Uncertainty quantification and propagation in dynamic models using ambient vibration measurements, application to a 10-story building

NASA Astrophysics Data System (ADS)

Behmanesh, Iman; Yousefianmoghadam, Seyedsina; Nozari, Amin; Moaveni, Babak; Stavridis, Andreas

2018-07-01

This paper investigates the application of Hierarchical Bayesian model updating for uncertainty quantification and response prediction of civil structures. In this updating framework, structural parameters of an initial finite element (FE) model (e.g., stiffness or mass) are calibrated by minimizing error functions between the identified modal parameters and the corresponding parameters of the model. These error functions are assumed to have Gaussian probability distributions with unknown parameters to be determined. The estimated parameters of error functions represent the uncertainty of the calibrated model in predicting building's response (modal parameters here). The focus of this paper is to answer whether the quantified model uncertainties using dynamic measurement at building's reference/calibration state can be used to improve the model prediction accuracies at a different structural state, e.g., damaged structure. Also, the effects of prediction error bias on the uncertainty of the predicted values is studied. The test structure considered here is a ten-story concrete building located in Utica, NY. The modal parameters of the building at its reference state are identified from ambient vibration data and used to calibrate parameters of the initial FE model as well as the error functions. Before demolishing the building, six of its exterior walls were removed and ambient vibration measurements were also collected from the structure after the wall removal. These data are not used to calibrate the model; they are only used to assess the predicted results. The model updating framework proposed in this paper is applied to estimate the modal parameters of the building at its reference state as well as two damaged states: moderate damage (removal of four walls) and severe damage (removal of six walls). Good agreement is observed between the model-predicted modal parameters and those identified from vibration tests. Moreover, it is shown that including prediction error bias in the updating process instead of commonly-used zero-mean error function can significantly reduce the prediction uncertainties.

The structure of binding curves and practical identifiability of equilibrium ligand-binding parameters

PubMed Central

Middendorf, Thomas R.

2017-01-01

A critical but often overlooked question in the study of ligands binding to proteins is whether the parameters obtained from analyzing binding data are practically identifiable (PI), i.e., whether the estimates obtained from fitting models to noisy data are accurate and unique. Here we report a general approach to assess and understand binding parameter identifiability, which provides a toolkit to assist experimentalists in the design of binding studies and in the analysis of binding data. The partial fraction (PF) expansion technique is used to decompose binding curves for proteins with n ligand-binding sites exactly and uniquely into n components, each of which has the form of a one-site binding curve. The association constants of the PF component curves, being the roots of an n-th order polynomial, may be real or complex. We demonstrate a fundamental connection between binding parameter identifiability and the nature of these one-site association constants: all binding parameters are identifiable if the constants are all real and distinct; otherwise, at least some of the parameters are not identifiable. The theory is used to construct identifiability maps from which the practical identifiability of binding parameters for any two-, three-, or four-site binding curve can be assessed. Instructions for extending the method to generate identifiability maps for proteins with more than four binding sites are also given. Further analysis of the identifiability maps leads to the simple rule that the maximum number of structurally identifiable binding parameters (shown in the previous paper to be equal to n) will also be PI only if the binding curve line shape contains n resolved components. PMID:27993951

Structural Damage Detection Using Virtual Passive Controllers

NASA Technical Reports Server (NTRS)

Lew, Jiann-Shiun; Juang, Jer-Nan

2001-01-01

This paper presents novel approaches for structural damage detection which uses the virtual passive controllers attached to structures, where passive controllers are energy dissipative devices and thus guarantee the closed-loop stability. The use of the identified parameters of various closed-loop systems can solve the problem that reliable identified parameters, such as natural frequencies of the open-loop system may not provide enough information for damage detection. Only a small number of sensors are required for the proposed approaches. The identified natural frequencies, which are generally much less sensitive to noise and more reliable than the identified natural frequencies, are used for damage detection. Two damage detection techniques are presented. One technique is based on the structures with direct output feedback controllers while the other technique uses the second-order dynamic feedback controllers. A least-squares technique, which is based on the sensitivity of natural frequencies to damage variables, is used for accurately identifying the damage variables.

Preliminary structural design of a lunar transfer vehicle aerobrake. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bush, Lance B.

1992-01-01

An aerobrake concept for a Lunar transfer vehicle was weight optimized through the use of the Taguchi design method, structural finite element analyses and structural sizing routines. Six design parameters were chosen to represent the aerobrake structural configuration. The design parameters included honeycomb core thickness, diameter to depth ratio, shape, material, number of concentric ring frames, and number of radial frames. Each parameter was assigned three levels. The minimum weight aerobrake configuration resulting from the study was approx. half the weight of the average of all twenty seven experimental configurations. The parameters having the most significant impact on the aerobrake structural weight were identified.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

PubMed

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Full-envelope aerodynamic modeling of the Harrier aircraft

NASA Technical Reports Server (NTRS)

Mcnally, B. David

1986-01-01

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

Structural identifiability analysis of a cardiovascular system model.

PubMed

Pironet, Antoine; Dauby, Pierre C; Chase, J Geoffrey; Docherty, Paul D; Revie, James A; Desaive, Thomas

2016-05-01

The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are not identifiable from any output set. In this work, two such cases of structural non-identifiability are first presented. These cases occur when the model output set only contains a single type of information (pressure or volume). A specific output set is thus chosen, mixing pressure and volume information and containing only a limited number of clinically available measurements. Then, by manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable. A further simplification is made, assuming known cardiac valve resistances. Because of the poor practical identifiability of these four parameters, this assumption is usual. Under this hypothesis, the six-chamber cardiovascular system model is structurally identifiable from an even smaller dataset. As a consequence, parameter values computed from limited but well-chosen datasets are theoretically unique. This means that the parameter identification procedure can safely be performed on the model from such a well-chosen dataset. Thus, the model may be considered suitable for use in diagnosis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

A simple method for identifying parameter correlations in partially observed linear dynamic models.

PubMed

Li, Pu; Vu, Quoc Dong

2015-12-14

Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability analysis has been extensively studied by analytical as well as numerical approaches, systematic methods for remedying practically non-identifiable models have rarely been investigated. We propose a simple method for identifying pairwise correlations and higher order interrelationships of parameters in partially observed linear dynamic models. This is made by derivation of the output sensitivity matrix and analysis of the linear dependencies of its columns. Consequently, analytical relations between the identifiability of the model parameters and the initial conditions as well as the input functions can be achieved. In the case of structural non-identifiability, identifiable combinations can be obtained by solving the resulting homogenous linear equations. In the case of practical non-identifiability, experiment conditions (i.e. initial condition and constant control signals) can be provided which are necessary for remedying the non-identifiability and unique parameter estimation. It is noted that the approach does not consider noisy data. In this way, the practical non-identifiability issue, which is popular for linear biological models, can be remedied. Several linear compartment models including an insulin receptor dynamics model are taken to illustrate the application of the proposed approach. Both structural and practical identifiability of partially observed linear dynamic models can be clarified by the proposed method. The result of this method provides important information for experimental design to remedy the practical non-identifiability if applicable. The derivation of the method is straightforward and thus the algorithm can be easily implemented into a software packet.

Selection of noisy measurement locations for error reduction in static parameter identification

NASA Astrophysics Data System (ADS)

Sanayei, Masoud; Onipede, Oladipo; Babu, Suresh R.

1992-09-01

An incomplete set of noisy static force and displacement measurements is used for parameter identification of structures at the element level. Measurement location and the level of accuracy in the measured data can drastically affect the accuracy of the identified parameters. A heuristic method is presented to select a limited number of degrees of freedom (DOF) to perform a successful parameter identification and to reduce the impact of measurement errors on the identified parameters. This pretest simulation uses an error sensitivity analysis to determine the effect of measurement errors on the parameter estimates. The selected DOF can be used for nondestructive testing and health monitoring of structures. Two numerical examples, one for a truss and one for a frame, are presented to demonstrate that using the measurements at the selected subset of DOF can limit the error in the parameter estimates.

Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

PubMed

Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

2014-05-01

In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

On the problem of modeling for parameter identification in distributed structures

NASA Technical Reports Server (NTRS)

Norris, Mark A.; Meirovitch, Leonard

1988-01-01

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Distillation tray structural parameter study: Phase 1

NASA Technical Reports Server (NTRS)

Winter, J. Ronald

1991-01-01

The purpose here is to identify the structural parameters (plate thickness, liquid level, beam size, number of beams, tray diameter, etc.) that affect the structural integrity of distillation trays in distillation columns. Once the sensitivity of the trays' dynamic response to these parameters has been established, the designer will be able to use this information to prepare more accurate specifications for the construction of new trays. Information is given on both static and dynamic analysis, modal response, and tray failure details.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

The structural identifiability and parameter estimation of a multispecies model for the transmission of mastitis in dairy cows with postmilking teat disinfection.

PubMed

White, L J; Evans, N D; Lam, T J G M; Schukken, Y H; Medley, G F; Godfrey, K R; Chappell, M J

2002-01-01

A mathematical model for the transmission of two interacting classes of mastitis causing bacterial pathogens in a herd of dairy cows is presented and applied to a specific data set. The data were derived from a field trial of a specific measure used in the control of these pathogens, where half the individuals were subjected to the control and in the others the treatment was discontinued. The resultant mathematical model (eight non-linear simultaneous ordinary differential equations) therefore incorporates heterogeneity in the host as well as the infectious agent and consequently the effects of control are intrinsic in the model structure. A structural identifiability analysis of the model is presented demonstrating that the scope of the novel method used allows application to high order non-linear systems. The results of a simultaneous estimation of six unknown system parameters are presented. Previous work has only estimated a subset of these either simultaneously or individually. Therefore not only are new estimates provided for the parameters relating to the transmission and control of the classes of pathogens under study, but also information about the relationships between them. We exploit the close link between mathematical modelling, structural identifiability analysis, and parameter estimation to obtain biological insights into the system modelled.

Foot Type Biomechanics Part 2: are structure and anthropometrics related to function?

PubMed

Mootanah, Rajshree; Song, Jinsup; Lenhoff, Mark W; Hafer, Jocelyn F; Backus, Sherry I; Gagnon, David; Deland, Jonathan T; Hillstrom, Howard J

2013-03-01

Many foot pathologies are associated with specific foot types. If foot structure and function are related, measurement of either could assist with differential diagnosis of pedal pathologies. Biomechanical measures of foot structure and function are related in asymptomatic healthy individuals. Sixty-one healthy subjects' left feet were stratified into cavus (n=12), rectus (n=27) and planus (n=22) foot types. Foot structure was assessed by malleolar valgus index, arch height index, and arch height flexibility. Anthropometrics (height and weight), age, and walking speed were measured. Foot function was assessed by center of pressure excursion index, peak plantar pressure, maximum force, and gait pattern parameters. Foot structure and anthropometric variables were entered into stepwise linear regression models to identify predictors of function. Measures of foot structure and anthropometrics explained 10-37% of the model variance (adjusted R(2)) for gait pattern parameters. When walking speed was included, the adjusted R(2) increased to 45-77% but foot structure was no longer a factor. Foot structure and anthropometrics predicted 7-47% of the model variance for plantar pressure and 16-64% for maximum force parameters. All multivariate models were significant (p<0.05), supporting acceptance of the hypothesis. Foot structure and function are related in asymptomatic healthy individuals. The structural parameters employed are basic measurements that do not require ionizing radiation and could be used in a clinical setting. Further research is needed to identify additional predictive parameters (plantar soft tissue characteristics, skeletal alignment, and neuromuscular control) and to include individuals with pathology. Copyright © 2012. Published by Elsevier B.V.

Foot Type Biomechanics Part 2: Are structure and anthropometrics related to function?

PubMed Central

Mootanah, Rajshree; Song, Jinsup; Lenhoff, Mark W.; Hafer, Jocelyn F.; Backus, Sherry I.; Gagnon, David; Deland, Jonathan T.; Hillstrom, Howard J.

2013-01-01

Background Many foot pathologies are associated with specific foot types. If foot structure and function are related, measurement of either could assist with differential diagnosis of pedal pathologies. Hypothesis Biomechanical measures of foot structure and function are related in asymptomatic healthy individuals. Methods Sixty-one healthy subjects' left feet were stratified into cavus (n = 12), rectus (n = 27) and planus (n = 22) foot types. Foot structure was assessed by malleolar valgus index, arch height index, and arch height flexibility. Anthropometrics (height and weight), age, and walking speed were measured. Foot function was assessed by center of pressure excursion index, peak plantar pressure, maximum force, and gait pattern parameters. Foot structure and anthropometric variables were entered into stepwise linear regression models to identify predictors of function. Results Measures of foot structure and anthropometrics explained 10–37% of the model variance (adjusted R2) for gait pattern parameters. When walking speed was included, the adjusted R2 increased to 45–77% but foot structure was no longer a factor. Foot structure and anthropometrics predicted 7–47% of the model variance for plantar pressure and 16–64% for maximum force parameters. All multivariate models were significant (p < 0.05), supporting acceptance of the hypothesis. Discussion and conclusion Foot structure and function are related in asymptomatic healthy individuals. The structural parameters employed are basic measurements that do not require ionizing radiation and could be used in a clinical setting. Further research is needed to identify additional predictive parameters (plantar soft tissue characteristics, skeletal alignment, and neuromuscular control) and to include individuals with pathology. PMID:23107624

A general model-based design of experiments approach to achieve practical identifiability of pharmacokinetic and pharmacodynamic models.

PubMed

Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio

2013-08-01

The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.

Can structural and functional characteristics be used to identify riparian zone width in southern Appalachian headwater catchments?

Treesearch

Barton Clinton; James Vose; Jennifer Knoepp; Katherine Elliott; Barbara Reynolds; Stanley Zarnock

2010-01-01

We characterized structural and functional attributes along hillslope gradients in headwater catchments. We endeavored to identify parameters that described significant transitions along the hillslope. On each of four catchments, we installed eight 50 m transects perpendicular to the stream. Structural attributes included woody and herbaceous vegetation; woody debris...

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Additive manufactured serialization

DOEpatents

Bobbitt, III, John T.

2017-04-18

Methods for forming an identifying mark in a structure are described. The method is used in conjunction with an additive manufacturing method and includes the alteration of a process parameter during the manufacturing process. The method can form in a unique identifying mark within or on the surface of a structure that is virtually impossible to be replicated. Methods can provide a high level of confidence that the identifying mark will remain unaltered on the formed structure.

Order parameters in lanthanum gallate lightly doped with manganese and paramagnetic resonance

NASA Astrophysics Data System (ADS)

Vazhenin, V. A.; Potapov, A. P.; Artyomov, M. Yu.; Guseva, V. B.

2010-09-01

The Cr3+ centers have been revealed, transitions at room temperature have been identified, and spin Hamiltonian parameters have been determined for the Cr3+ and Fe3+ triclinic centers in lanthanum gallate lightly doped with manganese. The principal axes of the fourth-rank fine-structure tensor for the Fe3+ triclinic centers have been established and used to determine the order parameters, i.e., the angles of rotation of oxygen octahedra of lanthanum gallate with respect to the perovskite structure. The order parameter in the rhombohedral phase has been estimated.

Identifiability and estimation of multiple transmission pathways in cholera and waterborne disease.

PubMed

Eisenberg, Marisa C; Robertson, Suzanne L; Tien, Joseph H

2013-05-07

Cholera and many waterborne diseases exhibit multiple characteristic timescales or pathways of infection, which can be modeled as direct and indirect transmission. A major public health issue for waterborne diseases involves understanding the modes of transmission in order to improve control and prevention strategies. An important epidemiological question is: given data for an outbreak, can we determine the role and relative importance of direct vs. environmental/waterborne routes of transmission? We examine whether parameters for a differential equation model of waterborne disease transmission dynamics can be identified, both in the ideal setting of noise-free data (structural identifiability) and in the more realistic setting in the presence of noise (practical identifiability). We used a differential algebra approach together with several numerical approaches, with a particular emphasis on identifiability of the transmission rates. To examine these issues in a practical public health context, we apply the model to a recent cholera outbreak in Angola (2006). Our results show that the model parameters-including both water and person-to-person transmission routes-are globally structurally identifiable, although they become unidentifiable when the environmental transmission timescale is fast. Even for water dynamics within the identifiable range, when noisy data are considered, only a combination of the water transmission parameters can practically be estimated. This makes the waterborne transmission parameters difficult to estimate, leading to inaccurate estimates of important epidemiological parameters such as the basic reproduction number (R0). However, measurements of pathogen persistence time in environmental water sources or measurements of pathogen concentration in the water can improve model identifiability and allow for more accurate estimation of waterborne transmission pathway parameters as well as R0. Parameter estimates for the Angola outbreak suggest that both transmission pathways are needed to explain the observed cholera dynamics. These results highlight the importance of incorporating environmental data when examining waterborne disease. Copyright © 2013 Elsevier Ltd. All rights reserved.

Sensitivity and Specificity of Eustachian Tube Function Tests in Adults

PubMed Central

Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.

2013-01-01

Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment Using Design of Experiments Methodology

NASA Technical Reports Server (NTRS)

Parsons, David S.; Ordway, David; Johnson, Kenneth

2013-01-01

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Characterizing the Response of Composite Panels to a Pyroshock Induced Environment using Design of Experiments Methodology

NASA Technical Reports Server (NTRS)

Parsons, David S.; Ordway, David O.; Johnson, Kenneth L.

2013-01-01

This experimental study seeks to quantify the impact various composite parameters have on the structural response of a composite structure in a pyroshock environment. The prediction of an aerospace structure's response to pyroshock induced loading is largely dependent on empirical databases created from collections of development and flight test data. While there is significant structural response data due to pyroshock induced loading for metallic structures, there is much less data available for composite structures. One challenge of developing a composite pyroshock response database as well as empirical prediction methods for composite structures is the large number of parameters associated with composite materials. This experimental study uses data from a test series planned using design of experiments (DOE) methods. Statistical analysis methods are then used to identify which composite material parameters most greatly influence a flat composite panel's structural response to pyroshock induced loading. The parameters considered are panel thickness, type of ply, ply orientation, and pyroshock level induced into the panel. The results of this test will aid in future large scale testing by eliminating insignificant parameters as well as aid in the development of empirical scaling methods for composite structures' response to pyroshock induced loading.

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

PubMed

Yang, Huan; Meijer, Hil G E; Buitenweg, Jan R; van Gils, Stephan A

2016-01-01

Healthy or pathological states of nociceptive subsystems determine different stimulus-response relations measured from quantitative sensory testing. In turn, stimulus-response measurements may be used to assess these states. In a recently developed computational model, six model parameters characterize activation of nerve endings and spinal neurons. However, both model nonlinearity and limited information in yes-no detection responses to electrocutaneous stimuli challenge to estimate model parameters. Here, we address the question whether and how one can overcome these difficulties for reliable parameter estimation. First, we fit the computational model to experimental stimulus-response pairs by maximizing the likelihood. To evaluate the balance between model fit and complexity, i.e., the number of model parameters, we evaluate the Bayesian Information Criterion. We find that the computational model is better than a conventional logistic model regarding the balance. Second, our theoretical analysis suggests to vary the pulse width among applied stimuli as a necessary condition to prevent structural non-identifiability. In addition, the numerically implemented profile likelihood approach reveals structural and practical non-identifiability. Our model-based approach with integration of psychophysical measurements can be useful for a reliable assessment of states of the nociceptive system.

A phase transition in energy-filtered RNA secondary structures.

PubMed

Han, Hillary S W; Reidys, Christian M

2012-10-01

In this article we study the effect of energy parameters on minimum free energy (mfe) RNA secondary structures. Employing a simplified combinatorial energy model that is only dependent on the diagram representation and is not sequence-specific, we prove the following dichotomy result. Mfe structures derived via the Turner energy parameters contain only finitely many complex irreducible substructures, and just minor parameter changes produce a class of mfe structures that contain a large number of small irreducibles. We localize the exact point at which the distribution of irreducibles experiences this phase transition from a discrete limit to a central limit distribution and, subsequently, put our result into the context of quantifying the effect of sparsification of the folding of these respective mfe structures. We show that the sparsification of realistic mfe structures leads to a constant time and space reduction, and that the sparsification of the folding of structures with modified parameters leads to a linear time and space reduction. We, furthermore, identify the limit distribution at the phase transition as a Rayleigh distribution.

Measurement and modelling of the y-direction apparent mass of sitting human body-cushioned seat system

NASA Astrophysics Data System (ADS)

Stein, George Juraj; Múčka, Peter; Hinz, Barbara; Blüthner, Ralph

2009-04-01

Laboratory tests were conducted using 13 male subjects seated on a cushioned commercial vehicle driver's seat. The hands gripped a mock-up steering wheel and the subjects were in contact with the lumbar region of the backrest. The accelerations and forces in the y-direction were measured during random lateral whole-body vibration with a frequency range between 0.25 and 30 Hz, vibration magnitudes 0.30, 0.98, and 1.92 m s -2 (unweighted root mean square (rms)). Based on these laboratory measurements, a linear multi-degree-of-freedom (mdof) model of the seated human body and cushioned seat in the lateral direction ( y-axis) was developed. Model parameters were identified from averaged measured apparent mass values (modulus and phase) for the three excitation magnitudes mentioned. A preferred model structure was selected from four 3-dof models analysed. The mean subject parameters were identified. In addition, identification of each subject's apparent mass model parameters was performed. The results are compared with previous studies. The developed model structure and the identified parameters can be used for further biodynamical research in seating dynamics.

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

Identification and calibration of the structural model of historical masonry building damaged during the 2016 Italian earthquakes: The case study of Palazzo del Podestà in Montelupone

NASA Astrophysics Data System (ADS)

Catinari, Federico; Pierdicca, Alessio; Clementi, Francesco; Lenci, Stefano

2017-11-01

The results of an ambient-vibration based investigation conducted on the "Palazzo del Podesta" in Montelupone (Italy) is presented. The case study was damaged during the 20I6 Italian earthquakes that stroke the central part of the Italy. The assessment procedure includes full-scale ambient vibration testing, modal identification from ambient vibration responses, finite element modeling and dynamic-based identification of the uncertain structural parameters of the model. A very good match between theoretical and experimental modal parameters was reached and the model updating has been performed identifying some structural parameters.

