover) will be reported on.

Modeling Bivariate Change in Individual Differences: Prospective Associations Between Personality and Life Satisfaction.

PubMed

Hounkpatin, Hilda Osafo; Boyce, Christopher J; Dunn, Graham; Wood, Alex M

2017-09-18

A number of structural equation models have been developed to examine change in 1 variable or the longitudinal association between 2 variables. The most common of these are the latent growth model, the autoregressive cross-lagged model, the autoregressive latent trajectory model, and the latent change score model. The authors first overview each of these models through evaluating their different assumptions surrounding the nature of change and how these assumptions may result in different data interpretations. They then, to elucidate these issues in an empirical example, examine the longitudinal association between personality traits and life satisfaction. In a representative Dutch sample (N = 8,320), with participants providing data on both personality and life satisfaction measures every 2 years over an 8-year period, the authors reproduce findings from previous research. However, some of the structural equation models overviewed have not previously been applied to the personality-life satisfaction relation. The extended empirical examination suggests intraindividual changes in life satisfaction predict subsequent intraindividual changes in personality traits. The availability of data sets with 3 or more assessment waves allows the application of more advanced structural equation models such as the autoregressive latent trajectory or the extended latent change score model, which accounts for the complex dynamic nature of change processes and allows stronger inferences on the nature of the association between variables. However, the choice of model should be determined by theories of change processes in the variables being studied. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

UTCI-Fiala multi-node model of human heat transfer and temperature regulation

NASA Astrophysics Data System (ADS)

Fiala, Dusan; Havenith, George; Bröde, Peter; Kampmann, Bernhard; Jendritzky, Gerd

2012-05-01

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

Computational intelligence techniques for biological data mining: An overview

NASA Astrophysics Data System (ADS)

Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

2014-10-01

Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

Charged-particle multiplicity at LHC energies

ScienceCinema

Grosse-Oetringhaus, Jan Fiete

2018-05-24

The talk presents the measurement of the pseudorapidity density and the multiplicity distribution with ALICE at the achieved LHC energies of 0.9 and 2.36 TeV.An overview about multiplicity measurements prior to LHC is given and the related theoretical concepts are briefly discussed.The analysis procedure is presented and the systematic uncertainties are detailed. The applied acceptance corrections and the treatment of diffraction are discussed.The results are compared with model predictions. The validity of KNO scaling in restricted phase space regions is revisited. 

Imaging spectrometer using a liquid crystal tunable filter

NASA Astrophysics Data System (ADS)

Chrien, Thomas G.; Chovit, Christopher; Miller, Peter J.

1993-09-01

A demonstration imaging spectrometer using a liquid crystal tunable filter (LCTF) was built and tested on a hot air balloon platform. The LCTF is a tunable polarization interference or Lyot filter. The LCTF enables a small, light weight, low power, band sequential imaging spectrometer design. An overview of the prototype system is given along with a description of balloon experiment results. System model performance predictions are given for a future LCTF based imaging spectrometer design. System design considerations of LCTF imaging spectrometers are discussed.

Big Data Analytic, Big Step for Patient Management and Care in Puerto Rico.

PubMed

Borrero, Ernesto E

2018-01-01

This letter provides an overview of the application of big data in health care system to improve quality of care, including predictive modelling for risk and resource use, precision medicine and clinical decision support, quality of care and performance measurement, public health and research applications, among others. The author delineates the tremendous potential for big data analytics and discuss how it can be successfully implemented in clinical practice, as an important component of a learning health-care system.

Chiral phosphoric acid catalysis: from numbers to insights.

PubMed

Maji, Rajat; Mallojjala, Sharath Chandra; Wheeler, Steven E

2018-02-19

Chiral phosphoric acids (CPAs) have emerged as powerful organocatalysts for asymmetric reactions, and applications of computational quantum chemistry have revealed important insights into the activity and selectivity of these catalysts. In this tutorial review, we provide an overview of computational tools at the disposal of computational organic chemists and demonstrate their application to a wide array of CPA catalysed reactions. Predictive models of the stereochemical outcome of these reactions are discussed along with specific examples of representative reactions and an outlook on remaining challenges in this area.

NASA Computational Fluid Dynamics Conference. Volume 1: Sessions 1-6

NASA Technical Reports Server (NTRS)

1989-01-01

Presentations given at the NASA Computational Fluid Dynamics (CFD) Conference held at the NASA Ames Research Center, Moffett Field, California, March 7-9, 1989 are given. Topics covered include research facility overviews of CFD research and applications, validation programs, direct simulation of compressible turbulence, turbulence modeling, advances in Runge-Kutta schemes for solving 3-D Navier-Stokes equations, grid generation and invicid flow computation around aircraft geometries, numerical simulation of rotorcraft, and viscous drag prediction for rotor blades.

Effects of surface chemistry on hot corrosion life: Overview

NASA Technical Reports Server (NTRS)

Merutka, J.

1982-01-01

This program concentrates on analyzing a limited number of hot corroded components from the field and the carrying out of a series of controlled laboratory experiments to establish the effects of oxide scale and coating chemistry on hot corrosion life. This is to be determined principally from the length of the incubation period, the investigation of the mechanisms of hot corrosion attack, and the fitting of the data generated from the test exposure experiments to an empirical life prediction model.

An Introduction to Observing System Simulation Experiments

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2017-01-01

Observing System Simulation Experiments (OSSEs) are used to estimate the potential impact of proposed new instruments and data on numerical weather prediction. OSSEs can also be used to help design new observing platforms and to investigate the behavior of data assimilation systems. A basic overview of how to design and perform an OSSE will be given, as well as best practices and pitfalls. Some examples using the OSSE framework developed at the NASA Global Modeling and Assimilation Office will be shown.

Pieces of the Puzzle: Tracking the Chemical Component of the ...

EPA Pesticide Factsheets

This presentation provides an overview of the risk assessment conducted at the U.S. EPA, as well as some research examples related to the exposome concept. This presentation also provides the recommendation of using two organizational and predictive frameworks for tracking chemical components in the exposome. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

Fluorescence Spectroscopy and Chemometric Modeling for Bioprocess Monitoring

PubMed Central

Faassen, Saskia M.; Hitzmann, Bernd

2015-01-01

On-line sensors for the detection of crucial process parameters are desirable for the monitoring, control and automation of processes in the biotechnology, food and pharma industry. Fluorescence spectroscopy as a highly developed and non-invasive technique that enables the on-line measurements of substrate and product concentrations or the identification of characteristic process states. During a cultivation process significant changes occur in the fluorescence spectra. By means of chemometric modeling, prediction models can be calculated and applied for process supervision and control to provide increased quality and the productivity of bioprocesses. A range of applications for different microorganisms and analytes has been proposed during the last years. This contribution provides an overview of different analysis methods for the measured fluorescence spectra and the model-building chemometric methods used for various microbial cultivations. Most of these processes are observed using the BioView® Sensor, thanks to its robustness and insensitivity to adverse process conditions. Beyond that, the PLS-method is the most frequently used chemometric method for the calculation of process models and prediction of process variables. PMID:25942644

Atmospheric Transport Studies Using In-situ Airborne Gas Chromatograph Measurements: An Overview of the NOAA Climate Monitoring and Diagnostics Laboratory (CMDL) Contribution.

NASA Astrophysics Data System (ADS)

Moore, F.; Dutton, G.; Elkins, J.; Hall, B.; Hurst, D.; Nance, D.; Ray, E.; Romashkin, P.; Thompson, T.; Volk, C. M.

2005-12-01

Accurate models of atmospheric transport are crucial to our current understanding of ozone production/loss and its coupling with climate change. Over the last ``20 years'', improvements in the ability to predict ``The Antarctic Ozone Hole and Polar Ozone Loss'' have tracked improvements in transport models. Data taken from the NOAA/CMDL airborne in-situ GC's (ACATS, LACE, PANTHER, and UCATS) have and will continue to play key roles in quantifying many aspects of stratospheric transport. Our data have been used in many of the model assessments to date. We will display an overview of the transport issues studied over the years using our data. They include descent with mixing within and into the polar vortex, entrainment of mid-latitude air across the vortex edge, upwelling and entrainment in the tropical pipe, isentropic transport across the tropopause into the lowermost stratosphere, mean ages of air parcels in the stratosphere, and stratospheric path distributions. ACATS - Airborne Chromatograph for Atmospheric Trace Species LACE - Lightweight Airborne Chromatograph Experiment PANTHER - PAN and Other Trace Hydrohalocarbons ExpeRiment UCATS - Unmanned aerial systems Chromatograph for Atmospheric Trace Species

Breast cancer risks and risk prediction models.

PubMed

Engel, Christoph; Fischer, Christine

2015-02-01

BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

“AQMEII Status Update” | Science Inventory | US EPA

EPA Pesticide Factsheets

“AQMEII Status Update”This presentation provided an overview and status update of the Air Quality Model Evaluation International Initative (AQMEII) to participants of a workshop of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) . In addition, the presentation also outlines the objectives and potential timeline for a possible next phase of AQMEII that would involve a collaboration with the current modeling activities of TF-HTAP. The purpose of the presentation was to provide participants at the HTAP meeting with an overview of current AQMEII activities and timelines and to obtain feedback from HTAP workshop participants regarding HTAP timelines. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air po

Current Testing Capabilities at the NASA Ames Ballistic Ranges

NASA Technical Reports Server (NTRS)

Ramsey, Alvin; Tam, Tim; Bogdanoff, David; Gage, Peter

1999-01-01

Capabilities for designing and performing ballistic range tests at the NASA Ames Research Center are presented. Computational tools to assist in designing and developing ballistic range models and to predict the flight characteristics of these models are described. A CFD code modeling two-stage gun performance is available, allowing muzzle velocity, maximum projectile base pressure, and gun erosion to be predicted. Aerodynamic characteristics such as drag and stability can be obtained at speeds ranging from 0.2 km/s to 8 km/s. The composition and density of the test gas can be controlled, which allows for an assessment of Reynolds number and specific heat ratio effects under conditions that closely match those encountered during planetary entry. Pressure transducers have been installed in the gun breech to record the time history of the pressure during launch, and pressure transducers have also been installed in the walls of the range to measure sonic boom effects. To illustrate the testing capabilities of the Ames ballistic ranges, an overview of some of the recent tests is given.

Applications of artificial neural networks (ANNs) in food science.

PubMed

Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

2007-01-01

Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

Chapter 6: Temperature

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Hauer, F. Richard; F. Richard Hauer,; Lamberti, G.A.

2017-01-01

Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.

Neutrophil dysregulation during sepsis: an overview and update.

PubMed

Shen, Xiao-Fei; Cao, Ke; Jiang, Jin-Peng; Guan, Wen-Xian; Du, Jun-Feng

2017-09-01

Sepsis remains a leading cause of death worldwide, despite advances in critical care, and understanding of the pathophysiology and treatment strategies. No specific therapy or drugs are available for sepsis. Neutrophils play a critical role in controlling infection under normal conditions, and it is suggested that their migration and antimicrobial activity are impaired during sepsis which contribute to the dysregulation of immune responses. Recent studies further demonstrated that interruption or reversal of the impaired migration and antimicrobial function of neutrophils improves the outcome of sepsis in animal models. In this review, we provide an overview of the associated mediators and signal pathways involved which govern the survival, migration and antimicrobial function of neutrophils in sepsis, and discuss the potential of neutrophils as a target to specifically diagnose and/or predict the outcome of sepsis. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Overview of the Martian radiation environment experiment

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

Zeitlin, C.; Cleghorn, T.F.; Cucinotta, F.A.

Space radiation presents a hazard to astronauts, particularly those journeying outside the protective influence of the geomagnetosphere. Crews on future missions to Mars will be exposed to the harsh radiation environment of deep space during the transit between Earth and Mars. Once on Mars, they will encounter radiation that is only slightly reduced, compared to free space, by the thin Martian atmosphere. NASA is obliged to minimize, where possible, the radiation exposures received by astronauts. Thus, as a precursor to eventual human exploration, it is necessary to measure the Martian radiation environment in detail. The MARIE experiment, aboard the 2001more » Mars Odyssey spacecraft, is returning the first data that bear directly on this problem. Here we provide an overview of the experiment, including introductory material on space radiation and radiation dosimetry, a description of the detector, model predictions of the radiation environment at Mars, and preliminary dose-rate data obtained at Mars.« less

Polymer-Ceramic Composite Materials for Pyroelectric Infrared Detectors: An Overview

NASA Technical Reports Server (NTRS)

Aggarwal, M. D; Currie, J. R.; Penn, B. G.; Batra, A. K.; Lal, R. B.

2007-01-01

Ferroelectrics:Polymer composites can be considered an established substitute for conventional electroceramics and ferroelectric polymers. The composites have a unique blend of polymeric properties such as mechanical flexibility, high strength, formability, and low cost, with the high electro-active properties of ceramic materials. They have attracted considerable interest because of their potential use in pyroelectric infrared detecting devices and piezoelectric transducers. These flexible sensors and transducers may eventually be useful for their health monitoring applications for NASA crew launch vehicles and crew exploration vehicles being developed. In the light of many technologically important applications in this field, it is worthwhile to present an overview of the pyroelectric infrared detector theory, models to predict dielectric behavior and pyroelectric coefficient, and the concept of connectivity and fabrication techniques of biphasic composites. An elaborate review of Pyroelectric-Polymer composite materials investigated to date for their potential use in pyroelectric infrared detectors is presented.

An Experimentalist's Overview of Solar Neutrinos

NASA Astrophysics Data System (ADS)

Oser, Scott M.

2012-02-01

Four decades of solar neutrino research have demonstrated that solar models do a remarkable job of predicting the neutrino fluxes from the Sun, to the extent that solar neutrinos can now serve as a calibrated neutrino source for experiments to understand neutrino oscillations and mixing. In this review article I will highlight the most significant experimental results, with emphasis on the latest model-independent measurements from the Sudbury Neutrino Observatory. The solar neutrino fluxes are seen to be generally well-determined experimentally, with no indications of time variability, while future experiments will elucidate the lower energy part of the neutrino spectrum, especially pep and CNO neutrinos.

ICHEP 2014 Summary: Theory Status after the First LHC Run

NASA Astrophysics Data System (ADS)

Pich, Antonio

2016-04-01

A brief overview of the main highlights discussed at ICHEP 2014 is presented. The experimental data confirm that the scalar boson discovered at the LHC couples to other particles as predicted in the Standard Model. This constitutes a great success of the present theoretical paradigm, which has been confirmed as the correct description at the electroweak scale. At the same time, the negative searches for signals of new phenomena tightly constrain many new-physics scenarios, challenging previous theoretical wisdom and opening new perspectives in fundamental physics. Fresh ideas are needed to face the many pending questions unanswered within the Standard Model framework.

Rate dependent constitutive behavior of dielectric elastomers and applications in legged robotics

NASA Astrophysics Data System (ADS)

Oates, William; Miles, Paul; Gao, Wei; Clark, Jonathan; Mashayekhi, Somayeh; Hussaini, M. Yousuff

2017-04-01

Dielectric elastomers exhibit novel electromechanical coupling that has been exploited in many adaptive structure applications. Whereas the quasi-static, one-dimensional constitutive behavior can often be accurately quantified by hyperelastic functions and linear dielectric relations, accurate predictions of electromechanical, rate-dependent deformation during multiaxial loading is non-trivial. In this paper, an overview of multiaxial electromechanical membrane finite element modeling is formulated. Viscoelastic constitutive relations are extended to include fractional order. It is shown that fractional order viscoelastic constitutive relations are superior to conventional integer order models. This knowledge is critical for transition to control of legged robotic structures that exhibit advanced mobility.

Verification of a VRF Heat Pump Computer Model in EnergyPlus

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

Nigusse, Bereket; Raustad, Richard

2013-06-15

This paper provides verification results of the EnergyPlus variable refrigerant flow (VRF) heat pump computer model using manufacturer's performance data. The paper provides an overview of the VRF model, presents the verification methodology, and discusses the results. The verification provides quantitative comparison of full and part-load performance to manufacturer's data in cooling-only and heating-only modes of operation. The VRF heat pump computer model uses dual range bi-quadratic performance curves to represent capacity and Energy Input Ratio (EIR) as a function of indoor and outdoor air temperatures, and dual range quadratic performance curves as a function of part-load-ratio for modeling part-loadmore » performance. These performance curves are generated directly from manufacturer's published performance data. The verification compared the simulation output directly to manufacturer's performance data, and found that the dual range equation fit VRF heat pump computer model predicts the manufacturer's performance data very well over a wide range of indoor and outdoor temperatures and part-load conditions. The predicted capacity and electric power deviations are comparbale to equation-fit HVAC computer models commonly used for packaged and split unitary HVAC equipment.« less

Overview and evaluation of different nuclear level density models for the 123I radionuclide production.

PubMed

Nikjou, A; Sadeghi, M

2018-06-01

The 123 I radionuclide (T 1/2 = 13.22 h, β+ = 100%) is one of the most potent gamma emitters for nuclear medicine. In this study, the cyclotron production of this radionuclide via different nuclear reactions namely, the 121 Sb(α,2n), 122 Te(d,n), 123 Te(p,n), 124 Te(p,2n), 124 Xe(p,2n), 127 I(p,5n) and 127 I(d,6n) were investigated. The effect of the various phenomenological nuclear level density models such as Fermi gas model (FGM), Back-shifted Fermi gas model (BSFGM), Generalized superfluid model (GSM) and Enhanced generalized superfluid model (EGSM) moreover, the three microscopic level density models were evaluated for predicting of cross sections and production yield predictions. The SRIM code was used to obtain the target thickness. The 123 I excitation function of reactions were calculated by using of the TALYS-1.8, EMPIRE-3.2 nuclear codes and with data which taken from TENDL-2015 database, and finally the theoretical calculations were compared with reported experimental measurements in which taken from EXFOR database. Copyright © 2018 Elsevier Ltd. All rights reserved.

Environmental Barrier Coating (EBC) Durability Modeling; An Overview and Preliminary Analysis

NASA Technical Reports Server (NTRS)

Abdul-Aziz, A.; Bhatt, R. T.; Grady, J. E.; Zhu, D.

2012-01-01

A study outlining a fracture mechanics based model that is being developed to investigate crack growth and spallation of environmental barrier coating (EBC) under thermal cycling conditions is presented. A description of the current plan and a model to estimate thermal residual stresses in the coating and preliminary fracture mechanics concepts for studying crack growth in the coating are also discussed. A road map for modeling life and durability of the EBC and the results of FEA model(s) developed for predicting thermal residual stresses and the cracking behavior of the coating are generated and described. Further initial assessment and preliminary results showed that developing a comprehensive EBC life prediction model incorporating EBC cracking, degradation and spalling mechanism under stress and temperature gradients typically seen in turbine components is difficult. This is basically due to mismatch in thermal expansion difference between sub-layers of EBC as well as between EBC and substrate, diffusion of moisture and oxygen though the coating, and densification of the coating during operating conditions as well as due to foreign object damage, the EBC can also crack and spall from the substrate causing oxidation and recession and reducing the design life of the EBC coated substrate.

Recent advances in modeling the propagation noise in high-rise cities

NASA Astrophysics Data System (ADS)

Li, Kai Ming

2005-04-01

In the past few decades, we have witnessed a rapid growth in mechanized transport and transportation systems. We live in a transport-dominated society which has led to a marked improvement in dispersal of land use and to the increased opportunity for the separate development of residential, commercial, and industrial areas. In dense and high-rise cities, various modes of land transportation are the primary source of noise. The problem of transportation noise is not confined by political or social frontiers. It affects the rich who may live in a quiet residential area but who must make full use of transport to maintain their affluent existence, as well as the less fortunate who must live close to a highway, a major road, or an elevated railway line. A systematic development of the capability for accurate predictions of the propagation of land transportation noise in dense high-rise cities is highly desirable. This paper summarizes the current models for predicting sound fields in urban environments and gives an overview of the recent advances of various numerical models to predict the sound field in urban environments. [Work supported by the Research Grants Council of the Hong Kong SAR Government and the Hong Kong Polytechnic University.

Hydro morphodynamic modelling in Mediterranean storms: errors and uncertainties under sharp gradients

NASA Astrophysics Data System (ADS)

Sánchez-Arcilla, A.; Gracia, V.; García, M.

2014-02-01

This paper deals with the limits in hydrodynamic and morphodynamic predictions for semi-enclosed coastal domains subject to sharp gradients (in bathymetry, topography, sediment transport and coastal damages). It starts with an overview of wave prediction limits (based on satellite images) in a restricted domain such as is the Mediterranean basin, followed by an in-depth analysis of the Catalan coast, one of the land boundaries of such a domain. The morphodynamic modeling for such gradient regions is next illustrated with the simulation of the largest recorded storm in the Catalan coast, whose morphological impact is a key element of the storm impact. The driving wave and surge conditions produce a morphodynamic response that is validated against the pre and post storm beach state, recovered from two LIDAR images. The quality of the fit is discussed in terms of the physical processes and the suitability of the employed modeling equations. Some remarks about the role of the numerical discretization and boundary conditions are also included in the analysis. From here an assessment of errors and uncertainties is presented, with the aim of establishing the prediction limits for coastal engineering flooding and erosion analyses.

NOAA Climate Program Office Contributions to National ESPC

NASA Astrophysics Data System (ADS)

Higgins, W.; Huang, J.; Mariotti, A.; Archambault, H. M.; Barrie, D.; Lucas, S. E.; Mathis, J. T.; Legler, D. M.; Pulwarty, R. S.; Nierenberg, C.; Jones, H.; Cortinas, J. V., Jr.; Carman, J.

2016-12-01

NOAA is one of five federal agencies (DOD, DOE, NASA, NOAA, and NSF) which signed an updated charter in 2016 to partner on the National Earth System Prediction Capability (ESPC). Situated within NOAA's Office of Oceanic and Atmospheric Research (OAR), NOAA Climate Program Office (CPO) programs contribute significantly to the National ESPC goals and activities. This presentation will provide an overview of CPO contributions to National ESPC. First, we will discuss selected CPO research and transition activities that directly benefit the ESPC coupled model prediction capability, including The North American Multi-Model Ensemble (NMME) seasonal prediction system The Subseasonal Experiment (SubX) project to test real-time subseasonal ensemble prediction systems. Improvements to the NOAA operational Climate Forecast System (CFS), including software infrastructure and data assimilation. Next, we will show how CPO's foundational research activities are advancing future ESPC capabilities. Highlights will include: The Tropical Pacific Observing System (TPOS) to provide the basis for predicting climate on subseasonal to decadal timescales. Subseasonal-to-Seasonal (S2S) processes and predictability studies to improve understanding, modeling and prediction of the MJO. An Arctic Research Program to address urgent needs for advancing monitoring and prediction capabilities in this major area of concern. Advances towards building an experimental multi-decadal prediction system through studies on the Atlantic Meridional Overturning Circulation (AMOC). Finally, CPO has embraced Integrated Information Systems (IIS's) that build on the innovation of programs such as the National Integrated Drought Information System (NIDIS) to develop and deliver end to end environmental information for key societal challenges (e.g. extreme heat; coastal flooding). These contributions will help the National ESPC better understand and address societal needs and decision support requirements.

Boundary Layer Transition Flight Experiment Overview

NASA Technical Reports Server (NTRS)

Berger, Karen T.; Anderson, Brian P.; Campbell, Charles H.; Garske, Michael T.; Saucedo, Luis A.; Kinder, Gerald R.; Micklos, Ann M.

2011-01-01

In support of the Boundary Layer Transition Flight Experiment (BLT FE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for STS-119, STS-128, STS-131 and STS-133 as well as Space Shuttle Endeavour for STS-134. Additional instrumentation was installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLT FE Project with emphasis on the STS-131 and STS-133 results. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that empirically correlated predictions for boundary layer transition onset time closely match the flight data, while predicted surface temperatures were significantly higher than observed flight temperatures. A thermocouple anomaly observed on a number of the missions is discussed as are a number of the mitigation actions that will be taken on the final flight, STS-134, including potential alterations of the flight trajectory and changes to the flight instrumentation.

Boundary Layer Transition Flight Experiment Overview and In-Situ Measurements

NASA Technical Reports Server (NTRS)

Anderson, Brian P.; Campbell, Charles H.; Saucedo, Luis A.; Kinder, Gerald R.; Berger, Karen T.

2010-01-01

In support of the Boundary Layer Transition Flight Experiment (BLTFE) Project, a manufactured protuberance tile was installed on the port wing of Space Shuttle Orbiter Discovery for the flights of STS-119 and STS-128. Additional instrumentation was also installed in order to obtain more spatially resolved measurements downstream of the protuberance. This paper provides an overview of the BLTFE Project, including the project history, organizations involved, and motivations for the flight experiment. Significant efforts were made to place the protuberance at an appropriate location on the Orbiter and to design the protuberance to withstand the expected environments. Efforts were also extended to understand the as-fabricated shape of the protuberance and the thermal protection system tile configuration surrounding the protuberance. A high-level overview of the in-situ flight data is presented, along with a summary of the comparisons between pre- and post-flight analysis predictions and flight data. Comparisons show that predictions for boundary layer transition onset time closely match the flight data, while predicted temperatures were significantly higher than observed flight temperatures.

Accelerated Time-Domain Modeling of Electromagnetic Pulse Excitation of Finite-Length Dissipative Conductors over a Ground Plane via Function Fitting and Recursive Convolution

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

Campione, Salvatore; Warne, Larry K.; Sainath, Kamalesh

In this report we overview the fundamental concepts for a pair of techniques which together greatly hasten computational predictions of electromagnetic pulse (EMP) excitation of finite-length dissipative conductors over a ground plane. In a time- domain, transmission line (TL) model implementation, predictions are computationally bottlenecked time-wise, either for late-time predictions (about 100ns-10000ns range) or predictions concerning EMP excitation of long TLs (order of kilometers or more ). This is because the method requires a temporal convolution to account for the losses in the ground. Addressing this to facilitate practical simulation of EMP excitation of TLs, we first apply a techniquemore » to extract an (approximate) complex exponential function basis-fit to the ground/Earth's impedance function, followed by incorporating this into a recursion-based convolution acceleration technique. Because the recursion-based method only requires the evaluation of the most recent voltage history data (versus the entire history in a "brute-force" convolution evaluation), we achieve necessary time speed- ups across a variety of TL/Earth geometry/material scenarios. Intentionally Left Blank« less

Overview of Global/Regional Models Used to Evaluate Tropospheric Ozone in North America

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.

2015-01-01

Ozone (O3) is an important greenhouse gas, toxic pollutant, and plays a major role in atmospheric chemistry. Tropospheric O3 which resides in the planetary boundary layer (PBL) is highly reactive and has a lifetime on the order of days, however, O3 in the free troposphere and stratosphere has a lifetime on the order of weeks or months. Modeling O3 mixing ratios at and above the surface is difficult due to the multiple formation/destruction processes and transport pathways that cause large spatio-temporal variability in O3 mixing ratios. This talk will summarize in detail the global/regional models that are commonly used to simulate/predict O3 mixing ratios in the United States. The major models which will be focused on are the: 1) Community Multi-scale Air Quality Model (CMAQ), 2) Comprehensive Air Quality Model with Extensions (CAMx), 3) Goddard Earth Observing System with Chemistry (GEOS-Chem), 4) Real Time Air Quality Modeling System (RAQMS), 5) Weather Research and Forecasting/Chemistry (WRF-Chem) model, National Center for Atmospheric Research (NCAR)'s Model for OZone And Related chemical Tracers (MOZART), and 7) Geophysical Fluid Dynamics Laboratory (GFDL) AM3 model. I will discuss the major modeling components which impact O3 mixing ratio calculations in each model and the similarities/differences between these models. This presentation is vital to the 2nd Annual Tropospheric Ozone Lidar Network (TOLNet) Conference as it will provide an overview of tools, which can be used in conjunction with TOLNet data, to evaluate the complex chemistry and transport pathways controlling tropospheric O3 mixing ratios.

Multivariate statistical analysis of a high rate biofilm process treating kraft mill bleach plant effluent.

PubMed

Goode, C; LeRoy, J; Allen, D G

2007-01-01

This study reports on a multivariate analysis of the moving bed biofilm reactor (MBBR) wastewater treatment system at a Canadian pulp mill. The modelling approach involved a data overview by principal component analysis (PCA) followed by partial least squares (PLS) modelling with the objective of explaining and predicting changes in the BOD output of the reactor. Over two years of data with 87 process measurements were used to build the models. Variables were collected from the MBBR control scheme as well as upstream in the bleach plant and in digestion. To account for process dynamics, a variable lagging approach was used for variables with significant temporal correlations. It was found that wood type pulped at the mill was a significant variable governing reactor performance. Other important variables included flow parameters, faults in the temperature or pH control of the reactor, and some potential indirect indicators of biomass activity (residual nitrogen and pH out). The most predictive model was found to have an RMSEP value of 606 kgBOD/d, representing a 14.5% average error. This was a good fit, given the measurement error of the BOD test. Overall, the statistical approach was effective in describing and predicting MBBR treatment performance.

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.

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.

Development of a high resolution interstellar dust engineering model - overview of the project

NASA Astrophysics Data System (ADS)

Sterken, V. J.; Strub, P.; Soja, R. H.; Srama, R.; Krüger, H.; Grün, E.

2013-09-01

Beyond 3 AU heliocentric distance, the flow of interstellar dust through the solar system is a dominant component of the total dust population. The modulation of this flux with the solar cycle and the position in the solar system has been predicted by theoretical studies since the seventies. The modulation was proven to exist by matching dust trajectory simulations with real spacecraft data from Ulysses in 1998. The modulations were further analyzed and studies in detail in 2012. The current ESA interplanetary meteoroid model IMEM includes an interstellar dust component, but this component was modelled only with straight line trajectories through the solar system. For the new ESA IMEX model, a high-resolution interstellar dust component is implemented separately from a dust streams module. The dust streams module focuses on dust in streams that was released from comets (cf. Abstract R. Soja). Parallel processing techniques are used to improve computation time (cf. Abstract P. Strub). The goal is to make predictions for the interstellar dust flux as close to the Sun as 1 AU or closer, for future space mission design.

Description of the University of Auckland Global Mars Mesoscale Meteorological Model (GM4)

NASA Astrophysics Data System (ADS)

Wing, D. R.; Austin, G. L.

2005-08-01

The University of Auckland Global Mars Mesoscale Meteorological Model (GM4) is a numerical weather prediction model of the Martian atmosphere that has been developed through the conversion of the Penn State University / National Center for Atmospheric Research fifth generation mesoscale model (MM5). The global aspect of this model is self consistent, overlapping, and forms a continuous domain around the entire planet, removing the need to provide boundary conditions other than at initialisation, yielding independence from the constraint of a Mars general circulation model. The brief overview of the model will be given, outlining the key physical processes and setup of the model. Comparison between data collected from Mars Pathfinder during its 1997 mission and simulated conditions using GM4 have been performed. Diurnal temperature variation as predicted by the model shows very good correspondence with the surface truth data, to within 5 K for the majority of the diurnal cycle. Mars Viking Data is also compared with the model, with good agreement. As a further means of validation for the model, various seasonal comparisons of surface and vertical atmospheric structure are conducted with the European Space Agency AOPP/LMD Mars Climate Database. Selected simulations over regions of interest will also be presented.

The Global Modeling Test Bed - Building a New National Capability for Advancing Operational Global Modeling in the United States.

