Hybrid experimental/analytical models of structural dynamics - Creation and use for predictions

NASA Technical Reports Server (NTRS)

Balmes, Etienne

1993-01-01

An original complete methodology for the construction of predictive models of damped structural vibrations is introduced. A consistent definition of normal and complex modes is given which leads to an original method to accurately identify non-proportionally damped normal mode models. A new method to create predictive hybrid experimental/analytical models of damped structures is introduced, and the ability of hybrid models to predict the response to system configuration changes is discussed. Finally a critical review of the overall methodology is made by application to the case of the MIT/SERC interferometer testbed.

Predictive analytics and child protection: constraints and opportunities.

PubMed

Russell, Jesse

2015-08-01

This paper considers how predictive analytics might inform, assist, and improve decision making in child protection. Predictive analytics represents recent increases in data quantity and data diversity, along with advances in computing technology. While the use of data and statistical modeling is not new to child protection decision making, its use in child protection is experiencing growth, and efforts to leverage predictive analytics for better decision-making in child protection are increasing. Past experiences, constraints and opportunities are reviewed. For predictive analytics to make the most impact on child protection practice and outcomes, it must embrace established criteria of validity, equity, reliability, and usefulness. Copyright © 2015 Elsevier Ltd. All rights reserved.

Aeroelastic loads and stability investigation of a full-scale hingeless rotor

NASA Technical Reports Server (NTRS)

Peterson, Randall L.; Johnson, Wayne

1991-01-01

An analytical investigation was conducted to study the influence of various parameters on predicting the aeroelastic loads and stability of a full-scale hingeless rotor in hover and forward flight. The CAMRAD/JA (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics, Johnson Aeronautics) analysis code is used to obtain the analytical predictions. Data are presented for rotor blade bending and torsional moments as well as inplane damping data obtained for rotor operation in hover at a constant rotor rotational speed of 425 rpm and thrust coefficients between 0.0 and 0.12. Experimental data are presented from a test in the wind tunnel. Validation of the rotor system structural model with experimental rotor blade loads data shows excellent correlation with analytical results. Using this analysis, the influence of different aerodynamic inflow models, the number of generalized blade and body degrees of freedom, and the control-system stiffness at predicted stability levels are shown. Forward flight predictions of the BO-105 rotor system for 1-G thrust conditions at advance ratios of 0.0 to 0.35 are presented. The influence of different aerodynamic inflow models, dynamic inflow models and shaft angle variations on predicted stability levels are shown as a function of advance ratio.

Analysis of a virtual memory model for maintaining database views

NASA Technical Reports Server (NTRS)

Kinsley, Kathryn C.; Hughes, Charles E.

1992-01-01

This paper presents an analytical model for predicting the performance of a new support strategy for database views. This strategy, called the virtual method, is compared with traditional methods for supporting views. The analytical model's predictions of improved performance by the virtual method are then validated by comparing these results with those achieved in an experimental implementation.

Thermal Modeling of Resistance Spot Welding and Prediction of Weld Microstructure

NASA Astrophysics Data System (ADS)

Sheikhi, M.; Valaee Tale, M.; Usefifar, GH. R.; Fattah-Alhosseini, Arash

2017-11-01

The microstructure of nuggets in resistance spot welding can be influenced by the many variables involved. This study aimed at examining such a relationship and, consequently, put forward an analytical model to predict the thermal history and microstructure of the nugget zone. Accordingly, a number of numerical simulations and experiments were conducted and the accuracy of the model was assessed. The results of this assessment revealed that the proposed analytical model could accurately predict the cooling rate in the nugget and heat-affected zones. Moreover, both analytical and numerical models confirmed that sheet thickness and electrode-sheet interface temperature were the most important factors influencing the cooling rate at temperatures lower than about T l/2. Decomposition of austenite is one of the most important transformations in steels occurring over this temperature range. Therefore, an easy-to-use map was designed against these parameters to predict the weld microstructure.

Predictive data modeling of human type II diabetes related statistics

NASA Astrophysics Data System (ADS)

Jaenisch, Kristina L.; Jaenisch, Holger M.; Handley, James W.; Albritton, Nathaniel G.

2009-04-01

During the course of routine Type II treatment of one of the authors, it was decided to derive predictive analytical Data Models of the daily sampled vital statistics: namely weight, blood pressure, and blood sugar, to determine if the covariance among the observed variables could yield a descriptive equation based model, or better still, a predictive analytical model that could forecast the expected future trend of the variables and possibly eliminate the number of finger stickings required to montior blood sugar levels. The personal history and analysis with resulting models are presented.

Development of an analytical-numerical model to predict radiant emission or absorption

NASA Technical Reports Server (NTRS)

Wallace, Tim L.

1994-01-01

The development of an analytical-numerical model to predict radiant emission or absorption is discussed. A voigt profile is assumed to predict the spectral qualities of a singlet atomic transition line for atomic species of interest to the OPAD program. The present state of this model is described in each progress report required under contract. Model and code development is guided by experimental data where available. When completed, the model will be used to provide estimates of specie erosion rates from spectral data collected from rocket exhaust plumes or other sources.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Pavement Performance : Approaches Using Predictive Analytics

DOT National Transportation Integrated Search

2018-03-23

Acceptable pavement condition is paramount to road safety. Using predictive analytics techniques, this project attempted to develop models that provide an assessment of pavement condition based on an array of indictors that include pavement distress,...

Analytical prediction of digital signal crosstalk of FCC

NASA Technical Reports Server (NTRS)

Belleisle, A. P.

1972-01-01

The results are presented of study effort whose aim was the development of accurate means of analyzing and predicting signal cross-talk in multi-wire digital data cables. A complete analytical model is developed n + 1 wire systems of uniform transmission lines with arbitrary linear boundary conditions. In addition, a minimum set of parameter measurements required for the application of the model are presented. Comparisons between cross-talk predicted by this model and actual measured cross-talk are shown for a six conductor ribbon cable.

Experimental validation of an analytical kinetic model for edge-localized modes in JET-ITER-like wall

NASA Astrophysics Data System (ADS)

Guillemaut, C.; Metzger, C.; Moulton, D.; Heinola, K.; O’Mullane, M.; Balboa, I.; Boom, J.; Matthews, G. F.; Silburn, S.; Solano, E. R.; contributors, JET

2018-06-01

The design and operation of future fusion devices relying on H-mode plasmas requires reliable modelling of edge-localized modes (ELMs) for precise prediction of divertor target conditions. An extensive experimental validation of simple analytical predictions of the time evolution of target plasma loads during ELMs has been carried out here in more than 70 JET-ITER-like wall H-mode experiments with a wide range of conditions. Comparisons of these analytical predictions with diagnostic measurements of target ion flux density, power density, impact energy and electron temperature during ELMs are presented in this paper and show excellent agreement. The analytical predictions tested here are made with the ‘free-streaming’ kinetic model (FSM) which describes ELMs as a quasi-neutral plasma bunch expanding along the magnetic field lines into the Scrape-Off Layer without collisions. Consequences of the FSM on energy reflection and deposition on divertor targets during ELMs are also discussed.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Predicting the Development of Analytical and Creative Abilities in Upper Elementary Grades

ERIC Educational Resources Information Center

Gubbels, Joyce; Segers, Eliane; Verhoeven, Ludo

2017-01-01

In some models, intelligence has been described as a multidimensional construct comprising both analytical and creative abilities. In addition, intelligence is considered to be dynamic rather than static. A structural equation model was used to examine the predictive role of cognitive (visual short-term memory, verbal short-term memory, selective…

Variations on Debris Disks. IV. An Improved Analytical Model for Collisional Cascades

NASA Astrophysics Data System (ADS)

Kenyon, Scott J.; Bromley, Benjamin C.

2017-04-01

We derive a new analytical model for the evolution of a collisional cascade in a thin annulus around a single central star. In this model, r max the size of the largest object changes with time, {r}\\max \\propto {t}-γ , with γ ≈ 0.1-0.2. Compared to standard models where r max is constant in time, this evolution results in a more rapid decline of M d , the total mass of solids in the annulus, and L d , the luminosity of small particles in the annulus: {M}d\\propto {t}-(γ +1) and {L}d\\propto {t}-(γ /2+1). We demonstrate that the analytical model provides an excellent match to a comprehensive suite of numerical coagulation simulations for annuli at 1 au and at 25 au. If the evolution of real debris disks follows the predictions of the analytical or numerical models, the observed luminosities for evolved stars require up to a factor of two more mass than predicted by previous analytical models.

Determining passive cooling limits in CPV using an analytical thermal model

NASA Astrophysics Data System (ADS)

Gualdi, Federico; Arenas, Osvaldo; Vossier, Alexis; Dollet, Alain; Aimez, Vincent; Arès, Richard

2013-09-01

We propose an original thermal analytical model aiming to predict the practical limits of passive cooling systems for high concentration photovoltaic modules. The analytical model is described and validated by comparison with a commercial 3D finite element model. The limiting performances of flat plate cooling systems in natural convection are then derived and discussed.

Incorporating photon recycling into the analytical drift-diffusion model of high efficiency solar cells

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

Lumb, Matthew P.; Naval Research Laboratory, Washington, DC 20375; Steiner, Myles A.

The analytical drift-diffusion formalism is able to accurately simulate a wide range of solar cell architectures and was recently extended to include those with back surface reflectors. However, as solar cells approach the limits of material quality, photon recycling effects become increasingly important in predicting the behavior of these cells. In particular, the minority carrier diffusion length is significantly affected by the photon recycling, with consequences for the solar cell performance. In this paper, we outline an approach to account for photon recycling in the analytical Hovel model and compare analytical model predictions to GaAs-based experimental devices operating close tomore » the fundamental efficiency limit.« less

Analytical modeling of fire growth on fire-resistive wood-based materials with changing conditions

Treesearch

Mark A. Dietenberger

2006-01-01

Our analytical model of fire growth for the ASTM E 84 tunnel, which simultaneously predicts heat release rate, flame-over area, and pyrolysis area as functions of time for constant conditions, was documented in the 2001 BCC Symposium for different treated wood materials. The model was extended to predict ignition and fire growth on exterior fire-resistive structures...

Heat generation in Aircraft tires under yawed rolling conditions

NASA Technical Reports Server (NTRS)

Dodge, Richard N.; Clark, Samuel K.

1987-01-01

An analytical model was developed for approximating the internal temperature distribution in an aircraft tire operating under conditions of yawed rolling. The model employs an assembly of elements to represent the tire cross section and treats the heat generated within the tire as a function of the change in strain energy associated with predicted tire flexure. Special contact scrubbing terms are superimposed on the symmetrical free rolling model to account for the slip during yawed rolling. An extensive experimental program was conducted to verify temperatures predicted from the analytical model. Data from this program were compared with calculation over a range of operating conditions, namely, vertical deflection, inflation pressure, yaw angle, and direction of yaw. Generally the analytical model predicted overall trends well and correlated reasonably well with individual measurements at locations throughout the cross section.

Modeling and Analysis of Structural Dynamics for a One-Tenth Scale Model NGST Sunshield

NASA Technical Reports Server (NTRS)

Johnston, John; Lienard, Sebastien; Brodeur, Steve (Technical Monitor)

2001-01-01

New modeling and analysis techniques have been developed for predicting the dynamic behavior of the Next Generation Space Telescope (NGST) sunshield. The sunshield consists of multiple layers of pretensioned, thin-film membranes supported by deployable booms. Modeling the structural dynamic behavior of the sunshield is a challenging aspect of the problem due to the effects of membrane wrinkling. A finite element model of the sunshield was developed using an approximate engineering approach, the cable network method, to account for membrane wrinkling effects. Ground testing of a one-tenth scale model of the NGST sunshield were carried out to provide data for validating the analytical model. A series of analyses were performed to predict the behavior of the sunshield under the ground test conditions. Modal analyses were performed to predict the frequencies and mode shapes of the test article and transient response analyses were completed to simulate impulse excitation tests. Comparison was made between analytical predictions and test measurements for the dynamic behavior of the sunshield. In general, the results show good agreement with the analytical model correctly predicting the approximate frequency and mode shapes for the significant structural modes.

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints

PubMed Central

Thompson, John R; Spata, Enti; Abrams, Keith R

2015-01-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing–remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions. PMID:26271918

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Spata, Enti; Abrams, Keith R

2017-10-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing-remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions.

An analytical model of leakage neutron equivalent dose for passively-scattered proton radiotherapy and validation with measurements.

PubMed

Schneider, Christopher; Newhauser, Wayne; Farah, Jad

2015-05-18

Exposure to stray neutrons increases the risk of second cancer development after proton therapy. Previously reported analytical models of this exposure were difficult to configure and had not been investigated below 100 MeV proton energy. The purposes of this study were to test an analytical model of neutron equivalent dose per therapeutic absorbed dose  at 75 MeV and to improve the model by reducing the number of configuration parameters and making it continuous in proton energy from 100 to 250 MeV. To develop the analytical model, we used previously published H/D values in water from Monte Carlo simulations of a general-purpose beamline for proton energies from 100 to 250 MeV. We also configured and tested the model on in-air neutron equivalent doses measured for a 75 MeV ocular beamline. Predicted H/D values from the analytical model and Monte Carlo agreed well from 100 to 250 MeV (10% average difference). Predicted H/D values from the analytical model also agreed well with measurements at 75 MeV (15% average difference). The results indicate that analytical models can give fast, reliable calculations of neutron exposure after proton therapy. This ability is absent in treatment planning systems but vital to second cancer risk estimation.

The rate of bubble growth in a superheated liquid in pool boiling

NASA Astrophysics Data System (ADS)

Abdollahi, Mohammad Reza; Jafarian, Mehdi; Jamialahmadi, Mohammad

2017-12-01

A semi-empirical model for the estimation of the rate of bubble growth in nucleate pool boiling is presented, considering a new equation to estimate the temperature history of the bubble in the bulk of liquid. The conservation equations of energy, mass and momentum have been firstly derived and solved analytically. The present analytical model of the bubble growth predicts that the radius of the bubble grows as a function of √{t}.{\\operatorname{erf}}( N√{t}) , while so far the bubble growth rate has been mainly correlated to √{t} in the previous studies. In the next step, the analytical solutions were used to develop a new semi-empirical equation. To achieve this, firstly the analytical solution were non-dimensionalised and then the experimental data, available in the literature, were applied to tune the dimensionless coefficients appeared in the dimensionless equation. Finally, the reliability of the proposed semi-empirical model was assessed through comparison of the model predictions with the available experimental data in the literature, which were not applied in the tuning of the dimensionless parameters of the model. The comparison of the model predictions with other proposed models in the literature was also performed. These comparisons show that this model enables more accurate predictions than previously proposed models with a deviation of less than 10% in a wide range of operating conditions.

Modeling and Predicting the Stress Relaxation of Composites with Short and Randomly Oriented Fibers

PubMed Central

Obaid, Numaira; Sain, Mohini

2017-01-01

The addition of short fibers has been experimentally observed to slow the stress relaxation of viscoelastic polymers, producing a change in the relaxation time constant. Our recent study attributed this effect of fibers on stress relaxation behavior to the interfacial shear stress transfer at the fiber-matrix interface. This model explained the effect of fiber addition on stress relaxation without the need to postulate structural changes at the interface. In our previous study, we developed an analytical model for the effect of fully aligned short fibers, and the model predictions were successfully compared to finite element simulations. However, in most industrial applications of short-fiber composites, fibers are not aligned, and hence it is necessary to examine the time dependence of viscoelastic polymers containing randomly oriented short fibers. In this study, we propose an analytical model to predict the stress relaxation behavior of short-fiber composites where the fibers are randomly oriented. The model predictions were compared to results obtained from Monte Carlo finite element simulations, and good agreement between the two was observed. The analytical model provides an excellent tool to accurately predict the stress relaxation behavior of randomly oriented short-fiber composites. PMID:29053601

Bridging the Gap between Human Judgment and Automated Reasoning in Predictive Analytics

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

Sanfilippo, Antonio P.; Riensche, Roderick M.; Unwin, Stephen D.

2010-06-07

Events occur daily that impact the health, security and sustainable growth of our society. If we are to address the challenges that emerge from these events, anticipatory reasoning has to become an everyday activity. Strong advances have been made in using integrated modeling for analysis and decision making. However, a wider impact of predictive analytics is currently hindered by the lack of systematic methods for integrating predictive inferences from computer models with human judgment. In this paper, we present a predictive analytics approach that supports anticipatory analysis and decision-making through a concerted reasoning effort that interleaves human judgment and automatedmore » inferences. We describe a systematic methodology for integrating modeling algorithms within a serious gaming environment in which role-playing by human agents provides updates to model nodes and the ensuing model outcomes in turn influence the behavior of the human players. The approach ensures a strong functional partnership between human players and computer models while maintaining a high degree of independence and greatly facilitating the connection between model and game structures.« less

How health leaders can benefit from predictive analytics.

PubMed

Giga, Aliyah

2017-11-01

Predictive analytics can support a better integrated health system providing continuous, coordinated, and comprehensive person-centred care to those who could benefit most. In addition to dollars saved, using a predictive model in healthcare can generate opportunities for meaningful improvements in efficiency, productivity, costs, and better population health with targeted interventions toward patients at risk.

Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

ERIC Educational Resources Information Center

Calvert, Carol Elaine

2014-01-01

This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…

Empirical and semi-analytical models for predicting peak outflows caused by embankment dam failures

NASA Astrophysics Data System (ADS)

Wang, Bo; Chen, Yunliang; Wu, Chao; Peng, Yong; Song, Jiajun; Liu, Wenjun; Liu, Xin

2018-07-01

Prediction of peak discharge of floods has attracted great attention for researchers and engineers. In present study, nine typical nonlinear mathematical models are established based on database of 40 historical dam failures. The first eight models that were developed with a series of regression analyses are purely empirical, while the last one is a semi-analytical approach that was derived from an analytical solution of dam-break floods in a trapezoidal channel. Water depth above breach invert (Hw), volume of water stored above breach invert (Vw), embankment length (El), and average embankment width (Ew) are used as independent variables to develop empirical formulas of estimating the peak outflow from breached embankment dams. It is indicated from the multiple regression analysis that a function using the former two variables (i.e., Hw and Vw) produce considerably more accurate results than that using latter two variables (i.e., El and Ew). It is shown that the semi-analytical approach works best in terms of both prediction accuracy and uncertainty, and the established empirical models produce considerably reasonable results except the model only using El. Moreover, present models have been compared with other models available in literature for estimating peak discharge.

The legal and ethical concerns that arise from using complex predictive analytics in health care.

PubMed

Cohen, I Glenn; Amarasingham, Ruben; Shah, Anand; Xie, Bin; Lo, Bernard

2014-07-01

Predictive analytics, or the use of electronic algorithms to forecast future events in real time, makes it possible to harness the power of big data to improve the health of patients and lower the cost of health care. However, this opportunity raises policy, ethical, and legal challenges. In this article we analyze the major challenges to implementing predictive analytics in health care settings and make broad recommendations for overcoming challenges raised in the four phases of the life cycle of a predictive analytics model: acquiring data to build the model, building and validating it, testing it in real-world settings, and disseminating and using it more broadly. For instance, we recommend that model developers implement governance structures that include patients and other stakeholders starting in the earliest phases of development. In addition, developers should be allowed to use already collected patient data without explicit consent, provided that they comply with federal regulations regarding research on human subjects and the privacy of health information. Project HOPE—The People-to-People Health Foundation, Inc.

Using predictive analytics and big data to optimize pharmaceutical outcomes.

PubMed

Hernandez, Inmaculada; Zhang, Yuting

2017-09-15

The steps involved, the resources needed, and the challenges associated with applying predictive analytics in healthcare are described, with a review of successful applications of predictive analytics in implementing population health management interventions that target medication-related patient outcomes. In healthcare, the term big data typically refers to large quantities of electronic health record, administrative claims, and clinical trial data as well as data collected from smartphone applications, wearable devices, social media, and personal genomics services; predictive analytics refers to innovative methods of analysis developed to overcome challenges associated with big data, including a variety of statistical techniques ranging from predictive modeling to machine learning to data mining. Predictive analytics using big data have been applied successfully in several areas of medication management, such as in the identification of complex patients or those at highest risk for medication noncompliance or adverse effects. Because predictive analytics can be used in predicting different outcomes, they can provide pharmacists with a better understanding of the risks for specific medication-related problems that each patient faces. This information will enable pharmacists to deliver interventions tailored to patients' needs. In order to take full advantage of these benefits, however, clinicians will have to understand the basics of big data and predictive analytics. Predictive analytics that leverage big data will become an indispensable tool for clinicians in mapping interventions and improving patient outcomes. Copyright © 2017 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Application of stiffened cylinder analysis to ATP interior noise studies

NASA Technical Reports Server (NTRS)

Wilby, E. G.; Wilby, J. F.

1983-01-01

An analytical model developed to predict the interior noise of propeller driven aircraft was applied to experimental configurations for a Fairchild Swearingen Metro II fuselage exposed to simulated propeller excitation. The floor structure of the test fuselage was of unusual construction - mounted on air springs. As a consequence, the analytical model was extended to include a floor treatment transmission coefficient which could be used to describe vibration attenuation through the mounts. Good agreement was obtained between measured and predicted noise reductions when the foor treatment transmission loss was about 20 dB - a value which is consistent with the vibration attenuation provided by the mounts. The analytical model was also adapted to allow the prediction of noise reductions associated with boundary layer excitation as well as propeller and reverberant noise.

Prediction of force and acceleration control spectra for Space Shuttle orbiter sidewall-mounted payloads

NASA Technical Reports Server (NTRS)

Hipol, Philip J.

1990-01-01

The development of force and acceleration control spectra for vibration testing of Space Shuttle (STS) orbiter sidewall-mounted payloads requiresreliable estimates of the sidewall apparent weight and free (i.e. unloaded) vibration during lift-off. The feasibility of analytically predicting these quantities has been investigated through the development and analysis of a finite element model of the STS cargo bay. Analytical predictions of the sidewall apparent weight were compared with apparent weight measurements made on OV-101, and analytical predictions of the sidewall free vibration response during lift-off were compared with flight measurements obtained from STS-3 and STS-4. These analysis suggest that the cargo bay finite element model has potential application for the estimation of force and acceleration control spectra for STS sidewall-mounted payloads.

Quantum decay model with exact explicit analytical solution

NASA Astrophysics Data System (ADS)

Marchewka, Avi; Granot, Er'El

2009-01-01

A simple decay model is introduced. The model comprises a point potential well, which experiences an abrupt change. Due to the temporal variation, the initial quantum state can either escape from the well or stay localized as a new bound state. The model allows for an exact analytical solution while having the necessary features of a decay process. The results show that the decay is never exponential, as classical dynamics predicts. Moreover, at short times the decay has a fractional power law, which differs from perturbation quantum method predictions. At long times the decay includes oscillations with an envelope that decays algebraically. This is a model where the final state can be either continuous or localized, and that has an exact analytical solution.

Predictive Analytics for Identification of Patients at Risk for QT Interval Prolongation - A Systematic Review.

PubMed

Tomaselli Muensterman, Elena; Tisdale, James E

2018-06-08

Prolongation of the heart rate-corrected QT (QTc) interval increases the risk for torsades de pointes (TdP), a potentially fatal arrhythmia. The likelihood of TdP is higher in patients with risk factors, which include female sex, older age, heart failure with reduced ejection fraction, hypokalemia, hypomagnesemia, concomitant administration of ≥ 2 QTc interval-prolonging medications, among others. Assessment and quantification of risk factors may facilitate prediction of patients at highest risk for developing QTc interval prolongation and TdP. Investigators have utilized the field of predictive analytics, which generates predictions using techniques including data mining, modeling, machine learning, and others, to develop methods of risk quantification and prediction of QTc interval prolongation. Predictive analytics have also been incorporated into clinical decision support (CDS) tools to alert clinicians regarding patients at increased risk of developing QTc interval prolongation. The objectives of this paper are to assess the effectiveness of predictive analytics for identification of patients at risk of drug-induced QTc interval prolongation, and to discuss the efficacy of incorporation of predictive analytics into CDS tools in clinical practice. A systematic review of English language articles (human subjects only) was performed, yielding 57 articles, with an additional 4 articles identified from other sources; a total of 10 articles were included in this review. Risk scores for QTc interval prolongation have been developed in various patient populations including those in cardiac intensive care units (ICUs) and in broader populations of hospitalized or health system patients. One group developed a risk score that includes information regarding genetic polymorphisms; this score significantly predicted TdP. Development of QTc interval prolongation risk prediction models and incorporation of these models into CDS tools reduces the risk of QTc interval prolongation in cardiac ICUs and identifies health-system patients at increased risk for mortality. The impact of these QTc interval prolongation predictive analytics on overall patient safety outcomes, such as TdP and sudden cardiac death relative to the cost of development and implementation, requires further study. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

An Analytical Model for Two-Order Asperity Degradation of Rock Joints Under Constant Normal Stiffness Conditions

NASA Astrophysics Data System (ADS)

Li, Yingchun; Wu, Wei; Li, Bo

2018-05-01

Jointed rock masses during underground excavation are commonly located under the constant normal stiffness (CNS) condition. This paper presents an analytical formulation to predict the shear behaviour of rough rock joints under the CNS condition. The dilatancy and deterioration of two-order asperities are quantified by considering the variation of normal stress. We separately consider the dilation angles of waviness and unevenness, which decrease to zero as the normal stress approaches the transitional stress. The sinusoidal function naturally yields the decay of dilation angle as a function of relative normal stress. We assume that the magnitude of transitional stress is proportionate to the square root of asperity geometric area. The comparison between the analytical prediction and experimental data shows the reliability of the analytical model. All the parameters involved in the analytical model possess explicit physical meanings and are measurable from laboratory tests. The proposed model is potentially practicable for assessing the stability of underground structures at various field scales.

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Viscoelastic behavior and lifetime (durability) predictions. [for laminated fiber reinforced plastics

NASA Technical Reports Server (NTRS)

Brinson, R. F.

1985-01-01

A method for lifetime or durability predictions for laminated fiber reinforced plastics is given. The procedure is similar to but not the same as the well known time-temperature-superposition principle for polymers. The method is better described as an analytical adaptation of time-stress-super-position methods. The analytical constitutive modeling is based upon a nonlinear viscoelastic constitutive model developed by Schapery. Time dependent failure models are discussed and are related to the constitutive models. Finally, results of an incremental lamination analysis using the constitutive and failure model are compared to experimental results. Favorable results between theory and predictions are presented using data from creep tests of about two months duration.

SVM-Based System for Prediction of Epileptic Seizures from iEEG Signal

PubMed Central

Cherkassky, Vladimir; Lee, Jieun; Veber, Brandon; Patterson, Edward E.; Brinkmann, Benjamin H.; Worrell, Gregory A.

2017-01-01

Objective This paper describes a data-analytic modeling approach for prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods Our work emphasizes understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during pre-processing and post-processing are considered and investigated for their effect on seizure prediction accuracy. Results Our empirical results show that the proposed SVM-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest good prediction is subject-specific (dog or human), in agreement with earlier studies. Conclusion Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages. PMID:27362758

Functionality of empirical model-based predictive analytics for the early detection of hemodynamic instabilty.

PubMed

Summers, Richard L; Pipke, Matt; Wegerich, Stephan; Conkright, Gary; Isom, Kristen C

2014-01-01

Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patient’s pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for smart monitoring of data streams from patients as a first tier automated detection system for clinical deterioration. As a prelude to human clinical trials, an empirical multivariate machine learning method called Similarity-Based Modeling (“SBM”), was tested in an In Silico experiment using data generated with the aid of a detailed computer simulator of human physiology (Quantitative Circulatory Physiology or “QCP”) which contains complex control systems with realistic integrated feedback loops. Methods. SBM is a kernel-based, multivariate machine learning method that that uses monitored clinical information to generate an empirical model of a patient’s physiologic state. This platform allows for the use of predictive analytic techniques to identify early changes in a patient’s condition that are indicative of a state of deterioration or instability. The integrity of the technique was tested through an In Silico experiment using QCP in which the output of computer simulations of a slowly evolving cardiac tamponade resulted in progressive state of cardiovascular decompensation. Simulator outputs for the variables under consideration were generated at a 2-min data rate (0.083Hz) with the tamponade introduced at a point 420 minutes into the simulation sequence. The functionality of the SBM predictive analytics methodology to identify clinical deterioration was compared to the thresholds used by conventional monitoring methods. Results. The SBM modeling method was found to closely track the normal physiologic variation as simulated by QCP. With the slow development of the tamponade, the SBM model are seen to disagree while the simulated biosignals in the early stages of physiologic deterioration and while the variables are still within normal ranges. Thus, the SBM system was found to identify pathophysiologic conditions in a timeframe that would not have been detected in a usual clinical monitoring scenario. Conclusion. In this study the functionality of a multivariate machine learning predictive methodology that that incorporates commonly monitored clinical information was tested using a computer model of human physiology. SBM and predictive analytics were able to differentiate a state of decompensation while the monitored variables were still within normal clinical ranges. This finding suggests that the SBM could provide for early identification of a clinical deterioration using predictive analytic techniques. predictive analytics, hemodynamic, monitoring.

Combined mechanical loading of composite tubes

NASA Technical Reports Server (NTRS)

Derstine, Mark S.; Pindera, Marek-Jerzy; Bowles, David E.

1988-01-01

An analytical/experimental investigation was performed to study the effect of material nonlinearities on the response of composite tubes subjected to combined axial and torsional loading. The effect of residual stresses on subsequent mechanical response was included in the investigation. Experiments were performed on P75/934 graphite-epoxy tubes with a stacking sequence of (15/0/ + or - 10/0/ -15), using pure torsion and combined axial/torsional loading. In the presence of residual stresses, the analytical model predicted a reduction in the initial shear modulus. Experimentally, coupling between axial loading and shear strain was observed in laminated tubes under combined loading. The phenomenon was predicted by the nonlinear analytical model. The experimentally observed linear limit of the global shear response was found to correspond to the analytically predicted first ply failure. Further, the failure of the tubes was found to be path dependent above a critical load level.

Monitoring Cosmic Radiation Risk: Comparisons between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-01-01

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and...radiation transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the...same dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6

Monitoring Cosmic Radiation Risk: Comparisons Between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-07-05

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and Heavy...transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the input...dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6 (PARMA

Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: Meta-analysis with a joint model.

PubMed

Emura, Takeshi; Nakatochi, Masahiro; Matsui, Shigeyuki; Michimae, Hirofumi; Rondeau, Virginie

2017-01-01

Developing a personalized risk prediction model of death is fundamental for improving patient care and touches on the realm of personalized medicine. The increasing availability of genomic information and large-scale meta-analytic data sets for clinicians has motivated the extension of traditional survival prediction based on the Cox proportional hazards model. The aim of our paper is to develop a personalized risk prediction formula for death according to genetic factors and dynamic tumour progression status based on meta-analytic data. To this end, we extend the existing joint frailty-copula model to a model allowing for high-dimensional genetic factors. In addition, we propose a dynamic prediction formula to predict death given tumour progression events possibly occurring after treatment or surgery. For clinical use, we implement the computation software of the prediction formula in the joint.Cox R package. We also develop a tool to validate the performance of the prediction formula by assessing the prediction error. We illustrate the method with the meta-analysis of individual patient data on ovarian cancer patients.

Compelling evidence for Lucky Survivor and gas phase protonation: the unified MALDI analyte protonation mechanism.

PubMed

Jaskolla, Thorsten W; Karas, Michael

2011-06-01

This work experimentally verifies and proves the two long since postulated matrix-assisted laser desorption/ionization (MALDI) analyte protonation pathways known as the Lucky Survivor and the gas phase protonation model. Experimental differentiation between the predicted mechanisms becomes possible by the use of deuterated matrix esters as MALDI matrices, which are stable under typical sample preparation conditions and generate deuteronated reagent ions, including the deuterated and deuteronated free matrix acid, only upon laser irradiation in the MALDI process. While the generation of deuteronated analyte ions proves the gas phase protonation model, the detection of protonated analytes by application of deuterated matrix compounds without acidic hydrogens proves the survival of analytes precharged from solution in accordance with the predictions from the Lucky Survivor model. The observed ratio of the two analyte ionization processes depends on the applied experimental parameters as well as the nature of analyte and matrix. Increasing laser fluences and lower matrix proton affinities favor gas phase protonation, whereas more quantitative analyte protonation in solution and intramolecular ion stabilization leads to more Lucky Survivors. The presented results allow for a deeper understanding of the fundamental processes causing analyte ionization in MALDI and may alleviate future efforts for increasing the analyte ion yield.

Analytic Guided-Search Model of Human Performance Accuracy in Target- Localization Search Tasks

NASA Technical Reports Server (NTRS)

Eckstein, Miguel P.; Beutter, Brent R.; Stone, Leland S.

2000-01-01

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-10-01

In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.

Comparison of simulator fidelity model predictions with in-simulator evaluation data

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Ashworth, B. R.

1983-01-01

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

Transition regime analytical solution to gas mass flow rate in a rectangular micro channel

NASA Astrophysics Data System (ADS)

Dadzie, S. Kokou; Dongari, Nishanth

2012-11-01

We present an analytical model predicting the experimentally observed gas mass flow rate in rectangular micro channels over slip and transition regimes without the use of any fitting parameter. Previously, Sone reported a class of pure continuum regime flows that requires terms of Burnett order in constitutive equations of shear stress to be predicted appropriately. The corrective terms to the conventional Navier-Stokes equation were named the ghost effect. We demonstrate in this paper similarity between Sone ghost effect model and newly so-called 'volume diffusion hydrodynamic model'. A generic analytical solution to gas mass flow rate in a rectangular micro channel is then obtained. It is shown that the volume diffusion hydrodynamics allows to accurately predict the gas mass flow rate up to Knudsen number of 5. This can be achieved without necessitating the use of adjustable parameters in boundary conditions or parametric scaling laws for constitutive relations. The present model predicts the non-linear variation of pressure profile along the axial direction and also captures the change in curvature with increase in rarefaction.

The role of mechanics during brain development

NASA Astrophysics Data System (ADS)

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2014-12-01

Convolutions are a classical hallmark of most mammalian brains. Brain surface morphology is often associated with intelligence and closely correlated with neurological dysfunction. Yet, we know surprisingly little about the underlying mechanisms of cortical folding. Here we identify the role of the key anatomic players during the folding process: cortical thickness, stiffness, and growth. To establish estimates for the critical time, pressure, and the wavelength at the onset of folding, we derive an analytical model using the Föppl-von Kármán theory. Analytical modeling provides a quick first insight into the critical conditions at the onset of folding, yet it fails to predict the evolution of complex instability patterns in the post-critical regime. To predict realistic surface morphologies, we establish a computational model using the continuum theory of finite growth. Computational modeling not only confirms our analytical estimates, but is also capable of predicting the formation of complex surface morphologies with asymmetric patterns and secondary folds. Taken together, our analytical and computational models explain why larger mammalian brains tend to be more convoluted than smaller brains. Both models provide mechanistic interpretations of the classical malformations of lissencephaly and polymicrogyria. Understanding the process of cortical folding in the mammalian brain has direct implications on the diagnostics of neurological disorders including severe retardation, epilepsy, schizophrenia, and autism.

The role of mechanics during brain development

PubMed Central

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2014-01-01

Convolutions are a classical hallmark of most mammalian brains. Brain surface morphology is often associated with intelligence and closely correlated to neurological dysfunction. Yet, we know surprisingly little about the underlying mechanisms of cortical folding. Here we identify the role of the key anatomic players during the folding process: cortical thickness, stiffness, and growth. To establish estimates for the critical time, pressure, and the wavelength at the onset of folding, we derive an analytical model using the Föppl-von-Kármán theory. Analytical modeling provides a quick first insight into the critical conditions at the onset of folding, yet it fails to predict the evolution of complex instability patterns in the post-critical regime. To predict realistic surface morphologies, we establish a computational model using the continuum theory of finite growth. Computational modeling not only confirms our analytical estimates, but is also capable of predicting the formation of complex surface morphologies with asymmetric patterns and secondary folds. Taken together, our analytical and computational models explain why larger mammalian brains tend to be more convoluted than smaller brains. Both models provide mechanistic interpretations of the classical malformations of lissencephaly and polymicrogyria. Understanding the process of cortical folding in the mammalian brain has direct implications on the diagnostics of neurological disorders including severe retardation, epilepsy, schizophrenia, and autism. PMID:25202162

Calculation of Thermally-Induced Displacements in Spherically Domed Ion Engine Grids

NASA Technical Reports Server (NTRS)

Soulas, George C.

2006-01-01

An analytical method for predicting the thermally-induced normal and tangential displacements of spherically domed ion optics grids under an axisymmetric thermal loading is presented. A fixed edge support that could be thermally expanded is used for this analysis. Equations for the displacements both normal and tangential to the surface of the spherical shell are derived. A simplified equation for the displacement at the center of the spherical dome is also derived. The effects of plate perforation on displacements and stresses are determined by modeling the perforated plate as an equivalent solid plate with modified, or effective, material properties. Analytical model results are compared to the results from a finite element model. For the solid shell, comparisons showed that the analytical model produces results that closely match the finite element model results. The simplified equation for the normal displacement of the spherical dome center is also found to accurately predict this displacement. For the perforated shells, the analytical solution and simplified equation produce accurate results for materials with low thermal expansion coefficients.

Analytical Modeling for Mechanical Strength Prediction with Raman Spectroscopy and Fractured Surface Morphology of Novel Coconut Shell Powder Reinforced: Epoxy Composites

NASA Astrophysics Data System (ADS)

Singh, Savita; Singh, Alok; Sharma, Sudhir Kumar

2017-06-01

In this paper, an analytical modeling and prediction of tensile and flexural strength of three dimensional micro-scaled novel coconut shell powder (CSP) reinforced epoxy polymer composites have been reported. The novel CSP has a specific mixing ratio of different coconut shell particle size. A comparison is made between obtained experimental strength and modified Guth model. The result shows a strong evidence for non-validation of modified Guth model for strength prediction. Consequently, a constitutive modeled equation named Singh model has been developed to predict the tensile and flexural strength of this novel CSP reinforced epoxy composite. Moreover, high resolution Raman spectrum shows that 40 % CSP reinforced epoxy composite has high dielectric constant to become an alternative material for capacitance whereas fractured surface morphology revealed that a strong bonding between novel CSP and epoxy polymer for the application as light weight composite materials in engineering.

Two-dimensional numerical simulation of a Stirling engine heat exchanger

NASA Technical Reports Server (NTRS)

Ibrahim, Mounir B.; Tew, Roy C.; Dudenhoefer, James E.

1989-01-01

The first phase of an effort to develop multidimensional models of Stirling engine components is described; the ultimate goal is to model an entire engine working space. More specifically, parallel plate and tubular heat exchanger models with emphasis on the central part of the channel (i.e., ignoring hydrodynamic and thermal end effects) are described. The model assumes: laminar, incompressible flow with constant thermophysical properties. In addition, a constant axial temperature gradient is imposed. The governing equations, describing the model, were solved using Crank-Nicloson finite-difference scheme. Model predictions were compared with analytical solutions for oscillating/reversing flow and heat transfer in order to check numerical accuracy. Excellent agreement was obtained for the model predictions with analytical solutions available for both flow in circular tubes and between parallel plates. Also the heat transfer computational results are in good agreement with the heat transfer analytical results for parallel plates.

Synthesized airfoil data method for prediction of dynamic stall and unsteady airloads

NASA Technical Reports Server (NTRS)

Gangwani, S. T.

1983-01-01

A detailed analysis of dynamic stall experiments has led to a set of relatively compact analytical expressions, called synthesized unsteady airfoil data, which accurately describe in the time-domain the unsteady aerodynamic characteristics of stalled airfoils. An analytical research program was conducted to expand and improve this synthesized unsteady airfoil data method using additional available sets of unsteady airfoil data. The primary objectives were to reduce these data to synthesized form for use in rotor airload prediction analyses and to generalize the results. Unsteady drag data were synthesized which provided the basis for successful expansion of the formulation to include computation of the unsteady pressure drag of airfoils and rotor blades. Also, an improved prediction model for airfoil flow reattachment was incorporated in the method. Application of this improved unsteady aerodynamics model has resulted in an improved correlation between analytic predictions and measured full scale helicopter blade loads and stress data.

Gradient retention prediction of acid-base analytes in reversed phase liquid chromatography: a simplified approach for acetonitrile-water mobile phases.

PubMed

Andrés, Axel; Rosés, Martí; Bosch, Elisabeth

2014-11-28

In previous work, a two-parameter model to predict chromatographic retention of ionizable analytes in gradient mode was proposed. However, the procedure required some previous experimental work to get a suitable description of the pKa change with the mobile phase composition. In the present study this previous experimental work has been simplified. The analyte pKa values have been calculated through equations whose coefficients vary depending on their functional group. Forced by this new approach, other simplifications regarding the retention of the totally neutral and totally ionized species also had to be performed. After the simplifications were applied, new prediction values were obtained and compared with the previously acquired experimental data. The simplified model gave pretty good predictions while saving a significant amount of time and resources. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparison of thermal analytic model with experimental test results for 30-sentimeter-diameter engineering model mercury ion thruster

NASA Technical Reports Server (NTRS)

Oglebay, J. C.

1977-01-01

A thermal analytic model for a 30-cm engineering model mercury-ion thruster was developed and calibrated using the experimental test results of tests of a pre-engineering model 30-cm thruster. A series of tests, performed later, simulated a wide range of thermal environments on an operating 30-cm engineering model thruster, which was instrumented to measure the temperature distribution within it. The modified analytic model is described and analytic and experimental results compared for various operating conditions. Based on the comparisons, it is concluded that the analytic model can be used as a preliminary design tool to predict thruster steady-state temperature distributions for stage and mission studies and to define the thermal interface bewteen the thruster and other elements of a spacecraft.

Development of a child head analytical dynamic model considering cranial nonuniform thickness and curvature - Applying to children aged 0-1 years old.

PubMed

Li, Zhigang; Ji, Cheng; Wang, Lishu

2018-07-01

Although analytical models have been used to quickly predict head response under impact condition, the existing models generally took the head as regular shell with uniform thickness which cannot account for the actual head geometry with varied cranial thickness and curvature at different locations. The objective of this study is to develop and validate an analytical model incorporating actual cranial thickness and curvature for child aged 0-1YO and investigate their effects on child head dynamic responses at different head locations. To develop the new analytical model, the child head was simplified into an irregular fluid-filled shell with non-uniform thickness and the cranial thickness and curvature at different locations were automatically obtained from CT scans using a procedure developed in this study. The implicit equation of maximum impact force was derived as a function of elastic modulus, thickness and radius of curvature of cranium. The proposed analytical model are compared with cadaver test data of children aged 0-1 years old and it is shown to be accurate in predicting head injury metrics. According to this model, obvious difference in injury metrics were observed among subjects with the same age, but different cranial thickness and curvature; and the injury metrics at forehead location are significant higher than those at other locations due to large thickness it owns. The proposed model shows good biofidelity and can be used in quickly predicting the dynamics response at any location of head for child younger than 1 YO. Copyright © 2018 Elsevier B.V. All rights reserved.

Blade Tip Rubbing Stress Prediction

NASA Technical Reports Server (NTRS)

Davis, Gary A.; Clough, Ray C.

1991-01-01

An analytical model was constructed to predict the magnitude of stresses produced by rubbing a turbine blade against its tip seal. This model used a linearized approach to the problem, after a parametric study, found that the nonlinear effects were of insignificant magnitude. The important input parameters to the model were: the arc through which rubbing occurs, the turbine rotor speed, normal force exerted on the blade, and the rubbing coefficient of friction. Since it is not possible to exactly specify some of these parameters, values were entered into the model which bracket likely values. The form of the forcing function was another variable which was impossible to specify precisely, but the assumption of a half-sine wave with a period equal to the duration of the rub was taken as a realistic assumption. The analytical model predicted resonances between harmonics of the forcing function decomposition and known harmonics of the blade. Thus, it seemed probable that blade tip rubbing could be at least a contributor to the blade-cracking phenomenon. A full-scale, full-speed test conducted on the space shuttle main engine high pressure fuel turbopump Whirligig tester was conducted at speeds between 33,000 and 28,000 RPM to confirm analytical predictions.

An analytical approach to obtaining JWL parameters from cylinder tests

NASA Astrophysics Data System (ADS)

Sutton, B. D.; Ferguson, J. W.; Hodgson, A. N.

2017-01-01

An analytical method for determining parameters for the JWL Equation of State from cylinder test data is described. This method is applied to four datasets obtained from two 20.3 mm diameter EDC37 cylinder tests. The calculated pressure-relative volume (p-Vr) curves agree with those produced by hydro-code modelling. The average calculated Chapman-Jouguet (CJ) pressure is 38.6 GPa, compared to the model value of 38.3 GPa; the CJ relative volume is 0.729 for both. The analytical pressure-relative volume curves produced agree with the one used in the model out to the commonly reported expansion of 7 relative volumes, as do the predicted energies generated by integrating under the p-Vr curve. The calculated energy is within 1.6% of that predicted by the model.

Predicting CH4 adsorption capacity of microporous carbon using N2 isotherm and a new analytical model

USGS Publications Warehouse

Sun, Jielun; Chen, S.; Rostam-Abadi, M.; Rood, M.J.

1998-01-01

A new analytical pore size distribution (PSD) model was developed to predict CH4 adsorption (storage) capacity of microporous adsorbent carbon. The model is based on a 3-D adsorption isotherm equation, derived from statistical mechanical principles. Least squares error minimization is used to solve the PSD without any pre-assumed distribution function. In comparison with several well-accepted analytical methods from the literature, this 3-D model offers relatively realistic PSD description for select reference materials, including activated carbon fibers. N2 and CH4 adsorption data were correlated using the 3-D model for commercial carbons BPL and AX-21. Predicted CH4 adsorption isotherms, based on N2 adsorption at 77 K, were in reasonable agreement with the experimental CH4 isotherms. Modeling results indicate that not all the pores contribute the same percentage Vm/Vs for CH4 storage due to different adsorbed CH4 densities. Pores near 8-9 A?? shows higher Vm/Vs on the equivalent volume basis than does larger pores.

Combustion of Nitramine Propellants

DTIC Science & Technology

1983-03-01

through development of a comprehensive analytical model. The ultimate goals are to enable prediction of deflagration rate over a wide pressure range...superior in burn rate prediction , both simple models fail in correlating existing temperature- sensitivity data. (2) In the second part, a...auxiliary condition to enable independent burn rate prediction ; improved melt phase model including decomposition-gas bubbles; model for far-field

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.

Effect of vibration on retention characteristics of screen acquisition systems. [for surface tension propellant acquisition

NASA Technical Reports Server (NTRS)

Tegart, J. R.; Aydelott, J. C.

1978-01-01

The design of surface tension propellant acquisition systems using fine-mesh screen must take into account all factors that influence the liquid pressure differentials within the system. One of those factors is spacecraft vibration. Analytical models to predict the effects of vibration have been developed. A test program to verify the analytical models and to allow a comparative evaluation of the parameters influencing the response to vibration was performed. Screen specimens were tested under conditions simulating the operation of an acquisition system, considering the effects of such parameters as screen orientation and configuration, screen support method, screen mesh, liquid flow and liquid properties. An analytical model, based on empirical coefficients, was most successful in predicting the effects of vibration.

Thermal-structural modeling of polymer Bragg grating waveguides illuminated by a light emitting diode.

PubMed

Joon Kim, Kyoung; Bar-Cohen, Avram; Han, Bongtae

2012-02-20

This study reports both analytical and numerical thermal-structural models of polymer Bragg grating (PBG) waveguides illuminated by a light emitting diode (LED). A polymethyl methacrylate (PMMA) Bragg grating (BG) waveguide is chosen as an analysis vehicle to explore parametric effects of incident optical powers and substrate materials on the thermal-structural behavior of the BG. Analytical models are verified by comparing analytically predicted average excess temperatures, and thermally induced axial strains and stresses with numerical predictions. A parametric study demonstrates that the PMMA substrate induces more adverse effects, such as higher excess temperatures, complex axial temperature profiles, and greater and more complicated thermally induced strains in the BG compared with the Si substrate. © 2012 Optical Society of America

Reports of the AAAI 2009 Spring Symposia: Technosocial Predictive Analytics.

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

Sanfilippo, Antonio P.

2009-10-01

The Technosocial Predictive Analytics AAAI symposium was held at Stanford University, Stanford, CA, March 23-25, 2009. The goal of this symposium was to explore new methods for anticipatory analytical thinking that provide decision advantage through the integration of human and physical models. Special attention was also placed on how to leverage supporting disciplines to (a) facilitate the achievement of knowledge inputs, (b) improve the user experience, and (c) foster social intelligence through collaborative/competitive work.

Analytical prediction of the interior noise for cylindrical models of aircraft fuselages for prescribed exterior noise fields. Phase 1: Development and validation of preliminary analytical models

NASA Technical Reports Server (NTRS)

Pope, L. D.; Rennison, D. C.; Wilby, E. G.

1980-01-01

The basic theoretical work required to understand sound transmission into an enclosed space (that is, one closed by the transmitting structure) is developed for random pressure fields and for harmonic (tonal) excitation. The analysis is used to predict the noise reducton of unpressurized unstiffened cylinder, and also the interior response of the cylinder given a tonal (plane wave) excitation. Predictions and measurements are compared and the transmission is analyzed. In addition, results for tonal (harmonic) mechanical excitation are considered.