Modal parameter identification based on combining transmissibility functions and blind source separation techniques

NASA Astrophysics Data System (ADS)

Araújo, Iván Gómez; Sánchez, Jesús Antonio García; Andersen, Palle

2018-05-01

Transmissibility-based operational modal analysis is a recent and alternative approach used to identify the modal parameters of structures under operational conditions. This approach is advantageous compared with traditional operational modal analysis because it does not make any assumptions about the excitation spectrum (i.e., white noise with a flat spectrum). However, common methodologies do not include a procedure to extract closely spaced modes with low signal-to-noise ratios. This issue is relevant when considering that engineering structures generally have closely spaced modes and that their measured responses present high levels of noise. Therefore, to overcome these problems, a new combined method for modal parameter identification is proposed in this work. The proposed method combines blind source separation (BSS) techniques and transmissibility-based methods. Here, BSS techniques were used to recover source signals, and transmissibility-based methods were applied to estimate modal information from the recovered source signals. To achieve this combination, a new method to define a transmissibility function was proposed. The suggested transmissibility function is based on the relationship between the power spectral density (PSD) of mixed signals and the PSD of signals from a single source. The numerical responses of a truss structure with high levels of added noise and very closely spaced modes were processed using the proposed combined method to evaluate its ability to identify modal parameters in these conditions. Colored and white noise excitations were used for the numerical example. The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes. The results showed that the proposed combined method is capable of identifying very closely spaced modes in the presence of noise and, thus, may be potentially applied to improve the identification of damping ratios.

Parameter optimization on the convergence surface of path simulations

NASA Astrophysics Data System (ADS)

Chandrasekaran, Srinivas Niranj

Computational treatments of protein conformational changes tend to focus on the trajectories themselves, despite the fact that it is the transition state structures that contain information about the barriers that impose multi-state behavior. PATH is an algorithm that computes a transition pathway between two protein crystal structures, along with the transition state structure, by minimizing the Onsager-Machlup action functional. It is rapid but depends on several unknown input parameters whose range of different values can potentially generate different transition-state structures. Transition-state structures arising from different input parameters cannot be uniquely compared with those generated by other methods. I outline modifications that I have made to the PATH algorithm that estimates these input parameters in a manner that circumvents these difficulties, and describe two complementary tests that validate the transition-state structures found by the PATH algorithm. First, I show that although the PATH algorithm and two other approaches to computing transition pathways produce different low-energy structures connecting the initial and final ground-states with the transition state, all three methods agree closely on the configurations of their transition states. Second, I show that the PATH transition states are close to the saddle points of free-energy surfaces connecting initial and final states generated by replica-exchange Discrete Molecular Dynamics simulations. I show that aromatic side-chain rearrangements create similar potential energy barriers in the transition-state structures identified by PATH for a signaling protein, a contractile protein, and an enzyme. Finally, I observed, but cannot account for, the fact that trajectories obtained for all-atom and Calpha-only simulations identify transition state structures in which the Calpha atoms are in essentially the same positions. The consistency between transition-state structures derived by different algorithms for unrelated protein systems argues that although functionally important protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. In the end, I outline the strategies that could enhance the efficiency and applicability of PATH.

Phase-contrast tomography of sciatic nerves: image quality and experimental parameters

NASA Astrophysics Data System (ADS)

Töpperwien, M.; Krenkel, M.; Ruhwedel, T.; Möbius, W.; Pacureanu, A.; Cloetens, P.; Salditt, T.

2017-06-01

We present propagation-based phase-contrast tomography of mouse sciatic nerves stained with osmium, leading to an enhanced contrast in the myelin sheath around the axons, in order to visualize the threedimensional (3D) structure of the nerve. We compare different experimental parameters and show that contrast and resolution are high enough to identify single axons in the nerve, including characteristic functional structures such as Schmidt-Lanterman incisures.

Computational Algorithms or Identification of Distributed Parameter Systems

DTIC Science & Technology

1993-04-24

delay-differential equations, Volterra integral equations, and partial differential equations with memory terms . In particular we investigated a...tested for estimating parameters in a Volterra integral equation arising from a viscoelastic model of a flexible structure with Boltzmann damping. In...particular, one of the parameters identified was the order of the derivative in Volterra integro-differential equations containing fractional

Analysis and Sizing for Transient Thermal Heating of Insulated Aerospace Vehicle Structures

NASA Technical Reports Server (NTRS)

Blosser, Max L.

2012-01-01

An analytical solution was derived for the transient response of an insulated structure subjected to a simplified heat pulse. The solution is solely a function of two nondimensional parameters. Simpler functions of these two parameters were developed to approximate the maximum structural temperature over a wide range of parameter values. Techniques were developed to choose constant, effective thermal properties to represent the relevant temperature and pressure-dependent properties for the insulator and structure. A technique was also developed to map a time-varying surface temperature history to an equivalent square heat pulse. Equations were also developed for the minimum mass required to maintain the inner, unheated surface below a specified temperature. In the course of the derivation, two figures of merit were identified. Required insulation masses calculated using the approximate equation were shown to typically agree with finite element results within 10%-20% over the relevant range of parameters studied.

QUANTIFYING OBSERVATIONAL PROJECTION EFFECTS USING MOLECULAR CLOUD SIMULATIONS

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

Beaumont, Christopher N.; Offner, Stella S.R.; Shetty, Rahul

2013-11-10

The physical properties of molecular clouds are often measured using spectral-line observations, which provide the only probes of the clouds' velocity structure. It is hard, though, to assess whether and to what extent intensity features in position-position-velocity (PPV) space correspond to 'real' density structures in position-position-position (PPP) space. In this paper, we create synthetic molecular cloud spectral-line maps of simulated molecular clouds, and present a new technique for measuring the reality of individual PPV structures. Using a dendrogram algorithm, we identify hierarchical structures in both PPP and PPV space. Our procedure projects density structures identified in PPP space into correspondingmore » intensity structures in PPV space and then measures the geometric overlap of the projected structures with structures identified from the synthetic observation. The fractional overlap between a PPP and PPV structure quantifies how well the synthetic observation recovers information about the three-dimensional structure. Applying this machinery to a set of synthetic observations of CO isotopes, we measure how well spectral-line measurements recover mass, size, velocity dispersion, and virial parameter for a simulated star-forming region. By disabling various steps of our analysis, we investigate how much opacity, chemistry, and gravity affect measurements of physical properties extracted from PPV cubes. For the simulations used here, which offer a decent, but not perfect, match to the properties of a star-forming region like Perseus, our results suggest that superposition induces a ∼40% uncertainty in masses, sizes, and velocity dispersions derived from {sup 13}CO (J = 1-0). As would be expected, superposition and confusion is worst in regions where the filling factor of emitting material is large. The virial parameter is most affected by superposition, such that estimates of the virial parameter derived from PPV and PPP information typically disagree by a factor of ∼2. This uncertainty makes it particularly difficult to judge whether gravitational or kinetic energy dominate a given region, since the majority of virial parameter measurements fall within a factor of two of the equipartition level α ∼ 2.« less

Visualizing spatial correlation: structural and electronic orders in iron-based superconductors on atomic scale

NASA Astrophysics Data System (ADS)

Maksov, Artem; Ziatdinov, Maxim; Li, Li; Sefat, Athena; Maksymovych, Petro; Kalinin, Sergei

Crystalline matter on the nanoscale level often exhibits strongly inhomogeneous structural and electronic orders, which have a profound effect on macroscopic properties. This may be caused by subtle interplay between chemical disorder, strain, magnetic, and structural order parameters. We present a novel approach based on combination of high resolution scanning tunneling microscopy/spectroscopy (STM/S) and deep data style analysis for automatic separation, extraction, and correlation of structural and electronic behavior which might lead us to uncovering the underlying sources of inhomogeneity in in iron-based family of superconductors (FeSe, BaFe2As2) . We identify STS spectral features using physically robust Bayesian linear unmixing, and show their direct relevance to the fundamental physical properties of the system, including electronic states associated with individual defects and impurities. We collect structural data from individual unit cells on the crystalline lattice, and calculate both global and local indicators of spatial correlation with electronic features, demonstrating, for the first time, a direct quantifiable connection between observed structural order parameters extracted from the STM data and electronic order parameters identified within the STS data. This research was sponsored by the Division of Materials Sciences and Engineering, Office of Science, Basic Energy Sciences, US DOE.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Complex Spiral Structure in the HD 100546 Transitional Disk as Revealed by GPI and MagAO

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

Follette, Katherine B.; Macintosh, Bruce; Mullen, Wyatt

We present optical and near-infrared high-contrast images of the transitional disk HD 100546 taken with the Magellan Adaptive Optics system (MagAO) and the Gemini Planet Imager (GPI). GPI data include both polarized intensity and total intensity imagery, and MagAO data are taken in Simultaneous Differential Imaging mode at H α . The new GPI H -band total intensity data represent a significant enhancement in sensitivity and field rotation compared to previous data sets and enable a detailed exploration of substructure in the disk. The data are processed with a variety of differential imaging techniques (polarized, angular, reference, and simultaneous differentialmore » imaging) in an attempt to identify the disk structures that are most consistent across wavelengths, processing techniques, and algorithmic parameters. The inner disk cavity at 15 au is clearly resolved in multiple data sets, as are a variety of spiral features. While the cavity and spiral structures are identified at levels significantly distinct from the neighboring regions of the disk under several algorithms and with a range of algorithmic parameters, emission at the location of HD 100546 “ c ” varies from point-like under aggressive algorithmic parameters to a smooth continuous structure with conservative parameters, and is consistent with disk emission. Features identified in the HD 100546 disk bear qualitative similarity to computational models of a moderately inclined two-armed spiral disk, where projection effects and wrapping of the spiral arms around the star result in a number of truncated spiral features in forward-modeled images.« less

Ab initio crystal structure prediction of magnesium (poly)sulfides and calculation of their NMR parameters.

PubMed

Mali, Gregor

2017-03-01

Ab initio prediction of sensible crystal structures can be regarded as a crucial task in the quickly-developing methodology of NMR crystallography. In this contribution, an evolutionary algorithm was used for the prediction of magnesium (poly)sulfide crystal structures with various compositions. The employed approach successfully identified all three experimentally detected forms of MgS, i.e. the stable rocksalt form and the metastable wurtzite and zincblende forms. Among magnesium polysulfides with a higher content of sulfur, the most probable structure with the lowest formation energy was found to be MgS 2 , exhibiting a modified rocksalt structure, in which S 2- anions were replaced by S 2 2- dianions. Magnesium polysulfides with even larger fractions of sulfur were not predicted to be stable. For the lowest-energy structures, 25 Mg quadrupolar coupling constants and chemical shift parameters were calculated using the density functional theory approach. The calculated NMR parameters could be well rationalized by the symmetries of the local magnesium environments, by the coordination of magnesium cations and by the nature of the surrounding anions. In the future, these parameters could serve as a reference for the experimentally determined 25 Mg NMR parameters of magnesium sulfide species.

Structural dynamic analysis of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Scott, L. P.; Jamison, G. T.; Mccutcheon, W. A.; Price, J. M.

1981-01-01

This structural dynamic analysis supports development of the SSME by evaluating components subjected to critical dynamic loads, identifying significant parameters, and evaluating solution methods. Engine operating parameters at both rated and full power levels are considered. Detailed structural dynamic analyses of operationally critical and life limited components support the assessment of engine design modifications and environmental changes. Engine system test results are utilized to verify analytic model simulations. The SSME main chamber injector assembly is an assembly of 600 injector elements which are called LOX posts. The overall LOX post analysis procedure is shown.

High frequency modal identification on noisy high-speed camera data

NASA Astrophysics Data System (ADS)

Javh, Jaka; Slavič, Janko; Boltežar, Miha

2018-01-01

Vibration measurements using optical full-field systems based on high-speed footage are typically heavily burdened by noise, as the displacement amplitudes of the vibrating structures are often very small (in the range of micrometers, depending on the structure). The modal information is troublesome to measure as the structure's response is close to, or below, the noise level of the camera-based measurement system. This paper demonstrates modal parameter identification for such noisy measurements. It is shown that by using the Least-Squares Complex-Frequency method combined with the Least-Squares Frequency-Domain method, identification at high-frequencies is still possible. By additionally incorporating a more precise sensor to identify the eigenvalues, a hybrid accelerometer/high-speed camera mode shape identification is possible even below the noise floor. An accelerometer measurement is used to identify the eigenvalues, while the camera measurement is used to produce the full-field mode shapes close to 10 kHz. The identified modal parameters improve the quality of the measured modal data and serve as a reduced model of the structure's dynamics.

Monitoring early hydration of reinforced concrete structures using structural parameters identified by piezo sensors via electromechanical impedance technique

NASA Astrophysics Data System (ADS)

Talakokula, Visalakshi; Bhalla, Suresh; Gupta, Ashok

2018-01-01

Concrete is the most widely used material in civil engineering construction. Its life begins when the hydration process is activated after mixing the cement granulates with water. In this paper, a non-dimensional hydration parameter, obtained from piezoelectric ceramic (PZT) patches bonded to rebars embedded inside concrete, is employed to monitor the early age hydration of concrete. The non-dimensional hydration parameter is derived from the equivalent stiffness determined from the piezo-impedance transducers using the electro-mechanical impedance (EMI) technique. The focus of the study is to monitor the hydration process of cementitious materials commencing from the early hours and continue till 28 days using single non-dimensional parameter. The experimental results show that the proposed piezo-based non-dimensional hydration parameter is very effective in monitoring the early age hydration, as it has been derived from the refined structural impedance parameters, obtained by eliminating the PZT contribution, and using both the real and imaginary components of the admittance signature.

Sensitivity and specificity of eustachian tube function tests in adults.

PubMed

Doyle, William J; Swarts, J Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M

2013-07-01

The study demonstrates the utility of eustachian tube (ET) function (ETF) test results for accurately assigning ears to disease state. To determine if ETF tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and to define the interrelatedness of ETF test parameters. Through use of the forced-response, inflation-deflation, Valsalva, and sniffing tests, ETF was evaluated in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). Data were analyzed using logistic regression including each parameter independently and then a step-down discriminant analysis including all ETF test parameters to predict group assignment. Factor analysis operating over all parameters was used to explore relatedness. ETF testing. ETF parameters for the forced response, inflation-deflation, Valsalva, and sniffing tests measured in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). The discriminant analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency, and percentage of positive pressure equilibrated) that together correctly assigned ears to group 2 at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters: the first had negative loadings of the ETF structural parameters; the second had positive loadings of the muscle-assisted ET opening parameters; and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories.

Rational selection of experimental readout and intervention sites for reducing uncertainties in computational model predictions.

PubMed

Flassig, Robert J; Migal, Iryna; der Zalm, Esther van; Rihko-Struckmann, Liisa; Sundmacher, Kai

2015-01-16

Understanding the dynamics of biological processes can substantially be supported by computational models in the form of nonlinear ordinary differential equations (ODE). Typically, this model class contains many unknown parameters, which are estimated from inadequate and noisy data. Depending on the ODE structure, predictions based on unmeasured states and associated parameters are highly uncertain, even undetermined. For given data, profile likelihood analysis has been proven to be one of the most practically relevant approaches for analyzing the identifiability of an ODE structure, and thus model predictions. In case of highly uncertain or non-identifiable parameters, rational experimental design based on various approaches has shown to significantly reduce parameter uncertainties with minimal amount of effort. In this work we illustrate how to use profile likelihood samples for quantifying the individual contribution of parameter uncertainty to prediction uncertainty. For the uncertainty quantification we introduce the profile likelihood sensitivity (PLS) index. Additionally, for the case of several uncertain parameters, we introduce the PLS entropy to quantify individual contributions to the overall prediction uncertainty. We show how to use these two criteria as an experimental design objective for selecting new, informative readouts in combination with intervention site identification. The characteristics of the proposed multi-criterion objective are illustrated with an in silico example. We further illustrate how an existing practically non-identifiable model for the chlorophyll fluorescence induction in a photosynthetic organism, D. salina, can be rendered identifiable by additional experiments with new readouts. Having data and profile likelihood samples at hand, the here proposed uncertainty quantification based on prediction samples from the profile likelihood provides a simple way for determining individual contributions of parameter uncertainties to uncertainties in model predictions. The uncertainty quantification of specific model predictions allows identifying regions, where model predictions have to be considered with care. Such uncertain regions can be used for a rational experimental design to render initially highly uncertain model predictions into certainty. Finally, our uncertainty quantification directly accounts for parameter interdependencies and parameter sensitivities of the specific prediction.

On 4-degree-of-freedom biodynamic models of seated occupants: Lumped-parameter modeling

NASA Astrophysics Data System (ADS)

Bai, Xian-Xu; Xu, Shi-Xu; Cheng, Wei; Qian, Li-Jun

2017-08-01

It is useful to develop an effective biodynamic model of seated human occupants to help understand the human vibration exposure to transportation vehicle vibrations and to help design and improve the anti-vibration devices and/or test dummies. This study proposed and demonstrated a methodology for systematically identifying the best configuration or structure of a 4-degree-of-freedom (4DOF) human vibration model and for its parameter identification. First, an equivalent simplification expression for the models was made. Second, all of the possible 23 structural configurations of the models were identified. Third, each of them was calibrated using the frequency response functions recommended in a biodynamic standard. An improved version of non-dominated sorting genetic algorithm (NSGA-II) based on Pareto optimization principle was used to determine the model parameters. Finally, a model evaluation criterion proposed in this study was used to assess the models and to identify the best one, which was based on both the goodness of curve fits and comprehensive goodness of the fits. The identified top configurations were better than those reported in the literature. This methodology may also be extended and used to develop the models with other DOFs.

Robust Level Coincidences in the Subband Structure of Quasi 2D Systems

NASA Astrophysics Data System (ADS)

Winkler, R.; Wang, L. Y.; Lin, Y. H.; Chu, C. S.

2011-03-01

Recently, level crossings in the energy bands of crystals have been identified as a key signature for topological phase transitions. In general, three independent parameters must be tuned appropriately to bring two quantum levels into degeneracy. Using realistic models we show that for Bloch electrons in a crystal the parameter space controlling the occurrence of level coincidences has a much richer structure than anticipated previously. In particular, we identify cases where level coincidences depend on only two independent parameters thus making the level coincidences robust, i.e., they cannot be removed by a small perturbation of the Hamiltonian compatible with the crystal symmetry. We consider HgTe/CdTe quantum wells as a specific example. (See arXiv:1011.xxxx) Work supported by Taiwan NSC (Contract No. 99-2112-M-009-006) and a MOE-ATU grant. Work at Argonne supported by DOE BES under Contract No. DE-AC02-06CH11357.

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models. PMID:25350289

A Computational Framework for Identifiability and Ill-Conditioning Analysis of Lithium-Ion Battery Models

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

López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio

2016-03-23

The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less

Regenerative Medicine and Restoration of Joint Function

DTIC Science & Technology

2012-10-01

identify the parameters that generate anatomically shaped bone substitutes of optimal composition and structure with an articulating profile. 2) to develop...strengths. An in vivo study in rabbits to evaluate these materials are ongoing. Task 2. Optimization of SFF Rolling Compaction Parameters : The work is...ongoing related to optimizing SFF rolling compaction parameters to control the density of green samples. We have used CPP powders for these studies

Modal Parameter Identification and Numerical Simulation for Self-anchored Suspension Bridges Based on Ambient Vibration

NASA Astrophysics Data System (ADS)

Liu, Bing; Sun, Li Guo

2018-06-01

This paper chooses the Nanjing-Hangzhou high speed overbridge, a self-anchored suspension bridge, as the research target, trying to identify the dynamic characteristic parameters of the bridge by using the peak-picking method to analyze the velocity response data under ambient excitation collected by 7 vibration pickup sensors set on the bridge deck. The ABAQUS is used to set up a three-dimensional finite element model for the full bridge and amends the finite element model of the suspension bridge based on the identified modal parameter, and suspender force picked by the PDV100 laser vibrometer. The study shows that the modal parameter can well be identified by analyzing the bridge vibration velocity collected by 7 survey points. The identified modal parameter and measured suspender force can be used as the basis of the amendment of the finite element model of the suspension bridge. The amended model can truthfully reflect the structural physical features and it can also be the benchmark model for the long-term health monitoring and condition assessment of the bridge.

High-order dynamic modeling and parameter identification of structural discontinuities in Timoshenko beams by using reflection coefficients

NASA Astrophysics Data System (ADS)

Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue

2013-02-01

Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.

Environmental effects on natural frequencies of the San Pietro bell tower in Perugia, Italy, and their removal for structural performance assessment

NASA Astrophysics Data System (ADS)

Ubertini, Filippo; Comanducci, Gabriele; Cavalagli, Nicola; Laura Pisello, Anna; Luigi Materazzi, Annibale; Cotana, Franco

2017-01-01

Continuously identified natural frequencies of vibration can provide unique information for low-cost automated condition assessment of civil constructions and infrastructures. However, the effects of changes in environmental parameters, such as temperature and humidity, need to be effectively investigated and accurately removed from identified frequency data for an effective performance assessment. This task is particularly challenging in the case of historical constructions that are typically massive and heterogeneous masonry structures characterized by complex variations of materials' properties with varying environmental parameters and by a differential heat conduction process where thermal capacity plays a major role. While there is abundance of documented monitoring data highlighting correlations between environmental parameters and natural frequencies in the case of new structures, such as long-span bridges, similar studies for historical constructions are still missing, with only a few literature works occasionally reporting increments in natural frequencies with increasing temperature of construction materials due to the closure of internal micro-cracks in the mortar layers caused by thermal expansion. In order to gain some knowledge on the effects of changes in temperature and humidity on the natural frequencies of slender masonry buildings, the paper focuses on the case study of an Italian monumental bell tower that has been monitored by the authors for more than nine months. Correlations between natural frequencies and environmental parameters are investigated in detail and the predictive capabilities of linear statistical regressive models based on the use of several environmental continuous monitoring sensors are assessed. At the end, three basic mechanisms governing environmentally-induced changes in the dynamic behavior of the tower are identified and essential information is achieved on the optimal location and minimum number of environmental sensors that are necessary in a structural health monitoring perspective.

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Lofberg, Johan; Brenner, Martin J.

2006-01-01

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

A regularization approach to hydrofacies delineation

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

Wohlberg, Brendt; Tartakovsky, Daniel

2009-01-01

We consider an inverse problem of identifying complex internal structures of composite (geological) materials from sparse measurements of system parameters and system states. Two conceptual frameworks for identifying internal boundaries between constitutive materials in a composite are considered. A sequential approach relies on support vector machines, nearest neighbor classifiers, or geostatistics to reconstruct boundaries from measurements of system parameters and then uses system states data to refine the reconstruction. A joint approach inverts the two data sets simultaneously by employing a regularization approach.

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2013-01-01

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

An information-theoretic approach to assess practical identifiability of parametric dynamical systems.