NASA Astrophysics Data System (ADS)

Toepfer, F.; Cortinas, J. V., Jr.; Kuo, W.; Tallapragada, V.; Stajner, I.; Nance, L. B.; Kelleher, K. E.; Firl, G.; Bernardet, L.

2017-12-01

NOAA develops, operates, and maintains an operational global modeling capability for weather, sub seasonal and seasonal prediction for the protection of life and property and fostering the US economy. In order to substantially improve the overall performance and accelerate advancements of the operational modeling suite, NOAA is partnering with NCAR to design and build the Global Modeling Test Bed (GMTB). The GMTB has been established to provide a platform and a capability for researchers to contribute to the advancement primarily through the development of physical parameterizations needed to improve operational NWP. The strategy to achieve this goal relies on effectively leveraging global expertise through a modern collaborative software development framework. This framework consists of a repository of vetted and supported physical parameterizations known as the Common Community Physics Package (CCPP), a common well-documented interface known as the Interoperable Physics Driver (IPD) for combining schemes into suites and for their configuration and connection to dynamic cores, and an open evidence-based governance process for managing the development and evolution of CCPP. In addition, a physics test harness designed to work within this framework has been established in order to facilitate easier like-to-like comparison of physics advancements. This paper will present an overview of the design of the CCPP and test platform. Additionally, an overview of potential new opportunities of how physics developers can engage in the process, from implementing code for CCPP/IPD compliance to testing their development within an operational-like software environment, will be presented. In addition, insight will be given as to how development gets elevated to CPPP-supported status, the pre-cursor to broad availability and use within operational NWP. An overview of how the GMTB can be expanded to support other global or regional modeling capabilities will also be presented.

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

PubMed Central

Paley, Suzanne M.; Krummenacker, Markus; Latendresse, Mario; Dale, Joseph M.; Lee, Thomas J.; Kaipa, Pallavi; Gilham, Fred; Spaulding, Aaron; Popescu, Liviu; Altman, Tomer; Paulsen, Ian; Keseler, Ingrid M.; Caspi, Ron

2010-01-01

Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry. PMID:19955237

Overview of the Aeroelastic Prediction Workshop

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel; Florance, Jennifer P.; Wieseman, Carol D.; Schuster, David M.; Perry, Raleigh B.

2013-01-01

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.

Overview and Summary of the Second AIAA High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Slotnick, Jeffrey P.

2014-01-01

The second AIAA CFD High-Lift Prediction Workshop was held in San Diego, California, in June 2013. The goals of the workshop continued in the tradition of the first high-lift workshop: to assess the numerical prediction capability of current-generation computational fluid dynamics (CFD) technology for swept, medium/high-aspect-ratio wings in landing/takeoff (high-lift) configurations. This workshop analyzed the flow over the DLR-F11 model in landing configuration at two different Reynolds numbers. Twenty-six participants submitted a total of 48 data sets of CFD results. A variety of grid systems (both structured and unstructured) were used. Trends due to grid density and Reynolds number were analyzed, and effects of support brackets were also included. This paper analyzes the combined results from all workshop participants. Comparisons with experimental data are made. A statistical summary of the CFD results is also included.

Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software.

PubMed

Peach, Megan L; Zakharov, Alexey V; Liu, Ruifeng; Pugliese, Angelo; Tawa, Gregory; Wallqvist, Anders; Nicklaus, Marc C

2012-10-01

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

State-of-the-Art Review on Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development.

PubMed

Yellepeddi, Venkata; Rower, Joseph; Liu, Xiaoxi; Kumar, Shaun; Rashid, Jahidur; Sherwin, Catherine M T

2018-05-18

Physiologically based pharmacokinetic modeling and simulation is an important tool for predicting the pharmacokinetics, pharmacodynamics, and safety of drugs in pediatrics. Physiologically based pharmacokinetic modeling is applied in pediatric drug development for first-time-in-pediatric dose selection, simulation-based trial design, correlation with target organ toxicities, risk assessment by investigating possible drug-drug interactions, real-time assessment of pharmacokinetic-safety relationships, and assessment of non-systemic biodistribution targets. This review summarizes the details of a physiologically based pharmacokinetic modeling approach in pediatric drug research, emphasizing reports on pediatric physiologically based pharmacokinetic models of individual drugs. We also compare and contrast the strategies employed by various researchers in pediatric physiologically based pharmacokinetic modeling and provide a comprehensive overview of physiologically based pharmacokinetic modeling strategies and approaches in pediatrics. We discuss the impact of physiologically based pharmacokinetic models on regulatory reviews and product labels in the field of pediatric pharmacotherapy. Additionally, we examine in detail the current limitations and future directions of physiologically based pharmacokinetic modeling in pediatrics with regard to the ability to predict plasma concentrations and pharmacokinetic parameters. Despite the skepticism and concern in the pediatric community about the reliability of physiologically based pharmacokinetic models, there is substantial evidence that pediatric physiologically based pharmacokinetic models have been used successfully to predict differences in pharmacokinetics between adults and children for several drugs. It is obvious that the use of physiologically based pharmacokinetic modeling to support various stages of pediatric drug development is highly attractive and will rapidly increase, provided the robustness and reliability of these techniques are well established.

A Drought Cyberinfrastructure System for Improving Water Resource Management and Policy Making

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir

2015-04-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness, management, and response decision making. This presentation provides an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using both remote sensing observations and model simulations. Designed as a cyberinfrastructure system, GIDMaPS provides drought information based on a wide range of model simulations and satellite observations from different space agencies. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts, and better management and distribution of water resources among and across different users. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is designed to provide drought information for water resource management, and short-term decision making. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The presentation will highlight how this drought cyberinfrastructure system can be used to improve water resource management in California. Furthermore, the presentation provides an overview of the information farmers need for better decision making and how GIDMaPS can be used to improve decision making and reducing drought impacts. Further Reading Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1. Momtaz F., Nakhjiri N., AghaKouchak A., 2014, Toward a Drought Cyberinfrastructure System, Eos, Transactions American Geophysical Union, 95(22), 182-183, doi:10.1002/2014EO220002. AghaKouchak A., 2014, A Baseline Probabilistic Drought Forecasting Framework Using Standardized Soil Moisture Index: Application to the 2012 United States Drought, Hydrology and Earth System Sciences, 18, 2485-2492, doi: 10.5194/hess-18-2485-2014.

The SAMPL4 host-guest blind prediction challenge: an overview.

PubMed

Muddana, Hari S; Fenley, Andrew T; Mobley, David L; Gilson, Michael K

2014-04-01

Prospective validation of methods for computing binding affinities can help assess their predictive power and thus set reasonable expectations for their performance in drug design applications. Supramolecular host-guest systems are excellent model systems for testing such affinity prediction methods, because their small size and limited conformational flexibility, relative to proteins, allows higher throughput and better numerical convergence. The SAMPL4 prediction challenge therefore included a series of host-guest systems, based on two hosts, cucurbit[7]uril and octa-acid. Binding affinities in aqueous solution were measured experimentally for a total of 23 guest molecules. Participants submitted 35 sets of computational predictions for these host-guest systems, based on methods ranging from simple docking, to extensive free energy simulations, to quantum mechanical calculations. Over half of the predictions provided better correlations with experiment than two simple null models, but most methods underperformed the null models in terms of root mean squared error and linear regression slope. Interestingly, the overall performance across all SAMPL4 submissions was similar to that for the prior SAMPL3 host-guest challenge, although the experimentalists took steps to simplify the current challenge. While some methods performed fairly consistently across both hosts, no single approach emerged as consistent top performer, and the nonsystematic nature of the various submissions made it impossible to draw definitive conclusions regarding the best choices of energy models or sampling algorithms. Salt effects emerged as an issue in the calculation of absolute binding affinities of cucurbit[7]uril-guest systems, but were not expected to affect the relative affinities significantly. Useful directions for future rounds of the challenge might involve encouraging participants to carry out some calculations that replicate each others' studies, and to systematically explore parameter options.

High-Fidelity Multi-Rotor Unmanned Aircraft System Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

NASA Technical Reports Server (NTRS)

Foster, John V.; Hartman, David C.

2017-01-01

The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.

Static Properties of Fibre Metal Laminates

NASA Astrophysics Data System (ADS)

Hagenbeek, M.; van Hengel, C.; Bosker, O. J.; Vermeeren, C. A. J. R.

2003-07-01

In this article a brief overview of the static properties of Fibre Metal Laminates is given. Starting with the stress-strain relation, an effective calculation tool for uniaxial stress-strain curves is given. The method is valid for all Glare types. The Norris failure model is described in combination with a Metal Volume Fraction approach leading to a useful tool to predict allowable blunt notch strength. The Volume Fraction approach is also useful in the case of the shear yield strength of Fibre Metal Laminates. With the use of the Iosipescu test shear yield properties are measured.

Ceramic thermal barrier coatings for commercial gas turbine engines

NASA Technical Reports Server (NTRS)

Meier, Susan Manning; Gupta, Dinesh K.; Sheffler, Keith D.

1991-01-01

The paper provides an overview of the short history, current status, and future prospects of ceramic thermal barrier coatings for gas turbine engines. Particular attention is given to plasma-sprayed and electron beam-physical vapor deposited yttria-stabilized (7 wt pct Y2O3) zirconia systems. Recent advances include improvements in the spallation life of thermal barrier coatings, improved bond coat composition and spraying techniques, and improved component design. The discussion also covers field experience, life prediction modeling, and future directions in ceramic coatings in relation to gas turbine engine design.

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.

Modelling the molecular mechanisms of aging

PubMed Central

Mc Auley, Mark T.; Guimera, Alvaro Martinez; Hodgson, David; Mcdonald, Neil; Mooney, Kathleen M.; Morgan, Amy E.

2017-01-01

The aging process is driven at the cellular level by random molecular damage that slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the aging process. The complexity of the aging process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards and discusses many specific examples of models that have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field. PMID:28096317

System-level modeling of acetone-butanol-ethanol fermentation.

PubMed

Liao, Chen; Seo, Seung-Oh; Lu, Ting

2016-05-01

Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Prospects for development of unified global flood observation and prediction systems (Invited)

NASA Astrophysics Data System (ADS)

Lettenmaier, D. P.

2013-12-01

Floods are among the most damaging of natural hazards, with global flood losses in 2011 alone estimated to have exceeded $100B. Historically, flood economic damages have been highest in the developed world (due in part to encroachment on historical flood plains), but loss of life, and human impacts have been greatest in the developing world. However, as the 2011 Thailand floods show, industrializing countries, many of which do not have well developed flood protection systems, are increasingly vulnerable to economic damages as they become more industrialized. At present, unified global flood observation and prediction systems are in their infancy; notwithstanding that global weather forecasting is a mature field. The summary for this session identifies two evolving capabilities that hold promise for development of more sophisticated global flood forecast systems: global hydrologic models and satellite remote sensing (primarily of precipitation, but also of flood inundation). To this I would add the increasing sophistication and accuracy of global precipitation analysis (and forecast) fields from numerical weather prediction models. In this brief overview, I will review progress in all three areas, and especially the evolution of hydrologic data assimilation which integrates modeling and data sources. I will also comment on inter-governmental and inter-agency cooperation, and related issues that have impeded progress in the development and utilization of global flood observation and prediction systems.

Feedback control of an electrorheological long-stroke vibration damper

NASA Astrophysics Data System (ADS)

Sims, Neil D.; Stanway, Roger; Johnson, Andrew R.; Peel, David J.; Bullough, William A.

1999-06-01

It is widely acknowledged that the inherent non-linearity of smart fluid dampers is inhibiting the development of effective control regimes, and mass-production devices. In an earlier publication, an innovative solution to this problem was presented -- using a simple feedback control strategy to linearize the response. The study used a quasi-steady model of a long-stroke Electrorheological damper, and showed how proportional feedback control could linearize the simulated response. However, this initial research did not consider the dynamics of the damper's behavior, and so the development of a more advanced model has been necessary. In this article, the authors present an extension to this earlier study, using a model of the damper's response that is capable of accurately predicting the dynamic response of the damper. To introduce the topic, the electrorheological long-stroke damper test rig is described, and an overview of the earlier study is given. The advanced model is then derived, and its predictions are compared to experimental data from the test rig. This model is then incorporated into the feedback control simulations, and it is shown how the control strategy is still able to linearize the response in simulations.

Modeling listeners' emotional response to music.

PubMed

Eerola, Tuomas

2012-10-01

An overview of the computational prediction of emotional responses to music is presented. Communication of emotions by music has received a great deal of attention during the last years and a large number of empirical studies have described the role of individual features (tempo, mode, articulation, timbre) in predicting the emotions suggested or invoked by the music. However, unlike the present work, relatively few studies have attempted to model continua of expressed emotions using a variety of musical features from audio-based representations in a correlation design. The construction of the computational model is divided into four separate phases, with a different focus for evaluation. These phases include the theoretical selection of relevant features, empirical assessment of feature validity, actual feature selection, and overall evaluation of the model. Existing research on music and emotions and extraction of musical features is reviewed in terms of these criteria. Examples drawn from recent studies of emotions within the context of film soundtracks are used to demonstrate each phase in the construction of the model. These models are able to explain the dominant part of the listeners' self-reports of the emotions expressed by music and the models show potential to generalize over different genres within Western music. Possible applications of the computational models of emotions are discussed. Copyright © 2012 Cognitive Science Society, Inc.

On Winning the Race for Predicting the Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Goswami, Bhupendra

2013-03-01

Skillful prediction of Indian summer monsoon rainfall (ISMR) one season in advance remains a ``grand challenge'' for the climate science community even though such forecasts have tremendous socio-economic implications over the region. Continued poor skill of the ocean-atmosphere coupled models in predicting ISMR is an enigma in the backdrop when these models have high skill in predicting seasonal mean rainfall over the rest of the Tropics. Here, I provide an overview of the fundamental processes responsible for limited skill of climate models and outline a framework for achieving the limit on potential predictability within a reasonable time frame. I also show that monsoon intra-seasonal oscillations (MISO) act as building blocks of the Asian monsoon and provide a bridge between the two problems, the potential predictability limit and the simulation of seasonal mean climate. The correlation between observed ISMR and ensemble mean of predicted ISMR (R) can still be used as a metric for forecast verification. Estimate of potential limit of predictability of Asian monsoon indicates that the highest achievable R is about 0.75. Improvements in climate models and data assimilation over the past one decade has slowly improved R from near zero a decade ago to about 0.4 currently. The race for achieving useful prediction can be won, if we can push this skill up to about 0.7. It requires focused research in improving simulations of MISO, monsoon seasonal cycle and ENSO-monsoon relationship by the climate models. In order to achieve this goal by 2015-16 timeframe, IITM is leading a Program called Monsoon Mission supported by the Ministry of Earth Sciences, Govt. of India (MoES). As improvement in skill of forecasts can come only if R & D is carried out on an operational modeling system, the Climate Forecast System of National Centre for Environmental Prediction (NCEP) of NOAA, U.S.A has been selected as our base system. The Mission envisages building partnership between operational forecasting agency and National and International R & D Organizations to work on improving modeling system. MoES has provided substantial funding to the Mission to fund proposals from International R & D Organizations to work with Indian Organizations in this Mission to achieve this goal. The conceptual framework and the roadmap for the Mission will be highlighted. Indian Institute of Tropical Meteorology is funded by Ministry of Earth Sciences, Govt. of India.

Atmospheric Constituents in GEOS-5: Components for an Earth System Model

NASA Technical Reports Server (NTRS)

Pawson, Steven; Douglass, Anne; Duncan, Bryan; Nielsen, Eric; Ott, Leslie; Strode, Sarah

2011-01-01

The GEOS-S model is being developed for weather and climate processes, including the implementation of "Earth System" components. While the stratospheric chemistry capabilities are mature, we are presently extending this to include predictions of the tropospheric composition and chemistry - this includes CO2, CH4, CO, nitrogen species, etc. (Aerosols are also implemented, but are beyond the scope of this paper.) This work will give an overview of our chemistry modules, the approaches taken to represent surface emissions and uptake of chemical species, and some studies of the sensitivity of the atmospheric circulation to changes in atmospheric composition. Results are obtained through focused experiments and multi-decadal simulations.

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.

Reason and reaction: the utility of a dual-focus, dual-processing perspective on promotion and prevention of adolescent health risk behaviour.

PubMed

Gibbons, Frederick X; Houlihan, Amy E; Gerrard, Meg

2009-05-01

A brief overview of theories of health behaviour that are based on the expectancy-value perspective is presented. This approach maintains that health behaviours are the result of a deliberative decision-making process that involves consideration of behavioural options along with anticipated outcomes associated with those options. It is argued that this perspective is effective at explaining and predicting many types of health behaviour, including health-promoting actions (e.g. UV protection, condom use, smoking cessation), but less effective at predicting risky health behaviours, such as unprotected, casual sex, drunk driving or binge drinking. These are behaviours that are less reasoned or premeditated - especially among adolescents. An argument is made for incorporating elements of dual-processing theories in an effort to improve the 'utility' of these models. Specifically, it is suggested that adolescent health behaviour involves both analytic and heuristic processing. Both types of processing are incorporated in the prototype-willingness (prototype) model, which is described in some detail. Studies of health behaviour based on the expectancy-value perspective (e.g. theory of reasoned action) are reviewed, along with studies based on the prototype model. These two sets of studies together suggest that the dual-processing perspective, in general, and the prototype model, in particular, add to the predictive validity of expectancy-value models for predicting adolescent health behaviour. Research and interventions that incorporate elements of dual-processing and elements of expectancy-value are more effective at explaining and changing adolescent health behaviour than are those based on expectancy-value theories alone.

Predictive Engineering Implementation at KSC

NASA Technical Reports Server (NTRS)

Mosconi, Jane; Schafer, Loraine

1995-01-01

This paper provides an overview of what the primary contractors at Kennedy Space Center (KSC) are doing in the field of predictive engineering. The technologies employed by each of the contractors and the cost savings associated with the implementation of these predictive engineering methods are discussed. The sources include predictive engineering implementation plans, published by each of the contractors and interviews with the authors of these implementation plans.

Characterizing Dark Energy Through Supernovae

NASA Astrophysics Data System (ADS)

Davis, Tamara M.; Parkinson, David

Type Ia supernovae are a powerful cosmological probe that gave the first strong evidence that the expansion of the universe is accelerating. Here we provide an overview of how supernovae can go further to reveal information about what is causing the acceleration, be it dark energy or some modification to our laws of gravity. We first review the methods of statistical inference that are commonly used, making a point of separating parameter estimation from model selection. We then summarize the many different approaches used to explain or test the acceleration, including parametric models (like the standard model, ΛCDM), nonparametric models, dark fluid models such as quintessence, and extensions to standard gravity. Finally, we also show how supernova data can be used beyond the Hubble diagram, to give information on gravitational lensing and peculiar velocities that can be used to distinguish between models that predict the same expansion history.

An Overview of Depression among Transgender Women

PubMed Central

2014-01-01

Rates of depression are higher in transgender women than in the general population, warranting an understanding of the variables related to depression in this group. Results of the literature review of depression in transgender women reveal several variables influencing depression, including social support, violence, sex work, and gender identity. The theoretical constructs of minority stress, coping, and identity control theory are explored in terms of how they may predict depression in transgender women. Depression and depressive symptoms have been used to predict high-risk sexual behaviors with mixed results. The implications of the findings on treating depression in transgender women include taking into account the stress of transition and the importance of supportive peers and family. Future studies should explore a model of depression and high-risk behaviors in transgender women. PMID:24744918

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.

Parallel Grand Canonical Monte Carlo (ParaGrandMC) Simulation Code

NASA Technical Reports Server (NTRS)

Yamakov, Vesselin I.

2016-01-01

This report provides an overview of the Parallel Grand Canonical Monte Carlo (ParaGrandMC) simulation code. This is a highly scalable parallel FORTRAN code for simulating the thermodynamic evolution of metal alloy systems at the atomic level, and predicting the thermodynamic state, phase diagram, chemical composition and mechanical properties. The code is designed to simulate multi-component alloy systems, predict solid-state phase transformations such as austenite-martensite transformations, precipitate formation, recrystallization, capillary effects at interfaces, surface absorption, etc., which can aid the design of novel metallic alloys. While the software is mainly tailored for modeling metal alloys, it can also be used for other types of solid-state systems, and to some degree for liquid or gaseous systems, including multiphase systems forming solid-liquid-gas interfaces.

An Overview of Ecological Modeling and Machine Learning Research Within the U.S. National Aeronautics and Space Administration

NASA Technical Reports Server (NTRS)

Coughlan, Joseph C.

2004-01-01

In the early 1980 s NASA began research to understand global habitability and quantify the processes and fluxes between the Earth's vegetation and the biosphere. This effort evolved into the Earth Observing System Program which current encompasses 18 platforms and 80 sensors. During this time, the global environmental research community has evolved from a data poor to a data rich research area and is challenged to provide timely use of these new data. This talk will outline some of the data mining research NASA has funded in support for the environmental sciences in the Intelligent Systems project and will give a specific example in ecological forecasting, predicting the land surface properties given nowcasts and weather forecasts, using the Terrestrial Observation and Prediction System (TOPS).

Dynamics and rheology of finitely extensible polymer coils: An overview

NASA Astrophysics Data System (ADS)

Yao, Donggang

2017-05-01

One contemporary research issue in non-Newtonian fluid mechanics is to accurately and effectively model viscoelastic polymer flow of practical relevance. In the past several years, we have been working on the formulation of a finitely extensible coil model for polymer flow, particularly including these elements: (1) decoupled equations for kinematical and dynamical variables, (2) logarithmic relaxation at large deformation, (3) rotational retardation, (4) controllable straining, and (5) finite stretch. In this paper, we provide a constructive overview of this nonlinear coil formulation focusing on integration of these elements in a single, unified constitutive model with a minimal number of model parameters that are linked with corresponding physical processes. We also use this opportunity to share the rationale and thought process in the model development. In one particular implement of the general formulation, three parameters are used to tackle with the principal dynamics of a deforming polymer coil: one for finite stretch dictated by a ceiling stretch of the coil, the second one for rotational recovery/retardation, and the third one for adjusting stretch hardening of the rubbery coil. The new model, even in a single mode, is able to simultaneously predict practical material functions in simple shear and coaxial extension and to fit well to representative experimental data. Particularly in the steady-state (or quasi-steady state) flow case, a nearly closed-form stress to velocity gradient relationship can be derived with which shear thinning and elongational thickening can be simultaneously considered while computational advantages of a classical GNF model is retained. The model also fits reasonably well to representative experimental transient data for both shear and extension.

Overview: What's Worked and What Hasn't as a Guide towards Predictive Admissions Tool Development

ERIC Educational Resources Information Center

Siu, Eric; Reiter, Harold I.

2009-01-01

Admissions committees and researchers around the globe have used diligence and imagination to develop and implement various screening measures with the ultimate goal of predicting future clinical and professional performance. What works for predicting future job performance in the human resources world and in most of the academic world may not,…

Measurement of the Rheological Properties of High Performance Concrete: State of the Art Report

PubMed Central

Ferraris, Chiara F.

1999-01-01

The rheological or flow properties of concrete in general and of high performance concrete (HPC) in particular, are important because many factors such as ease of placement, consolidation, durability, and strength depend on the flow properties. Concrete that is not properly consolidated may have defects, such as honeycombs, air voids, and aggregate segregation. Such an important performance attribute has triggered the design of numerous test methods. Generally, the flow behavior of concrete approximates that of a Bingham fluid. Therefore, at least two parameters, yield stress and viscosity, are necessary to characterize the flow. Nevertheless, most methods measure only one parameter. Predictions of the flow properties of concrete from its composition or from the properties of its components are not easy. No general model exists, although some attempts have been made. This paper gives an overview of the flow properties of a fluid or a suspension, followed by a critical review of the most commonly used concrete rheology tests. Particular attention is given to tests that could be used for HPC. Tentative definitions of terms such as workability, consistency, and rheological parameters are provided. An overview of the most promising tests and models for cement paste is given.

Resource Letter MPCVW-1: Modeling Political Conflict, Violence, and Wars: A Survey

NASA Astrophysics Data System (ADS)

Morgenstern, Ana P.; Velásquez, Nicolás; Manrique, Pedro; Hong, Qi; Johnson, Nicholas; Johnson, Neil

2013-11-01

This Resource Letter provides a guide into the literature on modeling and explaining political conflict, violence, and wars. Although this literature is dominated by social scientists, multidisciplinary work is currently being developed in the wake of myriad methodological approaches that have sought to analyze and predict political violence. The works covered herein present an overview of this abundance of methodological approaches. Since there is a variety of possible data sets and theoretical approaches, the level of detail and scope of models can vary quite considerably. The review does not provide a summary of the available data sets, but instead highlights recent works on quantitative or multi-method approaches to modeling different forms of political violence. Journal articles and books are organized in the following topics: social movements, diffusion of social movements, political violence, insurgencies and terrorism, and civil wars.

Prediction of the articular eminence shape in a patient with unilateral hypoplasia of the right mandibular ramus before and after distraction osteogenesis-A simulation study.

PubMed

de Zee, Mark; Cattaneo, Paolo M; Svensson, Peter; Pedersen, Thomas K; Melsen, Birte; Rasmussen, John; Dalstra, Michel

2009-05-29

The aim of this work was to predict the shape of the articular eminence in a patient with unilateral hypoplasia of the right mandibular ramus before and after distraction osteogenesis (DO). Using a patient-specific musculoskeletal model of the mandible the hypothesis that the observed differences in this patient in the left and right articular eminence inclinations were consistent with minimisation of joint loads was tested. Moreover, a prediction was made of the final shape of the articular eminence after DO when the expected remodelling has reached a steady state. The individual muscle forces and the average TMJ loading were computed for each combination of articular eminence angles both before and after DO. This exhaustive parameter study provides a full overview of average TMJ loading depending on the angles of the articular eminences. Before DO the parameter study resulted in different articular eminence inclinations between left and right sides consistent with patient data obtained from CT scans, indicating that in this patient the articular eminence shapes result from minimisation of joint loads. The simulation model predicts development of almost equal articular eminence shapes after DO. The same tendency was observed in cone beam CT scans (NewTom) of the patient taken 6.5 years after surgery.

Modeling and simulation of a direct ethanol fuel cell: An overview

NASA Astrophysics Data System (ADS)

Abdullah, S.; Kamarudin, S. K.; Hasran, U. A.; Masdar, M. S.; Daud, W. R. W.

2014-09-01

The commercialization of Direct Ethanol Fuel Cells (DEFCs) is still hindered because of economic and technical reasons. Fundamental scientific research is required to more completely understanding the complex electrochemical behavior and engineering technology of DEFCs. To use the DEFC system in real-world applications, fast, reliable, and cost-effective methods are needed to explore this complex phenomenon and to predict the performance of different system designs. Thus, modeling and simulation play an important role in examining the DEFC system as well as in designing an optimized DEFC system. The current DEFC literature shows that modeling studies on DEFCs are still in their early stages and are not able to describe the DEFC system as a whole. Potential DEFC applications and their current status are also presented.

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.

7Be(p,gamma)8B S-factor from Ab Initio Wave Functions

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

Navratil, P; Bertulani, C A; Caurier, E

2006-10-12

There has been a significant progress in ab initio approaches to the structure of light nuclei. Starting from realistic two- and three-nucleon interactions the ab initio no-core shell model (NCSM) predicts low-lying levels in p-shell nuclei. It is a challenging task to extend ab initio methods to describe nuclear reactions. We present here a brief overview of the first steps taken toward nuclear reaction applications. In particular, we discuss our calculation of the {sup 7}Be(p,{gamma}){sup 8}B S-factor. We also present our first results of the {sup 3}He({alpha},{gamma}){sup 7}Be S-factor and of the S-factor of the mirror reaction {sup 3}H({alpha},{gamma}){sup 7}Li.more » The {sup 7}Be(p,{gamma}){sup 8}B and {sup 3}He({alpha},{gamma}){sup 7}Be reactions correspond to the most important uncertainties in solar model predictions of neutrino fluxes.« less

The Adaptation of the Immigrant Second Generation in America: Theoretical Overview and Recent Evidence

PubMed Central

Portes, Alejandro; Fernández-Kelly, Patricia; Haller, William

2013-01-01

This paper summarises a research program on the new immigrant second generation initiated in the early 1990s and completed in 2006. The four field waves of the Children of Immigrants Longitudinal Study (CILS) are described and the main theoretical models emerging from it are presented and graphically summarised. After considering critical views of this theory, we present the most recent results from this longitudinal research program in the forum of quantitative models predicting downward assimilation in early adulthood and qualitative interviews identifying ways to escape it by disadvantaged children of immigrants. Quantitative results strongly support the predicted effects of exogenous variables identified by segmented assimilation theory and identify the intervening factors during adolescence that mediate their influence on adult outcomes. Qualitative evidence gathered during the last stage of the study points to three factors that can lead to exceptional educational achievement among disadvantaged youths. All three indicate the positive influence of selective acculturation. Implications of these findings for theory and policy are discussed. PMID:23626483

Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers

NASA Astrophysics Data System (ADS)

Landgrebe, Anton J.

1987-03-01

An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.

Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers

NASA Technical Reports Server (NTRS)

Landgrebe, Anton J.

1987-01-01

An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.

Miniaturized pre-clinical cancer models as research and diagnostic tools

PubMed Central

Håkanson, Maria; Cukierman, Edna; Charnley, Mirren

2014-01-01

Cancer is one of the most common causes of death worldwide. Consequently, important resources are directed towards bettering treatments and outcomes. Cancer is difficult to treat due to its heterogeneity, plasticity and frequent drug resistance. New treatment strategies should strive for personalized approaches. These should target neoplastic and/or activated microenvironmental heterogeneity and plasticity without triggering resistance and spare host cells. In this review, the putative use of increasingly physiologically relevant microfabricated cell-culturing systems intended for drug development is discussed. There are two main reasons for the use of miniaturized systems. First, scaling down model size allows for high control of microenvironmental cues enabling more predictive outcomes. Second, miniaturization reduces reagent consumption, thus facilitating combinatorial approaches with little effort and enables the application of scarce materials, such as patient-derived samples. This review aims to give an overview of the state-of-the-art of such systems while predicting their application in cancer drug development. PMID:24295904

Observing Clonal Dynamics across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer.

PubMed

McPherson, Andrew W; Chan, Fong Chun; Shah, Sohrab P

2018-02-01

The ability to accurately model evolutionary dynamics in cancer would allow for prediction of progression and response to therapy. As a prelude to quantitative understanding of evolutionary dynamics, researchers must gather observations of in vivo tumor evolution. High-throughput genome sequencing now provides the means to profile the mutational content of evolving tumor clones from patient biopsies. Together with the development of models of tumor evolution, reconstructing evolutionary histories of individual tumors generates hypotheses about the dynamics of evolution that produced the observed clones. In this review, we provide a brief overview of the concepts involved in predicting evolutionary histories, and provide a workflow based on bulk and targeted-genome sequencing. We then describe the application of this workflow to time series data obtained for transformed and progressed follicular lymphomas (FL), and contrast the observed evolutionary dynamics between these two subtypes. We next describe results from a spatial sampling study of high-grade serous (HGS) ovarian cancer, propose mechanisms of disease spread based on the observed clonal mixtures, and provide examples of diversification through subclonal acquisition of driver mutations and convergent evolution. Finally, we state implications of the techniques discussed in this review as a necessary but insufficient step on the path to predictive modelling of disease dynamics. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

PubMed

Hessel, Ellen V S; Staal, Yvonne C M; Piersma, Aldert H

2018-03-13

Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies provide only limited information as to human relevance. A multitude of alternative models have been developed over the years, providing insights into mechanisms of action. We give an overview of fundamental processes in neural tube formation, brain development and neural specification, aiming at illustrating complexity rather than comprehensiveness. We also give a flavor of the wealth of alternative methods in this area. Given the impressive progress in mechanistic knowledge of human biology and toxicology, the time is right for a conceptual approach for designing testing strategies that cover the integral mechanistic landscape of developmental neurotoxicity. The ontology approach provides a framework for defining this landscape, upon which an integral in silico model for predicting toxicity can be built. It subsequently directs the selection of in vitro assays for rate-limiting events in the biological network, to feed parameter tuning in the model, leading to prediction of the toxicological outcome. Validation of such models requires primary attention to coverage of the biological domain, rather than classical predictive value of individual tests. Proofs of concept for such an approach are already available. The challenge is in mining modern biology, toxicology and chemical information to feed intelligent designs, which will define testing strategies for neurodevelopmental toxicity testing. Copyright © 2018 Elsevier Inc. All rights reserved.