Importance of aggregation and small ice crystals in cirrus clouds, based on observations and an ice particle growth model

NASA Technical Reports Server (NTRS)

Mitchell, David L.; Chai, Steven K.; Dong, Yayi; Arnott, W. Patrick; Hallett, John

1993-01-01

The 1 November 1986 FIRE I case study was used to test an ice particle growth model which predicts bimodal size spectra in cirrus clouds. The model was developed from an analytically based model which predicts the height evolution of monomodal ice particle size spectra from the measured ice water content (IWC). Size spectra from the monomodal model are represented by a gamma distribution, N(D) = N(sub o)D(exp nu)exp(-lambda D), where D = ice particle maximum dimension. The slope parameter, lambda, and the parameter N(sub o) are predicted from the IWC through the growth processes of vapor diffusion and aggregation. The model formulation is analytical, computationally efficient, and well suited for incorporation into larger models. The monomodal model has been validated against two other cirrus cloud case studies. From the monomodal size spectra, the size distributions which determine concentrations of ice particles less than about 150 mu m are predicted.

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

PubMed

Alejo, Luz; Atkinson, John; Guzmán-Fierro, Víctor; Roeckel, Marlene

2018-05-16

Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. The analytical method considers the protein as the only source of ammonia production in AD after degradation. Total ammonia nitrogen (TAN), total solids (TS), chemical oxygen demand (COD), and total volatile solids (TVS) were measured in the influent and effluent of the process. The TAN concentration in the effluent was predicted, this being the most inhibiting and polluting compound in AD. Despite the limited data available, the SVM-based model outperformed the analytical method for the TAN prediction, achieving a relative average error of 15.2% against 43% for the analytical method. Moreover, SVM showed higher prediction accuracy in comparison with Artificial Neural Networks. This result reveals the future promise of SVM for prediction in non-linear and dynamic AD processes. Graphical abstract ᅟ.

A genetic algorithm-based job scheduling model for big data analytics.

PubMed

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

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

Li, G; Yuan, A; Wei, J

2014-06-15

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation.more » The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no training, and therefore is potentially more resilient to breathing irregularities. On-going investigation introduces airflow into the RMP model for improvement. This research is in part supported by NIH (U54CA137788/132378). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.« less

Precession and circularization of elliptical space-tether motion

NASA Technical Reports Server (NTRS)

Chapel, Jim D.; Grosserode, Patrick

1993-01-01

In this paper, we present a simplified analytic model for predicting motion of long space tethers. The perturbation model developed here addresses skip rope motion, where each end of the tether is held in place and the middle of the tether swings with a motion similar to that of a child's skip rope. If the motion of the tether midpoint is elliptical rather than circular, precession of the ellipse complicates the procedures required to damp this motion. The simplified analytic model developed in this paper parametrically predicts the precession of elliptical skip rope motion. Furthermore, the model shows that elliptic skip rope motion will circularize when damping is present in the longitudinal direction. Compared with high-fidelity simulation results, this simplified model provides excellent predictions of these phenomena.

Contrasting analytical and data-driven frameworks for radiogenomic modeling of normal tissue toxicities in prostate cancer.

PubMed

Coates, James; Jeyaseelan, Asha K; Ybarra, Norma; David, Marc; Faria, Sergio; Souhami, Luis; Cury, Fabio; Duclos, Marie; El Naqa, Issam

2015-04-01

We explore analytical and data-driven approaches to investigate the integration of genetic variations (single nucleotide polymorphisms [SNPs] and copy number variations [CNVs]) with dosimetric and clinical variables in modeling radiation-induced rectal bleeding (RB) and erectile dysfunction (ED) in prostate cancer patients. Sixty-two patients who underwent curative hypofractionated radiotherapy (66 Gy in 22 fractions) between 2002 and 2010 were retrospectively genotyped for CNV and SNP rs5489 in the xrcc1 DNA repair gene. Fifty-four patients had full dosimetric profiles. Two parallel modeling approaches were compared to assess the risk of severe RB (Grade⩾3) and ED (Grade⩾1); Maximum likelihood estimated generalized Lyman-Kutcher-Burman (LKB) and logistic regression. Statistical resampling based on cross-validation was used to evaluate model predictive power and generalizability to unseen data. Integration of biological variables xrcc1 CNV and SNP improved the fit of the RB and ED analytical and data-driven models. Cross-validation of the generalized LKB models yielded increases in classification performance of 27.4% for RB and 14.6% for ED when xrcc1 CNV and SNP were included, respectively. Biological variables added to logistic regression modeling improved classification performance over standard dosimetric models by 33.5% for RB and 21.2% for ED models. As a proof-of-concept, we demonstrated that the combination of genetic and dosimetric variables can provide significant improvement in NTCP prediction using analytical and data-driven approaches. The improvement in prediction performance was more pronounced in the data driven approaches. Moreover, we have shown that CNVs, in addition to SNPs, may be useful structural genetic variants in predicting radiation toxicities. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prediction of retention times in comprehensive two-dimensional gas chromatography using thermodynamic models.

PubMed

McGinitie, Teague M; Harynuk, James J

2012-09-14

A method was developed to accurately predict both the primary and secondary retention times for a series of alkanes, ketones and alcohols in a flow-modulated GC×GC system. This was accomplished through the use of a three-parameter thermodynamic model where ΔH, ΔS, and ΔC(p) for an analyte's interaction with the stationary phases in both dimensions are known. Coupling this thermodynamic model with a time summation calculation it was possible to accurately predict both (1)t(r) and (2)t(r) for all analytes. The model was able to predict retention times regardless of the temperature ramp used, with an average error of only 0.64% for (1)t(r) and an average error of only 2.22% for (2)t(r). The model shows promise for the accurate prediction of retention times in GC×GC for a wide range of compounds and is able to utilize data collected from 1D experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

10 CFR 431.445 - Determination of small electric motor efficiency.

Code of Federal Regulations, 2012 CFR

2012-01-01

... statistical analysis, computer simulation or modeling, or other analytic evaluation of performance data. (3... statistical analysis, computer simulation or modeling, and other analytic evaluation of performance data on.... (ii) If requested by the Department, the manufacturer shall conduct simulations to predict the...

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

PubMed

Taylor, R Andrew; Pare, Joseph R; Venkatesh, Arjun K; Mowafi, Hani; Melnick, Edward R; Fleischman, William; Hall, M Kennedy

2016-03-01

Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns with usability have generally constrained models to a preselected small set of variables judged to be clinically relevant and to rules that are easily calculated. Furthermore, CDRs frequently suffer from questions of generalizability, take years to develop, and lack the ability to be updated as new information becomes available. Newer analytic and machine learning techniques capable of harnessing the large number of variables that are already available through electronic health records (EHRs) may better predict patient outcomes and facilitate automation and deployment within clinical decision support systems. In this proof-of-concept study, a local, big data-driven, machine learning approach is compared to existing CDRs and traditional analytic methods using the prediction of sepsis in-hospital mortality as the use case. This was a retrospective study of adult ED visits admitted to the hospital meeting criteria for sepsis from October 2013 to October 2014. Sepsis was defined as meeting criteria for systemic inflammatory response syndrome with an infectious admitting diagnosis in the ED. ED visits were randomly partitioned into an 80%/20% split for training and validation. A random forest model (machine learning approach) was constructed using over 500 clinical variables from data available within the EHRs of four hospitals to predict in-hospital mortality. The machine learning prediction model was then compared to a classification and regression tree (CART) model, logistic regression model, and previously developed prediction tools on the validation data set using area under the receiver operating characteristic curve (AUC) and chi-square statistics. There were 5,278 visits among 4,676 unique patients who met criteria for sepsis. Of the 4,222 patients in the training group, 210 (5.0%) died during hospitalization, and of the 1,056 patients in the validation group, 50 (4.7%) died during hospitalization. The AUCs with 95% confidence intervals (CIs) for the different models were as follows: random forest model, 0.86 (95% CI = 0.82 to 0.90); CART model, 0.69 (95% CI = 0.62 to 0.77); logistic regression model, 0.76 (95% CI = 0.69 to 0.82); CURB-65, 0.73 (95% CI = 0.67 to 0.80); MEDS, 0.71 (95% CI = 0.63 to 0.77); and mREMS, 0.72 (95% CI = 0.65 to 0.79). The random forest model AUC was statistically different from all other models (p ≤ 0.003 for all comparisons). In this proof-of-concept study, a local big data-driven, machine learning approach outperformed existing CDRs as well as traditional analytic techniques for predicting in-hospital mortality of ED patients with sepsis. Future research should prospectively evaluate the effectiveness of this approach and whether it translates into improved clinical outcomes for high-risk sepsis patients. The methods developed serve as an example of a new model for predictive analytics in emergency care that can be automated, applied to other clinical outcomes of interest, and deployed in EHRs to enable locally relevant clinical predictions. © 2015 by the Society for Academic Emergency Medicine.

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data–Driven, Machine Learning Approach

PubMed Central

Taylor, R. Andrew; Pare, Joseph R.; Venkatesh, Arjun K.; Mowafi, Hani; Melnick, Edward R.; Fleischman, William; Hall, M. Kennedy

2018-01-01

Objectives Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns with usability have generally constrained models to a preselected small set of variables judged to be clinically relevant and to rules that are easily calculated. Furthermore, CDRs frequently suffer from questions of generalizability, take years to develop, and lack the ability to be updated as new information becomes available. Newer analytic and machine learning techniques capable of harnessing the large number of variables that are already available through electronic health records (EHRs) may better predict patient outcomes and facilitate automation and deployment within clinical decision support systems. In this proof-of-concept study, a local, big data–driven, machine learning approach is compared to existing CDRs and traditional analytic methods using the prediction of sepsis in-hospital mortality as the use case. Methods This was a retrospective study of adult ED visits admitted to the hospital meeting criteria for sepsis from October 2013 to October 2014. Sepsis was defined as meeting criteria for systemic inflammatory response syndrome with an infectious admitting diagnosis in the ED. ED visits were randomly partitioned into an 80%/20% split for training and validation. A random forest model (machine learning approach) was constructed using over 500 clinical variables from data available within the EHRs of four hospitals to predict in-hospital mortality. The machine learning prediction model was then compared to a classification and regression tree (CART) model, logistic regression model, and previously developed prediction tools on the validation data set using area under the receiver operating characteristic curve (AUC) and chi-square statistics. Results There were 5,278 visits among 4,676 unique patients who met criteria for sepsis. Of the 4,222 patients in the training group, 210 (5.0%) died during hospitalization, and of the 1,056 patients in the validation group, 50 (4.7%) died during hospitalization. The AUCs with 95% confidence intervals (CIs) for the different models were as follows: random forest model, 0.86 (95% CI = 0.82 to 0.90); CART model, 0.69 (95% CI = 0.62 to 0.77); logistic regression model, 0.76 (95% CI = 0.69 to 0.82); CURB-65, 0.73 (95% CI = 0.67 to 0.80); MEDS, 0.71 (95% CI = 0.63 to 0.77); and mREMS, 0.72 (95% CI = 0.65 to 0.79). The random forest model AUC was statistically different from all other models (p ≤ 0.003 for all comparisons). Conclusions In this proof-of-concept study, a local big data–driven, machine learning approach outperformed existing CDRs as well as traditional analytic techniques for predicting in-hospital mortality of ED patients with sepsis. Future research should prospectively evaluate the effectiveness of this approach and whether it translates into improved clinical outcomes for high-risk sepsis patients. The methods developed serve as an example of a new model for predictive analytics in emergency care that can be automated, applied to other clinical outcomes of interest, and deployed in EHRs to enable locally relevant clinical predictions. PMID:26679719

Hybrid perturbation methods based on statistical time series models

NASA Astrophysics Data System (ADS)

San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

2016-04-01

In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

USDA-ARS?s Scientific Manuscript database

The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop n...

Prediction of the chromatographic retention of acid-base compounds in pH buffered methanol-water mobile phases in gradient mode by a simplified model.

PubMed

Andrés, Axel; Rosés, Martí; Bosch, Elisabeth

2015-03-13

Retention of ionizable analytes under gradient elution depends on the pH of the mobile phase, the pKa of the analyte and their evolution along the programmed gradient. In previous work, a model depending on two fitting parameters was recommended because of its very favorable relationship between accuracy and required experimental work. It was developed using acetonitrile as the organic modifier and involves pKa modeling by means of equations that take into account the acidic functional group of the compound (carboxylic acid, protonated amine, etc.). In this work, the two-parameter predicting model is tested and validated using methanol as the organic modifier of the mobile phase and several compounds of higher pharmaceutical relevance and structural complexity as testing analytes. The results have been quite good overall, showing that the predicting model is applicable to a wide variety of acid-base compounds using mobile phases prepared with acetonitrile or methanol. Copyright © 2015 Elsevier B.V. All rights reserved.

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)

PubMed Central

Lechevalier, D.; Ak, R.; Ferguson, M.; Law, K. H.; Lee, Y.-T. T.; Rachuri, S.

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain. PMID:29202125

Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML).

PubMed

Park, J; Lechevalier, D; Ak, R; Ferguson, M; Law, K H; Lee, Y-T T; Rachuri, S

2017-01-01

This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the predictive estimations. Both features are needed to establish the foundation for uncertainty quantification analysis. Among various probabilistic machine-learning algorithms, GPR has been widely used for approximating a target function because of its capability of representing complex input and output relationships without predefining a set of basis functions, and predicting a target output with uncertainty quantification. GPR is being employed to various manufacturing data-analytics applications, which necessitates representing this model in a standardized form for easy and rapid employment. In this paper, we present a GPR model and its representation in PMML. Furthermore, we demonstrate a prototype using a real data set in the manufacturing domain.

An Extrapolation of a Radical Equation More Accurately Predicts Shelf Life of Frozen Biological Matrices.

PubMed

De Vore, Karl W; Fatahi, Nadia M; Sass, John E

2016-08-01

Arrhenius modeling of analyte recovery at increased temperatures to predict long-term colder storage stability of biological raw materials, reagents, calibrators, and controls is standard practice in the diagnostics industry. Predicting subzero temperature stability using the same practice is frequently criticized but nevertheless heavily relied upon. We compared the ability to predict analyte recovery during frozen storage using 3 separate strategies: traditional accelerated studies with Arrhenius modeling, and extrapolation of recovery at 20% of shelf life using either ordinary least squares or a radical equation y = B1x(0.5) + B0. Computer simulations were performed to establish equivalence of statistical power to discern the expected changes during frozen storage or accelerated stress. This was followed by actual predictive and follow-up confirmatory testing of 12 chemistry and immunoassay analytes. Linear extrapolations tended to be the most conservative in the predicted percent recovery, reducing customer and patient risk. However, the majority of analytes followed a rate of change that slowed over time, which was fit best to a radical equation of the form y = B1x(0.5) + B0. Other evidence strongly suggested that the slowing of the rate was not due to higher-order kinetics, but to changes in the matrix during storage. Predicting shelf life of frozen products through extrapolation of early initial real-time storage analyte recovery should be considered the most accurate method. Although in this study the time required for a prediction was longer than a typical accelerated testing protocol, there are less potential sources of error, reduced costs, and a lower expenditure of resources. © 2016 American Association for Clinical Chemistry.

Tools for studying dry-cured ham processing by using computed tomography.

PubMed

Santos-Garcés, Eva; Muñoz, Israel; Gou, Pere; Sala, Xavier; Fulladosa, Elena

2012-01-11

An accurate knowledge and optimization of dry-cured ham elaboration processes could help to reduce operating costs and maximize product quality. The development of nondestructive tools to characterize chemical parameters such as salt and water contents and a(w) during processing is of special interest. In this paper, predictive models for salt content (R(2) = 0.960 and RMSECV = 0.393), water content (R(2) = 0.912 and RMSECV = 1.751), and a(w) (R(2) = 0.906 and RMSECV = 0.008), which comprise the whole elaboration process, were developed. These predictive models were used to develop analytical tools such as distribution diagrams, line profiles, and regions of interest (ROIs) from the acquired computed tomography (CT) scans. These CT analytical tools provided quantitative information on salt, water, and a(w) in terms of content but also distribution throughout the process. The information obtained was applied to two industrial case studies. The main drawback of the predictive models and CT analytical tools is the disturbance that fat produces in water content and a(w) predictions.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

PubMed

Dinov, Ivo D; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W; Price, Nathan D; Van Horn, John D; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M; Dauer, William; Toga, Arthur W

2016-01-01

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

EVALUATION OF ACID DEPOSITION MODELS USING PRINCIPAL COMPONENT SPACES

EPA Science Inventory

An analytical technique involving principal components analysis is proposed for use in the evaluation of acid deposition models. elationships among model predictions are compared to those among measured data, rather than the more common one-to-one comparison of predictions to mea...

Analysis methods for Kevlar shield response to rotor fragments

NASA Technical Reports Server (NTRS)

Gerstle, J. H.

1977-01-01

Several empirical and analytical approaches to rotor burst shield sizing are compared and principal differences in metal and fabric dynamic behavior are discussed. The application of transient structural response computer programs to predict Kevlar containment limits is described. For preliminary shield sizing, present analytical methods are useful if insufficient test data for empirical modeling are available. To provide other information useful for engineering design, analytical methods require further developments in material characterization, failure criteria, loads definition, and post-impact fragment trajectory prediction.

Shape Phase Transition from Octupole Deformation to Octupole Vibrations: The Analytic Quadrupole Octupole Axially Symmetric Model

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

Bonatsos, Dennis; Lenis, D.; Petrellis, D.

An analytic collective model in which the relative presence of the quadrupole and octupole deformations is determined by a parameter ({phi}0), while axial symmetry is obeyed, is developed. The model [to be called the Analytic Quadrupole Octupole Axially symmetric model (AQOA)] involves an infinite well potential, provides predictions for energy and B(EL) ratios which depend only on {phi}0, draws the border between the regions of octupole deformation and octupole vibrations in an essentially parameter-independent way, and in the actinide region describes well 226Th and 226Ra, for which experimental energy data are shown to suggest that they lie close to thismore » border. The similarity of the AQOA results with {phi}0 = 45 deg. for ground state band spectra and B(E2) transition rates to the predictions of the X(5) model is pointed out.« less

Analytical Modeling of Groundwater Seepages to St. Lucie Estuary

NASA Astrophysics Data System (ADS)

Lee, J.; Yeh, G.; Hu, G.

2008-12-01

In this paper, six analytical models describing hydraulic interaction of stream-aquifer systems were applied to St Lucie Estuary (SLE) River Estuaries. These are analytical solutions for: (1) flow from a finite aquifer to a canal, (2) flow from an infinite aquifer to a canal, (3) the linearized Laplace system in a seepage surface, (4) wave propagation in the aquifer, (5) potential flow through stratified unconfined aquifers, and (6) flow through stratified confined aquifers. Input data for analytical solutions were obtained from monitoring wells and river stages at seepage-meter sites. Four transects in the study area are available: Club Med, Harbour Ridge, Lutz/MacMillan, and Pendarvis Cove located in the St. Lucie River. The analytical models were first calibrated with seepage meter measurements and then used to estimate of groundwater discharges into St. Lucie River. From this process, analytical relationships between the seepage rate and river stages and/or groundwater tables were established to predict the seasonal and monthly variation in groundwater seepage into SLE. It was found the seepage rate estimations by analytical models agreed well with measured data for some cases but only fair for some other cases. This is not unexpected because analytical solutions have some inherently simplified assumptions, which may be more valid for some cases than the others. From analytical calculations, it is possible to predict approximate seepage rates in the study domain when the assumptions underlying these analytical models are valid. The finite and infinite aquifer models and the linearized Laplace method are good for sites Pendarvis Cove and Lutz/MacMillian, but fair for the other two sites. The wave propagation model gave very good agreement in phase but only fairly agreement in magnitude for all four sites. The stratified unconfined and confined aquifer models gave similarly good agreements with measurements at three sites but poorly at the Club Med site. None of the analytical models presented here can fit the data at this site. To give better estimates at all sites numerical modeling that couple river hydraulics and groundwater flow involving less simplifications of and assumptions for the system may have to be adapted.

Modeling bicortical screws under a cantilever bending load.

PubMed

James, Thomas P; Andrade, Brendan A

2013-12-01

Cyclic loading of surgical plating constructs can precipitate bone screw failure. As the frictional contact between the plate and the bone is lost, cantilever bending loads are transferred from the plate to the head of the screw, which over time causes fatigue fracture from cyclic bending. In this research, analytical models using beam mechanics theory were developed to describe the elastic deflection of a bicortical screw under a statically applied load. Four analytical models were developed to simulate the various restraint conditions applicable to bicortical support of the screw. In three of the models, the cortical bone near the tip of the screw was simulated by classical beam constraints (1) simply supported, (2) cantilever, and (3) split distributed load. In the final analytical model, the cortices were treated as an elastic foundation, whereby the response of the constraint was proportional to screw deflection. To test the predictive ability of the new analytical models, 3.5 mm cortical bone screws were tested in a synthetic bone substitute. A novel instrument was developed to measure the bending deflection of screws under radial loads (225 N, 445 N, and 670 N) applied by a surrogate surgical plate at the head of the screw. Of the four cases considered, the analytical model utilizing an elastic foundation most accurately predicted deflection at the screw head, with an average difference of 19% between the measured and predicted results. Determination of the bending moments from the elastic foundation model revealed that a maximum moment of 2.3 N m occurred near the middle of the cortical wall closest to the plate. The location of the maximum bending moment along the screw axis was consistent with the fracture location commonly observed in clinical practice.

Galaxy Formation At Extreme Redshifts: Semi-Analytic Model Predictions And Challenges For Observations

NASA Astrophysics Data System (ADS)

Yung, L. Y. Aaron; Somerville, Rachel S.

2017-06-01

The well-established Santa Cruz semi-analytic galaxy formation framework has been shown to be quite successful at explaining observations in the local Universe, as well as making predictions for low-redshift observations. Recently, metallicity-based gas partitioning and H2-based star formation recipes have been implemented in our model, replacing the legacy cold-gas based recipe. We then use our revised model to explore the high-redshift Universe and make predictions up to z = 15. Although our model is only calibrated to observations from the local universe, our predictions seem to match incredibly well with mid- to high-redshift observational constraints available-to-date, including rest-frame UV luminosity functions and the reionization history as constrained by CMB and IGM observations. We provide predictions for individual and statistical galaxy properties at a wide range of redshifts (z = 4 - 15), including objects that are too far or too faint to be detected with current facilities. And using our model predictions, we also provide forecasted luminosity functions and other observables for upcoming studies with JWST.

Implementing Operational Analytics using Big Data Technologies to Detect and Predict Sensor Anomalies

NASA Astrophysics Data System (ADS)

Coughlin, J.; Mital, R.; Nittur, S.; SanNicolas, B.; Wolf, C.; Jusufi, R.

2016-09-01

Operational analytics when combined with Big Data technologies and predictive techniques have been shown to be valuable in detecting mission critical sensor anomalies that might be missed by conventional analytical techniques. Our approach helps analysts and leaders make informed and rapid decisions by analyzing large volumes of complex data in near real-time and presenting it in a manner that facilitates decision making. It provides cost savings by being able to alert and predict when sensor degradations pass a critical threshold and impact mission operations. Operational analytics, which uses Big Data tools and technologies, can process very large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, and other relevant information. When combined with predictive techniques, it provides a mechanism to monitor and visualize these data sets and provide insight into degradations encountered in large sensor systems such as the space surveillance network. In this study, data from a notional sensor is simulated and we use big data technologies, predictive algorithms and operational analytics to process the data and predict sensor degradations. This study uses data products that would commonly be analyzed at a site. This study builds on a big data architecture that has previously been proven valuable in detecting anomalies. This paper outlines our methodology of implementing an operational analytic solution through data discovery, learning and training of data modeling and predictive techniques, and deployment. Through this methodology, we implement a functional architecture focused on exploring available big data sets and determine practical analytic, visualization, and predictive technologies.

Predicting Student Success using Analytics in Course Learning Management Systems

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

Olama, Mohammed M; Thakur, Gautam; McNair, Wade

Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems,more » called Moodle. First, we have identified the data features useful for predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.« less

Predicting student success using analytics in course learning management systems

NASA Astrophysics Data System (ADS)

Olama, Mohammed M.; Thakur, Gautam; McNair, Allen W.; Sukumar, Sreenivas R.

2014-05-01

Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for predicting student outcomes such as students' scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.

An empirical model for calculation of the collimator contamination dose in therapeutic proton beams

NASA Astrophysics Data System (ADS)

Vidal, M.; De Marzi, L.; Szymanowski, H.; Guinement, L.; Nauraye, C.; Hierso, E.; Freud, N.; Ferrand, R.; François, P.; Sarrut, D.

2016-02-01

Collimators are used as lateral beam shaping devices in proton therapy with passive scattering beam lines. The dose contamination due to collimator scattering can be as high as 10% of the maximum dose and influences calculation of the output factor or monitor units (MU). To date, commercial treatment planning systems generally use a zero-thickness collimator approximation ignoring edge scattering in the aperture collimator and few analytical models have been proposed to take scattering effects into account, mainly limited to the inner collimator face component. The aim of this study was to characterize and model aperture contamination by means of a fast and accurate analytical model. The entrance face collimator scatter distribution was modeled as a 3D secondary dose source. Predicted dose contaminations were compared to measurements and Monte Carlo simulations. Measurements were performed on two different proton beam lines (a fixed horizontal beam line and a gantry beam line) with divergent apertures and for several field sizes and energies. Discrepancies between analytical algorithm dose prediction and measurements were decreased from 10% to 2% using the proposed model. Gamma-index (2%/1 mm) was respected for more than 90% of pixels. The proposed analytical algorithm increases the accuracy of analytical dose calculations with reasonable computation times.

Computational Simulation of the High Strain Rate Tensile Response of Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.

2002-01-01

A research program is underway to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. Under these types of loading conditions, the material response can be highly strain rate dependent and nonlinear. State variable constitutive equations based on a viscoplasticity approach have been developed to model the deformation of the polymer matrix. The constitutive equations are then combined with a mechanics of materials based micromechanics model which utilizes fiber substructuring to predict the effective mechanical and thermal response of the composite. To verify the analytical model, tensile stress-strain curves are predicted for a representative composite over strain rates ranging from around 1 x 10(exp -5)/sec to approximately 400/sec. The analytical predictions compare favorably to experimentally obtained values both qualitatively and quantitatively. Effective elastic and thermal constants are predicted for another composite, and compared to finite element results.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

USGS Publications Warehouse

Larocque, Guy R.; Bhatti, Jagtar S.; Ascough, J.C.; Liu, J.; Luckai, N.; Mailly, D.; Archambault, L.; Gordon, Andrew M.

2011-01-01

The predictions from most forest ecosystem models originate from deterministic simulations. However, few evaluation exercises for model outputs are performed by either model developers or users. This issue has important consequences for decision makers using these models to develop natural resource management policies, as they cannot evaluate the extent to which predictions stemming from the simulation of alternative management scenarios may result in significant environmental or economic differences. Various numerical methods, such as sensitivity/uncertainty analyses, or bootstrap methods, may be used to evaluate models and the errors associated with their outputs. However, the application of each of these methods carries unique challenges which decision makers do not necessarily understand; guidance is required when interpreting the output generated from each model. This paper proposes a decision flow chart in the form of an analytical framework to help decision makers apply, in an orderly fashion, different steps involved in examining the model outputs. The analytical framework is discussed with regard to the definition of problems and objectives and includes the following topics: model selection, identification of alternatives, modelling tasks and selecting alternatives for developing policy or implementing management scenarios. Its application is illustrated using an on-going exercise in developing silvicultural guidelines for a forest management enterprise in Ontario, Canada.

Analytical and numerical techniques for predicting the interfacial stresses of wavy carbon nanotube/polymer composites

NASA Astrophysics Data System (ADS)

Yazdchi, K.; Salehi, M.; Shokrieh, M. M.

2009-03-01

By introducing a new simplified 3D representative volume element for wavy carbon nanotubes, an analytical model is developed to study the stress transfer in single-walled carbon nanotube-reinforced polymer composites. Based on the pull-out modeling technique, the effects of waviness, aspect ratio, and Poisson ratio on the axial and interfacial shear stresses are analyzed in detail. The results of the present analytical model are in a good agreement with corresponding results for straight nanotubes.

Analytical and experimental studies of graphite-epoxy and boron-epoxy angle ply laminates in compression

NASA Technical Reports Server (NTRS)

Weller, T.

1977-01-01

The applicability and adequacy of several computer techniques in predicting satisfactorily the nonlinear/inelastic response of angle ply laminates were evaluated. The analytical predictions were correlated with the results of a test program on the inelastic response under axial compression of a large variety of graphite-epoxy and boron-epoxy angle ply laminates. These comparison studies indicate that neither of the abovementioned analyses can satisfactorily predict either the mode of response or the ultimate stress value corresponding to a particular angle ply laminate configuration. Consequently, also the simple failure mechanisms assumed in the analytical models were not verified.

S-2 stage 1/25 scale model base region thermal environment test. Volume 1: Test results, comparison with theory and flight data

NASA Technical Reports Server (NTRS)

Sadunas, J. A.; French, E. P.; Sexton, H.

1973-01-01

A 1/25 scale model S-2 stage base region thermal environment test is presented. Analytical results are included which reflect the effect of engine operating conditions, model scale, turbo-pump exhaust gas injection on base region thermal environment. Comparisons are made between full scale flight data, model test data, and analytical results. The report is prepared in two volumes. The description of analytical predictions and comparisons with flight data are presented. Tabulation of the test data is provided.

Prediction of pressure and flow transients in a gaseous bipropellant reaction control rocket engine

NASA Technical Reports Server (NTRS)

Markowsky, J. J.; Mcmanus, H. N., Jr.

1974-01-01

An analytic model is developed to predict pressure and flow transients in a gaseous hydrogen-oxygen reaction control rocket engine feed system. The one-dimensional equations of momentum and continuity are reduced by the method of characteristics from partial derivatives to a set of total derivatives which describe the state properties along the feedline. System components, e.g., valves, manifolds, and injectors are represented by pseudo steady-state relations at discrete junctions in the system. Solutions were effected by a FORTRAN IV program on an IBM 360/65. The results indicate the relative effect of manifold volume, combustion lag time, feedline pressure fluctuations, propellant temperature, and feedline length on the chamber pressure transient. The analytical combustion model is verified by good correlation between predicted and observed chamber pressure transients. The developed model enables a rocket designer to vary the design parameters analytically to obtain stable combustion for a particular mode of operation which is prescribed by mission objectives.

Turbofan forced mixer lobe flow modeling. 1: Experimental and analytical assessment

NASA Technical Reports Server (NTRS)

Barber, T.; Paterson, R. W.; Skebe, S. A.

1988-01-01

A joint analytical and experimental investigation of three-dimensional flowfield development within the lobe region of turbofan forced mixer nozzles is described. The objective was to develop a method for predicting the lobe exit flowfield. In the analytical approach, a linearized inviscid aerodynamical theory was used for representing the axial and secondary flows within the three-dimensional convoluted mixer lobes and three-dimensional boundary layer analysis was applied thereafter to account for viscous effects. The experimental phase of the program employed three planar mixer lobe models having different waveform shapes and lobe heights for which detailed measurements were made of the three-dimensional velocity field and total pressure field at the lobe exit plane. Velocity data was obtained using Laser Doppler Velocimetry (LDV) and total pressure probing and hot wire anemometry were employed to define exit plane total pressure and boundary layer development. Comparison of data and analysis was performed to assess analytical model prediction accuracy. As a result of this study a planar mixed geometry analysis was developed. A principal conclusion is that the global mixer lobe flowfield is inviscid and can be predicted from an inviscid analysis and Kutta condition.

Analytical Modeling for the Bending Resonant Frequency of Multilayered Microresonators with Variable Cross-Section

PubMed Central

Herrera-May, Agustín L.; Aguilera-Cortés, Luz A.; Plascencia-Mora, Hector; Rodríguez-Morales, Ángel L.; Lu, Jian

2011-01-01

Multilayered microresonators commonly use sensitive coating or piezoelectric layers for detection of mass and gas. Most of these microresonators have a variable cross-section that complicates the prediction of their fundamental resonant frequency (generally of the bending mode) through conventional analytical models. In this paper, we present an analytical model to estimate the first resonant frequency and deflection curve of single-clamped multilayered microresonators with variable cross-section. The analytical model is obtained using the Rayleigh and Macaulay methods, as well as the Euler-Bernoulli beam theory. Our model is applied to two multilayered microresonators with piezoelectric excitation reported in the literature. Both microresonators are composed by layers of seven different materials. The results of our analytical model agree very well with those obtained from finite element models (FEMs) and experimental data. Our analytical model can be used to determine the suitable dimensions of the microresonator’s layers in order to obtain a microresonator that operates at a resonant frequency necessary for a particular application. PMID:22164071

Temporal fluctuations after a quantum quench: Many-particle dephasing

NASA Astrophysics Data System (ADS)

Marquardt, Florian; Kiendl, Thomas

After a quantum quench, the expectation values of observables continue to fluctuate in time. In the thermodynamic limit, one expects such fluctuations to decrease to zero, in order for standard statistical physics to hold. However, it is a challenge to determine analytically how the fluctuations decay as a function of system size. So far, there have been analytical predictions for integrable models (which are, naturally, somewhat special), analytical bounds for arbitrary systems, and numerical results for moderate-size systems. We have discovered a dynamical regime where the decrease of fluctuations is driven by many-particle dephasing, instead of a redistribution of occupation numbers. On the basis of this insight, we are able to provide exact analytical expressions for a model with weak integrability breaking (transverse Ising chain with additional terms). These predictions explicitly show how fluctuations are exponentially suppressed with system size.

Accommodating subject and instrument variations in spectroscopic determinations

DOEpatents

Haas, Michael J [Albuquerque, NM; Rowe, Robert K [Corrales, NM; Thomas, Edward V [Albuquerque, NM

2006-08-29

A method and apparatus for measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved instrument-tailored or subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate instrument-specific attributes, resulting in a calibration data set modeling intra-instrument or intra-subject variation. In a prediction phase, the prediction process is tailored for each target instrument separately using a minimal number of spectral measurements from each instrument or subject.

Analytical Modelling of Transverse Matrix Cracking of [plus or minus Theta/90(sub n)](sub s) Composite Laminates Under Multiaxial Loading

NASA Technical Reports Server (NTRS)

Mayugo, J A.; Camanho, P. P.; Maimi, P.; Davila, C. G.

2010-01-01

An analytical model based on the analysis of a cracked unit cell of a composite laminate subjected to multiaxial loads is proposed to predict the onset and accumulation of transverse matrix cracks in the 90(sub n) plies of uniformly stressed [plus or minus Theta/90(sub n)](sub s) laminates. The model predicts the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate, and it accounts for the effect of the ply thickness on the ply strength. Several examples describing the predictions of laminate response, from damage onset up to final failure under both uniaxial and multiaxial loads, are presented.

Choice Defines Value: A Predictive Modeling Competition in Health Preference Research.

PubMed

Jakubczyk, Michał; Craig, Benjamin M; Barra, Mathias; Groothuis-Oudshoorn, Catharina G M; Hartman, John D; Huynh, Elisabeth; Ramos-Goñi, Juan M; Stolk, Elly A; Rand, Kim

2018-02-01

To identify which specifications and approaches to model selection better predict health preferences, the International Academy of Health Preference Research (IAHPR) hosted a predictive modeling competition including 18 teams from around the world. In April 2016, an exploratory survey was fielded: 4074 US respondents completed 20 out of 1560 paired comparisons by choosing between two health descriptions (e.g., longer life span vs. better health). The exploratory data were distributed to all teams. By July, eight teams had submitted their predictions for 1600 additional pairs and described their analytical approach. After these predictions had been posted online, a confirmatory survey was fielded (4148 additional respondents). The victorious team, "Discreetly Charming Econometricians," led by Michał Jakubczyk, achieved the smallest χ 2 , 4391.54 (a predefined criterion). Its primary scientific findings were that different models performed better with different pairs, that the value of life span is not constant proportional, and that logit models have poor predictive validity in health valuation. The results demonstrated the diversity and potential of new analytical approaches in health preference research and highlighted the importance of predictive validity in health valuation. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

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.

A Demonstration of Regression False Positive Selection in Data Mining

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2014-01-01

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

An elastic-plastic contact model for line contact structures

NASA Astrophysics Data System (ADS)

Zhu, Haibin; Zhao, Yingtao; He, Zhifeng; Zhang, Ruinan; Ma, Shaopeng

2018-06-01

Although numerical simulation tools are now very powerful, the development of analytical models is very important for the prediction of the mechanical behaviour of line contact structures for deeply understanding contact problems and engineering applications. For the line contact structures widely used in the engineering field, few analytical models are available for predicting the mechanical behaviour when the structures deform plastically, as the classic Hertz's theory would be invalid. Thus, the present study proposed an elastic-plastic model for line contact structures based on the understanding of the yield mechanism. A mathematical expression describing the global relationship between load history and contact width evolution of line contact structures was obtained. The proposed model was verified through an actual line contact test and a corresponding numerical simulation. The results confirmed that this model can be used to accurately predict the elastic-plastic mechanical behaviour of a line contact structure.

The use of analytical models in human-computer interface design

NASA Technical Reports Server (NTRS)

Gugerty, Leo

1993-01-01

Recently, a large number of human-computer interface (HCI) researchers have investigated building analytical models of the user, which are often implemented as computer models. These models simulate the cognitive processes and task knowledge of the user in ways that allow a researcher or designer to estimate various aspects of an interface's usability, such as when user errors are likely to occur. This information can lead to design improvements. Analytical models can supplement design guidelines by providing designers rigorous ways of analyzing the information-processing requirements of specific tasks (i.e., task analysis). These models offer the potential of improving early designs and replacing some of the early phases of usability testing, thus reducing the cost of interface design. This paper describes some of the many analytical models that are currently being developed and evaluates the usefulness of analytical models for human-computer interface design. This paper will focus on computational, analytical models, such as the GOMS model, rather than less formal, verbal models, because the more exact predictions and task descriptions of computational models may be useful to designers. The paper also discusses some of the practical requirements for using analytical models in complex design organizations such as NASA.

An analytical solution for predicting the transient seepage from a subsurface drainage system

NASA Astrophysics Data System (ADS)

Xin, Pei; Dan, Han-Cheng; Zhou, Tingzhang; Lu, Chunhui; Kong, Jun; Li, Ling

2016-05-01

Subsurface drainage systems have been widely used to deal with soil salinization and waterlogging problems around the world. In this paper, a mathematical model was introduced to quantify the transient behavior of the groundwater table and the seepage from a subsurface drainage system. Based on the assumption of a hydrostatic pressure distribution, the model considered the pore-water flow in both the phreatic and vadose soil zones. An approximate analytical solution for the model was derived to quantify the drainage of soils which were initially water-saturated. The analytical solution was validated against laboratory experiments and a 2-D Richards equation-based model, and found to predict well the transient water seepage from the subsurface drainage system. A saturated flow-based model was also tested and found to over-predict the time required for drainage and the total water seepage by nearly one order of magnitude, in comparison with the experimental results and the present analytical solution. During drainage, a vadose zone with a significant water storage capacity developed above the phreatic surface. A considerable amount of water still remained in the vadose zone at the steady state with the water table situated at the drain bottom. Sensitivity analyses demonstrated that effects of the vadose zone were intensified with an increased thickness of capillary fringe, capillary rise and/or burying depth of drains, in terms of the required drainage time and total water seepage. The analytical solution provides guidance for assessing the capillary effects on the effectiveness and efficiency of subsurface drainage systems for combating soil salinization and waterlogging problems.

Analytical solutions of hypersonic type IV shock - shock interactions

NASA Astrophysics Data System (ADS)

Frame, Michael John

An analytical model has been developed to predict the effects of a type IV shock interaction at high Mach numbers. This interaction occurs when an impinging oblique shock wave intersects the most normal portion of a detached bow shock. The flowfield which develops is complicated and contains an embedded jet of supersonic flow, which may be unsteady. The jet impinges on the blunt body surface causing very high pressure and heating loads. Understanding this type of interaction is vital to the designers of cowl lips and leading edges on air- breathing hypersonic vehicles. This analytical model represents the first known attempt at predicting the geometry of the interaction explicitly, without knowing beforehand the jet dimensions, including the length of the transmitted shock where the jet originates. The model uses a hyperbolic equation for the bow shock and by matching mass continuity, flow directions and pressure throughout the flowfield, a prediction of the interaction geometry can be derived. The model has been shown to agree well with the flowfield patterns and properties of experiments and CFD, but the prediction for where the peak pressure is located, and its value, can be significantly in error due to a lack of sophistication in the model of the jet fluid stagnation region. Therefore it is recommended that this region of the flowfield be modeled in more detail and more accurate experimental and CFD measurements be used for validation. However, the analytical model has been shown to be a fast and economic prediction tool, suitable for preliminary design, or for understanding the interactions effects, including the basic physics of the interaction, such as the jet unsteadiness. The model has been used to examine a wide parametric space of possible interactions, including different Mach number, impinging shock strength and location, and cylinder radius. It has also been used to examine the interaction on power-law shaped blunt bodies, a possible candidate for hypersonic leading edges. The formation of vortices at the termination shock of the supersonic jet has been modeled using the analytical method. The vortices lead to deflections in the jet terminating flow, and the presence of the cylinder surface seems to causes the vortices to break off the jet resulting in an oscillation in the jet flow.

Nearshore Tsunami Inundation Model Validation: Toward Sediment Transport Applications

USGS Publications Warehouse

Apotsos, Alex; Buckley, Mark; Gelfenbaum, Guy; Jaffe, Bruce; Vatvani, Deepak

2011-01-01

Model predictions from a numerical model, Delft3D, based on the nonlinear shallow water equations are compared with analytical results and laboratory observations from seven tsunami-like benchmark experiments, and with field observations from the 26 December 2004 Indian Ocean tsunami. The model accurately predicts the magnitude and timing of the measured water levels and flow velocities, as well as the magnitude of the maximum inundation distance and run-up, for both breaking and non-breaking waves. The shock-capturing numerical scheme employed describes well the total decrease in wave height due to breaking, but does not reproduce the observed shoaling near the break point. The maximum water levels observed onshore near Kuala Meurisi, Sumatra, following the 26 December 2004 tsunami are well predicted given the uncertainty in the model setup. The good agreement between the model predictions and the analytical results and observations demonstrates that the numerical solution and wetting and drying methods employed are appropriate for modeling tsunami inundation for breaking and non-breaking long waves. Extension of the model to include sediment transport may be appropriate for long, non-breaking tsunami waves. Using available sediment transport formulations, the sediment deposit thickness at Kuala Meurisi is predicted generally within a factor of 2.

Separation of very hydrophobic analytes by micellar electrokinetic chromatography IV. Modeling of the effective electrophoretic mobility from carbon number equivalents and octanol-water partition coefficients.

PubMed

Huhn, Carolin; Pyell, Ute

2008-07-11

It is investigated whether those relationships derived within an optimization scheme developed previously to optimize separations in micellar electrokinetic chromatography can be used to model effective electrophoretic mobilities of analytes strongly differing in their properties (polarity and type of interaction with the pseudostationary phase). The modeling is based on two parameter sets: (i) carbon number equivalents or octanol-water partition coefficients as analyte descriptors and (ii) four coefficients describing properties of the separation electrolyte (based on retention data for a homologous series of alkyl phenyl ketones used as reference analytes). The applicability of the proposed model is validated comparing experimental and calculated effective electrophoretic mobilities. The results demonstrate that the model can effectively be used to predict effective electrophoretic mobilities of neutral analytes from the determined carbon number equivalents or from octanol-water partition coefficients provided that the solvation parameters of the analytes of interest are similar to those of the reference analytes.

Review of Thawing Time Prediction Models Depending
on Process Conditions and Product Characteristics

PubMed Central

Kluza, Franciszek; Spiess, Walter E. L.; Kozłowicz, Katarzyna

2016-01-01

Summary Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi--graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized software and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing. PMID:27904387

Stochastic modeling of macrodispersion in unsaturated heterogeneous porous media. Final report

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

Yeh, T.C.J.

1995-02-01

Spatial heterogeneity of geologic media leads to uncertainty in predicting both flow and transport in the vadose zone. In this work an efficient and flexible, combined analytical-numerical Monte Carlo approach is developed for the analysis of steady-state flow and transient transport processes in highly heterogeneous, variably saturated porous media. The approach is also used for the investigation of the validity of linear, first order analytical stochastic models. With the Monte Carlo analysis accurate estimates of the ensemble conductivity, head, velocity, and concentration mean and covariance are obtained; the statistical moments describing displacement of solute plumes, solute breakthrough at a compliancemore » surface, and time of first exceedance of a given solute flux level are analyzed; and the cumulative probability density functions for solute flux across a compliance surface are investigated. The results of the Monte Carlo analysis show that for very heterogeneous flow fields, and particularly in anisotropic soils, the linearized, analytical predictions of soil water tension and soil moisture flux become erroneous. Analytical, linearized Lagrangian transport models also overestimate both the longitudinal and the transverse spreading of the mean solute plume in very heterogeneous soils and in dry soils. A combined analytical-numerical conditional simulation algorithm is also developed to estimate the impact of in-situ soil hydraulic measurements on reducing the uncertainty of concentration and solute flux predictions.« less

Towards Adaptive Educational Assessments: Predicting Student Performance using Temporal Stability and Data Analytics in Learning Management Systems

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

Thakur, Gautam; Olama, Mohammed M; McNair, Wade

Data-driven assessments and adaptive feedback are becoming a cornerstone research in educational data analytics and involve developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the students and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present our efforts in using data analytics that enable educationists to design novel data-driven assessment and feedback mechanisms. In order to achieve this objective, we investigate temporal stabilitymore » of students grades and perform predictive analytics on academic data collected from 2009 through 2013 in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for assessments and predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total Grade Point Average(GPA) at the same term they enrolled in the course. Second, time series models in both frequency and time domains are applied to characterize the progression as well as overall projections of the grades. In particular, the model analyzed the stability as well as fluctuation of grades among students during the collegiate years (from freshman to senior) and disciplines. Third, Logistic Regression and Neural Network predictive models are used to identify students as early as possible who are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. The time series analysis indicates that assessments and continuous feedback are critical for freshman and sophomores (even with easy courses) than for seniors, and those assessments may be provided using the predictive models. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy. Our results show that there are strong ties associated with the first few weeks for coursework and they have an impact on the design and distribution of individual modules.« less

Thermal induced flow oscillations in heat exchangers for supercritical fluids

NASA Technical Reports Server (NTRS)

Friedly, J. C.; Manganaro, J. L.; Krueger, P. G.

1972-01-01

Analytical model has been developed to predict possible unstable behavior in supercritical heat exchangers. From complete model, greatly simplified stability criterion is derived. As result of this criterion, stability of heat exchanger system can be predicted in advance.

Confocal Raman Microscopy for pH-Gradient Preconcentration and Quantitative Analyte Detection in Optically Trapped Phospholipid Vesicles.

PubMed

Hardcastle, Chris D; Harris, Joel M

2015-08-04

The ability of a vesicle membrane to preserve a pH gradient, while allowing for diffusion of neutral molecules across the phospholipid bilayer, can provide the isolation and preconcentration of ionizable compounds within the vesicle interior. In this work, confocal Raman microscopy is used to observe (in situ) the pH-gradient preconcentration of compounds into individual optically trapped vesicles that provide sub-femtoliter collectors for small-volume samples. The concentration of analyte accumulated in the vesicle interior is determined relative to a perchlorate-ion internal standard, preloaded into the vesicle along with a high-concentration buffer. As a guide to the experiments, a model for the transfer of analyte into the vesicle based on acid-base equilibria is developed to predict the concentration enrichment as a function of source-phase pH and analyte concentration. To test the concept, the accumulation of benzyldimethylamine (BDMA) was measured within individual 1 μm phospholipid vesicles having a stable initial pH that is 7 units lower than the source phase. For low analyte concentrations in the source phase (100 nM), a concentration enrichment into the vesicle interior of (5.2 ± 0.4) × 10(5) was observed, in agreement with the model predictions. Detection of BDMA from a 25 nM source-phase sample was demonstrated, a noteworthy result for an unenhanced Raman scattering measurement. The developed model accurately predicts the falloff of enrichment (and measurement sensitivity) at higher analyte concentrations, where the transfer of greater amounts of BDMA into the vesicle titrates the internal buffer and decreases the pH gradient. The predictable calibration response over 4 orders of magnitude in source-phase concentration makes it suitable for quantitative analysis of ionizable compounds from small-volume samples. The kinetics of analyte accumulation are relatively fast (∼15 min) and are consistent with the rate of transfer of a polar aromatic molecule across a gel-phase phospholipid membrane.

Generalized analytical solutions to multispecies transport equations with scale-dependent dispersion coefficients subject to time-dependent boundary conditions

NASA Astrophysics Data System (ADS)

Chen, J. S.; Chiang, S. Y.; Liang, C. P.

2017-12-01

It is essential to develop multispecies transport analytical models based on a set of advection-dispersion equations (ADEs) coupled with sequential first-order decay reactions for the synchronous prediction of plume migrations of both parent and its daughter species of decaying contaminants such as radionuclides, dissolved chlorinated organic compounds, pesticides and nitrogen. Although several analytical models for multispecies transport have already been reported, those currently available in the literature have primarily been derived based on ADEs with constant dispersion coefficients. However, there have been a number of studies demonstrating that the dispersion coefficients increase with the solute travel distance as a consequence of variation in the hydraulic properties of the porous media. This study presents novel analytical models for multispecies transport with distance-dependent dispersion coefficients. The correctness of the derived analytical models is confirmed by comparing them against the numerical models. Results show perfect agreement between the analytical and numerical models. Comparison of our new analytical model for multispecies transport with scale-dependent dispersion to an analytical model with constant dispersion is made to illustrate the effects of the dispersion coefficients on the multispecies transport of decaying contaminants.