PubMed

Pant, Sanjay; Lombardi, Damiano

2015-10-01

A new approach for assessing parameter identifiability of dynamical systems in a Bayesian setting is presented. The concept of Shannon entropy is employed to measure the inherent uncertainty in the parameters. The expected reduction in this uncertainty is seen as the amount of information one expects to gain about the parameters due to the availability of noisy measurements of the dynamical system. Such expected information gain is interpreted in terms of the variance of a hypothetical measurement device that can measure the parameters directly, and is related to practical identifiability of the parameters. If the individual parameters are unidentifiable, correlation between parameter combinations is assessed through conditional mutual information to determine which sets of parameters can be identified together. The information theoretic quantities of entropy and information are evaluated numerically through a combination of Monte Carlo and k-nearest neighbour methods in a non-parametric fashion. Unlike many methods to evaluate identifiability proposed in the literature, the proposed approach takes the measurement-noise into account and is not restricted to any particular noise-structure. Whilst computationally intensive for large dynamical systems, it is easily parallelisable and is non-intrusive as it does not necessitate re-writing of the numerical solvers of the dynamical system. The application of such an approach is presented for a variety of dynamical systems--ranging from systems governed by ordinary differential equations to partial differential equations--and, where possible, validated against results previously published in the literature. Copyright © 2015 Elsevier Inc. All rights reserved.

Influence of processing parameters on pore structure of 3D porous chitosan-alginate polyelectrolyte complex scaffolds.

PubMed

Florczyk, Stephen J; Kim, Dae-Joon; Wood, David L; Zhang, Miqin

2011-09-15

Fabrication of porous polymeric scaffolds with controlled structure can be challenging. In this study, we investigated the influence of key experimental parameters on the structures and mechanical properties of resultant porous chitosan-alginate (CA) polyelectrolyte complex (PEC) scaffolds, and on proliferation of MG-63 osteoblast-like cells, targeted at bone tissue engineering. We demonstrated that the porous structure is largely affected by the solution viscosity, which can be regulated by the acetic acid and alginate concentrations. We found that the CA PEC solutions with viscosity below 300 Pa.s yielded scaffolds of uniform pore structure and that more neutral pH promoted more complete complexation of chitosan and alginate, yielding stiffer scaffolds. CA PEC scaffolds produced from solutions with viscosities below 300 Pa.s also showed enhanced cell proliferation compared with other samples. By controlling the key experimental parameters identified in this study, CA PEC scaffolds of different structures can be made to suit various tissue engineering applications. Copyright © 2011 Wiley Periodicals, Inc.

Cross Flow Parameter Calculation for Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

Norman, David, Jr. (Inventor)

2014-01-01

A system and method for determining a cross flow angle for a feature on a structure. A processor unit receives location information identifying a location of the feature on the structure, determines an angle of the feature, identifies flow information for the location, determines a flow angle using the flow information, and determines the cross flow angle for the feature using the flow angle and the angle of the feature. The flow information describes a flow of fluid across the structure. The flow angle comprises an angle of the flow of fluid across the structure for the location of the feature.

Structure of the Large Magellanic Cloud from near infrared magnitudes of red clump stars

NASA Astrophysics Data System (ADS)

Subramanian, S.; Subramaniam, A.

2013-04-01

Context. The structural parameters of the disk of the Large Magellanic Cloud (LMC) are estimated. Aims: We used the JH photometric data of red clump (RC) stars from the Magellanic Cloud Point Source Catalog (MCPSC) obtained from the InfraRed Survey Facility (IRSF) to estimate the structural parameters of the LMC disk, such as the inclination, i, and the position angle of the line of nodes (PAlon), φ. Methods: The observed LMC region is divided into several sub-regions, and stars in each region are cross-identified with the optically identified RC stars to obtain the near infrared magnitudes. The peak values of H magnitude and (J - H) colour of the observed RC distribution are obtained by fitting a profile to the distributions and by taking the average value of magnitude and colour of the RC stars in the bin with largest number. Then the dereddened peak H0 magnitude of the RC stars in each sub-region is obtained from the peak values of H magnitude and (J - H) colour of the observed RC distribution. The right ascension (RA), declination (Dec), and relative distance from the centre of each sub-region are converted into x,y, and z Cartesian coordinates. A weighted least square plane fitting method is applied to this x,y,z data to estimate the structural parameters of the LMC disk. Results: An intrinsic (J - H)0 colour of 0.40 ± 0.03 mag in the Simultaneous three-colour InfraRed Imager for Unbiased Survey (SIRIUS) IRSF filter system is estimated for the RC stars in the LMC and a reddening map based on (J - H) colour of the RC stars is presented. When the peaks of the RC distribution were identified by averaging, an inclination of 25°.7 ± 1°.6 and a PAlon = 141°.5 ± 4°.5 were obtained. We estimate a distance modulus, μ = 18.47 ± 0.1 mag to the LMC. Extra-planar features which are both in front and behind the fitted plane are identified. They match with the optically identified extra-planar features. The bar of the LMC is found to be part of the disk within 500 pc. Conclusions: The estimates of the structural parameters are found to be independent of the photometric bands used for the analysis. The radial variation of the structural parameters are also studied. We find that the inner disk, within ~3°.0, is less inclined and has a larger value of PAlon when compared to the outer disk. Our estimates are compared with the literature values, and the possible reasons for the small discrepancies found are discussed.

DAISY: a new software tool to test global identifiability of biological and physiological systems.

PubMed

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D'Angiò, Leontina

2007-10-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/.

Least-squares sequential parameter and state estimation for large space structures

NASA Technical Reports Server (NTRS)

Thau, F. E.; Eliazov, T.; Montgomery, R. C.

1982-01-01

This paper presents the formulation of simultaneous state and parameter estimation problems for flexible structures in terms of least-squares minimization problems. The approach combines an on-line order determination algorithm, with least-squares algorithms for finding estimates of modal approximation functions, modal amplitudes, and modal parameters. The approach combines previous results on separable nonlinear least squares estimation with a regression analysis formulation of the state estimation problem. The technique makes use of sequential Householder transformations. This allows for sequential accumulation of matrices required during the identification process. The technique is used to identify the modal prameters of a flexible beam.

Sphericity determination using resonant ultrasound spectroscopy

DOEpatents

Dixon, Raymond D.; Migliori, Albert; Visscher, William M.

1994-01-01

A method is provided for grading production quantities of spherical objects, such as roller balls for bearings. A resonant ultrasound spectrum (RUS) is generated for each spherical object and a set of degenerate sphere-resonance frequencies is identified. From the degenerate sphere-resonance frequencies and known relationships between degenerate sphere-resonance frequencies and Poisson's ratio, a Poisson's ratio can be determined, along with a "best" spherical diameter, to form spherical parameters for the sphere. From the RUS, fine-structure resonant frequency spectra are identified for each degenerate sphere-resonance frequency previously selected. From each fine-structure spectrum and associated sphere parameter values an asphericity value is determined. The asphericity value can then be compared with predetermined values to provide a measure for accepting or rejecting the sphere.

Sphericity determination using resonant ultrasound spectroscopy

DOEpatents

Dixon, R.D.; Migliori, A.; Visscher, W.M.

1994-10-18

A method is provided for grading production quantities of spherical objects, such as roller balls for bearings. A resonant ultrasound spectrum (RUS) is generated for each spherical object and a set of degenerate sphere-resonance frequencies is identified. From the degenerate sphere-resonance frequencies and known relationships between degenerate sphere-resonance frequencies and Poisson's ratio, a Poisson's ratio can be determined, along with a 'best' spherical diameter, to form spherical parameters for the sphere. From the RUS, fine-structure resonant frequency spectra are identified for each degenerate sphere-resonance frequency previously selected. From each fine-structure spectrum and associated sphere parameter values an asphericity value is determined. The asphericity value can then be compared with predetermined values to provide a measure for accepting or rejecting the sphere. 14 figs.

Parameter identification of thermophilic anaerobic degradation of valerate.

PubMed

Flotats, Xavier; Ahring, Birgitte K; Angelidaki, Irini

2003-01-01

The considered mathematical model of the decomposition of valerate presents three unknown kinetic parameters, two unknown stoichiometric coefficients, and three unknown initial concentrations for biomass. Applying a structural identifiability study, we concluded that it is necessary to perform simultaneous batch experiments with different initial conditions for estimating these parameters. Four simultaneous batch experiments were conducted at 55 degrees C, characterized by four different initial acetate concentrations. Product inhibition of valerate degradation by acetate was considered. Practical identification was done optimizing the sum of the multiple determination coefficients for all measured state variables and for all experiments simultaneously. The estimated values of kinetic parameters and stoichiometric coefficients were characterized by the parameter correlation matrix, the confidence interval, and the student's t-test at 5% significance level with positive results except for the saturation constant, for which more experiments for improving its identifiability should be conducted. In this article, we discuss kinetic parameter estimation methods.

Matching experimental and three dimensional numerical models for structural vibration problems with uncertainties

NASA Astrophysics Data System (ADS)

Langer, P.; Sepahvand, K.; Guist, C.; Bär, J.; Peplow, A.; Marburg, S.

2018-03-01

The simulation model which examines the dynamic behavior of real structures needs to address the impact of uncertainty in both geometry and material parameters. This article investigates three-dimensional finite element models for structural dynamics problems with respect to both model and parameter uncertainties. The parameter uncertainties are determined via laboratory measurements on several beam-like samples. The parameters are then considered as random variables to the finite element model for exploring the uncertainty effects on the quality of the model outputs, i.e. natural frequencies. The accuracy of the output predictions from the model is compared with the experimental results. To this end, the non-contact experimental modal analysis is conducted to identify the natural frequency of the samples. The results show a good agreement compared with experimental data. Furthermore, it is demonstrated that geometrical uncertainties have more influence on the natural frequencies compared to material parameters and material uncertainties are about two times higher than geometrical uncertainties. This gives valuable insights for improving the finite element model due to various parameter ranges required in a modeling process involving uncertainty.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Review: To be or not to be an identifiable model. Is this a relevant question in animal science modelling?

PubMed

Muñoz-Tamayo, R; Puillet, L; Daniel, J B; Sauvant, D; Martin, O; Taghipoor, M; Blavy, P

2018-04-01

What is a good (useful) mathematical model in animal science? For models constructed for prediction purposes, the question of model adequacy (usefulness) has been traditionally tackled by statistical analysis applied to observed experimental data relative to model-predicted variables. However, little attention has been paid to analytic tools that exploit the mathematical properties of the model equations. For example, in the context of model calibration, before attempting a numerical estimation of the model parameters, we might want to know if we have any chance of success in estimating a unique best value of the model parameters from available measurements. This question of uniqueness is referred to as structural identifiability; a mathematical property that is defined on the sole basis of the model structure within a hypothetical ideal experiment determined by a setting of model inputs (stimuli) and observable variables (measurements). Structural identifiability analysis applied to dynamic models described by ordinary differential equations (ODEs) is a common practice in control engineering and system identification. This analysis demands mathematical technicalities that are beyond the academic background of animal science, which might explain the lack of pervasiveness of identifiability analysis in animal science modelling. To fill this gap, in this paper we address the analysis of structural identifiability from a practitioner perspective by capitalizing on the use of dedicated software tools. Our objectives are (i) to provide a comprehensive explanation of the structural identifiability notion for the community of animal science modelling, (ii) to assess the relevance of identifiability analysis in animal science modelling and (iii) to motivate the community to use identifiability analysis in the modelling practice (when the identifiability question is relevant). We focus our study on ODE models. By using illustrative examples that include published mathematical models describing lactation in cattle, we show how structural identifiability analysis can contribute to advancing mathematical modelling in animal science towards the production of useful models and, moreover, highly informative experiments via optimal experiment design. Rather than attempting to impose a systematic identifiability analysis to the modelling community during model developments, we wish to open a window towards the discovery of a powerful tool for model construction and experiment design.

Resolving structural influences on water-retention properties of alluvial deposits

USGS Publications Warehouse

Winfield, K.A.; Nimmo, J.R.; Izbicki, J.A.; Martin, P.M.

2006-01-01

With the goal of improving property-transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory-measured water retention (water content vs. potential [??(??)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris-flow structure based on observed stratification and measured spread of particle-size distribution. The ??(??) data were fit with the Rossi-Nimmo junction model, representing water retention with three parameters: the maximum water content (??max), the ??-scaling parameter (??o), and the shape parameter (??). We examined trends between these hydraulic parameters and bulk physical properties, both textural - geometric mean, Mg, and geometric standard deviation, ??g, of particle diameter - and structural - bulk density, ??b, the fraction of unfilled pore space at natural saturation, Ae, and porosity-based randomness index, ??s, defined as the excess of total porosity over 0.3. Structural parameters ??s and Ae were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore-size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for ??max, including Ae, ??s, and ??g, and for both ??o and ??, including only textural parameters, although use of Ae can somewhat improve ??o predictions. Textural properties can explain most of the sample-to-sample variation in ??(??) independent of deposit type, but inclusion of the simple structural indicators Ae and ??s can improve PTM predictions, especially for the wettest part of the ??(??) curve. ?? Soil Science Society of America.

A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling

ERIC Educational Resources Information Center

Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang

2017-01-01

It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…

RMB identification based on polarization parameters inversion imaging

NASA Astrophysics Data System (ADS)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

Social order is threatened by counterfeit money. Conventional anti-counterfeit technology is much too old to identify its authenticity or not. The intrinsic difference between genuine notes and counterfeit notes is its paper tissue. In this paper a new technology of detecting RMB is introduced, the polarization parameter indirect microscopic imaging technique. A conventional reflection microscopic system is used as the basic optical system, and inserting into it with polarization-modulation mechanics. The near-field structural characteristics can be delivered by optical wave and material coupling. According to coupling and conduction physics, calculate the changes of optical wave parameters, then get the curves of the intensity of the image. By analyzing near-field polarization parameters in nanoscale, finally calculate indirect polarization parameter imaging of the fiber of the paper tissue in order to identify its authenticity.

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

Rohrbaugh, Wayne Joseph

Results are reported from an investigation of correlations between molecular structural parameters of selected organophosphorus insecticides and their corresponding toxic effectiveness. The crystal and molecular structures of azinphos-methyl, emidithion, and tetrachlorvinphos were determined via three-dimensional x-ray analysis. Acetylcholinesterase (AChE) in nerve cells was identified as the target for organophosphorus insecticides.

Analysis of the structural behaviour of colonic segments by inflation tests: Experimental activity and physio-mechanical model.

PubMed

Carniel, Emanuele L; Mencattelli, Margherita; Bonsignori, Gabriella; Fontanella, Chiara G; Frigo, Alessandro; Rubini, Alessandro; Stefanini, Cesare; Natali, Arturo N

2015-11-01

A coupled experimental and computational approach is provided for the identification of the structural behaviour of gastrointestinal regions, accounting for both elastic and visco-elastic properties. The developed procedure is applied to characterize the mechanics of gastrointestinal samples from pig colons. Experimental data about the structural behaviour of colonic segments are provided by inflation tests. Different inflation processes are performed according to progressively increasing top pressure conditions. Each inflation test consists of an air in-flow, according to an almost constant increasing pressure rate, such as 3.5 mmHg/s, up to a prescribed top pressure, which is held constant for about 300 s to allow the development of creep phenomena. Different tests are interspersed by 600 s of rest to allow the recovery of the tissues' mechanical condition. Data from structural tests are post-processed by a physio-mechanical model in order to identify the mechanical parameters that interpret both the non-linear elastic behaviour of the sample, as the instantaneous pressure-stretch trend, and the time-dependent response, as the stretch increase during the creep processes. The parameters are identified by minimizing the discrepancy between experimental and model results. Different sets of parameters are evaluated for different specimens from different pigs. A statistical analysis is performed to evaluate the distribution of the parameters and to assess the reliability of the experimental and computational activities. © IMechE 2015.

Identifiability of conservative linear mechanical systems. [applied to large flexible spacecraft structures

NASA Technical Reports Server (NTRS)

Sirlin, S. W.; Longman, R. W.; Juang, J. N.

1985-01-01

With a sufficiently great number of sensors and actuators, any finite dimensional dynamic system is identifiable on the basis of input-output data. It is presently indicated that, for conservative nongyroscopic linear mechanical systems, the number of sensors and actuators required for identifiability is very large, where 'identifiability' is understood as a unique determination of the mass and stiffness matrices. The required number of sensors and actuators drops by a factor of two, given a relaxation of the identifiability criterion so that identification can fail only if the system parameters being identified lie in a set of measure zero. When the mass matrix is known a priori, this additional information does not significantly affect the requirements for guaranteed identifiability, though the number of parameters to be determined is reduced by a factor of two.

Global identifiability of linear compartmental models--a computer algebra algorithm.

PubMed

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Geometric parameter analysis to predetermine optimal radiosurgery technique for the treatment of arteriovenous malformation

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

Mestrovic, Ante; Clark, Brenda G.; Department of Medical Physics, British Columbia Cancer Agency, Vancouver, British Columbia

2005-11-01

Purpose: To develop a method of predicting the values of dose distribution parameters of different radiosurgery techniques for treatment of arteriovenous malformation (AVM) based on internal geometric parameters. Methods and Materials: For each of 18 previously treated AVM patients, four treatment plans were created: circular collimator arcs, dynamic conformal arcs, fixed conformal fields, and intensity-modulated radiosurgery. An algorithm was developed to characterize the target and critical structure shape complexity and the position of the critical structures with respect to the target. Multiple regression was employed to establish the correlation between the internal geometric parameters and the dose distribution for differentmore » treatment techniques. The results from the model were applied to predict the dosimetric outcomes of different radiosurgery techniques and select the optimal radiosurgery technique for a number of AVM patients. Results: Several internal geometric parameters showing statistically significant correlation (p < 0.05) with the treatment planning results for each technique were identified. The target volume and the average minimum distance between the target and the critical structures were the most effective predictors for normal tissue dose distribution. The structure overlap volume with the target and the mean distance between the target and the critical structure were the most effective predictors for critical structure dose distribution. The predicted values of dose distribution parameters of different radiosurgery techniques were in close agreement with the original data. Conclusions: A statistical model has been described that successfully predicts the values of dose distribution parameters of different radiosurgery techniques and may be used to predetermine the optimal technique on a patient-to-patient basis.« less

Maps on statistical manifolds exactly reduced from the Perron-Frobenius equations for solvable chaotic maps

NASA Astrophysics Data System (ADS)

Goto, Shin-itiro; Umeno, Ken

2018-03-01

Maps on a parameter space for expressing distribution functions are exactly derived from the Perron-Frobenius equations for a generalized Boole transform family. Here the generalized Boole transform family is a one-parameter family of maps, where it is defined on a subset of the real line and its probability distribution function is the Cauchy distribution with some parameters. With this reduction, some relations between the statistical picture and the orbital one are shown. From the viewpoint of information geometry, the parameter space can be identified with a statistical manifold, and then it is shown that the derived maps can be characterized. Also, with an induced symplectic structure from a statistical structure, symplectic and information geometric aspects of the derived maps are discussed.

Relationship between bacterial diversity and environmental parameters during composting of different raw materials.

PubMed

Wang, Xueqin; Cui, Hongyang; Shi, Jianhong; Zhao, Xinyu; Zhao, Yue; Wei, Zimin

2015-12-01

The aim of this study was to compare the bacterial structure of seven different composts. The primary environmental factors affecting bacterial species were identified, and a strategy to enhance the abundance of uncultured bacteria through controlling relevant environmental parameters was proposed. The results showed that the physical-chemical parameters of each different pile changed in its own manner during composting, which affected the structure and succession of bacteria in different ways. DGGE profiles showed that there were 10 prominent species during composting. Among them, four species existed in all compost types, two species existed in several piles and four species were detected in a single material. Redundancy analysis results showed that bacterial species compositions were significantly influenced by C/N and moisture (p<0.05). The optimal range of C/N was 14-27. Based on these results, the primary environmental factors affecting a certain species were further identified as a potential control of bacterial diversity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Progressive fracture of polymer matrix composite structures: A new approach

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Minnetyan, L.

1992-01-01

A new approach independent of stress intensity factors and fracture toughness parameters has been developed and is described for the computational simulation of progressive fracture of polymer matrix composite structures. The damage stages are quantified based on physics via composite mechanics while the degradation of the structural behavior is quantified via the finite element method. The approach account for all types of composite behavior, structures, load conditions, and fracture processes starting from damage initiation, to unstable propagation and to global structural collapse. Results of structural fracture in composite beams, panels, plates, and shells are presented to demonstrate the effectiveness and versatility of this new approach. Parameters and guidelines are identified which can be used as criteria for structural fracture, inspection intervals, and retirement for cause. Generalization to structures made of monolithic metallic materials are outlined and lessons learned in undertaking the development of new approaches, in general, are summarized.

Diseases that turn African hair silky.

PubMed

Ajose, Frances O A

2012-11-01

African hair in its natural state poses tenacious grooming challenges; consequently a large portion of the African cosmetic industry is focused on means to relax the tight curls of African hair to make the hair more manageable. In malnourished and hypoproteinemic states, African hair straightens in an uncomplimentary manner. Recently, we observed that in certain diseases African hair changes to a desirable silky wavy texture. To identify the diseases that turn African hair silky and their parameters we examined 5612 dermatology patients at a tertiary hospital in Nigeria. We then studied the clinical and basic laboratory parameters of those patients whose diseases were accompanied by the silky hair change. Silky hair change similar to the hair of the African neonatal child was observed in five diseases, namely AIDS, rheumatoid arthritis, systemic lupus erythematosus, pulmonary tuberculosis with cachexia, and Behçet's disease. Our study identified retrogression of African hair to the neonatal structure in five diseases. Anemia of chronic illness, high erythrocyte sedimentation rate, and mild hypocalcemia were significant laboratory parameters. This is an important observation, which should excite and advance research into the nature and structure of African hair. The causes of structural hair changes should include these five diseases. © 2012 The International Society of Dermatology.

Structural damage identification using an enhanced thermal exchange optimization algorithm

NASA Astrophysics Data System (ADS)

Kaveh, A.; Dadras, A.

2018-03-01

The recently developed optimization algorithm-the so-called thermal exchange optimization (TEO) algorithm-is enhanced and applied to a damage detection problem. An offline parameter tuning approach is utilized to set the internal parameters of the TEO, resulting in the enhanced heat transfer optimization (ETEO) algorithm. The damage detection problem is defined as an inverse problem, and ETEO is applied to a wide range of structures. Several scenarios with noise and noise-free modal data are tested and the locations and extents of damages are identified with good accuracy.