New tendencies in wildland fire simulation for understanding fire phenomena: An overview of the WFDS system capabilities in Mediterranean ecosystems

NASA Astrophysics Data System (ADS)

Pastor, E.; Tarragó, D.; Planas, E.

2012-04-01

Wildfire theoretical modeling endeavors predicting fire behavior characteristics, such as the rate of spread, the flames geometry and the energy released by the fire front by applying the physics and the chemistry laws that govern fire phenomena. Its ultimate aim is to help fire managers to improve fire prevention and suppression and hence reducing damage to population and protecting ecosystems. WFDS is a 3D computational fluid dynamics (CFD) model of a fire-driven flow. It is particularly appropriate for predicting the fire behaviour burning through the wildland-urban interface, since it is able to predict the fire behaviour in the intermix of vegetative and structural fuels that comprise the wildland urban interface. This model is not suitable for operational fire management yet due to computational costs constrains, but given the fact that it is open-source and that it has a detailed description of the fuels and of the combustion and heat transfer mechanisms it is currently a suitable system for research purposes. In this paper we present the most important characteristics of the WFDS simulation tool in terms of the models implemented, the input information required and the outputs that the simulator gives useful for understanding fire phenomena. We briefly discuss its advantages and opportunities through some simulation exercises of Mediterranean ecosystems.

Overview of the SAMPL5 host–guest challenge: Are we doing better?

PubMed Central

Yin, Jian; Henriksen, Niel M.; Slochower, David R.; Shirts, Michael R.; Chiu, Michael W.; Mobley, David L.; Gilson, Michael K.

2016-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein–ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host–guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host–guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host–guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements. PMID:27658802

Overview of the SAMPL5 host-guest challenge: Are we doing better?

PubMed

Yin, Jian; Henriksen, Niel M; Slochower, David R; Shirts, Michael R; Chiu, Michael W; Mobley, David L; Gilson, Michael K

2017-01-01

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein-ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host-guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host-guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host-guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements.

An Overview of Numerical Weather Prediction on Various Scales

NASA Astrophysics Data System (ADS)

Bao, J.-W.

2009-04-01

The increasing public need for detailed weather forecasts, along with the advances in computer technology, has motivated many research institutes and national weather forecasting centers to develop and run global as well as regional numerical weather prediction (NWP) models at high resolutions (i.e., with horizontal resolutions of ~10 km or higher for global models and 1 km or higher for regional models, and with ~60 vertical levels or higher). The need for running NWP models at high horizontal and vertical resolutions requires the implementation of non-hydrostatic dynamic core with a choice of horizontal grid configurations and vertical coordinates that are appropriate for high resolutions. Development of advanced numerics will also be needed for high resolution global and regional models, in particular, when the models are applied to transport problems and air quality applications. In addition to the challenges in numerics, the NWP community is also facing the challenges of developing physics parameterizations that are well suited for high-resolution NWP models. For example, when NWP models are run at resolutions of ~5 km or higher, the use of much more detailed microphysics parameterizations than those currently used in NWP model will become important. Another example is that regional NWP models at ~1 km or higher only partially resolve convective energy containing eddies in the lower troposphere. Parameterizations to account for the subgrid diffusion associated with unresolved turbulence still need to be developed. Further, physically sound parameterizations for air-sea interaction will be a critical component for tropical NWP models, particularly for hurricane predictions models. In this review presentation, the above issues will be elaborated on and the approaches to address them will be discussed.

Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

NASA Technical Reports Server (NTRS)

Wilson, Scott D.; Reid, Terry V.; Schifer, Nicholas A.; Briggs, Maxwell H.

2012-01-01

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using specially designed test hardware enabling measurement of heat transferred through a simulated Stirling cycle. The overall effort and results are discussed.

Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software

PubMed Central

Peach, Megan L; Zakharov, Alexey V; Liu, Ruifeng; Pugliese, Angelo; Tawa, Gregory; Wallqvist, Anders; Nicklaus, Marc C

2014-01-01

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely. PMID:23088273

Stream dynamics: An overview for land managers

Treesearch

Burchard H. Heede

1980-01-01

Concepts of stream dynamics are demonstrated through discussion of processes and process indicators; theory is included only where helpful to explain concepts. Present knowledge allows only qualitative prediction of stream behavior. However, such predictions show how management actions will affect the stream and its environment.

A Vision and Strategy:Predictive Ecotoxicology in the 21st Century

EPA Science Inventory

The manuscript provides an introduction and overview for a series of five papers resulting from a SETAC Pellston Workshop titled A Vision and Strategy for Predictive Ecotoxicology in the 21st Century: Defining Adverse Outcome Pathways Associated with Ecological Risk. It proposes...

On the Tropical Rainfall Measuring Mission (TRMM): Bringing NASA's Earth System Science Program to the Classroom

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall

1998-01-01

The Tropical Rainfall Measuring Mission is the first mission dedicated to measuring tropical and subtropical rainfall using a variety of remote sensing instrumentation, including the first spaceborne rain-measuring radar. Since the energy released when tropical rainfall occurs is a primary "fuel" supply for the weather and climate "engine"; improvements in computer models which predict future weather and climate states may depend on better measurements of global tropical rainfall and its energy. In support of the STANYS conference theme of Education and Space, this presentation focuses on one aspect of NASA's Earth Systems Science Program. We seek to present an overview of the TRMM mission. This overview will discuss the scientific motivation for TRMM, the TRMM instrument package, and recent images from tropical rainfall systems and hurricanes. The presentation also targets educational components of the TRMM mission in the areas of weather, mathematics, technology, and geography that can be used by secondary school/high school educators in the classroom.

EarthCARE mission, overview, implementation approach and development status

NASA Astrophysics Data System (ADS)

Lefebvre, Alain; Hélière, Arnaud; Pérez Albiñana, Abelardo; Wallace, Kotska; Maeusli, Damien; Lemanczyk, Jerzy; Lusteau, Cyrille; Nakatsuka, Hirotaka; Tomita, Eiichi

2016-05-01

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are co-operating to develop the EarthCARE satellite mission with the fundamental objective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth's atmosphere in order to include them correctly and reliably in climate and numerical weather prediction models. The satellite will be placed in a Sun-Synchronous Orbit at about 400 Km altitude and14h00 mean local solar time. The payload consisting of a High Spectral Resolution UV Atmospheric LIDar (ATLID), a 94GHz Cloud Profiling Radar (CPR) with Doppler capability, a Multi-Spectral Imager (MSI) and a Broad-Band Radiometer will provide information on cloud and aerosol vertical structure of the atmosphere along the satellite track as well as information about the horizontal structures of clouds and radiant flux from sub-satellite cells. The presentation will cover the configuration of the satellite with its four instruments, the mission implementation approach, an overview of the ground segment and the overall mission development status.

Overview of the Martian radiation environment experiment

NASA Technical Reports Server (NTRS)

Zeitlin, C.; Cleghorn, T.; Cucinotta, F.; Saganti, P.; Andersen, V.; Lee, K.; Pinsky, L.; Atwell, W.; Turner, R.; Badhwar, G.

2004-01-01

Space radiation presents a hazard to astronauts, particularly those journeying outside the protective influence of the geomagnetosphere. Crews on future missions to Mars will be exposed to the harsh radiation environment of deep space during the transit between Earth and Mars. Once on Mars, they will encounter radiation that is only slightly reduced, compared to free space, by the thin Martian atmosphere. NASA is obliged to minimize, where possible, the radiation exposures received by astronauts. Thus, as a precursor to eventual human exploration, it is necessary to measure the Martian radiation environment in detail. The MARIE experiment, aboard the 2001 Mars Odyssey spacecraft, is returning the first data that bear directly on this problem. Here we provide an overview of the experiment, including introductory material on space radiation and radiation dosimetry, a description of the detector, model predictions of the radiation environment at Mars, and preliminary dose-rate data obtained at Mars. c2003 COSPAR. Published by Elsevier Ltd. All rights reserved.

Measurements of clothing evaporative resistance using a sweating thermal manikin: an overview

PubMed Central

WANG, Faming

2017-01-01

Evaporative resistance has been widely used to describe the evaporative heat transfer property of clothing. It is also a critical variable in heat stress models for predicting human physiological responses in various environmental conditions. At present, sweating thermal manikins provide a fast and cost-effective way to determine clothing evaporative resistance. Unfortunately, the measurement repeatability and reproducibility of evaporative resistance are rather low due to the complicated moisture transfer processes through clothing. This review article presents a systematical overview on major influential factors affecting the measurement precision of clothing evaporative resistance measurements. It also illustrates the state-of-the-art knowledge on the development of test protocol to measure clothing evaporative resistance by means of a sweating manikin. Some feasible and robust test procedures for measurement of clothing evaporative resistance using a sweating manikin are described. Recommendations on how to improve the measurement accuracy of clothing evaporative resistance are addressed and expected future trends on development of advanced sweating thermal manikins are finally presented. PMID:28566566

Acoustic Treatment Design Scaling Methods. Volume 1; Overview, Results, and Recommendations

NASA Technical Reports Server (NTRS)

Kraft, R. E.; Yu, J.

1999-01-01

Scale model fan rigs that simulate new generation ultra-high-bypass engines at about 1/5-scale are achieving increased importance as development vehicles for the design of low-noise aircraft engines. Testing at small scale allows the tests to be performed in existing anechoic wind tunnels, which provides an accurate simulation of the important effects of aircraft forward motion on the noise generation. The ability to design, build, and test miniaturized acoustic treatment panels on scale model fan rigs representative of the fullscale engine provides not only a cost-savings, but an opportunity to optimize the treatment by allowing tests of different designs. The primary objective of this study was to develop methods that will allow scale model fan rigs to be successfully used as acoustic treatment design tools. The study focuses on finding methods to extend the upper limit of the frequency range of impedance prediction models and acoustic impedance measurement methods for subscale treatment liner designs, and confirm the predictions by correlation with measured data. This phase of the program had as a goal doubling the upper limit of impedance measurement from 6 kHz to 12 kHz. The program utilizes combined analytical and experimental methods to achieve the objectives.

Puget Sound Operational Forecast System - A Real-time Predictive Tool for Marine Resource Management and Emergency Responses

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

Yang, Zhaoqing; Khangaonkar, Tarang; Chase, Jared M.

2009-12-01

To support marine ecological resource management and emergency response and to enhance scientific understanding of physical and biogeochemical processes in Puget Sound, a real-time Puget Sound Operational Forecast System (PS-OFS) was developed by the Coastal Ocean Dynamics & Ecosystem Modeling group (CODEM) of Pacific Northwest National Laboratory (PNNL). PS-OFS employs the state-of-the-art three-dimensional coastal ocean model and closely follows the standards and procedures established by National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). PS-OFS consists of four key components supporting the Puget Sound Circulation and Transport Model (PS-CTM): data acquisition, model execution and product archive, model skill assessment,more » and model results dissemination. This paper provides an overview of PS-OFS and its ability to provide vital real-time oceanographic information to the Puget Sound community. PS-OFS supports pacific northwest region’s growing need for a predictive tool to assist water quality management, fish stock recovery efforts, maritime emergency response, nearshore land-use planning, and the challenge of climate change and sea level rise impacts. The structure of PS-OFS and examples of the system inputs and outputs, forecast results are presented in details.« less

Health Management and Service Life for Air Force Missiles

DTIC Science & Technology

2011-09-26

prediction of performance will be conducted DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. PA# TBD 24 • Empiricism ...Strategic Missile A&S Approach Overview Empiricism DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. PA# TBD...Extrapolation Simulated Data 25 • Empiricism cannot always predict future state • Mechanistic method enables enhanced predictions • Mechanistic will not be

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.

ACTIVIS: Visual Exploration of Industry-Scale Deep Neural Network Models.

PubMed

Kahng, Minsuk; Andrews, Pierre Y; Kalro, Aditya; Polo Chau, Duen Horng

2017-08-30

While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ACTIVIS, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ACTIVIS has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ACTIVIS may work with different models.

Prediction of miRNA targets.

PubMed

Oulas, Anastasis; Karathanasis, Nestoras; Louloupi, Annita; Pavlopoulos, Georgios A; Poirazi, Panayiota; Kalantidis, Kriton; Iliopoulos, Ioannis

2015-01-01

Computational methods for miRNA target prediction are currently undergoing extensive review and evaluation. There is still a great need for improvement of these tools and bioinformatics approaches are looking towards high-throughput experiments in order to validate predictions. The combination of large-scale techniques with computational tools will not only provide greater credence to computational predictions but also lead to the better understanding of specific biological questions. Current miRNA target prediction tools utilize probabilistic learning algorithms, machine learning methods and even empirical biologically defined rules in order to build models based on experimentally verified miRNA targets. Large-scale protein downregulation assays and next-generation sequencing (NGS) are now being used to validate methodologies and compare the performance of existing tools. Tools that exhibit greater correlation between computational predictions and protein downregulation or RNA downregulation are considered the state of the art. Moreover, efficiency in prediction of miRNA targets that are concurrently verified experimentally provides additional validity to computational predictions and further highlights the competitive advantage of specific tools and their efficacy in extracting biologically significant results. In this review paper, we discuss the computational methods for miRNA target prediction and provide a detailed comparison of methodologies and features utilized by each specific tool. Moreover, we provide an overview of current state-of-the-art high-throughput methods used in miRNA target prediction.

Building confidence and credibility amid growing model and computing complexity

NASA Astrophysics Data System (ADS)

Evans, K. J.; Mahajan, S.; Veneziani, C.; Kennedy, J. H.

2017-12-01

As global Earth system models are developed to answer an ever-wider range of science questions, software products that provide robust verification, validation, and evaluation must evolve in tandem. Measuring the degree to which these new models capture past behavior, predict the future, and provide the certainty of predictions is becoming ever more challenging for reasons that are generally well known, yet are still challenging to address. Two specific and divergent needs for analysis of the Accelerated Climate Model for Energy (ACME) model - but with a similar software philosophy - are presented to show how a model developer-based focus can address analysis needs during expansive model changes to provide greater fidelity and execute on multi-petascale computing facilities. A-PRIME is a python script-based quick-look overview of a fully-coupled global model configuration to determine quickly if it captures specific behavior before significant computer time and expense is invested. EVE is an ensemble-based software framework that focuses on verification of performance-based ACME model development, such as compiler or machine settings, to determine the equivalence of relevant climate statistics. The challenges and solutions for analysis of multi-petabyte output data are highlighted from the aspect of the scientist using the software, with the aim of fostering discussion and further input from the community about improving developer confidence and community credibility.

An Overview of the National Weather Service National Water Model

NASA Astrophysics Data System (ADS)

Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Feng, X.; Karsten, L. R.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.

2016-12-01

The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research (NCAR) and the NWS National Centers for Environmental Prediction (NCEP) recently implemented version 1.0 of the National Water Model (NWM) into operations. This model is an hourly cycling uncoupled analysis and forecast system that provides streamflow for 2.7 million river reaches and other hydrologic information on 1km and 250m grids. It will provide complementary hydrologic guidance at current NWS river forecast locations and significantly expand guidance coverage and type in underserved locations. The core of this system is the NCAR-supported community Weather Research and Forecasting (WRF)-Hydro hydrologic model. It ingests forcing from a variety of sources including Multi-Sensor Multi-Radar (MRMS) radar-gauge observed precipitation data and High Resolution Rapid Refresh (HRRR), Rapid Refresh (RAP), Global Forecast System (GFS) and Climate Forecast System (CFS) forecast data. WRF-Hydro is configured to use the Noah-Multi Parameterization (Noah-MP) Land Surface Model (LSM) to simulate land surface processes. Separate water routing modules perform diffusive wave surface routing and saturated subsurface flow routing on a 250m grid, and Muskingum-Cunge channel routing down National Hydrogaphy Dataset Plus V2 (NHDPlusV2) stream reaches. River analyses and forecasts are provided across a domain encompassing the Continental United States (CONUS) and hydrologically contributing areas, while land surface output is available on a larger domain that extends beyond the CONUS into Canada and Mexico (roughly from latitude 19N to 58N). The system includes an analysis and assimilation configuration along with three forecast configurations. These include a short-range 15 hour deterministic forecast, a medium-Range 10 day deterministic forecast and a long-range 30 day 16-member ensemble forecast. United Sates Geologic Survey (USGS) streamflow observations are assimilated into the analysis and assimilation configuration, and all four configurations benefit from the inclusion of 1,260 reservoirs. An overview of the National Water Model will be given, along with information on ongoing evaluation activities and plans for future NWM enhancements.

Technology Program Management Model (TPMM) Overview

DTIC Science & Technology

2006-05-10

1 1 “Secure the High Ground” Jeff Craver Project Manager Space and Missile Defense Technical Center Jeff.Craver@US.Army.Mil ff r r r j t r i il...f i l t r ff. r r . r . il UNCLASSIFIED UNCLASSIFIED Technology Program Management Model (TPMM) Overview 05-10-2006 Report Documentation Page Form...DATES COVERED 00-00-2006 to 00-00-2006 4. TITLE AND SUBTITLE Technology Program Management Model (TPMM) Overview 5a. CONTRACT NUMBER 5b. GRANT

Integrating model behavior, optimization, and sensitivity/uncertainty analysis: overview and application of the MOUSE software toolbox

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) software application, an open-source, Java-based toolbox of visual and numerical analysis components for the evaluation of environmental models. MOUSE is based on the OPTAS model calibration syst...

The Durham Adaptive Optics Simulation Platform (DASP): Current status

NASA Astrophysics Data System (ADS)

Basden, A. G.; Bharmal, N. A.; Jenkins, D.; Morris, T. J.; Osborn, J.; Peng, J.; Staykov, L.

2018-01-01

The Durham Adaptive Optics Simulation Platform (DASP) is a Monte-Carlo modelling tool used for the simulation of astronomical and solar adaptive optics systems. In recent years, this tool has been used to predict the expected performance of the forthcoming extremely large telescope adaptive optics systems, and has seen the addition of several modules with new features, including Fresnel optics propagation and extended object wavefront sensing. Here, we provide an overview of the features of DASP and the situations in which it can be used. Additionally, the user tools for configuration and control are described.

Ball Bearing Analysis with the ORBIS Tool

NASA Technical Reports Server (NTRS)

Halpin, Jacob D.

2016-01-01

Ball bearing design is critical to the success of aerospace mechanisms. Key bearing performance parameters, such as load capability, stiffness, torque, and life all depend on accurate determination of the internal load distribution. Hence, a good analytical bearing tool that provides both comprehensive capabilities and reliable results becomes a significant asset to the engineer. This paper introduces the ORBIS bearing tool. A discussion of key modeling assumptions and a technical overview is provided. Numerous validation studies and case studies using the ORBIS tool are presented. All results suggest the ORBIS code closely correlates to predictions on bearing internal load distributions, stiffness, deflection and stresses.

Remote sensing of estuarine fronts and their effects on pollutants

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator); Polis, D. F.

1975-01-01

The author has identified the following significant results. Imagery from LANDSAT 1 and 2 proved valuable in determining the location, type, and extent of estuarine fronts under different tidal conditions. Neither ships nor aircraft alone could provide as complete, synoptic, and repetitive an overview as did the satellites. Since estuarine fronts influence the movement of oil slicks and dispersion of other pollutants, cleanup operations depending on real time use of oil slick movement prediction models will benefit not only from aircraft tracking the actual slicks but also from real time satellite observations of surface currents and the location of frontal systems.

Designing Medical Support for a Near-Earth Asteroid Mission

NASA Technical Reports Server (NTRS)

Watkins, S. D.; Charles, J. B.; Kundrot, C. E.; Barr, Y. R.; Barsten, K. N.; Chin, D. A.; Kerstman, E. L.; Otto, C.

2011-01-01

This panel will discuss the design of medical support for a mission to a near-Earth asteroid (NEA) from a variety of perspectives. The panelists will discuss the proposed parameters for a NEA mission, the NEA medical condition list, recommendations from the NASA telemedicine workshop, an overview of the Exploration Medical System Demonstration planned for the International Space Station, use of predictive models for mission planning, and mission-related concerns for behavioral health and performance. This panel is intended to make the audience aware of the multitude of factors influencing medical support during a NEA mission.

ACCESS - A Science and Engineering Assessment of Space Coronagraph Concepts for the Direct Imaging and Spectroscopy of Exoplanetary Systems

NASA Technical Reports Server (NTRS)

Trauger, John

2008-01-01

Topics include and overview, science objectives, study objectives, coronagraph types, metrics, ACCESS observatory, laboratory validations, and summary. Individual slides examine ACCESS engineering approach, ACCESS gamut of coronagraph types, coronagraph metrics, ACCESS Discovery Space, coronagraph optical layout, wavefront control on the "level playing field", deformable mirror development for HCIT, laboratory testbed demonstrations, high contract imaging with the HCIT, laboratory coronagraph contrast and stability, model validation and performance predictions, HCIT coronagraph optical layout, Lyot coronagraph on the HCIT, pupil mapping (PIAA), shaped pupils, and vortex phase mask experiments on the HCIT.

An overview of polymer ageing studies in the nuclear power industry

NASA Astrophysics Data System (ADS)

Burnay, S. G.

2001-12-01

Polymeric components are widely used in nuclear power plants (NPPs) in equipment which is important to the safety of the plant. The degradation of such components is therefore of considerable interest to the industry and its regulatory bodies, generating a large number of studies worldwide. Some of these components need to remain functional over the full operational life of the plant, which may span up to 60 years. Predictive modelling of their behaviour is therefore of key importance. This paper outlines the main areas of research, particularly relating to the use of elastomeric seals and polymeric cable insulation in NPP.

A Compact Airborne High Spectral Resolution Lidar for Observations of Aerosol and Cloud Optical Properties

NASA Technical Reports Server (NTRS)

Hostetler, Chris A.; Hair, John W.; Cook, Anthony L.

2002-01-01

We are in the process of developing a nadir-viewing, aircraft-based high spectral resolution lidar (HSRL) at NASA Langley Research Center. The system is designed to measure backscatter and extinction of aerosols and tenuous clouds. The primary uses of the instrument will be to validate spaceborne aerosol and cloud observations, carry out regional process studies, and assess the predictions of chemical transport models. In this paper, we provide an overview of the instrument design and present the results of simulations showing the instrument's capability to accurately measure extinction and extinction-to-backscatter ratio.

Overview of major hazards. Part 2: Source term; dispersion; combustion; blast, missiles, venting; fire; radiation; runaway reactions; toxic substances; dust explosions

NASA Astrophysics Data System (ADS)

Vilain, J.

Approaches to major hazard assessment and prediction are reviewed. Source term: (phenomenology/modeling of release, influence on early stages of dispersion); dispersion (atmospheric advection, diffusion and deposition, emphasis on dense/cold gases); combustion (flammable clouds and mists covering flash fires, deflagration, transition to detonation; mostly unconfined/partly confined situations); blast formation, propagation, interaction with structures; catastrophic fires (pool fires, torches and fireballs; highly reactive substances) runaway reactions; features of more general interest; toxic substances, excluding toxicology; and dust explosions (phenomenology and protective measures) are discussed.

DELFIC: Department of Defense Fallout Prediction System. Volume I - Fundamentals

DTIC Science & Technology

1979-12-31

102 H2590D. DTIC•;. 17.) 1 i{1•ELECT ’ Prepared for " JAUG 2 ? 1980 Director DEFENSE NUCLEAR AGENCY B Wai’hington, D. C. 20305 808 1O8x Destroy this...2 1. INTRODUCTION AND OVERVIEW -- --- - -------------- - --- ---- 7 2. INITIALIZATION AND CLOUD RISE...61 6 1. INTRODUCTION AND OVERVIEW DELFIC (DEfense Land Fallout Interpretative Code) is intended for re- search in local nuclear fallout

PROGRAM VSAERO: A computer program for calculating the non-linear aerodynamic characteristics of arbitrary configurations: User's manual

NASA Technical Reports Server (NTRS)

Maskew, B.

1982-01-01

VSAERO is a computer program used to predict the nonlinear aerodynamic characteristics of arbitrary three-dimensional configurations in subsonic flow. Nonlinear effects of vortex separation and vortex surface interaction are treated in an iterative wake-shape calculation procedure, while the effects of viscosity are treated in an iterative loop coupling potential-flow and integral boundary-layer calculations. The program employs a surface singularity panel method using quadrilateral panels on which doublet and source singularities are distributed in a piecewise constant form. This user's manual provides a brief overview of the mathematical model, instructions for configuration modeling and a description of the input and output data. A listing of a sample case is included.

Computer-Aided Drug Design in Epigenetics

NASA Astrophysics Data System (ADS)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-03-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

Solvers for the Cardiac Bidomain Equations

PubMed Central

Vigmond, E.J.; Weber dos Santos, R.; Prassl, A.J.; Deo, M.; Plank, G.

2010-01-01

The bidomain equations are widely used for the simulation of electrical activity in cardiac tissue. They are especially important for accurately modelling extracellular stimulation, as evidenced by their prediction of virtual electrode polarization before experimental verification. However, solution of the equations is computationally expensive due to the fine spatial and temporal discretization needed. This limits the size and duration of the problem which can be modeled. Regardless of the specific form into which they are cast, the computational bottleneck becomes the repeated solution of a large, linear system. The purpose of this review is to give an overview of the equations, and the methods by which they have been solved. Of particular note are recent developments in multigrid methods, which have proven to be the most efficient. PMID:17900668

Computer-Aided Drug Design in Epigenetics

PubMed Central

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-01-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. PMID:29594101

Overview of the Aeroelastic Prediction Workshop

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel; Schuster, David M.; Dalenbring, Mats

2013-01-01

The AIAA Aeroelastic Prediction Workshop (AePW) was held in April, 2012, bringing together communities of aeroelasticians and computational fluid dynamicists. The objective in conducting this workshop on aeroelastic prediction was to assess state-of-the-art computational aeroelasticity methods as practical tools for the prediction of static and dynamic aeroelastic phenomena. No comprehensive aeroelastic benchmarking validation standard currently exists, greatly hindering validation and state-of-the-art assessment objectives. The workshop was a step towards assessing the state of the art in computational aeroelasticity. This was an opportunity to discuss and evaluate the effectiveness of existing computer codes and modeling techniques for unsteady flow, and to identify computational and experimental areas needing additional research and development. Three configurations served as the basis for the workshop, providing different levels of geometric and flow field complexity. All cases considered involved supercritical airfoils at transonic conditions. The flow fields contained oscillating shocks and in some cases, regions of separation. The computational tools principally employed Reynolds-Averaged Navier Stokes solutions. The successes and failures of the computations and the experiments are examined in this paper.

Coding tools investigation for next generation video coding based on HEVC

NASA Astrophysics Data System (ADS)

Chen, Jianle; Chen, Ying; Karczewicz, Marta; Li, Xiang; Liu, Hongbin; Zhang, Li; Zhao, Xin

2015-09-01

The new state-of-the-art video coding standard, H.265/HEVC, has been finalized in 2013 and it achieves roughly 50% bit rate saving compared to its predecessor, H.264/MPEG-4 AVC. This paper provides the evidence that there is still potential for further coding efficiency improvements. A brief overview of HEVC is firstly given in the paper. Then, our improvements on each main module of HEVC are presented. For instance, the recursive quadtree block structure is extended to support larger coding unit and transform unit. The motion information prediction scheme is improved by advanced temporal motion vector prediction, which inherits the motion information of each small block within a large block from a temporal reference picture. Cross component prediction with linear prediction model improves intra prediction and overlapped block motion compensation improves the efficiency of inter prediction. Furthermore, coding of both intra and inter prediction residual is improved by adaptive multiple transform technique. Finally, in addition to deblocking filter and SAO, adaptive loop filter is applied to further enhance the reconstructed picture quality. This paper describes above-mentioned techniques in detail and evaluates their coding performance benefits based on the common test condition during HEVC development. The simulation results show that significant performance improvement over HEVC standard can be achieved, especially for the high resolution video materials.

AQMEII Phase 2: Overview and WRF/CMAQ Application over North America

EPA Science Inventory

In this study, we provide an overview of the second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorologychemistry models. Participating modeling systems are being...

Inverse problems and computational cell metabolic models: a statistical approach

NASA Astrophysics Data System (ADS)

Calvetti, D.; Somersalo, E.

2008-07-01

In this article, we give an overview of the Bayesian modelling of metabolic systems at the cellular and subcellular level. The models are based on detailed description of key biochemical reactions occurring in tissue, which may in turn be compartmentalized into cytosol and mitochondria, and of transports between the compartments. The classical deterministic approach which models metabolic systems as dynamical systems with Michaelis-Menten kinetics, is replaced by a stochastic extension where the model parameters are interpreted as random variables with an appropriate probability density. The inverse problem of cell metabolism in this setting consists of estimating the density of the model parameters. After discussing some possible approaches to solving the problem, we address the issue of how to assess the reliability of the predictions of a stochastic model by proposing an output analysis in terms of model uncertainties. Visualization modalities for organizing the large amount of information provided by the Bayesian dynamic sensitivity analysis are also illustrated.

An Overview of the Human Systems Integration Division

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2015-01-01

This presentation will provide an overview of the Human Systems Integration Division, and will highlight some of the human performance modeling efforts undertaken in previously presented MIDAS human performance modeling efforts.

Life Sciences Implications of Lunar Surface Operations

NASA Technical Reports Server (NTRS)

Chappell, Steven P.; Norcross, Jason R.; Abercromby, Andrew F.; Gernhardt, Michael L.

2010-01-01

The purpose of this report is to document preliminary, predicted, life sciences implications of expected operational concepts for lunar surface extravehicular activity (EVA). Algorithms developed through simulation and testing in lunar analog environments were used to predict crew metabolic rates and ground reaction forces experienced during lunar EVA. Subsequently, the total metabolic energy consumption, the daily bone load stimulus, total oxygen needed, and other variables were calculated and provided to Human Research Program and Exploration Systems Mission Directorate stakeholders. To provide context to the modeling, the report includes an overview of some scenarios that have been considered. Concise descriptions of the analog testing and development of the algorithms are also provided. This document may be updated to remain current with evolving lunar or other planetary surface operations, assumptions and concepts, and to provide additional data and analyses collected during the ongoing analog research program.

Pressure Ulcers in Adults: Prediction and Prevention. Clinical Practice Guideline Number 3.

ERIC Educational Resources Information Center

Agency for Health Care Policy and Research (DHHS/PHS), Rockville, MD.