Model uncertainty of various settlement estimation methods in shallow tunnels excavation; case study: Qom subway tunnel

NASA Astrophysics Data System (ADS)

Khademian, Amir; Abdollahipour, Hamed; Bagherpour, Raheb; Faramarzi, Lohrasb

2017-10-01

In addition to the numerous planning and executive challenges, underground excavation in urban areas is always followed by certain destructive effects especially on the ground surface; ground settlement is the most important of these effects for which estimation there exist different empirical, analytical and numerical methods. Since geotechnical models are associated with considerable model uncertainty, this study characterized the model uncertainty of settlement estimation models through a systematic comparison between model predictions and past performance data derived from instrumentation. To do so, the amount of surface settlement induced by excavation of the Qom subway tunnel was estimated via empirical (Peck), analytical (Loganathan and Poulos) and numerical (FDM) methods; the resulting maximum settlement value of each model were 1.86, 2.02 and 1.52 cm, respectively. The comparison of these predicted amounts with the actual data from instrumentation was employed to specify the uncertainty of each model. The numerical model outcomes, with a relative error of 3.8%, best matched the reality and the analytical method, with a relative error of 27.8%, yielded the highest level of model uncertainty.

Testing a 1-D Analytical Salt Intrusion Model and the Predictive Equation in Malaysian Estuaries

NASA Astrophysics Data System (ADS)

Gisen, Jacqueline Isabella; Savenije, Hubert H. G.

2013-04-01

Little is known about the salt intrusion behaviour in Malaysian estuaries. Study on this topic sometimes requires large amounts of data especially if a 2-D or 3-D numerical models are used for analysis. In poor data environments, 1-D analytical models are more appropriate. For this reason, a fully analytical 1-D salt intrusion model, based on the theory of Savenije in 2005, was tested in three Malaysian estuaries (Bernam, Selangor and Muar) because it is simple and requires minimal data. In order to achieve that, site surveys were conducted in these estuaries during the dry season (June-August) at spring tide by moving boat technique. Data of cross-sections, water levels and salinity were collected, and then analysed with the salt intrusion model. This paper demonstrates a good fit between the simulated and observed salinity distribution for all three estuaries. Additionally, the calibrated Van der Burgh's coefficient K, Dispersion coefficient D0, and salt intrusion length L, for the estuaries also displayed a reasonable correlations with those calculated from the predictive equations. This indicates that not only is the salt intrusion model valid for the case studies in Malaysia but also the predictive model. Furthermore, the results from this study describe the current state of the estuaries with which the Malaysian water authority in Malaysia can make decisions on limiting water abstraction or dredging. Keywords: salt intrusion, Malaysian estuaries, discharge, predictive model, dispersion

Decisions through data: analytics in healthcare.

PubMed

Wills, Mary J

2014-01-01

The amount of data in healthcare is increasing at an astonishing rate. However, in general, the industry has not deployed the level of data management and analysis necessary to make use of those data. As a result, healthcare executives face the risk of being overwhelmed by a flood of unusable data. In this essay I argue that, in order to extract actionable information, leaders must take advantage of the promise of data analytics. Small data, predictive modeling expansion, and real-time analytics are three forms of data analytics. On the basis of my analysis for this study, I recommend all three for adoption. Recognizing the uniqueness of each organization's situation, I also suggest that practices, hospitals, and healthcare systems examine small data and conduct real-time analytics and that large-scale organizations managing populations of patients adopt predictive modeling. I found that all three solutions assist in the collection, management, and analysis of raw data to improve the quality of care and decrease costs.

Prediction of turning stability using receptance coupling

NASA Astrophysics Data System (ADS)

Jasiewicz, Marcin; Powałka, Bartosz

2018-01-01

This paper presents an issue of machining stability prediction of dynamic "lathe - workpiece" system evaluated using receptance coupling method. Dynamic properties of the lathe components (the spindle and the tailstock) are assumed to be constant and can be determined experimentally based on the results of the impact test. Hence, the variable of the system "machine tool - holder - workpiece" is the machined part, which can be easily modelled analytically. The method of receptance coupling enables a synthesis of experimental (spindle, tailstock) and analytical (machined part) models, so impact testing of the entire system becomes unnecessary. The paper presents methodology of analytical and experimental models synthesis, evaluation of the stability lobes and experimental validation procedure involving both the determination of the dynamic properties of the system and cutting tests. In the summary the experimental verification results would be presented and discussed.

The Role of a Reference Synthetic Data Generator within the Field of Learning Analytics

ERIC Educational Resources Information Center

Berg, Alan\tM.; Mol, Stefan T.; Kismihók, Gábor; Sclater, Niall

2016-01-01

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

PubMed Central

Dinov, Ivo D.; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W.; Price, Nathan D.; Van Horn, John D.; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M.; Dauer, William; Toga, Arthur W.

2016-01-01

Background A unique archive of Big Data on Parkinson’s Disease is collected, managed and disseminated by the Parkinson’s Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson’s disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data–large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources–all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Methods and Findings Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson’s disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Conclusions Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson’s disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications. PMID:27494614

Analytical Algorithms to Quantify the Uncertainty in Remaining Useful Life Prediction

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Saxena, Abhinav; Daigle, Matthew; Goebel, Kai

2013-01-01

This paper investigates the use of analytical algorithms to quantify the uncertainty in the remaining useful life (RUL) estimate of components used in aerospace applications. The prediction of RUL is affected by several sources of uncertainty and it is important to systematically quantify their combined effect by computing the uncertainty in the RUL prediction in order to aid risk assessment, risk mitigation, and decisionmaking. While sampling-based algorithms have been conventionally used for quantifying the uncertainty in RUL, analytical algorithms are computationally cheaper and sometimes, are better suited for online decision-making. While exact analytical algorithms are available only for certain special cases (for e.g., linear models with Gaussian variables), effective approximations can be made using the the first-order second moment method (FOSM), the first-order reliability method (FORM), and the inverse first-order reliability method (Inverse FORM). These methods can be used not only to calculate the entire probability distribution of RUL but also to obtain probability bounds on RUL. This paper explains these three methods in detail and illustrates them using the state-space model of a lithium-ion battery.

Ionization Efficiency of Doubly Charged Ions Formed from Polyprotic Acids in Electrospray Negative Mode

NASA Astrophysics Data System (ADS)

Liigand, Piia; Kaupmees, Karl; Kruve, Anneli

2016-07-01

The ability of polyprotic acids to give doubly charged ions in negative mode electrospray was studied and related to physicochemical properties of the acids via linear discriminant analysis (LDA). It was discovered that the compound has to be strongly acidic (low p K a1 and p K a2) and to have high hydrophobicity (log P ow) to become multiply charged. Ability to give multiply charged ions in ESI/MS cannot be directly predicted from the solution phase acidities. Therefore, for the first time, a quantitative model to predict the charge state of the analyte in ESI/MS is proposed and validated for small anions. Also, a model to predict ionization efficiencies of these analytes was developed. Results indicate that acidity of the analyte, its octanol-water partition coefficient, and charge delocalization are important factors that influence ionization efficiencies as well as charge states of the analytes. The pH of the solvent was also found to be an important factor influencing the ionization efficiency of doubly charged ions.

Assessment of analytical techniques for predicting solid propellant exhaust plumes

NASA Technical Reports Server (NTRS)

Tevepaugh, J. A.; Smith, S. D.; Penny, M. M.

1977-01-01

The calculation of solid propellant exhaust plume flow fields is addressed. Two major areas covered are: (1) the applicability of empirical data currently available to define particle drag coefficients, heat transfer coefficients, mean particle size and particle size distributions, and (2) thermochemical modeling of the gaseous phase of the flow field. Comparisons of experimentally measured and analytically predicted data are made. The experimental data were obtained for subscale solid propellant motors with aluminum loadings of 2, 10 and 15%. Analytical predictions were made using a fully coupled two-phase numerical solution. Data comparisons will be presented for radial distributions at plume axial stations of 5, 12, 16 and 20 diameters.

Analytic Formulation and Numerical Implementation of an Acoustic Pressure Gradient Prediction

NASA Technical Reports Server (NTRS)

Lee, Seongkyu; Brentner, Kenneth S.; Farassat, F.; Morris, Philip J.

2008-01-01

Two new analytical formulations of the acoustic pressure gradient have been developed and implemented in the PSU-WOPWOP rotor noise prediction code. The pressure gradient can be used to solve the boundary condition for scattering problems and it is a key aspect to solve acoustic scattering problems. The first formulation is derived from the gradient of the Ffowcs Williams-Hawkings (FW-H) equation. This formulation has a form involving the observer time differentiation outside the integrals. In the second formulation, the time differentiation is taken inside the integrals analytically. This formulation avoids the numerical time differentiation with respect to the observer time, which is computationally more efficient. The acoustic pressure gradient predicted by these new formulations is validated through comparison with available exact solutions for a stationary and moving monopole sources. The agreement between the predictions and exact solutions is excellent. The formulations are applied to the rotor noise problems for two model rotors. A purely numerical approach is compared with the analytical formulations. The agreement between the analytical formulations and the numerical method is excellent for both stationary and moving observer cases.

Mechanical behavior of regular open-cell porous biomaterials made of diamond lattice unit cells.

PubMed

Ahmadi, S M; Campoli, G; Amin Yavari, S; Sajadi, B; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

2014-06-01

Cellular structures with highly controlled micro-architectures are promising materials for orthopedic applications that require bone-substituting biomaterials or implants. The availability of additive manufacturing techniques has enabled manufacturing of biomaterials made of one or multiple types of unit cells. The diamond lattice unit cell is one of the relatively new types of unit cells that are used in manufacturing of regular porous biomaterials. As opposed to many other types of unit cells, there is currently no analytical solution that could be used for prediction of the mechanical properties of cellular structures made of the diamond lattice unit cells. In this paper, we present new analytical solutions and closed-form relationships for predicting the elastic modulus, Poisson׳s ratio, critical buckling load, and yield (plateau) stress of cellular structures made of the diamond lattice unit cell. The mechanical properties predicted using the analytical solutions are compared with those obtained using finite element models. A number of solid and porous titanium (Ti6Al4V) specimens were manufactured using selective laser melting. A series of experiments were then performed to determine the mechanical properties of the matrix material and cellular structures. The experimentally measured mechanical properties were compared with those obtained using analytical solutions and finite element (FE) models. It has been shown that, for small apparent density values, the mechanical properties obtained using analytical and numerical solutions are in agreement with each other and with experimental observations. The properties estimated using an analytical solution based on the Euler-Bernoulli theory markedly deviated from experimental results for large apparent density values. The mechanical properties estimated using FE models and another analytical solution based on the Timoshenko beam theory better matched the experimental observations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Description and comparison of selected models for hydrologic analysis of ground-water flow, St Joseph River basin, Indiana

USGS Publications Warehouse

Peters, J.G.

1987-01-01

The Indiana Department of Natural Resources (IDNR) is developing water-management policies designed to assess the effects of irrigation and other water uses on water supply in the basin. In support of this effort, the USGS, in cooperation with IDNR, began a study to evaluate appropriate methods for analyzing the effects of pumping on ground-water levels and streamflow in the basin 's glacial aquifer systems. Four analytical models describe drawdown for a nonleaky, confined aquifer and fully penetrating well; a leaky, confined aquifer and fully penetrating well; a leaky, confined aquifer and partially penetrating well; and an unconfined aquifer and partially penetrating well. Analytical equations, simplifying assumptions, and methods of application are described for each model. In addition to these four models, several other analytical models were used to predict the effects of ground-water pumping on water levels in the aquifer and on streamflow in local areas with up to two pumping wells. Analytical models for a variety of other hydrogeologic conditions are cited. A digital ground-water flow model was used to describe how a numerical model can be applied to a glacial aquifer system. The numerical model was used to predict the effects of six pumping plans in 46.5 sq mi area with as many as 150 wells. Water budgets for the six pumping plans were used to estimate the effect of pumping on streamflow reduction. Results of the analytical and numerical models indicate that, in general, the glacial aquifers in the basin are highly permeable. Radial hydraulic conductivity calculated by the analytical models ranged from 280 to 600 ft/day, compared to 210 and 360 ft/day used in the numerical model. Maximum seasonal pumping for irrigation produced maximum calculated drawdown of only one-fourth of available drawdown and reduced streamflow by as much as 21%. Analytical models are useful in estimating aquifer properties and predicting local effects of pumping in areas with simple lithology and boundary conditions and with few pumping wells. Numerical models are useful in regional areas with complex hydrogeology with many pumping wells and provide detailed water budgets useful for estimating the sources of water in pumping simulations. Numerical models are useful in constructing flow nets. The choice of which type of model to use is also based on the nature and scope of questions to be answered and on the degree of accuracy required. (Author 's abstract)

Charge conservation in electronegativity equalization and its implications for the electrostatic properties of fluctuating-charge models.

PubMed

Chen, Jiahao; Martínez, Todd J

2009-07-28

An analytical solution of fluctuating-charge models using Gaussian elimination allows us to isolate the contribution of charge conservation effects in determining the charge distribution. We use this analytical solution to calculate dipole moments and polarizabilities and show that charge conservation plays a critical role in maintaining the correct translational invariance of the electrostatic properties predicted by these models.

Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling

USGS Publications Warehouse

Briggs, Martin A.; Lautz, Laura K.; Buckley, Sean F.; Lane, John W.

2014-01-01

Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.

Mechanics Model of Plug Welding

NASA Technical Reports Server (NTRS)

Zuo, Q. K.; Nunes, A. C., Jr.

2015-01-01

An analytical model has been developed for the mechanics of friction plug welding. The model accounts for coupling of plastic deformation (material flow) and thermal response (plastic heating). The model predictions of the torque, energy, and pull force on the plug were compared to the data of a recent experiment, and the agreements between predictions and data are encouraging.

Modelling Complexity: Making Sense of Leadership Issues in 14-19 Education

ERIC Educational Resources Information Center

Briggs, Ann R. J.

2008-01-01

Modelling of statistical data is a well established analytical strategy. Statistical data can be modelled to represent, and thereby predict, the forces acting upon a structure or system. For the rapidly changing systems in the world of education, modelling enables the researcher to understand, to predict and to enable decisions to be based upon…

Bellows flow-induced vibrations

NASA Technical Reports Server (NTRS)

Tygielski, P. J.; Smyly, H. M.; Gerlach, C. R.

1983-01-01

The bellows flow excitation mechanism and results of comprehensive test program are summarized. The analytical model for predicting bellows flow induced stress is refined. The model includes the effects of an upstream elbow, arbitrary geometry, and multiple piles. A refined computer code for predicting flow induced stress is described which allows life prediction if a material S-N diagram is available.

A predictive pilot model for STOL aircraft landing

NASA Technical Reports Server (NTRS)

Kleinman, D. L.; Killingsworth, W. R.

1974-01-01

An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

PARAMO: A Parallel Predictive Modeling Platform for Healthcare Analytic Research using Electronic Health Records

PubMed Central

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R.; Stewart, Walter F.; Malin, Bradley; Sun, Jimeng

2014-01-01

Objective Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: 1) cohort construction, 2) feature construction, 3) cross-validation, 4) feature selection, and 5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. Methods To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which 1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, 2) schedules the tasks in a topological ordering of the graph, and 3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. Results We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 hours in parallel compared to 9 days if running sequentially. Conclusion This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. PMID:24370496

PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

PubMed

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R; Stewart, Walter F; Malin, Bradley; Sun, Jimeng

2014-04-01

Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3h in parallel compared to 9days if running sequentially. This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. Copyright © 2013 Elsevier Inc. All rights reserved.

Long Term Mean Local Time of the Ascending Node Prediction

NASA Technical Reports Server (NTRS)

McKinley, David P.

2007-01-01

Significant error has been observed in the long term prediction of the Mean Local Time of the Ascending Node on the Aqua spacecraft. This error of approximately 90 seconds over a two year prediction is a complication in planning and timing of maneuvers for all members of the Earth Observing System Afternoon Constellation, which use Aqua's MLTAN as the reference for their inclination maneuvers. It was determined that the source of the prediction error was the lack of a solid Earth tide model in the operational force models. The Love Model of the solid Earth tide potential was used to derive analytic corrections to the inclination and right ascension of the ascending node of Aqua's Sun-synchronous orbit. Additionally, it was determined that the resonance between the Sun and orbit plane of the Sun-synchronous orbit is the primary driver of this error. The analytic corrections have been added to the operational force models for the Aqua spacecraft reducing the two-year 90-second error to less than 7 seconds.

Aeroelastic Analysis for Rotorcraft

NASA Technical Reports Server (NTRS)

Johnson, W.

1982-01-01

Aeroelastic-analysis computer program incorporates an analytical model of aeroelastic behavior of wide range of rotorcraft. Such an analytical model is desirable for both pretest predictions and posttest correlations. Program can be applied in investigations of isolated rotor aeroelasticity and helicopter-flight dynamics and could be employed as basis for more-extensive investigations or aeroelastic behavior, such as automatic control system design.

Using Multilingual Analytics to Explore the Usage of a Learning Portal in Developing Countries

ERIC Educational Resources Information Center

Protonotarios, Vassilis; Stoitsis, Giannis; Kastrantas, Kostas; Sanchez-Alonso, Salvador

2013-01-01

Learning analytics is a domain that has been constantly evolving throughout recent years due to the acknowledgement of its importance by those using intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning [1]. Learning analytics may be applied in a…

Shuttle antenna radome technology test program. Volume 2: Development of S-band antenna interface design

NASA Technical Reports Server (NTRS)

Kuhlman, E. A.; Baranowski, L. C.

1977-01-01

The effects of the Thermal Protection Subsystem (TPS) contamination on the space shuttle orbiter S band quad antenna due to multiple mission buildup are discussed. A test fixture was designed, fabricated and exposed to ten cycles of simulated ground and flight environments. Radiation pattern and impedance tests were performed to measure the effects of the contaminates. The degradation in antenna performance was attributed to the silicone waterproofing in the TPS tiles rather than exposure to the contaminating sources used in the test program. Validation of the accuracy of an analytical thermal model is discussed. Thermal vacuum tests with a test fixture and a representative S band quad antenna were conducted to evaluate the predictions of the analytical thermal model for two orbital heating conditions and entry from each orbit. The results show that the accuracy of predicting the test fixture thermal responses is largely dependent on the ability to define the boundary and ambient conditions. When the test conditions were accurately included in the analytical model, the predictions were in excellent agreement with measurements.

Three-Dimensional Dynamic Deformation Measurements Using Stereoscopic Imaging and Digital Speckle Photography

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

Prentice, H. J.; Proud, W. G.

2006-07-28

A technique has been developed to determine experimentally the three-dimensional displacement field on the rear surface of a dynamically deforming plate. The technique combines speckle analysis with stereoscopy, using a modified angular-lens method: this incorporates split-frame photography and a simple method by which the effective lens separation can be adjusted and calibrated in situ. Whilst several analytical models exist to predict deformation in extended or semi-infinite targets, the non-trivial nature of the wave interactions complicates the generation and development of analytical models for targets of finite depth. By interrogating specimens experimentally to acquire three-dimensional strain data points, both analytical andmore » numerical model predictions can be verified more rigorously. The technique is applied to the quasi-static deformation of a rubber sheet and dynamically to Mild Steel sheets of various thicknesses.« less

3D analysis of eddy current loss in the permanent magnet coupling.

PubMed

Zhu, Zina; Meng, Zhuo

2016-07-01

This paper first presents a 3D analytical model for analyzing the radial air-gap magnetic field between the inner and outer magnetic rotors of the permanent magnet couplings by using the Amperian current model. Based on the air-gap field analysis, the eddy current loss in the isolation cover is predicted according to the Maxwell's equations. A 3D finite element analysis model is constructed to analyze the magnetic field spatial distributions and vector eddy currents, and then the simulation results obtained are analyzed and compared with the analytical method. Finally, the current losses of two types of practical magnet couplings are measured in the experiment to compare with the theoretical results. It is concluded that the 3D analytical method of eddy current loss in the magnet coupling is viable and could be used for the eddy current loss prediction of magnet couplings.

A methodology to enhance electromagnetic compatibility in joint military operations

NASA Astrophysics Data System (ADS)

Buckellew, William R.

The development and validation of an improved methodology to identify, characterize, and prioritize potential joint EMI (electromagnetic interference) interactions and identify and develop solutions to reduce the effects of the interference are discussed. The methodology identifies potential EMI problems using results from field operations, historical data bases, and analytical modeling. Operational expertise, engineering analysis, and testing are used to characterize and prioritize the potential EMI problems. Results can be used to resolve potential EMI during the development and acquisition of new systems and to develop engineering fixes and operational workarounds for systems already employed. The analytic modeling portion of the methodology is a predictive process that uses progressive refinement of the analysis and the operational electronic environment to eliminate noninterfering equipment pairs, defer further analysis on pairs lacking operational significance, and resolve the remaining EMI problems. Tests are conducted on equipment pairs to ensure that the analytical models provide a realistic description of the predicted interference.

A New Model for Temperature Jump at a Fluid-Solid Interface

PubMed Central

Shu, Jian-Jun; Teo, Ji Bin Melvin; Chan, Weng Kong

2016-01-01

The problem presented involves the development of a new analytical model for the general fluid-solid temperature jump. To the best of our knowledge, there are no analytical models that provide the accurate predictions of the temperature jump for both gas and liquid systems. In this paper, a unified model for the fluid-solid temperature jump has been developed based on our adsorption model of the interfacial interactions. Results obtained from this model are validated with available results from the literature. PMID:27764230

Pollen dispersal slows geographical range shift and accelerates ecological niche shift under climate change

PubMed Central

Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie

2016-01-01

Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change. PMID:27621443

Pollen dispersal slows geographical range shift and accelerates ecological niche shift under climate change.

PubMed

Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie

2016-09-27

Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change.

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform

PubMed Central

Poucke, Sven Van; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; Deyne, Cathy De

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner’s Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research. PMID:26731286

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

PubMed

Van Poucke, Sven; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; De Deyne, Cathy

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

PubMed Central

Austin, Peter C.; van Klaveren, David; Vergouwe, Yvonne; Nieboer, Daan; Lee, Douglas S.; Steyerberg, Ewout W.

2017-01-01

Objective Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting We illustrated different analytic methods for validation using a sample of 14,857 patients hospitalized with heart failure at 90 hospitals in two distinct time periods. Bootstrap resampling was used to assess internal validity. Meta-analytic methods were used to assess geographic transportability. Each hospital was used once as a validation sample, with the remaining hospitals used for model derivation. Hospital-specific estimates of discrimination (c-statistic) and calibration (calibration intercepts and slopes) were pooled using random effects meta-analysis methods. I2 statistics and prediction interval width quantified geographic transportability. Temporal transportability was assessed using patients from the earlier period for model derivation and patients from the later period for model validation. Results Estimates of reproducibility, pooled hospital-specific performance, and temporal transportability were on average very similar, with c-statistics of 0.75. Between-hospital variation was moderate according to I2 statistics and prediction intervals for c-statistics. Conclusion This study illustrates how performance of prediction models can be assessed in settings with multicenter data at different time periods. PMID:27262237

L-shaped piezoelectric motor--part II: analytical modeling.

PubMed

Avirovik, Dragan; Karami, M Amin; Inman, Daniel; Priya, Shashank

2012-01-01

This paper develops an analytical model for an L-shaped piezoelectric motor. The motor structure has been described in detail in Part I of this study. The coupling of the bending vibration mode of the bimorphs results in an elliptical motion at the tip. The emphasis of this paper is on the development of a precise analytical model which can predict the dynamic behavior of the motor based on its geometry. The motor was first modeled mechanically to identify the natural frequencies and mode shapes of the structure. Next, an electromechanical model of the motor was developed to take into account the piezoelectric effect, and dynamics of L-shaped piezoelectric motor were obtained as a function of voltage and frequency. Finally, the analytical model was validated by comparing it to experiment results and the finite element method (FEM). © 2012 IEEE

Buckling Testing and Analysis of Space Shuttle Solid Rocket Motor Cylinders

NASA Technical Reports Server (NTRS)

Weidner, Thomas J.; Larsen, David V.; McCool, Alex (Technical Monitor)

2002-01-01

A series of full-scale buckling tests were performed on the space shuttle Reusable Solid Rocket Motor (RSRM) cylinders. The tests were performed to determine the buckling capability of the cylinders and to provide data for analytical comparison. A nonlinear ANSYS Finite Element Analysis (FEA) model was used to represent and evaluate the testing. Analytical results demonstrated excellent correlation to test results, predicting the failure load within 5%. The analytical value was on the conservative side, predicting a lower failure load than was applied to the test. The resulting study and analysis indicated the important parameters for FEA to accurately predict buckling failure. The resulting method was subsequently used to establish the pre-launch buckling capability of the space shuttle system.

Analytical Modeling of Plasma Arc Cutting of Steel Plate

NASA Astrophysics Data System (ADS)

Cimbala, John; Fisher, Lance; Settles, Gary; Lillis, Milan

2000-11-01

A transferred-arc plasma torch cuts steel plate, and in the process ejects a molten stream of iron and ferrous oxides ("ejecta"). Under non-optimum conditions - especially during low speed cuts and/or small-radius corner cuts - "dross" is formed. Dross is re-solidified molten metal that sticks to the underside of the cut and renders it rough. The present research is an attempt to analytically model this process, with the goal of predicting dross formation. With the aid of experimental data, a control volume formulation is used in a steady frame of reference to predict the mass flow of molten material inside the cut. Although simple, the model is three-dimensional, can predict the shear stress driving the molten material in the direction of the plasma jet, and can predict the velocity of molten material exiting the bottom of the plate. In order to predict formation of dross, a momentum balance is performed on the flowing melt, considering the resisting viscous and surface tension forces. Preliminary results are promising, and provide a potential means of predicting dross formation without resorting to detailed computational analyses.

The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

NASA Technical Reports Server (NTRS)

Farassat, F.; Doty, Michael J.; Hunter, Craig A.

2004-01-01

The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

Chemoviscosity modeling for thermosetting resins - I

NASA Technical Reports Server (NTRS)

Hou, T. H.

1984-01-01

A new analytical model for chemoviscosity variation during cure of thermosetting resins was developed. This model is derived by modifying the widely used WLF (Williams-Landel-Ferry) Theory in polymer rheology. Major assumptions involved are that the rate of reaction is diffusion controlled and is linearly inversely proportional to the viscosity of the medium over the entire cure cycle. The resultant first order nonlinear differential equation is solved numerically, and the model predictions compare favorably with experimental data of EPON 828/Agent U obtained on a Rheometrics System 4 Rheometer. The model describes chemoviscosity up to a range of six orders of magnitude under isothermal curing conditions. The extremely non-linear chemoviscosity profile for a dynamic heating cure cycle is predicted as well. The model is also shown to predict changes of glass transition temperature for the thermosetting resin during cure. The physical significance of this prediction is unclear at the present time, however, and further research is required. From the chemoviscosity simulation point of view, the technique of establishing an analytical model as described here is easily applied to any thermosetting resin. The model thus obtained is used in real-time process controls for fabricating composite materials.

Analyses of ACPL thermal/fluid conditioning system

NASA Technical Reports Server (NTRS)

Stephen, L. A.; Usher, L. H.

1976-01-01

Results of engineering analyses are reported. Initial computations were made using a modified control transfer function where the systems performance was characterized parametrically using an analytical model. The analytical model was revised to represent the latest expansion chamber fluid manifold design, and systems performance predictions were made. Parameters which were independently varied in these computations are listed. Systems predictions which were used to characterize performance are primarily transient computer plots comparing the deviation between average chamber temperature and the chamber temperature requirement. Additional computer plots were prepared. Results of parametric computations with the latest fluid manifold design are included.

Predicting and explaining inflammation in Crohn's disease patients using predictive analytics methods and electronic medical record data.

PubMed

Reddy, Bhargava K; Delen, Dursun; Agrawal, Rupesh K

2018-01-01

Crohn's disease is among the chronic inflammatory bowel diseases that impact the gastrointestinal tract. Understanding and predicting the severity of inflammation in real-time settings is critical to disease management. Extant literature has primarily focused on studies that are conducted in clinical trial settings to investigate the impact of a drug treatment on the remission status of the disease. This research proposes an analytics methodology where three different types of prediction models are developed to predict and to explain the severity of inflammation in patients diagnosed with Crohn's disease. The results show that machine-learning-based analytic methods such as gradient boosting machines can predict the inflammation severity with a very high accuracy (area under the curve = 92.82%), followed by regularized regression and logistic regression. According to the findings, a combination of baseline laboratory parameters, patient demographic characteristics, and disease location are among the strongest predictors of inflammation severity in Crohn's disease patients.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

A crack-closure model for predicting fatigue-crack growth under aircraft spectrum loading

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1981-01-01

The development and application of an analytical model of cycle crack growth is presented that includes the effects of crack closure. The model was used to correlate crack growth rates under constant amplitude loading and to predict crack growth under aircraft spectrum loading on 2219-T851 aluminum alloy sheet material. The predicted crack growth lives agreed well with experimental data. The ratio of predicted to experimental lives ranged from 0.66 to 1.48. These predictions were made using data from an ASTM E24.06.01 Round Robin.

Thermal conductivity of microporous layers: Analytical modeling and experimental validation

NASA Astrophysics Data System (ADS)

Andisheh-Tadbir, Mehdi; Kjeang, Erik; Bahrami, Majid

2015-11-01

A new compact relationship is developed for the thermal conductivity of the microporous layer (MPL) used in polymer electrolyte fuel cells as a function of pore size distribution, porosity, and compression pressure. The proposed model is successfully validated against experimental data obtained from a transient plane source thermal constants analyzer. The thermal conductivities of carbon paper samples with and without MPL were measured as a function of load (1-6 bars) and the MPL thermal conductivity was found between 0.13 and 0.17 W m-1 K-1. The proposed analytical model predicts the experimental thermal conductivities within 5%. A correlation generated from the analytical model was used in a multi objective genetic algorithm to predict the pore size distribution and porosity for an MPL with optimized thermal conductivity and mass diffusivity. The results suggest that an optimized MPL, in terms of heat and mass transfer coefficients, has an average pore size of 122 nm and 63% porosity.

Understanding Fast and Robust Thermo-osmotic Flows through Carbon Nanotube Membranes: Thermodynamics Meets Hydrodynamics.

PubMed

Fu, Li; Merabia, Samy; Joly, Laurent

2018-04-19

Following our recent theoretical prediction of the giant thermo-osmotic response of the water-graphene interface, we explore the practical implementation of waste heat harvesting with carbon-based membranes, focusing on model membranes of carbon nanotubes (CNT). To that aim, we combine molecular dynamics simulations and an analytical model considering the details of hydrodynamics in the membrane and at the tube entrances. The analytical model and the simulation results match quantitatively, highlighting the need to take into account both thermodynamics and hydrodynamics to predict thermo-osmotic flows through membranes. We show that, despite viscous entrance effects and a thermal short-circuit mechanism, CNT membranes can generate very fast thermo-osmotic flows, which can overcome the osmotic pressure of seawater. We then show that in small tubes confinement has a complex effect on the flow and can even reverse the flow direction. Beyond CNT membranes, our analytical model can guide the search for other membranes to generate fast and robust thermo-osmotic flows.

Pressurization of cryogens - A review of current technology and its applicability to low-gravity conditions

NASA Technical Reports Server (NTRS)

Van Dresar, N. T.

1992-01-01

A review of technology, history, and current status for pressurized expulsion of cryogenic tankage is presented. Use of tank pressurization to expel cryogenic fluid will continue to be studied for future spacecraft applications over a range of operating conditions in the low-gravity environment. The review examines experimental test results and analytical model development for quiescent and agitated conditions in normal-gravity followed by a discussion of pressurization and expulsion in low-gravity. Validated, 1-D, finite difference codes exist for the prediction of pressurant mass requirements within the range of quiescent normal-gravity test data. To date, the effects of liquid sloshing have been characterized by tests in normal-gravity, but analytical models capable of predicting pressurant gas requirements remain unavailable. Efforts to develop multidimensional modeling capabilities in both normal and low-gravity have recently occurred. Low-gravity cryogenic fluid transfer experiments are needed to obtain low-gravity pressurized expulsion data. This data is required to guide analytical model development and to verify code performance.

Pressurization of cryogens: A review of current technology and its applicability to low-gravity conditions

NASA Technical Reports Server (NTRS)

Vandresar, N. T.

1992-01-01

A review of technology, history, and current status for pressurized expulsion of cryogenic tankage is presented. Use of tank pressurization to expel cryogenic fluids will continue to be studied for future spacecraft applications over a range of operating conditions in the low-gravity environment. The review examines experimental test results and analytical model development for quiescent and agitated conditions in normal-gravity, followed by a discussion of pressurization and expulsion in low-gravity. Validated, 1-D, finite difference codes exist for the prediction of pressurant mass requirements within the range of quiescent normal-gravity test data. To date, the effects of liquid sloshing have been characterized by tests in normal-gravity, but analytical models capable of predicting pressurant gas requirements remain unavailable. Efforts to develop multidimensional modeling capabilities in both normal and low-gravity have recently occurred. Low-gravity cryogenic fluid transfer experiments are needed to obtain low-gravity pressurized expulsion data. This data is required to guide analytical model development and to verify code performance.

Mated vertical ground vibration test

NASA Technical Reports Server (NTRS)

Ivey, E. W.

1980-01-01

The Mated Vertical Ground Vibration Test (MVGVT) was considered to provide an experimental base in the form of structural dynamic characteristics for the shuttle vehicle. This data base was used in developing high confidence analytical models for the prediction and design of loads, pogo controls, and flutter criteria under various payloads and operational missions. The MVGVT boost and launch program evolution, test configurations, and their suspensions are described. Test results are compared with predicted analytical results.

Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations

PubMed Central

Wall, Mark J.

2016-01-01

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions. PMID:27927788

Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations.

PubMed

Newton, Adam J H; Wall, Mark J; Richardson, Magnus J E

2017-03-01

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions. Copyright © 2017 the American Physiological Society.

Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior.

PubMed

Poore, Joshua C; Forlines, Clifton L; Miller, Sarah M; Regan, John R; Irvine, John M

2014-12-01

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures-personality, cognitive style, motivated cognition-predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated "top-down" cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains.

Personality, Cognitive Style, Motivation, and Aptitude Predict Systematic Trends in Analytic Forecasting Behavior

PubMed Central

Forlines, Clifton L.; Miller, Sarah M.; Regan, John R.; Irvine, John M.

2014-01-01

The decision sciences are increasingly challenged to advance methods for modeling analysts, accounting for both analytic strengths and weaknesses, to improve inferences taken from increasingly large and complex sources of data. We examine whether psychometric measures—personality, cognitive style, motivated cognition—predict analytic performance and whether psychometric measures are competitive with aptitude measures (i.e., SAT scores) as analyst sample selection criteria. A heterogeneous, national sample of 927 participants completed an extensive battery of psychometric measures and aptitude tests and was asked 129 geopolitical forecasting questions over the course of 1 year. Factor analysis reveals four dimensions among psychometric measures; dimensions characterized by differently motivated “top-down” cognitive styles predicted distinctive patterns in aptitude and forecasting behavior. These dimensions were not better predictors of forecasting accuracy than aptitude measures. However, multiple regression and mediation analysis reveals that these dimensions influenced forecasting accuracy primarily through bias in forecasting confidence. We also found that these facets were competitive with aptitude tests as forecast sampling criteria designed to mitigate biases in forecasting confidence while maximizing accuracy. These findings inform the understanding of individual difference dimensions at the intersection of analytic aptitude and demonstrate that they wield predictive power in applied, analytic domains. PMID:25983670

Experimental and analytical investigation of a modified ring cusp NSTAR engine

NASA Technical Reports Server (NTRS)

Sengupta, Anita

2005-01-01

A series of experimental measurements on a modified laboratory NSTAR engine were used to validate a zero dimensional analytical discharge performance model of a ring cusp ion thruster. The model predicts the discharge performance of a ring cusp NSTAR thruster as a function the magnetic field configuration, thruster geometry, and throttle level. Analytical formalisms for electron and ion confinement are used to predict the ionization efficiency for a given thruster design. Explicit determination of discharge loss and volume averaged plasma parameters are also obtained. The model was used to predict the performance of the nominal and modified three and four ring cusp 30-cm ion thruster configurations operating at the full power (2.3 kW) NSTAR throttle level. Experimental measurements of the modified engine configuration discharge loss compare well with the predicted value for propellant utilizations from 80 to 95%. The theory, as validated by experiment, indicates that increasing the magnetic strength of the minimum closed reduces maxwellian electron diffusion and electrostatically confines the ion population and subsequent loss to the anode wall. The theory also indicates that increasing the cusp strength and minimizing the cusp area improves primary electron confinement increasing the probability of an ionization collision prior to loss at the cusp.

Modeling the Soft Geometry of Biological Membranes

NASA Astrophysics Data System (ADS)

Daly, K.

This dissertation presents work done applying the techniques of physics to biological systems. The difference in length scales of the thickness of the phospolipid bilayer and overall size of a biological cell allows bilayer to be modeled elastically as a thin sheet. The Helfrich free energy is extended applied to models representing various biological systems, in order to find quasi-equilibrium states as well as transitions between states. Morphologies are approximated as axially sym-metric. Stable morphologies are de-termined analytically and through the use of computer simulation. The simple morphologies examined analytically give a model for the pearling transition seen in growing biological cells. An analytic model of celluar bulging in gram-negative bacteria predicts a critical pore radius for bulging of 20 nanometers. This model is extended to the membrane dynamics of human red blood cells, predicting three morphologic phases which are seen in vivo. A computer simulation was developed to study more complex morphologies with models representing different bilayer compositions. Single and multi-component bilayer models reproduce morphologies previously predicted by Seifert. A mean field model representing the intrinsic curvature of proteins coupling to membrane curvature is used to explore the stability of the particular morphology of rod outer segment cells. The process of pore formation and expansion in cell-cell fusion is not well understood. Simulation of the pore created in cell-cell fusion led to the finding of a minimal pore radius required for pore expansion, suggesting pores formed in nature are formed with a minimum size.

Design and Analysis of a Preconcentrator for the ChemLab

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

WONG,CHUNGNIN C.; FLEMMING,JEB H.; MANGINELL,RONALD P.

2000-07-17

Preconcentration is a critical analytical procedure when designing a microsystem for trace chemical detection, because it can purify a sample mixture and boost the small analyte concentration to a much higher level allowing a better analysis. This paper describes the development of a micro-fabricated planar preconcentrator for the {mu}ChemLab{trademark} at Sandia. To guide the design, an analytical model to predict the analyte transport, adsorption and resorption process in the preconcentrator has been developed. Experiments have also been conducted to analyze the adsorption and resorption process and to validate the model. This combined effort of modeling, simulation, and testing has ledmore » us to build a reliable, efficient preconcentrator with good performance.« less

Verification of spatial and temporal pressure distributions in segmented solid rocket motors

NASA Technical Reports Server (NTRS)

Salita, Mark

1989-01-01

A wide variety of analytical tools are in use today to predict the history and spatial distributions of pressure in the combustion chambers of solid rocket motors (SRMs). Experimental and analytical methods are presented here that allow the verification of many of these predictions. These methods are applied to the redesigned space shuttle booster (RSRM). Girth strain-gage data is compared to the predictions of various one-dimensional quasisteady analyses in order to verify the axial drop in motor static pressure during ignition transients as well as quasisteady motor operation. The results of previous modeling of radial flows in the bore, slots, and around grain overhangs are supported by approximate analytical and empirical techniques presented here. The predictions of circumferential flows induced by inhibitor asymmetries, nozzle vectoring, and propellant slump are compared to each other and to subscale cold air and water tunnel measurements to ascertain their validity.

Study on bending behaviour of nickel–titanium rotary endodontic instruments by analytical and numerical analyses

PubMed Central

Tsao, C C; Liou, J U; Wen, P H; Peng, C C; Liu, T S

2013-01-01

Aim To develop analytical models and analyse the stress distribution and flexibility of nickel–titanium (NiTi) instruments subject to bending forces. Methodology The analytical method was used to analyse the behaviours of NiTi instruments under bending forces. Two NiTi instruments (RaCe and Mani NRT) with different cross-sections and geometries were considered. Analytical results were derived using Euler–Bernoulli nonlinear differential equations that took into account the screw pitch variation of these NiTi instruments. In addition, the nonlinear deformation analysis based on the analytical model and the finite element nonlinear analysis was carried out. Numerical results are obtained by carrying out a finite element method. Results According to analytical results, the maximum curvature of the instrument occurs near the instrument tip. Results of the finite element analysis revealed that the position of maximum von Mises stress was near the instrument tip. Therefore, the proposed analytical model can be used to predict the position of maximum curvature in the instrument where fracture may occur. Finally, results of analytical and numerical models were compatible. Conclusion The proposed analytical model was validated by numerical results in analysing bending deformation of NiTi instruments. The analytical model is useful in the design and analysis of instruments. The proposed theoretical model is effective in studying the flexibility of NiTi instruments. Compared with the finite element method, the analytical model can deal conveniently and effectively with the subject of bending behaviour of rotary NiTi endodontic instruments. PMID:23173762

Theory and observations of upward field-aligned currents at the magnetopause boundary layer.

PubMed

Wing, Simon; Johnson, Jay R

2015-11-16

The dependence of the upward field-aligned current density ( J ‖ ) at the dayside magnetopause boundary layer is well described by a simple analytic model based on a velocity shear generator. A previous observational survey confirmed that the scaling properties predicted by the analytical model are applicable between 11 and 17 MLT. We utilize the analytic model to predict field-aligned currents using solar wind and ionospheric parameters and compare with direct observations. The calculated and observed parallel currents are in excellent agreement, suggesting that the model may be useful to infer boundary layer structures. However, near noon, where velocity shear is small, the kinetic pressure gradients and thermal currents, which are not included in the model, could make a small but significant contribution to J ‖ . Excluding data from noon, our least squares fit returns log( J ‖,max_cal ) = (0.96 ± 0.04) log( J ‖_obs ) + (0.03 ± 0.01) where J ‖,max_cal = calculated J ‖,max and J ‖_obs = observed J ‖ .

Analytical Prediction of the Seismic Response of a Reinforced Concrete Containment Vessel

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

James, R.J.; Rashid, Y.R.; Cherry, J.L.

Under the sponsorship of the Ministry of International Trade and Industry (MITI) of Japan, the Nuclear Power Engineering Corporation (NUPEC) is investigating the seismic behavior of a Reinforced Concrete Containment Vessel (RCCV) through scale-model testing using the high-performance shaking table at the Tadotsu Engineering Laboratory. A series of tests representing design-level seismic ground motions was initially conducted to gather valuable experimental measurements for use in design verification. Additional tests will be conducted with increasing amplifications of the seismic input until a structural failure of the test model occurs. In a cooperative program with NUPEC, the US Nuclear Regulatory Commission (USNRC),more » through Sandia National Laboratories (SNL), is conducting analytical research on the seismic behavior of RCCV structures. As part of this program, pretest analytical predictions of the model tests are being performed. The dynamic time-history analysis utilizes a highly detailed concrete constitutive model applied to a three-dimensional finite element representation of the test structure. This paper describes the details of the analysis model and provides analysis results.« less

Micromechanics Analysis Code (MAC) User Guide: Version 1.0

NASA Technical Reports Server (NTRS)

Wilt, T. E.; Arnold, S. M.

1994-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code, MAC, who's predictive capability rests entirely upon the fully analytical generalized method of cells, GMC, micromechanics model is described. MAC is a versatile form of research software that 'drives' the double or triple ply periodic micromechanics constitutive models based upon GMC. MAC enhances the basic capabilities of GMC by providing a modular framework wherein (1) various thermal, mechanical (stress or strain control), and thermomechanical load histories can be imposed; (2) different integration algorithms may be selected; (3) a variety of constituent constitutive models may be utilized and/or implemented; and (4) a variety of fiber architectures may be easily accessed through their corresponding representative volume elements.

Micromechanics Analysis Code (MAC). User Guide: Version 2.0

NASA Technical Reports Server (NTRS)

Wilt, T. E.; Arnold, S. M.

1996-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code's (MAC) who's predictive capability rests entirely upon the fully analytical generalized method of cells (GMC), micromechanics model is described. MAC is a versatile form of research software that 'drives' the double or triply periodic micromechanics constitutive models based upon GMC. MAC enhances the basic capabilities of GMC by providing a modular framework wherein (1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, (2) different integration algorithms may be selected, (3) a variety of constituent constitutive models may be utilized and/or implemented, and (4) a variety of fiber and laminate architectures may be easily accessed through their corresponding representative volume elements.

The design, analysis and experimental evaluation of an elastic model wing

NASA Technical Reports Server (NTRS)

Cavin, R. K., III; Thisayakorn, C.

1974-01-01

An elastic orbiter model was developed to evaluate the effectiveness of aeroelasticity computer programs. The elasticity properties were introduced by constructing beam-like straight wings for the wind tunnel model. A standard influence coefficient mathematical model was used to estimate aeroelastic effects analytically. In general good agreement was obtained between the empirical and analytical estimates of the deformed shape. However, in the static aeroelasticity case, it was found that the physical wing exhibited less bending and more twist than was predicted by theory.

Analytical and Finite Element Modeling of Nanomembranes for Miniaturized, Continuous Hemodialysis

PubMed Central

Burgin, Tucker; Johnson, Dean; Chung, Henry; Clark, Alfred; McGrath, James

2015-01-01

Hemodialysis involves large, periodic treatment doses using large-area membranes. If the permeability of dialysis membranes could be increased, it would reduce the necessary dialyzer size and could enable a wearable device that administers a continuous, low dose treatment of chronic kidney disease. This paper explores the application of ultrathin silicon membranes to this purpose, by way of analytical and finite element models of diffusive and convective transport of plasma solutes during hemodialysis, which we show to be predictive of experimental results. A proof-of-concept miniature nanomembrane dialyzer design is then proposed and analytically predicted to clear uremic toxins at near-ideal levels, as measured by several markers of dialysis adequacy. This work suggests the feasibility of miniature nanomembrane-based dialyzers that achieve therapeutic levels of uremic toxin clearance for patients with kidney failure. PMID:26729179

Black hole radiation and S-matrix.

NASA Astrophysics Data System (ADS)

Russo, J. G.

1999-04-01

The existence of an S-matrix below the threshold of black hole formation would be enough to exhibit, through its analytic structure, eventual thresholds for the creation of new objects and to describe, through analytic continuation, the physics above them in a unitary framework. In the context of a two-dimensional exactly soluble model, the semiclassical dynamics of quantum black holes is obtained by analytically continuing the description of the regime where no black hole is formed. The resulting spectrum of outgoing radiation departs from the one predicted by the Hawking model by the time the outgoing modes arise from the horizon with Planck-order frequencies. The theory predicts an unconventional scenario for the evolution: black holes only radiate out an energy of Planck mass order, stabilizing after a transitory period. A similar picture is obtained in 3+1 dimensions with spherical symmetry.

Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.

PubMed

Tulabandhula, Theja; Rudin, Cynthia

2014-06-01

Our goal is to design a prediction and decision system for real-time use during a professional car race. In designing a knowledge discovery process for racing, we faced several challenges that were overcome only when domain knowledge of racing was carefully infused within statistical modeling techniques. In this article, we describe how we leveraged expert knowledge of the domain to produce a real-time decision system for tire changes within a race. Our forecasts have the potential to impact how racing teams can optimize strategy by making tire-change decisions to benefit their rank position. Our work significantly expands previous research on sports analytics, as it is the only work on analytical methods for within-race prediction and decision making for professional car racing.

Mechanics of additively manufactured porous biomaterials based on the rhombicuboctahedron unit cell.

PubMed

Hedayati, R; Sadighi, M; Mohammadi-Aghdam, M; Zadpoor, A A

2016-01-01

Thanks to recent developments in additive manufacturing techniques, it is now possible to fabricate porous biomaterials with arbitrarily complex micro-architectures. Micro-architectures of such biomaterials determine their physical and biological properties, meaning that one could potentially improve the performance of such biomaterials through rational design of micro-architecture. The relationship between the micro-architecture of porous biomaterials and their physical and biological properties has therefore received increasing attention recently. In this paper, we studied the mechanical properties of porous biomaterials made from a relatively unexplored unit cell, namely rhombicuboctahedron. We derived analytical relationships that relate the micro-architecture of such porous biomaterials, i.e. the dimensions of the rhombicuboctahedron unit cell, to their elastic modulus, Poisson's ratio, and yield stress. Finite element models were also developed to validate the analytical solutions. Analytical and numerical results were compared with experimental data from one of our recent studies. It was found that analytical solutions and numerical results show a very good agreement particularly for smaller values of apparent density. The elastic moduli predicted by analytical and numerical models were in very good agreement with experimental observations too. While in excellent agreement with each other, analytical and numerical models somewhat over-predicted the yield stress of the porous structures as compared to experimental data. As the ratio of the vertical struts to the inclined struts, α, approaches zero and infinity, the rhombicuboctahedron unit cell respectively approaches the octahedron (or truncated cube) and cube unit cells. For those limits, the analytical solutions presented here were found to approach the analytic solutions obtained for the octahedron, truncated cube, and cube unit cells, meaning that the presented solutions are generalizations of the analytical solutions obtained for several other types of porous biomaterials. Copyright © 2015 Elsevier Ltd. All rights reserved.

Thermoelastic damping in microrings with circular cross-section

NASA Astrophysics Data System (ADS)

Li, Pu; Fang, Yuming; Zhang, Jianrun

2016-01-01

Predicting thermoelastic damping (TED) is crucial in the design of high Q micro-resonators. Microrings are often critical components in many micro-resonators. Some analytical models for TED in microrings have already been developed in the past. However, the previous works are limited to the microrings with rectangular cross-section. The temperature field in the rectangular cross-section is one-dimensional. This paper deals with TED in the microrings with circular cross-section. The temperature field in the circular cross-section is two-dimensional. This paper first presents a 2-D analytical model for TED in the microrings with circular cross-section. Only the two-dimensional heat conduction in the circular cross-section is considered. The heat conduction along the circumferential direction of the microring is neglected in the 2-D model. Then the 2-D model has been extended to cover the circumferential heat conduction, and a 3-D analytical model for TED has been developed. The analytical results from the present 2-D and 3-D models show good agreement with the numerical results of FEM model. The limitations of the present 2-D analytical model are assessed.