DAISY: a new software tool to test global identifiability of biological and physiological systems

PubMed Central

Bellu, Giuseppina; Saccomani, Maria Pia; Audoly, Stefania; D’Angiò, Leontina

2009-01-01

A priori global identifiability is a structural property of biological and physiological models. It is considered a prerequisite for well-posed estimation, since it concerns the possibility of recovering uniquely the unknown model parameters from measured input-output data, under ideal conditions (noise-free observations and error-free model structure). Of course, determining if the parameters can be uniquely recovered from observed data is essential before investing resources, time and effort in performing actual biomedical experiments. Many interesting biological models are nonlinear but identifiability analysis for nonlinear system turns out to be a difficult mathematical problem. Different methods have been proposed in the literature to test identifiability of nonlinear models but, to the best of our knowledge, so far no software tools have been proposed for automatically checking identifiability of nonlinear models. In this paper, we describe a software tool implementing a differential algebra algorithm to perform parameter identifiability analysis for (linear and) nonlinear dynamic models described by polynomial or rational equations. Our goal is to provide the biological investigator a completely automatized software, requiring minimum prior knowledge of mathematical modelling and no in-depth understanding of the mathematical tools. The DAISY (Differential Algebra for Identifiability of SYstems) software will potentially be useful in biological modelling studies, especially in physiology and clinical medicine, where research experiments are particularly expensive and/or difficult to perform. Practical examples of use of the software tool DAISY are presented. DAISY is available at the web site http://www.dei.unipd.it/~pia/. PMID:17707944

Parameter identification for structural dynamics based on interval analysis algorithm

NASA Astrophysics Data System (ADS)

Yang, Chen; Lu, Zixing; Yang, Zhenyu; Liang, Ke

2018-04-01

A parameter identification method using interval analysis algorithm for structural dynamics is presented in this paper. The proposed uncertain identification method is investigated by using central difference method and ARMA system. With the help of the fixed memory least square method and matrix inverse lemma, a set-membership identification technology is applied to obtain the best estimation of the identified parameters in a tight and accurate region. To overcome the lack of insufficient statistical description of the uncertain parameters, this paper treats uncertainties as non-probabilistic intervals. As long as we know the bounds of uncertainties, this algorithm can obtain not only the center estimations of parameters, but also the bounds of errors. To improve the efficiency of the proposed method, a time-saving algorithm is presented by recursive formula. At last, to verify the accuracy of the proposed method, two numerical examples are applied and evaluated by three identification criteria respectively.

Ab initio phasing based on topological restraints: automated determination of the space group and the number of molecules in the unit cell.

PubMed

Urzhumtseva, Ludmila; Lunina, Natalia; Fokine, Andrei; Samama, Jean Pierre; Lunin, Vladimir Y; Urzhumtsev, Alexandre

2004-09-01

The connectivity-based phasing method has been demonstrated to be capable of finding molecular packing and envelopes even for difficult cases of structure determination, as well as of identifying, in favorable cases, secondary-structure elements of protein molecules in the crystal. This method uses a single set of structure factor magnitudes and general topological features of a crystallographic image of the macromolecule under study. This information is expressed through a number of parameters. Most of these parameters are easy to estimate, and the results of phasing are practically independent of these parameters when they are chosen within reasonable limits. By contrast, the correct choice for such parameters as the expected number of connected regions in the unit cell is sometimes ambiguous. To study these dependencies, numerous tests were performed with simulated data, experimental data and mixed data sets, where several reflections missed in the experiment were completed by computed data. This paper demonstrates that the procedure is able to control this choice automatically and helps in difficult cases to identify the correct number of molecules in the asymmetric unit. In addition, the procedure behaves abnormally if the space group is defined incorrectly and therefore may distinguish between the rotation and screw axes even when high-resolution data are not available.

Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data.

PubMed

Florescu, Dorian; Coca, Daniel

2018-03-01

Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms.

Structural Analysis of Cubane-Type Iron Clusters

PubMed Central

Tan, Lay Ling; Holm, R. H.; Lee, Sonny C.

2013-01-01

The generalized cluster type [M4(μ3-Q)4Ln]x contains the cubane-type [M4Q4]z core unit that can approach, but typically deviates from, perfect Td symmetry. The geometric properties of this structure have been analyzed with reference to Td symmetry by a new protocol. Using coordinates of M and Q atoms, expressions have been derived for interatomic separations, bond angles, and volumes of tetrahedral core units (M4, Q4) and the total [M4Q4] core (as a tetracapped M4 tetrahedron). Values for structural parameters have been calculated from observed average values for a given cluster type. Comparison of calculated and observed values measures the extent of deviation of a given parameter from that required in an exact tetrahedral structure. The procedure has been applied to the structures of over 130 clusters containing [Fe4Q4] (Q = S2−, Se2−, Te2−, [NPR3]−, [NR]2−) units, of which synthetic and biological sulfide-bridged clusters constitute the largest subset. General structural features and trends in structural parameters are identified and summarized. An extensive database of structural properties (distances, angles, volumes) has been compiled in Supporting Information. PMID:24072952

Structural Analysis of Cubane-Type Iron Clusters.

PubMed

Tan, Lay Ling; Holm, R H; Lee, Sonny C

2013-07-13

The generalized cluster type [M 4 (μ 3 -Q) 4 L n ] x contains the cubane-type [M 4 Q 4 ] z core unit that can approach, but typically deviates from, perfect T d symmetry. The geometric properties of this structure have been analyzed with reference to T d symmetry by a new protocol. Using coordinates of M and Q atoms, expressions have been derived for interatomic separations, bond angles, and volumes of tetrahedral core units (M 4 , Q 4 ) and the total [M 4 Q 4 ] core (as a tetracapped M 4 tetrahedron). Values for structural parameters have been calculated from observed average values for a given cluster type. Comparison of calculated and observed values measures the extent of deviation of a given parameter from that required in an exact tetrahedral structure. The procedure has been applied to the structures of over 130 clusters containing [Fe 4 Q 4 ] (Q = S 2- , Se 2- , Te 2- , [NPR 3 ] - , [NR] 2- ) units, of which synthetic and biological sulfide-bridged clusters constitute the largest subset. General structural features and trends in structural parameters are identified and summarized. An extensive database of structural properties (distances, angles, volumes) has been compiled in Supporting Information.

An overview of STRUCTURE: applications, parameter settings, and supporting software

PubMed Central

Porras-Hurtado, Liliana; Ruiz, Yarimar; Santos, Carla; Phillips, Christopher; Carracedo, Ángel; Lareu, Maria V.

2013-01-01

Objectives: We present an up-to-date review of STRUCTURE software: one of the most widely used population analysis tools that allows researchers to assess patterns of genetic structure in a set of samples. STRUCTURE can identify subsets of the whole sample by detecting allele frequency differences within the data and can assign individuals to those sub-populations based on analysis of likelihoods. The review covers STRUCTURE's most commonly used ancestry and frequency models, plus an overview of the main applications of the software in human genetics including case-control association studies (CCAS), population genetics, and forensic analysis. The review is accompanied by supplementary material providing a step-by-step guide to running STRUCTURE. Methods: With reference to a worked example, we explore the effects of changing the principal analysis parameters on STRUCTURE results when analyzing a uniform set of human genetic data. Use of the supporting software: CLUMPP and distruct is detailed and we provide an overview and worked example of STRAT software, applicable to CCAS. Conclusion: The guide offers a simplified view of how STRUCTURE, CLUMPP, distruct, and STRAT can be applied to provide researchers with an informed choice of parameter settings and supporting software when analyzing their own genetic data. PMID:23755071

Multiple regimes of robust patterns between network structure and biodiversity

NASA Astrophysics Data System (ADS)

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-12-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities.

Multiple regimes of robust patterns between network structure and biodiversity

PubMed Central

Jover, Luis F.; Flores, Cesar O.; Cortez, Michael H.; Weitz, Joshua S.

2015-01-01

Ecological networks such as plant-pollinator and host-parasite networks have structured interactions that define who interacts with whom. The structure of interactions also shapes ecological and evolutionary dynamics. Yet, there is significant ongoing debate as to whether certain structures, e.g., nestedness, contribute positively, negatively or not at all to biodiversity. We contend that examining variation in life history traits is key to disentangling the potential relationship between network structure and biodiversity. Here, we do so by analyzing a dynamic model of virus-bacteria interactions across a spectrum of network structures. Consistent with prior studies, we find plausible parameter domains exhibiting strong, positive relationships between nestedness and biodiversity. Yet, the same model can exhibit negative relationships between nestedness and biodiversity when examined in a distinct, plausible region of parameter space. We discuss steps towards identifying when network structure could, on its own, drive the resilience, sustainability, and even conservation of ecological communities. PMID:26632996

Reliability analysis of composite structures

NASA Technical Reports Server (NTRS)

Kan, Han-Pin

1992-01-01

A probabilistic static stress analysis methodology has been developed to estimate the reliability of a composite structure. Closed form stress analysis methods are the primary analytical tools used in this methodology. These structural mechanics methods are used to identify independent variables whose variations significantly affect the performance of the structure. Once these variables are identified, scatter in their values is evaluated and statistically characterized. The scatter in applied loads and the structural parameters are then fitted to appropriate probabilistic distribution functions. Numerical integration techniques are applied to compute the structural reliability. The predicted reliability accounts for scatter due to variability in material strength, applied load, fabrication and assembly processes. The influence of structural geometry and mode of failure are also considerations in the evaluation. Example problems are given to illustrate various levels of analytical complexity.

Web-ware bioinformatical analysis and structure modelling of N-terminus of human multisynthetase complex auxiliary component protein p43.

PubMed

Deineko, Viktor

2006-01-01

Human multisynthetase complex auxiliary component, protein p43 is an endothelial monocyte-activating polypeptide II precursor. In this study, comprehensive sequence analysis of N-terminus has been performed to identify structural domains, motifs, sites of post-translation modification and other functionally important parameters. The spatial structure model of full-chain protein p43 is obtained.

Structural modal parameter identification using local mean decomposition

NASA Astrophysics Data System (ADS)

Keyhani, Ali; Mohammadi, Saeed

2018-02-01

Modal parameter identification is the first step in structural health monitoring of existing structures. Already, many powerful methods have been proposed for this concept and each method has some benefits and shortcomings. In this study, a new method based on local mean decomposition is proposed for modal identification of civil structures from free or ambient vibration measurements. The ability of the proposed method was investigated using some numerical studies and the results compared with those obtained from the Hilbert-Huang transform (HHT). As a major advantage, the proposed method can extract natural frequencies and damping ratios of all active modes from only one measurement. The accuracy of the identified modes depends on their participation in the measured responses. Nevertheless, the identified natural frequencies have reasonable accuracy in both cases of free and ambient vibration measurements, even in the presence of noise. The instantaneous phase angle and the natural logarithm of instantaneous amplitude curves obtained from the proposed method have more linearity rather than those from the HHT algorithm. Also, the end effect is more restricted for the proposed method.

[Crop geometry identification based on inversion of semiempirical BRDF models].

PubMed

Huang, Wen-jiang; Wang, Jin-di; Mu, Xi-han; Wang, Ji-hua; Liu, Liang-yun; Liu, Qiang; Niu, Zheng

2007-10-01

Investigations have been made on identification of erective and horizontal varieties by bidirectional canopy reflected spectrum and semi-empirical bidirectional reflectance distribution function (BRDF) models. The qualitative effect of leaf area index (LAI) and average leaf angle (ALA) on crop canopy reflected spectrum was studied. The structure parameter sensitive index (SPEI) based on the weight for the volumetric kernel (fvol), the weight for the geometric kernel (fgeo), and the weight for constant corresponding to isotropic reflectance (fiso), was defined in the present study for crop geometry identification. However, the weights associated with the kernels of semi-empirical BRDF model do not have a direct relationship with measurable biophysical parameters. Therefore, efforts have focused on trying to find the relation between these semi-empirical BRDF kernel weights and various vegetation structures. SPEI was proved to be more sensitive to identify crop geometry structures than structural scattering index (SSI) and normalized difference f-index (NDFI), SPEI could be used to distinguish erective and horizontal geometry varieties. So, it is feasible to identify horizontal and erective varieties of wheat by bidirectional canopy reflected spectrum.

The wavelet transform as an analysis tool for structure identification in molecular clouds

NASA Astrophysics Data System (ADS)

Gill, Arnold Gerald

1993-01-01

Of the many methods used to attempt to understand the complex structure of giant molecular clouds, perhaps the most commonly used are the autocorrelation functions (ACF), the structure function, and the power spectrum. However, these do not give unique interpretations of structure, as is shown by explicit examples compared to the Taurus Molecular Complex. Thus, another, independent method of analysis is indicated. Here, the wavelet transform is presented, a relatively new technique less than 10 years old. It can be thought of as a band-pass filter that identifies structures of specific sizes. In addition, its mathematical properties allow it to be used to identify fractal structures and accurately identify the scaling exponent. This is shown by the wavelet transform identifying the fractal dimension of a hierarchical rain cloud model first proposed by Frisch et al. (1978). A wavelet analysis is then carried out for a range of astronomical CO data, including the clouds Orion A and B and NGC 7538 (in (12)CO) and Orion A and B, Mon R2, and L1551 (in (13)CO). The data analyzed consists of the velocities of the fitted Gaussians to the individual spectra, the halfwidths and amplitude of these Gaussians, and the total area of the spectral line. For most of the clouds investigated, each of these data types showed a very high degree of scaling coherence over a wide range of scales, from down at the beam spacing up to the full size of the cloud. The analysis carried out uses both the scaling and structure identification strengths of the wavelet transform The fragmentation parameters used by Scalo (1985) and the parameters of the geometric molecular cloud description introduced by Henriksen (1986) are calculated for each cloud. These results are all consistent with previous observations of these and other molecular clouds, though they are obtained individually for each cloud investigated. It is found that the uncertainties are of a magnitude that the differentiation of various theories of molecular cloud structure is not possible. It is noted that the effects of projection and superposition strongly affect the values of some of these parameters, thus hampering a thorough understanding of the underlying physics. The strengths and weaknesses of the wavelet transform in the analysis of molecular cloud data are presented, as well as directions for future work.

Experimental identification of closely spaced modes using NExT-ERA

NASA Astrophysics Data System (ADS)

Hosseini Kordkheili, S. A.; Momeni Massouleh, S. H.; Hajirezayi, S.; Bahai, H.

2018-01-01

This article presents a study on the capability of the time domain OMA method, NExT-ERA, to identify closely spaced structural dynamic modes. A survey in the literature reveals that few experimental studies have been conducted on the effectiveness of the NExT-ERA methodology in case of closely spaced modes specifically. In this paper we present the formulation for NExT-ERA. This formulation is then implemented in an algorithm and a code, developed in house to identify the modal parameters of different systems using their generated time history data. Some numerical models are firstly investigated to validate the code. Two different case studies involving a plate with closely spaced modes and a pulley ring with greater extent of closeness in repeated modes are presented. Both structures are excited by random impulses under the laboratory condition. The resulting time response acceleration data are then used as input in the developed code to extract modal parameters of the structures. The accuracy of the results is checked against those obtained from experimental tests.

Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

PubMed Central

Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

2013-01-01

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

A modified PATH algorithm rapidly generates transition states comparable to those found by other well established algorithms

PubMed Central

Chandrasekaran, Srinivas Niranj; Das, Jhuma; Dokholyan, Nikolay V.; Carter, Charles W.

2016-01-01

PATH rapidly computes a path and a transition state between crystal structures by minimizing the Onsager-Machlup action. It requires input parameters whose range of values can generate different transition-state structures that cannot be uniquely compared with those generated by other methods. We outline modifications to estimate these input parameters to circumvent these difficulties and validate the PATH transition states by showing consistency between transition-states derived by different algorithms for unrelated protein systems. Although functional protein conformational change trajectories are to a degree stochastic, they nonetheless pass through a well-defined transition state whose detailed structural properties can rapidly be identified using PATH. PMID:26958584

The strength study of the rotating device driver indexing spatial mechanism

NASA Astrophysics Data System (ADS)

Zakharenkov, N. V.; Kvasov, I. N.

2018-04-01

The indexing spatial mechanisms are widely used in automatic machines. The mechanisms maximum load-bearing capacity measurement is possible based on both the physical and numerical models tests results. The paper deals with the driven disk indexing spatial cam mechanism numerical model at the constant angular cam velocity. The presented mechanism kinematics and geometry parameters and finite element model are analyzed in the SolidWorks design environment. The calculation initial data and missing parameters having been found from the structure analysis were identified. The structure and kinematics analysis revealed the mechanism failures possible reasons. The numerical calculations results showing the structure performance at the contact and bending stresses are represented.

Noise elimination algorithm for modal analysis

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

Bao, X. X., E-mail: baoxingxian@upc.edu.cn; Li, C. L.; Xiong, C. B.

2015-07-27

Modal analysis is an ongoing interdisciplinary physical issue. Modal parameters estimation is applied to determine the dynamic characteristics of structures under vibration excitation. Modal analysis is more challenging for the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of structured low rank approximation combined with the complex exponential method to estimate the modal parameters. Physical experiments using a steel cantilever beam with ten accelerometers mounted, excited by an impulse load, demonstrate that this method can significantly eliminate noise from measured signals and accurately identify the modal frequencies and damping ratios. This study provides amore » fundamental mechanism of noise elimination using structured low rank approximation in physical fields.« less

Effect of Discontinuities and Uncertainties on the Response and Failure of Composite Structures

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Perry, Ferman W.; Poteat, Marcia M. (Technical Monitor)

2000-01-01

The overall goal of this research was to assess the effect of discontinuities and uncertainties on the nonlinear response and failure of composite structures subjected to combined mechanical and thermal loads. The four key elements of the study were: (1) development of simple and efficient procedures for the accurate determination of transverse shear and transverse normal stresses in structural sandwiches as well as in unstiffened and stiffened composite panels and shells; (2) study the effects of transverse stresses on the response, damage initiation and propagation in composite and sandwich structures; (3) use of hierarchical sensitivity coefficients to identify the major parameters that affect the response and damage in each of the different levels in the hierarchy (micro-mechanical, layer, panel, subcomponent and component levels); and (4) application of fuzzy set techniques to identify the range and variation of possible responses. The computational models developed were used in conjunction with experiments, to understand the physical phenomena associated with the nonlinear response and failure of composite and sandwich structures. A toolkit was developed for use in conjunction with deterministic analysis programs to help the designer in assessing the effect of uncertainties in the different computational model parameters on the variability of the response quantities.

Formation of porous networks on polymeric surfaces by femtosecond laser micromachining

NASA Astrophysics Data System (ADS)

Assaf, Youssef; Kietzig, Anne-Marie

2017-02-01

In this study, porous network structures were successfully created on various polymer surfaces by femtosecond laser micromachining. Six different polymers (poly(tetrafluoroethylene) (PTFE), poly(methyl methacrylate) (PMMA), high density poly(ethylene) (HDPE), poly(lactic acid) (PLA), poly(carbonate) (PC), and poly(ethylene terephthalate) (PET)) were machined at different fluences and pulse numbers, and the resulting structures were identified and compared by lacunarity analysis. At low fluence and pulse numbers, porous networks were confirmed to form on all materials except PLA. Furthermore, all networks except for PMMA were shown to bundle up at high fluence and pulse numbers. In the case of PC, a complete breakdown of the structure at such conditions was observed. Operation slightly above threshold fluence and at low pulse numbers is therefore recommended for porous network formation. Finally, the thickness over which these structures formed was measured and compared to two intrinsic material dependent parameters: the single pulse threshold fluence and the incubation coefficient. Results indicate that a lower threshold fluence at operating conditions favors material removal over structure formation and is hence detrimental to porous network formation. Favorable machining conditions and material-dependent parameters for the formation of porous networks on polymer surfaces have thus been identified.

Global asymptotic stability of density dependent integral population projection models.

PubMed

Rebarber, Richard; Tenhumberg, Brigitte; Townley, Stuart

2012-02-01

Many stage-structured density dependent populations with a continuum of stages can be naturally modeled using nonlinear integral projection models. In this paper, we study a trichotomy of global stability result for a class of density dependent systems which include a Platte thistle model. Specifically, we identify those systems parameters for which zero is globally asymptotically stable, parameters for which there is a positive asymptotically stable equilibrium, and parameters for which there is no asymptotically stable equilibrium. Copyright © 2011 Elsevier Inc. All rights reserved.

Identification of damage in composite structures using Gaussian mixture model-processed Lamb waves

NASA Astrophysics Data System (ADS)

Wang, Qiang; Ma, Shuxian; Yue, Dong

2018-04-01

Composite materials have comprehensively better properties than traditional materials, and therefore have been more and more widely used, especially because of its higher strength-weight ratio. However, the damage of composite structures is usually varied and complicated. In order to ensure the security of these structures, it is necessary to monitor and distinguish the structural damage in a timely manner. Lamb wave-based structural health monitoring (SHM) has been proved to be effective in online structural damage detection and evaluation; furthermore, the characteristic parameters of the multi-mode Lamb wave varies in response to different types of damage in the composite material. This paper studies the damage identification approach for composite structures using the Lamb wave and the Gaussian mixture model (GMM). The algorithm and principle of the GMM, and the parameter estimation, is introduced. Multi-statistical characteristic parameters of the excited Lamb waves are extracted, and the parameter space with reduced dimensions is adopted by principal component analysis (PCA). The damage identification system using the GMM is then established through training. Experiments on a glass fiber-reinforced epoxy composite laminate plate are conducted to verify the feasibility of the proposed approach in terms of damage classification. The experimental results show that different types of damage can be identified according to the value of the likelihood function of the GMM.

Total systems design analysis of high performance structures

NASA Technical Reports Server (NTRS)

Verderaime, V.

1993-01-01

Designer-control parameters were identified at interdiscipline interfaces to optimize structural systems performance and downstream development and operations with reliability and least life-cycle cost. Interface tasks and iterations are tracked through a matrix of performance disciplines integration versus manufacturing, verification, and operations interactions for a total system design analysis. Performance integration tasks include shapes, sizes, environments, and materials. Integrity integrating tasks are reliability and recurring structural costs. Significant interface designer control parameters were noted as shapes, dimensions, probability range factors, and cost. Structural failure concept is presented, and first-order reliability and deterministic methods, benefits, and limitations are discussed. A deterministic reliability technique combining benefits of both is proposed for static structures which is also timely and economically verifiable. Though launch vehicle environments were primarily considered, the system design process is applicable to any surface system using its own unique filed environments.

Two-dimensional joint inversion of Magnetotelluric and local earthquake data: Discussion on the contribution to the solution of deep subsurface structures

NASA Astrophysics Data System (ADS)

Demirci, İsmail; Dikmen, Ünal; Candansayar, M. Emin

2018-02-01

Joint inversion of data sets collected by using several geophysical exploration methods has gained importance and associated algorithms have been developed. To explore the deep subsurface structures, Magnetotelluric and local earthquake tomography algorithms are generally used individually. Due to the usage of natural resources in both methods, it is not possible to increase data quality and resolution of model parameters. For this reason, the solution of the deep structures with the individual usage of the methods cannot be fully attained. In this paper, we firstly focused on the effects of both Magnetotelluric and local earthquake data sets on the solution of deep structures and discussed the results on the basis of the resolving power of the methods. The presence of deep-focus seismic sources increase the resolution of deep structures. Moreover, conductivity distribution of relatively shallow structures can be solved with high resolution by using MT algorithm. Therefore, we developed a new joint inversion algorithm based on the cross gradient function in order to jointly invert Magnetotelluric and local earthquake data sets. In the study, we added a new regularization parameter into the second term of the parameter correction vector of Gallardo and Meju (2003). The new regularization parameter is enhancing the stability of the algorithm and controls the contribution of the cross gradient term in the solution. The results show that even in cases where resistivity and velocity boundaries are different, both methods influence each other positively. In addition, the region of common structural boundaries of the models are clearly mapped compared with original models. Furthermore, deep structures are identified satisfactorily even with using the minimum number of seismic sources. In this paper, in order to understand the future studies, we discussed joint inversion of Magnetotelluric and local earthquake data sets only in two-dimensional space. In the light of these results and by means of the acceleration on the three-dimensional modelling and inversion algorithms, it is thought that it may be easier to identify underground structures with high resolution.