This package includes a clinical practice guideline, quick reference guide for clinicians, and patient's guide to predicting and preventing pressure ulcers in adults. The clinical practice guideline includes the following: overview of the incidence and prevalence of pressure ulcers; clinical practice guideline (introduction, risk assessment tools…

Understanding Rasch Measurement: Rasch Models Overview.

ERIC Educational Resources Information Center

Wright, Benjamin D.; Mok, Magdalena

2000-01-01

Presents an overview of Rasch measurement models that begins with a conceptualization of continuous experiences often captured as discrete observations. Discusses the mathematical properties of the Rasch family of models that allow the transformation of discrete deterministic counts into continuous probabilistic abstractions. Also discusses six of…

NEMS - National Energy Modeling System: An Overview

EIA Publications

2009-01-01

The National Energy Modeling System: An Overview 2009 a summary description of NEMS and each of its components. NEMS is a computer-based, energy-economy modeling system of energy markets for the midterm period through 2030. The NEMS is used to produce the Annual Energy Outlook.

Interacting Boson Model and nucleons

NASA Astrophysics Data System (ADS)

Otsuka, Takaharu

2012-10-01

An overview on the recent development of the microscopic derivation of the Interacting Boson Model is presented with some remarks not found elsewhere. The OAI mapping is reviewed very briefly, including the basic correspondence from nucleon-pair to boson. The new fermionboson mapping method is introduced, where intrinsic states of nucleons and bosons for a wide variation of shapes play an important role. Nucleon intrinsic states are obtained from mean field models, which is Skyrme model in examples to be shown. This method generates IBM-2 Hamiltonian which can describe and predict various situations of quadrupole collective states, including U(5), SU(3), O(6) and E(5) limits. The method is extended so that rotational response (cranking) can be handled, which enables us to describe rotational bands of strongly deformed nuclei. Thus, we have obtained a unified framework for the microscopic derivation of the IBM covering all known situations of quadrupole collectivity at low energy.

Overview of the arthritis Cost Consequence Evaluation System (ACCES): a pharmacoeconomic model for celecoxib.

PubMed

Pettitt, D; Goldstein, J L; McGuire, A; Schwartz, J S; Burke, T; Maniadakis, N

2000-12-01

Pharmacoeconomic analyses have become useful and essential tools for health care decision makers who increasingly require such analyses prior to placing a drug on a national, regional or hospital formulary. Previous health economic models of non-steroidal anti-inflammatory drugs (NSAIDs) have been restricted to evaluating a narrow range of agents within specific health care delivery systems using medical information derived from homogeneous clinical trial data. This paper summarizes the Arthritis Cost Consequence Evaluation System (ACCES)--a pharmacoeconomic model that has been developed to predict and evaluate the costs and consequences associated with the use of celecoxib in patients with arthritis, compared with other NSAIDs and NSAIDs plus gastroprotective agents. The advantage of this model is that it can be customized to reflect local practice patterns, resource utilization and costs, as well as provide context-specific health economic information to a variety of providers and/or decision makers.

An Anisotropic Model for Magnetostriction and Magnetization Computing for Noise Generation in Electric Devices.

PubMed

Mbengue, Serigne Saliou; Buiron, Nicolas; Lanfranchi, Vincent

2016-04-16

During the manufacturing process and use of ferromagnetic sheets, operations such as rolling, cutting, and tightening induce anisotropy that changes the material's behavior. Consequently for more accuracy in magnetization and magnetostriction calculations in electric devices such as transformers, anisotropic effects should be considered. In the following sections, we give an overview of a macroscopic model which takes into account the magnetic and magnetoelastic anisotropy of the material for both magnetization and magnetostriction computing. Firstly, a comparison between the model results and measurements from a Single Sheet Tester (SST) and values will be shown. Secondly, the model is integrated in a finite elements code to predict magnetostrictive deformation of an in-house test bench which is a stack of 40 sheets glued together by the Vacuum-Pressure Impregnation (VPI) method. Measurements on the test bench and Finite Elements results are presented.

Kuwaiti oil fires—Modeling revisited

NASA Astrophysics Data System (ADS)

Husain, Tahir

Just after the invasion of Kuwait, scientists began predictions on the environmental disaster due to threat by the Iraqi regime to blow out oil wells in the Kuwaiti oil fields. The findings with the speculations ranging from a nuclear winter to super-acid rain and global warming were presented in the World Climate Conference in Geneva in November 1990. Just before the war erupted in the middle of January 1991, a conference in London was called to discuss the potential risks to human life and ecological systems in case of blow out of oil fields. The scientists, using modeling techniques, raised the speculations about the global impact which, however, was discounted at a later stage. This paper presents an overview of the selected models used to assess the local, regional, and global impacts. The paper also highlights the model and data limitations and suggests future research directions to respond more effectively under emergency situations.

Review of electronic transport models for thermoelectric materials

NASA Astrophysics Data System (ADS)

Bulusu, A.; Walker, D. G.

2008-07-01

Thermoelectric devices have gained importance in recent years as viable solutions for applications such as spot cooling of electronic components, remote power generation in space stations and satellites etc. These solid-state devices have long been known for their reliability rather than their efficiency; they contain no moving parts, and their performance relies primarily on material selection, which has not generated many excellent candidates. Research in recent years has been focused on developing both thermoelectric structures and materials that have high efficiency. In general, thermoelectric research is two-pronged with (1) experiments focused on finding new materials and structures with enhanced thermoelectric performance and (2) analytical models that predict thermoelectric behavior to enable better design and optimization of materials and structures. While numerous reviews have discussed the importance of and dependence on materials for thermoelectric performance, an overview of how to predict the performance of various materials and structures based on fundamental quantities is lacking. In this paper we present a review of the theoretical models that were developed since thermoelectricity was first observed in 1821 by Seebeck and how these models have guided experimental material search for improved thermoelectric devices. A new quantum model is also presented, which provides opportunities for the optimization of nanoscale materials to enhance thermoelectric performance.

Open hydrological data at hypeweb.smhi.se

NASA Astrophysics Data System (ADS)

Arheimer, Berit; Strömbäck, Lena; Andersson, Jafet; Donnelly, Chantal; Gustafsson, David; Pechlivianidis, Ilias; Strömqvist, Johan

2016-04-01

Following the EU open data strategy the Swedish Meteorological and Hydrological Institute (SMHI) is providing large parts of the databases openly available. These data are ranging from historical observations to climate predictions in various areas such as weather, oceanography and hydrology. For the Water Service called Hypeweb (www.hypeweb.smhi.se), we provide data for water management. So far, the data has been used in: (i) Climate change impact assessments on water resources and dynamics; (ii) The European Water Framework Directive (WFD) for characterization and development of measure programs to improve the ecological status of water bodies; (iii) Design variables for infrastructure constructions; (iv) Spatial water-resource mapping; (v) Operational forecasts (1-10 days and seasonal) on floods and droughts; (vi) Input to oceanographic models for operational forecasts and marine status assessments; and (vii) Research. The data of Hypeweb is based on other open data sources that has been merged and re-purposed by using the Hydrological Predictions for the Environment (HYPE) model in world-wide applications with high resolution. HYPE is a dynamic, semi-distributed, process-based, and integrated catchment model. So far, the following regional domains have been modelled with different resolutions (number of subbasins within brackets): Sweden (37 000), Europe (35 000), Arctic basin (30 000), La Plata River (6 000), Niger River (800), Middle-East North-Africa (31 000), and the Indian subcontinent (6 000). The web site provides several interactive applications for exploring results from the models. The user can explore an overview of various water variables for historical and future conditions. Moreover the user can explore and download historical time series of discharge for each basin and explore the performance of the model towards observed river flow. The presentation will give an overview of the functionality of the web site and the available hydrological datasets. The first version if the site was launched early 2015, and new functionality and updated model data is regularly added. During the first year the site has attracted more than 2000 users from over 90 different countries, and we see an increasing trend in number of visitors. The presentation will describe the Open Data sources used, show the functionality of the web site and discuss model performance and experience from this world-wide hydrological modelling of multi-basins using open data.

The Global Integrated Drought Monitoring and Prediction System (GIDMaPS): Overview and Capabilities

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Hao, Z.; Farahmand, A.; Nakhjiri, N.

2013-12-01

Development of reliable monitoring and prediction indices and tools are fundamental to drought preparedness and management. Motivated by the Global Drought Information Systems (GDIS) activities, this paper presents the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which provides near real-time drought information using both remote sensing observations and model simulations. The monthly data from the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA-Land), North American Land Data Assimilation System (NLDAS), and remotely sensed precipitation data are used as input to GIDMaPS. Numerous indices have been developed for drought monitoring based on various indicator variables (e.g., precipitation, soil moisture, water storage). Defining droughts based on a single variable (e.g., precipitation, soil moisture or runoff) may not be sufficient for reliable risk assessment and decision making. GIDMaPS provides drought information based on multiple indices including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of droughts. The seasonal prediction component of GIDMaPS is based on a persistence model which requires historical data and near-past observations. The seasonal drought prediction component is based on two input data sets (MERRA and NLDAS) and three drought indicators (SPI, SSI and MSDI). The drought prediction model provides the empirical probability of drought for different severity levels. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from several major droughts including the 2013 Namibia, 2012-2013 United States, 2011-2012 Horn of Africa, and 2010 Amazon Droughts will be presented. The results indicate that GIDMaPS advances our drought monitoring and prediction capabilities through integration of multiple data and indicators.

Urothelial cancer of the upper urinary tract: emerging biomarkers and integrative models for risk stratification.

PubMed

Mathieu, Romain; Vartolomei, Mihai D; Mbeutcha, Aurélie; Karakiewicz, Pierre I; Briganti, Alberto; Roupret, Morgan; Shariat, Shahrokh F

2016-08-01

The aim of this review was to provide an overview of current biomarkers and risk stratification models in urothelial cancer of the upper urinary tract (UTUC). A non-systematic Medline/PubMed literature search was performed using the terms "biomarkers", "preoperative models", "postoperative models", "risk stratification", together with "upper tract urothelial carcinoma". Original articles published between January 2003 and August 2015 were included based on their clinical relevance. Additional references were collected by cross referencing the bibliography of the selected articles. Various promising predictive and prognostic biomarkers have been identified in UTUC thanks to the increasing knowledge of the different biological pathways involved in UTUC tumorigenesis. These biomarkers may help identify tumors with aggressive biology and worse outcomes. Current tools aim at predicting muscle invasive or non-organ confined disease, renal failure after radical nephroureterectomy and survival outcomes. These models are still mainly based on imaging and clinicopathological feature and none has integrated biomarkers. Risk stratification in UTUC is still suboptimal, especially in the preoperative setting due to current limitations in staging and grading. Identification of novel biomarkers and external validation of current prognostic models may help improve risk stratification to allow evidence-based counselling for kidney-sparing approaches, perioperative chemotherapy and/or risk-based surveillance. Despite growing understanding of the biology underlying UTUC, management of this disease remains difficult due to the lack of validated biomarkers and the limitations of current predictive and prognostic tools. Further efforts and collaborations are necessaryry to allow their integration in daily practice.

A Thermo-Poromechanics Finite Element Model for Predicting Arterial Tissue Fusion

NASA Astrophysics Data System (ADS)

Fankell, Douglas P.

This work provides modeling efforts and supplemental experimental work performed towards the ultimate goal of modeling heat transfer, mass transfer, and deformation occurring in biological tissue, in particular during arterial fusion and cutting. Developing accurate models of these processes accomplishes two goals. First, accurate models would enable engineers to design devices to be safer and less expensive. Second, the mechanisms behind tissue fusion and cutting are widely unknown; models with the ability to accurately predict physical phenomena occurring in the tissue will allow for insight into the underlying mechanisms of the processes. This work presents three aims and the efforts in achieving them, leading to an accurate model of tissue fusion and more broadly the thermo-poromechanics (TPM) occurring within biological tissue. Chapters 1 and 2 provide the motivation for developing accurate TPM models of biological tissue and an overview of previous modeling efforts. In Chapter 3, a coupled thermo-structural finite element (FE) model with the ability to predict arterial cutting is offered. From the work presented in Chapter 3, it became obvious a more detailed model was needed. Chapter 4 meets this need by presenting small strain TPM theory and its implementation in an FE code. The model is then used to simulate thermal tissue fusion. These simulations show the model's promise in predicting the water content and temperature of arterial wall tissue during the fusion process, but it is limited by its small deformation assumptions. Chapters 5-7 attempt to address this limitation by developing and implementing a large deformation TPM FE model. Chapters 5, 6, and 7 present a thermodynamically consistent, large deformation TPM FE model and its ability to simulate tissue fusion. Ultimately, this work provides several methods of simulating arterial tissue fusion and the thermo-poromechanics of biological tissue. It is the first work, to the author's knowledge, to simulate the fully coupled TPM of biological tissue and the first to present a fully coupled large deformation TPM FE model. In doing so, a stepping stone for more advanced modeling of biological tissue has been laid.

The role of learning-related dopamine signals in addiction vulnerability.

PubMed

Huys, Quentin J M; Tobler, Philippe N; Hasler, Gregor; Flagel, Shelly B

2014-01-01

Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction. © 2014 Elsevier B.V. All rights reserved.

Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

NASA Astrophysics Data System (ADS)

Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

2018-01-01

The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

NASA Astrophysics Data System (ADS)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Results of the Lake Michigan Mass Balance Project: Atrazine Modeling Report

EPA Science Inventory

This report covers an overview of chemical properties, measurements in air and water, model construct and assumptions, and results of mathematical mass balance modeling of the herbicide atrazine in the Lake Michigan basin. Within the context of the mass balance, an overview of a...

“AQMEII Phase 2: Overview and WRF/CMAQ Application over North America”.

EPA Science Inventory

This presentation provides an overview of the second phase of the Air Quality Model Evaluation International Initative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorology-chemistry models to assess how well these models can simu...

“Overview and Evaluation of AQMEII Phase 2 Coupled Simulations over North America”

EPA Science Inventory

This presentation provides an overview of the second phase of the Air Quality Model Evaluation International Initative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorology-chemistry models to assess how well these models can simu...

How a Multidimensional View of Perceived Organizational Support Impacts Self-Efficacy and Task Understanding during Training for Boundary Spanning Tasks

DTIC Science & Technology

2008-03-01

Literature Review Chapter Overview This chapter provides an overview of recent studies and research on theory and application of self-efficacy...from the literature and how it has been used in predicting success in varying measures of performance. Self-efficacy Many psychological theories ...shown to positively affect training outcomes (Bandura, 1977, Salas & Cannon-Bowers, 2001). Theories of expectancy and self-efficacy suggest 10

An Overview of an Experimental Demonstration Aerotow Program

NASA Technical Reports Server (NTRS)

Murray, James E.; Bowers, Albion H.; Lokos, William A.; Peters, Todd L.; Gera, Joseph

1998-01-01

An overview of an experimental demonstration of aerotowing a delta-wing airplane with low-aspect ratio and relatively high wing loading is presented. Aerotowing of future space launch configurations is a new concept, and the objective of the work described herein is to demonstrate the aerotow operation using an airplane configuration similar to conceptual space launch vehicles. Background information on the use of aerotow for a space launch vehicle is presented, and the aerotow system used in this demonstration is described. The ground tests, analytical studies, and flight planning used to predict system behavior and to enhance flight safety are detailed. The instrumentation suite and flight test maneuvers flown are discussed, preliminary performance is assessed, and flight test results are compared with the preflight predictions.

Aerodynamic Models for the Low Density Supersonic Declerator (LDSD) Supersonic Flight Dynamics Test (SFDT)

NASA Technical Reports Server (NTRS)

Van Norman, John W.; Dyakonov, Artem; Schoenenberger, Mark; Davis, Jody; Muppidi, Suman; Tang, Chun; Bose, Deepak; Mobley, Brandon; Clark, Ian

2015-01-01

An overview of pre-flight aerodynamic models for the Low Density Supersonic Decelerator (LDSD) Supersonic Flight Dynamics Test (SFDT) campaign is presented, with comparisons to reconstructed flight data and discussion of model updates. The SFDT campaign objective is to test Supersonic Inflatable Aerodynamic Decelerator (SIAD) and large supersonic parachute technologies at high altitude Earth conditions relevant to entry, descent, and landing (EDL) at Mars. Nominal SIAD test conditions are attained by lifting a test vehicle (TV) to 36 km altitude with a large helium balloon, then accelerating the TV to Mach 4 and and 53 km altitude with a solid rocket motor. The first flight test (SFDT-1) delivered a 6 meter diameter robotic mission class decelerator (SIAD-R) to several seconds of flight on June 28, 2014, and was successful in demonstrating the SFDT flight system concept and SIAD-R. The trajectory was off-nominal, however, lofting to over 8 km higher than predicted in flight simulations. Comparisons between reconstructed flight data and aerodynamic models show that SIAD-R aerodynamic performance was in good agreement with pre-flight predictions. Similar comparisons of powered ascent phase aerodynamics show that the pre-flight model overpredicted TV pitch stability, leading to underprediction of trajectory peak altitude. Comparisons between pre-flight aerodynamic models and reconstructed flight data are shown, and changes to aerodynamic models using improved fidelity and knowledge gained from SFDT-1 are discussed.

Air quality and climate change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III) - Part 1: Overview and model evaluation

NASA Astrophysics Data System (ADS)

Gao, Meng; Han, Zhiwei; Liu, Zirui; Li, Meng; Xin, Jinyuan; Tao, Zhining; Li, Jiawei; Kang, Jeong-Eon; Huang, Kan; Dong, Xinyi; Zhuang, Bingliang; Li, Shu; Ge, Baozhu; Wu, Qizhong; Cheng, Yafang; Wang, Yuesi; Lee, Hyo-Jung; Kim, Cheol-Hee; Fu, Joshua S.; Wang, Tijian; Chin, Mian; Woo, Jung-Hun; Zhang, Qiang; Wang, Zifa; Carmichael, Gregory R.

2018-04-01

Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-Asia III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry-meteorology models. Results are compared to meteorology and air quality measurements, including data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) and the Acid Deposition Monitoring Network in East Asia (EANET). The correlation coefficients between the multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5) for January 2010. However, large discrepancies exist between simulated aerosol chemical compositions from different models. The coefficient of variation (SD divided by the mean) can reach above 1.3 for sulfate in Beijing and above 1.6 for nitrate and organic aerosols in coastal regions, indicating that these compositions are less consistent from different models. During clean periods, simulated aerosol optical depths (AODs) from different models are similar, but peak values differ during severe haze events, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied relative humidity). These differences in composition and AOD suggest that future models can be improved by including new heterogeneous or aqueous pathways for sulfate and nitrate formation under hazy conditions, a secondary organic aerosol (SOA) formation chemical mechanism with new volatile organic compound (VOCs) precursors, yield data and approaches, and a more detailed evaluation of the dependence of aerosol optical properties on size distribution and mixing state. It was also found that using the ensemble mean of the models produced the best prediction skill. While this has been shown for other conditions (for example, the prediction of high-ozone events in the US (McKeen et al., 2005)), this is to our knowledge the first time it has been shown for heavy haze events.

The MVP Model: Overview and Application

ERIC Educational Resources Information Center

Keller, John M.

2017-01-01

This chapter contains an overview of the MVP model that is used as a basis for the other chapters in this issue. It also contains a description of key steps in the ARCS-V design process that is derived from the MVP model and a summary of a design-based research study illustrating the application of the ARCS-V model.

An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes

ERIC Educational Resources Information Center

Kapland, David

2008-01-01

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…

Advances in the Study of Moving Sediments and Evolving Seabeds

NASA Astrophysics Data System (ADS)

Davies, Alan G.; Thorne, Peter D.

2008-01-01

Sands and mud are continually being transported around the world’s coastal seas due to the action of tides, wind and waves. The transport of these sediments modifies the boundary between the land and the sea, changing and reshaping its form. Sometimes the nearshore bathymetry evolves slowly over long time periods, at other times more rapidly due to natural episodic events or the introduction of manmade structures at the shoreline. For over half a century we have been trying to understand the physics of sediment transport processes and formulate predictive models. Although significant progress has been made, our capability to forecast the future behaviour of the coastal zone from basic principles is still relatively poor. However, innovative acoustic techniques for studying the fundamentals of sediment movement experimentally are now providing new insights, and it is expected that such observations, coupled with developing theoretical works, will allow us to take further steps towards the goal of predicting the evolution of coastlines and coastal bathymetry. This paper presents an overview of our existing predictive capabilities, primarily in the field of non-cohesive sediment transport, and highlights how new acoustic techniques are enabling our modelling efforts to achieve greater sophistication and accuracy. The paper is aimed at coastal scientists and managers seeking to understand how detailed physical studies can contribute to the improvement of coastal area models and, hence, inform coastal zone management strategies.

Initializing decadal climate predictions over the North Atlantic region

NASA Astrophysics Data System (ADS)

Matei, Daniela Mihaela; Pohlmann, Holger; Jungclaus, Johann; Müller, Wolfgang; Haak, Helmuth; Marotzke, Jochem

2010-05-01

Decadal climate prediction aims to predict the internally-generated decadal climate variability in addition to externally-forced climate change signal. In order to achieve this it is necessary to start the predictions from the current climate state. In this study we investigate the forecast skill of the North Atlantic decadal climate predictions using two different ocean initialization strategies. First we apply an assimilation of ocean synthesis data provided by the GECCO project (Köhl and Stammer, 2008) as initial conditions for the coupled model ECHAM5/MPI-OM. Hindcast experiments are then performed over the period 1952-2001. An alternative approach is one in which the subsurface ocean temperature and salinity are diagnosed from an ensemble of ocean model runs forced by the NCEP-NCAR atmospheric reanalyzes for the period 1948-2007, then nudge into the coupled model to produce initial conditions for the hindcast experiments. An anomaly coupling scheme is used in both approaches to avoid the hindcast drift and the associated initial shock. Differences between the two assimilation approaches are discussed by comparing them with the observational data in key regions and processes. We asses the skill of the initialized decadal hindcast experiments against the prediction skill of the non-initialized hindcasts simulation. We obtain an overview of the regions with the highest predictability from the regional distribution of the anomaly correlation coefficients and RMSE for the SAT. For the first year the hindcast skill is increased over almost all ocean regions in the NCEP-forced approach. This increase in the hindcast skill for the 1 year lead time is somewhat reduced in the GECCO approach. At lead time 5yr and 10yr, the skill enhancement is still found over the North Atlantic and North Pacific regions. We also consider the potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) and Nordic Seas Overflow by comparing the predicted values to the respective assimilation experiments. Hindcasts of Atlantic MOC and Denmark Strait Overflow show higher predictability than the comparison experiments without initialization and damped persistence predictions up to about 5-6 years.

“Overview and Evaluation of AQMEII Phase 2 Coupled ...

EPA Pesticide Factsheets

This presentation provides an overview of the second phase of the Air Quality Model Evaluation International Initative (AQMEII). Activities in this phase are focused on the application and evaluation of coupled meteorology-chemistry models to assess how well these models can simulate the observed spatio-temporal variability in the optical and radiative characteristics of atmospheric aerosols and associated feedbacks among aerosols, radiation, clouds, and precipitation. To this end, these modeling systems are being applied for annual simulations over both North America and Europe using common emissions and boundary conditions for all modeling groups. We present an overview of these common input datasets, observational datasets for model evaluation, and case studies for diagnostic evaluation. In addition to this overview, we also present results from AQMEII Phase 2 WRF/CMAQ simulations over North America for both 2006 and 2010. The time period between 2006 and 2010 was characterized by a 35% reduction in U.S. SO2 emissions and 20% reduction in U.S. NOx emissions, providing an opportunity for dynamic model evaluation by investigating the impact of emission reductions on ambient concentrations as well as aerosol/radiation feedback effects. We present results of this dynamic evaluation. We also present a brief overview of initial results from WRF-Chem and GEM-MACH simulations performed for the same time period and domain as part of AQMEII Phase 2. The National Exposu

Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

Deep learning for computational chemistry

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

Goh, Garrett B.; Hodas, Nathan O.; Vishnu, Abhinav

The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. Inmore » this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.« less

Predicting chromosomal locations of genetically mapped loci in maize using the Morgan2McClintock Translator.

PubMed

Lawrence, Carolyn J; Seigfried, Trent E; Bass, Hank W; Anderson, Lorinda K

2006-03-01

The Morgan2McClintock Translator permits prediction of meiotic pachytene chromosome map positions from recombination-based linkage data using recombination nodule frequency distributions. Its outputs permit estimation of DNA content between mapped loci and help to create an integrated overview of the maize nuclear genome structure.

Recent modelling advances for ultrasonic TOFD inspections

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

Darmon, Michel; Ferrand, Adrien; Dorval, Vincent

The ultrasonic TOFD (Time of Flight Diffraction) Technique is commonly used to detect and characterize disoriented cracks using their edge diffraction echoes. An overview of the models integrated in the CIVA software platform and devoted to TOFD simulation is presented. CIVA allows to predict diffraction echoes from complex 3D flaws using a PTD (Physical Theory of Diffraction) based model. Other dedicated developments have been added to simulate lateral waves in 3D on planar entry surfaces and in 2D on irregular surfaces by a ray approach. Calibration echoes from Side Drilled Holes (SDHs), specimen echoes and shadowing effects from flaws canmore » also been modelled. Some examples of theoretical validation of the models are presented. In addition, experimental validations have been performed both on planar blocks containing calibration holes and various notches and also on a specimen with an irregular entry surface and allow to draw conclusions on the validity of all the developed models.« less

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2017-07-01

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

NASA Astrophysics Data System (ADS)

Brogniez, Helene; English, Stephen; Mahfouf, Jean-Francois; Behrendt, Andreas; Berg, Wesley; Boukabara, Sid; Buehler, Stefan Alexander; Chambon, Philippe; Gambacorta, Antonia; Geer, Alan; Ingram, William; Kursinski, E. Robert; Matricardi, Marco; Odintsova, Tatyana A.; Payne, Vivienne H.; Thorne, Peter W.; Tretyakov, Mikhail Yu.; Wang, Junhong

2016-05-01

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes.

UK Environmental Prediction - integration and evaluation at the convective scale

NASA Astrophysics Data System (ADS)

Lewis, Huw; Brunet, Gilbert; Harris, Chris; Best, Martin; Saulter, Andrew; Holt, Jason; Bricheno, Lucy; Brerton, Ashley; Reynard, Nick; Blyth, Eleanor; Martinez de la Torre, Alberto

2015-04-01

It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. This was well demonstrated in the UK throughout winter 2013/14 when an exceptional run of severe winter storms, often with damaging high winds and intense rainfall led to significant damage from the large waves and storm surge along coastlines, and from saturated soils, high river flows and significant flooding inland. The substantial impacts on individuals, businesses and infrastructure indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, Centre for Ecology & Hydrology and National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus on a 2-year Prototype project will demonstrate the UK coupled prediction concept in research mode, including an analysis of the winter 2013/14 storms and its impacts. By linking science development to operational collaborations such as the UK Natural Hazards Partnership, we can ensure that science priorities are rooted in user requirements. This presentation will provide an overview of UK environmental prediction activities and an update on progress during the first year of the Prototype project. We will present initial results from the coupled model development and discuss the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

Overview of the hydraulic characteristics of the ITER Central Solenoid Model Coil conductors after 15 years of test campaigns

NASA Astrophysics Data System (ADS)

Brighenti, A.; Bonifetto, R.; Isono, T.; Kawano, K.; Russo, G.; Savoldi, L.; Zanino, R.

2017-12-01

The ITER Central Solenoid Model Coil (CSMC) is a superconducting magnet, layer-wound two-in-hand using Nb3Sn cable-in-conduit conductors (CICCs) with the central channel typical of ITER magnets, cooled with supercritical He (SHe) at ∼4.5 K and 0.5 MPa, operating for approximately 15 years at the National Institutes for Quantum and Radiological Science and Technology in Naka, Japan. The aim of this work is to give an overview of the issues related to the hydraulic performance of the three different CICCs used in the CSMC based on the extensive experimental database put together during the past 15 years. The measured hydraulic characteristics are compared for the different test campaigns and compared also to those coming from the tests of short conductor samples when available. It is shown that the hydraulic performance of the CSMC conductors did not change significantly in the sequence of test campaigns with more than 50 cycles up to 46 kA and 8 cooldown/warmup cycles from 300 K to 4.5 K. The capability of the correlations typically used to predict the friction factor of the SHe for the design and analysis of ITER-like CICCs is also shown.

Universe or Multiverse?

NASA Astrophysics Data System (ADS)

Carr, Bernard

2009-08-01

Part I. Overviews: 1. Introduction and overview Bernard Carr; 2. Living in the multiverse Steven Weinberg; 3. Enlightenment, knowledge, ignorance, temptation Frank Wilczek; Part II. Cosmology and Astrophysics: 4. Cosmology and the multiverse Martin J. Rees; 5. The anthropic principle revisited Bernard Carr; 6. Cosmology from the top down Stephen Hawking; 7. The multiverse hierarchy Max Tegmark; 8. The inflationary universe Andrei Linde; 9. A model of anthropic reasoning: the dark to ordinary matter ratio Frank Wilczek; 10. Anthropic predictions: the case of the cosmological constant Alexander Vilenkin; 11. The definition and classification of universes James D. Bjorken; 12. M/string theory and anthropic reasoning Renata Kallosh; 13. The anthropic principle, dark energy and the LHC Savas Dimopoulos and Scott Thomas; Part III. Particle Physics and Quantum Theory: 14. Quarks, electrons and atoms in closely related universes Craig J. Hogan; 15. The fine-tuning problems of particle physics and anthropic mechanisms John F. Donoghue; 16. The anthropic landscape of string theory Leonard Susskind; 17. Cosmology and the many worlds interpretation of quantum mechanics Viatcheslav Mukhanov; 18. Anthropic reasoning and quantum cosmology James B. Hartle; 19. Micro-anthropic principle for quantum theory Brandon Carter; Part IV. More General Philosophical Issues: 20. Scientific alternatives to the anthropic principle Lee Smolin; 21. Making predictions in a multiverse: conundrums, dangers, coincidences Anthony Aguirre; 22. Multiverses: description, uniqueness and testing George Ellis; 23. Predictions and tests of multiverse theories Don N. Page; 24. Observation selection theory and cosmological fine-tuning Nick Bostrom; 25. Are anthropic arguments, involving multiverses and beyond, legitimate? William R. Stoeger; 26. The multiverse hypothesis: a theistic perspective Robin Collins; 27. Living in a simulated universe John D. Barrow; 28. Universes galore: where will it all end? Paul Davies; Index.

Adversarial Collaboration Decision-Making: An Overview of Social Quantum Information Processing

DTIC Science & Technology

2002-01-01

collaborative decision - making (CDM) to solve problems is an aspect of human behavior least yielding to rational predictions. To reduce the complexity of CDM...increases. Implications for C2 decision - making are discussed. Overview of research Game theory was one of the first rational approaches to the study of...Psychologist, 36, 343-356. Lawless, W.F. (2001), The quantum of social action and the function of emotion in decision - making , Proceedings, Emotional and

Forecasting Optimal Solar Energy Supply in Jiangsu Province (China): A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

PubMed Central

Zhao, Xiuli; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor. PMID:24511292

Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

PubMed

Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

2014-01-01

The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

Computational models for predicting interactions with membrane transporters.