Improving a regional model using reduced complexity and parameter estimation

USGS Publications Warehouse

Kelson, Victor A.; Hunt, Randall J.; Haitjema, Henk M.

2002-01-01

The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model's prediction that, for a model that is properly calibrated for heads, regional drawdowns are relatively unaffected by the choice of aquifer properties, but that mine inflows are strongly affected. Paradoxically, by reducing model complexity, we have increased the understanding gained from the modeling effort.

Improving a regional model using reduced complexity and parameter estimation.

PubMed

Kelson, Victor A; Hunt, Randall J; Haitjema, Henk M

2002-01-01

The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model's prediction that, for a model that is properly calibrated for heads, regional drawdowns are relatively unaffected by the choice of aquifer properties, but that mine inflows are strongly affected. Paradoxically, by reducing model complexity, we have increased the understanding gained from the modeling effort.

Uncertainty of relative sensitivity factors in glow discharge mass spectrometry

NASA Astrophysics Data System (ADS)

Meija, Juris; Methven, Brad; Sturgeon, Ralph E.

2017-10-01

The concept of the relative sensitivity factors required for the correction of the measured ion beam ratios in pin-cell glow discharge mass spectrometry is examined in detail. We propose a data-driven model for predicting the relative response factors, which relies on a non-linear least squares adjustment and analyte/matrix interchangeability phenomena. The model provides a self-consistent set of response factors for any analyte/matrix combination of any element that appears as either an analyte or matrix in at least one known response factor.

Analytical modeling and experimental validation of a magnetorheological mount

NASA Astrophysics Data System (ADS)

Nguyen, The; Ciocanel, Constantin; Elahinia, Mohammad

2009-03-01

Magnetorheological (MR) fluid has been increasingly researched and applied in vibration isolation devices. To date, the suspension system of several high performance vehicles has been equipped with MR fluid based dampers and research is ongoing to develop MR fluid based mounts for engine and powertrain isolation. MR fluid based devices have received attention due to the MR fluid's capability to change its properties in the presence of a magnetic field. This characteristic places MR mounts in the class of semiactive isolators making them a desirable substitution for the passive hydraulic mounts. In this research, an analytical model of a mixed-mode MR mount was constructed. The magnetorheological mount employs flow (valve) mode and squeeze mode. Each mode is powered by an independent electromagnet, so one mode does not affect the operation of the other. The analytical model was used to predict the performance of the MR mount with different sets of parameters. Furthermore, in order to produce the actual prototype, the analytical model was used to identify the optimal geometry of the mount. The experimental phase of this research was carried by fabricating and testing the actual MR mount. The manufactured mount was tested to evaluate the effectiveness of each mode individually and in combination. The experimental results were also used to validate the ability of the analytical model in predicting the response of the MR mount. Based on the observed response of the mount a suitable controller can be designed for it. However, the control scheme is not addressed in this study.

Comparison of particle tracking algorithms in commercial CFD packages: sedimentation and diffusion.

PubMed

Robinson, Risa J; Snyder, Pam; Oldham, Michael J

2007-05-01

Computational fluid dynamic modeling software has enabled microdosimetry patterns of inhaled toxins and toxicants to be predicted and visualized, and is being used in inhalation toxicology and risk assessment. These predicted microdosimetry patterns in airway structures are derived from predicted airflow patterns within these airways and particle tracking algorithms used in computational fluid dynamics (CFD) software packages. Although these commercial CFD codes have been tested for accuracy under various conditions, they have not been well tested for respiratory flows in general. Nor has their particle tracking algorithm accuracy been well studied. In this study, three software packages, Fluent Discrete Phase Model (DPM), Fluent Fine Particle Model (FPM), and ANSYS CFX, were evaluated. Sedimentation and diffusion were each isolated in a straight tube geometry and tested for accuracy. A range of flow rates corresponding to adult low activity (minute ventilation = 10 L/min) and to heavy exertion (minute ventilation = 60 L/min) were tested by varying the range of dimensionless diffusion and sedimentation parameters found using the Weibel symmetric 23 generation lung morphology. Numerical results for fully developed parabolic and uniform (slip) profiles were compared respectively, to Pich (1972) and Yu (1977) analytical sedimentation solutions. Schum and Yeh (1980) equations for sedimentation were also compared. Numerical results for diffusional deposition were compared to analytical solutions of Ingham (1975) for parabolic and uniform profiles. Significant differences were found among the various CFD software packages and between numerical and analytical solutions. Therefore, it is prudent to validate CFD predictions against analytical solutions in idealized geometry before tackling the complex geometries of the respiratory tract.

A semi-analytical model for the acoustic impedance of finite length circular holes with mean flow

NASA Astrophysics Data System (ADS)

Yang, Dong; Morgans, Aimee S.

2016-12-01

The acoustic response of a circular hole with mean flow passing through it is highly relevant to Helmholtz resonators, fuel injectors, perforated plates, screens, liners and many other engineering applications. A widely used analytical model [M.S. Howe. "Onthe theory of unsteady high Reynolds number flow through a circular aperture", Proc. of the Royal Soc. A. 366, 1725 (1979), 205-223] which assumes an infinitesimally short hole was recently shown to be insufficient for predicting the impedance of holes with a finite length. In the present work, an analytical model based on Green's function method is developed to take the hole length into consideration for "short" holes. The importance of capturing the modified vortex noise accurately is shown. The vortices shed at the hole inlet edge are convected to the hole outlet and further downstream to form a vortex sheet. This couples with the acoustic waves and this coupling has the potential to generate as well as absorb acoustic energy in the low frequency region. The impedance predicted by this model shows the importance of capturing the path of the shed vortex. When the vortex path is captured accurately, the impedance predictions agree well with previous experimental and CFD results, for example predicting the potential for generation of acoustic energy at higher frequencies. For "long" holes, a simplified model which combines Howe's model with plane acoustic waves within the hole is developed. It is shown that the most important effect in this case is the acoustic non-compactness of the hole.

Statistical Learning Theory for High Dimensional Prediction: Application to Criterion-Keyed Scale Development

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Duberstein, Paul

2016-01-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in “big data” problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how three common SLT algorithms–Supervised Principal Components, Regularization, and Boosting—can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach—or perhaps because of them–SLT methods may hold value as a statistically rigorous approach to exploratory regression. PMID:27454257

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

A Proposed Method to Predict Preterm Birth Using Clinical Data, Standard Maternal Serum Screening, and Cholesterol

PubMed Central

ALLEMAN, Brandon W.; SMITH, Amanda R.; BYERS, Heather M.; BEDELL, Bruce; RYCKMAN, Kelli K.; MURRAY, Jeffrey C.; BOROWSKI, Kristi S.

2013-01-01

Objective To create a predictive model for preterm birth (PTB) from available clinical data and serum analytes. Study Design Serum analytes, routine pregnancy screening plus cholesterol and corresponding health information were linked to birth certificate data for a cohort of 2699 Iowa women with serum sampled in the first and second trimester. Stepwise logistic regression was used to select the best predictive model for PTB. Results Serum screening markers remained significant predictors of PTB even after controlling for maternal characteristics. The best predictive model included maternal characteristics, first trimester total cholesterol (TC), TC change between trimesters and second trimester alpha-fetoprotein and inhibin A. The model showed better discriminatory ability than PTB history alone and performed similarly in subgroups of women without past PTB. Conclusions Using clinical and serum screening data a potentially useful predictor of PTB was constructed. Validation and replication in other populations, and incorporation of other measures that identify PTB risk, like cervical length, can be a step towards identifying additional women who may benefit from new or currently available interventions. PMID:23500456

Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

NASA Astrophysics Data System (ADS)

Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

2015-07-01

Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

Description of a Generalized Analytical Model for the Micro-dosimeter Response

NASA Technical Reports Server (NTRS)

Badavi, Francis F.; Stewart-Sloan, Charlotte R.; Xapsos, Michael A.; Shinn, Judy L.; Wilson, John W.; Hunter, Abigail

2007-01-01

An analytical prediction capability for space radiation in Low Earth Orbit (LEO), correlated with the Space Transportation System (STS) Shuttle Tissue Equivalent Proportional Counter (TEPC) measurements, is presented. The model takes into consideration the energy loss straggling and chord length distribution of the TEPC detector, and is capable of predicting energy deposition fluctuations in a micro-volume by incoming ions through both direct and indirect ionic events. The charged particle transport calculations correlated with STS 56, 51, 110 and 114 flights are accomplished by utilizing the most recent version (2005) of the Langley Research Center (LaRC) deterministic ionized particle transport code High charge (Z) and Energy TRaNsport WZETRN), which has been extensively validated with laboratory beam measurements and available space flight data. The agreement between the TEPC model prediction (response function) and the TEPC measured differential and integral spectra in lineal energy (y) domain is promising.

Towards Actionable Learning Analytics Using Dispositions

ERIC Educational Resources Information Center

Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan

2017-01-01

Studies in the field of learning analytics (LA) have shown students' demographics and learning management system (LMS) data to be effective identifiers of "at risk" performance. However, insights generated by these predictive models may not be suitable for pedagogically informed interventions due to the inability to explain why students…

Evaluation of simplified stream-aquifer depletion models for water rights administration

USGS Publications Warehouse

Sophocleous, Marios; Koussis, Antonis; Martin, J.L.; Perkins, S.P.

1995-01-01

We assess the predictive accuracy of Glover's (1974) stream-aquifer analytical solutions, which are commonly used in administering water rights, and evaluate the impact of the assumed idealizations on administrative and management decisions. To achieve these objectives, we evaluate the predictive capabilities of the Glover stream-aquifer depletion model against the MODFLOW numerical standard, which, unlike the analytical model, can handle increasing hydrogeologic complexity. We rank-order and quantify the relative importance of the various assumptions on which the analytical model is based, the three most important being: (1) streambed clogging as quantified by streambed-aquifer hydraulic conductivity contrast; (2) degree of stream partial penetration; and (3) aquifer heterogeneity. These three factors relate directly to the multidimensional nature of the aquifer flow conditions. From these considerations, future efforts to reduce the uncertainty in stream depletion-related administrative decisions should primarily address these three factors in characterizing the stream-aquifer process. We also investigate the impact of progressively coarser model grid size on numerically estimating stream leakage and conclude that grid size effects are relatively minor. Therefore, when modeling is required, coarser model grids could be used thus minimizing the input data requirements.

Analytical mesoscale modeling of aeolian sand transport

NASA Astrophysics Data System (ADS)

Lämmel, Marc; Kroy, Klaus

2017-11-01

The mesoscale structure of aeolian sand transport determines a variety of natural phenomena studied in planetary and Earth science. We analyze it theoretically beyond the mean-field level, based on the grain-scale transport kinetics and splash statistics. A coarse-grained analytical model is proposed and verified by numerical simulations resolving individual grain trajectories. The predicted height-resolved sand flux and other important characteristics of the aeolian transport layer agree remarkably well with a comprehensive compilation of field and wind-tunnel data, suggesting that the model robustly captures the essential mesoscale physics. By comparing the predicted saturation length with field data for the minimum sand-dune size, we elucidate the importance of intermittent turbulent wind fluctuations for field measurements and reconcile conflicting previous models for this most enigmatic emergent aeolian scale.

Assessment and prediction of drying shrinkage cracking in bonded mortar overlays

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

Beushausen, Hans, E-mail: hans.beushausen@uct.ac.za; Chilwesa, Masuzyo

2013-11-15

Restrained drying shrinkage cracking was investigated on composite beams consisting of substrate concrete and bonded mortar overlays, and compared to the performance of the same mortars when subjected to the ring test. Stress development and cracking in the composite specimens were analytically modeled and predicted based on the measurement of relevant time-dependent material properties such as drying shrinkage, elastic modulus, tensile relaxation and tensile strength. Overlay cracking in the composite beams could be very well predicted with the analytical model. The ring test provided a useful qualitative comparison of the cracking performance of the mortars. The duration of curing wasmore » found to only have a minor influence on crack development. This was ascribed to the fact that prolonged curing has a beneficial effect on tensile strength at the onset of stress development, but is in the same time not beneficial to the values of tensile relaxation and elastic modulus. -- Highlights: •Parameter study on material characteristics influencing overlay cracking. •Analytical model gives good quantitative indication of overlay cracking. •Ring test presents good qualitative indication of overlay cracking. •Curing duration has little effect on overlay cracking.« less

Loss model for off-design performance analysis of radial turbines with pivoting-vane, variable-area stators

NASA Technical Reports Server (NTRS)

Meitner, P. L.; Glassman, A. J.

1980-01-01

An off-design performance loss model for a radial turbine with pivoting, variable-area stators is developed through a combination of analytical modeling and experimental data analysis. A viscous loss model is used for the variation in stator loss with setting angle, and stator vane end-clearance leakage effects are predicted by a clearance flow model. The variation of rotor loss coefficient with stator setting angle is obtained by means of an analytical matching of experimental data for a rotor that was tested with six stators, having throat areas from 20 to 144% of the design area. An incidence loss model is selected to obtain best agreement with experimental data. The stator vane end-clearance leakage model predicts increasing mass flow and decreasing efficiency as a result of end-clearances, with changes becoming significantly larger with decreasing stator area.

Capillary device refilling. [liquid rocket propellant tank tests

NASA Technical Reports Server (NTRS)

Blatt, M. H.; Merino, F.; Symons, E. P.

1980-01-01

An analytical and experimental study was conducted dealing with refilling start baskets (capillary devices) with settled fluid. A computer program was written to include dynamic pressure, screen wicking, multiple-screen barriers, standpipe screens, variable vehicle mass for computing vehicle acceleration, and calculation of tank outflow rate and vapor pullthrough height. An experimental apparatus was fabricated and tested to provide data for correlation with the analytical model; the test program was conducted in normal gravity using a scale-model capillary device and ethanol as the test fluid. The test data correlated with the analytical model; the model is a versatile and apparently accurate tool for predicting start basket refilling under actual mission conditions.

An analytical technique for predicting the characteristics of a flexible wing equipped with an active flutter-suppression system and comparison with wind-tunnel data

NASA Technical Reports Server (NTRS)

Abel, I.

1979-01-01

An analytical technique for predicting the performance of an active flutter-suppression system is presented. This technique is based on the use of an interpolating function to approximate the unsteady aerodynamics. The resulting equations are formulated in terms of linear, ordinary differential equations with constant coefficients. This technique is then applied to an aeroelastic model wing equipped with an active flutter-suppression system. Comparisons between wind-tunnel data and analysis are presented for the wing both with and without active flutter suppression. Results indicate that the wing flutter characteristics without flutter suppression can be predicted very well but that a more adequate model of wind-tunnel turbulence is required when the active flutter-suppression system is used.

Rotor/Wing Interactions in Hover

NASA Technical Reports Server (NTRS)

Young, Larry A.; Derby, Michael R.

2002-01-01

Hover predictions of tiltrotor aircraft are hampered by the lack of accurate and computationally efficient models for rotor/wing interactional aerodynamics. This paper summarizes the development of an approximate, potential flow solution for the rotor-on-rotor and wing-on-rotor interactions. This analysis is based on actuator disk and vortex theory and the method of images. The analysis is applicable for out-of-ground-effect predictions. The analysis is particularly suited for aircraft preliminary design studies. Flow field predictions from this simple analytical model are validated against experimental data from previous studies. The paper concludes with an analytical assessment of the influence of rotor-on-rotor and wing-on-rotor interactions. This assessment examines the effect of rotor-to-wing offset distance, wing sweep, wing span, and flaperon incidence angle on tiltrotor inflow and performance.

Circular Functions Based Comprehensive Analysis of Plastic Creep Deformations in the Fiber Reinforced Composites

NASA Astrophysics Data System (ADS)

Monfared, Vahid

2016-12-01

Analytically based model is presented for behavioral analysis of the plastic deformations in the reinforced materials using the circular (trigonometric) functions. The analytical method is proposed to predict creep behavior of the fibrous composites based on basic and constitutive equations under a tensile axial stress. New insight of the work is to predict some important behaviors of the creeping matrix. In the present model, the prediction of the behaviors is simpler than the available methods. Principal creep strain rate behaviors are very noteworthy for designing the fibrous composites in the creeping composites. Analysis of the mentioned parameter behavior in the reinforced materials is necessary to analyze failure, fracture, and fatigue studies in the creep of the short fiber composites. Shuttles, spaceships, turbine blades and discs, and nozzle guide vanes are commonly subjected to the creep effects. Also, predicting the creep behavior is significant to design the optoelectronic and photonic advanced composites with optical fibers. As a result, the uniform behavior with constant gradient is seen in the principal creep strain rate behavior, and also creep rupture may happen at the fiber end. Finally, good agreements are found through comparing the obtained analytical and FEM results.

Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

PubMed

Taraji, Maryam; Haddad, Paul R; Amos, Ruth I J; Talebi, Mohammad; Szucs, Roman; Dolan, John W; Pohl, Chris A

2017-02-07

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R 2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

Communication — Modeling polymer-electrolyte fuel-cell agglomerates with double-trap kinetics

DOE PAGES

Pant, Lalit M.; Weber, Adam Z.

2017-04-14

A new semi-analytical agglomerate model is presented for polymer-electrolyte fuel-cell cathodes. The model uses double-trap kinetics for the oxygen-reduction reaction, which can capture the observed potential-dependent coverage and Tafel-slope changes. An iterative semi-analytical approach is used to obtain reaction rate constants from the double-trap kinetics, oxygen concentration at the agglomerate surface, and overall agglomerate reaction rate. The analytical method can predict reaction rates within 2% of the numerically simulated values for a wide range of oxygen concentrations, overpotentials, and agglomerate sizes, while saving simulation time compared to a fully numerical approach.

Verification of an Analytical Method for Measuring Crystal Nucleation Rates in Glasses from DTA Data

NASA Technical Reports Server (NTRS)

Ranasinghe, K. S.; Wei, P. F.; Kelton, K. F.; Ray, C. S.; Day, D. E.

2004-01-01

A recently proposed analytical (DTA) method for estimating the nucleation rates in glasses has been evaluated by comparing experimental data with numerically computed nucleation rates for a model lithium disilicate glass. The time and temperature dependent nucleation rates were predicted using the model and compared with those values from an analysis of numerically calculated DTA curves. The validity of the numerical approach was demonstrated earlier by a comparison with experimental data. The excellent agreement between the nucleation rates from the model calculations and fiom the computer generated DTA data demonstrates the validity of the proposed analytical DTA method.

Developing Uncertainty Models for Robust Flutter Analysis Using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Potter, Starr; Lind, Rick; Kehoe, Michael W. (Technical Monitor)

2001-01-01

A ground vibration test can be used to obtain information about structural dynamics that is important for flutter analysis. Traditionally, this information#such as natural frequencies of modes#is used to update analytical models used to predict flutter speeds. The ground vibration test can also be used to obtain uncertainty models, such as natural frequencies and their associated variations, that can update analytical models for the purpose of predicting robust flutter speeds. Analyzing test data using the -norm, rather than the traditional 2-norm, is shown to lead to a minimum-size uncertainty description and, consequently, a least-conservative robust flutter speed. This approach is demonstrated using ground vibration test data for the Aerostructures Test Wing. Different norms are used to formulate uncertainty models and their associated robust flutter speeds to evaluate which norm is least conservative.

A carrier-based analytical theory for negative capacitance symmetric double-gate field effect transistors and its simulation verification

NASA Astrophysics Data System (ADS)

Jiang, Chunsheng; Liang, Renrong; Wang, Jing; Xu, Jun

2015-09-01

A carrier-based analytical drain current model for negative capacitance symmetric double-gate field effect transistors (NC-SDG FETs) is proposed by solving the differential equation of the carrier, the Pao-Sah current formulation, and the Landau-Khalatnikov equation. The carrier equation is derived from Poisson’s equation and the Boltzmann distribution law. According to the model, an amplified semiconductor surface potential and a steeper subthreshold slope could be obtained with suitable thicknesses of the ferroelectric film and insulator layer at room temperature. Results predicted by the analytical model agree well with those of the numerical simulation from a 2D simulator without any fitting parameters. The analytical model is valid for all operation regions and captures the transitions between them without any auxiliary variables or functions. This model can be used to explore the operating mechanisms of NC-SDG FETs and to optimize device performance.

Turbine Vane External Heat Transfer. Volume 1: Analytical and Experimental Evaluation of Surface Heat Transfer Distributions with Leading Edge Showerhead Film Cooling

NASA Technical Reports Server (NTRS)

Turner, E. R.; Wilson, M. D.; Hylton, L. D.; Kaufman, R. M.

1985-01-01

Progress in predictive design capabilities for external heat transfer to turbine vanes was summarized. A two dimensional linear cascade (previously used to obtain vane surface heat transfer distributions on nonfilm cooled airfoils) was used to examine the effect of leading edge shower head film cooling on downstream heat transfer. The data were used to develop and evaluate analytical models. Modifications to the two dimensional boundary layer model are described. The results were used to formulate and test an effective viscosity model capable of predicting heat transfer phenomena downstream of the leading edge film cooling array on both the suction and pressure surfaces, with and without mass injection.

Modeling walker synchronization on the Millennium Bridge.

PubMed

Eckhardt, Bruno; Ott, Edward; Strogatz, Steven H; Abrams, Daniel M; McRobie, Allan

2007-02-01

On its opening day the London Millennium footbridge experienced unexpected large amplitude wobbling subsequent to the migration of pedestrians onto the bridge. Modeling the stepping of the pedestrians on the bridge as phase oscillators, we obtain a model for the combined dynamics of people and the bridge that is analytically tractable. It provides predictions for the phase dynamics of individual walkers and for the critical number of people for the onset of oscillations. Numerical simulations and analytical estimates reproduce the linear relation between pedestrian force and bridge velocity as observed in experiments. They allow prediction of the amplitude of bridge motion, the rate of relaxation to the synchronized state and the magnitude of the fluctuations due to a finite number of people.

Analytical methods for the development of Reynolds stress closures in turbulence

NASA Technical Reports Server (NTRS)

Speziale, Charles G.

1990-01-01

Analytical methods for the development of Reynolds stress models in turbulence are reviewed in detail. Zero, one and two equation models are discussed along with second-order closures. A strong case is made for the superior predictive capabilities of second-order closure models in comparison to the simpler models. The central points are illustrated by examples from both homogeneous and inhomogeneous turbulence. A discussion of the author's views concerning the progress made in Reynolds stress modeling is also provided along with a brief history of the subject.

Analytical prediction of sub-surface thermal history in translucent tissue phantoms during plasmonic photo-thermotherapy (PPTT).

PubMed

Dhar, Purbarun; Paul, Anup; Narasimhan, Arunn; Das, Sarit K

2016-12-01

Knowledge of thermal history and/or distribution in biological tissues during laser based hyperthermia is essential to achieve necrosis of tumour/carcinoma cells. A semi-analytical model to predict sub-surface thermal distribution in translucent, soft, tissue mimics has been proposed. The model can accurately predict the spatio-temporal temperature variations along depth and the anomalous thermal behaviour in such media, viz. occurrence of sub-surface temperature peaks. Based on optical and thermal properties, the augmented temperature and shift of the peak positions in case of gold nanostructure mediated tissue phantom hyperthermia can be predicted. Employing inverse approach, the absorption coefficient of nano-graphene infused tissue mimics is determined from the peak temperature and found to provide appreciably accurate predictions along depth. Furthermore, a simplistic, dimensionally consistent correlation to theoretically determine the position of the peak in such media is proposed and found to be consistent with experiments and computations. The model shows promise in predicting thermal distribution induced by lasers in tissues and deduction of therapeutic hyperthermia parameters, thereby assisting clinical procedures by providing a priori estimates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analytical and Experimental Evaluation of the Heat Transfer Distribution over the Surfaces of Turbine Vanes

NASA Technical Reports Server (NTRS)

Hylton, L. D.; Mihelc, M. S.; Turner, E. R.; Nealy, D. A.; York, R. E.

1983-01-01

Three airfoil data sets were selected for use in evaluating currently available analytical models for predicting airfoil surface heat transfer distributions in a 2-D flow field. Two additional airfoils, representative of highly loaded, low solidity airfoils currently being designed, were selected for cascade testing at simulated engine conditions. Some 2-D analytical methods were examined and a version of the STAN5 boundary layer code was chosen for modification. The final form of the method utilized a time dependent, transonic inviscid cascade code coupled to a modified version of the STAN5 boundary layer code featuring zero order turbulence modeling. The boundary layer code is structured to accommodate a full spectrum of empirical correlations addressing the coupled influences of pressure gradient, airfoil curvature, and free-stream turbulence on airfoil surface heat transfer distribution and boundary layer transitional behavior. Comparison of pedictions made with the model to the data base indicates a significant improvement in predictive capability.

Analytical and experimental evaluation of the heat transfer distribution over the surfaces of turbine vanes

NASA Astrophysics Data System (ADS)

Hylton, L. D.; Mihelc, M. S.; Turner, E. R.; Nealy, D. A.; York, R. E.

1983-05-01

Three airfoil data sets were selected for use in evaluating currently available analytical models for predicting airfoil surface heat transfer distributions in a 2-D flow field. Two additional airfoils, representative of highly loaded, low solidity airfoils currently being designed, were selected for cascade testing at simulated engine conditions. Some 2-D analytical methods were examined and a version of the STAN5 boundary layer code was chosen for modification. The final form of the method utilized a time dependent, transonic inviscid cascade code coupled to a modified version of the STAN5 boundary layer code featuring zero order turbulence modeling. The boundary layer code is structured to accommodate a full spectrum of empirical correlations addressing the coupled influences of pressure gradient, airfoil curvature, and free-stream turbulence on airfoil surface heat transfer distribution and boundary layer transitional behavior. Comparison of pedictions made with the model to the data base indicates a significant improvement in predictive capability.

Investigation of characteristics of feed system instabilities

NASA Technical Reports Server (NTRS)

Vaage, R. D.; Fidler, L. E.; Zehnle, R. A.

1972-01-01

The relationship between the structural and feed system natural frequencies in structure-propulsion system coupled longitudinal oscillations (pogo) is investigated. The feed system frequencies are usually very dependent upon the compressibility (compliance) of cavitation bubbles that exist to some extent in all operating turbopumps. This document includes: a complete review of cavitation mechanisms; development of a turbopump cavitation compliance model; an accumulation and analysis of all available cavitation compliance test data; and a correlation of empirical-analytical results. The analytical model is based on the analysis of flow relative to a set of cascaded blades, having any described shape, and assumes phase changes occur under conditions of isentropic equilibrium. Analytical cavitation compliance predictions for the J-2 LOX, F-1 LOX, H-1 LOX and LR87 oxidizer turbopump inducers do not compare favorably with test data. The model predicts much less cavitation than is derived from the test data. This implies that mechanisms other than blade cavitation contribute significantly to the total amount of turbopump cavitation.

Analytics to Action: Predictive Model Outcomes and a Communication Strategy for Student Persistence

ERIC Educational Resources Information Center

Miller, Nathan Brad; Bell, Bryan

2016-01-01

Increased federal attention to student completion metrics and uncertain financial forecasts have heightened the tenor of student retention conversations. Improved institutional retention rates will lead to higher completion rates and relieve some funding concerns. To accomplish these improvements, institutions have invested in analytics to better…

Numerically calibrated model for propagation of a relativistic unmagnetized jet in dense media

NASA Astrophysics Data System (ADS)

Harrison, Richard; Gottlieb, Ore; Nakar, Ehud

2018-06-01

Relativistic jets reside in high-energy astrophysical systems of all scales. Their interaction with the surrounding media is critical as it determines the jet evolution, observable signature, and feedback on the environment. During its motion, the interaction of the jet with the ambient media inflates a highly pressurized cocoon, which under certain conditions collimates the jet and strongly affects its propagation. Recently, Bromberg et al. derived a general simplified (semi-)analytic solution for the evolution of the jet and the cocoon in case of an unmagnetized jet that propagates in a medium with a range of density profiles. In this work we use a large suite of 2D and 3D relativistic hydrodynamic simulations in order to test the validity and accuracy of this model. We discuss the similarities and differences between the analytic model and numerical simulations and also, to some extent, between 2D and 3D simulations. Our main finding is that although the analytic model is highly simplified, it properly predicts the evolution of the main ingredients of the jet-cocoon system, including its temporal evolution and the transition between various regimes (e.g. collimated to uncollimated). The analytic solution predicts a jet head velocity that is faster by a factor of about 3 compared to the simulations, as long as the head velocity is Newtonian. We use the results of the simulations to calibrate the analytic model which significantly increases its accuracy. We provide an applet that calculates semi-analytically the propagation of a jet in an arbitrary density profile defined by the user at http://www.astro.tau.ac.il/˜ore/propagation.html.

Debris flow runup on vertical barriers and adverse slopes

USGS Publications Warehouse

Iverson, Richard M.; George, David L.; Logan, Matthew

2016-01-01

Runup of debris flows against obstacles in their paths is a complex process that involves profound flow deceleration and redirection. We investigate the dynamics and predictability of runup by comparing results from large-scale laboratory experiments, four simple analytical models, and a depth-integrated numerical model (D-Claw). The experiments and numerical simulations reveal the important influence of unsteady, multidimensional flow on runup, and the analytical models highlight key aspects of the underlying physics. Runup against a vertical barrier normal to the flow path is dominated by rapid development of a shock, or jump in flow height, associated with abrupt deceleration of the flow front. By contrast, runup on sloping obstacles is initially dominated by a smooth flux of mass and momentum from the flow body to the flow front, which precedes shock development and commonly increases the runup height. D-Claw simulations that account for the emergence of shocks show that predicted runup heights vary systematically with the adverse slope angle and also with the Froude number and degree of liquefaction (or effective basal friction) of incoming flows. They additionally clarify the strengths and limitations of simplified analytical models. Numerical simulations based on a priori knowledge of the evolving dynamics of incoming flows yield quite accurate runup predictions. Less predictive accuracy is attained in ab initio simulations that compute runup based solely on knowledge of static debris properties in a distant debris flow source area. Nevertheless, the paucity of inputs required in ab initio simulations enhances their prospective value in runup forecasting.

Analytical model of flame spread in full-scale room/corner tests (ISO9705)

Treesearch

Mark Dietenberger; Ondrej Grexa

1999-01-01

A physical, yet analytical, model of fire growth has predicted flame spread and rate of heat release (RHR) for an ISO9705 test scenario using bench-scale data from the cone calorimeter. The test scenario simulated was the propane ignition burner at the comer with a 100/300 kW program and the specimen lined on the walls only. Four phases of fire growth were simulated....

Model updating strategy for structures with localised nonlinearities using frequency response measurements

NASA Astrophysics Data System (ADS)

Wang, Xing; Hill, Thomas L.; Neild, Simon A.; Shaw, Alexander D.; Haddad Khodaparast, Hamed; Friswell, Michael I.

2018-02-01

This paper proposes a model updating strategy for localised nonlinear structures. It utilises an initial finite-element (FE) model of the structure and primary harmonic response data taken from low and high amplitude excitations. The underlying linear part of the FE model is first updated using low-amplitude test data with established techniques. Then, using this linear FE model, the nonlinear elements are localised, characterised, and quantified with primary harmonic response data measured under stepped-sine or swept-sine excitations. Finally, the resulting model is validated by comparing the analytical predictions with both the measured responses used in the updating and with additional test data. The proposed strategy is applied to a clamped beam with a nonlinear mechanism and good agreements between the analytical predictions and measured responses are achieved. Discussions on issues of damping estimation and dealing with data from amplitude-varying force input in the updating process are also provided.

Spectral multivariate calibration without laboratory prepared or determined reference analyte values.

PubMed

Ottaway, Josh; Farrell, Jeremy A; Kalivas, John H

2013-02-05

An essential part to calibration is establishing the analyte calibration reference samples. These samples must characterize the sample matrix and measurement conditions (chemical, physical, instrumental, and environmental) of any sample to be predicted. Calibration usually requires measuring spectra for numerous reference samples in addition to determining the corresponding analyte reference values. Both tasks are typically time-consuming and costly. This paper reports on a method named pure component Tikhonov regularization (PCTR) that does not require laboratory prepared or determined reference values. Instead, an analyte pure component spectrum is used in conjunction with nonanalyte spectra for calibration. Nonanalyte spectra can be from different sources including pure component interference samples, blanks, and constant analyte samples. The approach is also applicable to calibration maintenance when the analyte pure component spectrum is measured in one set of conditions and nonanalyte spectra are measured in new conditions. The PCTR method balances the trade-offs between calibration model shrinkage and the degree of orthogonality to the nonanalyte content (model direction) in order to obtain accurate predictions. Using visible and near-infrared (NIR) spectral data sets, the PCTR results are comparable to those obtained using ridge regression (RR) with reference calibration sets. The flexibility of PCTR also allows including reference samples if such samples are available.

Engine isolation for structural-borne interior noise reduction in a general aviation aircraft

NASA Technical Reports Server (NTRS)

Unruh, J. F.; Scheidt, D. C.

1981-01-01

Engine vibration isolation for structural-borne interior noise reduction is investigated. A laboratory based test procedure to simulate engine induced structure-borne noise transmission, the testing of a range of candidate isolators for relative performance data, and the development of an analytical model of the transmission phenomena for isolator design evaluation are addressed. The isolator relative performance test data show that the elastomeric isolators do not appear to operate as single degree of freedom systems with respect to noise isolation. Noise isolation beyond 150 Hz levels off and begins to decrease somewhat above 600 Hz. Coupled analytical and empirical models were used to study the structure-borne noise transmission phenomena. Correlation of predicted results with measured data show that (1) the modeling procedures are reasonably accurate for isolator design evaluation, (2) the frequency dependent properties of the isolators must be included in the model if reasonably accurate noise prediction beyond 150 Hz is desired. The experimental and analytical studies were carried out in the frequency range from 10 Hz to 1000 Hz.

Experimental Validation of the Transverse Shear Behavior of a Nomex Core for Sandwich Panels

NASA Astrophysics Data System (ADS)

Farooqi, M. I.; Nasir, M. A.; Ali, H. M.; Ali, Y.

2017-05-01

This work deals with determination of the transverse shear moduli of a Nomex® honeycomb core of sandwich panels. Their out-of-plane shear characteristics depend on the transverse shear moduli of the honeycomb core. These moduli were determined experimentally, numerically, and analytically. Numerical simulations were performed by using a unit cell model and three analytical approaches. Analytical calculations showed that two of the approaches provided reasonable predictions for the transverse shear modulus as compared with experimental results. However, the approach based upon the classical lamination theory showed large deviations from experimental data. Numerical simulations also showed a trend similar to that resulting from the analytical models.

Application of Interface Technology in Progressive Failure Analysis of Composite Panels

NASA Technical Reports Server (NTRS)

Sleight, D. W.; Lotts, C. G.

2002-01-01

A progressive failure analysis capability using interface technology is presented. The capability has been implemented in the COMET-AR finite element analysis code developed at the NASA Langley Research Center and is demonstrated on composite panels. The composite panels are analyzed for damage initiation and propagation from initial loading to final failure using a progressive failure analysis capability that includes both geometric and material nonlinearities. Progressive failure analyses are performed on conventional models and interface technology models of the composite panels. Analytical results and the computational effort of the analyses are compared for the conventional models and interface technology models. The analytical results predicted with the interface technology models are in good correlation with the analytical results using the conventional models, while significantly reducing the computational effort.

Multi-analytical Approaches Informing the Risk of Sepsis

NASA Astrophysics Data System (ADS)

Gwadry-Sridhar, Femida; Lewden, Benoit; Mequanint, Selam; Bauer, Michael

Sepsis is a significant cause of mortality and morbidity and is often associated with increased hospital resource utilization, prolonged intensive care unit (ICU) and hospital stay. The economic burden associated with sepsis is huge. With advances in medicine, there are now aggressive goal oriented treatments that can be used to help these patients. If we were able to predict which patients may be at risk for sepsis we could start treatment early and potentially reduce the risk of mortality and morbidity. Analytic methods currently used in clinical research to determine the risk of a patient developing sepsis may be further enhanced by using multi-modal analytic methods that together could be used to provide greater precision. Researchers commonly use univariate and multivariate regressions to develop predictive models. We hypothesized that such models could be enhanced by using multiple analytic methods that together could be used to provide greater insight. In this paper, we analyze data about patients with and without sepsis using a decision tree approach and a cluster analysis approach. A comparison with a regression approach shows strong similarity among variables identified, though not an exact match. We compare the variables identified by the different approaches and draw conclusions about the respective predictive capabilities,while considering their clinical significance.

Analytical and experimental studies on detection of longitudinal, L and inverted T cracks in isotropic and bi-material beams based on changes in natural frequencies

NASA Astrophysics Data System (ADS)

Ravi, J. T.; Nidhan, S.; Muthu, N.; Maiti, S. K.

2018-02-01

An analytical method for determination of dimensions of longitudinal crack in monolithic beams, based on frequency measurements, has been extended to model L and inverted T cracks. Such cracks including longitudinal crack arise in beams made of layered isotropic or composite materials. A new formulation for modelling cracks in bi-material beams is presented. Longitudinal crack segment sizes, for L and inverted T cracks, varying from 2.7% to 13.6% of length of Euler-Bernoulli beams are considered. Both forward and inverse problems have been examined. In the forward problems, the analytical results are compared with finite element (FE) solutions. In the inverse problems, the accuracy of prediction of crack dimensions is verified using FE results as input for virtual testing. The analytical results show good agreement with the actual crack dimensions. Further, experimental studies have been done to verify the accuracy of the analytical method for prediction of dimensions of three types of crack in isotropic and bi-material beams. The results show that the proposed formulation is reliable and can be employed for crack detection in slender beam like structures in practice.

An experimental and analytical investigation of isolated rotor flap-lag stability in forward flight

NASA Technical Reports Server (NTRS)

Gaonkar, Gopal H.; Mcnulty, Michael J.

1985-01-01

For flap-lag stability of isolated rotors, experimental and analytical investigations are conducted in hover and forward flight on the adequacy of a linear quasi-steady aerodynamics theory with dynamic inflow. Forward flight effects on lag regressing mode are emphasized. Accordingly, a soft inplane hingeless rotor with three blades is tested at advance ratios as high as 0.55 and at shaft angles as high as 20 deg. The 1.62-m model rotor is untrimmed with an essentially unrestricted tilt of the tip path plane. By computerized symbolic manipulation, an analytical model is developed in substall to predict stability margins with mode indentification. It also predicts substall and stall regions to help explain the correlation between theory and data. The correlation shows both the strengths and weaknesses of the data and theory, and promotes further insights into areas in which further study is needed in substall and stall.

Simultaneous determination of three herbicides by differential pulse voltammetry and chemometrics.

PubMed

Ni, Yongnian; Wang, Lin; Kokot, Serge

2011-01-01

A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D - first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples.

A Simplified Model of Moisture Transport in Hydrophilic Porous Media With Applications to Pharmaceutical Tablets.

PubMed

Klinzing, Gerard R; Zavaliangos, Antonios

2016-08-01

This work establishes a predictive model that explicitly recognizes microstructural parameters in the description of the overall mass uptake and local gradients of moisture into tablets. Model equations were formulated based on local tablet geometry to describe the transient uptake of moisture. An analytical solution to a simplified set of model equations was solved to predict the overall mass uptake and moisture gradients with the tablets. The analytical solution takes into account individual diffusion mechanisms in different scales of porosity and diffusion into the solid phase. The time constant of mass uptake was found to be a function of several key material properties, such as tablet relative density, pore tortuosity, and equilibrium moisture content of the material. The predictions of the model are in excellent agreement with experimental results for microcrystalline cellulose tablets without the need for parameter fitting. The model presented provides a new method to analyze the transient uptake of moisture into hydrophilic materials with the knowledge of only a few fundamental material and microstructural parameters. In addition, the model allows for quick and insightful predictions of moisture diffusion for a variety of practical applications including pharmaceutical tablets, porous polymer systems, or cementitious materials. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Investigation of the short argon arc with hot anode. II. Analytical model

NASA Astrophysics Data System (ADS)

Khrabry, A.; Kaganovich, I. D.; Nemchinsky, V.; Khodak, A.

2018-01-01

A short atmospheric pressure argon arc is studied numerically and analytically. In a short arc with an inter-electrode gap of several millimeters, non-equilibrium effects in plasma play an important role in operation of the arc. High anode temperature leads to electron emission and intensive radiation from its surface. A complete, self-consistent analytical model of the whole arc comprising of models for near-electrode regions, arc column, and a model of heat transfer in cylindrical electrodes was developed. The model predicts the width of non-equilibrium layers and arc column, voltages and plasma profiles in these regions, and heat and ion fluxes to the electrodes. Parametric studies of the arc have been performed for a range of the arc current densities, inter-electrode gap widths, and gas pressures. The model was validated against experimental data and verified by comparison with numerical solution. Good agreement between the analytical model and simulations and reasonable agreement with experimental data were obtained.

Investigation of the short argon arc with hot anode. II. Analytical model

DOE PAGES

Khrabry, A.; Kaganovich, I. D.; Nemchinsky, V.; ...

2018-01-22

A short atmospheric pressure argon arc is studied numerically and analytically. In a short arc with an inter-electrode gap of several millimeters, non-equilibrium effects in plasma play an important role in operation of the arc. High anode temperature leads to electron emission and intensive radiation from its surface. A complete, self-consistent analytical model of the whole arc comprising of models for near-electrode regions, arc column, and a model of heat transfer in cylindrical electrodes was developed. The model predicts the width of non-equilibrium layers and arc column, voltages and plasma profiles in these regions, and heat and ion fluxes tomore » the electrodes. Parametric studies of the arc have been performed for a range of the arc current densities, inter-electrode gap widths, and gas pressures. The model was validated against experimental data and verified by comparison with numerical solution. In conclusion, good agreement between the analytical model and simulations and reasonable agreement with experimental data were obtained.« less

Investigation of the short argon arc with hot anode. II. Analytical model

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

Khrabry, A.; Kaganovich, I. D.; Nemchinsky, V.

A short atmospheric pressure argon arc is studied numerically and analytically. In a short arc with an inter-electrode gap of several millimeters, non-equilibrium effects in plasma play an important role in operation of the arc. High anode temperature leads to electron emission and intensive radiation from its surface. A complete, self-consistent analytical model of the whole arc comprising of models for near-electrode regions, arc column, and a model of heat transfer in cylindrical electrodes was developed. The model predicts the width of non-equilibrium layers and arc column, voltages and plasma profiles in these regions, and heat and ion fluxes tomore » the electrodes. Parametric studies of the arc have been performed for a range of the arc current densities, inter-electrode gap widths, and gas pressures. The model was validated against experimental data and verified by comparison with numerical solution. In conclusion, good agreement between the analytical model and simulations and reasonable agreement with experimental data were obtained.« less

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications: Preprint

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

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-08-24

This paper presents a nonlinear analytical model of a novel double-sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets, stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry that makes it a good alternative for evaluating prospective designs of TFM compared to finite element solversmore » that are numerically intensive and require more computation time. A single-phase, 1-kW, 400-rpm machine is analytically modeled, and its resulting flux distribution, no-load EMF, and torque are verified with finite element analysis. The results are found to be in agreement, with less than 5% error, while reducing the computation time by 25 times.« less

Analytical Modeling of a Novel Transverse Flux Machine for Direct Drive Wind Turbine Applications

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

Hasan, IIftekhar; Husain, Tausif; Uddin, Md Wasi

2015-09-02

This paper presents a nonlinear analytical model of a novel double sided flux concentrating Transverse Flux Machine (TFM) based on the Magnetic Equivalent Circuit (MEC) model. The analytical model uses a series-parallel combination of flux tubes to predict the flux paths through different parts of the machine including air gaps, permanent magnets (PM), stator, and rotor. The two-dimensional MEC model approximates the complex three-dimensional flux paths of the TFM and includes the effects of magnetic saturation. The model is capable of adapting to any geometry which makes it a good alternative for evaluating prospective designs of TFM as compared tomore » finite element solvers which are numerically intensive and require more computation time. A single phase, 1 kW, 400 rpm machine is analytically modeled and its resulting flux distribution, no-load EMF and torque, verified with Finite Element Analysis (FEA). The results are found to be in agreement with less than 5% error, while reducing the computation time by 25 times.« less

An investigation of the information propagation and entropy transport aspects of Stirling machine numerical simulation

NASA Technical Reports Server (NTRS)

Goldberg, Louis F.

1992-01-01

Aspects of the information propagation modeling behavior of integral machine computer simulation programs are investigated in terms of a transmission line. In particular, the effects of pressure-linking and temporal integration algorithms on the amplitude ratio and phase angle predictions are compared against experimental and closed-form analytic data. It is concluded that the discretized, first order conservation balances may not be adequate for modeling information propagation effects at characteristic numbers less than about 24. An entropy transport equation suitable for generalized use in Stirling machine simulation is developed. The equation is evaluated by including it in a simulation of an incompressible oscillating flow apparatus designed to demonstrate the effect of flow oscillations on the enhancement of thermal diffusion. Numerical false diffusion is found to be a major factor inhibiting validation of the simulation predictions with experimental and closed-form analytic data. A generalized false diffusion correction algorithm is developed which allows the numerical results to match their analytic counterparts. Under these conditions, the simulation yields entropy predictions which satisfy Clausius' inequality.

Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective

PubMed Central

Mench-Bressan, Nadja; McGregor, Carolyn; Pugh, James Edward

2015-01-01

The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children’s Hospital in Hamilton. We collect not only physiological data but also the infusion pumps data that are attached to NICU beds. Using the proposed analytical model, we predict the amount of storage, memory, and computation power required for the system. Capacity planning and tradeoff analysis would be more accurate and systematic by applying the proposed analytical model in this paper. Numerical results are obtained using real inputs acquired from McMaster Children’s Hospital and a pilot deployment of the system at The Hospital for Sick Children (SickKids) in Toronto. PMID:27170907

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

Qualitative comparison of calculated turbulence responses with wind-tunnel measurements for a DC-10 derivative wing with an active control system

NASA Technical Reports Server (NTRS)

Perry, B., III

1981-01-01

Comparisons are presented analytically predicted and experimental turbulence responses of a wind tunnel model of a DC-10 derivative wing equipped with an active control system. The active control system was designed for the purpose of flutter suppression, but it had additional benefit of alleviating gust loads (wing bending moment) by about 25%. Comparisions of various wing responses are presented for variations in active control system parameters and tunnel speed. The analytical turbulence responses were obtained using DYLOFLEX, a computer program for dynamic loads analyses of flexible airplanes with active controls. In general, the analytical predictions agreed reasonably well with the experimental data.

Autonomous Soil Assessment System: A Data-Driven Approach to Planetary Mobility Hazard Detection

NASA Astrophysics Data System (ADS)

Raimalwala, K.; Faragalli, M.; Reid, E.

2018-04-01

The Autonomous Soil Assessment System predicts mobility hazards for rovers. Its development and performance are presented, with focus on its data-driven models, machine learning algorithms, and real-time sensor data fusion for predictive analytics.

Design and analysis of tubular permanent magnet linear generator for small-scale wave energy converter

NASA Astrophysics Data System (ADS)

Kim, Jeong-Man; Koo, Min-Mo; Jeong, Jae-Hoon; Hong, Keyyong; Cho, Il-Hyoung; Choi, Jang-Young

2017-05-01

This paper reports the design and analysis of a tubular permanent magnet linear generator (TPMLG) for a small-scale wave-energy converter. The analytical field computation is performed by applying a magnetic vector potential and a 2-D analytical model to determine design parameters. Based on analytical solutions, parametric analysis is performed to meet the design specifications of a wave-energy converter (WEC). Then, 2-D FEA is employed to validate the analytical method. Finally, the experimental result confirms the predictions of the analytical and finite element analysis (FEA) methods under regular and irregular wave conditions.

Flight simulator fidelity assessment in a rotorcraft lateral translation maneuver

NASA Technical Reports Server (NTRS)

Hess, R. A.; Malsbury, T.; Atencio, A., Jr.

1992-01-01

A model-based methodology for assessing flight simulator fidelity in closed-loop fashion is exercised in analyzing a rotorcraft low-altitude maneuver for which flight test and simulation results were available. The addition of a handling qualities sensitivity function to a previously developed model-based assessment criteria allows an analytical comparison of both performance and handling qualities between simulation and flight test. Model predictions regarding the existence of simulator fidelity problems are corroborated by experiment. The modeling approach is used to assess analytically the effects of modifying simulator characteristics on simulator fidelity.

Improvement of analytical dynamic models using modal test data

NASA Technical Reports Server (NTRS)

Berman, A.; Wei, F. S.; Rao, K. V.

1980-01-01

A method developed to determine maximum changes in analytical mass and stiffness matrices to make them consistent with a set of measured normal modes and natural frequencies is presented. The corrected model will be an improved base for studies of physical changes, boundary condition changes, and for prediction of forced responses. The method features efficient procedures not requiring solutions of the eigenvalue problem, and the ability to have more degrees of freedom than the test data. In addition, modal displacements are obtained for all analytical degrees of freedom, and the frequency dependence of the coordinate transformations is properly treated.

Analytic study of the effect of dark energy-dark matter interaction on the growth of structures

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

Marcondes, Rafael J.F.; Landim, Ricardo C.G.; Costa, André A.