An easily implemented static condensation method for structural sensitivity analysis

NASA Technical Reports Server (NTRS)

Gangadharan, S. N.; Haftka, R. T.; Nikolaidis, E.

1990-01-01

A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.

Automatic high-throughput screening of colloidal crystals using machine learning

NASA Astrophysics Data System (ADS)

Spellings, Matthew; Glotzer, Sharon C.

Recent improvements in hardware and software have united to pose an interesting problem for computational scientists studying self-assembly of particles into crystal structures: while studies covering large swathes of parameter space can be dispatched at once using modern supercomputers and parallel architectures, identifying the different regions of a phase diagram is often a serial task completed by hand. While analytic methods exist to distinguish some simple structures, they can be difficult to apply, and automatic identification of more complex structures is still lacking. In this talk we describe one method to create numerical ``fingerprints'' of local order and use them to analyze a study of complex ordered structures. We can use these methods as first steps toward automatic exploration of parameter space and, more broadly, the strategic design of new materials.

Spacecraft structural system identification by modal test

NASA Technical Reports Server (NTRS)

Chen, J.-C.; Peretti, L. F.; Garba, J. A.

1984-01-01

A structural parameter estimation procedure using the measured natural frequencies and kinetic energy distribution as observers is proposed. The theoretical derivation of the estimation procedure is described and its constraints and limitations are explained. This procedure is applied to a large complex spacecraft structural system to identify the inertia matrix using modal test results. The inertia matrix is chosen after the stiffness matrix has been updated by the static test results.

Damage detection of rotating wind turbine blades using local flexibility method and long-gauge fiber Bragg grating sensors

NASA Astrophysics Data System (ADS)

Hsu, Ting-Yu; Shiao, Shen-Yuan; Liao, Wen-I.

2018-01-01

Wind turbines are a cost-effective alternative energy source; however, their blades are susceptible to damage. Therefore, damage detection of wind turbine blades is of great importance for condition monitoring of wind turbines. Many vibration-based structural damage detection techniques have been proposed in the last two decades. The local flexibility method, which can determine local stiffness variations of beam-like structures by using measured modal parameters, is one of the most promising vibration-based approaches. The local flexibility method does not require a finite element model of the structure. A few structural modal parameters identified from the ambient vibration signals both before and after damage are required for this method. In this study, we propose a damage detection approach for rotating wind turbine blades using the local flexibility method based on the dynamic macro-strain signals measured by long-gauge fiber Bragg grating (FBG)-based sensors. A small wind turbine structure was constructed and excited using a shaking table to generate vibration signals. The structure was designed to have natural frequencies as close as possible to those of a typical 1.5 MW wind turbine in real scale. The optical fiber signal of the rotating blades was transmitted to the data acquisition system through a rotary joint fixed inside the hollow shaft of the wind turbine. Reversible damage was simulated by aluminum plates attached to some sections of the wind turbine blades. The damaged locations of the rotating blades were successfully detected using the proposed approach, with the extent of damage somewhat over-estimated. Nevertheless, although the specimen of wind turbine blades cannot represent a real one, the results still manifest that FBG-based macro-strain measurement has potential to be employed to obtain the modal parameters of the rotating wind turbines and then locations of wind turbine segments with a change of rigidity can be estimated effectively by utilizing these identified parameters.

Parametric Study of Single Bolted Composite Bolted Joint Subjected to Static Tensile Loading

NASA Astrophysics Data System (ADS)

Awadhani, L. V.; Bewoor, Anand, Dr.

2017-08-01

The use of composites is increasing in the engineering applications in order to reduce the weight, building energy efficient systems, designing a suitable material according to the requirements of the application. But at the same time, building a structure is possible only by bonding or bolting or combination of them. There are limitations for the bonding methods and problems with the bolting such as stress concentration near the neighborhood of the bolt hole, tensile or shear failure, delamination etc. Hence the design of a composite bolted structure needs a special attention. This paper focuses on the performance of the composite bolted joint under static tensile loading and the effect of variation in the parameters such as the bolt pitch, plate width, thickness, bolt tightening torque, composite material, coefficient of friction between the bolt and plate etc. A simple spring mass model is used to study the single bolted composite bolted joint. The influencing parameters are identified through the developed model and compared with the results from the literature. The best geometric parameters for the applied load are identified for the composite bolted joints.

SIMBAD : a sequence-independent molecular-replacement pipeline

DOE PAGES

Simpkin, Adam J.; Simkovic, Felix; Thomas, Jens M. H.; ...

2018-06-08

The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here,more » SIMBAD , a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD , this approach has solved novel cases that have otherwise proved difficult to solve.« less

SIMBAD : a sequence-independent molecular-replacement pipeline

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

Simpkin, Adam J.; Simkovic, Felix; Thomas, Jens M. H.

The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here,more » SIMBAD , a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD , this approach has solved novel cases that have otherwise proved difficult to solve.« less

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

PubMed

Snyder, David A; Montelione, Gaetano T

2005-06-01

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

A meta-analysis of the mechanical properties of ice-templated ceramics and metals

PubMed Central

Deville, Sylvain; Meille, Sylvain; Seuba, Jordi

2015-01-01

Ice templating, also known as freeze casting, is a popular shaping route for macroporous materials. Over the past 15 years, it has been widely applied to various classes of materials, and in particular ceramics. Many formulation and process parameters, often interdependent, affect the outcome. It is thus difficult to understand the various relationships between these parameters from isolated studies where only a few of these parameters have been investigated. We report here the results of a meta analysis of the structural and mechanical properties of ice templated materials from an exhaustive collection of records. We use these results to identify which parameters are the most critical to control the structure and properties, and to derive guidelines for optimizing the mechanical response of ice templated materials. We hope these results will be a helpful guide to anyone interested in such materials. PMID:27877817

A meta-analysis of the mechanical properties of ice-templated ceramics and metals

NASA Astrophysics Data System (ADS)

Deville, Sylvain; Meille, Sylvain; Seuba, Jordi

2015-08-01

Ice templating, also known as freeze casting, is a popular shaping route for macroporous materials. Over the past 15 years, it has been widely applied to various classes of materials, and in particular ceramics. Many formulation and process parameters, often interdependent, affect the outcome. It is thus difficult to understand the various relationships between these parameters from isolated studies where only a few of these parameters have been investigated. We report here the results of a meta analysis of the structural and mechanical properties of ice templated materials from an exhaustive collection of records. We use these results to identify which parameters are the most critical to control the structure and properties, and to derive guidelines for optimizing the mechanical response of ice templated materials. We hope these results will be a helpful guide to anyone interested in such materials.

Detection of damage in welded structure using experimental modal data

NASA Astrophysics Data System (ADS)

Abu Husain, N.; Ouyang, H.

2011-07-01

A typical automotive structure could contain thousands of spot weld joints that contribute significantly to the vehicle's structural stiffness and dynamic characteristics. However, some of these joints may be imperfect or even absent during the manufacturing process and they are also highly susceptible to damage due to operational and environmental conditions during the vehicle lifetime. Therefore, early detection and estimation of damage are important so necessary actions can be taken to avoid further problems. Changes in physical parameters due to existence of damage in a structure often leads to alteration of vibration modes; thus demonstrating the dependency between the vibration characteristics and the physical properties of structures. A sensitivity-based model updating method, performed using a combination of MATLAB and NASTRAN, has been selected for the purpose of this work. The updating procedure is regarded as parameter identification which aims to bring the numerical prediction to be as closely as possible to the measured natural frequencies and mode shapes data of the damaged structure in order to identify the damage parameters (characterised by the reductions in the Young's modulus of the weld patches to indicate the loss of material/stiffness at the damage region).

Identification of walking human model using agent-based modelling

NASA Astrophysics Data System (ADS)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Improving substructure identification accuracy of shear structures using virtual control system

NASA Astrophysics Data System (ADS)

Zhang, Dongyu; Yang, Yang; Wang, Tingqiang; Li, Hui

2018-02-01

Substructure identification is a powerful tool to identify the parameters of a complex structure. Previously, the authors developed an inductive substructure identification method for shear structures. The identification error analysis showed that the identification accuracy of this method is significantly influenced by the magnitudes of two key structural responses near a certain frequency; if these responses are unfavorable, the method cannot provide accurate estimation results. In this paper, a novel method is proposed to improve the substructure identification accuracy by introducing a virtual control system (VCS) into the structure. A virtual control system is a self-balanced system, which consists of some control devices and a set of self-balanced forces. The self-balanced forces counterbalance the forces that the control devices apply on the structure. The control devices are combined with the structure to form a controlled structure used to replace the original structure in the substructure identification; and the self-balance forces are treated as known external excitations to the controlled structure. By optimally tuning the VCS’s parameters, the dynamic characteristics of the controlled structure can be changed such that the original structural responses become more favorable for the substructure identification and, thus, the identification accuracy is improved. A numerical example of 6-story shear structure is utilized to verify the effectiveness of the VCS based controlled substructure identification method. Finally, shake table tests are conducted on a 3-story structural model to verify the efficacy of the VCS to enhance the identification accuracy of the structural parameters.

Structural Monitoring and Field Test for Kao Ping Hsi Cable-Stayed Bridge in Taiwan

NASA Astrophysics Data System (ADS)

Chen, Chern-Hwa

2010-05-01

This work applies system identification techniques to analyze the measured data from structural monitoring system and field test for Kao Ping Hsi cable-stayed bridge in Taiwan. The continuous wavelet transform algorithm can be used to identify the dynamic characteristics of the cable-stayed bridge under environmental vibration. The identified results with traffic flow were compared with those obtained from ambient vibration test. The excellent agreement both the identified results from different traffic conditions indicates that the traffic flow would not significantly change the natural frequencies of the cable-stayed bridge. The modal parameters identified from the field vibration test will be compared with those used in the finite element analysis. The results obtained herein will be used as the damage detection for monitoring the long-term safety of the Kao Ping Hsi cable-stayed bridge by using structural monitoring system.

A Path Model for Evaluating Dosing Parameters for Children With Cerebral Palsy

PubMed Central

Christy, Jennifer B.; Heathcock, Jill C.; Kolobe, Thubi H.A.

2014-01-01

Dosing of pediatric rehabilitation services for children with cerebral palsy (CP) has been identified as a national priority. Establishing dosing parameters for pediatric physical therapy interventions is critical for informing clinical decision making, health policy, and guidelines for reimbursement. The purpose of this perspective article is to describe a path model for evaluating dosing parameters of interventions for children with CP. The model is intended for dose-related and effectiveness studies of pediatric physical therapy interventions. The premise of the model is: Intervention type (focus on body structures, activity, or the environment) acts on a child first through the family, then through the dose (frequency, intensity, time), to yield structural and behavioral changes. As a result, these changes are linked to improvements in functional independence. Community factors affect dose as well as functional independence (performance and capacity), influencing the relationships between type of intervention and intervention responses. The constructs of family characteristics; child characteristics (eg, age, level of severity, comorbidities, readiness to change, preferences); plastic changes in bone, muscle, and brain; motor skill acquisition; and community access warrant consideration from researchers who are designing intervention studies. Multiple knowledge gaps are identified, and a framework is provided for conceptualizing dosing parameters for children with CP. PMID:24231231

ON IDENTIFIABILITY OF NONLINEAR ODE MODELS AND APPLICATIONS IN VIRAL DYNAMICS

PubMed Central

MIAO, HONGYU; XIA, XIAOHUA; PERELSON, ALAN S.; WU, HULIN

2011-01-01

Ordinary differential equations (ODE) are a powerful tool for modeling dynamic processes with wide applications in a variety of scientific fields. Over the last 2 decades, ODEs have also emerged as a prevailing tool in various biomedical research fields, especially in infectious disease modeling. In practice, it is important and necessary to determine unknown parameters in ODE models based on experimental data. Identifiability analysis is the first step in determing unknown parameters in ODE models and such analysis techniques for nonlinear ODE models are still under development. In this article, we review identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiability analysis, practical identifiability analysis and sensitivity-based identifiability analysis. Some advanced topics and ongoing research are also briefly reviewed. Finally, some examples from modeling viral dynamics of HIV, influenza and hepatitis viruses are given to illustrate how to apply these identifiability analysis methods in practice. PMID:21785515

Bayesian calibration of the Community Land Model using surrogates

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

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural errormore » in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.« less

Etude du comportement sous charges laterales des ossatures de beton arme avec murs de remplissage de maconnerie, construites avant les annees 1960

NASA Astrophysics Data System (ADS)

Lefebvre, Karine

Reinforced concrete structures with unreinforced masonry infills (BMR) are considered vulnerable to earthquakes. Under seismic actions, infills could fail (causing injuries or death) and cause damages to columns. In Quebec and Canada, most of BMR structures have been constructed prior to the introduction of modern seismic design codes raising question on the contribution of the infill to the structure lateral resistance. The aim of this thesis is to improve modelling technique of BMR structures built in Quebec between 1915 and 1960. This type of structures is found in hospitals or schools buildings, which must comply with some post-earthquake functionality requirements. They could also be residential or office buildings. Actually, practicing engineers usually calculate seismic capacity of BMR structures without considering the infill's structural contribution to the lateral resistance. Yet, this contribution should not be omitted. The first part of the thesis investigates the construction techniques and material properties of the old BMR structures in the Province. The results are the material properties (concrete, reinforcing steel, brick, terra cotta tile, and mortar) and the characteristics of the assemblies (wall section, reinforcement details…). The second part of the thesis presents the results of series of parametric analyses to identify among modelling and geometric parameters, which ones are the most influent on the lateral load response (rigidity, fundamental period, normal modes). Linear and modal analyses were performed. The most influent parameters identified are: number of storeys, number of bays, bay's width, soft storey, openings, upper storeys modelized (instead of being replaced by punctual loads) and the modelization technique of infills panels (strut or shell). Nonlinear static analyses have been performed to identify the most influent parameters to be considered for evaluating the lateral resistance, the capacity (load / displacement) and the yielding sequence (beam versus columns versus infills). The identified parameters are the presence of the infills, the openings and the geometric characteristics of the models (number of storeys and number of bays). One important contribution of this work is the development of an equivalent strut model to represent the action of the infill. The model could be easily implemented in standard analysis software. A central axial hinge reproducing the nonlinear behaviour of the masonry is added to the strut element. This model is a hybridization of existing proposals (FEMA and others) with added innovations by the author. It has been validated with experimental and numerical analyses results from literature. An important conclusion of this thesis is that the contribution of infills to lateral load resisting capacities of BMR structures should be considered for structure of more than one storey. Infills can add up to 51 % to bare frame capacity. The National building code requires that the lateral resistance of existing buildings must be at least 60 % of the equivalent static seismic force (V2005). It is concluded that one storey BMR buildings have a sufficient resistance, while three-storeys structures exhibit plastic deformations for loads under 0,6* V2005.

Development of a smart timber bridge - a five-year plan

Treesearch

Brent M. Phares; Terry J. Wipf; Ursula Deza; James P. Wacker

2011-01-01

This paper outlines a 5-year research plan for the development of a structural health monitoring system for timber bridges. A series of studies identify and evaluate various sensing technologies for measurement of structural adequacy and/or deterioration parameters. The overall goal is to develop a turn-key system to analyze, monitor, and report on the performance and...

The application of artificial intelligence in the optimal design of mechanical systems

NASA Astrophysics Data System (ADS)

Poteralski, A.; Szczepanik, M.

2016-11-01

The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.

On structural identifiability analysis of the cascaded linear dynamic systems in isotopically non-stationary 13C labelling experiments.

PubMed

Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang

2018-06-01

The isotopically non-stationary 13C labelling experiments, as an emerging experimental technique, can estimate the intracellular fluxes of the cell culture under an isotopic transient period. However, to the best of our knowledge, the issue of the structural identifiability analysis of non-stationary isotope experiments is not well addressed in the literature. In this work, the local structural identifiability analysis for non-stationary cumomer balance equations is conducted based on the Taylor series approach. The numerical rank of the Jacobian matrices of the finite extended time derivatives of the measured fractions with respect to the free parameters is taken as the criterion. It turns out that only one single time point is necessary to achieve the structural identifiability analysis of the cascaded linear dynamic system of non-stationary isotope experiments. The equivalence between the local structural identifiability of the cascaded linear dynamic systems and the local optimum condition of the nonlinear least squares problem is elucidated in the work. Optimal measurements sets can then be determined for the metabolic network. Two simulated metabolic networks are adopted to demonstrate the utility of the proposed method. Copyright © 2018 Elsevier Inc. All rights reserved.

Global Sensitivity Analysis for Identifying Important Parameters of Nitrogen Nitrification and Denitrification under Model and Scenario Uncertainties

NASA Astrophysics Data System (ADS)

Ye, M.; Chen, Z.; Shi, L.; Zhu, Y.; Yang, J.

2017-12-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. While global sensitivity analysis is a vital tool for identifying the parameters important to nitrogen reactive transport, conventional global sensitivity analysis only considers parametric uncertainty. This may result in inaccurate selection of important parameters, because parameter importance may vary under different models and modeling scenarios. By using a recently developed variance-based global sensitivity analysis method, this paper identifies important parameters with simultaneous consideration of parametric uncertainty, model uncertainty, and scenario uncertainty. In a numerical example of nitrogen reactive transport modeling, a combination of three scenarios of soil temperature and two scenarios of soil moisture leads to a total of six scenarios. Four alternative models are used to evaluate reduction functions used for calculating actual rates of nitrification and denitrification. The model uncertainty is tangled with scenario uncertainty, as the reduction functions depend on soil temperature and moisture content. The results of sensitivity analysis show that parameter importance varies substantially between different models and modeling scenarios, which may lead to inaccurate selection of important parameters if model and scenario uncertainties are not considered. This problem is avoided by using the new method of sensitivity analysis in the context of model averaging and scenario averaging. The new method of sensitivity analysis can be applied to other problems of contaminant transport modeling when model uncertainty and/or scenario uncertainty are present.

Identifiability of sorption parameters in stirred flow-through reactor experiments and their identification with a Bayesian approach.

PubMed

Nicoulaud-Gouin, V; Garcia-Sanchez, L; Giacalone, M; Attard, J C; Martin-Garin, A; Bois, F Y

2016-10-01

This paper addresses the methodological conditions -particularly experimental design and statistical inference- ensuring the identifiability of sorption parameters from breakthrough curves measured during stirred flow-through reactor experiments also known as continuous flow stirred-tank reactor (CSTR) experiments. The equilibrium-kinetic (EK) sorption model was selected as nonequilibrium parameterization embedding the K d approach. Parameter identifiability was studied formally on the equations governing outlet concentrations. It was also studied numerically on 6 simulated CSTR experiments on a soil with known equilibrium-kinetic sorption parameters. EK sorption parameters can not be identified from a single breakthrough curve of a CSTR experiment, because K d,1 and k - were diagnosed collinear. For pairs of CSTR experiments, Bayesian inference allowed to select the correct models of sorption and error among sorption alternatives. Bayesian inference was conducted with SAMCAT software (Sensitivity Analysis and Markov Chain simulations Applied to Transfer models) which launched the simulations through the embedded simulation engine GNU-MCSim, and automated their configuration and post-processing. Experimental designs consisting in varying flow rates between experiments reaching equilibrium at contamination stage were found optimal, because they simultaneously gave accurate sorption parameters and predictions. Bayesian results were comparable to maximum likehood method but they avoided convergence problems, the marginal likelihood allowed to compare all models, and credible interval gave directly the uncertainty of sorption parameters θ. Although these findings are limited to the specific conditions studied here, in particular the considered sorption model, the chosen parameter values and error structure, they help in the conception and analysis of future CSTR experiments with radionuclides whose kinetic behaviour is suspected. Copyright © 2016 Elsevier Ltd. All rights reserved.

Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

USGS Publications Warehouse

Clark, Martyn P.; Slater, Andrew G.; Rupp, David E.; Woods, Ross A.; Vrugt, Jasper A.; Gupta, Hoshin V.; Wagener, Thorsten; Hay, Lauren E.

2008-01-01

The problems of identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure remain outstanding research challenges for the discipline of hydrology. Progress on these problems requires understanding of the nature of differences between models. This paper presents a methodology to diagnose differences in hydrological model structures: the Framework for Understanding Structural Errors (FUSE). FUSE was used to construct 79 unique model structures by combining components of 4 existing hydrological models. These new models were used to simulate streamflow in two of the basins used in the Model Parameter Estimation Experiment (MOPEX): the Guadalupe River (Texas) and the French Broad River (North Carolina). Results show that the new models produced simulations of streamflow that were at least as good as the simulations produced by the models that participated in the MOPEX experiment. Our initial application of the FUSE method for the Guadalupe River exposed relationships between model structure and model performance, suggesting that the choice of model structure is just as important as the choice of model parameters. However, further work is needed to evaluate model simulations using multiple criteria to diagnose the relative importance of model structural differences in various climate regimes and to assess the amount of independent information in each of the models. This work will be crucial to both identifying the most appropriate model structure for a given problem and quantifying the uncertainty in model structure. To facilitate research on these problems, the FORTRAN‐90 source code for FUSE is available upon request from the lead author.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

Toward a better understanding of helicopter stability derivatives

NASA Technical Reports Server (NTRS)

Hansen, R. S.

1982-01-01

An amended six degree of freedom helicopter stability and control derivative model was developed in which body acceleration and control rate derivatives were included in the Taylor series expansion. These additional derivatives were derived from consideration of the effects of the higher order rotor flapping dynamics, which are known to be inadequately represented in the conventional six degree of freedom, quasistatic stability derivative model. The amended model was a substantial improvement over the conventional model, effectively doubling the unsable bandwidth and providing a more accurate representation of the short period and cross axis characteristics. Further investigations assessed the applicability of the two stability derivative model structures for flight test parameter identification. Parameters were identified using simulation data generated from a higher order base line model having sixth order rotor tip path plane dynamics. Three lower order models were identified: one using the conventional stability derivative model structure, a second using the amended six degree of freedom model structure, and a third model having eight degrees of freedom that included a simplified rotor tip path plane tilt representation.

Radiologic imaging of the renal parenchyma structure and function.