PubMed

Xu, Y; Shen, Q; Liu, X; Lu, J; Li, S; Luo, C; Gong, L; Luo, X; Zheng, M; Jiang, H

2013-01-01

Membrane transporters, including two members: ATP-binding cassette (ABC) transporters and solute carrier (SLC) transporters are proteins that play important roles to facilitate molecules into and out of cells. Consequently, these transporters can be major determinants of the therapeutic efficacy, toxicity and pharmacokinetics of a variety of drugs. Considering the time and expense of bio-experiments taking, research should be driven by evaluation of efficacy and safety. Computational methods arise to be a complementary choice. In this article, we provide an overview of the contribution that computational methods made in transporters field in the past decades. At the beginning, we present a brief introduction about the structure and function of major members of two families in transporters. In the second part, we focus on widely used computational methods in different aspects of transporters research. In the absence of a high-resolution structure of most of transporters, homology modeling is a useful tool to interpret experimental data and potentially guide experimental studies. We summarize reported homology modeling in this review. Researches in computational methods cover major members of transporters and a variety of topics including the classification of substrates and/or inhibitors, prediction of protein-ligand interactions, constitution of binding pocket, phenotype of non-synonymous single-nucleotide polymorphisms, and the conformation analysis that try to explain the mechanism of action. As an example, one of the most important transporters P-gp is elaborated to explain the differences and advantages of various computational models. In the third part, the challenges of developing computational methods to get reliable prediction, as well as the potential future directions in transporter related modeling are discussed.

Applications of holographic spacetime

NASA Astrophysics Data System (ADS)

Torres, Terrence J.

Here we present an overview of the theory of holographic spacetime (HST), originally devised and primarily developed by Tom Banks and Willy Fischler, as well as its various applications and predictions for cosmology and particle phenomenology. First we cover the basic theory and motivation for holographic spacetime and move on to present the latest developments therein as of the time of this writing. Then we indicate the origin of the quantum degrees of freedom in the theory and then present a correspondence with low energy effective field theory. Further, we proceed to show the general origins of inflation and the cosmic microwave background (CMB) within the theory of HST as well as predict the functional forms of two and three point correlation functions for scalar and tensor curvature fluctuations in the early universe. Next, we constrain the theory parameters by insisting on agreement with observational bounds on the scalar spectral index of CMB fluctuations from the Planck experiment as well as theoretical bounds on the number of e-folds of inflation. Finally, we argue that HST predicts specific gauge structures for the low-energy effective field theory at the present era and proceed to construct a viable supersymmetric model extension. Constraints on model parameters and couplings are then calculated by numerically minimizing the theory's scalar potential and comparing the resultant model mass spectra to current observational limits from the LHC SUSY searches. In the end we find that the low-energy theory, while presenting a little hierarchy problem, is fully compatible with current observational limits. Additionally, the high-energy underlying theory is generically compatible with observational constraints stemming from inflation, and predictions on favored model parameters are given.

Evaluation of markers and risk prediction models: Overview of relationships between NRI and decision-analytic measures

PubMed Central

Calster, Ben Van; Vickers, Andrew J; Pencina, Michael J; Baker, Stuart G; Timmerman, Dirk; Steyerberg, Ewout W

2014-01-01

BACKGROUND For the evaluation and comparison of markers and risk prediction models, various novel measures have recently been introduced as alternatives to the commonly used difference in the area under the ROC curve (ΔAUC). The Net Reclassification Improvement (NRI) is increasingly popular to compare predictions with one or more risk thresholds, but decision-analytic approaches have also been proposed. OBJECTIVE We aimed to identify the mathematical relationships between novel performance measures for the situation that a single risk threshold T is used to classify patients as having the outcome or not. METHODS We considered the NRI and three utility-based measures that take misclassification costs into account: difference in Net Benefit (ΔNB), difference in Relative Utility (ΔRU), and weighted NRI (wNRI). We illustrate the behavior of these measures in 1938 women suspect of ovarian cancer (prevalence 28%). RESULTS The three utility-based measures appear transformations of each other, and hence always lead to consistent conclusions. On the other hand, conclusions may differ when using the standard NRI, depending on the adopted risk threshold T, prevalence P and the obtained differences in sensitivity and specificity of the two models that are compared. In the case study, adding the CA-125 tumor marker to a baseline set of covariates yielded a negative NRI yet a positive value for the utility-based measures. CONCLUSIONS The decision-analytic measures are each appropriate to indicate the clinical usefulness of an added marker or compare prediction models, since these measures each reflect misclassification costs. This is of practical importance as these measures may thus adjust conclusions based on purely statistical measures. A range of risk thresholds should be considered in applying these measures. PMID:23313931

OPS MCC level B/C formulation requirements: Area targets and space volumes processor

NASA Technical Reports Server (NTRS)

Bishop, M. J., Jr.

1979-01-01

The level B/C mathematical specifications for the area targets and space volumes processor (ATSVP) are described. The processor is designed to compute the acquisition-of-signal (AOS) and loss-of-signal (LOS) times for area targets and space volumes. The characteristics of the area targets and space volumes are given. The mathematical equations necessary to determine whether the spacecraft lies within the area target or space volume are given. These equations provide a detailed model of the target geometry. A semianalytical technique for predicting the AOS and LOS time periods is disucssed. This technique was designed to bound the actual visibility period using a simplified target geometry model and unperturbed orbital motion. Functional overview of the ATSVP is presented and it's detailed logic flow is described.

Understanding Slat Noise Sources

NASA Technical Reports Server (NTRS)

Khorrami, Medhi R.

2003-01-01

Model-scale aeroacoustic tests of large civil transports point to the leading-edge slat as a dominant high-lift noise source in the low- to mid-frequencies during aircraft approach and landing. Using generic multi-element high-lift models, complementary experimental and numerical tests were carefully planned and executed at NASA in order to isolate slat noise sources and the underlying noise generation mechanisms. In this paper, a brief overview of the supporting computational effort undertaken at NASA Langley Research Center, is provided. Both tonal and broadband aspects of slat noise are discussed. Recent gains in predicting a slat s far-field acoustic noise, current shortcomings of numerical simulations, and other remaining open issues, are presented. Finally, an example of the ever-expanding role of computational simulations in noise reduction studies also is given.

Intraoperative neural monitoring in thyroid surgery: lessons learned from animal studies

PubMed Central

Randolph, Gregory W.; Lu, I-Cheng; Chang, Pi-Ying; Chen, Yi-Ting; Hun, Pao-Chu; Lin, Yi-Chu; Dionigi, Gianlorenzo; Chiang, Feng-Yu

2016-01-01

Recurrent laryngeal nerve (RLN) injury remains a significant morbidity associated with thyroid and parathyroid surgery. In the past decade, surgeons have increasingly used intraoperative neural monitoring (IONM) as an adjunct technique for localizing and identifying the RLN, detecting RLN injury, and predicting the outcome of vocal cord function. In recent years, many animal studies have investigated common pitfalls and new applications of IONM. For example, the use of IONM technology in animal models has proven valuable in studies of the electrophysiology of RLN injury. The advent of animal studies has substantially improved understanding of IONM technology. Lessons learned from animal studies have immediate clinical applications in establishing reliable strategies for preventing intraoperative RLN injury. This article gives an overview of the research progress on IONM-relevant animal models. PMID:27867861

Model-based reasoning in SSF ECLSS

NASA Technical Reports Server (NTRS)

Miller, J. K.; Williams, George P. W., Jr.

1992-01-01

The interacting processes and reconfigurable subsystems of the Space Station Freedom Environmental Control and Life Support System (ECLSS) present a tremendous technical challenge to Freedom's crew and ground support. ECLSS operation and problem analysis is time-consuming for crew members and difficult for current computerized control, monitoring, and diagnostic software. These challenges can be at least partially mitigated by the use of advanced techniques such as Model-Based Reasoning (MBR). This paper will provide an overview of MBR as it is being applied to Space Station Freedom ECLSS. It will report on work being done to produce intelligent systems to help design, control, monitor, and diagnose Freedom's ECLSS. Specifically, work on predictive monitoring, diagnosability, and diagnosis, with emphasis on the automated diagnosis of the regenerative water recovery and air revitalization processes will be discussed.

An International Disaster Management SensorWeb Consisting of Space-based and Insitu Sensors

NASA Astrophysics Data System (ADS)

Mandl, D.; Frye, S. W.; Policelli, F. S.; Cappelaere, P. G.

2009-12-01

For the past year, NASA along with partners consisting of the United Nations Space-based Information for Disaster and Emergency Response (UN-SPIDER) office, the Canadian Space Agency, the Ukraine Space Research Institute (SRI), Taiwan National Space Program Office (NSPO) and in conjunction with the Committee on Earth Observing Satellite (CEOS) Working Group on Information Systems and Services (WGISS) have been conducting a pilot project to automate the process of obtaining sensor data for the purpose of flood management and emergency response. This includes experimenting with flood prediction models based on numerous meteorological satellites and a global hydrological model and then automatically triggering follow up high resolution satellite imagery with rapid delivery of data products. This presentation will provide a overview of the effort, recent accomplishments and future plans.

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

PubMed Central

Hill, Camilla Beate; Czauderna, Tobias; Klapperstück, Matthias; Roessner, Ute; Schreiber, Falk

2015-01-01

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions. PMID:26557642

Transmission loss of double panels filled with porogranular materials.

PubMed

Chazot, Jean-Daniel; Guyader, Jean-Louis

2009-12-01

Sound transmission through hollow structures found its interest in several industrial domains such as building acoustics, automotive industry, and aeronautics. However, in practice, hollow structures are often filled with porous materials to improve acoustic properties without adding an excessive mass. Recently a lot of interest arises for granular materials of low density that can be an alternative to standard absorbing materials. This paper aims to predict vibro-acoustic behavior of double panels filled with porogranular materials by using the patch-mobility method recently published. Biot's theory is a basic tool for the description of porous material but is quite difficult to use in practice, mostly because of the solid phase characterization. The original simplified Biot's model (fluid-fluid model) for porogranular material permitting a considerable reduction in data necessary for calculation has been recently published. The aim of the present paper is to propose a model to predict sound transmission through a double panel filled with a porogranular material. The method is an extension of a previous paper to take into account the porogranular material through fluid-fluid Biot's model. After a global overview of the method, the case of a double panel filled with expanded polystyrene beads is studied and a comparison with measurements is realized.

Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

NASA Technical Reports Server (NTRS)

Strutzenberg, Louise L.; Liever, Peter A.

2011-01-01

This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

Data mining for water resource management part 2 - methods and approaches to solving contemporary problems

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2010-01-01

This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.

Dynamics of the Final Stages of Terrestrial Planet Growth and the Formation of the Earth-Moon System

NASA Technical Reports Server (NTRS)

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

2000-01-01

An overview of current theories of star and planet formation, with emphasis on terrestrial planet accretion and the formation of the Earth-Moon system is presented. These models 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 impacts during the final stages of growth can produce large planetary satellites, such as Earth's Moon. 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.

High School Substance Use as a Predictor of College Attendance, Completion, and Dropout: A National Multi-cohort Longitudinal Study.

PubMed

Patrick, Megan E; Schulenberg, John E; O'Malley, Patrick M

2016-05-01

National data from Monitoring the Future were used to examine patterns and predictors of college attendance. Samples of American 12 th -grade students from 1977-2003 were followed for seven years (modal ages 18-25; N =10,020). College attendance and graduation patterns varied considerably over historical time and based on family background. Substance use during high school predicted a greater likelihood of never attending (for cigarettes, illegal drugs), of graduating from a 2-year rather than a 4-year school (for cigarettes), and of dropping out versus graduating from a 4-year school (for cigarettes, marijuana, and other illegal drugs). High school binge drinking predicted lower college dropout, but only in models also controlling for cigarette, marijuana, and other illicit drug use. This study provides a needed overview of adolescent predictors of patterns of college attendance among American young adults over the past three decades.

Visuo-motor coordination and internal models for object interception.

PubMed

Zago, Myrka; McIntyre, Joseph; Senot, Patrice; Lacquaniti, Francesco

2009-02-01

Intercepting and avoiding collisions with moving objects are fundamental skills in daily life. Anticipatory behavior is required because of significant delays in transforming sensory information about target and body motion into a timed motor response. The ability to predict the kinematics and kinetics of interception or avoidance hundreds of milliseconds before the event may depend on several different sources of information and on different strategies of sensory-motor coordination. What are exactly the sources of spatio-temporal information and what are the control strategies remain controversial issues. Indeed, these topics have been the battlefield of contrasting views on how the brain interprets visual information to guide movement. Here we attempt a synthetic overview of the vast literature on interception. We discuss in detail the behavioral and neurophysiological aspects of interception of targets falling under gravity, as this topic has received special attention in recent years. We show that visual cues alone are insufficient to predict the time and place of interception or avoidance, and they need to be supplemented by prior knowledge (or internal models) about several features of the dynamic interaction with the moving object.

Overview and Meteorological Validation of the Wind Integration National Dataset toolkit

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

Draxl, C.; Hodge, B. M.; Clifton, A.

2015-04-13

The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.

A systems theoretic approach to analysis and control of mammalian circadian dynamics

PubMed Central

Abel, John H.; Doyle, Francis J.

2016-01-01

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

Remote Sensing of Drought: Progress and Opportunities for Improving Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Huning, L. S.; Love, C. A.; Farahmand, A.

2017-12-01

This presentation surveys current and emerging drought monitoring approaches using satellite remote sensing observations from climatological and ecosystem perspectives. Satellite observations that are not currently used for operational drought monitoring, such as near-surface air relative humidity and water vapor, provide opportunities to improve early drought warning. Current and future satellite missions offer opportunities to develop composite and multi-indicator drought models. This presentation describes how different satellite observations can be combined for overall drought development and impact assessment. Finally, we provide an overview of the research gaps and challenges that are facing us ahead in the remote sensing of drought.

Predictability and possible earlier awareness of extreme precipitation across Europe

NASA Astrophysics Data System (ADS)

Lavers, David; Pappenberger, Florian; Richardson, David; Zsoter, Ervin

2017-04-01

Extreme hydrological events can cause large socioeconomic damages in Europe. In winter, a large proportion of these flood episodes are associated with atmospheric rivers, a region of intense water vapour transport within the warm sector of extratropical cyclones. When preparing for such extreme events, forecasts of precipitation from numerical weather prediction models or river discharge forecasts from hydrological models are generally used. Given the strong link between water vapour transport (integrated vapour transport IVT) and heavy precipitation, it is possible that IVT could be used to warn of extreme events. Furthermore, as IVT is located in extratropical cyclones, it is hypothesized to be a more predictable variable due to its link with synoptic-scale atmospheric dynamics. In this research, we firstly provide an overview of the predictability of IVT and precipitation forecasts, and secondly introduce and evaluate the ECMWF Extreme Forecast Index (EFI) for IVT. The EFI is a tool that has been developed to evaluate how ensemble forecasts differ from the model climate, thus revealing the extremeness of the forecast. The ability of the IVT EFI to capture extreme precipitation across Europe during winter 2013/14, 2014/15, and 2015/16 is presented. The results show that the IVT EFI is more capable than the precipitation EFI of identifying extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase. However, the precipitation EFI is superior during the negative NAO phase and at shorter lead times. An IVT EFI example is shown for storm Desmond in December 2015 highlighting its potential to identify upcoming hydrometeorological extremes.

Utilization of Integrated Assessment Modeling for determining geologic CO2 storage security

NASA Astrophysics Data System (ADS)

Pawar, R.

2017-12-01

Geologic storage of carbon dioxide (CO2) has been extensively studied as a potential technology to mitigate atmospheric concentration of CO2. Multiple international research & development efforts, large-scale demonstration and commercial projects are helping advance the technology. One of the critical areas of active investigation is prediction of long-term CO2 storage security and risks. A quantitative methodology for predicting a storage site's long-term performance is critical for making key decisions necessary for successful deployment of commercial scale projects where projects will require quantitative assessments of potential long-term liabilities. These predictions are challenging given that they require simulating CO2 and in-situ fluid movements as well as interactions through the primary storage reservoir, potential leakage pathways (such as wellbores, faults, etc.) and shallow resources such as groundwater aquifers. They need to take into account the inherent variability and uncertainties at geologic sites. This talk will provide an overview of an approach based on integrated assessment modeling (IAM) to predict long-term performance of a geologic storage site including, storage reservoir, potential leakage pathways and shallow groundwater aquifers. The approach utilizes reduced order models (ROMs) to capture the complex physical/chemical interactions resulting due to CO2 movement and interactions but are computationally extremely efficient. Applicability of the approach will be demonstrated through examples that are focused on key storage security questions such as what is the probability of leakage of CO2 from a storage reservoir? how does storage security vary for different geologic environments and operational conditions? how site parameter variability and uncertainties affect storage security, etc.

An Overview of NASA's Oribital Debris Environment Model

NASA Technical Reports Server (NTRS)

Matney, Mark

2010-01-01

Using updated measurement data, analysis tools, and modeling techniques; the NASA Orbital Debris Program Office has created a new Orbital Debris Environment Model. This model extends the coverage of orbital debris flux throughout the Earth orbit environment, and includes information on the mass density of the debris as well as the uncertainties in the model environment. This paper will give an overview of this model and its implications for spacecraft risk analysis.

Peridynamics with LAMMPS : a user guide.

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

Lehoucq, Richard B.; Silling, Stewart Andrew; Plimpton, Steven James

2008-01-01

Peridynamics is a nonlocal formulation of continuum mechanics. The discrete peridynamic model has the same computational structure as a molecular dynamic model. This document details the implementation of a discrete peridynamic model within the LAMMPS molecular dynamic code. This document provides a brief overview of the peridynamic model of a continuum, then discusses how the peridynamic model is discretized, and overviews the LAMMPS implementation. A nontrivial example problem is also included.

An Overview of Modeling Middle Atmospheric Odd Nitrogen

NASA Technical Reports Server (NTRS)

Jackman, Charles H.; Kawa, S. Randolph; Einaudi, Franco (Technical Monitor)

2001-01-01

Odd nitrogen (N, NO, NO2, NO3, N2O5, HNO3, HO2NO2, ClONO2, and BrONO2) constituents are important components in the control of middle atmospheric ozone. Several processes lead to the production of odd nitrogen (NO(sub y)) in the middle atmosphere (stratosphere and mesosphere) including the oxidation of nitrous oxide (N2O), lightning, downflux from the thermosphere, and energetic charged particles (e.g., galactic cosmic rays, solar proton events, and energetic electron precipitation). The dominant production mechanism of NO(sub y) in the stratosphere is N2O oxidation, although other processes contribute. Mesospheric NO(sub y) is influenced by N2O oxidation, downflux from the thermosphere, and energetic charged particles. NO(sub y) is destroyed in the middle atmosphere primarily via two processes: 1) dissociation of NO to form N and O followed by N + NO yielding N2 + O to reform even nitrogen; and 2) transport to the troposphere where HNO3 can be rapidly scavenged in water droplets and rained out of the atmosphere. There are fairly significant differences among global models that predict NO(sub y). NO(sub y) has a fairly long lifetime in the stratosphere (months to years), thus disparate transport in the models probably contributes to many of these differences. Satellite and aircraft measurement provide modeling tests of the various components of NO(sub y). Although some recent reaction rate measurements have led to improvements in model/measurement agreement, significant differences do remain. This presentation will provide an overview of several proposed sources and sinks of NO(sub y) and their regions of importance. Multi-dimensional modeling results for NO(sub y) and its components with comparisons to observations will also be presented.

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models

PubMed Central

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C

2017-01-01

Abstract Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28940491

Aircraft engine hot section technology: An overview of the HOST Project

NASA Technical Reports Server (NTRS)

Sokolowski, Daniel E.; Hirschberg, Marvin H.

1990-01-01

NASA sponsored the Turbine Engine Hot Section (HOST) project to address the need for improved durability in advanced aircraft engine combustors and turbines. Analytical and experimental activities aimed at more accurate prediction of the aerothermal environment, the thermomechanical loads, the material behavior and structural responses to loads, and life predictions for cyclic high temperature operation were conducted from 1980 to 1987. The project involved representatives from six engineering disciplines who are spread across three work disciplines - industry, academia, and NASA. The HOST project not only initiated and sponsored 70 major activities, but also was the keystone in joining the multiple disciplines and work sectors to focus on critical research needs. A broad overview of the project is given along with initial indications of the project's impact.

Rarefied-flow pitching moment coefficient measurements of the Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Blanchard, R. C.; Hinson, E. W.

1988-01-01

An overview of the process for obtaining the Shuttle Orbiter rarefied-flow pitching moment from flight gyro data is presented. The extraction technique involves differentiation of the output of the pitch gyro after accounting for nonaerodynamic torques, such as those produced by gravity gradient and the Orbiter's auxiliary power unit and adjusting for drift biases. The overview of the extraction technique includes examples of results from each of the steps involved in the process, using the STS-32 mission as a typical sample case. The total pitching moment and moment coefficient (Cm) for that flight are calculated and compared with preflight predictions. The flight results show the anticipated decrease in Cm with increasing altitude. However, the total moment coefficient is less than predicted using preflight estimates.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Computer simulation: A modern day crystal ball?

NASA Technical Reports Server (NTRS)

Sham, Michael; Siprelle, Andrew

1994-01-01

It has long been the desire of managers to be able to look into the future and predict the outcome of decisions. With the advent of computer simulation and the tremendous capability provided by personal computers, that desire can now be realized. This paper presents an overview of computer simulation and modeling, and discusses the capabilities of Extend. Extend is an iconic-driven Macintosh-based software tool that brings the power of simulation to the average computer user. An example of an Extend based model is presented in the form of the Space Transportation System (STS) Processing Model. The STS Processing Model produces eight shuttle launches per year, yet it takes only about ten minutes to run. In addition, statistical data such as facility utilization, wait times, and processing bottlenecks are produced. The addition or deletion of resources, such as orbiters or facilities, can be easily modeled and their impact analyzed. Through the use of computer simulation, it is possible to look into the future to see the impact of today's decisions.

Contributions of Dynamic Systems Theory to Cognitive Development

PubMed Central

Spencer, John P.; Austin, Andrew; Schutte, Anne R.

2015-01-01

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples—the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future. PMID:26052181

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

The Current Status of Unsteady CFD Approaches for Aerodynamic Flow Control

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Singer, Bart A.; Yamaleev, Nail; Vatsa, Veer N.; Viken, Sally A.; Atkins, Harold L.

2002-01-01

An overview of the current status of time dependent algorithms is presented. Special attention is given to algorithms used to predict fluid actuator flows, as well as other active and passive flow control devices. Capabilities for the next decade are predicted, and principal impediments to the progress of time-dependent algorithms are identified.

Predicting Chromosomal Locations of Genetically Mapped Loci in Maize Using the Morgan2McClintock Translator

PubMed Central

Lawrence, Carolyn J.; Seigfried, Trent E.; Bass, Hank W.; Anderson, Lorinda K.

2006-01-01

The Morgan2McClintock Translator permits prediction of meiotic pachytene chromosome map positions from recombination-based linkage data using recombination nodule frequency distributions. Its outputs permit estimation of DNA content between mapped loci and help to create an integrated overview of the maize nuclear genome structure. PMID:16387866

Modeling Weather Impact on Airport Arrival Miles-in-Trail Restrictions

NASA Technical Reports Server (NTRS)

Wang, Yao; Grabbe, Shon

2013-01-01

When the demand for either a region of airspace or an airport approaches or exceeds the available capacity, miles-in-trail (MIT) restrictions are the most frequently issued traffic management initiatives (TMIs) that are used to mitigate these imbalances. Miles-intrail operations require aircraft in a traffic stream to meet a specific inter-aircraft separation in exchange for maintaining a safe and orderly flow within the stream. This stream of aircraft can be departing an airport, over a common fix, through a sector, on a specific route or arriving at an airport. This study begins by providing a high-level overview of the distribution and causes of arrival MIT restrictions for the top ten airports in the United States. This is followed by an in-depth analysis of the frequency, duration and cause of MIT restrictions impacting the Hartsfield-Jackson Atlanta International Airport (ATL) from 2009 through 2011. Then, machine-learning methods for predicting (1) situations in which MIT restrictions for ATL arrivals are implemented under low demand scenarios, and (2) days in which a large number of MIT restrictions are required to properly manage and control ATL arrivals are presented. More specifically, these predictions were accomplished by using an ensemble of decision trees with Bootstrap aggregation (BDT) and supervised machine learning was used to train the BDT binary classification models. The models were subsequently validated using data cross validation methods. When predicting the occurrence of arrival MIT restrictions under low demand situations, the model was able to achieve over all accuracy rates ranging from 84% to 90%, with false alarm ratios ranging from 10% to 15%. In the second set of studies designed to predict days on which a high number of MIT restrictions were required, overall accuracy rates of 80% were achieved with false alarm ratios of 20%. Overall, the predictions proposed by the model give better MIT usage information than what has been currently provided under current day operations. Traffic flow managers can use these predictions to identify potential MIT restrictions to eliminate (e.g., those occurring during low arrival demand periods), and to determine the days in which a significant number of restrictions may be required

Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

NASA Astrophysics Data System (ADS)

Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

2015-03-01

Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

The National Solar Radiation Database (NSRDB): A Brief Overview

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

Habte, Aron M; Sengupta, Manajit; Lopez, Anthony

This poster presents a high-level overview of the National Solar Radiation Database (NSRDB). The NSRDB uses the physics-based model (PSM), which was developed using: adapted PATMOS-X model for cloud identification and properties, REST-2 model for clear-sky conditions, and NREL's Fast All-sky Radiation Model for Solar Applications (FARMS) for cloudy-sky Global Horizontal Irradiance (GHI) solar irradiance calculations.

Validation Metrics for Improving Our Understanding of Turbulent Transport - Moving Beyond Proof by Pretty Picture and Loud Assertion

NASA Astrophysics Data System (ADS)

Holland, C.

2013-10-01

Developing validated models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. This tutorial will present an overview of the key guiding principles and practices for state-of-the-art validation studies, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. The primary focus of the talk will be the development of quantiatve validation metrics, which are essential for moving beyond qualitative and subjective assessments of model performance and fidelity. Particular emphasis and discussion is given to (i) the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment, and (ii) the importance of robust uncertainty quantification and its inclusion within the metrics. To illustrate these concepts, we first review the structure and key insights gained from commonly used ``global'' transport model metrics (e.g. predictions of incremental stored energy or radially-averaged temperature), as well as their limitations. Building upon these results, a new form of turbulent transport metrics is then proposed, which focuses upon comparisons of predicted local gradients and fluctuation characteristics against observation. We demonstrate the utility of these metrics by applying them to simulations and modeling of a newly developed ``validation database'' derived from the results of a systematic, multi-year turbulent transport validation campaign on the DIII-D tokamak, in which comprehensive profile and fluctuation measurements have been obtained from a wide variety of heating and confinement scenarios. Finally, we discuss extensions of these metrics and their underlying design concepts to other areas of plasma confinement research, including both magnetohydrodynamic stability and integrated scenario modeling. Supported by the US DOE under DE-FG02-07ER54917 and DE-FC02-08ER54977.

An overview on the ecology of Triatominae (Hemiptera:Reduviidae).

PubMed

Galvão, Cleber; Justi, Silvia A

2015-11-01

Chagas disease, the American trypanosomiasis, is an important neglected tropical illness caused by the flagellate protozoan Trypanosoma cruzi (Kinetoplastida, Trypanosomatidae) and transmitted by insects of the subfamily Triatominae (Hemiptera: Reduviidae). Here we provide an overview on the current knowledge about Triatominae ecology, its association with human, T. cruzi infection and the immediate consequences of habitat fragmentation. We also discuss the geographic distribution of the species and the importance of predicting their distributions to control programs. Copyright © 2015 Elsevier B.V. All rights reserved.

Abiotic Stress Signaling in Wheat – An Inclusive Overview of Hormonal Interactions During Abiotic Stress Responses in Wheat

PubMed Central

Abhinandan, Kumar; Skori, Logan; Stanic, Matija; Hickerson, Neil M. N.; Jamshed, Muhammad; Samuel, Marcus A.

2018-01-01

Rapid global warming directly impacts agricultural productivity and poses a major challenge to the present-day agriculture. Recent climate change models predict severe losses in crop production worldwide due to the changing environment, and in wheat, this can be as large as 42 Mt/°C rise in temperature. Although wheat occupies the largest total harvested area (38.8%) among the cereals including rice and maize, its total productivity remains the lowest. The major production losses in wheat are caused more by abiotic stresses such as drought, salinity, and high temperature than by biotic insults. Thus, understanding the effects of these stresses becomes indispensable for wheat improvement programs which have depended mainly on the genetic variations present in the wheat genome through conventional breeding. Notably, recent biotechnological breakthroughs in the understanding of gene functions and access to whole genome sequences have opened new avenues for crop improvement. Despite the availability of such resources in wheat, progress is still limited to the understanding of the stress signaling mechanisms using model plants such as Arabidopsis, rice and Brachypodium and not directly using wheat as the model organism. This review presents an inclusive overview of the phenotypic and physiological changes in wheat due to various abiotic stresses followed by the current state of knowledge on the identified mechanisms of perception and signal transduction in wheat. Specifically, this review provides an in-depth analysis of different hormonal interactions and signaling observed during abiotic stress signaling in wheat. PMID:29942321

Customizing G Protein-coupled receptor models for structure-based virtual screening.

PubMed

de Graaf, Chris; Rognan, Didier

2009-01-01

This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.

Supersonics--Airport Noise

NASA Technical Reports Server (NTRS)

Bridges, James

2007-01-01

At this, the first year-end meeting of the Fundamental Aeronautics Program, an overview of the Airport Noise discipline of the Supersonics Project leads the presentation of technical plans and achievements in this area of the Project. The overview starts by defining the Technical Challenges targeted by Airport Noise efforts, and the Approaches planned to meet these challenges. These are fleshed out in Elements, namely Prediction, Diagnostics, and Engineering, and broken down into Tasks. The Tasks level is where individual researchers' work is defined and from whence the technical presentations to follow this presentation come. This overview also presents the Milestones accomplished to date and to be completed in the next year. Finally, the NASA Research Announcement cooperative agreement activities are covered and tied to the Tasks and Milestones.

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.

Active control of large space structures: An introduction and overview

NASA Technical Reports Server (NTRS)

Doane, G. B., III; Tollison, D. K.; Waites, H. B.

1985-01-01

An overview of the large space structure (LSS) control system design problem is presented. The LSS is defined as a class of system, and LSS modeling techniques are discussed. Model truncation, control system objectives, current control law design techniques, and particular problem areas are discussed.

Hydrological Predictability for the Peruvian Amazon

NASA Astrophysics Data System (ADS)

Towner, Jamie; Stephens, Elizabeth; Cloke, Hannah; Bazo, Juan; Coughlan, Erin; Zsoter, Ervin

2017-04-01

Population growth in the Peruvian Amazon has prompted the expansion of livelihoods further into the floodplain and thus increasing vulnerability to the annual rise and fall of the river. This growth has coincided with a period of increasing hydrological extremes with more frequent severe flood events. The anticipation and forecasting of these events is crucial for mitigating vulnerability. Forecast-based Financing (FbF) an initiative of the German Red Cross implements risk reducing actions based on threshold exceedance within hydrometeorological forecasts using the Global Flood Awareness System (GloFAS). However, the lead times required to complete certain actions can be long (e.g. several weeks to months ahead to purchase materials and reinforce houses) and are beyond the current capabilities of GloFAS. Therefore, further calibration of the model is required in addition to understanding the climatic drivers and associated hydrological response for specific flood events, such as those observed in 2009, 2012 and 2015. This review sets out to determine the current capabilities of the GloFAS model while exploring the limits of predictability for the Amazon basin. More specifically, how the temporal patterns of flow within the main coinciding tributaries correspond to the overall Amazonian flood wave under various climatic and meteorological influences. Linking the source areas of flow to predictability within the seasonal forecasting system will develop the ability to expand the limit of predictability of the flood wave. This presentation will focus on the Iquitos region of Peru, while providing an overview of the new techniques and current challenges faced within seasonal flood prediction.