2016-12-01

Large-scale structure has been shown as a promising cosmic probe for distinguishing and constraining dark energy models. Using the growth index parametrization, we obtain an analytic formula for the growth rate of structures in a coupled dark energy model in which the exchange of energy-momentum is proportional to the dark energy density. We find that the evolution of f σ{sub 8} can be determined analytically once we know the coupling, the dark energy equation of state, the present value of the dark energy density parameter and the current mean amplitude of dark matter fluctuations. After correcting the growth function formore » the correspondence with the velocity field through the continuity equation in the interacting model, we use our analytic result to compare the model's predictions with large-scale structure observations.« less

Analytical methods to predict liquid congealing in ram air heat exchangers during cold operation

NASA Astrophysics Data System (ADS)

Coleman, Kenneth; Kosson, Robert

1989-07-01

Ram air heat exchangers used to cool liquids such as lube oils or Ethylene-Glycol/water solutions can be subject to congealing in very cold ambients, resulting in a loss of cooling capability. Two-dimensional, transient analytical models have been developed to explore this phenomenon with both continuous and staggered fin cores. Staggered fin predictions are compared to flight test data from the E-2C Allison T56 engine lube oil system during winter conditions. For simpler calculations, a viscosity ratio correction was introduced and found to provide reasonable cold ambient performance predictions for the staggered fin core, using a one-dimensional approach.

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Quantitative structure-retention relationships applied to development of liquid chromatography gradient-elution method for the separation of sartans.

PubMed

Golubović, Jelena; Protić, Ana; Otašević, Biljana; Zečević, Mira

2016-04-01

QSRR are mathematically derived relationships between the chromatographic parameters determined for a representative series of analytes in given separation systems and the molecular descriptors accounting for the structural differences among the investigated analytes. Artificial neural network is a technique of data analysis, which sets out to emulate the human brain's way of working. The aim of the present work was to optimize separation of six angiotensin receptor antagonists, so-called sartans: losartan, valsartan, irbesartan, telmisartan, candesartan cilexetil and eprosartan in a gradient-elution HPLC method. For this purpose, ANN as a mathematical tool was used for establishing a QSRR model based on molecular descriptors of sartans and varied instrumental conditions. The optimized model can be further used for prediction of an external congener of sartans and analysis of the influence of the analyte structure, represented through molecular descriptors, on retention behaviour. Molecular descriptors included in modelling were electrostatic, geometrical and quantum-chemical descriptors: connolly solvent excluded volume non-1,4 van der Waals energy, octanol/water distribution coefficient, polarizability, number of proton-donor sites and number of proton-acceptor sites. Varied instrumental conditions were gradient time, buffer pH and buffer molarity. High prediction ability of the optimized network enabled complete separation of the analytes within the run time of 15.5 min under following conditions: gradient time of 12.5 min, buffer pH of 3.95 and buffer molarity of 25 mM. Applied methodology showed the potential to predict retention behaviour of an external analyte with the properties within the training space. Connolly solvent excluded volume, polarizability and number of proton-acceptor sites appeared to be most influential paramateres on retention behaviour of the sartans. Copyright © 2015 Elsevier B.V. All rights reserved.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

PubMed

Chapman, Benjamin P; Weiss, Alexander; Duberstein, Paul R

2016-12-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how 3 common SLT algorithms-supervised principal components, regularization, and boosting-can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach-or perhaps because of them-SLT methods may hold value as a statistically rigorous approach to exploratory regression. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

Estimation of the curvature of the solid liquid interface during Bridgman crystal growth

NASA Astrophysics Data System (ADS)

Barat, Catherine; Duffar, Thierry; Garandet, Jean-Paul

1998-11-01

An approximate solution for the solid/liquid interface curvature due to the crucible effect in crystal growth is derived from simple heat flux considerations. The numerical modelling of the problem carried out with the help of the finite element code FIDAP supports the predictions of our analytical expression and allows to identify its range of validity. Experimental interface curvatures, measured in gallium antimonide samples grown by the vertical Bridgman method, are seen to compare satisfactorily to analytical and numerical results. Other literature data are also in fair agreement with the predictions of our models in the case where the amount of heat carried by the crucible is small compared to the overall heat flux.

An analytical method for designing low noise helicopter transmissions

NASA Technical Reports Server (NTRS)

Bossler, R. B., Jr.; Bowes, M. A.; Royal, A. C.

1978-01-01

The development and experimental validation of a method for analytically modeling the noise mechanism in the helicopter geared power transmission systems is described. This method can be used within the design process to predict interior noise levels and to investigate the noise reducing potential of alternative transmission design details. Examples are discussed.

A Simple Analytical Model for Magnetization and Coercivity of Hard/Soft Nanocomposite Magnets

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

Park, Jihoon; Hong, Yang-Ki; Lee, Woncheol

Here, we present a simple analytical model to estimate the magnetization (σ s) and intrinsic coercivity (Hci) of a hard/soft nanocomposite magnet using the mass fraction. Previously proposed models are based on the volume fraction of the hard phase of the composite. But, it is difficult to measure the volume of the hard or soft phase material of a composite. We synthesized Sm 2Co 7/Fe-Co, MnAl/Fe-Co, MnBi/Fe-Co, and BaFe 12O 19/Fe-Co composites for characterization of their σs and Hci. The experimental results are in good agreement with the present model. Therefore, this analytical model can be extended to predict themore » maximum energy product (BH) max of hard/soft composite.« less

Design of permanent magnet eddy current brake for a small scaled electromagnetic launch model

NASA Astrophysics Data System (ADS)

Zhou, Shigui; Yu, Haitao; Hu, Minqiang; Huang, Lei

2012-04-01

A variable pole-pitch double-sided permanent magnet (PM) linear eddy current brake (LECB) is proposed for a small scaled electromagnetic launch model. A two-dimensional (2D) analytical steady state model is presented for the double-sided PM-LECB, and the expression for the braking force is derived. Based on the analytical model, the material and eddy current skin effect of the conducting plate are analyzed. Moreover, a variable pole-pitch double-sided PM-LECB is proposed for the effective braking of the moving plate. In addition, the braking force is predicted by finite element (FE) analysis, and the simulated results are in good agreement with the analytical model. Finally, a prototype is presented to test the braking profile for validation of the proposed design.

A Simple Analytical Model for Magnetization and Coercivity of Hard/Soft Nanocomposite Magnets

DOE PAGES

Park, Jihoon; Hong, Yang-Ki; Lee, Woncheol; ...

2017-07-10

Here, we present a simple analytical model to estimate the magnetization (σ s) and intrinsic coercivity (Hci) of a hard/soft nanocomposite magnet using the mass fraction. Previously proposed models are based on the volume fraction of the hard phase of the composite. But, it is difficult to measure the volume of the hard or soft phase material of a composite. We synthesized Sm 2Co 7/Fe-Co, MnAl/Fe-Co, MnBi/Fe-Co, and BaFe 12O 19/Fe-Co composites for characterization of their σs and Hci. The experimental results are in good agreement with the present model. Therefore, this analytical model can be extended to predict themore » maximum energy product (BH) max of hard/soft composite.« less

Experimental and analytical characterization of triaxially braided textile composites

NASA Technical Reports Server (NTRS)

Masters, John E.; Fedro, Mark J.; Ifju, Peter G.

1993-01-01

There were two components, experimental and analytical, to this investigation of triaxially braided textile composite materials. The experimental portion of the study centered on measuring the materials' longitudinal and transverse tensile moduli, Poisson's ratio, and strengths. The identification of the damage mechanisms exhibited by these materials was also a prime objective of the experimental investigation. The analytical portion of the investigation utilized the Textile Composites Analysis (TECA) model to predict modulus and strength. The analytical and experimental results were compared to assess the effectiveness of the analysis. The figures contained in this paper reflect the presentation made at the conference. They may be divided into four sections: a definition of the material system tested; followed by a series of figures summarizing the experimental results (these figures contain results of a Moire interferometry study of the strain distribution in the material, examples and descriptions of the types of damage encountered in these materials, and a summary of the measured properties); a description of the TECA model follows the experimental results (this includes a series of predicted results and a comparison with measured values); and finally, a brief summary completes the paper.

System identification of analytical models of damped structures

NASA Technical Reports Server (NTRS)

Fuh, J.-S.; Chen, S.-Y.; Berman, A.

1984-01-01

A procedure is presented for identifying linear nonproportionally damped system. The system damping is assumed to be representable by a real symmetric matrix. Analytical mass, stiffness and damping matrices which constitute an approximate representation of the system are assumed to be available. Given also are an incomplete set of measured natural frequencies, damping ratios and complex mode shapes of the structure, normally obtained from test data. A method is developed to find the smallest changes in the analytical model so that the improved model can exactly predict the measured modal parameters. The present method uses the orthogonality relationship to improve mass and damping matrices and the dynamic equation to find the improved stiffness matrix.

A Comparison of Tension and Compression Creep in a Polymeric Composite and the Effects of Physical Aging on Creep Behavior

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Veazie, David R.; Brinson, L. Catherine

1996-01-01

Experimental and analytical methods were used to investigate the similarities and differences of the effects of physical aging on creep compliance of IM7/K3B composite loaded in tension and compression. Two matrix dominated loading modes, shear and transverse, were investigated for two load cases, tension and compression. The tests, run over a range of sub-glass transition temperatures, provided material constants, material master curves and aging related parameters. Comparing results from the short-term data indicated that although trends in the data with respect to aging time and aging temperature are similar, differences exist due to load direction and mode. The analytical model used for predicting long-term behavior using short-term data as input worked equally as well for the tension or compression loaded cases. Comparison of the loading modes indicated that the predictive model provided more accurate long term predictions for the shear mode as compared to the transverse mode. Parametric studies showed the usefulness of the predictive model as a tool for investigating long-term performance and compliance acceleration due to temperature.

Analysis on Experimental Investigation and Mathematical Modeling of Incompressible Flow Through Ceramic Foam Filters

NASA Astrophysics Data System (ADS)

Akbarnejad, Shahin; Jonsson, Lage Tord Ingemar; Kennedy, Mark William; Aune, Ragnhild Elizabeth; Jönsson, Pӓr Göran

2016-08-01

This paper presents experimental results of pressure drop measurements on 30, 50, and 80 pores per inch (PPI) commercial alumina ceramic foam filters (CFF) and compares the obtained pressure drop profiles to numerically modeled values. In addition, it is aimed at investigating the adequacy of the mathematical correlations used in the analytical and the computational fluid dynamics (CFD) simulations. It is shown that the widely used correlations for predicting pressure drop in porous media continuously under-predict the experimentally obtained pressure drop profiles. For analytical predictions, the negative deviations from the experimentally obtained pressure drop using the unmodified Ergun and Dietrich equations could be as high as 95 and 74 pct, respectively. For the CFD predictions, the deviation to experimental results is in the range of 84.3 to 88.5 pct depending on filter PPI. Better results can be achieved by applying the Forchheimer second-order drag term instead of the Brinkman-Forchheimer drag term. Thus, the final deviation of the CFD model estimates lie in the range of 0.3 to 5.5 pct compared to the measured values.

Comparison between numeric and approximate analytic solutions for the prediction of soil metal uptake by roots. Example of cadmium.

PubMed

Schneider, André; Lin, Zhongbing; Sterckeman, Thibault; Nguyen, Christophe

2018-04-01

The dissociation of metal complexes in the soil solution can increase the availability of metals for root uptake. When it is accounted for in models of bioavailability of soil metals, the number of partial differential equations (PDEs) increases and the computation time to numerically solve these equations may be problematic when a large number of simulations are required, for example for sensitivity analyses or when considering root architecture. This work presents analytical solutions for the set of PDEs describing the bioavailability of soil metals including the kinetics of complexation for three scenarios where the metal complex in solution was fully inert, fully labile, or partially labile. The analytical solutions are only valid i) at steady-state when the PDEs become ordinary differential equations, the transient phase being not covered, ii) when diffusion is the major mechanism of transport and therefore, when convection is negligible, iii) when there is no between-root competition. The formulation of the analytical solutions is for cylindrical geometry but the solutions rely on the spread of the depletion profile around the root, which was modelled assuming a planar geometry. The analytical solutions were evaluated by comparison with the corresponding PDEs for cadmium in the case of the French agricultural soils. Provided that convection was much lower than diffusion (Péclet's number<0.02), the cumulative uptakes calculated from the analytic solutions were in very good agreement with those calculated from the PDEs, even in the case of a partially labile complex. The analytic solutions can be used instead of the PDEs to predict root uptake of metals. The analytic solutions were also used to build an indicator of the contribution of a complex to the uptake of the metal by roots, which can be helpful to predict the effect of soluble organic matter on the bioavailability of soil metals. Copyright © 2017 Elsevier B.V. All rights reserved.

A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study.

PubMed

AbdelRahman, Samir E; Zhang, Mingyuan; Bray, Bruce E; Kawamoto, Kensaku

2014-05-27

The aim of this study was to propose an analytical approach to develop high-performing predictive models for congestive heart failure (CHF) readmission using an operational dataset with incomplete records and changing data over time. Our analytical approach involves three steps: pre-processing, systematic model development, and risk factor analysis. For pre-processing, variables that were absent in >50% of records were removed. Moreover, the dataset was divided into a validation dataset and derivation datasets which were separated into three temporal subsets based on changes to the data over time. For systematic model development, using the different temporal datasets and the remaining explanatory variables, the models were developed by combining the use of various (i) statistical analyses to explore the relationships between the validation and the derivation datasets; (ii) adjustment methods for handling missing values; (iii) classifiers; (iv) feature selection methods; and (iv) discretization methods. We then selected the best derivation dataset and the models with the highest predictive performance. For risk factor analysis, factors in the highest-performing predictive models were analyzed and ranked using (i) statistical analyses of the best derivation dataset, (ii) feature rankers, and (iii) a newly developed algorithm to categorize risk factors as being strong, regular, or weak. The analysis dataset consisted of 2,787 CHF hospitalizations at University of Utah Health Care from January 2003 to June 2013. In this study, we used the complete-case analysis and mean-based imputation adjustment methods; the wrapper subset feature selection method; and four ranking strategies based on information gain, gain ratio, symmetrical uncertainty, and wrapper subset feature evaluators. The best-performing models resulted from the use of a complete-case analysis derivation dataset combined with the Class-Attribute Contingency Coefficient discretization method and a voting classifier which averaged the results of multi-nominal logistic regression and voting feature intervals classifiers. Of 42 final model risk factors, discharge disposition, discretized age, and indicators of anemia were the most significant. This model achieved a c-statistic of 86.8%. The proposed three-step analytical approach enhanced predictive model performance for CHF readmissions. It could potentially be leveraged to improve predictive model performance in other areas of clinical medicine.

A Fractal Permeability Model for Shale Oil Reservoir

NASA Astrophysics Data System (ADS)

Zhang, Tao; Dong, Mingzhe; Li, Yajun

2018-01-01

In this work, a fractal analytical model is proposed to predict the permeability of shale reservoir. The proposed model explicitly relates the permeability to the micro-structural parameters (tortuosity, pore area fractal dimensions, porosity and slip velocity coefficient) of shale.

Validation of urban freeway models. [supporting datasets

DOT National Transportation Integrated Search

2015-01-01

The goal of the SHRP 2 Project L33 Validation of Urban Freeway Models was to assess and enhance the predictive travel time reliability models developed in the SHRP 2 Project L03, Analytic Procedures for Determining the Impacts of Reliability Mitigati...

Fretting Fatigue Analysis of Additively Manufactured Blade Root Made of Intermetallic Ti-48Al-2Cr-2Nb Alloy at High Temperature.

PubMed

Lavella, Mario; Botto, Daniele

2018-06-21

Slots in the disk of aircraft turbines restrain the centrifugal load of blades. Contact surfaces between the blade root and the disk slot undergo high contact pressure and relative displacement that is the typical condition in which fretting occurs. The load level ranges from zero to the maximum during take-off. This cycle is repeated for each mission. In this paper, a fretting fatigue analysis of additively manufactured blades is presented. Blades are made of an intermetallic alloy γTiAl. Fretting fatigue experiments were performed at a frequency of 0.5 Hz and at a temperature of 640 °C to match the operating condition of real blades. The minimum load was fixed at 0.5 KN and three maximum loads were applied, namely 16, 18 and 20 kN. Both an analytical and a two-dimensional finite element model were used to evaluate the state of stress at the contact interfaces. The results of the analytical model showed good agreement with the numerical model. Experiments showed that cracks nucleate where the analytical model predicts the maximum contact pressure and the numerical model predicts the maximum equivalent stress. A parametric analysis performed with the analytical model indicates that there exists an optimum geometry to minimize the contact pressure. Tests showed that the component life changed dramatically with the maximum load variation. Optical topography and scanning electron microscopy (SEM) analysis reveals information about the damage mechanism.

Experimental Validation of Lightning-Induced Electromagnetic (Indirect) Coupling to Short Monopole Antennas

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

Crull, E W; Brown Jr., C G; Perkins, M P

2008-07-30

For short monopoles in this low-power case, it has been shown that a simple circuit model is capable of accurate predictions for the shape and magnitude of the antenna response to lightning-generated electric field coupling effects, provided that the elements of the circuit model have accurate values. Numerical EM simulation can be used to provide more accurate values for the circuit elements than the simple analytical formulas, since the analytical formulas are used outside of their region of validity. However, even with the approximate analytical formulas the simple circuit model produces reasonable results, which would improve if more accurate analyticalmore » models were used. This report discusses the coupling analysis approaches taken to understand the interaction between a time-varying EM field and a short monopole antenna, within the context of lightning safety for nuclear weapons at DOE facilities. It describes the validation of a simple circuit model using laboratory study in order to understand the indirect coupling of energy into a part, and the resulting voltage. Results show that in this low-power case, the circuit model predicts peak voltages within approximately 32% using circuit component values obtained from analytical formulas and about 13% using circuit component values obtained from numerical EM simulation. We note that the analytical formulas are used outside of their region of validity. First, the antenna is insulated and not a bare wire and there are perhaps fringing field effects near the termination of the outer conductor that the formula does not take into account. Also, the effective height formula is for a monopole directly over a ground plane, while in the time-domain measurement setup the monopole is elevated above the ground plane by about 1.5-inch (refer to Figure 5).« less

Constraints on the nuclear equation of state from nuclear masses and radii in a Thomas-Fermi meta-modeling approach

NASA Astrophysics Data System (ADS)

Chatterjee, D.; Gulminelli, F.; Raduta, Ad. R.; Margueron, J.

2017-12-01

The question of correlations among empirical equation of state (EoS) parameters constrained by nuclear observables is addressed in a Thomas-Fermi meta-modeling approach. A recently proposed meta-modeling for the nuclear EoS in nuclear matter is augmented with a single finite size term to produce a minimal unified EoS functional able to describe the smooth part of the nuclear ground state properties. This meta-model can reproduce the predictions of a large variety of models, and interpolate continuously between them. An analytical approximation to the full Thomas-Fermi integrals is further proposed giving a fully analytical meta-model for nuclear masses. The parameter space is sampled and filtered through the constraint of nuclear mass reproduction with Bayesian statistical tools. We show that this simple analytical meta-modeling has a predictive power on masses, radii, and skins comparable to full Hartree-Fock or extended Thomas-Fermi calculations with realistic energy functionals. The covariance analysis on the posterior distribution shows that no physical correlation is present between the different EoS parameters. Concerning nuclear observables, a strong correlation between the slope of the symmetry energy and the neutron skin is observed, in agreement with previous studies.

Correlation of finite element free vibration predictions using random vibration test data. M.S. Thesis - Cleveland State Univ.

NASA Technical Reports Server (NTRS)

Chambers, Jeffrey A.

1994-01-01

Finite element analysis is regularly used during the engineering cycle of mechanical systems to predict the response to static, thermal, and dynamic loads. The finite element model (FEM) used to represent the system is often correlated with physical test results to determine the validity of analytical results provided. Results from dynamic testing provide one means for performing this correlation. One of the most common methods of measuring accuracy is by classical modal testing, whereby vibratory mode shapes are compared to mode shapes provided by finite element analysis. The degree of correlation between the test and analytical mode shapes can be shown mathematically using the cross orthogonality check. A great deal of time and effort can be exhausted in generating the set of test acquired mode shapes needed for the cross orthogonality check. In most situations response data from vibration tests are digitally processed to generate the mode shapes from a combination of modal parameters, forcing functions, and recorded response data. An alternate method is proposed in which the same correlation of analytical and test acquired mode shapes can be achieved without conducting the modal survey. Instead a procedure is detailed in which a minimum of test information, specifically the acceleration response data from a random vibration test, is used to generate a set of equivalent local accelerations to be applied to the reduced analytical model at discrete points corresponding to the test measurement locations. The static solution of the analytical model then produces a set of deformations that once normalized can be used to represent the test acquired mode shapes in the cross orthogonality relation. The method proposed has been shown to provide accurate results for both a simple analytical model as well as a complex space flight structure.

Emerging approaches in predictive toxicology.

PubMed

Zhang, Luoping; McHale, Cliona M; Greene, Nigel; Snyder, Ronald D; Rich, Ivan N; Aardema, Marilyn J; Roy, Shambhu; Pfuhler, Stefan; Venkatactahalam, Sundaresan

2014-12-01

Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described. © 2014 Wiley Periodicals, Inc.

Emerging Approaches in Predictive Toxicology

PubMed Central

Zhang, Luoping; McHale, Cliona M.; Greene, Nigel; Snyder, Ronald D.; Rich, Ivan N.; Aardema, Marilyn J.; Roy, Shambhu; Pfuhler, Stefan; Venkatactahalam, Sundaresan

2016-01-01

Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described. PMID:25044351

Study of the elastic behavior of synthetic lightweight aggregates (SLAs)

NASA Astrophysics Data System (ADS)

Jin, Na

Synthetic lightweight aggregates (SLAs), composed of coal fly ash and recycled plastics, represent a resilient construction material that could be a key aspect to future sustainable development. This research focuses on a prediction of the elastic modulus of SLA, assumed as a homogenous and isotropic composite of particulates of high carbon fly ash (HCFA) and a matrix of plastics (HDPE, LDPE, PS and mixture of plastics), with the emphasis on SLAs made of HCFA and PS. The elastic moduli of SLA with variable fly ash volume fractions are predicted based on finite element analyses (FEA) performed using the computer programs ABAQUS and PLAXIS. The effect of interface friction (roughness) between phases and other computation parameters; e.g., loading strain, stiffness of component, element type and boundary conditions, are included in these analyses. Analytical models and laboratory tests provide a baseline for comparison. Overall, results indicate ABAQUS generates elastic moduli closer to those predicted by well-established analytical models than moduli predicted from PLAXIS, especially for SLAs with lower fly ash content. In addition, an increase in roughness, loading strain indicated increase of SLAs stiffness, especially as fly ash content increases. The elastic moduli obtained from unconfined compression generally showed less elastic moduli than those obtained from analytical and ABAQUS 3D predictions. This may be caused by possible existence of pre-failure surface in specimen and the directly interaction between HCFA particles. Recommendations for the future work include laboratory measurements of SLAs moduli and FEM modeling that considers various sizes and random distribution of HCFA particles in SLAs.

Analytical investigation of the faster-is-slower effect with a simplified phenomenological model

NASA Astrophysics Data System (ADS)

Suzuno, K.; Tomoeda, A.; Ueyama, D.

2013-11-01

We investigate the mechanism of the phenomenon called the “faster-is-slower”effect in pedestrian flow studies analytically with a simplified phenomenological model. It is well known that the flow rate is maximized at a certain strength of the driving force in simulations using the social force model when we consider the discharge of self-driven particles through a bottleneck. In this study, we propose a phenomenological and analytical model based on a mechanics-based modeling to reveal the mechanism of the phenomenon. We show that our reduced system, with only a few degrees of freedom, still has similar properties to the original many-particle system and that the effect comes from the competition between the driving force and the nonlinear friction from the model. Moreover, we predict the parameter dependences on the effect from our model qualitatively, and they are confirmed numerically by using the social force model.

Theoretical studies of tone noise from a fan rotor

NASA Technical Reports Server (NTRS)

Rao, G. V. R.; Chu, W. T.; Digumarthi, R. V.

1973-01-01

An analytical study was made of some possible rotor alone noise sources of dipole, quadrapole and monopole characters which generate discrete tone noise. Particular emphasis is given to the tone noise caused by fan inlet flow distortion and turbulence. Analytical models are developed to allow prediction of absolute levels. Experimental data measured on a small scale fan is presented which indicates inlet turbulence interaction with a fan rotor can be a source of tone noise. Predicted and measured tone noise for the small scale rotor are shown to be in reasonable agreement.

Distribution analysis for F100(3) engine

NASA Technical Reports Server (NTRS)

Walter, W. A.; Shaw, M.

1980-01-01

The F100(3) compression system response to inlet circumferential distortion was investigated using an analytical compressor flow model. Compression system response to several types of distortion, including pressure, temperature, and combined pressure/temperature distortions, was investigated. The predicted response trends were used in planning future F100(3) distortion tests. Results show that compression system response to combined temperature and pressure distortions depends upon the relative orientation, as well as the individual amplitudes and circumferential extents of the distortions. Also the usefulness of the analytical predictions in planning engine distortion tests is indicated.

Big Data Analytics for Modelling and Forecasting of Geomagnetic Field Indices

NASA Astrophysics Data System (ADS)

Wei, H. L.

2016-12-01

A massive amount of data are produced and stored in research areas of space weather and space climate. However, the value of a vast majority of the data acquired every day may not be effectively or efficiently exploited in our daily practice when we try to forecast solar wind parameters and geomagnetic field indices using these recorded measurements or digital signals, probably due to the challenges stemming from the dealing with big data which are characterized by the 4V futures: volume (a massively large amount of data), variety (a great number of different types of data), velocity (a requirement of quick processing of the data), and veracity (the trustworthiness and usability of the data). In order to obtain more reliable and accurate predictive models for geomagnetic field indices, it requires that models should be developed from the big data analytics perspective (or it at least benefits from such a perspective). This study proposes a few data-based modelling frameworks which aim to produce more efficient predictive models for space weather parameters forecasting by means of system identification and big data analytics. More specifically, it aims to build more reliable mathematical models that characterise the relationship between solar wind parameters and geomagnetic filed indices, for example the dependent relationship of Dst and Kp indices on a few solar wind parameters and magnetic field indices, namely, solar wind velocity (V), southward interplanetary magnetic field (Bs), solar wind rectified electric field (VBs), and dynamic flow pressure (P). Examples are provided to illustrate how the proposed modelling approaches are applied to Dst and Kp index prediction.

Using Empirical Models for Communication Prediction of Spacecraft

NASA Technical Reports Server (NTRS)

Quasny, Todd

2015-01-01

A viable communication path to a spacecraft is vital for its successful operation. For human spaceflight, a reliable and predictable communication link between the spacecraft and the ground is essential not only for the safety of the vehicle and the success of the mission, but for the safety of the humans on board as well. However, analytical models of these communication links are challenged by unique characteristics of space and the vehicle itself. For example, effects of radio frequency during high energy solar events while traveling through a solar array of a spacecraft can be difficult to model, and thus to predict. This presentation covers the use of empirical methods of communication link predictions, using the International Space Station (ISS) and its associated historical data as the verification platform and test bed. These empirical methods can then be incorporated into communication prediction and automation tools for the ISS in order to better understand the quality of the communication path given a myriad of variables, including solar array positions, line of site to satellites, position of the sun, and other dynamic structures on the outside of the ISS. The image on the left below show the current analytical model of one of the communication systems on the ISS. The image on the right shows a rudimentary empirical model of the same system based on historical archived data from the ISS.

An implementation of an aeroacoustic prediction model for broadband noise from a vertical axis wind turbine using a CFD informed methodology

NASA Astrophysics Data System (ADS)

Botha, J. D. M.; Shahroki, A.; Rice, H.

2017-12-01

This paper presents an enhanced method for predicting aerodynamically generated broadband noise produced by a Vertical Axis Wind Turbine (VAWT). The method improves on existing work for VAWT noise prediction and incorporates recently developed airfoil noise prediction models. Inflow-turbulence and airfoil self-noise mechanisms are both considered. Airfoil noise predictions are dependent on aerodynamic input data and time dependent Computational Fluid Dynamics (CFD) calculations are carried out to solve for the aerodynamic solution. Analytical flow methods are also benchmarked against the CFD informed noise prediction results to quantify errors in the former approach. Comparisons to experimental noise measurements for an existing turbine are encouraging. A parameter study is performed and shows the sensitivity of overall noise levels to changes in inflow velocity and inflow turbulence. Noise sources are characterised and the location and mechanism of the primary sources is determined, inflow-turbulence noise is seen to be the dominant source. The use of CFD calculations is seen to improve the accuracy of noise predictions when compared to the analytic flow solution as well as showing that, for inflow-turbulence noise sources, blade generated turbulence dominates the atmospheric inflow turbulence.

Comparison of retention models for polymers 1. Poly(ethylene glycol)s.

PubMed

Bashir, Mubasher A; Radke, Wolfgang

2006-10-27

The suitability of three different retention models to predict the retention times of poly(ethylene glycol)s (PEGs) in gradient and isocratic chromatography was investigated. The models investigated were the linear (LSSM) and the quadratic solvent strength model (QSSM). In addition, a model describing the retention behaviour of polymers was extended to account for gradient elution (PM). It was found that all models are suited to properly predict gradient retention volumes provided the extraction of the analyte specific parameters is performed from gradient experiments as well. The LSSM and QSSM on principle cannot describe retention behaviour under critical or SEC conditions. Since the PM is designed to cover all three modes of polymer chromatography, it is therefore superior to the other models. However, the determination of the analyte specific parameters, which are needed to calibrate the retention behaviour, strongly depend on the suitable selection of initial experiments. A useful strategy for a purposeful selection of these calibration experiments is proposed.

Modeling Carbon-Black/Polymer Composite Sensors

PubMed Central

Lei, Hua; Pitt, William G.; McGrath, Lucas K.; Ho, Clifford K.

2012-01-01

Conductive polymer composite sensors have shown great potential in identifying gaseous analytes. To more thoroughly understand the physical and chemical mechanisms of this type of sensor, a mathematical model was developed by combining two sub-models: a conductivity model and a thermodynamic model, which gives a relationship between the vapor concentration of analyte(s) and the change of the sensor signals. In this work, 64 chemiresistors representing eight different carbon concentrations (8–60 vol% carbon) were constructed by depositing thin films of a carbon-black/polyisobutylene composite onto concentric spiral platinum electrodes on a silicon chip. The responses of the sensors were measured in dry air and at various vapor pressures of toluene and trichloroethylene. Three parameters in the conductivity model were determined by fitting the experimental data. It was shown that by applying this model, the sensor responses can be adequately predicted for given vapor pressures; furthermore the analyte vapor concentrations can be estimated based on the sensor responses. This model will guide the improvement of the design and fabrication of conductive polymer composite sensors for detecting and identifying mixtures of organic vapors. PMID:22518071

Analytical solutions for benchmarking cold regions subsurface water flow and energy transport models: one-dimensional soil thaw with conduction and advection

USGS Publications Warehouse

Kurylyk, Barret L.; McKenzie, Jeffrey M; MacQuarrie, Kerry T. B.; Voss, Clifford I.

2014-01-01

Numerous cold regions water flow and energy transport models have emerged in recent years. Dissimilarities often exist in their mathematical formulations and/or numerical solution techniques, but few analytical solutions exist for benchmarking flow and energy transport models that include pore water phase change. This paper presents a detailed derivation of the Lunardini solution, an approximate analytical solution for predicting soil thawing subject to conduction, advection, and phase change. Fifteen thawing scenarios are examined by considering differences in porosity, surface temperature, Darcy velocity, and initial temperature. The accuracy of the Lunardini solution is shown to be proportional to the Stefan number. The analytical solution results obtained for soil thawing scenarios with water flow and advection are compared to those obtained from the finite element model SUTRA. Three problems, two involving the Lunardini solution and one involving the classic Neumann solution, are recommended as standard benchmarks for future model development and testing.

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav

2010-01-01

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Guidelines and Parameter Selection for the Simulation of Progressive Delamination

NASA Technical Reports Server (NTRS)

Song, Kyongchan; Davila, Carlos G.; Rose, Cheryl A.

2008-01-01

Turon s methodology for determining optimal analysis parameters for the simulation of progressive delamination is reviewed. Recommended procedures for determining analysis parameters for efficient delamination growth predictions using the Abaqus/Standard cohesive element and relatively coarse meshes are provided for single and mixed-mode loading. The Abaqus cohesive element, COH3D8, and a user-defined cohesive element are used to develop finite element models of the double cantilever beam specimen, the end-notched flexure specimen, and the mixed-mode bending specimen to simulate progressive delamination growth in Mode I, Mode II, and mixed-mode fracture, respectively. The predicted responses are compared with their analytical solutions. The results show that for single-mode fracture, the predicted responses obtained with the Abaqus cohesive element correlate well with the analytical solutions. For mixed-mode fracture, it was found that the response predicted using COH3D8 elements depends on the damage evolution criterion that is used. The energy-based criterion overpredicts the peak loads and load-deflection response. The results predicted using a tabulated form of the BK criterion correlate well with the analytical solution and with the results predicted with the user-written element.

The influence of retrieval practice on metacognition: The contribution of analytic and non-analytic processes.

PubMed

Miller, Tyler M; Geraci, Lisa

2016-05-01

People may change their memory predictions after retrieval practice using naïve theories of memory and/or by using subjective experience - analytic and non-analytic processes respectively. The current studies disentangled contributions of each process. In one condition, learners studied paired-associates, made a memory prediction, completed a short-run of retrieval practice and made a second prediction. In another condition, judges read about a yoked learners' retrieval practice performance but did not participate in retrieval practice and therefore, could not use non-analytic processes for the second prediction. In Study 1, learners reduced their predictions following moderately difficult retrieval practice whereas judges increased their predictions. In Study 2, learners made lower adjusted predictions than judges following both easy and difficult retrieval practice. In Study 3, judge-like participants used analytic processes to report adjusted predictions. Overall, the results suggested non-analytic processes play a key role for participants to reduce their predictions after retrieval practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column.

PubMed

Markopoulou, Catherine K; Kouskoura, Maria G; Koundourellis, John E

2011-06-01

Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proxy-SU(3) symmetry in heavy deformed nuclei

NASA Astrophysics Data System (ADS)

Bonatsos, Dennis; Assimakis, I. E.; Minkov, N.; Martinou, Andriana; Cakirli, R. B.; Casten, R. F.; Blaum, K.

2017-06-01

Background: Microscopic calculations of heavy nuclei face considerable difficulties due to the sizes of the matrices that need to be solved. Various approximation schemes have been invoked, for example by truncating the spaces, imposing seniority limits, or appealing to various symmetry schemes such as pseudo-SU(3). This paper proposes a new symmetry scheme also based on SU(3). This proxy-SU(3) can be applied to well-deformed nuclei, is simple to use, and can yield analytic predictions. Purpose: To present the new scheme and its microscopic motivation, and to test it using a Nilsson model calculation with the original shell model orbits and with the new proxy set. Method: We invoke an approximate, analytic, treatment of the Nilsson model, that allows the above vetting and yet is also transparent in understanding the approximations involved in the new proxy-SU(3). Results: It is found that the new scheme yields a Nilsson diagram for well-deformed nuclei that is very close to the original Nilsson diagram. The specific levels of approximation in the new scheme are also shown, for each major shell. Conclusions: The new proxy-SU(3) scheme is a good approximation to the full set of orbits in a major shell. Being able to replace a complex shell model calculation with a symmetry-based description now opens up the possibility to predict many properties of nuclei analytically and often in a parameter-free way. The new scheme works best for heavier nuclei, precisely where full microscopic calculations are most challenged. Some cases in which the new scheme can be used, often analytically, to make specific predictions, are shown in a subsequent paper.

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

PubMed

Kassemi, Mohammad; Thompson, David

2016-09-01

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

Analytical model for vibration prediction of two parallel tunnels in a full-space

NASA Astrophysics Data System (ADS)

He, Chao; Zhou, Shunhua; Guo, Peijun; Di, Honggui; Zhang, Xiaohui

2018-06-01

This paper presents a three-dimensional analytical model for the prediction of ground vibrations from two parallel tunnels embedded in a full-space. The two tunnels are modelled as cylindrical shells of infinite length, and the surrounding soil is modelled as a full-space with two cylindrical cavities. A virtual interface is introduced to divide the soil into the right layer and the left layer. By transforming the cylindrical waves into the plane waves, the solution of wave propagation in the full-space with two cylindrical cavities is obtained. The transformations from the plane waves to cylindrical waves are then used to satisfy the boundary conditions on the tunnel-soil interfaces. The proposed model provides a highly efficient tool to predict the ground vibration induced by the underground railway, which accounts for the dynamic interaction between neighbouring tunnels. Analysis of the vibration fields produced over a range of frequencies and soil properties is conducted. When the distance between the two tunnels is smaller than three times the tunnel diameter, the interaction between neighbouring tunnels is highly significant, at times in the order of 20 dB. It is necessary to consider the interaction between neighbouring tunnels for the prediction of ground vibrations induced underground railways.

Analytical modeling of eddy-current losses caused by pulse-width-modulation switching in permanent-magnet brushless direct-current motors

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

Deng, F.; Nehl, T.W.

1998-09-01

Because of their high efficiency and power density the PM brushless dc motor is a strong candidate for electric and hybrid vehicle propulsion systems. An analytical approach is developed to predict the inverter high frequency pulse width modulation (PWM) switching caused eddy-current losses in a permanent magnet brushless dc motor. The model uses polar coordinates to take curvature effects into account, and is also capable of including the space harmonic effect of the stator magnetic field and the stator lamination effect on the losses. The model was applied to an existing motor design and was verified with the finite elementmore » method. Good agreement was achieved between the two approaches. Hence, the model is expected to be very helpful in predicting PWM switching losses in permanent magnet machine design.« less

A generic analytical foot rollover model for predicting translational ankle kinematics in gait simulation studies.

PubMed

Ren, Lei; Howard, David; Ren, Luquan; Nester, Chris; Tian, Limei

2010-01-19

The objective of this paper is to develop an analytical framework to representing the ankle-foot kinematics by modelling the foot as a rollover rocker, which cannot only be used as a generic tool for general gait simulation but also allows for case-specific modelling if required. Previously, the rollover models used in gait simulation have often been based on specific functions that have usually been of a simple form. In contrast, the analytical model described here is in a general form that the effective foot rollover shape can be represented by any polar function rho=rho(phi). Furthermore, a normalized generic foot rollover model has been established based on a normative foot rollover shape dataset of 12 normal healthy subjects. To evaluate model accuracy, the predicted ankle motions and the centre of pressure (CoP) were compared with measurement data for both subject-specific and general cases. The results demonstrated that the ankle joint motions in both vertical and horizontal directions (relative RMSE approximately 10%) and CoP (relative RMSE approximately 15% for most of the subjects) are accurately predicted over most of the stance phase (from 10% to 90% of stance). However, we found that the foot cannot be very accurately represented by a rollover model just after heel strike (HS) and just before toe off (TO), probably due to shear deformation of foot plantar tissues (ankle motion can occur without any foot rotation). The proposed foot rollover model can be used in both inverse and forward dynamics gait simulation studies and may also find applications in rehabilitation engineering. Copyright 2009 Elsevier Ltd. All rights reserved.

Shielding Characteristics Using an Ultrasonic Configurable Fan Artificial Noise Source to Generate Modes - Experimental Measurements and Analytical Predictions

NASA Technical Reports Server (NTRS)

Sutliff, Daniel L.; Walker, Bruce E.

2014-01-01

An Ultrasonic Configurable Fan Artificial Noise Source (UCFANS) was designed, built, and tested in support of the NASA Langley Research Center's 14x22 wind tunnel test of the Hybrid Wing Body (HWB) full 3-D 5.8% scale model. The UCFANS is a 5.8% rapid prototype scale model of a high-bypass turbofan engine that can generate the tonal signature of proposed engines using artificial sources (no flow). The purpose of the program was to provide an estimate of the acoustic shielding benefits possible from mounting an engine on the upper surface of a wing; a flat plate model was used as the shielding surface. Simple analytical simulations were used to preview the radiation patterns - Fresnel knife-edge diffraction was coupled with a dense phased array of point sources to compute shielded and unshielded sound pressure distributions for potential test geometries and excitation modes. Contour plots of sound pressure levels, and integrated power levels, from nacelle alone and shielded configurations for both the experimental measurements and the analytical predictions are presented in this paper.

A predictive analytic model for the solar modulation of cosmic rays

DOE PAGES

Cholis, Ilias; Hooper, Dan; Linden, Tim

2016-02-23

An important factor limiting our ability to understand the production and propagation of cosmic rays pertains to the effects of heliospheric forces, commonly known as solar modulation. The solar wind is capable of generating time- and charge-dependent effects on the spectrum and intensity of low-energy (≲10 GeV) cosmic rays reaching Earth. Previous analytic treatments of solar modulation have utilized the force-field approximation, in which a simple potential is adopted whose amplitude is selected to best fit the cosmic-ray data taken over a given period of time. Making use of recently available cosmic-ray data from the Voyager 1 spacecraft, along withmore » measurements of the heliospheric magnetic field and solar wind, we construct a time-, charge- and rigidity-dependent model of solar modulation that can be directly compared to data from a variety of cosmic-ray experiments. Here, we provide a simple analytic formula that can be easily utilized in a variety of applications, allowing us to better predict the effects of solar modulation and reduce the number of free parameters involved in cosmic-ray propagation models.« less

A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics.

PubMed

Devriendt, Floris; Moldovan, Darie; Verbeke, Wouter

2018-03-01

Prescriptive analytics extends on predictive analytics by allowing to estimate an outcome in function of control variables, allowing as such to establish the required level of control variables for realizing a desired outcome. Uplift modeling is at the heart of prescriptive analytics and aims at estimating the net difference in an outcome resulting from a specific action or treatment that is applied. In this article, a structured and detailed literature survey on uplift modeling is provided by identifying and contrasting various groups of approaches. In addition, evaluation metrics for assessing the performance of uplift models are reviewed. An experimental evaluation on four real-world data sets provides further insight into their use. Uplift random forests are found to be consistently among the best performing techniques in terms of the Qini and Gini measures, although considerable variability in performance across the various data sets of the experiments is observed. In addition, uplift models are frequently observed to be unstable and display a strong variability in terms of performance across different folds in the cross-validation experimental setup. This potentially threatens their actual use for business applications. Moreover, it is found that the available evaluation metrics do not provide an intuitively understandable indication of the actual use and performance of a model. Specifically, existing evaluation metrics do not facilitate a comparison of uplift models and predictive models and evaluate performance either at an arbitrary cutoff or over the full spectrum of potential cutoffs. In conclusion, we highlight the instability of uplift models and the need for an application-oriented approach to assess uplift models as prime topics for further research.

The effect of air entrapment on the performance of squeeze film dampers: Experiments and analysis

NASA Astrophysics Data System (ADS)

Diaz Briceno, Sergio Enrique

Squeeze film dampers (SFDs) are an effective means to introduce the required damping in rotor-bearing systems. They are a standard application in jet engines and are commonly used in industrial compressors. Yet, lack of understanding of their operation has confined the design of SFDs to a costly trial and error process based on prior experience. The main factor deterring the success of analytical models for the prediction of SFDs' performance lays on the modeling of the dynamic film rupture. Usually, the cavitation models developed for journal bearings are applied to SFDs. Yet, the characteristic motion of the SFD results in the entrapment of air into the oil film, thus producing a bubbly mixture that can not be represented by these models. In this work, an extensive experimental study establishes qualitatively and---for the first time---quantitatively the differences between operation with vapor cavitation and with air entrainment. The experiments show that most operating conditions lead to air entrainment and demonstrate the paramount effect it has on the performance of SFDs, evidencing the limitation of currently available models. Further experiments address the operation of SFDs with controlled bubbly mixtures. These experiments bolster the possibility of modeling air entrapment by representing the lubricant as a homogeneous mixture of air and oil and provide a reliable data base for benchmarking such a model. An analytical model is developed based on a homogeneous mixture assumption and where the bubbles are described by the Rayleigh-Plesset equation. Good agreement is obtained between this model and the measurements performed in the SFD operating with controlled mixtures. A complementary analytical model is devised to estimate the amount of air entrained from the balance of axial flows in the film. A combination of the analytical models for prediction of the air volume fraction and of the hydrodynamic pressures renders promising results for prediction of the performance of SFDs with freely entrained air. The results of this work are of immediate engineering applicability. Furthermore, they represent a firm step to advance the understanding on the effects of air entrapment in the performance of SFD.

An analytical solubility model for nitrogen-methane-ethane ternary mixtures

NASA Astrophysics Data System (ADS)

Hartwig, Jason; Meyerhofer, Peter; Lorenz, Ralph; Lemmon, Eric

2018-01-01

Saturn's moon Titan has surface liquids of liquid hydrocarbons and a thick, cold, nitrogen atmosphere, and is a target for future exploration. Critical to the design and operation of vehicles for this environment is knowledge of the amount of dissolved nitrogen gas within the cryogenic liquid methane and ethane seas. This paper rigorously reviews experimental data on the vapor-liquid equilibrium of nitrogen/methane/ethane mixtures, noting the possibility for split liquid phases, and presents simple analytical models for conveniently predicting solubility of nitrogen in pure liquid ethane, pure liquid methane, and a mixture of liquid ethane and methane. Model coefficients are fit to three temperature ranges near the critical point, intermediate range, and near the freezing point to permit accurate predictions across the full range of thermodynamic conditions. The models are validated against the consolidated database of 2356 experimental data points, with mean absolute error between data and model less than 8% for both binary nitrogen/methane and nitrogen/ethane systems, and less than 17% for the ternary nitrogen/methane/ethane system. The model can be used to predict the mole fractions of ethane, methane, and nitrogen as a function of location within the Titan seas.

Coupling between structure and liquids in a parallel stage space shuttle design

NASA Technical Reports Server (NTRS)

Kana, D. D.; Ko, W. L.; Francis, P. H.; Nagy, A.

1972-01-01

A study was conducted to determine the influence of liquid propellants on the dynamic loads for space shuttle vehicles. A parallel-stage configuration model was designed and tested to determine the influence of liquid propellants on coupled natural modes. A forty degree-of-freedom analytical model was also developed for predicting these modes. Currently available analytical models were used to represent the liquid contributions, even though coupled longitudinal and lateral motions are present in such a complex structure. Agreement between the results was found in the lower few modes.

A comparison of finite element and analytic models of acoustic scattering from rough poroelastic interfaces.

PubMed

Bonomo, Anthony L; Isakson, Marcia J; Chotiros, Nicholas P

2015-04-01

The finite element method is used to model acoustic scattering from rough poroelastic surfaces. Both monostatic and bistatic scattering strengths are calculated and compared with three analytic models: Perturbation theory, the Kirchhoff approximation, and the small-slope approximation. It is found that the small-slope approximation is in very close agreement with the finite element results for all cases studied and that perturbation theory and the Kirchhoff approximation can be considered valid in those instances where their predictions match those given by the small-slope approximation.

Analytic Formulation and Numerical Implementation of an Acoustic Pressure Gradient Prediction

NASA Technical Reports Server (NTRS)

Lee, Seongkyu; Brentner, Kenneth S.; Farassat, Fereidoun

2007-01-01

The scattering of rotor noise is an area that has received little attention over the years, yet the limited work that has been done has shown that both the directivity and intensity of the acoustic field may be significantly modified by the presence of scattering bodies. One of the inputs needed to compute the scattered acoustic field is the acoustic pressure gradient on a scattering surface. Two new analytical formulations of the acoustic pressure gradient have been developed and implemented in the PSU-WOPWOP rotor noise prediction code. These formulations are presented in this paper. The first formulation is derived by taking the gradient of Farassat's retarded-time Formulation 1A. Although this formulation is relatively simple, it requires numerical time differentiation of the acoustic integrals. In the second formulation, the time differentiation is taken inside the integrals analytically. The acoustic pressure gradient predicted by these new formulations is validated through comparison with the acoustic pressure gradient determined by a purely numerical approach for two model rotors. The agreement between analytic formulations and numerical method is excellent for both stationary and moving observers case.

Mid-infrared and near-infrared spectroscopy for rapid detection of Gardeniae Fructus by a liquid-liquid extraction process.

PubMed

Tao, Lingyan; Lin, Zhonglin; Chen, Jiashan; Wu, Yongjiang; Liu, Xuesong

2017-10-25

Gardeniae Fructus is widely used in the pharmaceutical industry, and many studies have confirmed its medical and economic value. In this study, samples collected from different liquid-liquid extraction batches of Gardeniae Fructus were detected by mid-infrared (MIR) and near-infrared (NIR) spectroscopy. Seven analytes, neochlorogenic acid (5-CQA), cryptochlorogenic acid (4-CQA), chlorogenic acid (3-CQA), geniposidic acid (GEA), deacetyl-asperulosidic acid methyl ester (DAAME), genipin-gentiobioside (GGB), and gardenoside (GA), were chosen as quality property indexes of Gardeniae Fructus. The two kinds of spectra were each used to build models by single partial least squares (PLS). Additionally, both spectral data were combined and modeled by multiblock PLS. For single spectroscopy modeling results, NIR had a better prediction for high-concentration analytes (3-CQA, DAAME, GGB, and GA) whereas MIR performed better for low-concentration analytes (5-CQA, 4-CQA, and GEA). The multiblock methodology was found to be better compared to single spectroscopy models for all seven analytes. Specifically, the coefficients of determination (R 2 ) of the NIR, MIR, and multiblock PLS calibration models of all seven components were higher than 0.95. Relative standard errors of prediction (RSEP) were all less than 7%, except for models of GGB, which were 10.36%, 13.24%, and 8.15% for the NIR-PLS, MIR-PLS, and multiblock models, respectively. These results indicate that MIR and NIR spectrographic techniques could provide a new choice for quality control in industrial production of Gardeniae Fructus. Copyright © 2017 Elsevier B.V. All rights reserved.