PubMed

Grenier, Nicolas; Merville, Pierre; Combe, Christian

2016-06-01

Radiologic imaging has the potential to identify several functional and/or structural biomarkers of acute and chronic kidney diseases that are useful diagnostics to guide patient management. A renal ultrasound examination can provide information regarding the gross anatomy and macrostructure of the renal parenchyma, and ultrasound imaging modalities based on Doppler or elastography techniques can provide haemodynamic and structural information, respectively. CT is also able to combine morphological and functional information, but the use of CT is limited due to the required exposure to X-ray irradiation and a risk of contrast-induced nephropathy following intravenous injection of a radio-contrast agent. MRI can be used to identify a wide range of anatomical and physiological parameters at the tissue and even cellular level, such as tissue perfusion, oxygenation, water diffusion, cellular phagocytic activity, tissue stiffness, and level of renal filtration. The ability of MRI to provide valuable information for most of these parameters within a renal context is still in development and requires more clinical experience, harmonization of technical procedures, and an evaluation of reliability and validity on a large scale.

High speed inscription of uniform, large-area laser-induced periodic surface structures in Cr films using a high repetition rate fs laser.

PubMed

Ruiz de la Cruz, A; Lahoz, R; Siegel, J; de la Fuente, G F; Solis, J

2014-04-15

We report on the fabrication of laser-induced periodic surface structures in Cr films upon high repetition rate fs laser irradiation (up to 1 MHz, 500 fs, 1030 nm), employing beam scanning. Highly regular large-area (9  cm2) gratings with a relative diffraction efficiency of 42% can be produced within less than 6 min. The ripple period at moderate and high fluences is 0.9 μm, with a small period of 0.5 μm appearing at lower energies. The role of the irradiation parameters on the characteristics of the laser-induced periodic surface structures (LIPSS) is studied and discussed in the frame of the models presently used. We have identified the polarization vector orientation with respect to the scan direction as a key parameter for the fabrication of high-quality, large-area LIPSS, which, for perpendicular orientation, allows the coherent extension of the sub-wavelength structure over macroscopic distances. The processing strategy is robust in terms of broad parameter windows and applicable to other materials featuring LIPSS.

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

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

Szczykutowicz, T; Rubert, N; Ranallo, F

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specificmore » anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.« less

A new qualitative acoustic emission parameter based on Shannon's entropy for damage monitoring

NASA Astrophysics Data System (ADS)

Chai, Mengyu; Zhang, Zaoxiao; Duan, Quan

2018-02-01

An important objective of acoustic emission (AE) non-destructive monitoring is to accurately identify approaching critical damage and to avoid premature failure by means of the evolutions of AE parameters. One major drawback of most parameters such as count and rise time is that they are strongly dependent on the threshold and other settings employed in AE data acquisition system. This may hinder the correct reflection of original waveform generated from AE sources and consequently bring difficulty for the accurate identification of the critical damage and early failure. In this investigation, a new qualitative AE parameter based on Shannon's entropy, i.e. AE entropy is proposed for damage monitoring. Since it derives from the uncertainty of amplitude distribution of each AE waveform, it is independent of the threshold and other time-driven parameters and can characterize the original micro-structural deformations. Fatigue crack growth test on CrMoV steel and three point bending test on a ductile material are conducted to validate the feasibility and effectiveness of the proposed parameter. The results show that the new parameter, compared to AE amplitude, is more effective in discriminating the different damage stages and identifying the critical damage.

Selection of regularization parameter for l1-regularized damage detection

NASA Astrophysics Data System (ADS)

Hou, Rongrong; Xia, Yong; Bao, Yuequan; Zhou, Xiaoqing

2018-06-01

The l1 regularization technique has been developed for structural health monitoring and damage detection through employing the sparsity condition of structural damage. The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution. However, the l1 regularization problem has no closed-form solution, and the regularization parameter is usually selected by experience. This study proposes two strategies of selecting the regularization parameter for the l1-regularized damage detection problem. The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small. The other method is based on the discrepancy principle, which requires that the variance of the discrepancy between the calculated and measured responses is close to the variance of the measurement noise. The two methods are applied to a cantilever beam and a three-story frame. A range of the regularization parameter, rather than one single value, can be determined. When the regularization parameter in this range is selected, the damage can be accurately identified even for multiple damage scenarios. This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.

Two Growth Modes of Graphitic Carbon Nanofibers with Herring-Bone Structure

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

Merkulov, Igor A; Melechko, Anatoli Vasilievich; Wells, Jack C

2005-01-01

A simple mathematical model of the carbon nanofiber catalytic growth process is presented. Two major types of the fiber-catalyst interface shapes have been identified and described having qualitatively different structure in the center of a nanofiber. Presently, we discuss that the appearance of the irregular structure in the nanofiber central area is a result of curved-interface-growth kinematics. We suggest the method to determine the phenomenological parameters of the developed model from experimental data.

Two growth modes of graphitic carbon nanofibers with herring-bone structure

NASA Astrophysics Data System (ADS)

Merkulov, I. A.; Meleshko, A. V.; Wells, J. C.; Cui, H.; Merkulov, V. I.; Simpson, M. L.; Lowndes, D. H.

2005-07-01

A simple mathematical model of the carbon nanofiber catalytic growth process is presented. Two major types of the fiber-catalyst interface shapes have been identified and described having qualitatively different structure in the center of a nanofiber. Presently, we discuss that the appearance of the irregular structure in the nanofiber central area is a result of curved-interface-growth kinematics. We suggest the method to determine the phenomenological parameters of the developed model from experimental data.

Likelihood analysis of spatial capture-recapture models for stratified or class structured populations

USGS Publications Warehouse

Royle, J. Andrew; Sutherland, Christopher S.; Fuller, Angela K.; Sun, Catherine C.

2015-01-01

We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

Factors Predictive of Improved Abdominal Ultrasound Visualization after Oral Administration of Simethicone.

PubMed

Marsico, Maria; Gabbani, Tommaso; Casseri, Tommaso; Biagini, Maria Rosa

2016-11-01

Ultrasonography is a non-invasive, accurate and low-cost technique used to study the upper abdomen, but it has reduced reliability in the study of the pancreas and retroperitoneum. Simethicone is a well-known emulsifying agent that has been used to improve ultrasonographic visualization. The aim of this study was to identify anthropometric parameters that are able to predict a good response to simethicone in improving ultrasonographic visualization of abdominal structures. One hundred twenty-seven patients were recruited. After basal examination, their anthropometric parameters were collected. Patients with an incomplete upper abdominal examination because of gastrointestinal gas have greater body mass index, waist circumference and abdominal wall thickness. In our study, the best anthropometric parameter for identifying patients with poor visualization at abdominal ultrasound examination is waist circumference. Using a cutoff of 84 cm, we can identify patients with poor visibility at abdominal ultrasound examination (group B) with a sensitivity of 90%. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Repair, Evaluation, Maintenance, and Rehabilitation Research Program: Geotechnical Aspects of Rock Erosion in Emergency Spillway Channels. Report 3. Remediation

DTIC Science & Technology

1988-09-01

identified early and treated promptly. The same authors proposed that the rock-mass parameters that govern rippability , when combined with...lithostratigraphic continuity factors, may provide predictive erosion indices from a geotechnical point of view. 16. Rippability is a form of rock-mass...The rock-mass parameters from which a rippability rating (RR) is derived include rock type, hardness, weathering, structure (strike and dip orientation

Population models for passerine birds: structure, parameterization, and analysis

USGS Publications Warehouse

Noon, B.R.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.

1992-01-01

Population models have great potential as management tools, as they use infonnation about the life history of a species to summarize estimates of fecundity and survival into a description of population change. Models provide a framework for projecting future populations, determining the effects of management decisions on future population dynamics, evaluating extinction probabilities, and addressing a variety of questions of ecological and evolutionary interest. Even when insufficient information exists to allow complete identification of the model, the modelling procedure is useful because it forces the investigator to consider the life history of the species when determining what parameters should be estimated from field studies and provides a context for evaluating the relative importance of demographic parameters. Models have been little used in the study of the population dynamics of passerine birds because of: (1) widespread misunderstandings of the model structures and parameterizations, (2) a lack of knowledge of life histories of many species, (3) difficulties in obtaining statistically reliable estimates of demographic parameters for most passerine species, and (4) confusion about functional relationships among demographic parameters. As a result, studies of passerine demography are often designed inappropriately and fail to provide essential data. We review appropriate models for passerine bird populations and illustrate their possible uses in evaluating the effects of management or other environmental influences on population dynamics. We identify environmental influences on population dynamics. We identify parameters that must be estimated from field data, briefly review existing statistical methods for obtaining valid estimates, and evaluate the present status of knowledge of these parameters.

Quantitative analysis of ground penetrating radar data in the Mu Us Sandland

NASA Astrophysics Data System (ADS)

Fu, Tianyang; Tan, Lihua; Wu, Yongqiu; Wen, Yanglei; Li, Dawei; Duan, Jinlong

2018-06-01

Ground penetrating radar (GPR), which can reveal the sedimentary structure and development process of dunes, is widely used to evaluate aeolian landforms. The interpretations for GPR profiles are mostly based on qualitative descriptions of geometric features of the radar reflections. This research quantitatively analyzed the waveform parameter characteristics of different radar units by extracting the amplitude and time interval parameters of GPR data in the Mu Us Sandland in China, and then identified and interpreted different sedimentary structures. The results showed that different types of radar units had specific waveform parameter characteristics. The main waveform parameter characteristics of sand dune radar facies and sandstone radar facies included low amplitudes and wide ranges of time intervals, ranging from 0 to 0.25 and 4 to 33 ns respectively, and the mean amplitudes changed gradually with time intervals. The amplitude distribution curves of various sand dune radar facies were similar as unimodal distributions. The radar surfaces showed high amplitudes with time intervals concentrated in high-value areas, ranging from 0.08 to 0.61 and 9 to 34 ns respectively, and the mean amplitudes changed drastically with time intervals. The amplitude and time interval values of lacustrine radar facies were between that of sand dune radar facies and radar surfaces, ranging from 0.08 to 0.29 and 11 to 30 ns respectively, and the mean amplitude and time interval curve was approximately trapezoidal. The quantitative extraction and analysis of GPR reflections could help distinguish various radar units and provide evidence for identifying sedimentary structure in aeolian landforms.

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

NASA Technical Reports Server (NTRS)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Flexural Behavior of Aluminum Honeycomb Core Sandwich Structure

NASA Astrophysics Data System (ADS)

Matta, Vidyasagar; Kumar, J. Suresh; Venkataraviteja, Duddu; Reddy, Guggulla Bharath Kumar

2017-05-01

This project is concerned with the fabrication and flexural testing of aluminium honey comb sandwich structure which is a special case of composite materials that is fabricated by attaching two thin but stiff skins to a light weight but thick core. The core material is normally low density material but its high thickness provide the sandwich composite with high bonding stiffness. Honeycomb core are classified into two types based on the materials and structures. Hexagonal shape has a unique properties i.e has more bonding strength and less formation time based on the cell size and sheet thickness. Sandwich structure exhibit different properties such as high load bearing capacity at low weight and has excellent thermal insulation. By considering the above properties it has tendency to minimize the structural problem. So honey comb sandwich structure is choosed. The core structure has a different applications such as aircraft, ship interiors, construction industries. As there is no proper research on strength characteristics of sandwich structure. So, we use light weight material to desire the strength. There are different parameters involved in this structure i.e cell size, sheet thickness and core height. In this project we considered 3 level of comparison among the 3 different parameters cell size of 4, 6 and 8 mm, sheet thickness of 0.3, 0.5 and 0.7 mm, and core height of 20,25 and 30 mm. In order to reduce the number of experiment we use taguchi design of experiment, and we select the L8 orthogonal array is the best array for this type of situation, which clearly identifies the parameters by independent of material weight to support this we add the minitab software, to identify the main effective plots and regression equation which involves the individual response and corresponding parameters. Aluminium material is used for the fabrication of Honeycomb sandwich structure among the various grades of aluminium we consider the AL6061 which is light weight material and has more strength. By the power press used as forming method we fabricate the honey comb core and stacking the sheets with adhesive as epoxy resin or laser beam welding and sandwich structure will form with two face sheets. Then the specimen is taken to be tested to know the flexural behaviour by the flexural test as 3 point and 4 pont bend test. After testing of two different tests then we get the force vs displacement curve by this we can know the maximum force and by loading configurations and its displacement or deflection then we can calculate flexural stiffness and core shear modulus by the variation of three parameters. Our ultimate aim is to achieve maximum strength by minimum weight.

Structural Aspects of System Identification

NASA Technical Reports Server (NTRS)

Glover, Keith

1973-01-01

The problem of identifying linear dynamical systems is studied by considering structural and deterministic properties of linear systems that have an impact on stochastic identification algorithms. In particular considered is parametrization of linear systems so that there is a unique solution and all systems in appropriate class can be represented. It is assumed that a parametrization of system matrices has been established from a priori knowledge of the system, and the question is considered of when the unknown parameters of this system can be identified from input/output observations. It is assumed that the transfer function can be asymptotically identified, and the conditions are derived for the local, global and partial identifiability of the parametrization. Then it is shown that, with the right formulation, identifiability in the presence of feedback can be treated in the same way. Similarly the identifiability of parametrizations of systems driven by unobserved white noise is considered using the results from the theory of spectral factorization.

Design for inadvertent damage in composite laminates

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Chamis, Christos C.

1992-01-01

Simplified predictive methods and models to computationally simulate durability and damage in polymer matrix composite materials/structures are described. The models include (1) progressive fracture, (2) progressively damaged structural behavior, (3) progressive fracture in aggressive environments, (4) stress concentrations, and (5) impact resistance. Several examples are included to illustrate applications of the models and to identify significant parameters and sensitivities. Comparisons with limited experimental data are made.

Use of Linear Prediction Uncertainty Analysis to Guide Conditioning of Models Simulating Surface-Water/Groundwater Interactions

NASA Astrophysics Data System (ADS)

Hughes, J. D.; White, J.; Doherty, J.

2011-12-01

Linear prediction uncertainty analysis in a Bayesian framework was applied to guide the conditioning of an integrated surface water/groundwater model that will be used to predict the effects of groundwater withdrawals on surface-water and groundwater flows. Linear prediction uncertainty analysis is an effective approach for identifying (1) raw and processed data most effective for model conditioning prior to inversion, (2) specific observations and periods of time critically sensitive to specific predictions, and (3) additional observation data that would reduce model uncertainty relative to specific predictions. We present results for a two-dimensional groundwater model of a 2,186 km2 area of the Biscayne aquifer in south Florida implicitly coupled to a surface-water routing model of the actively managed canal system. The model domain includes 5 municipal well fields withdrawing more than 1 Mm3/day and 17 operable surface-water control structures that control freshwater releases from the Everglades and freshwater discharges to Biscayne Bay. More than 10 years of daily observation data from 35 groundwater wells and 24 surface water gages are available to condition model parameters. A dense parameterization was used to fully characterize the contribution of the inversion null space to predictive uncertainty and included bias-correction parameters. This approach allows better resolution of the boundary between the inversion null space and solution space. Bias-correction parameters (e.g., rainfall, potential evapotranspiration, and structure flow multipliers) absorb information that is present in structural noise that may otherwise contaminate the estimation of more physically-based model parameters. This allows greater precision in predictions that are entirely solution-space dependent, and reduces the propensity for bias in predictions that are not. Results show that application of this analysis is an effective means of identifying those surface-water and groundwater data, both raw and processed, that minimize predictive uncertainty, while simultaneously identifying the maximum solution-space dimensionality of the inverse problem supported by the data.

Ranges of applicability for the continuum beam model in the mechanics of carbon nanotubes and nanorods

NASA Technical Reports Server (NTRS)

Harik, V. M.

2001-01-01

Limitations in the validity of the continuum beam model for carbon nanotubes (NTs) and nanorods are examined. Applicability of all assumptions used in the model is restricted by the two criteria for geometric parameters that characterize the structure of NTs. The key non-dimensional parameters that control the NT buckling behavior are derived via dimensional analysis of the nanomechanical problem. A mechanical law of geometric similitude for NT buckling is extended from continuum mechanics for different molecular structures. A model applicability map, where two classes of beam-like NTs are identified, is constructed for distinct ranges of non-dimensional parameters. Expressions for the critical buckling loads and strains are tailored for two classes of NTs and compared with the data provided by the molecular dynamics simulations. copyright 2001 Elsevier Science Ltd. All rights reserved.

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

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

Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/ormore » line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.« less

Parameterized centrality metric for network analysis

NASA Astrophysics Data System (ADS)

Ghosh, Rumi; Lerman, Kristina

2011-06-01

A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [P. Bonacich, Am. J. Sociol.0002-960210.1086/228631 92, 1170 (1987)], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, for example, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. Studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed metric to several benchmark networks and show that it leads to better insights into network structure than alternative metrics.

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Sampling of Stochastic Input Parameters for Rockfall Calculations and for Structural Response Calculations Under Vibratory Ground Motion

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

M. Gross

2004-09-01

The purpose of this scientific analysis is to define the sampled values of stochastic (random) input parameters for (1) rockfall calculations in the lithophysal and nonlithophysal zones under vibratory ground motions, and (2) structural response calculations for the drip shield and waste package under vibratory ground motions. This analysis supplies: (1) Sampled values of ground motion time history and synthetic fracture pattern for analysis of rockfall in emplacement drifts in nonlithophysal rock (Section 6.3 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (2) Sampled values of ground motion time history and rock mechanical properties category for analysis of rockfall inmore » emplacement drifts in lithophysal rock (Section 6.4 of ''Drift Degradation Analysis'', BSC 2004 [DIRS 166107]); (3) Sampled values of ground motion time history and metal to metal and metal to rock friction coefficient for analysis of waste package and drip shield damage to vibratory motion in ''Structural Calculations of Waste Package Exposed to Vibratory Ground Motion'' (BSC 2004 [DIRS 167083]) and in ''Structural Calculations of Drip Shield Exposed to Vibratory Ground Motion'' (BSC 2003 [DIRS 163425]). The sampled values are indices representing the number of ground motion time histories, number of fracture patterns and rock mass properties categories. These indices are translated into actual values within the respective analysis and model reports or calculations. This report identifies the uncertain parameters and documents the sampled values for these parameters. The sampled values are determined by GoldSim V6.04.007 [DIRS 151202] calculations using appropriate distribution types and parameter ranges. No software development or model development was required for these calculations. The calculation of the sampled values allows parameter uncertainty to be incorporated into the rockfall and structural response calculations that support development of the seismic scenario for the Total System Performance Assessment for the License Application (TSPA-LA). The results from this scientific analysis also address project requirements related to parameter uncertainty, as specified in the acceptance criteria in ''Yucca Mountain Review Plan, Final Report'' (NRC 2003 [DIRS 163274]). This document was prepared under the direction of ''Technical Work Plan for: Regulatory Integration Modeling of Drift Degradation, Waste Package and Drip Shield Vibratory Motion and Seismic Consequences'' (BSC 2004 [DIRS 170528]) which directed the work identified in work package ARTM05. This document was prepared under procedure AP-SIII.9Q, ''Scientific Analyses''. There are no specific known limitations to this analysis.« less

Polarization-dependent diffraction in all-dielectric, twisted-band structures

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

Kardaś, Tomasz M.; Jagodnicka, Anna; Wasylczyk, Piotr, E-mail: pwasylcz@fuw.edu.pl

2015-11-23

We propose a concept for light polarization management: polarization-dependent diffraction in all-dielectric microstructures. Numerical simulations of light propagation show that with an appropriately configured array of twisted bands, such structures may exhibit zero birefringence and at the same time diffract two circular polarizations with different efficiencies. Non-birefringent structures as thin as 3 μm have a significant difference in diffraction efficiency for left- and right-hand circular polarizations. We identify the structural parameters of such twisted-band matrices for optimum performance as circular polarizers.

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data.

PubMed

Cho, Kwang-Hyun; Choo, Sang-Mok; Wellstead, Peter; Wolkenhauer, Olaf

2005-08-15

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

NASA Technical Reports Server (NTRS)

Kuguoglu, Latife; Ludwiczak, Damian

2006-01-01

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Log-amplitude variance and wave structure function: A new perspective for Gaussian beams

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

Miller, W.B.; Ricklin, J.C.; Andrews, L.C.

1993-04-01

Two naturally linked pairs of nondimensional parameters are identified such that either pair, together with wavelength and path length, completely specifies the diffractive propagation environment for a lowest-order paraxial Gaussian beam. Both parameter pairs are intuitive, and within the context of locally homogeneous and isotropic turbulence they reflect the long-recognized importance of the Fresnel zone size in the behavior of Rytov propagation statistics. These parameter pairs, called, respectively, the transmitter and receiver parameters, also provide a change in perspective in the analysis of optical turbulence effects on Gaussian beams by unifying a number of behavioral traits previously observed or predicted,more » and they create an environment in which the determination of limiting interrelationships between beam forms is especially simple. The fundamental nature of the parameter pairs becomes apparent in the derived analytical expressions for the log-amplitude variance and the wave structure function. These expressions verify general optical turbulence-related characteristics predicted for Gaussian beams, provide additional insights into beam-wave behavior, and are convenient tools for beam-wave analysis. 22 refs., 10 figs., 2 tabs.« less

Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean

NASA Technical Reports Server (NTRS)

Subrahmanyam, Bulusu; Heffner, David M.; Cromwell, David; Shriver, Jay F.

2009-01-01

Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.

Complex bifurcation patterns in a discrete predator-prey model with periodic environmental modulation

NASA Astrophysics Data System (ADS)

Harikrishnan, K. P.

2018-02-01

We consider the simplest model in the family of discrete predator-prey system and introduce for the first time an environmental factor in the evolution of the system by periodically modulating the natural death rate of the predator. We show that with the introduction of environmental modulation, the bifurcation structure becomes much more complex with bubble structure and inverse period doubling bifurcation. The model also displays the peculiar phenomenon of coexistence of multiple limit cycles in the domain of attraction for a given parameter value that combine and finally gets transformed into a single strange attractor as the control parameter is increased. To identify the chaotic regime in the parameter plane of the model, we apply the recently proposed scheme based on the correlation dimension analysis. We show that the environmental modulation is more favourable for the stable coexistence of the predator and the prey as the regions of fixed point and limit cycle in the parameter plane increase at the expense of chaotic domain.

Body weight of hypersonic aircraft, part 1

NASA Technical Reports Server (NTRS)

Ardema, Mark D.

1988-01-01

The load bearing body weight of wing-body and all-body hypersonic aircraft is estimated for a wide variety of structural materials and geometries. Variations of weight with key design and configuration parameters are presented and discussed. Both hot and cool structure approaches are considered in isotropic, organic composite, and metal matrix composite materials; structural shells are sandwich or skin-stringer. Conformal and pillow-tank designs are investigated for the all-body shape. The results identify the most promising hypersonic aircraft body structure design approaches and their weight trends. Geometric definition of vehicle shapes and structural analysis methods are presented in appendices.