The Role of Theory and Modeling in the International Living with a Star Program

NASA Technical Reports Server (NTRS)

Hesse, M.

2004-01-01

Today, theory and modeling play a critical role in our quest to understand the connection between solar eruptive phenomena, and their impacts in interplanetary space and in the near-Earth space environment. This new role is based on two developments, one related to the goal of basic physical understanding, and the other to space weather-related applications. When targeting physical our focus is shifting away from investigations aiming at basic discoveries, to missions and studies that address our basic understanding of processes we know to be important. For these studies, theory and models provide physical explanations that need to be verified or falsified by empirical evidence. Within this paradigm, a much more tight integration between theory modeling, and space flight mission design and execution is not only beneficial, but essential. One of the prime objectives of space weather research, on the other hand, is the prediction of space environmental conditions for the benefit of humans and their assets in near-Earth space and on the ground, as well as on solar system bodies like Mars that are of interest to exploration by humans. By its very nature, prediction requires modeling, which, in turn, requires understanding. We will present an overview of the role of theory and modeling within the International Living With a Star program. Specifically, we will focus on an assessment of present-day and future capabilities, as well as on strategies for tight integration of theory and modeling in space science investigations.

Creep-Fatigue Relationsihps in Electroactive Polymer Systems and Predicted Effects in an Actuator Design

NASA Technical Reports Server (NTRS)

Vinogradov, Aleksandra M.; Ihlefeld, Curtis M.; Henslee, Issac

2009-01-01

The paper concerns the time-dependent behavior of electroactive polymers (EAP) and their use in advanced intelligent structures for space exploration. Innovative actuator design for low weight and low power valves required in small plants planned for use on the moon for chemical analysis is discussed. It is shown that in-depth understanding of cyclic loading effects observed through accelerated creep rates due to creep-fatigue interaction in polymers is critical in terms of proper functioning of EAP based actuator devices. In the paper, an overview of experimental results concerning the creep properties and cyclic creep response of a thin film piezoelectric polymer polyvinylidene fluoride (PVDF) is presented. The development of a constitutive creep-fatigue interaction model to predict the durability and service life of electroactive polymers is discussed. A novel method is proposed to predict damage accumulation and fatigue life of polymers under oyclic loading conditions in the presence of creep. The study provides a basis for ongoing research initiatives at the NASA Kennedy Space Center in the pursuit of new technologies using EAP as active elements for lunar exploration systems.

Autonomous Formation Flight: Project Overview

NASA Technical Reports Server (NTRS)

Cole, Jennifer; Cobleigh, Brent; Vachon, Jake; Ray, Ronald J.; Ennix, Kimberly; Walsh, Kevin

2008-01-01

Objectives: a) Map the vortex effects; b) Formation Auto-Pilot Requirements. Two NASA F/A-18 aircraft in formation: a) NASA 845 Systems Research Aircraft; b) NASA 847 Support Aircraft. Flight Conditions: M = 0.56, 25000 feet (Subsonic condition); b) M = 0.86, 36000 feet (Transonic condition). Nose-To-Tail (N2T) Distances: 20, 55, 110 and 190 feet. Lessons learned: a) Controllable flight in vortex is possible with pilot feedback (displays); b) Position hold at best C(sub D), is attainable; c) Best drag location is close to max rolling moment; e) Drag reductions demonstrated up to 22% (WFE up to 20%); f) Induced drag results compare favorably with simple prediction model; g) "Sweet Spot" (lateral & vertical area > 25%) is larger than predicted; h) Larger wing overlaps result in sign reversals in roll, yaw; i) As predicted, favorable effects degrade gradually with increased nose-to-tail distances after peaking at 3 span lengths aft; and j) Demonstrated - over 100 N mi (>15%) range improvement and 650 lbs (14%) fuel savings on actual simulated F/A-18 cruise mission.

First-order fire effects models for land Management: Overview and issues

Treesearch

Elizabeth D. Reinhardt; Matthew B. Dickinson

2010-01-01

We give an overview of the science application process at work in supporting fire management. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days to centuries. Fire effects may be modeled using empirical, rule based, or process...

Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

NASA Astrophysics Data System (ADS)

Aghakouchak, Amir; Tourian, Mohammad J.

2015-04-01

Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014 California Drought will be presented. Further Reading: Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1:140001, 1-10, doi: 10.1038/sdata.2014.1.

Characterization of Aerodynamic Interactions with the Mars Science Laboratory Reaction Control System Using Computation and Experiment

NASA Technical Reports Server (NTRS)

Schoenenberger, Mark; VanNorman, John; Rhode, Matthew; Paulson, John

2013-01-01

On August 5 , 2012, the Mars Science Laboratory (MSL) entry capsule successfully entered Mars' atmosphere and landed the Curiosity rover in Gale Crater. The capsule used a reaction control system (RCS) consisting of four pairs of hydrazine thrusters to fly a guided entry. The RCS provided bank control to fly along a flight path commanded by an onboard computer and also damped unwanted rates due to atmospheric disturbances and any dynamic instabilities of the capsule. A preliminary assessment of the MSL's flight data from entry showed that the capsule flew much as predicted. This paper will describe how the MSL aerodynamics team used engineering analyses, computational codes and wind tunnel testing in concert to develop the RCS system and certify it for flight. Over the course of MSL's development, the RCS configuration underwent a number of design iterations to accommodate mechanical constraints, aeroheating concerns and excessive aero/RCS interactions. A brief overview of the MSL RCS configuration design evolution is provided. Then, a brief description is presented of how the computational predictions of RCS jet interactions were validated. The primary work to certify that the RCS interactions were acceptable for flight was centered on validating computational predictions at hypersonic speeds. A comparison of computational fluid dynamics (CFD) predictions to wind tunnel force and moment data gathered in the NASA Langley 31-Inch Mach 10 Tunnel was the lynch pin to validating the CFD codes used to predict aero/RCS interactions. Using the CFD predictions and experimental data, an interaction model was developed for Monte Carlo analyses using 6-degree-of-freedom trajectory simulation. The interaction model used in the flight simulation is presented.

A Neo-Piagetian Theory of Constructive Operators: Applications to Perceptual-Motor Development and Learning.

ERIC Educational Resources Information Center

Todor, John I.

The author presents an overview of Pascual-Leone's Theory of Constructive Operators, a process-structural theory based upon Piagetian constructs which has evolved to both explain and predict the temporal unfolding of behavior. An application is made of the theory to the demands of a discrete motor task and prediction of (a) the minimal age…

PEER NGA-East Overview: Development of a Ground Motion Characterization Model (Ground Motion Prediction Equations) for Central and Eastern North America

NASA Astrophysics Data System (ADS)

Goulet, C. A.; Abrahamson, N. A.; Al Atik, L.; Atkinson, G. M.; Bozorgnia, Y.; Graves, R. W.; Kuehn, N. M.; Youngs, R. R.

2017-12-01

The Next Generation Attenuation project for Central and Eastern North America (CENA), NGA-East, is a major multi-disciplinary project coordinated by the Pacific Earthquake Engineering Research Center (PEER). The project was co-sponsored by the U.S. Nuclear Regulatory Commission (NRC), the U.S. Department of Energy (DOE), the Electric Power Research Institute (EPRI) and the U.S. Geological Survey (USGS). NGA-East involved a large number of participating researchers from various organizations in academia, industry and government and was carried-out as a combination of 1) a scientific research project and 2) a model-building component following the NRC Seismic Senior Hazard Analysis Committee (SSHAC) Level 3 process. The science part of the project led to several data products and technical reports while the SSHAC component aggregated the various results into a ground motion characterization (GMC) model. The GMC model consists in a set of ground motion models (GMMs) for median and standard deviation of ground motions and their associated weights, combined into logic-trees for use in probabilistic seismic hazard analyses (PSHA). NGA-East addressed many technical challenges, most of them related to the relatively small number of earthquake recordings available for CENA. To resolve this shortcoming, the project relied on ground motion simulations to supplement the available data. Other important scientific issues were addressed through research projects on topics such as the regionalization of seismic source, path and attenuation of motions, the treatment of variability and uncertainties and on the evaluation of site effects. Seven working groups were formed to cover the complexity and breadth of topics in the NGA-East project, each focused on a specific technical area. This presentation provides an overview of the NGA-East research project and its key products.

Data-driven mapping of the potential mountain permafrost distribution.

PubMed

Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2017-07-15

Existing mountain permafrost distribution models generally offer a good overview of the potential extent of this phenomenon at a regional scale. They are however not always able to reproduce the high spatial discontinuity of permafrost at the micro-scale (scale of a specific landform; ten to several hundreds of meters). To overcome this lack, we tested an alternative modelling approach using three classification algorithms belonging to statistics and machine learning: Logistic regression, Support Vector Machines and Random forests. These supervised learning techniques infer a classification function from labelled training data (pixels of permafrost absence and presence) with the aim of predicting the permafrost occurrence where it is unknown. The research was carried out in a 588km 2 area of the Western Swiss Alps. Permafrost evidences were mapped from ortho-image interpretation (rock glacier inventorying) and field data (mainly geoelectrical and thermal data). The relationship between selected permafrost evidences and permafrost controlling factors was computed with the mentioned techniques. Classification performances, assessed with AUROC, range between 0.81 for Logistic regression, 0.85 with Support Vector Machines and 0.88 with Random forests. The adopted machine learning algorithms have demonstrated to be efficient for permafrost distribution modelling thanks to consistent results compared to the field reality. The high resolution of the input dataset (10m) allows elaborating maps at the micro-scale with a modelled permafrost spatial distribution less optimistic than classic spatial models. Moreover, the probability output of adopted algorithms offers a more precise overview of the potential distribution of mountain permafrost than proposing simple indexes of the permafrost favorability. These encouraging results also open the way to new possibilities of permafrost data analysis and mapping. Copyright © 2017 Elsevier B.V. All rights reserved.

EIA model documentation: World oil refining logistics demand model,``WORLD`` reference manual. Version 1.1

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

Not Available

1994-04-11

This manual is intended primarily for use as a reference by analysts applying the WORLD model to regional studies. It also provides overview information on WORLD features of potential interest to managers and analysts. Broadly, the manual covers WORLD model features in progressively increasing detail. Section 2 provides an overview of the WORLD model, how it has evolved, what its design goals are, what it produces, and where it can be taken with further enhancements. Section 3 reviews model management covering data sources, managing over-optimization, calibration and seasonality, check-points for case construction and common errors. Section 4 describes in detailmore » the WORLD system, including: data and program systems in overview; details of mainframe and PC program control and files;model generation, size management, debugging and error analysis; use with different optimizers; and reporting and results analysis. Section 5 provides a detailed description of every WORLD model data table, covering model controls, case and technology data. Section 6 goes into the details of WORLD matrix structure. It provides an overview, describes how regional definitions are controlled and defines the naming conventions for-all model rows, columns, right-hand sides, and bounds. It also includes a discussion of the formulation of product blending and specifications in WORLD. Several Appendices supplement the main sections.« less

Prediction of physical protein protein interactions

NASA Astrophysics Data System (ADS)

Szilágyi, András; Grimm, Vera; Arakaki, Adrián K.; Skolnick, Jeffrey

2005-06-01

Many essential cellular processes such as signal transduction, transport, cellular motion and most regulatory mechanisms are mediated by protein-protein interactions. In recent years, new experimental techniques have been developed to discover the protein-protein interaction networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited, and computational approaches remain essential both to assist in the design and validation of experimental studies and for the prediction of interaction partners and detailed structures of protein complexes. Here, we provide a critical overview of existing structure-independent and structure-based computational methods. Although these techniques have significantly advanced in the past few years, we find that most of them are still in their infancy. We also provide an overview of experimental techniques for the detection of protein-protein interactions. Although the developments are promising, false positive and false negative results are common, and reliable detection is possible only by taking a consensus of different experimental approaches. The shortcomings of experimental techniques affect both the further development and the fair evaluation of computational prediction methods. For an adequate comparative evaluation of prediction and high-throughput experimental methods, an appropriately large benchmark set of biophysically characterized protein complexes would be needed, but is sorely lacking.

An Overview of Software for Conducting Dimensionality Assessment in Multidimensional Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2012-01-01

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

NASA GRC MBSE Implementation Status

NASA Technical Reports Server (NTRS)

Parrott, Edith; Trase, Katie; Green, Randi; Varga, Denise; Powell, Joe

2016-01-01

This presentation gives a brief overview on GRCs Model Based System Engineering (MBSE) implementation status. This overview covers: history, project usage and implementation, challenges and future work.

Results of Microgravity Fluid Dynamics Captured With the Spheres-Slosh Experiment

NASA Technical Reports Server (NTRS)

Lapilli, Gabriel; Kirk, Daniel; Gutierrez, Hector; Schallhorn, Paul; Marsell, Brandon; Roth, Jacob; Moder, Jeffrey

2015-01-01

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

Result of Microgravity Fluid Dynamics Captured with the SPHERES-Slosh Experiment

NASA Technical Reports Server (NTRS)

Lapilli, Gabriel; Kirk, Daniel; Gutierrez, Hector; Schallhorn, Paul; Marsell, Brandon; Roth, Jacob; Moder, Jeffrey

2015-01-01

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

Thermal Analysis and Testing of Candidate Materials for PAIDAE Inflatable Aeroshell

NASA Technical Reports Server (NTRS)

DelCorso, Joseph A.; Bruce, Walter E., III; Liles, Kaitlin A.; Hughes, Stephen J.

2009-01-01

The Program to Advance Inflatable-Decelerators for Atmospheric Entry (PAIDAE) is a NASA project tasked with developing and evaluating viable inflatable-decelerator aeroshell geometries and materials. Thermal analysis of material layups supporting an inflatable aeroshell was completed in order to identify expected material response, failure times, and to establish an experimental test matrix to keep barrier layer materials from reaching critical temperature limits during thermal soak. Material layups were then tested in the 8- foot High Temperature Tunnel (8'HTT), where they were subjected to hypersonic aerothermal heating conditions, similar to those expected for a Mars entry. This paper presents a broad overview of the thermal analysis supporting multiple materials, and layup configurations tested in the 8'HTT at flight conditions similar to those that would be experienced during Mars entry trajectories. Direct comparison of TPS samples tested in the 8'HTT verify that the thermal model accurately predicted temperature profiles when there are up to four materials in the test layup. As the number of material layers in each test layup increase (greater than 4), the accuracy of the prediction decreases significantly. The inaccuracy of the model predictions for layups with more than four material layers is believed to be a result of the contact resistance values used throughout the model being inaccurate. In addition, the harsh environment of the 8'HTT, including hot gas penetrating through the material layers, could also be a contributing factor.

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

Results of Microgravity Fluid Dynamics Captured with the Spheres-Slosh Experiment

NASA Technical Reports Server (NTRS)

Lapilli, Gabriel; Kirk, Daniel Robert; Gutierrez, Hector; Schallhorn, Paul; Marsell, Brandon; Roth, Jacob; Jeffrey Moder

2015-01-01

This paper provides an overview of the SPHERES-Slosh Experiment (SSE) aboard the International Space Station (ISS) and presents on-orbit results with data analysis. In order to predict the location of the liquid propellant during all times of a spacecraft mission, engineers and mission analysts utilize Computational Fluid Dynamics (CFD). These state-of-the-art computer programs numerically solve the fluid flow equations to predict the location of the fluid at any point in time during different spacecraft maneuvers. The models and equations used by these programs have been extensively validated on the ground, but long duration data has never been acquired in a microgravity environment. The SSE aboard the ISS is designed to acquire this type of data, used by engineers on earth to validate and improve the CFD prediction models, improving the design of the next generation of space vehicles as well as the safety of current missions. The experiment makes use of two Synchronized Position Hold, Engage, Reorient Experimental Satellites (SPHERES) connected by a frame. In the center of the frame there is a plastic, pill shaped tank that is partially filled with green-colored water. A pair of high resolution cameras records the movement of the liquid inside the tank as the experiment maneuvers within the Japanese Experimental Module test volume. Inertial measurement units record the accelerations and rotations of the tank, making the combination of stereo imaging and inertial data the inputs for CFD model validation.

Composite Higgses

NASA Astrophysics Data System (ADS)

Bellazzini, Brando; Csáki, Csaba; Serra, Javi

2014-05-01

For the closing article in this volume on supersymmetry, we consider the alternative options to SUSY theories: we present an overview of composite Higgs models in light of the discovery of the Higgs boson. The small value of the physical Higgs mass suggests that the Higgs quartic is likely loop generated; thus models with tree-level quartics will generically be more tuned. We classify the various models (including bona fide composite Higgs, little Higgs, holographic composite Higgs, twin Higgs and dilatonic Higgs) based on their predictions for the Higgs potential, review the basic ingredients of each of them, and quantify the amount of tuning needed, which is not negligible in any model. We explain the main ideas for generating flavor structure and the main mechanisms for protecting against large flavor violating effects, and we present a summary of the various coset models that can result in realistic pseudo-Goldstone Higgses. We review the current experimental status of such models by discussing the electroweak precision, flavor, and direct search bounds, and we comment on the UV completions of such models and on ways to incorporate dark matter.

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models.

PubMed

Butler, T; Graham, L; Estep, D; Dawson, C; Westerink, J J

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

Definition and solution of a stochastic inverse problem for the Manning's n parameter field in hydrodynamic models

NASA Astrophysics Data System (ADS)

Butler, T.; Graham, L.; Estep, D.; Dawson, C.; Westerink, J. J.

2015-04-01

The uncertainty in spatially heterogeneous Manning's n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented. Technical details that arise in practice by applying the framework to determine the Manning's n parameter field in a shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of "condition" for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. This notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning's n parameter and the effect on model predictions is analyzed.

CADDIS Volume 4. Data Analysis: Predicting Environmental Conditions from Biological Observations (PECBO Appendix)

EPA Pesticide Factsheets

Overview of PECBO Module, using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, methods for inferring environmental conditions, statistical scripts in module.

Overview of a simple model describing variation of dissolved organic carbon in an upland catchment

USGS Publications Warehouse

Boyer, Elizabeth W.; Hornberger, George M.; Bencala, Kenneth E.; McKnight, Diane M.

1996-01-01

Hydrological mechanisms controlling the variation of dissolved organic carbon (DOC) were investigated in the Deer Creek catchment located near Montezuma, CO. Patterns of DOC in streamflow suggested that increased flows through the upper soil horizon during snowmelt are responsible for flushing this DOC-enriched interstitial water to the streams. We examined possible hydrological mechanisms to explain the observed variability of DOC in Deer Creek by first simulating the hydrological response of the catchment using TOPMODEL and then routing the predicted flows through a simple model that accounted for temporal changes in DOC. Conceptually the DOC model can be taken to represent a terrestrial (soil) reservoir in which DOC builds up during low flow periods and is flushed out when infiltrating meltwaters cause the water table to rise into this “reservoir”. Concentrations of DOC measured in the upper soil and in streamflow were compared to model simulations. The simulated DOC response provides a reasonable reproduction of the observed dynamics of DOC in the stream at Deer Creek.

Neutronics calculation of RTP core

NASA Astrophysics Data System (ADS)

Rabir, Mohamad Hairie B.; Zin, Muhammad Rawi B. Mohamed; Karim, Julia Bt. Abdul; Bayar, Abi Muttaqin B. Jalal; Usang, Mark Dennis Anak; Mustafa, Muhammad Khairul Ariff B.; Hamzah, Na'im Syauqi B.; Said, Norfarizan Bt. Mohd; Jalil, Muhammad Husamuddin B.

2017-01-01

Reactor calculation and simulation are significantly important to ensure safety and better utilization of a research reactor. The Malaysian's PUSPATI TRIGA Reactor (RTP) achieved initial criticality on June 28, 1982. The reactor is designed to effectively implement the various fields of basic nuclear research, manpower training, and production of radioisotopes. Since early 90s, neutronics modelling were used as part of its routine in-core fuel management activities. The are several computer codes have been used in RTP since then, based on 1D neutron diffusion, 2D neutron diffusion and 3D Monte Carlo neutron transport method. This paper describes current progress and overview on neutronics modelling development in RTP. Several important parameters were analysed such as keff, reactivity, neutron flux, power distribution and fission product build-up for the latest core configuration. The developed core neutronics model was validated by means of comparison with experimental and measurement data. Along with the RTP core model, the calculation procedure also developed to establish better prediction capability of RTP's behaviour.

The discovery of the Higgs boson at the Large Hadron Collider

NASA Astrophysics Data System (ADS)

Nisati, A.; Tonelli, G.

2015-11-01

This paper summarises the work done by the ATLAS and CMS collaborations, and by the teams of the Large Hadron Collider at CERN, that led to the discovery of a new particle, with mass near 125GeV and properties consistent with the ones predicted for the Standard Model Higgs boson. An overview of the Standard Model, with a description of the role of the Higgs boson in the theory, and a summary of the searches for this particle prior to the LHC operations is also given. The paper presents the results obtained by ATLAS and CMS from the analysis of the full data set produced in the first physics run of LHC. After a short discussion on the implications of the discovery, the future prospects for the precision study of the new particle are lastly discussed.

Geomechanical/Geochemical Modeling Studies Conducted within theInternational DECOVALEX Project

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

Birkholzer, J.T.; Rutqvist, J.; Sonnenthal, E.L.

2005-10-19

The DECOVALEX project is an international cooperative project initiated by SKI, the Swedish Nuclear Power Inspectorate, with participation of about 10 international organizations. The general goal of this project is to encourage multidisciplinary interactive and cooperative research on modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in geologic formations in support of the performance assessment for underground storage of radioactive waste. One of the research tasks, initiated in 2004 by the U.S. Department of Energy (DOE), addresses the long-term impact of geomechanical and geochemical processes on the flow conditions near waste emplacement tunnels. Within this task, four international research teams conduct predictive analysismore » of the coupled processes in two generic repositories, using multiple approaches and different computer codes. Below, we give an overview of the research task and report its current status.« less

Geomechanical/ Geochemical Modeling Studies onducted Within the International DECOVALEX Project

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

J.T. Birkholzer; J. Rutqvist; E.L. Sonnenthal

2006-02-01

The DECOVALEX project is an international cooperative project initiated by SKI, the Swedish Nuclear Power Inspectorate, with participation of about 10 international organizations. The general goal of this project is to encourage multidisciplinary interactive and cooperative research on modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in geologic formations in support of the performance assessment for underground storage of radioactive waste. One of the research tasks, initiated in 2004 by the U.S. Department of Energy (DOE), addresses the long-term impact of geomechanical and geochemical processes on the flow conditions near waste emplacement tunnels. Within this task, four international research teams conduct predictive analysismore » of the coupled processes in two generic repositories, using multiple approaches and different computer codes. Below, we give an overview of the research task and report its current status.« less

Motivation, description, and summary status of geomechanical andgeochemical modeling studies in Task D of the InternationalDECOVALEX-THMC Project

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

Birkholzer, J.T.; Barr, D.; Rutqvist, J.

2005-11-15

The DECOVALEX project is an international cooperativeproject initiated by SKI, the Swedish Nuclear Power Inspectorate, withparticipation of about 10 international organizations. The general goalof this project is to encourage multidisciplinary interactive andcooperative research on modelling coupledthermo-hydro-mechanical-chemical (THMC) processes in geologic formationsin support of the performance assessment for underground storage ofradioactive waste. One of the research tasks, initiated in 2004 by theU.S. Department of Energy (DOE), addresses the long-term impact ofgeomechanical and geochemical processes on the flow conditions near wasteemplacement tunnels. Within this task, four international research teamsconduct predictive analysis of the coupled processes in two genericrepositories, using multiple approaches andmore » different computer codes.Below, we give an overview of the research task and report its currentstatus.« less

The Use of Mathematical Models of Chlamydia Transmission to Address Public Health Policy Questions: A Systematic Review.

PubMed

Rönn, Minttu M; Wolf, Emory E; Chesson, Harrell; Menzies, Nicolas A; Galer, Kara; Gorwitz, Rachel; Gift, Thomas; Hsu, Katherine; Salomon, Joshua A

2017-05-01

Mathematical models of chlamydia transmission can help inform disease control policy decisions when direct empirical evaluation of alternatives is impractical. We reviewed published chlamydia models to understand the range of approaches used for policy analyses and how the studies have responded to developments in the field. We performed a literature review by searching Medline and Google Scholar (up to October 2015) to identify publications describing dynamic chlamydia transmission models used to address public health policy questions. We extracted information on modeling methodology, interventions, and key findings. We identified 47 publications (including two model comparison studies), which reported collectively on 29 distinct mathematical models. Nine models were individual-based, and 20 were deterministic compartmental models. The earliest studies evaluated the benefits of national-level screening programs and predicted potentially large benefits from increased screening. Subsequent trials and further modeling analyses suggested the impact might have been overestimated. Partner notification has been increasingly evaluated in mathematical modeling, whereas behavioral interventions have received relatively limited attention. Our review provides an overview of chlamydia transmission models and gives a perspective on how mathematical modeling has responded to increasing empirical evidence and addressed policy questions related to prevention of chlamydia infection and sequelae.

A guide to differences between stochastic point-source and stochastic finite-fault simulations

USGS Publications Warehouse

Atkinson, G.M.; Assatourians, K.; Boore, D.M.; Campbell, K.; Motazedian, D.

2009-01-01

Why do stochastic point-source and finite-fault simulation models not agree on the predicted ground motions for moderate earthquakes at large distances? This question was posed by Ken Campbell, who attempted to reproduce the Atkinson and Boore (2006) ground-motion prediction equations for eastern North America using the stochastic point-source program SMSIM (Boore, 2005) in place of the finite-source stochastic program EXSIM (Motazedian and Atkinson, 2005) that was used by Atkinson and Boore (2006) in their model. His comparisons suggested that a higher stress drop is needed in the context of SMSIM to produce an average match, at larger distances, with the model predictions of Atkinson and Boore (2006) based on EXSIM; this is so even for moderate magnitudes, which should be well-represented by a point-source model. Why? The answer to this question is rooted in significant differences between point-source and finite-source stochastic simulation methodologies, specifically as implemented in SMSIM (Boore, 2005) and EXSIM (Motazedian and Atkinson, 2005) to date. Point-source and finite-fault methodologies differ in general in several important ways: (1) the geometry of the source; (2) the definition and application of duration; and (3) the normalization of finite-source subsource summations. Furthermore, the specific implementation of the methods may differ in their details. The purpose of this article is to provide a brief overview of these differences, their origins, and implications. This sets the stage for a more detailed companion article, "Comparing Stochastic Point-Source and Finite-Source Ground-Motion Simulations: SMSIM and EXSIM," in which Boore (2009) provides modifications and improvements in the implementations of both programs that narrow the gap and result in closer agreement. These issues are important because both SMSIM and EXSIM have been widely used in the development of ground-motion prediction equations and in modeling the parameters that control observed ground motions.

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

Computational understanding of Li-ion batteries

NASA Astrophysics Data System (ADS)

Urban, Alexander; Seo, Dong-Hwa; Ceder, Gerbrand

2016-03-01

Over the last two decades, computational methods have made tremendous advances, and today many key properties of lithium-ion batteries can be accurately predicted by first principles calculations. For this reason, computations have become a cornerstone of battery-related research by providing insight into fundamental processes that are not otherwise accessible, such as ionic diffusion mechanisms and electronic structure effects, as well as a quantitative comparison with experimental results. The aim of this review is to provide an overview of state-of-the-art ab initio approaches for the modelling of battery materials. We consider techniques for the computation of equilibrium cell voltages, 0-Kelvin and finite-temperature voltage profiles, ionic mobility and thermal and electrolyte stability. The strengths and weaknesses of different electronic structure methods, such as DFT+U and hybrid functionals, are discussed in the context of voltage and phase diagram predictions, and we review the merits of lattice models for the evaluation of finite-temperature thermodynamics and kinetics. With such a complete set of methods at hand, first principles calculations of ordered, crystalline solids, i.e., of most electrode materials and solid electrolytes, have become reliable and quantitative. However, the description of molecular materials and disordered or amorphous phases remains an important challenge. We highlight recent exciting progress in this area, especially regarding the modelling of organic electrolytes and solid-electrolyte interfaces.

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 9: Oceans

NASA Technical Reports Server (NTRS)

Lietzke, K. R.

1974-01-01

The impact of remote sensing upon marine activities and oceanography is presented. The present capabilities of the current Earth Resources Technology Satellite (ERTS-1), as demonstrated by the principal investigators are discussed. Cost savings benefits are quantified in the area of nautical and hygrographic mapping and charting. Benefits are found in aiding coastal zone management and in the fields of weather (marine) prediction, fishery harvesting and management, and potential uses for ocean vegetation. Difficulties in quantification are explained, the primary factor being that remotely sensed information will be of greater benefit as input to forecasting models which have not yet been constructed.

Supporting Energy-Related Societal Applications Using NASA's Satellite and Modeling Data

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Whitlock, C. H.; Chandler, W. S.; Hoell, J. M.; Zhang, T.; Mikovitz, J. C.; Leng, G. S.; Lilienthal, P.

2006-01-01

Improvements to NASA Surface Meteorology and Solar Energy (SSE) web site are now being made through the Prediction of Worldwide Energy Resource (POWER) project under NASA Science Mission Directorate Applied Science Energy Management Program. The purpose of this project is to tailor NASA Science Mission results for energy sector applications and decision support systems. The current status of SSE and research towards upgrading estimates of total, direct and diffuse solar irradiance from NASA satellite measurements and analysis are discussed. Part of this work involves collaborating with partners such as the National Renewable Energy Laboratory (NREL) and the Natural Resources Canada (NRCan). Energy Management and POWER plans including historic, near-term and forecast datasets are also overviewed.

Application of identification techniques to remote manipulator system flight data

NASA Technical Reports Server (NTRS)

Shepard, G. D.; Lepanto, J. A.; Metzinger, R. W.; Fogel, E.

1983-01-01

This paper addresses the application of identification techniques to flight data from the Space Shuttle Remote Manipulator System (RMS). A description of the remote manipulator, including structural and control system characteristics, sensors, and actuators is given. A brief overview of system identification procedures is presented, and the practical aspects of implementing system identification algorithms are discussed. In particular, the problems posed by desampling rate, numerical error, and system nonlinearities are considered. Simulation predictions of damping, frequency, and system order are compared with values identified from flight data to support an evaluation of RMS structural and control system models. Finally, conclusions are drawn regarding the application of identification techniques to flight data obtained from a flexible space structure.

The Global Observing System in the Assimilation Context

NASA Technical Reports Server (NTRS)

Reinecker, Michele M.; Gelaro, R.; Pawson, S.; Reichle, R.; McCarty, W.

2011-01-01

Weather and climate analyses and predictions all rely on the global observing system. However, the observing system, whether atmosphere, ocean, or land surface, yields a diverse set of incomplete observations of the different components of Earth s environment. Data assimilation systems are essential to synthesize the wide diversity of in situ and remotely sensed observations into four-dimensional state estimates by combining the various observations with model-based estimates. Assimilation, or associated tools and products, are also useful in providing guidance for the evolution of the observing system of the future. This paper provides a brief overview of the global observing system and information gleaned through assimilation tools, and presents some evaluations of observing system gaps and issues.