Cardiac data mining (CDM); organization and predictive analytics on biomedical (cardiac) data

NASA Astrophysics Data System (ADS)

Bilal, M. Musa; Hussain, Masood; Basharat, Iqra; Fatima, Mamuna

2013-10-01

Data mining and data analytics has been of immense importance to many different fields as we witness the evolution of data sciences over recent years. Biostatistics and Medical Informatics has proved to be the foundation of many modern biological theories and analysis techniques. These are the fields which applies data mining practices along with statistical models to discover hidden trends from data that comprises of biological experiments or procedures on different entities. The objective of this research study is to develop a system for the efficient extraction, transformation and loading of such data from cardiologic procedure reports given by Armed Forces Institute of Cardiology. It also aims to devise a model for the predictive analysis and classification of this data to some important classes as required by cardiologists all around the world. This includes predicting patient impressions and other important features.

Coupled rotor/fuselage dynamic analysis of the AH-1G helicopter and correlation with flight vibrations data

NASA Technical Reports Server (NTRS)

Corrigan, J. C.; Cronkhite, J. D.; Dompka, R. V.; Perry, K. S.; Rogers, J. P.; Sadler, S. G.

1989-01-01

Under a research program designated Design Analysis Methods for VIBrationS (DAMVIBS), existing analytical methods are used for calculating coupled rotor-fuselage vibrations of the AH-1G helicopter for correlation with flight test data from an AH-1G Operational Load Survey (OLS) test program. The analytical representation of the fuselage structure is based on a NASTRAN finite element model (FEM), which has been developed, extensively documented, and correlated with ground vibration test. One procedure that was used for predicting coupled rotor-fuselage vibrations using the advanced Rotorcraft Flight Simulation Program C81 and NASTRAN is summarized. Detailed descriptions of the analytical formulation of rotor dynamics equations, fuselage dynamic equations, coupling between the rotor and fuselage, and solutions to the total system of equations in C81 are included. Analytical predictions of hub shears for main rotor harmonics 2p, 4p, and 6p generated by C81 are used in conjunction with 2p OLS measured control loads and a 2p lateral tail rotor gearbox force, representing downwash impingement on the vertical fin, to excite the NASTRAN model. NASTRAN is then used to correlate with measured OLS flight test vibrations. Blade load comparisons predicted by C81 showed good agreement. In general, the fuselage vibration correlations show good agreement between anslysis and test in vibration response through 15 to 20 Hz.

Satellite attitude motion models for capture and retrieval investigations

NASA Technical Reports Server (NTRS)

Cochran, John E., Jr.; Lahr, Brian S.

1986-01-01

The primary purpose of this research is to provide mathematical models which may be used in the investigation of various aspects of the remote capture and retrieval of uncontrolled satellites. Emphasis has been placed on analytical models; however, to verify analytical solutions, numerical integration must be used. Also, for satellites of certain types, numerical integration may be the only practical or perhaps the only possible method of solution. First, to provide a basis for analytical and numerical work, uncontrolled satellites were categorized using criteria based on: (1) orbital motions, (2) external angular momenta, (3) internal angular momenta, (4) physical characteristics, and (5) the stability of their equilibrium states. Several analytical solutions for the attitude motions of satellite models were compiled, checked, corrected in some minor respects and their short-term prediction capabilities were investigated. Single-rigid-body, dual-spin and multi-rotor configurations are treated. To verify the analytical models and to see how the true motion of a satellite which is acted upon by environmental torques differs from its corresponding torque-free motion, a numerical simulation code was developed. This code contains a relatively general satellite model and models for gravity-gradient and aerodynamic torques. The spacecraft physical model for the code and the equations of motion are given. The two environmental torque models are described.

Phenomenology of wall-bounded Newtonian turbulence.

PubMed

L'vov, Victor S; Pomyalov, Anna; Procaccia, Itamar; Zilitinkevich, Sergej S

2006-01-01

We construct a simple analytic model for wall-bounded turbulence, containing only four adjustable parameters. Two of these parameters are responsible for the viscous dissipation of the components of the Reynolds stress tensor. The other two parameters control the nonlinear relaxation of these objects. The model offers an analytic description of the profiles of the mean velocity and the correlation functions of velocity fluctuations in the entire boundary region, from the viscous sublayer, through the buffer layer, and further into the log-law turbulent region. In particular, the model predicts a very simple distribution of the turbulent kinetic energy in the log-law region between the velocity components: the streamwise component contains a half of the total energy whereas the wall-normal and cross-stream components contain a quarter each. In addition, the model predicts a very simple relation between the von Kármán slope k and the turbulent velocity in the log-law region v+ (in wall units): v+=6k. These predictions are in excellent agreement with direct numerical simulation data and with recent laboratory experiments.

The backend design of an environmental monitoring system upon real-time prediction of groundwater level fluctuation under the hillslope.

PubMed

Lin, Hsueh-Chun; Hong, Yao-Ming; Kan, Yao-Chiang

2012-01-01

The groundwater level represents a critical factor to evaluate hillside landslides. A monitoring system upon the real-time prediction platform with online analytical functions is important to forecast the groundwater level due to instantaneously monitored data when the heavy precipitation raises the groundwater level under the hillslope and causes instability. This study is to design the backend of an environmental monitoring system with efficient algorithms for machine learning and knowledge bank for the groundwater level fluctuation prediction. A Web-based platform upon the model-view controller-based architecture is established with technology of Web services and engineering data warehouse to support online analytical process and feedback risk assessment parameters for real-time prediction. The proposed system incorporates models of hydrological computation, machine learning, Web services, and online prediction to satisfy varieties of risk assessment requirements and approaches of hazard prevention. The rainfall data monitored from the potential landslide area at Lu-Shan, Nantou and Li-Shan, Taichung, in Taiwan, are applied to examine the system design.

Fast analytical model of MZI micro-opto-mechanical pressure sensor

NASA Astrophysics Data System (ADS)

Rochus, V.; Jansen, R.; Goyvaerts, J.; Neutens, P.; O’Callaghan, J.; Rottenberg, X.

2018-06-01

This paper presents a fast analytical procedure in order to design a micro-opto-mechanical pressure sensor (MOMPS) taking into account the mechanical nonlinearity and the optical losses. A realistic model of the photonic MZI is proposed, strongly coupled to a nonlinear mechanical model of the membrane. Based on the membrane dimensions, the residual stress, the position of the waveguide, the optical wavelength and the phase variation due to the opto-mechanical coupling, we derive an analytical model which allows us to predict the response of the total system. The effect of the nonlinearity and the losses on the total performance are carefully studied and measurements on fabricated devices are used to validate the model. Finally, a design procedure is proposed in order to realize fast design of this new type of pressure sensor.

Steady-state analytical model of suspended p-type 3C-SiC bridges under consideration of Joule heating

NASA Astrophysics Data System (ADS)

Balakrishnan, Vivekananthan; Dinh, Toan; Phan, Hoang-Phuong; Kozeki, Takahiro; Namazu, Takahiro; Viet Dao, Dzung; Nguyen, Nam-Trung

2017-07-01

This paper reports an analytical model and its validation for a released microscale heater made of 3C-SiC thin films. A model for the equivalent electrical and thermal parameters was developed for the two-layer multi-segment heat and electric conduction. The model is based on a 1D energy equation, which considers the temperature-dependent resistivity and allows for the prediction of voltage-current and power-current characteristics of the microheater. The steady-state analytical model was validated by experimental characterization. The results, in particular the nonlinearity caused by temperature dependency, are in good agreement. The low power consumption of the order of 0.18 mW at approximately 310 K indicates the potential use of the structure as thermal sensors in portable applications.

Theoretical and experimental investigation of architected core materials incorporating negative stiffness elements

NASA Astrophysics Data System (ADS)

Chang, Chia-Ming; Keefe, Andrew; Carter, William B.; Henry, Christopher P.; McKnight, Geoff P.

2014-04-01

Structural assemblies incorporating negative stiffness elements have been shown to provide both tunable damping properties and simultaneous high stiffness and damping over prescribed displacement regions. In this paper we explore the design space for negative stiffness based assemblies using analytical modeling combined with finite element analysis. A simplified spring model demonstrates the effects of element stiffness, geometry, and preloads on the damping and stiffness performance. Simplified analytical models were validated for realistic structural implementations through finite element analysis. A series of complementary experiments was conducted to compare with modeling and determine the effects of each element on the system response. The measured damping performance follows the theoretical predictions obtained by analytical modeling. We applied these concepts to a novel sandwich core structure that exhibited combined stiffness and damping properties 8 times greater than existing foam core technologies.

An Analytical Solution for the Impact of Vegetation Changes on Hydrological Partitioning Within the Budyko Framework

NASA Astrophysics Data System (ADS)

Zhang, Shulei; Yang, Yuting; McVicar, Tim R.; Yang, Dawen

2018-01-01

Vegetation change is a critical factor that profoundly affects the terrestrial water cycle. Here we derive an analytical solution for the impact of vegetation changes on hydrological partitioning within the Budyko framework. This is achieved by deriving an analytical expression between leaf area index (LAI) change and the Budyko land surface parameter (n) change, through the combination of a steady state ecohydrological model with an analytical carbon cost-benefit model for plant rooting depth. Using China where vegetation coverage has experienced dramatic changes over the past two decades as a study case, we quantify the impact of LAI changes on the hydrological partitioning during 1982-2010 and predict the future influence of these changes for the 21st century using climate model projections. Results show that LAI change exhibits an increasing importance on altering hydrological partitioning as climate becomes drier. In semiarid and arid China, increased LAI has led to substantial streamflow reductions over the past three decades (on average -8.5% in 1990s and -11.7% in 2000s compared to the 1980s baseline), and this decreasing trend in streamflow is projected to continue toward the end of this century due to predicted LAI increases. Our result calls for caution regarding the large-scale revegetation activities currently being implemented in arid and semiarid China, which may result in serious future water scarcity issues here. The analytical model developed here is physically based and suitable for simultaneously assessing both vegetation changes and climate change induced changes to streamflow globally.

Kennedy Space Center (KSC) Launch Complex 39 (LC-39) Gaseous Hydrogen (GH2) Vent Arm Behavior Prediction Model Review Technical Assessment Report

NASA Technical Reports Server (NTRS)

Wilson, Timmy R.; Beech, Geoffrey; Johnston, Ian

2009-01-01

The NESC Assessment Team reviewed a computer simulation of the LC-39 External Tank (ET) GH2 Vent Umbilical system developed by United Space Alliance (USA) for the Space Shuttle Program (SSP) and designated KSC Analytical Tool ID 451 (KSC AT-451). The team verified that the vent arm kinematics were correctly modeled, but noted that there were relevant system sensitivities. Also, the structural stiffness used in the math model varied somewhat from the analytic calculations. Results of the NESC assessment were communicated to the model developers.

Tank System Integrated Model: A Cryogenic Tank Performance Prediction Program

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

Prediction of pressure drop in fluid tuned mounts using analytical and computational techniques

NASA Technical Reports Server (NTRS)

Lasher, William C.; Khalilollahi, Amir; Mischler, John; Uhric, Tom

1993-01-01

A simplified model for predicting pressure drop in fluid tuned isolator mounts was developed. The model is based on an exact solution to the Navier-Stokes equations and was made more general through the use of empirical coefficients. The values of these coefficients were determined by numerical simulation of the flow using the commercial computational fluid dynamics (CFD) package FIDAP.

An analytical model for regular respiratory signals derived from the probability density function of Rayleigh distribution.

PubMed

Li, Xin; Li, Ye

2015-01-01

Regular respiratory signals (RRSs) acquired with physiological sensing systems (e.g., the life-detection radar system) can be used to locate survivors trapped in debris in disaster rescue, or predict the breathing motion to allow beam delivery under free breathing conditions in external beam radiotherapy. Among the existing analytical models for RRSs, the harmonic-based random model (HRM) is shown to be the most accurate, which, however, is found to be subject to considerable error if the RRS has a slowly descending end-of-exhale (EOE) phase. The defect of the HRM motivates us to construct a more accurate analytical model for the RRS. In this paper, we derive a new analytical RRS model from the probability density function of Rayleigh distribution. We evaluate the derived RRS model by using it to fit a real-life RRS in the sense of least squares, and the evaluation result shows that, our presented model exhibits lower error and fits the slowly descending EOE phases of the real-life RRS better than the HRM.

A methodology for the assessment of manned flight simulator fidelity

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; Malsbury, Terry N.

1989-01-01

A relatively simple analytical methodology for assessing the fidelity of manned flight simulators for specific vehicles and tasks is offered. The methodology is based upon an application of a structural model of the human pilot, including motion cue effects. In particular, predicted pilot/vehicle dynamic characteristics are obtained with and without simulator limitations. A procedure for selecting model parameters can be implemented, given a probable pilot control strategy. In analyzing a pair of piloting tasks for which flight and simulation data are available, the methodology correctly predicted the existence of simulator fidelity problems. The methodology permitted the analytical evaluation of a change in simulator characteristics and indicated that a major source of the fidelity problems was a visual time delay in the simulation.

Correlation of analytical and experimental hot structure vibration results

NASA Technical Reports Server (NTRS)

Kehoe, Michael W.; Deaton, Vivian C.

1993-01-01

High surface temperatures and temperature gradients can affect the vibratory characteristics and stability of aircraft structures. Aircraft designers are relying more on finite-element model analysis methods to ensure sufficient vehicle structural dynamic stability throughout the desired flight envelope. Analysis codes that predict these thermal effects must be correlated and verified with experimental data. Experimental modal data for aluminum, titanium, and fiberglass plates heated at uniform, nonuniform, and transient heating conditions are presented. The data show the effect of heat on each plate's modal characteristics, a comparison of predicted and measured plate vibration frequencies, the measured modal damping, and the effect of modeling material property changes and thermal stresses on the accuracy of the analytical results at nonuniform and transient heating conditions.

An improved method for predicting the lightning performance of high and extra-high-voltage substation shielding

NASA Astrophysics Data System (ADS)

Vinh, T.

1980-08-01

There is a need for better and more effective lightning protection for transmission and switching substations. In the past, a number of empirical methods were utilized to design systems to protect substations and transmission lines from direct lightning strokes. The need exists for convenient analytical lightning models adequate for engineering usage. In this study, analytical lightning models were developed along with a method for improved analysis of the physical properties of lightning through their use. This method of analysis is based upon the most recent statistical field data. The result is an improved method for predicting the occurrence of sheilding failure and for designing more effective protection for high and extra high voltage substations from direct strokes.

Acoustic solitons in waveguides with Helmholtz resonators: transmission line approach.

PubMed

Achilleos, V; Richoux, O; Theocharis, G; Frantzeskakis, D J

2015-02-01

We report experimental results and study theoretically soliton formation and propagation in an air-filled acoustic waveguide side loaded with Helmholtz resonators. We propose a theoretical modeling of the system, which relies on a transmission-line approach, leading to a nonlinear dynamical lattice model. The latter allows for an analytical description of the various soliton solutions for the pressure, which are found by means of dynamical systems and multiscale expansion techniques. These solutions include Boussinesq-like and Korteweg-de Vries pulse-shaped solitons that are observed in the experiment, as well as nonlinear Schrödinger envelope solitons, that are predicted theoretically. The analytical predictions are in excellent agreement with direct numerical simulations and in qualitative agreement with the experimental observations.

Thermal behavior spiral bevel gears. Ph.D. Thesis - Case Western Univ., Aug. 1993

NASA Technical Reports Server (NTRS)

Handschuh, Robert F.

1995-01-01

An experimental and analytical study of the thermal behavior of spiral bevel gears is presented. Experimental data were taken using thermocoupled test hardware and an infrared microscope. Many operational parameters were varied to investigate their effects on the thermal behavior. The data taken were also used to validate the boundary conditions applied to the analytical model. A finite element-based solution sequence was developed. The three-dimensional model was developed based on the manufacturing process for these gears. Contact between the meshing gears was found using tooth contact analysis to describe the location, curvatures, orientations, and surface velocities. This information was then used in a three-dimensional Hertzian contact analysis to predict contact ellipse size and maximum pressure. From these results, an estimate of the heat flux magnitude and the location on the finite element model was made. The finite element model used time-averaged boundary conditions to permit the solution to attain steady state in a computationally efficient manner.Then time- and position-varying boundary conditions were applied to the model to analyze the cyclic heating and cooling due to the gears meshing and transferring heat to the surroundings, respectively. The model was run in this mode until the temperature behavior stabilized. The transient flash temperature on the surface was therefore described. The analysis can be used to predict the overall expected thermal behavior of spiral bevel gears. The experimental and analytical results were compared for this study and also with a limited number of other studies. The experimental and analytical results attained in the current study were basically within 10% of each other for the cases compared. The experimental comparison was for bulk thermocouple locations and data taken with an infrared microscope. The results of a limited number of other studies were compared with those obtained herein and predicted the same basic behavior.

An Excel Solver Exercise to Introduce Nonlinear Regression

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2013-01-01

Business students taking business analytics courses that have significant predictive modeling components, such as marketing research, data mining, forecasting, and advanced financial modeling, are introduced to nonlinear regression using application software that is a "black box" to the students. Thus, although correct models are…

Multiphysics modeling of microwave heating of whole tomato

USDA-ARS?s Scientific Manuscript database

A mathematical model of a food is useful for prediction of temperature profiles during microwave heating. However, due to their complex geometry and interaction with electromagnetic fields, whole tomatoes resist an analytical approach to modeling the fruit as it is subjected to microwave energy. T...

Retention prediction and separation optimization under multilinear gradient elution in liquid chromatography with Microsoft Excel macros.

PubMed

Fasoula, S; Zisi, Ch; Gika, H; Pappa-Louisi, A; Nikitas, P

2015-05-22

A package of Excel VBA macros have been developed for modeling multilinear gradient retention data obtained in single or double gradient elution mode by changing organic modifier(s) content and/or eluent pH. For this purpose, ten chromatographic models were used and four methods were adopted for their application. The methods were based on (a) the analytical expression of the retention time, provided that this expression is available, (b) the retention times estimated using the Nikitas-Pappa approach, (c) the stepwise approximation, and (d) a simple numerical approximation involving the trapezoid rule for integration of the fundamental equation for gradient elution. For all these methods, Excel VBA macros have been written and implemented using two different platforms; the fitting and the optimization platform. The fitting platform calculates not only the adjustable parameters of the chromatographic models, but also the significance of these parameters and furthermore predicts the analyte elution times. The optimization platform determines the gradient conditions that lead to the optimum separation of a mixture of analytes by using the Solver evolutionary mode, provided that proper constraints are set in order to obtain the optimum gradient profile in the minimum gradient time. The performance of the two platforms was tested using experimental and artificial data. It was found that using the proposed spreadsheets, fitting, prediction, and optimization can be performed easily and effectively under all conditions. Overall, the best performance is exhibited by the analytical and Nikitas-Pappa's methods, although the former cannot be used under all circumstances. Copyright © 2015 Elsevier B.V. All rights reserved.

Analytical solutions to dissolved contaminant plume evolution with source depletion during carbon dioxide storage.

PubMed

Yang, Yong; Liu, Yongzhong; Yu, Bo; Ding, Tian

2016-06-01

Volatile contaminants may migrate with carbon dioxide (CO2) injection or leakage in subsurface formations, which leads to the risk of the CO2 storage and the ecological environment. This study aims to develop an analytical model that could predict the contaminant migration process induced by CO2 storage. The analytical model with two moving boundaries is obtained through the simplification of the fully coupled model for the CO2-aqueous phase -stagnant phase displacement system. The analytical solutions are confirmed and assessed through the comparison with the numerical simulations of the fully coupled model. Then, some key variables in the analytical solutions, including the critical time, the locations of the dual moving boundaries and the advance velocity, are discussed to present the characteristics of contaminant migration in the multi-phase displacement system. The results show that these key variables are determined by four dimensionless numbers, Pe, RD, Sh and RF, which represent the effects of the convection, the dispersion, the interphase mass transfer and the retention factor of contaminant, respectively. The proposed analytical solutions could be used for tracking the migration of the injected CO2 and the contaminants in subsurface formations, and also provide an analytical tool for other solute transport in multi-phase displacement system. Copyright © 2016 Elsevier B.V. All rights reserved.

An approximate analytical solution for describing surface runoff and sediment transport over hillslope

NASA Astrophysics Data System (ADS)

Tao, Wanghai; Wang, Quanjiu; Lin, Henry

2018-03-01

Soil and water loss from farmland causes land degradation and water pollution, thus continued efforts are needed to establish mathematical model for quantitative analysis of relevant processes and mechanisms. In this study, an approximate analytical solution has been developed for overland flow model and sediment transport model, offering a simple and effective means to predict overland flow and erosion under natural rainfall conditions. In the overland flow model, the flow regime was considered to be transitional with the value of parameter β (in the kinematic wave model) approximately two. The change rate of unit discharge with distance was assumed to be constant and equal to the runoff rate at the outlet of the plane. The excess rainfall was considered to be constant under uniform rainfall conditions. The overland flow model developed can be further applied to natural rainfall conditions by treating excess rainfall intensity as constant over a small time interval. For the sediment model, the recommended values of the runoff erosion calibration constant (cr) and the splash erosion calibration constant (cf) have been given in this study so that it is easier to use the model. These recommended values are 0.15 and 0.12, respectively. Comparisons with observed results were carried out to validate the proposed analytical solution. The results showed that the approximate analytical solution developed in this paper closely matches the observed data, thus providing an alternative method of predicting runoff generation and sediment yield, and offering a more convenient method of analyzing the quantitative relationships between variables. Furthermore, the model developed in this study can be used as a theoretical basis for developing runoff and erosion control methods.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Comparison of modeled backscatter with SAR data at P-band

NASA Technical Reports Server (NTRS)

Wang, Yong; Davis, Frank W.; Melack, John M.

1992-01-01

In recent years several analytical models were developed to predict microwave scattering by trees and forest canopies. These models contribute to the understanding of radar backscatter over forested regions to the extent that they capture the basic interactions between microwave radiation and tree canopies, understories, and ground layers as functions of incidence angle, wavelength, and polarization. The Santa Barbara microwave model backscatter model for woodland (i.e. with discontinuous tree canopies) combines a single-tree backscatter model and a gap probability model. Comparison of model predictions with synthetic aperture radar (SAR) data and L-band (lambda = 0.235 m) is promising, but much work is still needed to test the validity of model predictions at other wavelengths. The validity of the model predictions at P-band (lambda = 0.68 m) for woodland stands at our Mt. Shasta test site was tested.

Contact-coupled impact of slender rods: analysis and experimental validation

PubMed Central

Tibbitts, Ira B.; Kakarla, Deepika; Siskey, Stephanie; Ochoa, Jorge A.; Ong, Kevin L.; Brannon, Rebecca M.

2013-01-01

To validate models of contact mechanics in low speed structural impact, slender rods were impacted in a drop tower, and measurements of the contact and vibration were compared to analytical and finite element (FE) models. The contact area was recorded using a novel thin-film transfer technique, and the contact duration was measured using electrical continuity. Strain gages recorded the vibratory strain in one rod, and a laser Doppler vibrometer measured speed. The experiment was modeled analytically on a one-dimensional spatial domain using a quasi-static Hertzian contact law and a system of delay differential equations. The three-dimensional FE model used hexahedral elements, a penalty contact algorithm, and explicit time integration. A small submodel taken from the initial global FE model economically refined the analysis in the small contact region. Measured contact areas were within 6% of both models’ predictions, peak speeds within 2%, cyclic strains within 12 με (RMS value), and contact durations within 2 μs. The global FE model and the measurements revealed small disturbances, not predicted by the analytical model, believed to be caused by interactions of the non-planar stress wavefront with the rod’s ends. The accuracy of the predictions for this simple test, as well as the versatility of the diagnostic tools, validates the theoretical and computational models, corroborates instrument calibration, and establishes confidence that the same methods may be used in experimental and computational study of contact mechanics during impact of more complicated structures. Recommendations are made for applying the methods to a particular biomechanical problem: the edge-loading of a loose prosthetic hip joint which can lead to premature wear and prosthesis failure. PMID:24729630

Analytical determination of thermal conductivity of W-UO2 and W-UN CERMET nuclear fuels

NASA Astrophysics Data System (ADS)

Webb, Jonathan A.; Charit, Indrajit

2012-08-01

The thermal conductivity of tungsten based CERMET fuels containing UO2 and UN fuel particles are determined as a function of particle geometry, stabilizer fraction and fuel-volume fraction, by using a combination of an analytical approach and experimental data collected from literature. Thermal conductivity is estimated using the Bruggeman-Fricke model. This study demonstrates that thermal conductivities of various CERMET fuels can be analytically predicted to values that are very close to the experimentally determined ones.

Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122

Viscoplastic deformations and compressive damage in an A359/SiC{sub p} metal-matrix composite

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

Li, Y.; Ramesh, K.T.; Chin, E.S.C.

2000-04-19

Recent work by the authors has examined the high-strain-rate compression of a metal-matrix composite consisting of an A359 Al alloy matrix reinforced by 20 vol.% of silicon carbide particulates (SiC{sub p}). The work-hardening that is observed in the experiments is much lower than that predicted by analytical and computational models which assume perfect particle-matrix interfaces and undamaged particles. In this work, the authors show that the discrepancy is a result of particle damage that develops within the A359/SiC{sub p} composite under compression. The evolution of particle damage has been characterized using quantitative microscopy, and is shown to be a functionmore » of the applied strain. A simple analytical model that incorporates evolving damage within the composite is proposed, and it is shown that the analytical predictions are consistent with the experimental observations over a wide range of strain rates.« less

The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares.

PubMed

Pellegrino Vidal, Rocío B; Allegrini, Franco; Olivieri, Alejandro C

2018-03-20

Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic contraction behaviour of pneumatic artificial muscle

NASA Astrophysics Data System (ADS)

Doumit, Marc D.; Pardoel, Scott

2017-07-01

The development of a dynamic model for the Pneumatic Artificial Muscle (PAM) is an imperative undertaking for understanding and analyzing the behaviour of the PAM as a function of time. This paper proposes a Newtonian based dynamic PAM model that includes the modeling of the muscle geometry, force, inertia, fluid dynamic, static and dynamic friction, heat transfer and valve flow while ignoring the effect of bladder elasticity. This modeling contribution allows the designer to predict, analyze and optimize PAM performance prior to its development. Thus advancing successful implementations of PAM based powered exoskeletons and medical systems. To date, most muscle dynamic properties are determined experimentally, furthermore, no analytical models that can accurately predict the muscle's dynamic behaviour are found in the literature. Most developed analytical models adequately predict the muscle force in static cases but neglect the behaviour of the system in the transient response. This could be attributed to the highly challenging task of deriving such a dynamic model given the number of system elements that need to be identified and the system's highly non-linear properties. The proposed dynamic model in this paper is successfully simulated through MATLAB programing and validated the pressure, contraction distance and muscle temperature with experimental testing that is conducted with in-house built prototype PAM's.

Acoustic Predictions of Manned and Unmanned Rotorcraft Using the Comprehensive Analytical Rotorcraft Model for Acoustics (CARMA) Code System

NASA Technical Reports Server (NTRS)

Boyd, D. Douglas, Jr.; Burley, Casey L.; Conner, David A.

2005-01-01

The Comprehensive Analytical Rotorcraft Model for Acoustics (CARMA) is being developed under the Quiet Aircraft Technology Project within the NASA Vehicle Systems Program. The purpose of CARMA is to provide analysis tools for the design and evaluation of efficient low-noise rotorcraft, as well as support the development of safe, low-noise flight operations. The baseline prediction system of CARMA is presented and current capabilities are illustrated for a model rotor in a wind tunnel, a rotorcraft in flight and for a notional coaxial rotor configuration; however, a complete validation of the CARMA system capabilities with respect to a variety of measured databases is beyond the scope of this work. For the model rotor illustration, predicted rotor airloads and acoustics for a BO-105 model rotor are compared to test data from HART-II. For the flight illustration, acoustic data from an MD-520N helicopter flight test, which was conducted at Eglin Air Force Base in September 2003, are compared with CARMA full vehicle flight predictions. Predicted acoustic metrics at three microphone locations are compared for limited level flight and descent conditions. Initial acoustic predictions using CARMA for a notional coaxial rotor system are made. The effect of increasing the vertical separation between the rotors on the predicted airloads and acoustic results are shown for both aerodynamically non-interacting and aerodynamically interacting rotors. The sensitivity of including the aerodynamic interaction effects of each rotor on the other, especially when the rotors are in close proximity to one another is initially examined. The predicted coaxial rotor noise is compared to that of a conventional single rotor system of equal thrust, where both are of reasonable size for an unmanned aerial vehicle (UAV).

Experimental investigation of elastic mode control on a model of a transport aircraft

NASA Technical Reports Server (NTRS)

Abramovitz, M.; Heimbaugh, R. M.; Nomura, J. K.; Pearson, R. M.; Shirley, W. A.; Stringham, R. H.; Tescher, E. L.; Zoock, I. E.

1981-01-01

A 4.5 percent DC-10 derivative flexible model with active controls is fabricated, developed, and tested to investigate the ability to suppress flutter and reduce gust loads with active controlled surfaces. The model is analyzed and tested in both semispan and complete model configuration. Analytical methods are refined and control laws are developed and successfully tested on both versions of the model. A 15 to 25 percent increase in flutter speed due to the active system is demonstrated. The capability of an active control system to significantly reduce wing bending moments due to turbulence is demonstrated. Good correlation is obtained between test and analytical prediction.

Dual nozzle aerodynamic and cooling analysis study

NASA Technical Reports Server (NTRS)

Meagher, G. M.

1981-01-01

Analytical models to predict performance and operating characteristics of dual nozzle concepts were developed and improved. Aerodynamic models are available to define flow characteristics and bleed requirements for both the dual throat and dual expander concepts. Advanced analytical techniques were utilized to provide quantitative estimates of the bleed flow, boundary layer, and shock effects within dual nozzle engines. Thermal analyses were performed to define cooling requirements for baseline configurations, and special studies of unique dual nozzle cooling problems defined feasible means of achieving adequate cooling.

26th International Symposium on Ballistics

DTIC Science & Technology

2011-09-16

judicious use of analytical predictions correlated with ballistic testing and post - test failure morphology investigations. •Our approach...ballistic predictions. The numerical predictions correlate well with the damage pattern. Post - Test Morphology Simulation Imbedded Steel Plate Removed Post ... Test •Numerical simulation of damage to embedded steel plate compares well with the post - test plate morphology •Multi-strike modeling in work

Analytical study of the heat loss attenuation by clothing on thermal manikins under radiative heat loads.

PubMed

Den Hartog, Emiel A; Havenith, George

2010-01-01

For wearers of protective clothing in radiation environments there are no quantitative guidelines available for the effect of a radiative heat load on heat exchange. Under the European Union funded project ThermProtect an analytical effort was defined to address the issue of radiative heat load while wearing protective clothing. As within the ThermProtect project much information has become available from thermal manikin experiments in thermal radiation environments, these sets of experimental data are used to verify the analytical approach. The analytical approach provided a good prediction of the heat loss in the manikin experiments, 95% of the variance was explained by the model. The model has not yet been validated at high radiative heat loads and neglects some physical properties of the radiation emissivity. Still, the analytical approach provides a pragmatic approach and may be useful for practical implementation in protective clothing standards for moderate thermal radiation environments.

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Vartio, Eric; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott,Robert C.

2007-01-01

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott, Robert C.

2006-01-01

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Low velocity impact analysis of composite laminated plates

NASA Astrophysics Data System (ADS)

Zheng, Daihua

2007-12-01

In the past few decades polymer composites have been utilized more in structures where high strength and light weight are major concerns, e.g., aircraft, high-speed boats and sports supplies. It is well known that they are susceptible to damage resulting from lateral impact by foreign objects, such as dropped tools, hail and debris thrown up from the runway. The impact response of the structures depends not only on the material properties but also on the dynamic behavior of the impacted structure. Although commercial software is capable of analyzing such impact processes, it often requires extensive expertise and rigorous training for design and analysis. Analytical models are useful as they allow parametric studies and provide a foundation for validating the numerical results from large-scale commercial software. Therefore, it is necessary to develop analytical or semi-analytical models to better understand the behaviors of composite structures under impact and their associated failure process. In this study, several analytical models are proposed in order to analyze the impact response of composite laminated plates. Based on Meyer's Power Law, a semi-analytical model is obtained for small mass impact response of infinite composite laminates by the method of asymptotic expansion. The original nonlinear second-order ordinary differential equation is transformed into two linear ordinary differential equations. This is achieved by neglecting high-order terms in the asymptotic expansion. As a result, the semi-analytical solution of the overall impact response can be applied to contact laws with varying coefficients. Then an analytical model accounting for permanent deformation based on an elasto-plastic contact law is proposed to obtain the closed-form solutions of the wave-controlled impact responses of composite laminates. The analytical model is also used to predict the threshold velocity for delamination onset by combining with an existing quasi-static delamination criterion. The predictions are compared with experimental data and explicit finite element LS-DYNA simulation. The comparisons show reasonable agreement. Furthermore, an analytical model is developed to evaluate the combined effects of prestresses and permanent deformation based on the linearized elasto-plastic contact law and the Laplace Transform technique. It is demonstrated that prestresses do not have noticeable effects on the time history of contact force and strains, but they have significant consequences on the plate central displacement. For a impacted composite laminate with the presence of prestresses, the contact force increases with the increasing of the mass of impactor, thickness and interlaminar shear strength of the laminate. The combined analytical and numerical investigations provide validated models for elastic and elasto-plastic impact analysis of composite structures and shed light on the design of impact-resistant composite systems.

Light-Frame Wall Systems: Performance and Predictability.

Treesearch

David S. Gromala

1983-01-01

This paper compares results of all wall tests with analytical predictions of performance.Conventional wood-stud walls of one configuration failed at bending loads that were 4 to 6 times design load.The computer model overpredicted wall strength by and average of 10 percent and deflection by an average of 6 percent.

Performance Models for the Spike Banded Linear System Solver

DOE PAGES

Manguoglu, Murat; Saied, Faisal; Sameh, Ahmed; ...

2011-01-01

With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and beyond, there is significant impetus for the development of scalable parallel sparse linear system solvers and preconditioners. An integral part of this design process is the development of performance models capable of predicting performance and providing accurate cost models for the solvers and preconditioners. There has been some work in the past on characterizing performance of the iterative solvers themselves. In this paper, we investigate the problem of characterizing performance and scalability of banded preconditioners. Recent work has demonstrated the superior convergence properties and robustness of banded preconditioners,more » compared to state-of-the-art ILU family of preconditioners as well as algebraic multigrid preconditioners. Furthermore, when used in conjunction with efficient banded solvers, banded preconditioners are capable of significantly faster time-to-solution. Our banded solver, the Truncated Spike algorithm is specifically designed for parallel performance and tolerance to deep memory hierarchies. Its regular structure is also highly amenable to accurate performance characterization. Using these characteristics, we derive the following results in this paper: (i) we develop parallel formulations of the Truncated Spike solver, (ii) we develop a highly accurate pseudo-analytical parallel performance model for our solver, (iii) we show excellent predication capabilities of our model – based on which we argue the high scalability of our solver. Our pseudo-analytical performance model is based on analytical performance characterization of each phase of our solver. These analytical models are then parameterized using actual runtime information on target platforms. An important consequence of our performance models is that they reveal underlying performance bottlenecks in both serial and parallel formulations. All of our results are validated on diverse heterogeneous multiclusters – platforms for which performance prediction is particularly challenging. Finally, we provide predict the scalability of the Spike algorithm using up to 65,536 cores with our model. In this paper we extend the results presented in the Ninth International Symposium on Parallel and Distributed Computing.« less

A theoretical and computational study of lithium-ion battery thermal management for electric vehicles using heat pipes

NASA Astrophysics Data System (ADS)

Greco, Angelo; Cao, Dongpu; Jiang, Xi; Yang, Hong

2014-07-01

A simplified one-dimensional transient computational model of a prismatic lithium-ion battery cell is developed using thermal circuit approach in conjunction with the thermal model of the heat pipe. The proposed model is compared to an analytical solution based on variable separation as well as three-dimensional (3D) computational fluid dynamics (CFD) simulations. The three approaches, i.e. the 1D computational model, analytical solution, and 3D CFD simulations, yielded nearly identical results for the thermal behaviours. Therefore the 1D model is considered to be sufficient to predict the temperature distribution of lithium-ion battery thermal management using heat pipes. Moreover, a maximum temperature of 27.6 °C was predicted for the design of the heat pipe setup in a distributed configuration, while a maximum temperature of 51.5 °C was predicted when forced convection was applied to the same configuration. The higher surface contact of the heat pipes allows a better cooling management compared to forced convection cooling. Accordingly, heat pipes can be used to achieve effective thermal management of a battery pack with confined surface areas.

Application of Precipitate Free Zone Growth Kinetics to the β-Phase Depletion Behavior in a CoNiCrAlY Coating Alloy: An Analytical Approach

NASA Astrophysics Data System (ADS)

Chen, H.

2018-06-01

This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/ β interface, and the Al concentration at γ/ γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.

Application of Precipitate Free Zone Growth Kinetics to the β-Phase Depletion Behavior in a CoNiCrAlY Coating Alloy: An Analytical Approach

NASA Astrophysics Data System (ADS)

Chen, H.

2018-03-01

This paper concerns the β-phase depletion kinetics of a thermally sprayed free-standing CoNiCrAlY (Co-31.7 pct Ni-20.8 pct Cr-8.1 pct Al-0.5 pct Y, all in wt pct) coating alloy. An analytical β-phase depletion model based on the precipitate free zone growth kinetics was developed to calculate the β-phase depletion kinetics during isothermal oxidation. This approach, which accounts for the molar volume of the alloy, the interfacial energy of the γ/β interface, and the Al concentration at γ/γ + β boundary, requires the Al concentrations in the β-phase depletion zone as the input rather than the oxidation kinetics at the oxide/coating interface. The calculated β-phase depletion zones derived from the current model were compared with experimental results. It is shown that the calculated β-phase depletion zones using the current model are in reasonable agreement with those obtained experimentally. The constant compositional terms used in the model are likely to cause the discrepancies between the model predictions and experimental results. This analytical approach, which shows a reasonable correlation with experimental results, demonstrates a good reliability in the fast evaluation on lifetime prediction of MCrAlY coatings.

Finite Element Modeling of the Buckling Response of Sandwich Panels

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Moore, David F.; Knight, Norman F., Jr.; Rankin, Charles C.

2002-01-01

A comparative study of different modeling approaches for predicting sandwich panel buckling response is described. The study considers sandwich panels with anisotropic face sheets and a very thick core. Results from conventional analytical solutions for sandwich panel overall buckling and face-sheet-wrinkling type modes are compared with solutions obtained using different finite element modeling approaches. Finite element solutions are obtained using layered shell element models, with and without transverse shear flexibility, layered shell/solid element models, with shell elements for the face sheets and solid elements for the core, and sandwich models using a recently developed specialty sandwich element. Convergence characteristics of the shell/solid and sandwich element modeling approaches with respect to in-plane and through-the-thickness discretization, are demonstrated. Results of the study indicate that the specialty sandwich element provides an accurate and effective modeling approach for predicting both overall and localized sandwich panel buckling response. Furthermore, results indicate that anisotropy of the face sheets, along with the ratio of principle elastic moduli, affect the buckling response and these effects may not be represented accurately by analytical solutions. Modeling recommendations are also provided.

Healthcare predictive analytics: An overview with a focus on Saudi Arabia.

PubMed

Alharthi, Hana

2018-03-08

Despite a newfound wealth of data and information, the healthcare sector is lacking in actionable knowledge. This is largely because healthcare data, though plentiful, tends to be inherently complex and fragmented. Health data analytics, with an emphasis on predictive analytics, is emerging as a transformative tool that can enable more proactive and preventative treatment options. This review considers the ways in which predictive analytics has been applied in the for-profit business sector to generate well-timed and accurate predictions of key outcomes, with a focus on key features that may be applicable to healthcare-specific applications. Published medical research presenting assessments of predictive analytics technology in medical applications are reviewed, with particular emphasis on how hospitals have integrated predictive analytics into their day-to-day healthcare services to improve quality of care. This review also highlights the numerous challenges of implementing predictive analytics in healthcare settings and concludes with a discussion of current efforts to implement healthcare data analytics in the developing country, Saudi Arabia. Copyright © 2018 The Author. Published by Elsevier Ltd.. All rights reserved.

Developing an analytical tool for evaluating EMS system design changes and their impact on cardiac arrest outcomes: combining geographic information systems with register data on survival rates

PubMed Central

2013-01-01

Background Out-of-hospital cardiac arrest (OHCA) is a frequent and acute medical condition that requires immediate care. We estimate survival rates from OHCA in the area of Stockholm, through developing an analytical tool for evaluating Emergency Medical Services (EMS) system design changes. The study also is an attempt to validate the proposed model used to generate the outcome measures for the study. Methods and results This was done by combining a geographic information systems (GIS) simulation of driving times with register data on survival rates. The emergency resources comprised ambulance alone and ambulance plus fire services. The simulation model predicted a baseline survival rate of 3.9 per cent, and reducing the ambulance response time by one minute increased survival to 4.6 per cent. Adding the fire services as first responders (dual dispatch) increased survival to 6.2 per cent from the baseline level. The model predictions were validated using empirical data. Conclusion We have presented an analytical tool that easily can be generalized to other regions or countries. The model can be used to predict outcomes of cardiac arrest prior to investment in EMS design changes that affect the alarm process, e.g. (1) static changes such as trimming the emergency call handling time or (2) dynamic changes such as location of emergency resources or which resources should carry a defibrillator. PMID:23415045

Analytic prediction of unconfined boundary layer flashback limits in premixed hydrogen-air flames

NASA Astrophysics Data System (ADS)

Hoferichter, Vera; Hirsch, Christoph; Sattelmayer, Thomas

2017-05-01

Flame flashback is a major challenge in premixed combustion. Hence, the prediction of the minimum flow velocity to prevent boundary layer flashback is of high technical interest. This paper presents an analytic approach to predicting boundary layer flashback limits for channel and tube burners. The model reflects the experimentally observed flashback mechanism and consists of a local and global analysis. Based on the local analysis, the flow velocity at flashback initiation is obtained depending on flame angle and local turbulent burning velocity. The local turbulent burning velocity is calculated in accordance with a predictive model for boundary layer flashback limits of duct-confined flames presented by the authors in an earlier publication. This ensures consistency of both models. The flame angle of the stable flame near flashback conditions can be obtained by various methods. In this study, an approach based on global mass conservation is applied and is validated using Mie-scattering images from a channel burner test rig at ambient conditions. The predicted flashback limits are compared to experimental results and to literature data from preheated tube burner experiments. Finally, a method for including the effect of burner exit temperature is demonstrated and used to explain the discrepancies in flashback limits obtained from different burner configurations reported in the literature.

Prediction of Precipitation Strengthening in the Commercial Mg Alloy AZ91 Using Dislocation Dynamics

DOE PAGES

Aagesen, L. K.; Miao, J.; Allison, J. E.; ...

2018-03-05

In this paper, dislocation dynamics simulations were used to predict the strengthening of a commercial magnesium alloy, AZ91, due to β-Mg 17Al 12 formed in the continuous precipitation mode. The precipitate distributions used in simulations were determined based on experimental characterization of the sizes, shapes, and number densities of the precipitates for 10-hour aging and 50-hour aging. For dislocations gliding on the basal plane, which is expected to be the dominant contributor to plastic deformation at room temperature, the critical resolved shear stress to bypass the precipitate distribution was 3.5 MPa for the 10-hour aged sample and 16.0 MPa formore » the 50-hour aged sample. The simulation results were compared to an analytical model of strengthening in this alloy, and the analytical model was found to predict critical resolved shear stresses that were approximately 30 pct lower. A model for the total yield strength was developed and compared with experiment for the 50-hour aged sample. Finally, the predicted yield strength, which included the precipitate strengthening contribution from the DD simulations, was 132.0 MPa, in good agreement with the measured yield strength of 141 MPa.« less

Prediction of Precipitation Strengthening in the Commercial Mg Alloy AZ91 Using Dislocation Dynamics

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

Aagesen, L. K.; Miao, J.; Allison, J. E.

In this paper, dislocation dynamics simulations were used to predict the strengthening of a commercial magnesium alloy, AZ91, due to β-Mg 17Al 12 formed in the continuous precipitation mode. The precipitate distributions used in simulations were determined based on experimental characterization of the sizes, shapes, and number densities of the precipitates for 10-hour aging and 50-hour aging. For dislocations gliding on the basal plane, which is expected to be the dominant contributor to plastic deformation at room temperature, the critical resolved shear stress to bypass the precipitate distribution was 3.5 MPa for the 10-hour aged sample and 16.0 MPa formore » the 50-hour aged sample. The simulation results were compared to an analytical model of strengthening in this alloy, and the analytical model was found to predict critical resolved shear stresses that were approximately 30 pct lower. A model for the total yield strength was developed and compared with experiment for the 50-hour aged sample. Finally, the predicted yield strength, which included the precipitate strengthening contribution from the DD simulations, was 132.0 MPa, in good agreement with the measured yield strength of 141 MPa.« less

Prediction of Precipitation Strengthening in the Commercial Mg Alloy AZ91 Using Dislocation Dynamics

NASA Astrophysics Data System (ADS)

Aagesen, L. K.; Miao, J.; Allison, J. E.; Aubry, S.; Arsenlis, A.

2018-03-01

Dislocation dynamics simulations were used to predict the strengthening of a commercial magnesium alloy, AZ91, due to β-Mg17Al12 formed in the continuous precipitation mode. The precipitate distributions used in simulations were determined based on experimental characterization of the sizes, shapes, and number densities of the precipitates for 10-hour aging and 50-hour aging. For dislocations gliding on the basal plane, which is expected to be the dominant contributor to plastic deformation at room temperature, the critical resolved shear stress to bypass the precipitate distribution was 3.5 MPa for the 10-hour aged sample and 16.0 MPa for the 50-hour aged sample. The simulation results were compared to an analytical model of strengthening in this alloy, and the analytical model was found to predict critical resolved shear stresses that were approximately 30 pct lower. A model for the total yield strength was developed and compared with experiment for the 50-hour aged sample. The predicted yield strength, which included the precipitate strengthening contribution from the DD simulations, was 132.0 MPa, in good agreement with the measured yield strength of 141 MPa.

Plasticity solutions for soil behaviour around contracting cavities and tunnels

NASA Astrophysics Data System (ADS)

Yu, H. S.; Rowe, R. K.

1999-10-01

The action of tunnel excavation reduces the in-situ stresses along the excavated circumference and can therefore be simulated by unloading of cavities from the in-situ stress state. Increasing evidence suggests that soil behavior in the plane perpendicular to the tunnel axis can be modelled reasonably by a contracting cylindrical cavity, while movements ahead of an advancing tunnel heading can be better predicted by spherical cavity contraction theory. In the past, solutions for unloading of cavities from in-situ stresses in cohesive-frictional soils have mainly concentrated on the small strain, cylindrical cavity model. Large strain spherical cavity contraction solutions with a non-associated Mohr-Coulomb model do not seem to be widely available for tunnel applications. Also, cavity unloading solutions in undrained clays have been developed only in terms of total stresses with a linear elastic-perfectly plastic soil model. The total stress analyses do not account for the effects of strain hardening/softening, variable soil stiffness, and soil stress history (OCR). The effect of these simplifying assumptions on the predicted soil behavior around tunnels is not known.In this paper, analytical and semi-analytical solutions are presented for unloading of both cylindrical and spherical cavities from in-situ state of stresses under both drained and undrained conditions. The non-associated Mohr-Coulomb model and various critical state theories are used respectively to describe the drained and undrained stress-strain behaviors of the soils. The analytical solutions presented in this paper are developed in terms of large strain formulations. These solutions can be used to serve two main purposes: (1) to provide models for predicting soil behavior around tunnels; (2) to provide valuable benchmark solutions for verifying various numerical methods involving both Mohr-Coulomb and critical state plasticity models.

Small-World Network Spectra in Mean-Field Theory

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc

2012-05-01

Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.

A Squeeze-film Damping Model for the Circular Torsion Micro-resonators

NASA Astrophysics Data System (ADS)

Yang, Fan; Li, Pu

2017-07-01

In recent years, MEMS devices are widely used in many industries. The prediction of squeeze-film damping is very important for the research of high quality factor resonators. In the past, there have been many analytical models predicting the squeeze-film damping of the torsion micro-resonators. However, for the circular torsion micro-plate, the works over it is very rare. The only model presented by Xia et al[7] using the method of eigenfunction expansions. In this paper, The Bessel series solution is used to solve the Reynolds equation under the assumption of the incompressible gas of the gap, the pressure distribution of the gas between two micro-plates is obtained. Then the analytical expression for the damping constant of the device is derived. The result of the present model matches very well with the finite element method (FEM) solutions and the result of Xia’s model, so the present models’ accuracy is able to be validated.

Quality by control: Towards model predictive control of mammalian cell culture bioprocesses.

PubMed

Sommeregger, Wolfgang; Sissolak, Bernhard; Kandra, Kulwant; von Stosch, Moritz; Mayer, Martin; Striedner, Gerald

2017-07-01

The industrial production of complex biopharmaceuticals using recombinant mammalian cell lines is still mainly built on a quality by testing approach, which is represented by fixed process conditions and extensive testing of the end-product. In 2004 the FDA launched the process analytical technology initiative, aiming to guide the industry towards advanced process monitoring and better understanding of how critical process parameters affect the critical quality attributes. Implementation of process analytical technology into the bio-production process enables moving from the quality by testing to a more flexible quality by design approach. The application of advanced sensor systems in combination with mathematical modelling techniques offers enhanced process understanding, allows on-line prediction of critical quality attributes and subsequently real-time product quality control. In this review opportunities and unsolved issues on the road to a successful quality by design and dynamic control implementation are discussed. A major focus is directed on the preconditions for the application of model predictive control for mammalian cell culture bioprocesses. Design of experiments providing information about the process dynamics upon parameter change, dynamic process models, on-line process state predictions and powerful software environments seem to be a prerequisite for quality by control realization. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

An Analytical Approach to Obtaining JWL Parameters from Cylinder Tests

NASA Astrophysics Data System (ADS)

Sutton, Ben; Ferguson, James

2015-06-01

An analytical method for determining parameters for the JWL equation of state (EoS) from cylinder test data is described. This method is applied to four datasets obtained from two 20.3 mm diameter EDC37 cylinder tests. The calculated parameters and pressure-volume (p-V) curves agree with those produced by hydro-code modelling. The calculated Chapman-Jouguet (CJ) pressure is 38.6 GPa, compared to the model value of 38.3 GPa; the CJ relative volume is 0.729 for both. The analytical pressure-volume curves produced agree with the one used in the model out to the commonly reported expansion of 7 relative volumes, as do the predicted energies generated by integrating under the p-V curve. The calculated and model energies are 8.64 GPa and 8.76 GPa respectively.