Metrological reliability of optical coherence tomography in biomedical applications

NASA Astrophysics Data System (ADS)

Goloni, C. M.; Temporão, G. P.; Monteiro, E. C.

2013-09-01

Optical coherence tomography (OCT) has been proving to be an efficient diagnostics technique for imaging in vivo tissues, an optical biopsy with important perspectives as a diagnostic tool for quantitative characterization of tissue structures. Despite its established clinical use, there is no international standard to address the specific requirements for basic safety and essential performance of OCT devices for biomedical imaging. The present work studies the parameters necessary for conformity assessment of optoelectronics equipment used in biomedical applications like Laser, Intense Pulsed Light (IPL), and OCT, targeting to identify the potential requirements to be considered in the case of a future development of a particular standard for OCT equipment. In addition to some of the particular requirements standards for laser and IPL, also applicable for metrological reliability analysis of OCT equipment, specific parameters for OCT's evaluation have been identified, considering its biomedical application. For each parameter identified, its information on the accompanying documents and/or its measurement has been recommended. Among the parameters for which the measurement requirement was recommended, including the uncertainty evaluation, the following are highlighted: optical radiation output, axial and transverse resolution, pulse duration and interval, and beam divergence.

The seesaw space, a vector space to identify and characterize large-scale structures at 1 AU

NASA Astrophysics Data System (ADS)

Lara, A.; Niembro, T.

2017-12-01

We introduce the seesaw space, an orthonormal space formed by the local and the global fluctuations of any of the four basic solar parameters: velocity, density, magnetic field and temperature at any heliospheric distance. The fluctuations compare the standard deviation of a moving average of three hours against the running average of the parameter in a month (consider as the local fluctuations) and in a year (global fluctuations) We created this new vectorial spaces to identify the arrival of transients to any spacecraft without the need of an observer. We applied our method to the one-minute resolution data of WIND spacecraft from 1996 to 2016. To study the behavior of the seesaw norms in terms of the solar cycle, we computed annual histograms and fixed piecewise functions formed by two log-normal distributions and observed that one of the distributions is due to large-scale structures while the other to the ambient solar wind. The norm values in which the piecewise functions change vary in terms of the solar cycle. We compared the seesaw norms of each of the basic parameters due to the arrival of coronal mass ejections, co-rotating interaction regions and sector boundaries reported in literature. High seesaw norms are due to large-scale structures. We found three critical values of the norms that can be used to determined the arrival of coronal mass ejections. We present as well general comparisons of the norms during the two maxima and the minimum solar cycle periods and the differences of the norms due to large-scale structures depending on each period.

Multiple scales and phases in discrete chains with application to folded proteins

NASA Astrophysics Data System (ADS)

Sinelnikova, A.; Niemi, A. J.; Nilsson, Johan; Ulybyshev, M.

2018-05-01

Chiral heteropolymers such as large globular proteins can simultaneously support multiple length scales. The interplay between the different scales brings about conformational diversity, determines the phase properties of the polymer chain, and governs the structure of the energy landscape. Most importantly, multiple scales produce complex dynamics that enable proteins to sustain live matter. However, at the moment there is incomplete understanding of how to identify and distinguish the various scales that determine the structure and dynamics of a complex protein. Here we address this impending problem. We develop a methodology with the potential to systematically identify different length scales, in the general case of a linear polymer chain. For this we introduce and analyze the properties of an order parameter that can both reveal the presence of different length scales and can also probe the phase structure. We first develop our concepts in the case of chiral homopolymers. We introduce a variant of Kadanoff's block-spin transformation to coarse grain piecewise linear chains, such as the C α backbone of a protein. We derive analytically, and then verify numerically, a number of properties that the order parameter can display, in the case of a chiral polymer chain. In particular, we propose that in the case of a chiral heteropolymer the order parameter can reveal traits of several different phases, contingent on the length scale at which it is scrutinized. We confirm that this is the case with crystallographic protein structures in the Protein Data Bank. Thus our results suggest relations between the scales, the phases, and the complexity of folding pathways.

SOMBI: Bayesian identification of parameter relations in unstructured cosmological data

NASA Astrophysics Data System (ADS)

Frank, Philipp; Jasche, Jens; Enßlin, Torsten A.

2016-11-01

This work describes the implementation and application of a correlation determination method based on self organizing maps and Bayesian inference (SOMBI). SOMBI aims to automatically identify relations between different observed parameters in unstructured cosmological or astrophysical surveys by automatically identifying data clusters in high-dimensional datasets via the self organizing map neural network algorithm. Parameter relations are then revealed by means of a Bayesian inference within respective identified data clusters. Specifically such relations are assumed to be parametrized as a polynomial of unknown order. The Bayesian approach results in a posterior probability distribution function for respective polynomial coefficients. To decide which polynomial order suffices to describe correlation structures in data, we include a method for model selection, the Bayesian information criterion, to the analysis. The performance of the SOMBI algorithm is tested with mock data. As illustration we also provide applications of our method to cosmological data. In particular, we present results of a correlation analysis between galaxy and active galactic nucleus (AGN) properties provided by the SDSS catalog with the cosmic large-scale-structure (LSS). The results indicate that the combined galaxy and LSS dataset indeed is clustered into several sub-samples of data with different average properties (for example different stellar masses or web-type classifications). The majority of data clusters appear to have a similar correlation structure between galaxy properties and the LSS. In particular we revealed a positive and linear dependency between the stellar mass, the absolute magnitude and the color of a galaxy with the corresponding cosmic density field. A remaining subset of data shows inverted correlations, which might be an artifact of non-linear redshift distortions.

On Theoretical Limits of Dynamic Model Updating Using a Sensitivity-Based Approach

NASA Astrophysics Data System (ADS)

GOLA, M. M.; SOMÀ, A.; BOTTO, D.

2001-07-01

The present work deals with the determination of the newly discovered conditions necessary for model updating with the eigensensitivity approach. The treatment concerns the maximum number of identifiable parameters regarding the structure of the eigenvectors derivatives. A mathematical demonstration is based on the evaluation of the rank of the least-squares matrix and produces the algebraic limiting conditions. Numerical application to a lumped parameter structure is employed to validate the mathematical limits taking into account different subsets of mode shapes. The demonstration is extended to the calculation of the eigenvector derivatives with both the Fox and Kapoor, and Nelson methods. III conditioning of the least-squares sensitivity matrix is revealed through the covariance jump.

Sensitivity analysis of infectious disease models: methods, advances and their application

PubMed Central

Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

2013-01-01

Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

Fast Bayesian approach for modal identification using forced vibration data considering the ambient effect

NASA Astrophysics Data System (ADS)

Ni, Yan-Chun; Zhang, Feng-Liang

2018-05-01

Modal identification based on vibration response measured from real structures is becoming more popular, especially after benefiting from the great improvement of the measurement technology. The results are reliable to estimate the dynamic performance, which fits the increasing requirement of different design configurations of the new structures. However, the high-quality vibration data collection technology calls for a more accurate modal identification method to improve the accuracy of the results. Through the whole measurement process of dynamic testing, there are many aspects that will cause the rise of uncertainty, such as measurement noise, alignment error and modeling error, since the test conditions are not directly controlled. Depending on these demands, a Bayesian statistical approach is developed in this work to estimate the modal parameters using the forced vibration response of structures, simultaneously considering the effect of the ambient vibration. This method makes use of the Fast Fourier Transform (FFT) of the data in a selected frequency band to identify the modal parameters of the mode dominating this frequency band and estimate the remaining uncertainty of the parameters correspondingly. In the existing modal identification methods for forced vibration, it is generally assumed that the forced vibration response dominates the measurement data and the influence of the ambient vibration response is ignored. However, ambient vibration will cause modeling error and affect the accuracy of the identified results. The influence is shown in the spectra as some phenomena that are difficult to explain and irrelevant to the mode to be identified. These issues all mean that careful choice of assumptions in the identification model and fundamental formulation to account for uncertainty are necessary. During the calculation, computational difficulties associated with calculating the posterior statistics are addressed. Finally, a fast computational algorithm is proposed so that the method can be practically implemented. Numerical verification with synthetic data and applicable investigation with full-scale field structures data are all carried out for the proposed method.

Process and assembly plans for low cost commercial fuselage structure

NASA Technical Reports Server (NTRS)

Willden, Kurtis; Metschan, Stephen; Starkey, Val

1991-01-01

Cost and weight reduction for a composite structure is a result of selecting design concepts that can be built using efficient low cost manufacturing and assembly processes. Since design and manufacturing are inherently cost dependent, concurrent engineering in the form of a Design-Build Team (DBT) is essential for low cost designs. Detailed cost analysis from DBT designs and hardware verification must be performed to identify the cost drivers and relationships between design and manufacturing processes. Results from the global evaluation are used to quantitatively rank design, identify cost centers for higher ranking design concepts, define and prioritize a list of technical/economic issues and barriers, and identify parameters that control concept response. These results are then used for final design optimization.

Aerodynamic and structural studies of joined-wing aircraft

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Smith, Stephen; Gallman, John

1991-01-01

A method for rapidly evaluating the structural and aerodynamic characteristics of joined-wing aircraft was developed and used to study the fundamental advantages attributed to this concept. The technique involves a rapid turnaround aerodynamic analysis method for computing minimum trimmed drag combined with a simple structural optimization. A variety of joined-wing designs are compared on the basis of trimmed drag, structural weight, and, finally, trimmed drag with fixed structural weight. The range of joined-wing design parameters resulting in best cruise performance is identified. Structural weight savings and net drag reductions are predicted for certain joined-wing configurations compared with conventional cantilever-wing configurations.

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

PubMed

Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry

2018-06-19

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

Spin dynamics in the stripe-ordered buckled honeycomb lattice antiferromagnet Ba 2 NiTeO 6

DOE PAGES

Asai, Shinichiro; Soda, Minoru; Kasatani, Kazuhiro; ...

2017-09-01

We carried out inelastic neutron scattering experiments on a buckled honeycomb lattice antiferromagnet Ba 2NiTeO 6 exhibiting a stripe structure at a low temperature. Magnetic excitations are observed in the energy range of ℏω≲10 meV having an anisotropy gap of 2 meV at 2 K. We perform spin-wave calculations to identify the spin model. The obtained microscopic parameters are consistent with the location of the stripe structure in the classical phase diagram. Furthermore, the Weiss temperature independently estimated from a bulk magnetic susceptibility is consistent with the microscopic parameters. The results reveal that a competition between the nearest-neighbor and next-nearest-neighbormore » interactions that together with a relatively large single-ion magnetic anisotropy stabilize the stripe magnetic structure.« less

Spin dynamics in the stripe-ordered buckled honeycomb lattice antiferromagnet Ba 2 NiTeO 6

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

Asai, Shinichiro; Soda, Minoru; Kasatani, Kazuhiro

We carried out inelastic neutron scattering experiments on a buckled honeycomb lattice antiferromagnet Ba 2NiTeO 6 exhibiting a stripe structure at a low temperature. Magnetic excitations are observed in the energy range of ℏω≲10 meV having an anisotropy gap of 2 meV at 2 K. We perform spin-wave calculations to identify the spin model. The obtained microscopic parameters are consistent with the location of the stripe structure in the classical phase diagram. Furthermore, the Weiss temperature independently estimated from a bulk magnetic susceptibility is consistent with the microscopic parameters. The results reveal that a competition between the nearest-neighbor and next-nearest-neighbormore » interactions that together with a relatively large single-ion magnetic anisotropy stabilize the stripe magnetic structure.« less

Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling

NASA Astrophysics Data System (ADS)

Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.

2016-04-01

Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.

Effect of microwave argon plasma on the glycosidic and hydrogen bonding system of cotton cellulose.

PubMed

Prabhu, S; Vaideki, K; Anitha, S

2017-01-20

Cotton fabric was processed with microwave (Ar) plasma to alter its hydrophilicity. The process parameters namely microwave power, process gas pressure and processing time were optimized using Box-Behnken method available in the Design Expert software. It was observed that certain combinations of process parameters improved existing hydrophilicity while the other combinations decreased it. ATR-FTIR spectral analysis was used to identify the strain induced in inter chain, intra chain, and inter sheet hydrogen bond and glycosidic covalent bond due to plasma treatment. X-ray diffraction (XRD) studies was used to analyze the effect of plasma on unit cell parameters and degree of crystallinity. Fabric surface etching was identified using FESEM analysis. Thus, it can be concluded that the increase/decrease in the hydrophilicity of the plasma treated fabric was due to these structural and physical changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Physico-chemical characterization of products from vacuum oil under delayed coking process by infrared spectroscopy and chemometrics methods

NASA Astrophysics Data System (ADS)

Meléndez, L. V.; Cabanzo, R.; Mejía-Ospino, E.; Guzmán, A.

2016-02-01

Eight vacuum residues and their delayed coking liquids products from Colombian crude were study by infrared spectroscopy with attenuated total reflectance (FTIR-ATR) and principal component analysis (PCA). For the samples the structural parameters of aromaticity factor (fa), alifaticity (A2500-3100cm-1), aromatic condensation degree (GCA), length of aliphatic chains (LCA) and aliphatic chain length associated with aromatic (LACAR) were determined through the development of a methodology, which includes the previous processing of spectroscopy data, identifying the regions in the IR spectra of greatest variance using PCA and molecules patterns. The parameters were compared with the results obtained from proton magnetic resonance (1H-NMR) and 13C-NMR. The results showed the influence and correlation of structural parameters with some physicochemical properties such as API gravity, weight percent sulphur (% S) and Conradson carbon content (% CCR)

Calibration of a flexible measurement system based on industrial articulated robot and structured light sensor

NASA Astrophysics Data System (ADS)

Mu, Nan; Wang, Kun; Xie, Zexiao; Ren, Ping

2017-05-01

To realize online rapid measurement for complex workpieces, a flexible measurement system based on an articulated industrial robot with a structured light sensor mounted on the end-effector is developed. A method for calibrating the system parameters is proposed in which the hand-eye transformation parameters and the robot kinematic parameters are synthesized in the calibration process. An initial hand-eye calibration is first performed using a standard sphere as the calibration target. By applying the modified complete and parametrically continuous method, we establish a synthesized kinematic model that combines the initial hand-eye transformation and distal link parameters as a whole with the sensor coordinate system as the tool frame. According to the synthesized kinematic model, an error model is constructed based on spheres' center-to-center distance errors. Consequently, the error model parameters can be identified in a calibration experiment using a three-standard-sphere target. Furthermore, the redundancy of error model parameters is eliminated to ensure the accuracy and robustness of the parameter identification. Calibration and measurement experiments are carried out based on an ER3A-C60 robot. The experimental results show that the proposed calibration method enjoys high measurement accuracy, and this efficient and flexible system is suitable for online measurement in industrial scenes.

Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

PubMed

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

Lithology-derived structure classification from the joint interpretation of magnetotelluric and seismic models

USGS Publications Warehouse

Bedrosian, P.A.; Maercklin, N.; Weckmann, U.; Bartov, Y.; Ryberg, T.; Ritter, O.

2007-01-01

Magnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physical properties in a joint parameter space and is independent of theoretical or empirical relations linking electrical and seismic parameters. Regions of high correlation (classes) between resistivity and velocity can in turn be mapped back and re-examined in depth section. The spatial distribution of these classes, and the boundaries between them, provide structural information not evident in the individual models. This method is applied to a 10 km long profile crossing the Dead Sea Transform in Jordan. Several prominent classes are identified with specific lithologies in accordance with local geology. An abrupt change in lithology across the fault, together with vertical uplift of the basement suggest the fault is sub-vertical within the upper crust. ?? 2007 The Authors Journal compilation ?? 2007 RAS.

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

Identification and management of filament-wound case stiffness parameters

NASA Technical Reports Server (NTRS)

Verderaime, V.; Rheinfurth, M.

1983-01-01

The high specific strength and the high specific modules made graphite epoxy laminate an expedient material substitute for the Shuttle Solid Rocket Motor steel case to substantially increase the payload performance without increasing the composite case axial growth during thrust build up which was constrained to minimize liftoff excitation effects on existing structural elements and interfaces. Parameters associated with axial growth were identified for quality and manufacturing controls. Included is an innovative method for experimentally verifying extensional elastic properties on a laminate pressurized test bottle.

Inverse problems in the design, modeling and testing of engineering systems

NASA Technical Reports Server (NTRS)

Alifanov, Oleg M.

1991-01-01

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions.

PubMed

Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen; Plósz, Benedek Gy

2014-10-15

Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

Static network analysis of a pork supply chain in Northern Germany-Characterisation of the potential spread of infectious diseases via animal movements.

PubMed

Büttner, Kathrin; Krieter, Joachim; Traulsen, Arne; Traulsen, Imke

2013-07-01

Transport of live animals is a major risk factor in the spread of infectious diseases between holdings. The present study analysed the pork supply chain of a producer community in Northern Germany. The structure of trade networks can be characterised by carrying out a network analysis. To identify holdings with a central position in this directed network of pig production, several parameters describing these properties were measured (in-degree, out-degree, ingoing and outgoing infection chain, betweenness centrality and ingoing and outgoing closeness centrality). To obtain the importance of the different holding types (multiplier, farrowing farms, finishing farms and farrow-to-finishing farms) within the pyramidal structure of the pork supply chain, centrality parameters were calculated for the entire network as well as for the individual holding types. Using these centrality parameters, two types of holdings could be identified. In the network studied, finishing and farrow-to-finishing farms were more likely to be infected due to the high number of ingoing trade contacts. Due to the high number of outgoing trade contacts multipliers and farrowing farms had an increased risk to spread a disease to other holdings. However, the results of the centrality parameters degree and infection chain were not always consistent, such that the indirect trade contacts should be taken into consideration to understand the real importance of a holding in spreading or contracting an infection. Furthermore, all calculated parameters showed a highly right-skewed distribution. Networks with such a degree distribution are considered to be highly resistant concerning the random removal of nodes. But by strategic removal of the most central holdings, e.g. by trade restrictions or selective vaccination or culling, the network structure can be changed efficiently and thus decompose into fragments. Such a fragmentation of the trade networks is of particular importance from an epidemiological perspective. Copyright © 2013 Elsevier B.V. All rights reserved.

Impact force as a scaling parameter

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.; Jackson, Wade C.

1994-01-01

The Federal Aviation Administration (FAR PART 25) requires that a structure carry ultimate load with nonvisible impact damage and carry 70 percent of limit flight loads with discrete damage. The Air Force has similar criteria (MIL-STD-1530A). Both civilian and military structures are designed by a building block approach. First, critical areas of the structure are determined, and potential failure modes are identified. Then, a series of representative specimens are tested that will fail in those modes. The series begins with tests of simple coupons, progresses through larger and more complex subcomponents, and ends with a test on a full-scale component, hence the term 'building block.' In order to minimize testing, analytical models are needed to scale impact damage and residual strength from the simple coupons to the full-scale component. Using experiments and analysis, the present paper illustrates that impact damage can be better understood and scaled using impact force than just kinetic energy. The plate parameters considered are size and thickness, boundary conditions, and material, and the impact parameters are mass, shape, and velocity.

Theoretical study on the antitumor properties of Ru(II) complexes containing 2-pyridyl, 2-pyridine-4-carboxylic acid ligands

NASA Astrophysics Data System (ADS)

Erkan kariper, Sultan; Sayin, Koray; Karakaş, Duran

2017-12-01

[Ru(bipy)2(CppH)]2+(1), [Ru(bipy)2(Cpp-NH-Hex-COOH)]2+(2), [Ru(dppz)2(CppH)]2+(3) and [Ru(dppz)2(Cpp-NH-Hex-COOH)]2+(4) were calculated by Hartree-Fock (HF), Density Functional Theory (DFT) hybrid B3LYP and Moller-Plesset Perturbation (MPn n = 2,3) theory method and CEP-4G, CEP-31G, CEP-121G, LANL2DZ, LANL2MB, SDD basic sets and a mixed basic set with the keyword GEN in gas phase and water. Structure parameters obtained from optimized structures were compared with experimental parameters. M062X/(6-31G(d))(CEP-4G) level was taken into account for the most appropriate calculation level. IR, UV-VIS and NMR spectrums were examined for structural characterization. The optimal structure was identified via structure parameters, IR, UV-VIS and NMR spectrums. For the most compatible structure, the highest molecular orbital energy (EHOMO) which one of the most effective chemical determiners on the antitumor activity of the complexes, the lowest molecular orbital energy (ELUMO), LUMO-HOMO energy gap, hardness (η), softness (σ), electronegativity (χ), chemical potential (μ), electrophilicity index (ω), molar volume (V), dipole moment (DM), total negative charge (TNC), enthalpy (H), entropy (S) and total energy (E) were calculated. The causes of anticancer activity of the complexes have been studied.

Phononic Band Gaps in 2D Quadratic and 3D Cubic Cellular Structures

PubMed Central

Warmuth, Franziska; Körner, Carolin

2015-01-01

The static and dynamic mechanical behaviour of cellular materials can be designed by the architecture of the underlying unit cell. In this paper, the phononic band structure of 2D and 3D cellular structures is investigated. It is shown how the geometry of the unit cell influences the band structure and eventually leads to full band gaps. The mechanism leading to full band gaps is elucidated. Based on this knowledge, a 3D cellular structure with a broad full band gap is identified. Furthermore, the dependence of the width of the gap on the geometry parameters of the unit cell is presented. PMID:28793713

Phononic Band Gaps in 2D Quadratic and 3D Cubic Cellular Structures.

PubMed

Warmuth, Franziska; Körner, Carolin

2015-12-02

The static and dynamic mechanical behaviour of cellular materials can be designed by the architecture of the underlying unit cell. In this paper, the phononic band structure of 2D and 3D cellular structures is investigated. It is shown how the geometry of the unit cell influences the band structure and eventually leads to full band gaps. The mechanism leading to full band gaps is elucidated. Based on this knowledge, a 3D cellular structure with a broad full band gap is identified. Furthermore, the dependence of the width of the gap on the geometry parameters of the unit cell is presented.

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

NASA Technical Reports Server (NTRS)

Juang, J. N.; Pappa, R. S.

1985-01-01

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Damage localization and quantification of composite stratified beam Structures using residual force method

NASA Astrophysics Data System (ADS)

Behtani, A.; Bouazzouni, A.; Khatir, S.; Tiachacht, S.; Zhou, Y.-L.; Abdel Wahab, M.

2017-05-01

In this paper, the problem of using measured modal parameters to detect and locate damage in beam composite stratified structures with four layers of graphite/epoxy [0°/902°/0°] is investigated. A technique based on the residual force method is applied to composite stratified structure with different boundary conditions, the results of damage detection for several damage cases demonstrate that using residual force method as damage index, the damage location can be identified correctly and the damage extents can be estimated as well.