Overview of mechanics of materials branch activities in the computational structures area

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1992-01-01

Base programs and system programs are discussed. The base programs include fundamental research of composites and metals for airframes leading to characterization of advanced materials, models of behavior, and methods for predicting damage tolerance. Results from the base programs support the systems programs, which change as NASA's missions change. The National Aerospace Plane (NASP), Advanced Composites Technology (ACT), Airframe Structural Integrity Program (Aging Aircraft), and High Speed Research (HSR) programs are currently being supported. Airframe durability is one of the key issues in each of these system programs. The base program has four major thrusts, which will be reviewed subsequently. Additionally, several technical highlights will be reviewed for each thrust.

Development and evaluation of a hybrid averaged orbit generator

NASA Technical Reports Server (NTRS)

Mcclain, W. D.; Long, A. C.; Early, L. W.

1978-01-01

A rapid orbit generator based on a first-order application of the Generalized Method of Averaging has been developed for the Research and Development (R&D) version of the Goddard Trajectory Determination System (GTDS). The evaluation of the averaged equations of motion can use both numerically averaged and recursively evaluated, analytically averaged perturbation models. These equations are numerically integrated to obtain the secular and long-period motion. Factors affecting efficient orbit prediction are discussed and guidelines are presented for treatment of each major perturbation. Guidelines for obtaining initial mean elements compatible with the theory are presented. An overview of the orbit generator is presented and comparisons with high precision methods are given.

Evaluation of balloon trajectory forecast routines for GAINS

NASA Astrophysics Data System (ADS)

Collander, R.; Girz, C.

The Global Air-ocean IN-situ System (GAINS) is a global observing system designed to augment current environmental observing and monitoring networks. GAINS is a network of long-duration, stratospheric platforms that carry onboard sensors and hundreds of dropsondes to acquire meteorological, air chemistry, and climate data over oceans and in remote land regions of the globe. Although GAINS platforms will include balloons and Remotely Operated Aircraft (ROA), the scope of this paper is limited to balloon-based platforms. A primary goal of GAINS balloon test flights is post-flight recovery of the balloon shell and payload, which requires information on the expected flight path and landing site prior to launch. Software has been developed for the prediction of the balloon trajectory and landing site, with separate versions written to generate predictions based upon rawinsonde data and model output. Balloon positions are calculated in 1-min increments based on wind data from the closest rawinsonde site or model grid point, given a known launch point, ascent and descent rate and flight duration. For short flights (< 6h), rawinsonde winds interpolated to 10-mb levels are used for trajectory calculations. Predictions for flight durations of 6 to 48h are based upon the initialization and 3 h forecast wind fields from NOAA's global aviation- (AVN) and Rapid Update Cycle (RUC) models. Given a limited number of actual balloon launches, trajectories computed from a chronological series of hourly RUC initializations are used as the baseline for comparison purposes. These baseline trajectories are compared to trajectory predictions from the rawinsonde and model-based versions on a monthly and seasonal basis over a 1-year period (January 1 - December 31, 2001) for flight durations of 3h, 6h and 48h. Predicted trajectories diverge from the baseline path, with the divergence increasing with increasing time. We examine the zonal, meridional and net magnitudes of these deviations, and attempt to determine directional biases in the predictions. This paper gives an overview of the software, including methods employed, physical considerations and limitations, and discusses results of this evaluation.

Why is traditional accounting failing managers?

PubMed

Cokins, G

1998-11-01

This article provides an account of activity-based costing. It presents a general overview of this costing method, lists benefits and key concerns, discusses some of the impediments to its spread, and predicts its increasing use.

South American smoke coverage and flux estimations from the Fire Locating and Modeling of Burning Emissions (FLAMBE') system.

NASA Astrophysics Data System (ADS)

Reid, J. S.; Westphal, D. L.; Christopher, S. A.; Prins, E. M.; Gasso, S.; Reid, E.; Theisen, M.; Schmidt, C. C.; Hunter, J.; Eck, T.

2002-05-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE') project is a joint Navy, NOAA, NASA and university project to integrate satellite products with numerical aerosol models to produce a real time fire and emissions inventory. At the center of the program is the Wildfire Automated Biomass Burning Algorithm (WF ABBA) which provides real-time fire products and the NRL Aerosol Analysis and Prediction System to model smoke transport. In this presentation we give a brief overview of the system and methods, but emphasize new estimations of smoke coverage and emission fluxes from the South American continent. Temporal and smoke patterns compare reasonably well with AERONET and MODIS aerosol optical depth products for the 2000 and 2001 fire seasons. Fluxes are computed by relating NAAPS output fields and MODIS optical depth maps with modeled wind fields. Smoke emissions and transport fluxes out of the continent can then be estimated by perturbing the modeled emissions to gain agreement with the satellite and wind products. Regional smoke emissions are also presented for grass and forest burning.

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

NASA Astrophysics Data System (ADS)

Butchart, Neal; Anstey, James A.; Hamilton, Kevin; Osprey, Scott; McLandress, Charles; Bushell, Andrew C.; Kawatani, Yoshio; Kim, Young-Ha; Lott, Francois; Scinocca, John; Stockdale, Timothy N.; Andrews, Martin; Bellprat, Omar; Braesicke, Peter; Cagnazzo, Chiara; Chen, Chih-Chieh; Chun, Hye-Yeong; Dobrynin, Mikhail; Garcia, Rolando R.; Garcia-Serrano, Javier; Gray, Lesley J.; Holt, Laura; Kerzenmacher, Tobias; Naoe, Hiroaki; Pohlmann, Holger; Richter, Jadwiga H.; Scaife, Adam A.; Schenzinger, Verena; Serva, Federico; Versick, Stefan; Watanabe, Shingo; Yoshida, Kohei; Yukimoto, Seiji

2018-03-01

The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.

Candidate Predictors of Health-Related Quality of Life of Colorectal Cancer Survivors: A Systematic Review

PubMed Central

van der Linden, Bernadette W.A.; Winkels, Renate M.; van Duijnhoven, Fränzel J.; Mols, Floortje; van Roekel, Eline H.; Kampman, Ellen; Beijer, Sandra; Weijenberg, Matty P.

2016-01-01

The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals. Implications for Practice: More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models. PMID:26911406

Wake Vortex Inverse Model User's Guide

NASA Technical Reports Server (NTRS)

Lai, David; Delisi, Donald

2008-01-01

NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B.

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.

2004-01-01

Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.

An overview of aerospace gas turbine technology of relevance to the development of the automotive gas turbine engine

NASA Technical Reports Server (NTRS)

Evans, D. G.; Miller, T. J.

1978-01-01

Technology areas related to gas turbine propulsion systems with potential for application to the automotive gas turbine engine are discussed. Areas included are: system steady-state and transient performance prediction techniques, compressor and turbine design and performance prediction programs and effects of geometry, combustor technology and advanced concepts, and ceramic coatings and materials technology.

Common features of microRNA target prediction tools

PubMed Central

Peterson, Sarah M.; Thompson, Jeffrey A.; Ufkin, Melanie L.; Sathyanarayana, Pradeep; Liaw, Lucy; Congdon, Clare Bates

2014-01-01

The human genome encodes for over 1800 microRNAs (miRNAs), which are short non-coding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one miRNA to target multiple gene transcripts, miRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of miRNA targets is a critical initial step in identifying miRNA:mRNA target interactions for experimental validation. The available tools for miRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to miRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all miRNA target prediction tools, four main aspects of the miRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MiRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output. PMID:24600468

Common features of microRNA target prediction tools.

PubMed

Peterson, Sarah M; Thompson, Jeffrey A; Ufkin, Melanie L; Sathyanarayana, Pradeep; Liaw, Lucy; Congdon, Clare Bates

2014-01-01

The human genome encodes for over 1800 microRNAs (miRNAs), which are short non-coding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one miRNA to target multiple gene transcripts, miRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of miRNA targets is a critical initial step in identifying miRNA:mRNA target interactions for experimental validation. The available tools for miRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to miRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all miRNA target prediction tools, four main aspects of the miRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MiRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.

Nitrogen dynamics in flooded soil systems: an overview on concepts and performance of models.

PubMed

Nurulhuda, Khairudin; Gaydon, Donald S; Jing, Qi; Zakaria, Mohamad P; Struik, Paul C; Keesman, Karel J

2018-02-01

Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multidisciplinary research, and with substantial progress in understanding of N dynamics in flooded soil systems, the objective of this paper is to provide an overview of the modelling concepts and performance of 14 models developed to simulate N dynamics in flooded soil systems. This overview provides breadth of knowledge on the models, and, therefore, is valuable as a first step in the selection of an appropriate model for a specific application. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Calculations of critical misfit and thickness: An overview

NASA Technical Reports Server (NTRS)

Vandermerwe, Jan H.; Jesser, W. A.

1988-01-01

This overview stresses the equilibrium/nonequilibrium nature of the physical properties, as well as the basic properties of the models, used to calculate critical misfit and critical thickness in epitaxy.

Data Quality Control and Maintenance for the Qweak Experiment

NASA Astrophysics Data System (ADS)

Heiner, Nicholas; Spayde, Damon

2014-03-01

The Qweak collaboration seeks to quantify the weak charge of a proton through the analysis of the parity-violating electron asymmetry in elastic electron-proton scattering. The asymmetry is calculated by measuring how many electrons deflect from a hydrogen target at the chosen scattering angle for aligned and anti-aligned electron spins, then evaluating the difference between the numbers of deflections that occurred for both polarization states. The weak charge can then be extracted from this data. Knowing the weak charge will allow us to calculate the electroweak mixing angle for the particular Q2 value of the chosen electrons, which the Standard Model makes a firm prediction for. Any significant deviation from this prediction would be a prime indicator of the existence of physics beyond what the Standard Model describes. After the experiment was conducted at Jefferson Lab, collected data was stored within a MySQL database for further analysis. I will present an overview of the database and its functions as well as a demonstration of the quality checks and maintenance performed on the data itself. These checks include an analysis of errors occurring throughout the experiment, specifically data acquisition errors within the main detector array, and an analysis of data cuts.

Survey of Recent Results from the PHOBOS Experiment at RHIC

NASA Astrophysics Data System (ADS)

Roland, Christof; Back, B. B.; Baker, M. D.; Barton, D. S.; Betts, R. R.; Ballintijn, M.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Decowski, M. P.; Garcia, E.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Hołyński, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Michałowski, J.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sarin, P.; Sawicki, P.; Skulski, W.; Steadman, S. G.; Steinberg, P.; Stephans, G. S. F.; Stodulski, M.; Sukhanov, A.; Tang, J.-L.; Teng, R.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Verdier, R.; Wadsworth, B.; Wolfs, F. L. H.; Wosiek, B.; Woźniak, K.; Wuosmaa, A. H.; Wysłouch, B.

2002-10-01

We present an overview of the latest results for interactions of Au+Au ions at center-of-mass energies of √SNN of 56, 130 and 200 GeV obtained by the PHOBOS collaboration at the Relativistic Heavy Ion Collider (RHIC). These data have allowed us to perform an extensive study of the pseudorapidity density of primary charged particles as a function of incident energy, centrality and pseudorapidity. Our results show a non-trivial evolution of particle densities with both centrality and collision energy, reaching significantly higher values per participating nucleon than at lower energies or in nucleon-nucleon collisions. Further we present results on the azimuthal asymmetry of particle production observed in the √SNN of 130 GeV data set. The observed strong event anisotropy of v2max > 0.06, reaching beyond the value predicted in hadronic cascade models, indicates a closer approach to local thermal equilibration than at lower collision energies. The measured antiparticle-particle ratios of production rates for pions kaons and protons in central Au+Au interactions at √SNN of 130 GeV are compatible with predictions from statistical models, showing an approach to a baryon free region in mid-rapidity with the increase in collision energy.

Flight motor set 360L009 (STS-36). Volume 1: System overview

NASA Technical Reports Server (NTRS)

Garecht, Diane M.

1990-01-01

Flight Motor Set 360L009, as part of NASA Space Shuttle Mission STS-36, a Department of Defence mission, was launched after two launch attempts. One launch was scrubbed following the failure of a ground-based Range Safety computer and one was scrubbed due to cloud cover at the return to launch landing site. As with all previous redesigned solid rocket motor launches, overall motor performance was excellent. There were no debris concerns from either motor. All ballistic and mass property parameters that could be assessed, closely matched the predicted values and were well within the required contract item specification levels. All field joint heaters and igniter joint heaters performed without anomalies. Evaluation of the ground environment instrumentation measurements again verified thermal model analysis data and showed agreement with predicted environmental effects. No launch commit criteria violations occurred. Postflight inspection again verified nominal performance of the insulation, phenolics, metal parts, and seals. Postflight evaluation indicated that both nozzles performed as expected during flight. All combustion gas was contained by insulation in the field and case-to-nozzle joints. Recommendations were made concerning improved thermal modeling and measurements. The rationale for these recommendations and complete result details are presented.

Overview of MST Research

NASA Astrophysics Data System (ADS)

Sarff, J. S.

2016-10-01

MST progress in advancing the RFP for (1) fusion plasma confinement with ohmic heating and minimal external magnetization, (2) predictive capability in toroidal confinement physics, and (3) basic plasma physics is summarized. Validation of key plasma models is a program priority. Programmable power supplies (PPS) are being developed to maximize inductive capability. Well-controlled flattops with current as low as 0.02 MA are produced with an existing PPS, and Ip <= 0.8 MA is anticipated with a second PPS under construction. The Lundquist number spans S =10(4 - 9) for 0.02-0.8 MA, allowing nonlinear MHD validation using NIMROD and DEBS at low S to be connected to highest S experiments. The PPS also enables MST tokamak operation for studying transients and runaway electron suppression with RMPs. Gyrokinetic modeling with GENE predicts unstable TEM in improved-confinement plasmas. Fluctuations are measured with TEM properties including a density-gradient threshold larger than for tokamak plasmas. Probe measurements hint that drift waves are also excited via the turbulent cascade in standard RFP plasmas. Turbulent energization of an electron tail occurs during sawtooth reconnection. New diagnostics are being developed to measure the energetic ion profile and transport from EP instabilities with NBI. Supported by US DoE and NSF.

Immunoglobulin E mediated food allergy.Modelling and application of diagnostic and predictive tests for existing and novel foods.

PubMed

Elizabeth I Opara Sarah L Oehlschlager A Bryan Hanley

1998-01-01

It is known that some foods cause an allergenic response in certain individuals. Clinical and immunological tests are available for the diagnosis of food allergy and identification of food allergens. However, there are no valid tests for the prediction of the allergenic potential of foods not normally recognized as allergenic. Such foods include: food products developed from foods which may not be recognizable as allergenic in their modified forms; foods produced using novel processes (novel foods), for example genetically modified foods; and foods not normally consumed but that are being used increasingly as alternatives to more traditional foods. Both the risks associated with food allergy and the fact that foods such as the ones described above will become available to the consumer, highlight the need for methods to screen for potential food allergens. This review provides a general overview of food allergy including mechanism, development and prevalence, but focuses on and discusses: 1) the possible risks (with specific reference to food allergy) associated with new and novel foods; and 2) the development/use of food allergy models (in vivo and in vitro) to assess the allergenic potential of new and novel foods.

Advanced decision support for winter road maintenance

DOT National Transportation Integrated Search

2008-01-01

This document provides an overview of the Federal Highway Administration's winter Maintenance Decision Support System (MDSS). The MDSS is a decision support tool that has the ability to provide weather predictions focused toward the road surface. The...

An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

PubMed Central

Majarena, Ana C.; Santolaria, Jorge; Samper, David; Aguilar, Juan J.

2010-01-01

This paper presents an overview of the literature on kinematic and calibration models of parallel mechanisms, the influence of sensors in the mechanism accuracy and parallel mechanisms used as sensors. The most relevant classifications to obtain and solve kinematic models and to identify geometric and non-geometric parameters in the calibration of parallel robots are discussed, examining the advantages and disadvantages of each method, presenting new trends and identifying unsolved problems. This overview tries to answer and show the solutions developed by the most up-to-date research to some of the most frequent questions that appear in the modelling of a parallel mechanism, such as how to measure, the number of sensors and necessary configurations, the type and influence of errors or the number of necessary parameters. PMID:22163469

The impact of natural aging on computational and neural indices of perceptual decision making: A review.

PubMed

Dully, Jessica; McGovern, David P; O'Connell, Redmond G

2018-02-10

It is well established that natural aging negatively impacts on a wide variety of cognitive functions and research has sought to identify core neural mechanisms that may account for these disparate changes. A central feature of any cognitive task is the requirement to translate sensory information into an appropriate action - a process commonly known as perceptual decision making. While computational, psychophysical, and neurophysiological research has made substantial progress in establishing the key computations and neural mechanisms underpinning decision making, it is only relatively recently that this knowledge has begun to be applied to research on aging. The purpose of this review is to provide an overview of this work which is beginning to offer new insights into the core psychological processes that mediate age-related cognitive decline in adults aged 65 years and over. Mathematical modelling studies have consistently reported that older adults display longer non-decisional processing times and implement more conservative decision policies than their younger counterparts. However, there are limits on what we can learn from behavioural modeling alone and neurophysiological analyses can play an essential role in empirically validating model predictions and in pinpointing the precise neural mechanisms that are impacted by aging. Although few studies to date have explicitly examined correspondences between computational models and neural data with respect to cognitive aging, neurophysiological studies have already highlighted age-related changes at multiple levels of the sensorimotor hierarchy that are likely to be consequential for decision making behaviour. Here, we provide an overview of this literature and suggest some future directions for the field. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

An Overview of Literature Topics Related to Current Concepts, Methods, Tools, and Applications for Cumulative Risk Assessment (2007-2016).

PubMed

Fox, Mary A; Brewer, L Elizabeth; Martin, Lawrence

2017-04-07

Cumulative risk assessments (CRAs) address combined risks from exposures to multiple chemical and nonchemical stressors and may focus on vulnerable communities or populations. Significant contributions have been made to the development of concepts, methods, and applications for CRA over the past decade. Work in both human health and ecological cumulative risk has advanced in two different contexts. The first context is the effects of chemical mixtures that share common modes of action, or that cause common adverse outcomes. In this context two primary models are used for predicting mixture effects, dose addition or response addition. The second context is evaluating the combined effects of chemical and nonchemical (e.g., radiation, biological, nutritional, economic, psychological, habitat alteration, land-use change, global climate change, and natural disasters) stressors. CRA can be adapted to address risk in many contexts, and this adaptability is reflected in the range in disciplinary perspectives in the published literature. This article presents the results of a literature search and discusses a range of selected work with the intention to give a broad overview of relevant topics and provide a starting point for researchers interested in CRA applications.

An Overview of Literature Topics Related to Current Concepts, Methods, Tools, and Applications for Cumulative Risk Assessment (2007–2016)

PubMed Central

Fox, Mary A.; Brewer, L. Elizabeth; Martin, Lawrence

2017-01-01

Cumulative risk assessments (CRAs) address combined risks from exposures to multiple chemical and nonchemical stressors and may focus on vulnerable communities or populations. Significant contributions have been made to the development of concepts, methods, and applications for CRA over the past decade. Work in both human health and ecological cumulative risk has advanced in two different contexts. The first context is the effects of chemical mixtures that share common modes of action, or that cause common adverse outcomes. In this context two primary models are used for predicting mixture effects, dose addition or response addition. The second context is evaluating the combined effects of chemical and nonchemical (e.g., radiation, biological, nutritional, economic, psychological, habitat alteration, land-use change, global climate change, and natural disasters) stressors. CRA can be adapted to address risk in many contexts, and this adaptability is reflected in the range in disciplinary perspectives in the published literature. This article presents the results of a literature search and discusses a range of selected work with the intention to give a broad overview of relevant topics and provide a starting point for researchers interested in CRA applications. PMID:28387705

Control-Structure-Interaction (CSI) technologies and trends to future NASA missions

NASA Technical Reports Server (NTRS)

1990-01-01

Control-structure-interaction (CSI) issues which are relevant for future NASA missions are reviewed. This goal was achieved by: (1) reviewing large space structures (LSS) technologies to provide a background and survey of the current state of the art (SOA); (2) analytically studying a focus mission to identify opportunities where CSI technology may be applied to enhance or enable future NASA spacecraft; and (3) expanding a portion of the focus mission, the large antenna, to provide in-depth trade studies, scaling laws, and methodologies which may be applied to other NASA missions. Several sections are presented. Section 1 defines CSI issues and presents an overview of the relevant modeling and control issues for LLS. Section 2 presents the results of the three phases of the CSI study. Section 2.1 gives the results of a CSI study conducted with the Geostationary Platform (Geoplat) as the focus mission. Section 2.2 contains an overview of the CSI control design methodology available in the technical community. Included is a survey of the CSI ground-based experiments which were conducted to verify theoretical performance predictions. Section 2.3 presents and demonstrates a new CSI scaling law methodology for assessing potential CSI with large antenna systems.

Operational Prototype Development of a Global Aircraft Radiation Exposure Nowcast

NASA Astrophysics Data System (ADS)

Mertens, Christopher; Kress, Brian; Wiltberger, Michael; Tobiska, W. Kent; Bouwer, Dave

Galactic cosmic rays (GCR) and solar energetic particles (SEP) are the primary sources of human exposure to high linear energy transfer (LET) radiation in the atmosphere. High-LET radiation is effective at directly breaking DNA strands in biological tissue, or producing chemically active radicals in tissue that alter the cell function, both of which can lead to cancer or other adverse health effects. A prototype operational nowcast model of air-crew radiation exposure is currently under development and funded by NASA. The model predicts air-crew radiation exposure levels from both GCR and SEP that may accompany solar storms. The new air-crew radiation exposure model is called the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) model. NAIRAS will provide global, data-driven, real-time exposure predictions of biologically harmful radiation at aviation altitudes. Observations are utilized from the ground (neutron monitors), from the atmosphere (the NCEP Global Forecast System), and from space (NASA/ACE and NOAA/GOES). Atmospheric observations characterize the overhead mass shielding and the ground-and space-based observations provide boundary conditions on the incident GCR and SEP particle flux distributions for transport and dosimetry calculations. Radiation exposure rates are calculated using the NASA physics-based HZETRN (High Charge (Z) and Energy TRaNsport) code. An overview of the NAIRAS model is given: the concept, design, prototype implementation status, data access, and example results. Issues encountered thus far and known and/or anticipated hurdles to research to operations transition are also discussed.

Development and Use of Engineering Standards for Computational Fluid Dynamics for Complex Aerospace Systems

NASA Technical Reports Server (NTRS)

Lee, Hyung B.; Ghia, Urmila; Bayyuk, Sami; Oberkampf, William L.; Roy, Christopher J.; Benek, John A.; Rumsey, Christopher L.; Powers, Joseph M.; Bush, Robert H.; Mani, Mortaza

2016-01-01

Computational fluid dynamics (CFD) and other advanced modeling and simulation (M&S) methods are increasingly relied on for predictive performance, reliability and safety of engineering systems. Analysts, designers, decision makers, and project managers, who must depend on simulation, need practical techniques and methods for assessing simulation credibility. The AIAA Guide for Verification and Validation of Computational Fluid Dynamics Simulations (AIAA G-077-1998 (2002)), originally published in 1998, was the first engineering standards document available to the engineering community for verification and validation (V&V) of simulations. Much progress has been made in these areas since 1998. The AIAA Committee on Standards for CFD is currently updating this Guide to incorporate in it the important developments that have taken place in V&V concepts, methods, and practices, particularly with regard to the broader context of predictive capability and uncertainty quantification (UQ) methods and approaches. This paper will provide an overview of the changes and extensions currently underway to update the AIAA Guide. Specifically, a framework for predictive capability will be described for incorporating a wide range of error and uncertainty sources identified during the modeling, verification, and validation processes, with the goal of estimating the total prediction uncertainty of the simulation. The Guide's goal is to provide a foundation for understanding and addressing major issues and concepts in predictive CFD. However, this Guide will not recommend specific approaches in these areas as the field is rapidly evolving. It is hoped that the guidelines provided in this paper, and explained in more detail in the Guide, will aid in the research, development, and use of CFD in engineering decision-making.

Data-driven Applications for the Sun-Earth System

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.

2016-12-01

Advances in observational and data mining techniques allow extracting information from the large volume of Sun-Earth observational data that can be assimilated into first principles physical models. However, equations governing Sun-Earth phenomena are typically nonlinear, complex, and high-dimensional. The high computational demand of solving the full governing equations over a large range of scales precludes the use of a variety of useful assimilative tools that rely on applied mathematical and statistical techniques for quantifying uncertainty and predictability. Effective use of such tools requires the development of computationally efficient methods to facilitate fusion of data with models. This presentation will provide an overview of various existing as well as newly developed data-driven techniques adopted from atmospheric and oceanic sciences that proved to be useful for space physics applications, such as computationally efficient implementation of Kalman Filter in radiation belts modeling, solar wind gap-filling by Singular Spectrum Analysis, and low-rank procedure for assimilation of low-altitude ionospheric magnetic perturbations into the Lyon-Fedder-Mobarry (LFM) global magnetospheric model. Reduced-order non-Markovian inverse modeling and novel data-adaptive decompositions of Sun-Earth datasets will be also demonstrated.

The Los Alamos suite of relativistic atomic physics codes

DOE PAGES

Fontes, C. J.; Zhang, H. L.; Jr, J. Abdallah; ...

2015-05-28

The Los Alamos SuitE of Relativistic (LASER) atomic physics codes is a robust, mature platform that has been used to model highly charged ions in a variety of ways. The suite includes capabilities for calculating data related to fundamental atomic structure, as well as the processes of photoexcitation, electron-impact excitation and ionization, photoionization and autoionization within a consistent framework. These data can be of a basic nature, such as cross sections and collision strengths, which are useful in making predictions that can be compared with experiments to test fundamental theories of highly charged ions, such as quantum electrodynamics. The suitemore » can also be used to generate detailed models of energy levels and rate coefficients, and to apply them in the collisional-radiative modeling of plasmas over a wide range of conditions. Such modeling is useful, for example, in the interpretation of spectra generated by a variety of plasmas. In this work, we provide a brief overview of the capabilities within the Los Alamos relativistic suite along with some examples of its application to the modeling of highly charged ions.« less

Using remote sensing and machine learning for the spatial modelling of a bluetongue virus vector

NASA Astrophysics Data System (ADS)

Van doninck, J.; Peters, J.; De Baets, B.; Ducheyne, E.; Verhoest, N. E. C.

2012-04-01

Bluetongue is a viral vector-borne disease transmitted between hosts, mostly cattle and small ruminants, by some species of Culicoides midges. Within the Mediterranean basin, C. imicola is the main vector of the bluetongue virus. The spatial distribution of this species is limited by a number of environmental factors, including temperature, soil properties and land cover. The identification of zones at risk of bluetongue outbreaks thus requires detailed information on these environmental factors, as well as appropriate epidemiological modelling techniques. We here give an overview of the environmental factors assumed to be constraining the spatial distribution of C. imicola, as identified in different studies. Subsequently, remote sensing products that can be used as proxies for these environmental constraints are presented. Remote sensing data are then used together with species occurrence data from the Spanish Bluetongue National Surveillance Programme to calibrate a supervised learning model, based on Random Forests, to model the probability of occurrence of the C. imicola midge. The model will then be applied for a pixel-based prediction over the Iberian peninsula using remote sensing products for habitat characterization.

Mathematical, Constitutive and Numerical Modelling of Catastrophic Landslides and Related Phenomena

NASA Astrophysics Data System (ADS)

Pastor, M.; Fernández Merodo, J. A.; Herreros, M. I.; Mira, P.; González, E.; Haddad, B.; Quecedo, M.; Tonni, L.; Drempetic, V.

2008-02-01

Mathematical and numerical models are a fundamental tool for predicting the behaviour of geostructures and their interaction with the environment. The term “mathematical model” refers to a mathematical description of the more relevant physical phenomena which take place in the problem being analyzed. It is indeed a wide area including models ranging from the very simple ones for which analytical solutions can be obtained to those more complicated requiring the use of numerical approximations such as the finite element method. During the last decades, mathematical, constitutive and numerical models have been very much improved and today their use is widespread both in industry and in research. One special case is that of fast catastrophic landslides, for which simplified methods are not able to provide accurate solutions in many occasions. Moreover, many finite element codes cannot be applied for propagation of the mobilized mass. The purpose of this work is to present an overview of the different alternative mathematical and numerical models which can be applied to both the initiation and propagation mechanisms of fast catastrophic landslides and other related problems such as waves caused by landslides.

Wind power forecasting: IEA Wind Task 36 & future research issues

NASA Astrophysics Data System (ADS)

Giebel, G.; Cline, J.; Frank, H.; Shaw, W.; Pinson, P.; Hodge, B.-M.; Kariniotakis, G.; Madsen, J.; Möhrlen, C.

2016-09-01

This paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.

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

Giebel, G.; Cline, J.; Frank, H.

Here, this paper presents the new International Energy Agency Wind Task 36 on Forecasting, and invites to collaborate within the group. Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, MetOffice, met.no, DMI,...), operational forecaster and forecast users. The Taskmore » is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. As first results, an overview of current issues for research in short-term forecasting of wind power is presented.« less

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory.

PubMed

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2014-12-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory's predictions about reliance on gist processing.

Single-polymer dynamics under constraints: scaling theory and computer experiment.

PubMed

Milchev, Andrey

2011-03-16

The relaxation, diffusion and translocation dynamics of single linear polymer chains in confinement is briefly reviewed with emphasis on the comparison between theoretical scaling predictions and observations from experiment or, most frequently, from computer simulations. Besides cylindrical, spherical and slit-like constraints, related problems such as the chain dynamics in a random medium and the translocation dynamics through a nanopore are also considered. Another particular kind of confinement is imposed by polymer adsorption on attractive surfaces or selective interfaces--a short overview of single-chain dynamics is also contained in this survey. While both theory and numerical experiments consider predominantly coarse-grained models of self-avoiding linear chain molecules with typically Rouse dynamics, we also note some recent studies which examine the impact of hydrodynamic interactions on polymer dynamics in confinement. In all of the aforementioned cases we focus mainly on the consequences of imposed geometric restrictions on single-chain dynamics and try to check our degree of understanding by assessing the agreement between theoretical predictions and observations.

An Overview of Judgment and Decision Making Research Through the Lens of Fuzzy Trace Theory

PubMed Central

Setton, Roni; Wilhelms, Evan; Weldon, Becky; Chick, Christina; Reyna, Valerie

2017-01-01

We present the basic tenets of fuzzy trace theory, a comprehensive theory of memory, judgment, and decision making that is grounded in research on how information is stored as knowledge, mentally represented, retrieved from storage, and processed. In doing so, we highlight how it is distinguished from traditional models of decision making in that gist reasoning plays a central role. The theory also distinguishes advanced intuition from primitive impulsivity. It predicts that different sorts of errors occur with respect to each component of judgment and decision making: background knowledge, representation, retrieval, and processing. Classic errors in the judgment and decision making literature, such as risky-choice framing and the conjunction fallacy, are accounted for by fuzzy trace theory and new results generated by the theory contradict traditional approaches. We also describe how developmental changes in brain and behavior offer crucial insight into adult cognitive processing. Research investigating brain and behavior in developing and special populations supports fuzzy trace theory’s predictions about reliance on gist processing. PMID:28725239

Evidence-based pain management: is the concept of integrative medicine applicable?