Simulating the universe(s) II: phenomenology of cosmic bubble collisions in full general relativity

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

Wainwright, Carroll L.; Aguirre, Anthony; Johnson, Matthew C.

2014-10-01

Observing the relics of collisions between bubble universes would provide direct evidence for the existence of an eternally inflating Multiverse; the non-observation of such events can also provide important constraints on inflationary physics. Realizing these prospects requires quantitative predictions for observables from the properties of the possible scalar field Lagrangians underlying eternal inflation. Building on previous work, we establish this connection in detail. We perform a fully relativistic numerical study of the phenomenology of bubble collisions in models with a single scalar field, computing the comoving curvature perturbation produced in a wide variety of models. We also construct a setmore » of analytic predictions, allowing us to identify the phenomenologically relevant properties of the scalar field Lagrangian. The agreement between the analytic predictions and numerics in the relevant regions is excellent, and allows us to generalize our results beyond the models we adopt for the numerical studies. Specifically, the signature is completely determined by the spatial profile of the colliding bubble just before the collision, and the de Sitter invariant distance between the bubble centers. The analytic and numerical results support a power-law fit with an index 1< κ ∼< 2. For collisions between identical bubbles, we establish a lower-bound on the observed amplitude of collisions that is set by the present energy density in curvature.« less

A Bayesian prediction model between a biomarker and the clinical endpoint for dichotomous variables.

PubMed

Jiang, Zhiwei; Song, Yang; Shou, Qiong; Xia, Jielai; Wang, William

2014-12-20

Early biomarkers are helpful for predicting clinical endpoints and for evaluating efficacy in clinical trials even if the biomarker cannot replace clinical outcome as a surrogate. The building and evaluation of an association model between biomarkers and clinical outcomes are two equally important concerns regarding the prediction of clinical outcome. This paper is to address both issues in a Bayesian framework. A Bayesian meta-analytic approach is proposed to build a prediction model between the biomarker and clinical endpoint for dichotomous variables. Compared with other Bayesian methods, the proposed model only requires trial-level summary data of historical trials in model building. By using extensive simulations, we evaluate the link function and the application condition of the proposed Bayesian model under scenario (i) equal positive predictive value (PPV) and negative predictive value (NPV) and (ii) higher NPV and lower PPV. In the simulations, the patient-level data is generated to evaluate the meta-analytic model. PPV and NPV are employed to describe the patient-level relationship between the biomarker and the clinical outcome. The minimum number of historical trials to be included in building the model is also considered. It is seen from the simulations that the logit link function performs better than the odds and cloglog functions under both scenarios. PPV/NPV ≥0.5 for equal PPV and NPV, and PPV + NPV ≥1 for higher NPV and lower PPV are proposed in order to predict clinical outcome accurately and precisely when the proposed model is considered. Twenty historical trials are required to be included in model building when PPV and NPV are equal. For unequal PPV and NPV, the minimum number of historical trials for model building is proposed to be five. A hypothetical example shows an application of the proposed model in global drug development. The proposed Bayesian model is able to predict well the clinical endpoint from the observed biomarker data for dichotomous variables as long as the conditions are satisfied. It could be applied in drug development. But the practical problems in applications have to be studied in further research.

MODEL CORRELATION STUDY OF A RETRACTABLE BOOM FOR A SOLAR SAIL SPACECRAFT

NASA Technical Reports Server (NTRS)

Adetona, O.; Keel, L. H.; Oakley, J. D.; Kappus, K.; Whorton, M. S.; Kim, Y. K.; Rakpczy, J. M.

2005-01-01

To realize design concepts, predict dynamic behavior and develop appropriate control strategies for high performance operation of a solar-sail spacecraft, we developed a simple analytical model that represents dynamic behavior of spacecraft with various sizes. Since motion of the vehicle is dominated by retractable booms that support the structure, our study concentrates on developing and validating a dynamic model of a long retractable boom. Extensive tests with various configurations were conducted for the 30 Meter, light-weight, retractable, lattice boom at NASA MSFC that is structurally and dynamically similar to those of a solar-sail spacecraft currently under construction. Experimental data were then compared with the corresponding response of the analytical model. Though mixed results were obtained, the analytical model emulates several key characteristics of the boom. The paper concludes with a detailed discussion of issues observed during the study.

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

Bourdon, Christopher Jay; Olsen, Michael G.; Gorby, Allen D.

The analytical model for the depth of correlation (measurement depth) of a microscopic particle image velocimetry (micro-PIV) experiment derived by Olsen and Adrian (Exp. Fluids, 29, pp. S166-S174, 2000) has been modified to be applicable to experiments using high numerical aperture optics. A series of measurements are presented that experimentally quantify the depth of correlation of micro-PIV velocity measurements which employ high numerical aperture and magnification optics. These measurements demonstrate that the modified analytical model is quite accurate in estimating the depth of correlation in micro-PIV measurements using this class of optics. Additionally, it was found that the Gaussian particlemore » approximation made in this model does not significantly affect the model's performance. It is also demonstrated that this modified analytical model easily predicts the depth of correlation when viewing into a medium of a different index of refraction than the immersion medium.« less

A simulation technique for predicting thickness of thermal sprayed coatings

NASA Technical Reports Server (NTRS)

Goedjen, John G.; Miller, Robert A.; Brindley, William J.; Leissler, George W.

1995-01-01

The complexity of many of the components being coated today using the thermal spray process makes the trial and error approach traditionally followed in depositing a uniform coating inadequate, thereby necessitating a more analytical approach to developing robotic trajectories. A two dimensional finite difference simulation model has been developed to predict the thickness of coatings deposited using the thermal spray process. The model couples robotic and component trajectories and thermal spraying parameters to predict coating thickness. Simulations and experimental verification were performed on a rotating disk to evaluate the predictive capabilities of the approach.

Determination of Uncertainties for the New SSME Model

NASA Technical Reports Server (NTRS)

Coleman, Hugh W.; Hawk, Clark W.

1996-01-01

This report discusses the uncertainty analysis performed in support of a new test analysis and performance prediction model for the Space Shuttle Main Engine. The new model utilizes uncertainty estimates for experimental data and for the analytical model to obtain the most plausible operating condition for the engine system. This report discusses the development of the data sets and uncertainty estimates to be used in the development of the new model. It also presents the application of uncertainty analysis to analytical models and the uncertainty analysis for the conservation of mass and energy balance relations is presented. A new methodology for the assessment of the uncertainty associated with linear regressions is presented.

Propeller aircraft interior noise model

NASA Technical Reports Server (NTRS)

Pope, L. D.; Wilby, E. G.; Wilby, J. F.

1984-01-01

An analytical model was developed to predict the interior noise of propeller-driven aircraft. The fuselage model is that of a cylinder with a structurally-integral floor. The cabin sidewall is stiffened by stringers and ring frames, and the floor by longitudinal beams. The cabin interior is covered with a sidewall treatments consisting of layers of porous material and an impervious trim septum. Representation of the propeller pressure field is utilized as input data in the form of the propeller noise signature at a series of locations on a grid over the fuselage structure. Results obtained from the analytical model are compared with test data measured by NASA in a scale model cylindrical fuselage excited by a model propeller.

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers.

PubMed

Wang, Fang; Annable, Michael D; Jawitz, James W

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E=0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important influence of well configuration and the associated flow patterns on dissolution. © 2013.

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers

NASA Astrophysics Data System (ADS)

Wang, Fang; Annable, Michael D.; Jawitz, James W.

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E = 0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important influence of well configuration and the associated flow patterns on dissolution.

Bending elasticity of macromolecules: analytic predictions from the wormlike chain model.

PubMed

Polley, Anirban; Samuel, Joseph; Sinha, Supurna

2013-01-01

We present a study of the bend angle distribution of semiflexible polymers of short and intermediate lengths within the wormlike chain model. This enables us to calculate the elastic response of a stiff molecule to a bending moment. Our results go beyond the Hookean regime and explore the nonlinear elastic behavior of a single molecule. We present analytical formulas for the bend angle distribution and for the moment-angle relation. Our analytical study is compared against numerical Monte Carlo simulations. The functional forms derived here can be applied to fluorescence microscopic studies on actin and DNA. Our results are relevant to recent studies of "kinks" and cyclization in short and intermediate length DNA strands.

External evaluation of population pharmacokinetic models of vancomycin in neonates: the transferability of published models to different clinical settings

PubMed Central

Zhao, Wei; Kaguelidou, Florentia; Biran, Valérie; Zhang, Daolun; Allegaert, Karel; Capparelli, Edmund V; Holford, Nick; Kimura, Toshimi; Lo, Yoke-Lin; Peris, José-Esteban; Thomson, Alison; Anker, John N; Fakhoury, May; Jacqz-Aigrain, Evelyne

2013-01-01

Aims Vancomycin is one of the most evaluated antibiotics in neonates using modeling and simulation approaches. However no clear consensus on optimal dosing has been achieved. The objective of the present study was to perform an external evaluation of published models, in order to test their predictive performances in an independent dataset and to identify the possible study-related factors influencing the transferability of pharmacokinetic models to different clinical settings. Method Published neonatal vancomycin pharmacokinetic models were screened from the literature. The predictive performance of six models was evaluated using an independent dataset (112 concentrations from 78 neonates). The evaluation procedures used simulation-based diagnostics [visual predictive check (VPC) and normalized prediction distribution errors (NPDE)]. Results Differences in predictive performances of models for vancomycin pharmacokinetics in neonates were found. The mean of NPDE for six evaluated models were 1.35, −0.22, −0.36, 0.24, 0.66 and 0.48, respectively. These differences were explained, at least partly, by taking into account the method used to measure serum creatinine concentrations. The adult conversion factor of 1.3 (enzymatic to Jaffé) was tested with an improvement in the VPC and NPDE, but it still needs to be evaluated and validated in neonates. Differences were also identified between analytical methods for vancomycin. Conclusion The importance of analytical techniques for serum creatinine concentrations and vancomycin as predictors of vancomycin concentrations in neonates have been confirmed. Dosage individualization of vancomycin in neonates should consider not only patients' characteristics and clinical conditions, but also the methods used to measure serum creatinine and vancomycin. PMID:23148919

Dark-ages Reionization and Galaxy Formation Simulation - XIV. Gas accretion, cooling, and star formation in dwarf galaxies at high redshift

NASA Astrophysics Data System (ADS)

Qin, Yuxiang; Duffy, Alan R.; Mutch, Simon J.; Poole, Gregory B.; Geil, Paul M.; Mesinger, Andrei; Wyithe, J. Stuart B.

2018-06-01

We study dwarf galaxy formation at high redshift (z ≥ 5) using a suite of high-resolution, cosmological hydrodynamic simulations and a semi-analytic model (SAM). We focus on gas accretion, cooling, and star formation in this work by isolating the relevant process from reionization and supernova feedback, which will be further discussed in a companion paper. We apply the SAM to halo merger trees constructed from a collisionless N-body simulation sharing identical initial conditions to the hydrodynamic suite, and calibrate the free parameters against the stellar mass function predicted by the hydrodynamic simulations at z = 5. By making comparisons of the star formation history and gas components calculated by the two modelling techniques, we find that semi-analytic prescriptions that are commonly adopted in the literature of low-redshift galaxy formation do not accurately represent dwarf galaxy properties in the hydrodynamic simulation at earlier times. We propose three modifications to SAMs that will provide more accurate high-redshift simulations. These include (1) the halo mass and baryon fraction which are overestimated by collisionless N-body simulations; (2) the star formation efficiency which follows a different cosmic evolutionary path from the hydrodynamic simulation; and (3) the cooling rate which is not well defined for dwarf galaxies at high redshift. Accurate semi-analytic modelling of dwarf galaxy formation informed by detailed hydrodynamical modelling will facilitate reliable semi-analytic predictions over the large volumes needed for the study of reionization.

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Riley, Richard D; Abrams, Keith R

2016-03-30

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Computationally efficient thermal-mechanical modelling of selective laser melting

NASA Astrophysics Data System (ADS)

Yang, Yabin; Ayas, Can

2017-10-01

The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is anticipated to be instrumental for understanding and predicting the development of residual stress field during the build process. However, SLM process modelling requires determination of the heat transients within the part being built which is coupled to a mechanical boundary value problem to calculate displacement and residual stress fields. Thermal models associated with SLM are typically complex and computationally demanding. In this paper, we present a simple semi-analytical thermal-mechanical model, developed for SLM that represents the effect of laser scanning vectors with line heat sources. The temperature field within the part being build is attained by superposition of temperature field associated with line heat sources in a semi-infinite medium and a complimentary temperature field which accounts for the actual boundary conditions. An analytical solution of a line heat source in a semi-infinite medium is first described followed by the numerical procedure used for finding the complimentary temperature field. This analytical description of the line heat sources is able to capture the steep temperature gradients in the vicinity of the laser spot which is typically tens of micrometers. In turn, semi-analytical thermal model allows for having a relatively coarse discretisation of the complimentary temperature field. The temperature history determined is used to calculate the thermal strain induced on the SLM part. Finally, a mechanical model governed by elastic-plastic constitutive rule having isotropic hardening is used to predict the residual stresses.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

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

Welch, Jr., Paul Michael; Welch, Cynthia F.

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

Acoustic impedance of micro perforated membranes: Velocity continuity condition at the perforation boundary.

PubMed

Li, Chenxi; Cazzolato, Ben; Zander, Anthony

2016-01-01

The classic analytical model for the sound absorption of micro perforated materials is well developed and is based on a boundary condition where the velocity of the material is assumed to be zero, which is accurate when the material vibration is negligible. This paper develops an analytical model for finite-sized circular micro perforated membranes (MPMs) by applying a boundary condition such that the velocity of air particles on the hole wall boundary is equal to the membrane vibration velocity (a zero-slip condition). The acoustic impedance of the perforation, which varies with its position, is investigated. A prediction method for the overall impedance of the holes and the combined impedance of the MPM is also provided. The experimental results for four different MPM configurations are used to validate the model and good agreement between the experimental and predicted results is achieved.

Eigenvector centrality is a metric of elastomer modulus, heterogeneity, and damage

DOE PAGES

Welch, Jr., Paul Michael; Welch, Cynthia F.

2017-04-27

Here, we present an application of eigenvector centrality to encode the connectivity of polymer networks resolved at the micro- and meso-scopic length scales. This method captures the relative importance of different nodes within the network structure and provides a route toward the development of a statistical mechanics model that correlates connectivity with mechanical response. This scheme may be informed by analytical and semi-analytical models for the network structure, or through direct experimental examination. It may be used to predict the reduction in mechanical performance for heterogeneous materials subjected to specific modes of damage. Here, we develop the method and demonstratemore » that it leads to the prediction of established trends in elastomers. We also apply the model to the case of a self-healing polymer network reported in the literature, extracting insight about the fraction of bonds broken and re-formed during strain and recovery.« less

High-performance heat pipes for heat recovery applications

NASA Technical Reports Server (NTRS)

Saaski, E. W.; Hartl, J. H.

1980-01-01

Methods to improve the performance of reflux heat pipes for heat recovery applications were examined both analytically and experimentally. Various models for the estimation of reflux heat pipe transport capacity were surveyed in the literature and compared with experimental data. A high transport capacity reflux heat pipe was developed that provides up to a factor of 10 capacity improvement over conventional open tube designs; analytical models were developed for this device and incorporated into a computer program HPIPE. Good agreement of the model predictions with data for R-11 and benzene reflux heat pipes was obtained.

An Improved Analytic Model for Microdosimeter Response

NASA Technical Reports Server (NTRS)

Shinn, Judy L.; Wilson, John W.; Xapsos, Michael A.

2001-01-01

An analytic model used to predict energy deposition fluctuations in a microvolume by ions through direct events is improved to include indirect delta ray events. The new model can now account for the increase in flux at low lineal energy when the ions are of very high energy. Good agreement is obtained between the calculated results and available data for laboratory ion beams. Comparison of GCR (galactic cosmic ray) flux between Shuttle TEPC (tissue equivalent proportional counter) flight data and current calculations draws a different assessment of developmental work required for the GCR transport code (HZETRN) than previously concluded.

An analytical prediction of the oscillation and extinction thresholds of a clarinet

NASA Astrophysics Data System (ADS)

Dalmont, Jean-Pierre; Gilbert, Joël; Kergomard, Jean; Ollivier, Sébastien

2005-11-01

This paper investigates the dynamic range of the clarinet from the oscillation threshold to the extinction at high pressure level. The use of an elementary model for the reed-mouthpiece valve effect combined with a simplified model of the pipe assuming frequency independent losses (Raman's model) allows an analytical calculation of the oscillations and their stability analysis. The different thresholds are shown to depend on parameters related to embouchure parameters and to the absorption coefficient in the pipe. Their values determine the dynamic range of the fundamental oscillations and the bifurcation scheme at the extinction.

Cell-model prediction of the melting of a Lennard-Jones solid

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

Holian, B.L.

The classical free energy of the Lennard-Jones 6-12 solid is computed from a single-particle anharmonic cell model with a correction to the entropy given by the classical correlational entropy of quasiharmonic lattice dynamics. The free energy of the fluid is obtained from the Hansen-Ree analytic fit to Monte Carlo equation-of-state calculations. The resulting predictions of the solid-fluid coexistence curves by this corrected cell model of the solid are in excellent agreement with the computer experiments.

Engine Structures Modeling Software System (ESMOSS)

NASA Technical Reports Server (NTRS)

1991-01-01

Engine Structures Modeling Software System (ESMOSS) is the development of a specialized software system for the construction of geometric descriptive and discrete analytical models of engine parts, components, and substructures which can be transferred to finite element analysis programs such as NASTRAN. The NASA Lewis Engine Structures Program is concerned with the development of technology for the rational structural design and analysis of advanced gas turbine engines with emphasis on advanced structural analysis, structural dynamics, structural aspects of aeroelasticity, and life prediction. Fundamental and common to all of these developments is the need for geometric and analytical model descriptions at various engine assembly levels which are generated using ESMOSS.

Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

PubMed

McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G

2015-11-11

Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

Black holes by analytic continuation

NASA Astrophysics Data System (ADS)

Amati, D.; Russo, J. G.

1997-07-01

In the context of a two-dimensional exactly solvable model, the dynamics of quantum black holes is obtained by analytically continuing the description of the regime where no black hole is formed. The resulting spectrum of outgoing radiation departs from the one predicted by the Hawking model in the region where the outgoing modes arise from the horizon with Planck-order frequencies. This occurs early in the evaporation process, and the resulting physical picture is unconventional. The theory predicts that black holes will only radiate out an energy of Planck mass order, stabilizing after a transitory period. The continuation from a regime without black hole formation-accessible in the 1+1 gravity theory considered-is implicit in an S-matrix approach and suggests in this way a possible solution to the problem of information loss.

Buckling Imperfection Sensitivity of Axially Compressed Orthotropic Cylinders

NASA Technical Reports Server (NTRS)

Schultz, Marc R.; Nemeth, Michael P.

2010-01-01

Structural stability is a major consideration in the design of lightweight shell structures. However, the theoretical predictions of geometrically perfect structures often considerably over predict the buckling loads of inherently imperfect real structures. It is reasonably well understood how the shell geometry affects the imperfection sensitivity of axially compressed cylindrical shells; however, the effects of shell anisotropy on the imperfection sensitivity is less well understood. In the present paper, the development of an analytical model for assessing the imperfection sensitivity of axially compressed orthotropic cylinders is discussed. Results from the analytical model for four shell designs are compared with those from a general-purpose finite-element code, and good qualitative agreement is found. Reasons for discrepancies are discussed, and potential design implications of this line of research are discussed.

Propeller aircraft interior noise model. II - Scale-model and flight-test comparisons

NASA Technical Reports Server (NTRS)

Willis, C. M.; Mayes, W. H.

1987-01-01

A program for predicting the sound levels inside propeller driven aircraft arising from sidewall transmission of airborne exterior noise is validated through comparisons of predictions with both scale-model test results and measurements obtained in flight tests on a turboprop aircraft. The program produced unbiased predictions for the case of the scale-model tests, with a standard deviation of errors of about 4 dB. For the case of the flight tests, the predictions revealed a bias of 2.62-4.28 dB (depending upon whether or not the data for the fourth harmonic were included) and the standard deviation of the errors ranged between 2.43 and 4.12 dB. The analytical model is shown to be capable of taking changes in the flight environment into account.

A theoretical study on pure bending of hexagonal close-packed metal sheet

NASA Astrophysics Data System (ADS)

Mehrabi, Hamed; Yang, Chunhui

2018-05-01

Hexagonal close-packed (HCP) metals have quite different mechanical behaviours in comparison to conventional cubic metals such as steels and aluminum alloys [1, 2]. They exhibit a significant tension-compression asymmetry in initial yielding and subsequent plastic hardening. The reason for this unique behaviour can be attributed to their limited symmetric crystal structure, which leads to twining deformation [3-5]. This unique behaviour strongly influences sheet metal forming of such metals, especially for roll forming, in which the bending is dominant. Hence, it is crucial to represent constitutive relations of HCP metals for accurate estimation of bending moment-curvature behaviours. In this paper, an analytical model for asymmetric elastoplastic pure bending with an application of Cazacu-Barlat asymmetric yield function [6] is presented. This yield function considers the asymmetrical tension-compression behaviour of HCP metals by using second and third invariants of the stress deviator tensor and a specified constant, which can be expressed in terms of uniaxial yield stresses in tension and compression. As a case study, the analytical model is applied to predict the moment-curvature behaviours of AZ31B magnesium alloy sheets under uniaxial loading condition. Furthermore, the analytical model is implemented as a user-defined material through the UMAT interface in Abaqus [7, 8] for conducting pure bending simulations. The results show that the analytical model can reasonably capture the asymmetric tension-compression behaviour of the magnesium alloy. The predicted moment-curvature behaviour has good agreement with the experimental results. Furthermore, numerical results show a better accuracy by the application of the Cazacu-Barlat yield function than those using the von-Mises yield function, which are more conservative than analytical results.

Analytical performance evaluation of SAR ATR with inaccurate or estimated models

NASA Astrophysics Data System (ADS)

DeVore, Michael D.

2004-09-01

Hypothesis testing algorithms for automatic target recognition (ATR) are often formulated in terms of some assumed distribution family. The parameter values corresponding to a particular target class together with the distribution family constitute a model for the target's signature. In practice such models exhibit inaccuracy because of incorrect assumptions about the distribution family and/or because of errors in the assumed parameter values, which are often determined experimentally. Model inaccuracy can have a significant impact on performance predictions for target recognition systems. Such inaccuracy often causes model-based predictions that ignore the difference between assumed and actual distributions to be overly optimistic. This paper reports on research to quantify the effect of inaccurate models on performance prediction and to estimate the effect using only trained parameters. We demonstrate that for large observation vectors the class-conditional probabilities of error can be expressed as a simple function of the difference between two relative entropies. These relative entropies quantify the discrepancies between the actual and assumed distributions and can be used to express the difference between actual and predicted error rates. Focusing on the problem of ATR from synthetic aperture radar (SAR) imagery, we present estimators of the probabilities of error in both ideal and plug-in tests expressed in terms of the trained model parameters. These estimators are defined in terms of unbiased estimates for the first two moments of the sample statistic. We present an analytical treatment of these results and include demonstrations from simulated radar data.

Analytical model development for the prediction of the frictional resistance of a capsule endoscope inside an intestine.

PubMed

Kim, J S; Sung, I H; Kim, Y T; Kim, D E; Jang, Y H

2007-11-01

For the purpose of optimizing the design of the locomotion mechanism as well as the body shape of a self-propelled capsule endoscope, an analytical model for the prediction of frictional resistance of the capsule moving inside the small intestine was first developed. The model was developed by considering the contact geometry and viscoelasticity of the intestine, based on the experimental investigations on the material properties of the intestine and the friction of the capsule inside the small intestine. In order to verify the model and to investigate the distributions of various stress components applied to the capsule, finite element (FE) analyses were carried out. The comparison of the frictional resistance between the predicted and the experimental values suggested that the proposed model could predict the frictional force of the capsule with reasonable accuracy. Also, the FE analysis results of various stress components revealed the stress relaxation of the intestine and explained that such stress relaxation characteristics of the intestine resulted in lower frictional force as the speed of the capsule decreased. These results suggested that the frontal shape of the capsule was critical to the design of the capsule with desired frictional performance. It was shown that the proposed model can provide quantitative estimation of the frictional resistance of the capsule under various moving conditions inside the intestine. The model is expected to be useful in the design optimization of the capsule locomotion inside the intestine.

Feedbacks Between Shallow Groundwater Dynamics and Surface Topography on Runoff Generation in Flat Fields

NASA Astrophysics Data System (ADS)

Appels, Willemijn M.; Bogaart, Patrick W.; van der Zee, Sjoerd E. A. T. M.

2017-12-01

In winter, saturation excess (SE) ponding is observed regularly in temperate lowland regions. Surface runoff dynamics are controlled by small topographical features that are unaccounted for in hydrological models. To better understand storage and routing effects of small-scale topography and their interaction with shallow groundwater under SE conditions, we developed a model of reduced complexity to investigate SE runoff generation, emphasizing feedbacks between shallow groundwater dynamics and mesotopography. The dynamic specific yield affected unsaturated zone water storage, causing rapid switches between negative and positive head and a flatter groundwater mound than predicted by analytical agrohydrological models. Accordingly, saturated areas were larger and local groundwater fluxes smaller than predicted, leading to surface runoff generation. Mesotopographic features routed water over larger distances, providing a feedback mechanism that amplified changes to the shape of the groundwater mound. This in turn enhanced runoff generation, but whether it also resulted in runoff events depended on the geometry and location of the depressions. Whereas conditions favorable to runoff generation may abound during winter, these feedbacks profoundly reduce the predictability of SE runoff: statistically identical rainfall series may result in completely different runoff generation. The model results indicate that waterlogged areas in any given rainfall event are larger than those predicted by current analytical groundwater models used for drainage design. This change in the groundwater mound extent has implications for crop growth and damage assessments.

The effect of analytic and experiential modes of thought on moral judgment.

PubMed

Kvaran, Trevor; Nichols, Shaun; Sanfey, Alan

2013-01-01

According to dual-process theories, moral judgments are the result of two competing processes: a fast, automatic, affect-driven process and a slow, deliberative, reason-based process. Accordingly, these models make clear and testable predictions about the influence of each system. Although a small number of studies have attempted to examine each process independently in the context of moral judgment, no study has yet tried to experimentally manipulate both processes within a single study. In this chapter, a well-established "mode-of-thought" priming technique was used to place participants in either an experiential/emotional or analytic mode while completing a task in which participants provide judgments about a series of moral dilemmas. We predicted that individuals primed analytically would make more utilitarian responses than control participants, while emotional priming would lead to less utilitarian responses. Support was found for both of these predictions. Implications of these findings for dual-process theories of moral judgment will be discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Accurate analytical modeling of junctionless DG-MOSFET by green's function approach

NASA Astrophysics Data System (ADS)

Nandi, Ashutosh; Pandey, Nilesh

2017-11-01

An accurate analytical model of Junctionless double gate MOSFET (JL-DG-MOSFET) in the subthreshold regime of operation is developed in this work using green's function approach. The approach considers 2-D mixed boundary conditions and multi-zone techniques to provide an exact analytical solution to 2-D Poisson's equation. The Fourier coefficients are calculated correctly to derive the potential equations that are further used to model the channel current and subthreshold slope of the device. The threshold voltage roll-off is computed from parallel shifts of Ids-Vgs curves between the long channel and short-channel devices. It is observed that the green's function approach of solving 2-D Poisson's equation in both oxide and silicon region can accurately predict channel potential, subthreshold current (Isub), threshold voltage (Vt) roll-off and subthreshold slope (SS) of both long & short channel devices designed with different doping concentrations and higher as well as lower tsi/tox ratio. All the analytical model results are verified through comparisons with TCAD Sentaurus simulation results. It is observed that the model matches quite well with TCAD device simulations.

A correlative study between analysis and experiment on the fracture behavior of graphite/epoxy composites

NASA Technical Reports Server (NTRS)

Yeow, Y. T.; Morris, D. H.; Brinson, H. F.

1979-01-01

The paper compares the fracture behavior of a composite material by using the analytical models of Waddoups et al. (1971), Whitney and Nuismer (1974, 1975), and Snyder and Cruse (1975) with experimental results from tests performed on center-notched tensile strips. Laminate configurations of (0 deg)8s, (0 deg/90 deg)4s, (+ and -45 deg)4s, and (0 deg/+ and -45 deg/0 deg)2s from T300/934 graphite/epoxy are tested. These particular configurations are used so that the effect of various degrees of anisotropy can be studied. The procedure adopted uses the results from one test for crack size aspect ratio to predict the results of tests of other aspect ratios. For those methods that use a characteristic dimension, predictions are made by assuming the magnitude of this dimension to be constant. The validity of this assumption for a laminate is assessed by comparing predicted and experimental results. Analytical models using a characteristic dimension are compared to the model developed by Cruse (1973).

Study of cavitating inducer instabilities

NASA Technical Reports Server (NTRS)

Young, W. E.; Murphy, R.; Reddecliff, J. M.

1972-01-01

An analytic and experimental investigation into the causes and mechanisms of cavitating inducer instabilities was conducted. Hydrofoil cascade tests were performed, during which cavity sizes were measured. The measured data were used, along with inducer data and potential flow predictions, to refine an analysis for the prediction of inducer blade suction surface cavitation cavity volume. Cavity volume predictions were incorporated into a linearized system model, and instability predictions for an inducer water test loop were generated. Inducer tests were conducted and instability predictions correlated favorably with measured instability data.

Measured and calculated acoustic attenuation rates of tuned resonator arrays for two surface impedance distribution models with flow

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Abrahamson, A. Louis; Jones, Michael G.

1988-01-01

An experiment was performed to validate two analytical models for predicting low frequency attenuation of duct liner configurations built from an array of seven resonators that could be individually tuned via adjustable cavity depths. These analytical models had previously been developed for high frequency aero-engine inlet duct liner design. In the low frequency application, the liner surface impedance distribution is unavoidably spatially varying by virtue of available fabrication techniques. The characteristic length of this spatial variation may be a significant fraction of the acoustic wavelength. Comparison of measured and predicted attenuation rates and transmission losses for both modal decomposition and finite element propagation models were in good to excellent agreement for a test frequency range that included the first and second cavity resonance frequencies. This was true for either of two surface impedance distribution modeling procedures used to simplify the impedance boundary conditions. In the presence of mean flow, measurements revealed a fine scale structure of acoustic hot spots in the attenuation and phase profiles. These details were accurately predicted by the finite element model. Since no impedance changes due to mean flow were assumed, it is concluded that this fine scale structure was due to convective effects of the mean flow interacting with the surface impedance nonuniformities.

Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC): User Guide. Version 3

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.; Wilt, T. E.; Trowbridge, D.

1999-01-01

The ability to accurately predict the thermomechanical deformation response of advanced composite materials continues to play an important role in the development of these strategic materials. Analytical models that predict the effective behavior of composites are used not only by engineers performing structural analysis of large-scale composite components but also by material scientists in developing new material systems. For an analytical model to fulfill these two distinct functions it must be based on a micromechanics approach which utilizes physically based deformation and life constitutive models and allows one to generate the average (macro) response of a composite material given the properties of the individual constituents and their geometric arrangement. Here the user guide for the recently developed, computationally efficient and comprehensive micromechanics analysis code, MAC, who's predictive capability rests entirely upon the fully analytical generalized method of cells, GMC, micromechanics model is described. MAC/ GMC is a versatile form of research software that "drives" the double or triply periodic micromechanics constitutive models based upon GMC. MAC/GMC enhances the basic capabilities of GMC by providing a modular framework wherein 1) various thermal, mechanical (stress or strain control) and thermomechanical load histories can be imposed, 2) different integration algorithms may be selected, 3) a variety of material constitutive models (both deformation and life) may be utilized and/or implemented, and 4) a variety of fiber architectures (both unidirectional, laminate and woven) may be easily accessed through their corresponding representative volume elements contained within the supplied library of RVEs or input directly by the user, and 5) graphical post processing of the macro and/or micro field quantities is made available.

Outgassing and dimensional changes of polymer matrix composites in space

NASA Technical Reports Server (NTRS)

Tennyson, R. C.; Matthews, R.

1993-01-01

A thermal-vacuum outgassing model and test protocol for predicting outgassing times and dimensional changes for polymer matrix composites is described. Experimental results derived from a 'control' sample are used to provide the basis for analytical predictions to compare with the outgassing response of Long Duration Exposure Facility (LDEF) flight samples.

Prediction of response of aircraft panels subjected to acoustic and thermal loads

NASA Technical Reports Server (NTRS)

Mei, Chuh

1992-01-01

The primary effort of this research project has been focused on the development of analytical methods for the prediction of random response of structural panels subjected to combined and intense acoustic and thermal loads. The accomplishments on various acoustic fatigue research activities are described first, then followed by publications and theses. Topics covered include: transverse shear deformation; finite element models of vibrating composite laminates; large deflection vibration modeling; finite element analysis of thermal buckling; and prediction of three dimensional duct using boundary element method.

Modeling Kelvin Wave Cascades in Superfluid Helium

NASA Astrophysics Data System (ADS)

Boffetta, G.; Celani, A.; Dezzani, D.; Laurie, J.; Nazarenko, S.

2009-09-01

We study two different types of simplified models for Kelvin wave turbulence on quantized vortex lines in superfluids near zero temperature. Our first model is obtained from a truncated expansion of the Local Induction Approximation (Truncated-LIA) and it is shown to possess the same scalings and the essential behaviour as the full Biot-Savart model, being much simpler than the later and, therefore, more amenable to theoretical and numerical investigations. The Truncated-LIA model supports six-wave interactions and dual cascades, which are clearly demonstrated via the direct numerical simulation of this model in the present paper. In particular, our simulations confirm presence of the weak turbulence regime and the theoretically predicted spectra for the direct energy cascade and the inverse wave action cascade. The second type of model we study, the Differential Approximation Model (DAM), takes a further drastic simplification by assuming locality of interactions in k-space via using a differential closure that preserves the main scalings of the Kelvin wave dynamics. DAMs are even more amenable to study and they form a useful tool by providing simple analytical solutions in the cases when extra physical effects are present, e.g. forcing by reconnections, friction dissipation and phonon radiation. We study these models numerically and test their theoretical predictions, in particular the formation of the stationary spectra, and closeness of numerics for the higher-order DAM to the analytical predictions for the lower-order DAM.

Analytical Modeling of Pressure Wall Hole Size and Maximum Tip-to-Tip Crack Length for Perforating Normal and Oblique Orbital Debris Impacts

NASA Technical Reports Server (NTRS)

Schonberg, William P.; Mohamed, Essam

1997-01-01

This report presents the results of a study whose objective was to develop first-principles-based models of hole size and maximum tip-to-tip crack length for a spacecraft module pressure wall that has been perforated in an orbital debris particle impact. The hole size and crack length models are developed by sequentially characterizing the phenomena comprising the orbital debris impact event, including the initial impact, the creation and motion of a debris cloud within the dual-wall system, the impact of the debris cloud on the pressure wall, the deformation of the pressure wall due to debris cloud impact loading prior to crack formation, pressure wall crack initiation, propagation, and arrest, and finally pressure wall deformation following crack initiation and growth. The model development has been accomplished through the application of elementary shock physics and thermodynamic theory, as well as the principles of mass, momentum, and energy conservation. The predictions of the model developed herein are compared against the predictions of empirically-based equations for hole diameters and maximum tip-to-tip crack length for three International Space Station wall configurations. The ISS wall systems considered are the baseline U.S. Lab Cylinder, the enhanced U.S. Lab Cylinder, and the U.S. Lab Endcone. The empirical predictor equations were derived from experimentally obtained hole diameters and crack length data. The original model predictions did not compare favorably with the experimental data, especially for cases in which pressure wall petalling did not occur. Several modifications were made to the original model to bring its predictions closer in line with the experimental results. Following the adjustment of several empirical constants, the predictions of the modified analytical model were in much closer agreement with the experimental results.

Heat generation in aircraft tires under braked rolling conditions

NASA Technical Reports Server (NTRS)

Clark, S. K.; Dodge, R. N.

1984-01-01

An analytical model was developed to approximate the internal temperature distribution in an aircraft tire operating under conditions of unyawed braked rolling. The model employs an array of elements to represent the tire cross section and considers the heat generated within the tire to be caused by the change in strain energy associated with cyclic tire deflection. The additional heating due to tire slip and stresses induced by braking are superimposed on the previously developed free rolling model. An extensive experimental program was conducted to verify temperatures predicted from the analytical model. Data from these tests were compared with calculations over a range of operating conditions. The model results were in reasonably good agreement with measured values.

Analytical modeling of the mechanics of early invasion of a merozoite into a human erythrocyte.

PubMed

Abdalrahman, Tamer; Franz, Thomas

2017-12-01

In this study, we used a continuum model based on contact mechanics to understand the mechanics of merozoite invasion into human erythrocytes. This model allows us to evaluate the indentation force and work as well as the contact pressure between the merozoite and erythrocyte for an early stage of invasion (γ = 10%). The model predicted an indentation force of 1.3e -11 N and an indentation work of 1e -18 J. The present analytical model can be considered as a useful tool not only for investigations in mechanobiology and biomechanics but also to explore novel therapeutic targets for malaria and other parasite infections.

An innovative hybrid 3D analytic-numerical model for air breathing parallel channel counter-flow PEM fuel cells.

PubMed

Tavčar, Gregor; Katrašnik, Tomaž

2014-01-01

The parallel straight channel PEM fuel cell model presented in this paper extends the innovative hybrid 3D analytic-numerical (HAN) approach previously published by the authors with capabilities to address ternary diffusion systems and counter-flow configurations. The model's core principle is modelling species transport by obtaining a 2D analytic solution for species concentration distribution in the plane perpendicular to the cannel gas-flow and coupling consecutive 2D solutions by means of a 1D numerical pipe-flow model. Electrochemical and other nonlinear phenomena are coupled to the species transport by a routine that uses derivative approximation with prediction-iteration. The latter is also the core of the counter-flow computation algorithm. A HAN model of a laboratory test fuel cell is presented and evaluated against a professional 3D CFD simulation tool showing very good agreement between results of the presented model and those of the CFD simulation. Furthermore, high accuracy results are achieved at moderate computational times, which is owed to the semi-analytic nature and to the efficient computational coupling of electrochemical kinetics and species transport.

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.

Evaluation and Prediction of Water Resources Based on AHP

NASA Astrophysics Data System (ADS)

Li, Shuai; Sun, Anqi

2017-01-01

Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm. After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

Experimental and theoretical analysis of defocused CO2 laser microchanneling on PMMA for enhanced surface finish

NASA Astrophysics Data System (ADS)

Prakash, Shashi; Kumar, Subrata

2017-02-01

The poor surface finish of CO2 laser-micromachined microchannel walls is a major limitation of its utilization despite several key advantages, like low fabrication cost and low time consumption. Defocused CO2 laser beam machining is an effective solution for fabricating smooth microchannel walls on polymer and glass substrates. In this research work, the CO2 laser microchanneling process on PMMA has been analyzed at different beam defocus positions. Defocused processing has been investigated both theoretically and experimentally, and the depth of focus and beam diameter have been determined experimentally. The effect of beam defocusing on the microchannel width, depth, surface roughness, heat affected zone and microchannel profile were examined. A previously developed analytical model for microchannel depth prediction has been improved by incorporating the threshold energy density factor. A semi-analytical model for predicting the microchannel width at different defocus positions has been developed. A semi-empirical model has also been developed for predicting microchannel widths at different defocusing conditions for lower depth values. The developed models were compared and verified by performing actual experiments. Multi-objective optimization was performed to select the best optimum set of input parameters for achieving the desired surface roughness.

Spatial Evolution of Human Dialects

NASA Astrophysics Data System (ADS)

Burridge, James

2017-07-01

The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wavelike spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy's curve giving the relationship between geographical and linguistic distance, and a generalization of the curve to account for the presence of a population center. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.

2D Analytical Model for the Directivity Prediction of Ultrasonic Contact Type Transducers in the Generation of Guided Waves.

PubMed

Tiwari, Kumar Anubhav; Raisutis, Renaldas; Mazeika, Liudas; Samaitis, Vykintas

2018-03-26

In this paper, a novel 2D analytical model based on the Huygens's principle of wave propagation is proposed in order to predict the directivity patterns of contact type ultrasonic transducers in the generation of guided waves (GWs). The developed model is able to estimate the directivity patterns at any distance, at any excitation frequency and for any configuration and shape of the transducers with prior information of phase dispersive characteristics of the guided wave modes and the behavior of transducer. This, in turn, facilitates to choose the appropriate transducer or arrays of transducers, suitable guided wave modes and excitation frequency for the nondestructive testing (NDT) and structural health monitoring (SHM) applications. The model is demonstrated for P1-type macro-fiber composite (MFC) transducer glued on a 2 mm thick aluminum (Al) alloy plate. The directivity patterns of MFC transducer in the generation of fundamental guided Lamb modes (the S0 and A0) and shear horizontal mode (the SH0) are successfully obtained at 80 kHz, 5-period excitation signal. The results are verified using 3D finite element (FE) modelling and experimental investigation. The results obtained using the proposed model shows the good agreement with those obtained using numerical simulations and experimental analysis. The calculation time using the analytical model was significantly shorter as compared to the time spent in experimental analysis and FE numerical modelling.

The impact of JP-4/JP-8 conversion on aircraft engine exhaust emissions. Interim technical report Jul 75--Feb 76

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

Blazowski, W.S.

1976-05-01

The proposed conversion of predominant Air Force fuel usage from JP-4 to JP-8 has created the need to examine the dependence of engine pollutant emission on fuel type. Available data concerning the effect of fuel type on emissions has been reviewed. T56 single combustor testing has been undertaken to determine JP-4/JP-8 emission variations over a wide range of simulated engine cycle operating conditions at idle. In addition, a J85-5 engine was tested using JP-4 and JP-8. Results of the previous and new data collectively led to the following conclusions regarding conversion to JP-8: (a) HC and CO emission changes willmore » depend upon individual combustor design features, (b) no change to NOx emission will occur, and (c) an increase in smoke/particulate emissions will result. It is recommended that these findings be incorporated into air quality analytical models to define the overall impact of the proposed conversion. Further, it is recommended that combustor analytical models be employed to attempt prediction of the results described herein. Should these models be successful, analytical prediction of JP-8 emissions from other Air Force engine models may be substituted for more combustor rig or engine testing. (auth)« less

Initial study of thermal energy storage in unconfined aquifers. [UCATES

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

Haitjema, H.M.; Strack, O.D.L.

1986-04-01

Convective heat transport in unconfined aquifers is modeled in a semi-analytic way. The transient groundwater flow is modeled by superposition of analytic functions, whereby changes in the aquifer storage are represented by a network of triangles, each with a linearly varying sink distribution. This analytic formulation incorporates the nonlinearity of the differential equation for unconfined flow and eliminates numerical dispersion in modeling heat convection. The thermal losses through the aquifer base and vadose zone are modeled rather crudely. Only vertical heat conduction is considered in these boundaries, whereby a linearly varying temperature is assumed at all times. The latter assumptionmore » appears reasonable for thin aquifer boundaries. However, assuming such thin aquifer boundaries may lead to an overestimation of the thermal losses when the aquifer base is regarded as infinitely thick in reality. The approach is implemented in the computer program UCATES, which serves as a first step toward the development of a comprehensive screening tool for ATES systems in unconfined aquifers. In its present form, the program is capable of predicting the relative effects of regional flow on the efficiency of ATES systems. However, only after a more realistic heatloss mechanism is incorporated in UCATES will reliable predictions of absolute ATES efficiencies be possible.« less

Comprehensive analytical model for locally contacted rear surface passivated solar cells

NASA Astrophysics Data System (ADS)

Wolf, Andreas; Biro, Daniel; Nekarda, Jan; Stumpp, Stefan; Kimmerle, Achim; Mack, Sebastian; Preu, Ralf

2010-12-01

For optimum performance of solar cells featuring a locally contacted rear surface, the metallization fraction as well as the size and distribution of the local contacts are crucial, since Ohmic and recombination losses have to be balanced. In this work we present a set of equations which enable to calculate this trade off without the need of numerical simulations. Our model combines established analytical and empirical equations to predict the energy conversion efficiency of a locally contacted device. For experimental verification, we fabricate devices from float zone silicon wafers of different resistivity using the laser fired contact technology for forming the local rear contacts. The detailed characterization of test structures enables the determination of important physical parameters, such as the surface recombination velocity at the contacted area and the spreading resistance of the contacts. Our analytical model reproduces the experimental results very well and correctly predicts the optimum contact spacing without the use of free fitting parameters. We use our model to estimate the optimum bulk resistivity for locally contacted devices fabricated from conventional Czochralski-grown silicon material. These calculations use literature values for the stable minority carrier lifetime to account for the bulk recombination caused by the formation of boron-oxygen complexes under carrier injection.

Assessment of Geometry and In-Flow Effects on Contra-Rotating Open Rotor Broadband Noise Predictions

NASA Technical Reports Server (NTRS)

Zawodny, Nikolas S.; Nark, Douglas M.; Boyd, D. Douglas, Jr.

2015-01-01

Application of previously formulated semi-analytical models for the prediction of broadband noise due to turbulent rotor wake interactions and rotor blade trailing edges is performed on the historical baseline F31/A31 contra-rotating open rotor configuration. Simplified two-dimensional blade element analysis is performed on cambered NACA 4-digit airfoil profiles, which are meant to serve as substitutes for the actual rotor blade sectional geometries. Rotor in-flow effects such as induced axial and tangential velocities are incorporated into the noise prediction models based on supporting computational fluid dynamics (CFD) results and simplified in-flow velocity models. Emphasis is placed on the development of simplified rotor in-flow models for the purpose of performing accurate noise predictions independent of CFD information. The broadband predictions are found to compare favorably with experimental acoustic results.

Theoretical predicting of permeability evolution in damaged rock under compressive stress

NASA Astrophysics Data System (ADS)

Vu, M. N.; Nguyen, S. T.; To, Q. D.; Dao, N. H.

2017-05-01

This paper outlines an analytical model of crack growth induced permeability changes. A theoretical solution of effective permeability of cracked porous media is derived. The fluid flow obeys Poisseuille's law along the crack and Darcy's law in the porous matrix. This solution exhibits a percolation threshold for any type of crack distribution apart from a parallel crack distribution. The physical behaviour of fluid flow through a cracked porous material is well reproduced by the proposed model. The presence of this effective permeability coupling to analytical expression of crack growth under compression enables the modelling of the permeability variation due to stress-induced cracking in a porous rock. This incorporation allows the prediction of the permeability change of a porous rock embedding an anisotropic crack distribution from any initial crack density, that is, lower, around or upper to percolation threshold. The interaction between cracks is not explicitly taken into account. The model is well applicable both to micro- and macrocracks.

Shaking table test and dynamic response prediction on an earthquake-damaged RC building

NASA Astrophysics Data System (ADS)

Xianguo, Ye; Jiaru, Qian; Kangning, Li

2004-12-01

This paper presents the results from shaking table tests of a one-tenth-scale reinforced concrete (RC) building model. The test model is a protype of a building that was seriously damaged during the 1985 Mexico earthquake. The input ground excitation used during the test was from the records obtained near the site of the prototype building during the 1985 and 1995 Mexico earthquakes. The tests showed that the damage pattern of the test model agreed well with that of the prototype building. Analytical prediction of earthquake response has been conducted for the prototype building using a sophisticated 3-D frame model. The input motion used for the dynamic analysis was the shaking table test measurements with similarity transformation. The comparison of the analytical results and the shaking table test results indicates that the response of the RC building to minor and the moderate earthquakes can be predicated well. However, there is difference between the predication and the actual response to the major earthquake.

Noise from Supersonic Coaxial Jets. Part 1; Mean Flow Predictions

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Morris, Philip J.

1997-01-01

Recent theories for supersonic jet noise have used an instability wave noise generation model to predict radiated noise. This model requires a known mean flow that has typically been described by simple analytic functions for single jet mean flows. The mean flow of supersonic coaxial jets is not described easily in terms of analytic functions. To provide these profiles at all axial locations, a numerical scheme is developed to calculate the mean flow properties of a coaxial jet. The Reynolds-averaged, compressible, parabolic boundary layer equations are solved using a mixing length turbulence model. Empirical correlations are developed to account for the effects of velocity and temperature ratios and Mach number on the shear layer spreading. Both normal velocity profile and inverted velocity profile coaxial jets are considered. The mixing length model is modified in each case to obtain reasonable results when the two stream jet merges into a single fully developed jet. The mean flow calculations show both good qualitative and quantitative agreement with measurements in single and coaxial jet flows.

Flow adjustment inside homogeneous canopies after a leading edge – An analytical approach backed by LES

DOE PAGES

Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik; ...