PubMed Central

2012-01-01

This article is dedicated to the concept of predictive, preventive, and personalized (integrative) medicine beneficial and applicable to advance pain management, overviews recent insights, and discusses novel minimally invasive tools, performed under ultrasound guidance, enhanced by model-guided approach in the field of musculoskeletal pain and neuromuscular diseases. The complexity of pain emergence and regression demands intellectual-, image-guided techniques personally specified to the patient. For personalized approach, the combination of the modalities of ultrasound, EMG, MRI, PET, and SPECT gives new opportunities to experimental and clinical studies. Neuromuscular imaging should be crucial for emergence of studies concerning advanced neuroimaging technologies to predict movement disorders, postural imbalance with integrated application of imaging, and functional modalities for rehabilitation and pain management. Scientific results should initiate evidence-based preventive movement programs in sport medicine rehabilitation. Traditional medicine and mathematical analytical approaches and education challenges are discussed in this review. The physiological management of exactly assessed pathological condition, particularly in movement disorders, requires participative medical approach to gain harmonized and sustainable effect. PMID:23088743

The Formation of the Earth-Moon System and the Planets

NASA Technical Reports Server (NTRS)

Lissauer, Jack J.; Young, Richard E. (Technical Monitor)

1998-01-01

An overview of current theories of star and planet formation, with emphasis on terrestrial planet accretion and the formation of the Earth-Moon system 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 impacts during the final stages of growth can produce large planetary satellites, such as Earth's Moon. 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.

Flight-determined engine exhaust characteristics of an F404 engine in an F-18 airplane

NASA Technical Reports Server (NTRS)

Ennix, Kimberly A.; Burcham, Frank W., Jr.; Webb, Lannie D.

1993-01-01

Personnel at the NASA Langley Research Center (NASA-Langley) and the NASA Dryden Flight Research Facility (NASA-Dryden) recently completed a joint acoustic flight test program. Several types of aircraft with high nozzle pressure ratio engines were flown to satisfy a twofold objective. First, assessments were made of subsonic climb-to-cruise noise from flights conducted at varying altitudes in a Mach 0.30 to 0.90 range. Second, using data from flights conducted at constant altitude in a Mach 0.30 to 0.95 range, engineers obtained a high quality noise database. This database was desired to validate the Aircraft Noise Prediction Program and other system noise prediction codes. NASA-Dryden personnel analyzed the engine data from several aircraft that were flown in the test program to determine the exhaust characteristics. The analysis of the exhaust characteristics from the F-18 aircraft are reported. An overview of the flight test planning, instrumentation, test procedures, data analysis, engine modeling codes, and results are presented.

Endocrine disrupting chemicals in fish: developing exposure indicators and predictive models of effects based on mechanism of action.

PubMed

Ankley, Gerald T; Bencic, David C; Breen, Michael S; Collette, Timothy W; Conolly, Rory B; Denslow, Nancy D; Edwards, Stephen W; Ekman, Drew R; Garcia-Reyero, Natalia; Jensen, Kathleen M; Lazorchak, James M; Martinović, Dalma; Miller, David H; Perkins, Edward J; Orlando, Edward F; Villeneuve, Daniel L; Wang, Rong-Lin; Watanabe, Karen H

2009-05-05

Knowledge of possible toxic mechanisms (or modes) of action (MOA) of chemicals can provide valuable insights as to appropriate methods for assessing exposure and effects, thereby reducing uncertainties related to extrapolation across species, endpoints and chemical structure. However, MOA-based testing seldom has been used for assessing the ecological risk of chemicals. This is in part because past regulatory mandates have focused more on adverse effects of chemicals (reductions in survival, growth or reproduction) than the pathways through which these effects are elicited. A recent departure from this involves endocrine-disrupting chemicals (EDCs), where there is a need to understand both MOA and adverse outcomes. To achieve this understanding, advances in predictive approaches are required whereby mechanistic changes caused by chemicals at the molecular level can be translated into apical responses meaningful to ecological risk assessment. In this paper we provide an overview and illustrative results from a large, integrated project that assesses the effects of EDCs on two small fish models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio). For this work a systems-based approach is being used to delineate toxicity pathways for 12 model EDCs with different known or hypothesized toxic MOA. The studies employ a combination of state-of-the-art genomic (transcriptomic, proteomic, metabolomic), bioinformatic and modeling approaches, in conjunction with whole animal testing, to develop response linkages across biological levels of organization. This understanding forms the basis for predictive approaches for species, endpoint and chemical extrapolation. Although our project is focused specifically on EDCs in fish, we believe that the basic conceptual approach has utility for systematically assessing exposure and effects of chemicals with other MOA across a variety of biological systems.

Overview of an internationally-harmonized program for adverse outcome pathway development

EPA Science Inventory

Adverse outcome pathways (AOPs) are critical frameworks for organizing knowledge concerning the scientifically-credible predictive linkages between toxicological observations made at molecular and cellular levels (e.g., via molecular screening assays, biomarker responses, or chem...

Use of randomized sampling for analysis of metabolic networks.

PubMed

Schellenberger, Jan; Palsson, Bernhard Ø

2009-02-27

Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise in analyzing the systemic properties of these network reconstructions. Notably, constraint-based models have been used successfully to predict the phenotypic effects of knock-outs and for metabolic engineering. The inherent uncertainty in both parameters and variables of large-scale models is significant and is well suited to study by Monte Carlo sampling of the solution space. These techniques have been applied extensively to the reaction rate (flux) space of networks, with more recent work focusing on dynamic/kinetic properties. Monte Carlo sampling as an analysis tool has many advantages, including the ability to work with missing data, the ability to apply post-processing techniques, and the ability to quantify uncertainty and to optimize experiments to reduce uncertainty. We present an overview of this emerging area of research in systems biology.

Review of Trackside Monitoring Solutions: From Strain Gages to Optical Fibre Sensors

PubMed Central

Kouroussis, Georges; Caucheteur, Christophe; Kinet, Damien; Alexandrou, Georgios; Verlinden, Olivier; Moeyaert, Véronique

2015-01-01

A review of recent research on structural monitoring in railway industry is proposed in this paper, with a special focus on stress-based solutions. After a brief analysis of the mechanical behaviour of ballasted railway tracks, an overview of the most common monitoring techniques is presented. A special attention is paid on strain gages and accelerometers for which the accurate mounting position on the track is requisite. These types of solution are then compared to another modern approach based on the use of optical fibres. Besides, an in-depth discussion is made on the evolution of numerical models that investigate the interaction between railway vehicles and tracks. These models are used to validate experimental devices and to predict the best location(s) of the sensors. It is hoped that this review article will stimulate further research activities in this continuously expanding field. PMID:26287207

Non-clinical studies required for new drug development - Part I: early in silico and in vitro studies, new target discovery and validation, proof of principles and robustness of animal studies.

PubMed

Andrade, E L; Bento, A F; Cavalli, J; Oliveira, S K; Freitas, C S; Marcon, R; Schwanke, R C; Siqueira, J M; Calixto, J B

2016-10-24

This review presents a historical overview of drug discovery and the non-clinical stages of the drug development process, from initial target identification and validation, through in silico assays and high throughput screening (HTS), identification of leader molecules and their optimization, the selection of a candidate substance for clinical development, and the use of animal models during the early studies of proof-of-concept (or principle). This report also discusses the relevance of validated and predictive animal models selection, as well as the correct use of animal tests concerning the experimental design, execution and interpretation, which affect the reproducibility, quality and reliability of non-clinical studies necessary to translate to and support clinical studies. Collectively, improving these aspects will certainly contribute to the robustness of both scientific publications and the translation of new substances to clinical development.

The influence of wing, fuselage and tail design on rotational flow aerodynamics data obtained beyond maximum lift with general aviation configurations

NASA Technical Reports Server (NTRS)

Bihrle, W., Jr.; Bowman, J. S., Jr.

1980-01-01

The NASA Langley Research Center has initiated a broad general aviation stall/spin research program. A rotary balance system was developed to support this effort. Located in the Langley spin tunnel, this system makes it possible to identify an airplane's aerodynamic characteristics in a rotational flow environment, and thereby permits prediction of spins. This paper presents a brief description of the experimental set-up, testing technique, five model programs conducted to date, and an overview of the rotary balance results and their correlation with spin tunnel free-spinning model results. It is shown, for example, that there is a large, nonlinear dependency of the aerodynamic moments on rotational rate and that these moments are pronouncedly configuration-dependent. Fuselage shape, horizontal tail and, in some instances, wing location are shown to appreciably influence the yawing moment characteristics above an angle of attack of 45 deg.

Overview of the United States Department of Energy's ARM (Atmospheric Radiation Measurement) Program

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

Stokes, G.M.; Tichler, J.L.

The Department of Energy (DOE) is initiating a major atmospheric research effort, the Atmospheric Radiation Measurement Program (ARM). The program is a key component of DOE's research strategy to address global climate change and is a direct continuation of DOE's decade-long effort to improve the ability of General Circulation Models (GCMs) to provide reliable simulations of regional, and long-term climate change in response to increasing greenhouse gases. The effort is multi-disciplinary and multi-agency, involving universities, private research organizations and more than a dozen government laboratories. The objective of the ARM Research is to provide an experimental testbed for the studymore » of important atmospheric effects, particularly cloud and radiative processes, and to test parameterizations of these processes for use in atmospheric models. This effort will support the continued and rapid improvement of GCM predictive capability. 2 refs.« less

Analysis Methods for Progressive Damage of Composite Structures

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Davila, Carlos G.; Leone, Frank A.

2013-01-01

This document provides an overview of recent accomplishments and lessons learned in the development of general progressive damage analysis methods for predicting the residual strength and life of composite structures. These developments are described within their State-of-the-Art (SoA) context and the associated technology barriers. The emphasis of the authors is on developing these analysis tools for application at the structural level. Hence, modeling of damage progression is undertaken at the mesoscale, where the plies of a laminate are represented as a homogenous orthotropic continuum. The aim of the present effort is establish the ranges of validity of available models, to identify technology barriers, and to establish the foundations of the future investigation efforts. Such are the necessary steps towards accurate and robust simulations that can replace some of the expensive and time-consuming "building block" tests that are currently required for the design and certification of aerospace structures.

Energy-level alignment at organic heterointerfaces

PubMed Central

Oehzelt, Martin; Akaike, Kouki; Koch, Norbert; Heimel, Georg

2015-01-01

Today’s champion organic (opto-)electronic devices comprise an ever-increasing number of different organic-semiconductor layers. The functionality of these complex heterostructures largely derives from the relative alignment of the frontier molecular-orbital energies in each layer with respect to those in all others. Despite the technological relevance of the energy-level alignment at organic heterointerfaces, and despite continued scientific interest, a reliable model that can quantitatively predict the full range of phenomena observed at such interfaces is notably absent. We identify the limitations of previous attempts to formulate such a model and highlight inconsistencies in the interpretation of the experimental data they were based on. We then develop a theoretical framework, which we demonstrate to accurately reproduce experiment. Applying this theory, a comprehensive overview of all possible energy-level alignment scenarios that can be encountered at organic heterojunctions is finally given. These results will help focus future efforts on developing functional organic interfaces for superior device performance. PMID:26702447

Modeling and Analysis of Wrinkled Membranes: An Overview

NASA Technical Reports Server (NTRS)

Yang, B.; Ding, H.; Lou, M.; Fang, H.; Broduer, Steve (Technical Monitor)

2001-01-01

Thin-film membranes are basic elements of a variety of space inflatable/deployable structures. Wrinkling degrades the performance and reliability of these membrane structures, and hence has been a topic of continued interest. Wrinkling analysis of membranes for general geometry and arbitrary boundary conditions is quite challenging. The objective of this presentation is two-fold. Firstly, the existing models of wrinkled membranes and related numerical solution methods are reviewed. The important issues to be discussed are the capability of a membrane model to characterize taut, wrinkled and slack states of membranes in a consistent and physically reasonable manner; the ability of a wrinkling analysis method to predict the formation and growth of wrinkled regions, and to determine out-of-plane deformation and wrinkled waves; the convergence of a numerical solution method for wrinkling analysis; and the compatibility of a wrinkling analysis with general-purpose finite element codes. According to this review, several opening issues in modeling and analysis of wrinkled membranes that are to be addressed in future research are summarized, The second objective of this presentation is to discuss a newly developed membrane model of two viable parameters (2-VP model) and associated parametric finite element method (PFEM) for wrinkling analysis are introduced. The innovations and advantages of the proposed membrane model and PFEM-based wrinkling analysis are: (1) Via a unified stress-strain relation; the 2-VP model treat the taut, wrinkled, and slack states of membranes consistently; (2) The PFEM-based wrinkling analysis has guaranteed convergence; (3) The 2-VP model along with PFEM is capable of predicting membrane out-of-plane deformations; and (4) The PFEM can be integrated into any existing finite element code. Preliminary numerical examples are also included in this presentation to demonstrate the 2-VP model and PFEM-based wrinkling analysis approach.

Living on the edge: Flood risks to societies Balázs M. Fekete, Shahabeddin Afshari Tork and Charles J. Vörösmarty

NASA Astrophysics Data System (ADS)

Fekete, B. M.; Afshari Tork, S.; Vorosmarty, C. J.

2015-12-01

Characterizing hydrological extreme events and assessing their societal impacts is perpetual challenge for hydrologists. Climate models predict that anticipated temperature rise leads to an intensification of the hydrological cycle and to a corresponding increase in the reoccurrence and the severity of extreme events. The societal impact of the hydrological extremes are interlinked with anthropogenic activities therefore the damages to manmade infrastructures are rarely a good measure of the extreme events' magnitudes. Extreme events are rare by definition therefore detecting change in their distributions requires long-term observational records. Currently, only in-situ monitoring time series has the temporal extent necessary for assessing the reoccurrence probabilities of extreme events, but they frequently lack the spatial coverage. Satellite remote sensing is often advocated to provide the required spatial coverage, but satellites have to compromise between spatial and temporal resolutions. Furthermore, the retrieval algorithms are often as complex as comparable hydrological models with similar degree of uncertainties in their parameterization and the validity of the final data products. In addition, anticipated changes over time in the reoccurrence frequencies of extreme events invalidates the stationarity assumption, which is the basis for using past observations to predict the probabilities future extreme events. Probably the best approach to provide more robust predictions of extreme events is the integration of the available data (in-situ and remote sensing) in a comprehensive data assimilation frameworks built on top of adequate hydrological modeling platforms. Our presentation will provide an overview of the current state of hydrological models to support data assimilations and the viable pathways to integrate in-situ and remote sensing observations for flood predictions. We will demonstrate the use of socio-economic data in combination with hydrological data assimilation to assess the resiliency to extreme flood events.

Use and interpretation of climate envelope models: a practical guide

USGS Publications Warehouse

Watling, James I.; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

2013-01-01

This guidebook is intended to provide a practical overview of climate envelope modeling for conservation professionals and natural resource managers. The material is intended for people with little background or experience in climate envelope modeling who want to better understand and interpret models developed by others and the results generated by such models, or want to do some modeling themselves. This is not an exhaustive review of climate envelope modeling, but rather a brief introduction to some key concepts in the discipline. Readers interested in a more in-depth treatment of much of the material presented here are referred to an excellent book, Mapping Species Distributions: Spatial Inference and Prediction by Janet Franklin. Also, a recent review (Araújo & Peterson 2012) provides an excellent, though more technical, discussion of many of the issues dealt with here. Here we treat selected topics from a practical perspective, using minimal jargon to explain and illustrate some of the many issues that one has to be aware of when using climate envelope models. When we do introduce specialized terminology in the guidebook, we bold the term when it is first used; a glossary of these terms is included at the back of the guidebook.

Key Issues in the Production of Ionospheric Outflows

NASA Astrophysics Data System (ADS)

Lotko, W.

2017-12-01

Global models demonstrate that outflows of ionospheric ions can have profound effects on the dynamics of the solar wind-magnetosphere-ionosphere-thermosphere system, particularly during geomagnetic storms. Yet the processes that determine where and when outflows occur are poorly understood, in large part because a full complement of critical multivariable measurements of outflows and their causal drivers has yet to be assembled. Development of accurate regional and global predictive models of outflows has been hampered by this lack of empirical knowledge, but models are also challenged by the additional requirement of having to reduce the complex microphysics of ion energization into lumped relations that specify outflow characteristics through causal regulators. Opportunities to improve understanding of this problem are vast. This overview will focus on a limited set of priority questions that address how ions overcome gravity to leave the ionosphere; the timing, rate, spatial distribution and energetics of their exodus; how their flight impacts the ionosphere-thermosphere environment that spawns outflows; and the influence of magnetospheric feedback on outflow production.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger

2008-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A inflight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

The X-43A Six Degree of Freedom Monte Carlo Analysis

NASA Technical Reports Server (NTRS)

Baumann, Ethan; Bahm, Catherine; Strovers, Brian; Beck, Roger; Richard, Michael

2007-01-01

This report provides an overview of the Hyper-X research vehicle Monte Carlo analysis conducted with the six-degree-of-freedom simulation. The methodology and model uncertainties used for the Monte Carlo analysis are presented as permitted. In addition, the process used to select hardware validation test cases from the Monte Carlo data is described. The preflight Monte Carlo analysis indicated that the X-43A control system was robust to the preflight uncertainties and provided the Hyper-X project an important indication that the vehicle would likely be successful in accomplishing the mission objectives. The X-43A in-flight performance is compared to the preflight Monte Carlo predictions and shown to exceed the Monte Carlo bounds in several instances. Possible modeling shortfalls are presented that may account for these discrepancies. The flight control laws and guidance algorithms were robust enough as a result of the preflight Monte Carlo analysis that the unexpected in-flight performance did not have undue consequences. Modeling and Monte Carlo analysis lessons learned are presented.

Computational Aeroelastic Modeling of Airframes and TurboMachinery: Progress and Challenges

NASA Technical Reports Server (NTRS)

Bartels, R. E.; Sayma, A. I.

2006-01-01

Computational analyses such as computational fluid dynamics and computational structural dynamics have made major advances toward maturity as engineering tools. Computational aeroelasticity is the integration of these disciplines. As computational aeroelasticity matures it too finds an increasing role in the design and analysis of aerospace vehicles. This paper presents a survey of the current state of computational aeroelasticity with a discussion of recent research, success and continuing challenges in its progressive integration into multidisciplinary aerospace design. This paper approaches computational aeroelasticity from the perspective of the two main areas of application: airframe and turbomachinery design. An overview will be presented of the different prediction methods used for each field of application. Differing levels of nonlinear modeling will be discussed with insight into accuracy versus complexity and computational requirements. Subjects will include current advanced methods (linear and nonlinear), nonlinear flow models, use of order reduction techniques and future trends in incorporating structural nonlinearity. Examples in which computational aeroelasticity is currently being integrated into the design of airframes and turbomachinery will be presented.

Artificial neural networks in mammography interpretation and diagnostic decision making.

PubMed

Ayer, Turgay; Chen, Qiushi; Burnside, Elizabeth S

2013-01-01

Screening mammography is the most effective means for early detection of breast cancer. Although general rules for discriminating malignant and benign lesions exist, radiologists are unable to perfectly detect and classify all lesions as malignant and benign, for many reasons which include, but are not limited to, overlap of features that distinguish malignancy, difficulty in estimating disease risk, and variability in recommended management. When predictive variables are numerous and interact, ad hoc decision making strategies based on experience and memory may lead to systematic errors and variability in practice. The integration of computer models to help radiologists increase the accuracy of mammography examinations in diagnostic decision making has gained increasing attention in the last two decades. In this study, we provide an overview of one of the most commonly used models, artificial neural networks (ANNs), in mammography interpretation and diagnostic decision making and discuss important features in mammography interpretation. We conclude by discussing several common limitations of existing research on ANN-based detection and diagnostic models and provide possible future research directions.

Life prediction of turbine components: On-going studies at the NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Spera, D. A.; Grisaffe, S. J.

1973-01-01

An overview is presented of the many studies at NASA-Lewis that form the turbine component life prediction program. This program has three phases: (1) development of life prediction methods for major failure modes through materials studies, (2) evaluation and improvement of these methods through a variety of burner rig studies on simulated components in research engines and advanced rigs. These three phases form a cooperative, interdisciplinary program. A bibliography of Lewis publications on fatigue, oxidation and coatings, and turbine engine alloys is included.

Alcohol and Other Drug Prevention: An Overview for Educators: A Description of the Implementation of a Model Course Outline.

ERIC Educational Resources Information Center

Berliner, BethAnn

In the fall of 1991, the Western Regional Center for Drug-Free Schools and communities published "Alcohol and Other Drug Prevention: An Overview for Educators." This model course outline was designed to assist institutes of higher education in offering preservice and continuing education courses for teachers and other educational…

Rotorcraft technology at Boeing Vertol: Recent advances

NASA Technical Reports Server (NTRS)

Shaw, John; Dadone, Leo; Wiesner, Robert

1988-01-01

An overview is presented of key accomplishments in the rotorcraft development at Boeing Vertol. Projects of particular significance: high speed rotor development and the Model 360 Advanced Technology Helicopter. Areas addressed in the overview are: advanced rotors with reduced noise and vibration, 3-D aerodynamic modeling, flight control and avionics, active control, automated diagnostics and prognostics, composite structures, and drive systems.

Overview of the SHIELDS Project at LANL

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

A model approach to assess the long-term trends of indirect photochemistry in lake water. The case of Lake Maggiore (NW Italy).

PubMed

Minella, Marco; Rogora, Michela; Vione, Davide; Maurino, Valter; Minero, Claudio

2011-08-15

A model-based approach is here developed and applied to predict the long-term trends of indirect photochemical processes in the surface layer (5m water depth) of Lake Maggiore, NW Italy. For this lake, time series of the main parameters of photochemical importance that cover almost two decades are available. As a way to assess the relevant photochemical reactions, the modelled steady-state concentrations of important photogenerated transients ((•)OH, ³CDOM* and CO₃(-•)) were taken into account. A multivariate analysis approach was adopted to have an overview of the system, to emphasise relationships among chemical, photochemical and seasonal variables, and to highlight annual and long-term trends. Over the considered time period, because of the decrease of the dissolved organic carbon (DOC) content of water and of the increase of alkalinity, a significant increase is predicted for the steady-state concentrations of the radicals (•)OH and CO₃(-•). Therefore, the photochemical degradation processes that involve the two radical species would be enhanced. Another issue of potential photochemical importance is related to the winter maxima of nitrate (a photochemical (•)OH source) and the summer maxima of DOC ((•)OH sink and ³CDOM* source) in the lake water under consideration. From the combination of sunlight irradiance and chemical composition data, one predicts that the processes involving (•)OH and CO₃(-•) would be most important in spring, while the reactions involving ³CDOM* would be most important in summer. Copyright © 2011 Elsevier B.V. All rights reserved.

W-8 Acoustic Casing Treatment Test Overview

NASA Technical Reports Server (NTRS)

Bozak, Rick; Podboy, Gary; Dougherty, Robert

2017-01-01

During February 2017, aerodynamic and acoustic testing was performed on a scale-model high bypass ratio turbofan rotor, R4, in an internal flow component test facility. An overview of the testing completed is presented.

NASA Standard for Models and Simulations: Philosophy and Requirements Overview

NASA Technical Reports Server (NTRS)

Blattnig, Steve R.; Luckring, James M.; Morrison, Joseph H.; Sylvester, Andre J.; Tripathi, Ram K.; Zang, Thomas A.

2013-01-01

Following the Columbia Accident Investigation Board report, the NASA Administrator chartered an executive team (known as the Diaz Team) to identify those CAIB report elements with NASA-wide applicability and to develop corrective measures to address each element. One such measure was the development of a standard for the development, documentation, and operation of models and simulations. This report describes the philosophy and requirements overview of the resulting NASA Standard for Models and Simulations.

NASA Standard for Models and Simulations: Philosophy and Requirements Overview

NASA Technical Reports Server (NTRS)

Blattnig, St3eve R.; Luckring, James M.; Morrison, Joseph H.; Sylvester, Andre J.; Tripathi, Ram K.; Zang, Thomas A.

2009-01-01

Following the Columbia Accident Investigation Board report, the NASA Administrator chartered an executive team (known as the Diaz Team) to identify those CAIB report elements with NASA-wide applicability and to develop corrective measures to address each element. One such measure was the development of a standard for the development, documentation, and operation of models and simulations. This report describes the philosophy and requirements overview of the resulting NASA Standard for Models and Simulations.

Transient Mathematical Modeling for Liquid Rocket Engine Systems: Methods, Capabilities, and Experience

NASA Technical Reports Server (NTRS)

Seymour, David C.; Martin, Michael A.; Nguyen, Huy H.; Greene, William D.

2005-01-01

The subject of mathematical modeling of the transient operation of liquid rocket engines is presented in overview form from the perspective of engineers working at the NASA Marshall Space Flight Center. The necessity of creating and utilizing accurate mathematical models as part of liquid rocket engine development process has become well established and is likely to increase in importance in the future. The issues of design considerations for transient operation, development testing, and failure scenario simulation are discussed. An overview of the derivation of the basic governing equations is presented along with a discussion of computational and numerical issues associated with the implementation of these equations in computer codes. Also, work in the field of generating usable fluid property tables is presented along with an overview of efforts to be undertaken in the future to improve the tools use for the mathematical modeling process.

Transient Mathematical Modeling for Liquid Rocket Engine Systems: Methods, Capabilities, and Experience

NASA Technical Reports Server (NTRS)

Martin, Michael A.; Nguyen, Huy H.; Greene, William D.; Seymout, David C.

2003-01-01

The subject of mathematical modeling of the transient operation of liquid rocket engines is presented in overview form from the perspective of engineers working at the NASA Marshall Space Flight Center. The necessity of creating and utilizing accurate mathematical models as part of liquid rocket engine development process has become well established and is likely to increase in importance in the future. The issues of design considerations for transient operation, development testing, and failure scenario simulation are discussed. An overview of the derivation of the basic governing equations is presented along with a discussion of computational and numerical issues associated with the implementation of these equations in computer codes. Also, work in the field of generating usable fluid property tables is presented along with an overview of efforts to be undertaken in the future to improve the tools use for the mathematical modeling process.

Overview of the Novel Intelligent JAXA Active Rotor Program

NASA Technical Reports Server (NTRS)

Saito, Shigeru; Kobiki, Noboru; Tanabe, Yasutada; Johnson, Wayne; Yamauchi, Gloria K.; Young, Larry A.

2010-01-01

The Novel Intelligent JAXA Active Rotor (NINJA Rotor) program is a cooperative effort between JAXA and NASA, involving a test of a JAXA pressure-instrumented, active-flap rotor in the 40- by 80-Foot Wind Tunnel at Ames Research Center. The objectives of the program are to obtain an experimental database of a rotor with active flaps and blade pressure instrumentation, and to use that data to develop analyses to predict the aerodynamic and aeroacoustic performance of rotors with active flaps. An overview of the program is presented, including a description of the rotor and preliminary pretest calculations.

Benchmark Dose Software (BMDS) Development and ...

EPA Pesticide Factsheets

This report is intended to provide an overview of beta version 1.0 of the implementation of a model of repeated measures data referred to as the Toxicodiffusion model. The implementation described here represents the first steps towards integration of the Toxicodiffusion model into the EPA benchmark dose software (BMDS). This version runs from within BMDS 2.0 using an option screen for making model selection, as is done for other models in the BMDS 2.0 suite. This report is intended to provide an overview of beta version 1.0 of the implementation of a model of repeated measures data referred to as the Toxicodiffusion model.

The SOFIA Massive (SOMA) Star Formation Survey. I. Overview and First Results

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

De Buizer, James M.; Shuping, Ralph; Liu, Mengyao

We present an overview and first results of the Stratospheric Observatory For Infrared Astronomy Massive (SOMA) Star Formation Survey, which is using the FORCAST instrument to image massive protostars from ∼10 to 40 μ m. These wavelengths trace thermal emission from warm dust, which in Core Accretion models mainly emerges from the inner regions of protostellar outflow cavities. Dust in dense core envelopes also imprints characteristic extinction patterns at these wavelengths, causing intensity peaks to shift along the outflow axis and profiles to become more symmetric at longer wavelengths. We present observational results for the first eight protostars in themore » survey, i.e., multiwavelength images, including some ancillary ground-based mid-infrared (MIR) observations and archival Spitzer and Herschel data. These images generally show extended MIR/FIR emission along directions consistent with those of known outflows and with shorter wavelength peak flux positions displaced from the protostar along the blueshifted, near-facing sides, thus confirming qualitative predictions of Core Accretion models. We then compile spectral energy distributions and use these to derive protostellar properties by fitting theoretical radiative transfer models. Zhang and Tan models, based on the Turbulent Core Model of McKee and Tan, imply the sources have protostellar masses m {sub *} ∼ 10–50 M {sub ⊙} accreting at ∼10{sup −4}–10{sup −3} M {sub ⊙} yr{sup −1} inside cores of initial masses M {sub c} ∼ 30–500 M {sub ⊙} embedded in clumps with mass surface densities Σ{sub cl} ∼ 0.1–3 g cm{sup −2}. Fitting the Robitaille et al. models typically leads to slightly higher protostellar masses, but with disk accretion rates ∼100× smaller. We discuss reasons for these differences and overall implications of these first survey results for massive star formation theories.« less

Osteoarthritis: new insights in animal models.

PubMed

Longo, Umile Giuseppe; Loppini, Mattia; Fumo, Caterina; Rizzello, Giacomo; Khan, Wasim Sardar; Maffulli, Nicola; Denaro, Vincenzo

2012-01-01

Osteoarthritis (OA) is the most frequent and symptomatic health problem in the middle-aged and elderly population, with over one-half of all people over the age of 65 showing radiographic changes in painful knees. The aim of the present study was to perform an overview on the available animal models used in the research field on the OA. Discrepancies between the animal models and the human disease are present. As regards human 'idiopathic' OA, with late onset and slow progression, it is perhaps wise not to be overly enthusiastic about animal models that show severe chondrodysplasia and very early OA. Advantage by using genetically engineered mouse models, in comparison with other surgically induced models, is that molecular etiology is known. Find potential molecular markers for the onset of the disease and pay attention to the role of gender and environmental factors should be very helpful in the study of mice that acquire premature OA. Surgically induced destabilization of joint is the most widely used induction method. These models allow the temporal control of disease induction and follow predictable progression of the disease. In animals, ACL transection and meniscectomy show a speed of onset and severity of disease higher than in humans after same injury.

Definition and solution of a stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models

DOE PAGES

Butler, Troy; Graham, L.; Estep, D.; ...

2015-02-03

The uncertainty in spatially heterogeneous Manning’s n fields is quantified using a novel formulation and numerical solution of stochastic inverse problems for physics-based models. The uncertainty is quantified in terms of a probability measure and the physics-based model considered here is the state-of-the-art ADCIRC model although the presented methodology applies to other hydrodynamic models. An accessible overview of the formulation and solution of the stochastic inverse problem in a mathematically rigorous framework based on measure theory is presented in this paper. Technical details that arise in practice by applying the framework to determine the Manning’s n parameter field in amore » shallow water equation model used for coastal hydrodynamics are presented and an efficient computational algorithm and open source software package are developed. A new notion of “condition” for the stochastic inverse problem is defined and analyzed as it relates to the computation of probabilities. Finally, this notion of condition is investigated to determine effective output quantities of interest of maximum water elevations to use for the inverse problem for the Manning’s n parameter and the effect on model predictions is analyzed.« less