2017-10-06

A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less

Flow adjustment inside homogeneous canopies after a leading edge – An analytical approach backed by LES

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

Kroniger, Konstantin; Banerjee, Tirtha; De Roo, Frederik

A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptionsmore » for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height ( h), the canopy length and the adjustment length ( Lc), in additional LES. Even if the model parameters are, in general, functions of h/ Lc, it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman, which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. As a result, the model is tested against an analytical model based on a linearization approach.« less

Calibrant-Free Analyte Quantitation via a Variable Velocity Flow Cell.

PubMed

Beck, Jason G; Skuratovsky, Aleksander; Granger, Michael C; Porter, Marc D

2017-01-17

In this paper, we describe a novel method for analyte quantitation that does not rely on calibrants, internal standards, or calibration curves but, rather, leverages the relationship between disparate and predictable surface-directed analyte flux to an array of sensing addresses and a measured resultant signal. To reduce this concept to practice, we fabricated two flow cells such that the mean linear fluid velocity, U, was varied systematically over an array of electrodes positioned along the flow axis. This resulted in a predictable variation of the address-directed flux of a redox analyte, ferrocenedimethanol (FDM). The resultant limiting currents measured at a series of these electrodes, and accurately described by a convective-diffusive transport model, provided a means to calculate an "unknown" concentration without the use of calibrants, internal standards, or a calibration curve. Furthermore, the experiment and concentration calculation only takes minutes to perform. Deviation in calculated FDM concentrations from true values was minimized to less than 0.5% when empirically derived values of U were employed.

Heterogeneous postsurgical data analytics for predictive modeling of mortality risks in intensive care units.

PubMed

Yun Chen; Hui Yang

2014-01-01

The rapid advancements of biomedical instrumentation and healthcare technology have resulted in data-rich environments in hospitals. However, the meaningful information extracted from rich datasets is limited. There is a dire need to go beyond current medical practices, and develop data-driven methods and tools that will enable and help (i) the handling of big data, (ii) the extraction of data-driven knowledge, (iii) the exploitation of acquired knowledge for optimizing clinical decisions. This present study focuses on the prediction of mortality rates in Intensive Care Units (ICU) using patient-specific healthcare recordings. It is worth mentioning that postsurgical monitoring in ICU leads to massive datasets with unique properties, e.g., variable heterogeneity, patient heterogeneity, and time asyncronization. To cope with the challenges in ICU datasets, we developed the postsurgical decision support system with a series of analytical tools, including data categorization, data pre-processing, feature extraction, feature selection, and predictive modeling. Experimental results show that the proposed data-driven methodology outperforms traditional approaches and yields better results based on the evaluation of real-world ICU data from 4000 subjects in the database. This research shows great potentials for the use of data-driven analytics to improve the quality of healthcare services.

Extended Lindhard-Scharf-Schiott Theory for Ion Implantation Profiles Expressed with Pearson Function

NASA Astrophysics Data System (ADS)

Suzuki, Kunihiro

2009-04-01

Ion implantation profiles are expressed by the Pearson function with first, second, third, and fourth moment parameters of Rp, ΔRp, γ, and β. We derived an analytical model for these profile moments by solving a Lindhard-Scharf-Schiott (LSS) integration equation using perturbation approximation. This analytical model reproduces Monte Carlo data that were well calibrated to reproduce a vast experimental database. The extended LSS theory is vital for instantaneously predicting ion implantation profiles with any combination of incident ions and substrate atoms including their energy dependence.

Vibration characteristics of 1/8-scale dynamic models of the space-shuttle solid-rocket boosters

NASA Technical Reports Server (NTRS)

Leadbetter, S. A.; Stephens, W.; Sewall, J. L.; Majka, J. W.; Barret, J. R.

1976-01-01

Vibration tests and analyses of six 1/8 scale models of the space shuttle solid rocket boosters are reported. Natural vibration frequencies and mode shapes were obtained for these aluminum shell models having internal solid fuel configurations corresponding to launch, midburn (maximum dynamic pressure), and near endburn (burnout) flight conditions. Test results for longitudinal, torsional, bending, and shell vibration frequencies are compared with analytical predictions derived from thin shell theory and from finite element plate and beam theory. The lowest analytical longitudinal, torsional, bending, and shell vibration frequencies were within + or - 10 percent of experimental values. The effects of damping and asymmetric end skirts on natural vibration frequency were also considered. The analytical frequencies of an idealized full scale space shuttle solid rocket boosted structure are computed with and without internal pressure and are compared with the 1/8 scale model results.

An Experimental Investigation of Mechanical Properties in Clay Brick Masonry by Partial Replacement of Fine Aggregate with Clay Brick Waste

NASA Astrophysics Data System (ADS)

Kumavat, Hemraj Ramdas

2016-09-01

The compressive stress-strain behavior and mechanical properties of clay brick masonry and its constituents clay bricks and mortar, have been studied by several laboratory tests. Using linear regression analysis, a analytical model has been proposed for obtaining the stress-strain curves for masonry that can be used in the analysis and design procedures. The model requires only the compressive strengths of bricks and mortar as input data, which can be easily obtained experimentally. Development of analytical model from the obtained experimental results of Young's modulus and compressive strength. Simple relationships have been identified for obtaining the modulus of elasticity of bricks, mortar, and masonry from their corresponding compressive strengths. It was observed that the proposed analytical model clearly demonstrates a reasonably good prediction of the stress-strain curves when compared with the experimental curves.

Analytical theory of the hydrophobic effect of solutes in water.

PubMed

Urbic, Tomaz; Dill, Ken A

2017-09-01

We develop an analytical statistical-mechanical model for hydrophobic solvation in water. In this three-dimensional Mercedes-Benz-like model, two neighboring waters have three possible interaction states: a radial van der Waals interaction, a tetrahedral orientation-dependent hydrogen-bonding interaction, or no interaction. Nonpolar solutes are modeled as van der Waals particles of different radii. The model is sufficiently simple that we can calculate the partition function and thermal and volumetric properties of solvation versus temperature, pressure, and solute radius. Predictions are in good agreement with results of Monte Carlo simulations. And their trends agree with experiments on hydrophobic solute insertion. The theory shows that first-shell waters are more highly structured than bulk waters, because of hydrogen bonding, and that that structure melts out faster with temperature than it does in bulk waters. Because the theory is analytical, it can explore a broad range of solvation properties and anomalies of water, at minimal computational expense.

Analytical theory of the hydrophobic effect of solutes in water

NASA Astrophysics Data System (ADS)

Urbic, Tomaz; Dill, Ken A.

2017-09-01

We develop an analytical statistical-mechanical model for hydrophobic solvation in water. In this three-dimensional Mercedes-Benz-like model, two neighboring waters have three possible interaction states: a radial van der Waals interaction, a tetrahedral orientation-dependent hydrogen-bonding interaction, or no interaction. Nonpolar solutes are modeled as van der Waals particles of different radii. The model is sufficiently simple that we can calculate the partition function and thermal and volumetric properties of solvation versus temperature, pressure, and solute radius. Predictions are in good agreement with results of Monte Carlo simulations. And their trends agree with experiments on hydrophobic solute insertion. The theory shows that first-shell waters are more highly structured than bulk waters, because of hydrogen bonding, and that that structure melts out faster with temperature than it does in bulk waters. Because the theory is analytical, it can explore a broad range of solvation properties and anomalies of water, at minimal computational expense.

Generalized constitutive equations for piezo-actuated compliant mechanism

NASA Astrophysics Data System (ADS)

Cao, Junyi; Ling, Mingxiang; Inman, Daniel J.; Lin, Jin

2016-09-01

This paper formulates analytical models to describe the static displacement and force interactions between generic serial-parallel compliant mechanisms and their loads by employing the matrix method. In keeping with the familiar piezoelectric constitutive equations, the generalized constitutive equations of compliant mechanism represent the input-output displacement and force relations in the form of a generalized Hooke’s law and as analytical functions of physical parameters. Also significantly, a new model of output displacement for compliant mechanism interacting with piezo-stacks and elastic loads is deduced based on the generalized constitutive equations. Some original findings differing from the well-known constitutive performance of piezo-stacks are also given. The feasibility of the proposed models is confirmed by finite element analysis and by experiments under various elastic loads. The analytical models can be an insightful tool for predicting and optimizing the performance of a wide class of compliant mechanisms that simultaneously consider the influence of loads and piezo-stacks.

Theoretical and experimental evaluation of the effects of an argon gas mixture on the pressure drop through adult tracheobronchial airway replicas.

PubMed

Litwin, Patrick D; Reis Dib, Anna Luisa; Chen, John; Noga, Michelle; Finlay, Warren H; Martin, Andrew R

2017-06-14

Argon has the potential to be a novel inhaled therapeutic agent, owing to the neuroprotective and organoprotective properties demonstrated in preclinical studies. Before human trials are performed, an understanding of varying gas properties on airway resistance during inhalation is essential. This study predicts the effect of an 80% argon/20% oxygen gas mixture on the pressure drop through conducting airways, and by extension the airway resistance, and then verifies these predictions experimentally using 3-D printed adult tracheobronchial airway replicas. The predicted pressure drop was calculated using established analytical models of airway resistance, incorporating the change in viscosity and density of the 80% argon/20% oxygen mixture versus that of air. Predicted pressure drop for the argon mixture increased by approximately 29% compared to that for air. The experimental results were consistent with this prediction for inspiratory flows ranging from 15 to 90slpm. These results indicate that established analytical models may be used to predict increases in conducting airway resistance for argon/oxygen mixtures, compared with air. Such predictions are valuable in predicting average patient response to breathing argon/oxygen mixtures, and in selecting or designing delivery systems for use in administration of argon/oxygen mixtures to critically ill or injured patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Empirical Approach for Determining Axial Strength of Circular Concrete Filled Steel Tubular Columns

NASA Astrophysics Data System (ADS)

Jayalekshmi, S.; Jegadesh, J. S. Sankar; Goel, Abhishek

2018-06-01

The concrete filled steel tubular (CFST) columns are highly regarded in recent years as an interesting option in the construction field by designers and structural engineers, due to their exquisite structural performance, with enhanced load bearing capacity and energy absorption capacity. This study presents a new approach to simulate the capacity of circular CFST columns under axial loading condition, using a large database of experimental results by applying artificial neural network (ANN). A well trained network is established and is used to simulate the axial capacity of CFST columns. The validation and testing of the ANN is carried out. The current study is focused on proposing a simplified equation that can predict the ultimate strength of the axially loaded columns with high level of accuracy. The predicted results are compared with five existing analytical models which estimate the strength of the CFST column. The ANN-based equation has good prediction with experimental data, when compared with the analytical models.

Consideration of some factors affecting low-frequency fuselage noise transmission for propeller aircraft

NASA Technical Reports Server (NTRS)

Mixson, J. S.; Roussos, L. A.

1986-01-01

Possible reasons for disagreement between measured and predicted trends of sidewall noise transmission at low frequency are investigated using simplified analysis methods. An analytical model combining incident plane acoustic waves with an infinite flat panel is used to study the effects of sound incidence angle, plate structural properties, frequency, absorption, and the difference between noise reduction and transmission loss. Analysis shows that these factors have significant effects on noise transmission but they do not account for the differences between measured and predicted trends at low frequencies. An analytical model combining an infinite flat plate with a normally incident acoustic wave having exponentially decaying magnitude along one coordinate is used to study the effect of a localized source distribution such as is associated with propeller noise. Results show that the localization brings the predicted low-frequency trend of noise transmission into better agreement with measured propeller results. This effect is independent of low-frequency stiffness effects that have been previously reported to be associated with boundary conditions.

Empirical Approach for Determining Axial Strength of Circular Concrete Filled Steel Tubular Columns

NASA Astrophysics Data System (ADS)

Jayalekshmi, S.; Jegadesh, J. S. Sankar; Goel, Abhishek

2018-03-01

The concrete filled steel tubular (CFST) columns are highly regarded in recent years as an interesting option in the construction field by designers and structural engineers, due to their exquisite structural performance, with enhanced load bearing capacity and energy absorption capacity. This study presents a new approach to simulate the capacity of circular CFST columns under axial loading condition, using a large database of experimental results by applying artificial neural network (ANN). A well trained network is established and is used to simulate the axial capacity of CFST columns. The validation and testing of the ANN is carried out. The current study is focused on proposing a simplified equation that can predict the ultimate strength of the axially loaded columns with high level of accuracy. The predicted results are compared with five existing analytical models which estimate the strength of the CFST column. The ANN-based equation has good prediction with experimental data, when compared with the analytical models.

Development and application of a three dimensional numerical model for predicting pollutant and sediment transport using an Eulerian-Lagrangian marker particle technique

NASA Technical Reports Server (NTRS)

Pavish, D. L.; Spaulding, M. L.

1977-01-01

A computer coded Lagrangian marker particle in Eulerian finite difference cell solution to the three dimensional incompressible mass transport equation, Water Advective Particle in Cell Technique, WAPIC, was developed, verified against analytic solutions, and subsequently applied in the prediction of long term transport of a suspended sediment cloud resulting from an instantaneous dredge spoil release. Numerical results from WAPIC were verified against analytic solutions to the three dimensional incompressible mass transport equation for turbulent diffusion and advection of Gaussian dye releases in unbounded uniform and uniformly sheared uni-directional flow, and for steady-uniform plug channel flow. WAPIC was utilized to simulate an analytic solution for non-equilibrium sediment dropout from an initially vertically uniform particle distribution in one dimensional turbulent channel flow.

Survey of NASA research on crash dynamics

NASA Technical Reports Server (NTRS)

Thomson, R. G.; Carden, H. D.; Hayduk, R. J.

1984-01-01

Ten years of structural crash dynamics research activities conducted on general aviation aircraft by the National Aeronautics and Space Administration (NASA) are described. Thirty-two full-scale crash tests were performed at Langley Research Center, and pertinent data on airframe and seat behavior were obtained. Concurrent with the experimental program, analytical methods were developed to help predict structural behavior during impact. The effects of flight parameters at impact on cabin deceleration pulses at the seat/occupant interface, experimental and analytical correlation of data on load-limiting subfloor and seat configurations, airplane section test results for computer modeling validation, and data from emergency-locator-transmitter (ELT) investigations to determine probable cause of false alarms and nonactivations are assessed. Computer programs which provide designers with analytical methods for predicting accelerations, velocities, and displacements of collapsing structures are also discussed.

Evaluation of Lightning Induced Effects in a Graphite Composite Fairing Structure. Parts 1 and 2

NASA Technical Reports Server (NTRS)

Trout, Dawn H.; Stanley, James E.; Wahid, Parveen F.

2011-01-01

Defining the electromagnetic environment inside a graphite composite fairing due to lightning is of interest to spacecraft developers. This paper is the first in a two part series and studies the shielding effectiveness of a graphite composite model fairing using derived equivalent properties. A frequency domain Method of Moments (MoM) model is developed and comparisons are made with shielding test results obtained using a vehicle-like composite fairing. The comparison results show that the analytical models can adequately predict the test results. Both measured and model data indicate that graphite composite fairings provide significant attenuation to magnetic fields as frequency increases. Diffusion effects are also discussed. Part 2 examines the time domain based effects through the development of a loop based induced field testing and a Transmission-Line-Matrix (TLM) model is developed in the time domain to study how the composite fairing affects lightning induced magnetic fields. Comparisons are made with shielding test results obtained using a vehicle-like composite fairing in the time domain. The comparison results show that the analytical models can adequately predict the test and industry results.

Star formation in Herschel's Monsters versus semi-analytic models

NASA Astrophysics Data System (ADS)

Gruppioni, C.; Calura, F.; Pozzi, F.; Delvecchio, I.; Berta, S.; De Lucia, G.; Fontanot, F.; Franceschini, A.; Marchetti, L.; Menci, N.; Monaco, P.; Vaccari, M.

2015-08-01

We present a direct comparison between the observed star formation rate functions (SFRFs) and the state-of-the-art predictions of semi-analytic models (SAMs) of galaxy formation and evolution. We use the PACS Evolutionary Probe Survey and Herschel Multi-tiered Extragalactic Survey data sets in the COSMOS and GOODS-South fields, combined with broad-band photometry from UV to sub-mm, to obtain total (IR+UV) instantaneous star formation rates (SFRs) for individual Herschel galaxies up to z ˜ 4, subtracted of possible active galactic nucleus (AGN) contamination. The comparison with model predictions shows that SAMs broadly reproduce the observed SFRFs up to z ˜ 2, when the observational errors on the SFR are taken into account. However, all the models seem to underpredict the bright end of the SFRF at z ≳ 2. The cause of this underprediction could lie in an improper modelling of several model ingredients, like too strong (AGN or stellar) feedback in the brighter objects or too low fallback of gas, caused by weak feedback and outflows at earlier epochs.

An analytical model of the mechanical properties of bulk coal under confined stress

USGS Publications Warehouse

Wang, G.X.; Wang, Z.T.; Rudolph, V.; Massarotto, P.; Finley, R.J.

2007-01-01

This paper presents the development of an analytical model which can be used to relate the structural parameters of coal to its mechanical properties such as elastic modulus and Poisson's ratio under a confined stress condition. This model is developed primarily to support process modeling of coalbed methane (CBM) or CO2-enhanced CBM (ECBM) recovery from coal seam. It applied an innovative approach by which stresses acting on and strains occurring in coal are successively combined in rectangular coordinates, leading to the aggregated mechanical constants. These mechanical properties represent important information for improving CBM/ECBM simulations and incorporating within these considerations of directional permeability. The model, consisting of constitutive equations which implement a mechanically consistent stress-strains correlation, can be used as a generalized tool to study the mechanical and fluid behaviors of coal composites. An example using the model to predict the stress-strain correlation of coal under triaxial confined stress by accounting for the elastic and brittle (non-elastic) deformations is discussed. The result shows a good agreement between the prediction and the experimental measurement. ?? 2007 Elsevier Ltd. All rights reserved.

Prediction of the interior noise levels of high-speed propeller-driven aircraft

NASA Technical Reports Server (NTRS)

Rennison, D. C.; Wilby, J. F.; Wilby, E. G.

1980-01-01

The theoretical basis for an analytical model developed to predict the interior noise levels of high-speed propeller-driven airplanes is presented. Particular emphasis is given to modeling the transmission of discrete tones through a fuselage element into a cavity, estimates for the mean and standard deviation of the acoustic power flow, the coupling between a non-homogeneous excitation and the fuselage vibration response, and the prediction of maximum interior noise levels. The model allows for convenient examination of the various roles of the excitation and fuselage structural characteristics on the fuselage vibration response and the interior noise levels, as is required for the design of model or prototype noise control validation tests.

A Numerical-Analytical Approach to Modeling the Axial Rotation of the Earth

NASA Astrophysics Data System (ADS)

Markov, Yu. G.; Perepelkin, V. V.; Rykhlova, L. V.; Filippova, A. S.

2018-04-01

A model for the non-uniform axial rotation of the Earth is studied using a celestial-mechanical approach and numerical simulations. The application of an approximate model containing a small number of parameters to predict variations of the axial rotation velocity of the Earth over short time intervals is justified. This approximate model is obtained by averaging variable parameters that are subject to small variations due to non-stationarity of the perturbing factors. The model is verified and compared with predictions over a long time interval published by the International Earth Rotation and Reference Systems Service (IERS).

An enhanced beam model for constrained layer damping and a parameter study of damping contribution

NASA Astrophysics Data System (ADS)

Xie, Zhengchao; Shepard, W. Steve, Jr.

2009-01-01

An enhanced analytical model is presented based on an extension of previous models for constrained layer damping (CLD) in beam-like structures. Most existing CLD models are based on the assumption that shear deformation in the core layer is the only source of damping in the structure. However, previous research has shown that other types of deformation in the core layer, such as deformations from longitudinal extension and transverse compression, can also be important. In the enhanced analytical model developed here, shear, extension, and compression deformations are all included. This model can be used to predict the natural frequencies and modal loss factors. The numerical study shows that compared to other models, this enhanced model is accurate in predicting the dynamic characteristics. As a result, the model can be accepted as a general computation model. With all three types of damping included and the formulation used here, it is possible to study the impact of the structure's geometry and boundary conditions on the relative contribution of each type of damping. To that end, the relative contributions in the frequency domain for a few sample cases are presented.

Big Data and Predictive Analytics: Applications in the Care of Children.

PubMed

Suresh, Srinivasan

2016-04-01

Emerging changes in the United States' healthcare delivery model have led to renewed interest in data-driven methods for managing quality of care. Analytics (Data plus Information) plays a key role in predictive risk assessment, clinical decision support, and various patient throughput measures. This article reviews the application of a pediatric risk score, which is integrated into our hospital's electronic medical record, and provides an early warning sign for clinical deterioration. Dashboards that are a part of disease management systems, are a vital tool in peer benchmarking, and can help in reducing unnecessary variations in care. Copyright © 2016 Elsevier Inc. All rights reserved.

The Lessons Oscar Taught Us: Data Science and Media & Entertainment.

PubMed

Gold, Michael; McClarren, Ryan; Gaughan, Conor

2013-06-01

Farsite Group, a data science firm based in Columbus, Ohio, launched a highly visible campaign in early 2013 to use predictive analytics to forecast the winners of the 85th Annual Academy Awards. The initiative was fun and exciting for the millions of Oscar viewers, but it also illustrated how data science could be further deployed in the media and entertainment industries. This article explores the current and potential use cases for big data and predictive analytics in those industries. It further discusses how the Farsite Forecast was built, as well as how the model was iterated, how the projections performed, and what lessons were learned in the process.

The effect of inclined soil layers on surface vibration from underground railways using a semi-analytical approach

NASA Astrophysics Data System (ADS)

Jones, S.; Hunt, H.

2009-08-01

Ground vibration due to underground railways is a significant source of disturbance for people living or working near the subways. The numerical models used to predict vibration levels have inherent uncertainty which must be understood to give confidence in the predictions. A semi-analytical approach is developed herein to investigate the effect of soil layering on the surface vibration of a halfspace where both soil properties and layer inclination angles are varied. The study suggests that both material properties and inclination angle of the layers have significant effect (± 10dB) on the surface vibration response.

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Hyperspectral imaging using near infrared spectroscopy to monitor coat thickness uniformity in the manufacture of a transdermal drug delivery system.

PubMed

Pavurala, Naresh; Xu, Xiaoming; Krishnaiah, Yellela S R

2017-05-15

Hyperspectral imaging using near infrared spectroscopy (NIRS) integrates spectroscopy and conventional imaging to obtain both spectral and spatial information of materials. The non-invasive and rapid nature of hyperspectral imaging using NIRS makes it a valuable process analytical technology (PAT) tool for in-process monitoring and control of the manufacturing process for transdermal drug delivery systems (TDS). The focus of this investigation was to develop and validate the use of Near Infra-red (NIR) hyperspectral imaging to monitor coat thickness uniformity, a critical quality attribute (CQA) for TDS. Chemometric analysis was used to process the hyperspectral image and a partial least square (PLS) model was developed to predict the coat thickness of the TDS. The goodness of model fit and prediction were 0.9933 and 0.9933, respectively, indicating an excellent fit to the training data and also good predictability. The % Prediction Error (%PE) for internal and external validation samples was less than 5% confirming the accuracy of the PLS model developed in the present study. The feasibility of the hyperspectral imaging as a real-time process analytical tool for continuous processing was also investigated. When the PLS model was applied to detect deliberate variation in coating thickness, it was able to predict both the small and large variations as well as identify coating defects such as non-uniform regions and presence of air bubbles. Published by Elsevier B.V.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Numerical modeling and analytical modeling of cryogenic carbon capture in a de-sublimating heat exchanger

NASA Astrophysics Data System (ADS)

Yu, Zhitao; Miller, Franklin; Pfotenhauer, John M.

2017-12-01

Both a numerical and analytical model of the heat and mass transfer processes in a CO2, N2 mixture gas de-sublimating cross-flow finned duct heat exchanger system is developed to predict the heat transferred from a mixture gas to liquid nitrogen and the de-sublimating rate of CO2 in the mixture gas. The mixture gas outlet temperature, liquid nitrogen outlet temperature, CO2 mole fraction, temperature distribution and de-sublimating rate of CO2 through the whole heat exchanger was computed using both the numerical and analytic model. The numerical model is built using EES [1] (engineering equation solver). According to the simulation, a cross-flow finned duct heat exchanger can be designed and fabricated to validate the models. The performance of the heat exchanger is evaluated as functions of dimensionless variables, such as the ratio of the mass flow rate of liquid nitrogen to the mass flow rate of inlet flue gas.

Predicting the velocity and azimuth of fragments generated by the range destruction or random failure of rocket casings and tankage

NASA Technical Reports Server (NTRS)

Eck, Marshall; Mukunda, Meera

1988-01-01

A calculational method is described which provides a powerful tool for predicting solid rocket motor (SRM) casing and liquid rocket tankage fragmentation response. The approach properly partitions the available impulse to each major system-mass component. It uses the Pisces code developed by Physics International to couple the forces generated by an Eulerian-modeled gas flow field to a Lagrangian-modeled fuel and casing system. The details of the predictive analytical modeling process and the development of normalized relations for momentum partition as a function of SRM burn time and initial geometry are discussed. Methods for applying similar modeling techniques to liquid-tankage-overpressure failures are also discussed. Good agreement between predictions and observations are obtained for five specific events.

MetaKTSP: a meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis.

PubMed

Kim, SungHwan; Lin, Chien-Wei; Tseng, George C

2016-07-01

Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational potential. The top scoring pair (TSP) algorithm is an example that applies a simple rank-based algorithm to identify rank-altered gene pairs for classifier construction. Although many classification methods perform well in cross-validation of single expression profile, the performance usually greatly reduces in cross-study validation (i.e. the prediction model is established in the training study and applied to an independent test study) for all machine learning methods, including TSP. The failure of cross-study validation has largely diminished the potential translational and clinical values of the models. The purpose of this article is to develop a meta-analytic top scoring pair (MetaKTSP) framework that combines multiple transcriptomic studies and generates a robust prediction model applicable to independent test studies. We proposed two frameworks, by averaging TSP scores or by combining P-values from individual studies, to select the top gene pairs for model construction. We applied the proposed methods in simulated data sets and three large-scale real applications in breast cancer, idiopathic pulmonary fibrosis and pan-cancer methylation. The result showed superior performance of cross-study validation accuracy and biomarker selection for the new meta-analytic framework. In conclusion, combining multiple omics data sets in the public domain increases robustness and accuracy of the classification model that will ultimately improve disease understanding and clinical treatment decisions to benefit patients. An R package MetaKTSP is available online. (http://tsenglab.biostat.pitt.edu/software.htm). ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Orion Parachute Riser Cutter Development

NASA Technical Reports Server (NTRS)

Oguz, Sirri; Salazar, Frank

2011-01-01

This paper presents the tests and analytical approach used on the development of a steel riser cutter for the CEV Parachute Assembly System (CPAS) used on the Orion crew module. Figure 1 shows the riser cutter and the steel riser bundle which consists of six individual cables. Due to the highly compressed schedule, initial unavailability of the riser material and the Orion Forward Bay mechanical constraints, JSC primarily relied on a combination of internal ballistics analysis and LS-DYNA simulation for this project. Various one dimensional internal ballistics codes that use standard equation of state and conservation of energy have commonly used in the development of CAD devices for initial first order estimates and as an enhancement to the test program. While these codes are very accurate for propellant performance prediction, they usually lack a fully defined kinematic model for dynamic predictions. A simple piston device can easily and accurately be modeled using an equation of motion. However, the accuracy of analytical models is greatly reduced on more complicated devices with complex external loads, nonlinear trajectories or unique unlocking features. A 3D finite element model of CAD device with all critical features included can vastly improve the analytical ballistic predictions when it is used as a supplement to the ballistic code. During this project, LS-DYNA structural 3D model was used to predict the riser resisting load that was needed for the ballistic code. A Lagrangian model with eroding elements shown in Figure 2 was used for the blade, steel riser and the anvil. The riser material failure strain was fine tuned by matching the dent depth on the anvil with the actual test data. LS-DYNA model was also utilized to optimize the blade tip design for the most efficient cut. In parallel, the propellant type and the amount were determined by using CADPROG internal ballistics code. Initial test results showed a good match with LS-DYNA and CADPROG simulations. Final paper will present a detailed roadmap from initial ballistic modeling and LS-DYNA simulation to the performance testing. Blade shape optimization study will also be presented.

10 CFR 431.17 - Determination of efficiency.

Code of Federal Regulations, 2014 CFR

2014-01-01

... characteristics of that basic model, and (ii) Based on engineering or statistical analysis, computer simulation or... simulation or modeling, and other analytic evaluation of performance data on which the AEDM is based... applied. (iii) If requested by the Department, the manufacturer shall conduct simulations to predict the...

10 CFR 431.17 - Determination of efficiency.

Code of Federal Regulations, 2012 CFR

2012-01-01

... characteristics of that basic model, and (ii) Based on engineering or statistical analysis, computer simulation or... simulation or modeling, and other analytic evaluation of performance data on which the AEDM is based... applied. (iii) If requested by the Department, the manufacturer shall conduct simulations to predict the...

An analytical study of aircraft lateral-directional handling qualities using pilot models

NASA Technical Reports Server (NTRS)

Adams, J. J.; Moore, F. L.

1976-01-01

A procedure for predicting lateral-directional pilot ratings on the basis of the characteristics of the pilot model and the closed-loop system characteristics is demonstrated. A correlation is shown to exist between experimentally obtained pilot ratings and the computed pilot ratings.

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Test and Analysis Correlation for a Y-Joint Specimen for a Composite Cryotank

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Sleight, David W.; Grenoble, Ray

2015-01-01

The Composite Cryotank Technology Demonstration (CCTD) project under NASA's Game Changing Development Program (GCDP) developed space technologies using advanced composite materials. Under CCTD, NASA funded the Boeing Company to design and test a number of element-level joint specimens as a precursor to a 2.4-m diameter composite cryotank. Preliminary analyses indicated that the y-joint in the cryotank had low margins of safety; hence the y-joint was considered to be a critical design region. The y-joint design includes a softening strip wedge to reduce localized shear stresses at the skirt/dome interface. In this paper, NASA-developed analytical models will be correlated with the experimental results of a series of positive-peel y-joint specimens from Boeing tests. Initial analytical models over-predicted the experimental strain gage readings in the far-field region by approximately 10%. The over-prediction was attributed to uncertainty in the elastic properties of the laminate and a mismatch between the thermal expansion of the strain gages and the laminate. The elastic properties of the analytical model were adjusted to account for the strain gage differences. The experimental strain gages also indicated a large non-linear effect in the softening strip region that was not predicted by the analytical model. This non-linear effect was attributed to delamination initiating in the softening strip region at below 20% of the failure load for the specimen. Because the specimen was contained in a thermally insulated box during cryogenic testing to failure, delamination initiation and progression was not visualized during the test. Several possible failure initiation locations were investigated, and a most likely failure scenario was determined that correlated well with the experimental data. The most likely failure scenario corresponded to damage initiating in the softening strip and delamination extending to the grips at final failure.

The Theory and Practice of Estimating the Accuracy of Dynamic Flight-Determined Coefficients

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1981-01-01

Means of assessing the accuracy of maximum likelihood parameter estimates obtained from dynamic flight data are discussed. The most commonly used analytical predictors of accuracy are derived and compared from both statistical and simplified geometrics standpoints. The accuracy predictions are evaluated with real and simulated data, with an emphasis on practical considerations, such as modeling error. Improved computations of the Cramer-Rao bound to correct large discrepancies due to colored noise and modeling error are presented. The corrected Cramer-Rao bound is shown to be the best available analytical predictor of accuracy, and several practical examples of the use of the Cramer-Rao bound are given. Engineering judgement, aided by such analytical tools, is the final arbiter of accuracy estimation.

An analytical model of prominence dynamics

NASA Astrophysics Data System (ADS)

Routh, Swati; Saha, Snehanshu; Bhat, Atul; Sundar, M. N.

2018-01-01

Solar prominences are magnetic structures incarcerating cool and dense gas in an otherwise hot solar corona. Prominences can be categorized as quiescent and active. Their origin and the presence of cool gas (∼104 K) within the hot (∼106K) solar corona remains poorly understood. The structure and dynamics of solar prominences was investigated in a large number of observational and theoretical (both analytical and numerical) studies. In this paper, an analytic model of quiescent solar prominence is developed and used to demonstrate that the prominence velocity increases exponentially, which means that some gas falls downward towards the solar surface, and that Alfvén waves are naturally present in the solar prominences. These theoretical predictions are consistent with the current observational data of solar quiescent prominences.

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

PubMed

Kassemi, Mohammad; Thompson, David

2016-09-01

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

Amplitudes of doping striations: comparison of numerical calculations and analytical approaches

NASA Astrophysics Data System (ADS)

Jung, T.; Müller, G.

1997-02-01

Transient, axisymmetric numerical calculations of the heat and species transport including convection were performed for a simplified vertical gradient freeze (Bridgman) process with bottom seeding for GaAs. Periodical oscillations were superimposed onto the transient heater temperature profile. The amplitudes of the resulting oscillations of the growth rate and the dopant concentration (striations) in the growing crystals are compared with the predictions of analytical models.

Evaluation of strength and failure of brittle rock containing initial cracks under lithospheric conditions

NASA Astrophysics Data System (ADS)

Li, Xiaozhao; Qi, Chengzhi; Shao, Zhushan; Ma, Chao

2018-02-01

Natural brittle rock contains numerous randomly distributed microcracks. Crack initiation, growth, and coalescence play a predominant role in evaluation for the strength and failure of brittle rocks. A new analytical method is proposed to predict the strength and failure of brittle rocks containing initial microcracks. The formulation of this method is based on an improved wing crack model and a suggested micro-macro relation. In this improved wing crack model, the parameter of crack angle is especially introduced as a variable, and the analytical stress-crack relation considering crack angle effect is obtained. Coupling the proposed stress-crack relation and the suggested micro-macro relation describing the relation between crack growth and axial strain, the stress-strain constitutive relation is obtained to predict the rock strength and failure. Considering different initial microcrack sizes, friction coefficients and confining pressures, effects of crack angle on tensile wedge force acting on initial crack interface are studied, and effects of crack angle on stress-strain constitutive relation of rocks are also analyzed. The strength and crack initiation stress under different crack angles are discussed, and the value of most disadvantaged angle triggering crack initiation and rock failure is founded. The analytical results are similar to the published study results. Rationality of this proposed analytical method is verified.

A simple analytical model of coupled single flow channel over porous electrode in vanadium redox flow battery with serpentine flow channel

NASA Astrophysics Data System (ADS)

Ke, Xinyou; Alexander, J. Iwan D.; Prahl, Joseph M.; Savinell, Robert F.

2015-08-01

A simple analytical model of a layered system comprised of a single passage of a serpentine flow channel and a parallel underlying porous electrode (or porous layer) is proposed. This analytical model is derived from Navier-Stokes motion in the flow channel and Darcy-Brinkman model in the porous layer. The continuities of flow velocity and normal stress are applied at the interface between the flow channel and the porous layer. The effects of the inlet volumetric flow rate, thickness of the flow channel and thickness of a typical carbon fiber paper porous layer on the volumetric flow rate within this porous layer are studied. The maximum current density based on the electrolyte volumetric flow rate is predicted, and found to be consistent with reported numerical simulation. It is found that, for a mean inlet flow velocity of 33.3 cm s-1, the analytical maximum current density is estimated to be 377 mA cm-2, which compares favorably with experimental result reported by others of ∼400 mA cm-2.

Molecular modeling of polymer composite interactions with analytes in electronic nose sensors for environmental monitoring in International Space Station

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K.

2002-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL Electronic Nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings (with no hydrogens). The Dreiding 2.21 force field is used for the polymer and solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4- vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic (ammonia) and organic (methanol, toluene, hydrazine) compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites.

Molecular modeling of polymer composite-analyte interactions in electronic nose sensors

NASA Technical Reports Server (NTRS)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K. S.

2003-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.

Flight motor set 360L001 (STS-26R). (Reconstructed dynamic loads analysis)

NASA Technical Reports Server (NTRS)

Call, V. B.

1989-01-01

A transient analysis was performed to correlate the predicted versus measured behavior of the Redesigned Solid Rocket Booster (RSRB) during Flight 360L001 (STS-26R) liftoff. Approximately 9 accelerometers, 152 strain gages, and 104 girth gages were bonded to the motors during this event. Prior to Flight 360L001, a finite element model of the RSRB was analyzed to predict the accelerations, strains, and displacements measured by this developmental flight instrumentation (DFI) within an order of magnitude. Subsequently, an analysis has been performed which uses actual Flight 360L001 liftoff loading conditions, and makes more precise predictions for the RSRB structural behavior. Essential information describing the analytical model, analytical techniques used, correlation of the predicted versus measured RSRB behavior, and conclusions, are presented. A detailed model of the RSRB was developed and correlated for use in analyzing the motor behavior during liftoff loading conditions. This finite element model, referred to as the RSRB global model, uses super-element techniques to model all components of the RSRB. The objective of the RSRB global model is to accurately predict deflections and gap openings in the field joints to an accuracy of approximately 0.001 inch. The model of the field joint component was correlated to Referee and Joint Environment Simulation (JES) tests. The accuracy of the assembled RSRB global model was validated by correlation to static-fire tests such DM-8, DM-9, QM-7, and QM-8. This validated RSRB global model was used to predict RSRB structural behavior and joint gap opening during Flight 360L001 liftoff. The results of a transient analysis of the RSRB global model with imposed liftoff loading conditions are presented. Rockwell used many gage measurements to reconstruct the load parameters which were imposed on the RSRB during the Flight 360L001 liftoff. Each load parameter, and its application, is described. Also presented are conclusions and recommendations based on the analysis of this load case and the resulting correlation between predicted and measured RSRB structural behavior.

Integrated Modeling for Road Condition Prediction

DOT National Transportation Integrated Search

2017-12-31

Transportation Systems Management and Operations (TSMO) is at a critical point in its development due to an explosion in data availability and analytics. Intelligent transportation systems (ITS) gathering data about weather and traffic conditions cou...

Fuel Spray Diagnostics

NASA Technical Reports Server (NTRS)

Humenik, F. M.; Bosque, M. A.

1983-01-01

Fundamental experimental data base for turbulent flow mixing models is provided and better prediction of the more complex turbulent chemical reacting flows. Analytical application to combustor design is provided and a better fundamental understanding of the combustion process.

Research in structures, structural dynamics and materials, 1989

NASA Technical Reports Server (NTRS)

Hunter, William F. (Compiler); Noor, Ahmed K. (Compiler)

1989-01-01

Topics addressed include: composite plates; buckling predictions; missile launch tube modeling; structural/control systems design; optimization of nonlinear R/C frames; error analysis for semi-analytic displacement; crack acoustic emission; and structural dynamics.

Evaporative segregation in 80% Ni-20% Cr and 60% Fe-40% Ni alloys

NASA Technical Reports Server (NTRS)

Gupta, K. P.; Mukherjee, J. L.; Li, C. H.

1974-01-01

An analytical approach is outlined to calculate the evaporative segregation behavior in metallic alloys. The theoretical predictions are based on a 'normal' evaporation model and have been examined for Fe-Ni and Ni-Cr alloys. A fairly good agreement has been found between the predicted values and the experimental results found in the literature.

Hemolytic potential of hydrodynamic cavitation.

PubMed

Chambers, S D; Bartlett, R H; Ceccio, S L

2000-08-01

The purpose of this study was to determine the hemolytic potentials of discrete bubble cavitation and attached cavitation. To generate controlled cavitation events, a venturigeometry hydrodynamic device, called a Cavitation Susceptibility Meter (CSM), was constructed. A comparison between the hemolytic potential of discrete bubble cavitation and attached cavitation was investigated with a single-pass flow apparatus and a recirculating flow apparatus, both utilizing the CSM. An analytical model, based on spherical bubble dynamics, was developed for predicting the hemolysis caused by discrete bubble cavitation. Experimentally, discrete bubble cavitation did not correlate with a measurable increase in plasma-free hemoglobin (PFHb), as predicted by the analytical model. However, attached cavitation did result in significant PFHb generation. The rate of PFHb generation scaled inversely with the Cavitation number at a constant flow rate, suggesting that the size of the attached cavity was the dominant hemolytic factor.

Chilldown study of the single stage inducer test rig

NASA Technical Reports Server (NTRS)

Kimura, L. A.

1972-01-01

Of the six chilldown tests, data from only one could be used for evaluation. During the rest of the chilldown tests, there was leakage hydrogen flow into the pump cavity prior to the initiation of the chilldown test. In all of the tests the hydrogen condition into the pump was probably 100% vapor. The data from this one test, therefore, can be used to compare only the single phase fluid correlation in the analytical pump chilldown model. In general, the actual pump chilled down much faster than predicted by the analytical pump model. There were insufficient data from the test to measure the pump flow rate and pump inlet fluid condition; therefore, these parameters were extrapolated based on related data which were available. However, even with the highest probable flow rate, the pump chilled faster than predicted.

Field Telemetry of Blade-rotor Coupled Torsional Vibration at Matuura Power Station Number 1 Unit

NASA Technical Reports Server (NTRS)

Isii, Kuniyoshi; Murakami, Hideaki; Otawara, Yasuhiko; Okabe, Akira

1991-01-01

The quasi-modal reduction technique and finite element model (FEM) were used to construct an analytical model for the blade-rotor coupled torsional vibration of a steam turbine generator of the Matuura Power Station. A single rotor test was executed in order to evaluate umbrella vibration characteristics. Based on the single rotor test results and the quasi-modal procedure, the total rotor system was analyzed to predict coupled torsional frequencies. Finally, field measurement of the vibration of the last stage buckets was made, which confirmed that the double synchronous resonance was 124.2 Hz, meaning that the machine can be safely operated. The measured eigen values are very close to the predicted value. The single rotor test and this analytical procedure thus proved to be a valid technique to estimate coupled torsional vibration.

Prediction of unsaturated flow and water backfill during infiltration in layered soils

NASA Astrophysics Data System (ADS)

Cui, Guotao; Zhu, Jianting

2018-02-01

We develop a new analytical infiltration model to determine water flow dynamics around layer interfaces during infiltration process in layered soils. The model mainly involves the analytical solutions to quadratic equations to determine the flux rates around the interfaces. Active water content profile behind the wetting front is developed based on the solution of steady state flow to dynamically update active parameters in sharp wetting front infiltration equations and to predict unsaturated flow in coarse layers before the front reaches an impeding fine layer. The effect of water backfill to saturate the coarse layers after the wetting front encounters the impeding fine layer is analytically expressed based on the active water content profiles. Comparison to the numerical solutions of the Richards equation shows that the new model can well capture water dynamics in relation to the arrangement of soil layers. The steady state active water content profile can be used to predict the saturation state of all layers when the wetting front first passes through these layers during the unsteady infiltration process. Water backfill effect may occur when the unsaturated wetting front encounters a fine layer underlying a coarse layer. Sensitivity analysis shows that saturated hydraulic conductivity is the parameter dictating the occurrence of unsaturated flow and water backfill and can be used to represent the coarseness of soil layers. Water backfill effect occurs in coarse layers between upper and lower fine layers when the lower layer is not significantly coarser than the upper layer.

Round-robin pretest analyses of a 1:6-scale reinforced concrete containment model subject to static internal pressurization

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

Clauss, D.B.

Analyses of a 1:6-scale reinforced concrete containment model that will be tested to failure at Sandia National Laboratories in the spring of 1987 were conducted by the following organizations in the United States and Europe: Sandia National Laboratories (USA), Argonne National Laboratory (USA), Electric Power Research Institute (USA), Commissariat a L'Energie Atomique (France), HM Nuclear Installations Inspectorate (UK), Comitato Nazionale per la ricerca e per lo sviluppo dell'Energia Nucleare e delle Energie Alternative (Italy), UK Atomic Energy Authority, Safety and Reliability Directorate (UK), Gesellschaft fuer Reaktorsicherheit (FRG), Brookhaven National Laboratory (USA), and Central Electricity Generating Board (UK). Each organization wasmore » supplied with a standard information package, which included construction drawings and actual material properties for most of the materials used in the model. Each organization worked independently using their own analytical methods. This report includes descriptions of the various analytical approaches and pretest predictions submitted by each organization. Significant milestones that occur with increasing pressure, such as damage to the concrete (cracking and crushing) and yielding of the steel components, and the failure pressure (capacity) and failure mechanism are described. Analytical predictions for pressure histories of strain in the liner and rebar and displacements are compared at locations where experimental results will be available after the test. Thus, these predictions can be compared to one another and to experimental results after the test.« less

Evolution of the social network of scientific collaborations

NASA Astrophysics Data System (ADS)

Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T.

2002-08-01

The co-authorship network of scientists represents a prototype of complex evolving networks. In addition, it offers one of the most extensive database to date on social networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an 8-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. Three complementary approaches allow us to obtain a detailed characterization. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. In some limits the model can be solved analytically, predicting a two-regime scaling in agreement with the measurements. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically. The combined numerical and analytical results underline the important role internal links play in determining the observed scaling behavior and network topology. The results and methodologies developed in the context of the co-authorship network could be useful for a systematic study of other complex evolving networks as well, such as the world wide web, Internet, or other social networks.

Tachyon logamediate inflation on the brane

NASA Astrophysics Data System (ADS)

Kamali, Vahid; Nik, Elahe Navaee

2017-07-01

According to a Barrow solution for the scale factor of the universe, the main properties of the tachyon inflation model in the framework of the RSII braneworld are studied. Within this framework the basic slow-roll parameters are calculated analytically. We compare this inflationary scenario to the latest observational data. The predicted spectral index and the tensor-to-scalar fluctuation ratio are in excellent agreement with those of Planck 2015. The current predictions are consistent with those of viable inflationary models.

Analytical Performance Modeling and Validation of Intel’s Xeon Phi Architecture

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

Chunduri, Sudheer; Balaprakash, Prasanna; Morozov, Vitali

Modeling the performance of scientific applications on emerging hardware plays a central role in achieving extreme-scale computing goals. Analytical models that capture the interaction between applications and hardware characteristics are attractive because even a reasonably accurate model can be useful for performance tuning before the hardware is made available. In this paper, we develop a hardware model for Intel’s second-generation Xeon Phi architecture code-named Knights Landing (KNL) for the SKOPE framework. We validate the KNL hardware model by projecting the performance of mini-benchmarks and application kernels. The results show that our KNL model can project the performance with prediction errorsmore » of 10% to 20%. The hardware model also provides informative recommendations for code transformations and tuning.« less

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structures. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville Distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Analytical and Experimental Vibration Analysis of a Faulty Gear System

NASA Technical Reports Server (NTRS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-01-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Toward Big Data Analytics: Review of Predictive Models in Management of Diabetes and Its Complications.

PubMed

Cichosz, Simon Lebech; Johansen, Mette Dencker; Hejlesen, Ole

2015-10-14

Diabetes is one of the top priorities in medical science and health care management, and an abundance of data and information is available on these patients. Whether data stem from statistical models or complex pattern recognition models, they may be fused into predictive models that combine patient information and prognostic outcome results. Such knowledge could be used in clinical decision support, disease surveillance, and public health management to improve patient care. Our aim was to review the literature and give an introduction to predictive models in screening for and the management of prevalent short- and long-term complications in diabetes. Predictive models have been developed for management of diabetes and its complications, and the number of publications on such models has been growing over the past decade. Often multiple logistic or a similar linear regression is used for prediction model development, possibly owing to its transparent functionality. Ultimately, for prediction models to prove useful, they must demonstrate impact, namely, their use must generate better patient outcomes. Although extensive effort has been put in to building these predictive models, there is a remarkable scarcity of impact studies. © 2015 Diabetes Technology Society.

Modeling of vortex generated sound in solid propellant rocket motors

NASA Technical Reports Server (NTRS)

Flandro, G. A.

1980-01-01

There is considerable evidence based on both full scale firings and cold flow simulations that hydrodynamically unstable shear flows in solid propellant rocket motors can lead to acoustic pressure fluctuations of significant amplitude. Although a comprehensive theoretical understanding of this problem does not yet exist, procedures were explored for generating useful analytical models describing the vortex shedding phenomenon and the mechanisms of coupling to the acoustic field in a rocket combustion chamber. Since combustion stability prediction procedures cannot be successful without incorporation of all acoustic gains and losses, it is clear that a vortex driving model comparable in quality to the analytical models currently employed to represent linear combustion instability must be formulated.

Analytic model for ultrasound energy receivers and their optimal electric loads

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-08-01

In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.

Sinking bubbles in stout beers

NASA Astrophysics Data System (ADS)

Lee, W. T.; Kaar, S.; O'Brien, S. B. G.

2018-04-01

A surprising phenomenon witnessed by many is the sinking bubbles seen in a settling pint of stout beer. Bubbles are less dense than the surrounding fluid so how does this happen? Previous work has shown that the explanation lies in a circulation of fluid promoted by the tilted sides of the glass. However, this work has relied heavily on computational fluid dynamics (CFD) simulations. Here, we show that the phenomenon of sinking bubbles can be predicted using a simple analytic model. To make the model analytically tractable, we work in the limit of small bubbles and consider a simplified geometry. The model confirms both the existence of sinking bubbles and the previously proposed mechanism.

Quasilinear Line Broadened Model for Energetic Particle Transport

NASA Astrophysics Data System (ADS)

Ghantous, Katy; Gorelenkov, Nikolai; Berk, Herbert

2011-10-01

We present a self-consistent quasi-linear model that describes wave-particle interaction in toroidal geometry and computes fast ion transport during TAE mode evolution. The model bridges the gap between single mode resonances, where it predicts the analytically expected saturation levels, and the case of multiple modes overlapping, where particles diffuse across phase space. Results are presented in the large aspect ratio limit where analytic expressions are used for Fourier harmonics of the power exchange between waves and particles, . Implemention of a more realistic mode structure calculated by NOVAK code are also presented. This work is funded by DOE contract DE-AC02-09CH11466.