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Fasanella, Edwin L.; Melis, Matthew; Carney, Kelly; Gabrys, Jonathan

2004-01-01

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Wiener-Hammerstein system identification - an evolutionary approach

NASA Astrophysics Data System (ADS)

Naitali, Abdessamad; Giri, Fouad

2016-01-01

The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

Autonomous Modal Identification of the Space Shuttle Tail Rudder

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; James, George H., III; Zimmerman, David C.

1997-01-01

Autonomous modal identification automates the calculation of natural vibration frequencies, damping, and mode shapes of a structure from experimental data. This technology complements damage detection techniques that use continuous or periodic monitoring of vibration characteristics. The approach shown in the paper incorporates the Eigensystem Realization Algorithm (ERA) as a data analysis engine and an autonomous supervisor to condense multiple estimates of modal parameters using ERA's Consistent-Mode Indicator and correlation of mode shapes. The procedure was applied to free-decay responses of a Space Shuttle tail rudder and successfully identified the seven modes of the structure below 250 Hz. The final modal parameters are a condensed set of results for 87 individual ERA cases requiring approximately five minutes of CPU time on a DEC Alpha computer.

Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Dong, Keqiang; Zhang, Hong; Gao, You

2017-01-01

Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.

Reynolds number influence on the formation of vortical structures on a pitching flat plate.

PubMed

Widmann, Alexander; Tropea, Cameron

2017-02-06

The impact of chord-based Reynolds number on the formation of leading-edge vortices (LEVs) on unsteady pitching flat plates is investigated. The influence of secondary flow structures on the shear layer feeding the LEV and the subsequent topological change at the leading edge as the result of viscous processes are demonstrated. Time-resolved velocity fields are measured using particle image velocimetry simultaneously in two fields of view to correlate local and global flow phenomena in order to identify unsteady boundary-layer separation and the subsequent flow structures. Finally, the Reynolds number is identified as a parameter that is responsible for the transition in mechanisms leading to LEV detachment from an aerofoil, as it determines the viscous response of the boundary layer in the vortex-wall interaction.

Reynolds number influence on the formation of vortical structures on a pitching flat plate

PubMed Central

Tropea, Cameron

2017-01-01

The impact of chord-based Reynolds number on the formation of leading-edge vortices (LEVs) on unsteady pitching flat plates is investigated. The influence of secondary flow structures on the shear layer feeding the LEV and the subsequent topological change at the leading edge as the result of viscous processes are demonstrated. Time-resolved velocity fields are measured using particle image velocimetry simultaneously in two fields of view to correlate local and global flow phenomena in order to identify unsteady boundary-layer separation and the subsequent flow structures. Finally, the Reynolds number is identified as a parameter that is responsible for the transition in mechanisms leading to LEV detachment from an aerofoil, as it determines the viscous response of the boundary layer in the vortex–wall interaction. PMID:28163871

Activation and thermodynamic parameter study of the heteronuclear C=O···H-N hydrogen bonding of diphenylurethane isomeric structures by FT-IR spectroscopy using the regularized inversion of an eigenvalue problem.

PubMed

Spegazzini, Nicolas; Siesler, Heinz W; Ozaki, Yukihiro

2012-08-02

The doublet of the ν(C=O) carbonyl band in isomeric urethane systems has been extensively discussed in qualitative terms on the basis of FT-IR spectroscopy of the macromolecular structures. Recently, a reaction extent model was proposed as an inverse kinetic problem for the synthesis of diphenylurethane for which hydrogen-bonded and non-hydrogen-bonded C=O functionalities were identified. In this article, the heteronuclear C=O···H-N hydrogen bonding in the isomeric structure of diphenylurethane synthesized from phenylisocyanate and phenol was investigated via FT-IR spectroscopy, using a methodology of regularization for the inverse reaction extent model through an eigenvalue problem. The kinetic and thermodynamic parameters of this system were derived directly from the spectroscopic data. The activation and thermodynamic parameters of the isomeric structures of diphenylurethane linked through a hydrogen bonding equilibrium were studied. The study determined the enthalpy (ΔH = 15.25 kJ/mol), entropy (TΔS = 14.61 kJ/mol), and free energy (ΔG = 0.6 kJ/mol) of heteronuclear C=O···H-N hydrogen bonding by FT-IR spectroscopy through direct calculation from the differences in the kinetic parameters (δΔ(‡)H, -TδΔ(‡)S, and δΔ(‡)G) at equilibrium in the chemical reaction system. The parameters obtained in this study may contribute toward a better understanding of the properties of, and interactions in, supramolecular systems, such as the switching behavior of hydrogen bonding.

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

Controlling microtube permeability via grafted polymers and solvent quality.

PubMed

Suo, Tongchuan; Whitmore, Mark D

2014-03-21

We examine pressure-driven flow through a microtube with grafted polymers using a "doubly self-consistent field" steady-state theory. Our focus is on the structure of the polymer layer, the tube permeability, and the effects of solvent quality, for different regimes of open and closed tubes. We find that, within experimentally attainable pressure gradients, the flow has very little effect on the grafted layer. However, the polymers, and in particular variations in the solvent quality and cylinder radii, can have large effects on the flow. We find that the permeability can either increase or decrease with either the radius or solvent quality, and we identify the regimes for different behaviors in terms of general parameters that can be used to generalize to other systems. This allows us to identify regimes where the systems are most sensitive to these "tuning" parameters, and we find that they correspond to the boundaries between open and closed tubes identified earlier.

PRince: a web server for structural and physicochemical analysis of protein-RNA interface.

PubMed

Barik, Amita; Mishra, Abhishek; Bahadur, Ranjit Prasad

2012-07-01

We have developed a web server, PRince, which analyzes the structural features and physicochemical properties of the protein-RNA interface. Users need to submit a PDB file containing the atomic coordinates of both the protein and the RNA molecules in complex form (in '.pdb' format). They should also mention the chain identifiers of interacting protein and RNA molecules. The size of the protein-RNA interface is estimated by measuring the solvent accessible surface area buried in contact. For a given protein-RNA complex, PRince calculates structural, physicochemical and hydration properties of the interacting surfaces. All these parameters generated by the server are presented in a tabular format. The interacting surfaces can also be visualized with software plug-in like Jmol. In addition, the output files containing the list of the atomic coordinates of the interacting protein, RNA and interface water molecules can be downloaded. The parameters generated by PRince are novel, and users can correlate them with the experimentally determined biophysical and biochemical parameters for better understanding the specificity of the protein-RNA recognition process. This server will be continuously upgraded to include more parameters. PRince is publicly accessible and free for use. Available at http://www.facweb.iitkgp.ernet.in/~rbahadur/prince/home.html.

Internal rotation in halogenated toluenes: Rotational spectrum of 2,3-difluorotoluene

NASA Astrophysics Data System (ADS)

Nair, K. P. Rajappan; Herbers, Sven; Grabow, Jens-Uwe; Lesarri, Alberto

2018-07-01

The microwave rotational spectrum of 2,3-difluorotoluene has been studied by pulsed supersonic jet using Fourier transform microwave spectroscopy. The tunneling splitting due to the methyl internal rotation in the ground torsional state could be unambiguously identified and the three-fold (V3) potential barrier hindering the internal rotation of the methyl top was determined as 2518.70(15) J/mol. The ground-state rotational parameters for the parent and seven 13C isotopic species in natural abundance were determined with high accuracy, including all quartic centrifugal distortion constants. The molecular structure was derived using the substitution (rs) method. From the rotational constants of the different isotopic species the rs structure as well as the r0 structure was determined. Supporting ab initio (MP2) and DFT (B3LYP) calculations provided comparative values for the potential barrier and molecular parameters.

Quantifying Adventitious Error in a Covariance Structure as a Random Effect

PubMed Central

Wu, Hao; Browne, Michael W.

2017-01-01

We present an approach to quantifying errors in covariance structures in which adventitious error, identified as the process underlying the discrepancy between the population and the structured model, is explicitly modeled as a random effect with a distribution, and the dispersion parameter of this distribution to be estimated gives a measure of misspecification. Analytical properties of the resultant procedure are investigated and the measure of misspecification is found to be related to the RMSEA. An algorithm is developed for numerical implementation of the procedure. The consistency and asymptotic sampling distributions of the estimators are established under a new asymptotic paradigm and an assumption weaker than the standard Pitman drift assumption. Simulations validate the asymptotic sampling distributions and demonstrate the importance of accounting for the variations in the parameter estimates due to adventitious error. Two examples are also given as illustrations. PMID:25813463

Sharp Refractory Composite Leading Edges on Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Walker, Sandra P.; Sullivan, Brian J.

2003-01-01

On-going research of advanced sharp refractory composite leading edges for use on hypersonic air-breathing vehicles is presented in this paper. Intense magnitudes of heating and of heating gradients on the leading edge lead to thermal stresses that challenge the survivability of current material systems. A fundamental understanding of the problem is needed to further design development. Methodology for furthering the technology along with the use of advanced fiber architectures to improve the thermal-structural response is explored in the current work. Thermal and structural finite element analyses are conducted for several advanced fiber architectures of interest. A tailored thermal shock parameter for sharp orthotropic leading edges is identified for evaluating composite material systems. The use of the tailored thermal shock parameter has the potential to eliminate the need for detailed thermal-structural finite element analyses for initial screening of material systems being considered for a leading edge component.

Nematicity in stripe ordered cuprates probed via resonant x-ray scattering

DOE PAGES

Achkar, A. J.; Zwiebler, M.; McMahon, Christopher; ...

2016-02-05

We found that in underdoped cuprate superconductors, a rich competition occurs between superconductivity and charge density wave (CDW) order. Whether rotational symmetry-breaking (nematicity) occurs intrinsically and generically or as a consequence of other orders is under debate. Here, we employ resonant x-ray scattering in stripe-ordered superconductors (La,M) 2CuO 4 to probe the relationship between electronic nematicity of the Cu 3d orbitals, structure of the (La,M) 2O 2 layers, and CDW order. We find distinct temperature dependences for the structure of the (La,M) 2O 2 layers and the electronic nematicity of the CuO 2 planes, with only the latter being enhancedmore » by the onset of CDW order. Our results identify electronic nematicity as an order parameter that is distinct from a purely structural order parameter in underdoped striped cuprates.« less

Theoretical Studies on Structures and Relative Stability for Polynitrohexaazaadamantanes

NASA Astrophysics Data System (ADS)

Xu, Xiao-juan; Xiao, He-ming; Wang, Gui-xiang; Ju, Xue-hai

2006-10-01

The density function theory at the B3LYP/6-31G* level was employed to study the structures, including the total energies (EZPE), the geometries, the oxygen balances (OB100), the dipole moments, of polynitro-hexaazaadamantanes (PNHAAs) and the potential candidates of high energy density compounds (HEDCs). The structural parameters of PNHAAs, such as the the maximum N—NO2 bond length (LBmax), the least N—N Mulliken population (BN—N), the least negative charge on the nitro group (QNO2) and OB100, were studied to predict their relative stability or sensitivity (the easiness for initiating a detonation, high sensitivity means low stability). It was found that the same conclusion was drawn from the four parameters. With the number of nitro groups increasing, the stabilities of these compounds decrease. OB100 failed in identifying the isomers, but the EZPE energy and the dipole moment were considered to give more reliable results for the isomers.

Structural characterization of LiCrxMn2-xO4 via a simple reflux technique

NASA Astrophysics Data System (ADS)

Purwaningsih, Dyah; Roto, Roto; Sutrisno, Hari; Purwanto, Agus

2017-03-01

LiCrxMn2-xO4 (x=0; 0.02; 0.04; 0.06; 0.08, 0.10) have been successfully synthesized via a facile and simple reflux technique. The SEM-EDS data confirm the presence of Cr, Mn and O elements in the products, while the XRD pattern suggests that the materials have well-developed cubic crystals. Direct method was applied to extract structural parameters of LiCrxMn2-xO4 using the Fullprof and Oscail software in WinPlotr package program. Materials were refined in the crystal system, and space group of structures Fd3m phase were then identified. The lattice parameters decrease with the decrease in Cr content. The highest Li-O bond length was found for LiCr0.10Mn1.90O4. It was observed that there is no significant change in particle size as Cr content increased.

Distributed control of large space antennas

NASA Technical Reports Server (NTRS)

Cameron, J. M.; Hamidi, M.; Lin, Y. H.; Wang, S. J.

1983-01-01

A systematic way to choose control design parameters and to evaluate performance for large space antennas is presented. The structural dynamics and control properties for a Hoop and Column Antenna and a Wrap-Rib Antenna are characterized. Some results of the effects of model parameter uncertainties to the stability, surface accuracy, and pointing errors are presented. Critical dynamics and control problems for these antenna configurations are identified and potential solutions are discussed. It was concluded that structural uncertainties and model error can cause serious performance deterioration and can even destabilize the controllers. For the hoop and column antenna, large hoop and long meat and the lack of stiffness between the two substructures result in low structural frequencies. Performance can be improved if this design can be strengthened. The two-site control system is more robust than either single-site control systems for the hoop and column antenna.

Nematicity in stripe ordered cuprates probed via resonant x-ray scattering

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

Achkar, A. J.; Zwiebler, M.; McMahon, Christopher

We found that in underdoped cuprate superconductors, a rich competition occurs between superconductivity and charge density wave (CDW) order. Whether rotational symmetry-breaking (nematicity) occurs intrinsically and generically or as a consequence of other orders is under debate. Here, we employ resonant x-ray scattering in stripe-ordered superconductors (La,M) 2CuO 4 to probe the relationship between electronic nematicity of the Cu 3d orbitals, structure of the (La,M) 2O 2 layers, and CDW order. We find distinct temperature dependences for the structure of the (La,M) 2O 2 layers and the electronic nematicity of the CuO 2 planes, with only the latter being enhancedmore » by the onset of CDW order. Our results identify electronic nematicity as an order parameter that is distinct from a purely structural order parameter in underdoped striped cuprates.« less

Structuring of material parameters in lithium niobate crystals with low-mass, high-energy ion radiation

NASA Astrophysics Data System (ADS)

Peithmann, K.; Eversheim, P.-D.; Goetze, J.; Haaks, M.; Hattermann, H.; Haubrich, S.; Hinterberger, F.; Jentjens, L.; Mader, W.; Raeth, N. L.; Schmid, H.; Zamani-Meymian, M.-R.; Maier, K.

2011-10-01

Ferroelectric lithium niobate crystals offer a great potential for applications in modern optics. To provide powerful optical components, tailoring of key material parameters, especially of the refractive index n and the ferroelectric domain landscape, is required. Irradiation of lithium niobate crystals with accelerated ions causes strong structured modifications in the material. The effects induced by low-mass, high-energy ions (such as 3He with 41 MeV, which are not implanted, but transmit through the entire crystal volume) are reviewed. Irradiation yields large changes of the refractive index Δn, improved domain engineering capability within the material along the ion track, and waveguiding structures. The periodic modification of Δn as well as the formation of periodically poled lithium niobate (PPLN) (supported by radiation damage) is described. Two-step knock-on displacement processes, 3He→Nb and 3He→O causing thermal spikes, are identified as origin for the material modifications.

Effect of power and type of substrate on calcium-phosphate coating morphology and microhardness

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

Kulyashova, Ksenia, E-mail: kseniya@ispms.tsc.ru; Glushko, Yurii, E-mail: glushko@ispms.tsc.ru; Sharkeev, Yurii, E-mail: sharkeev@ispms.tsc.ru

2015-10-27

As known, the influence of the different sputtering process parameters and type of substrate on structure of the deposited coating is important to identify, because these parameters are significantly affected on structure of coating. The studies of the morphology and microhardness of calcium-phosphate (CaP) coatings formed and obtained on the surface of titanium, zirconium, titanium and niobium alloy for different values of the power of radio frequency discharge are presented. The increase in the radio frequency (rf) magnetron discharge leads to the formation of a larger grain structure of the coating. The critical depths of indentation for coatings determining themore » value of their microhardness have been estimated. Mechanical properties of the composite material on the basis of the bioinert substrate metal and CaP coatings are superior to the properties of the separate components that make up this composite material.« less

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization.

PubMed

Sánchez, Benjamín J; Pérez-Correa, José R; Agosin, Eduardo

2014-09-01

Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Simulation of Low-Intensity Ultrasound Propagating in a Beagle Dog Dentoalveolar Structure to Investigate the Relations between Ultrasonic Parameters and Cementum Regeneration.

PubMed

Vafaeian, Behzad; Al-Daghreer, Saleh; El-Rich, Marwan; Adeeb, Samer; El-Bialy, Tarek

2015-08-01

The therapeutic effect of low-intensity pulsed ultrasound on orthodontically induced inflammatory root resorption is believed to be brought about through mechanical signals induced by the low-intensity pulsed ultrasound. However, the stimulatory mechanism triggering dental cell response has not been clearly identified yet. The aim of this study was to evaluate possible relations between the amounts of new cementum regeneration and ultrasonic parameters such as pressure amplitude and time-averaged energy density. We used the finite-element method to simulate the previously published experiment on ultrasonic wave propagation in the dentoalveolar structure of beagle dogs. Qualitative relations between the thickness of the regenerated cementum in the experiment and the ultrasonic parameters were observed. Our results indicated that the areas of the root surface with greater ultrasonic pressure were associated with larger amounts of cementum regeneration. However, the establishment of reliable quantitative correlations between ultrasound parameters and cementum regeneration requires more experimental data and simulations. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Economic evaluation in chronic pain: a systematic review and de novo flexible economic model.

PubMed

Sullivan, W; Hirst, M; Beard, S; Gladwell, D; Fagnani, F; López Bastida, J; Phillips, C; Dunlop, W C N

2016-07-01

There is unmet need in patients suffering from chronic pain, yet innovation may be impeded by the difficulty of justifying economic value in a field beset by data limitations and methodological variability. A systematic review was conducted to identify and summarise the key areas of variability and limitations in modelling approaches in the economic evaluation of treatments for chronic pain. The results of the literature review were then used to support the development of a fully flexible open-source economic model structure, designed to test structural and data assumptions and act as a reference for future modelling practice. The key model design themes identified from the systematic review included: time horizon; titration and stabilisation; number of treatment lines; choice/ordering of treatment; and the impact of parameter uncertainty (given reliance on expert opinion). Exploratory analyses using the model to compare a hypothetical novel therapy versus morphine as first-line treatments showed cost-effectiveness results to be sensitive to structural and data assumptions. Assumptions about the treatment pathway and choice of time horizon were key model drivers. Our results suggest structural model design and data assumptions may have driven previous cost-effectiveness results and ultimately decisions based on economic value. We therefore conclude that it is vital that future economic models in chronic pain are designed to be fully transparent and hope our open-source code is useful in order to aspire to a common approach to modelling pain that includes robust sensitivity analyses to test structural and parameter uncertainty.

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

Computational study of the melting-freezing transition in the quantum hard-sphere system for intermediate densities. II. Structural features.

PubMed

Sesé, Luis M; Bailey, Lorna E

2007-04-28

The structural features of the quantum hard-sphere system in the region of the fluid-face-centered-cubic-solid transition, for reduced number densities 0.45

Assessing local structure motifs using order parameters for motif recognition, interstitial identification, and diffusion path characterization

NASA Astrophysics Data System (ADS)

Zimmermann, Nils E. R.; Horton, Matthew K.; Jain, Anubhav; Haranczyk, Maciej

2017-11-01

Structure-property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal closed packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

Joint Model and Parameter Dimension Reduction for Bayesian Inversion Applied to an Ice Sheet Flow Problem

NASA Astrophysics Data System (ADS)

Ghattas, O.; Petra, N.; Cui, T.; Marzouk, Y.; Benjamin, P.; Willcox, K.

2016-12-01

Model-based projections of the dynamics of the polar ice sheets play a central role in anticipating future sea level rise. However, a number of mathematical and computational challenges place significant barriers on improving predictability of these models. One such challenge is caused by the unknown model parameters (e.g., in the basal boundary conditions) that must be inferred from heterogeneous observational data, leading to an ill-posed inverse problem and the need to quantify uncertainties in its solution. In this talk we discuss the problem of estimating the uncertainty in the solution of (large-scale) ice sheet inverse problems within the framework of Bayesian inference. Computing the general solution of the inverse problem--i.e., the posterior probability density--is intractable with current methods on today's computers, due to the expense of solving the forward model (3D full Stokes flow with nonlinear rheology) and the high dimensionality of the uncertain parameters (which are discretizations of the basal sliding coefficient field). To overcome these twin computational challenges, it is essential to exploit problem structure (e.g., sensitivity of the data to parameters, the smoothing property of the forward model, and correlations in the prior). To this end, we present a data-informed approach that identifies low-dimensional structure in both parameter space and the forward model state space. This approach exploits the fact that the observations inform only a low-dimensional parameter space and allows us to construct a parameter-reduced posterior. Sampling this parameter-reduced posterior still requires multiple evaluations of the forward problem, therefore we also aim to identify a low dimensional state space to reduce the computational cost. To this end, we apply a proper orthogonal decomposition (POD) approach to approximate the state using a low-dimensional manifold constructed using ``snapshots'' from the parameter reduced posterior, and the discrete empirical interpolation method (DEIM) to approximate the nonlinearity in the forward problem. We show that using only a limited number of forward solves, the resulting subspaces lead to an efficient method to explore the high-dimensional posterior.

Application of viscous and Iwan modal damping models to experimental measurements from bolted structures

DOE PAGES

Deaner, Brandon J.; Allen, Matthew S.; Starr, Michael James; ...

2015-01-20

Measurements are presented from a two-beam structure with several bolted interfaces in order to characterize the nonlinear damping introduced by the joints. The measurements (all at force levels below macroslip) reveal that each underlying mode of the structure is well approximated by a single degree-of-freedom (SDOF) system with a nonlinear mechanical joint. At low enough force levels, the measurements show dissipation that scales as the second power of the applied force, agreeing with theory for a linear viscously damped system. This is attributed to linear viscous behavior of the material and/or damping provided by the support structure. At larger forcemore » levels, the damping is observed to behave nonlinearly, suggesting that damping from the mechanical joints is dominant. A model is presented that captures these effects, consisting of a spring and viscous damping element in parallel with a four-parameter Iwan model. As a result, the parameters of this model are identified for each mode of the structure and comparisons suggest that the model captures the stiffness and damping accurately over a range of forcing levels.« less

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

PubMed

Sudell, Maria; Kolamunnage-Dona, Ruwanthi; Tudur-Smith, Catrin

2016-12-05

Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied.

Nonlinear dynamics of solitary and optically injected two-element laser arrays with four different waveguide structures: a numerical study.

PubMed

Li, Nianqiang; Susanto, H; Cemlyn, B R; Henning, I D; Adams, M J

2018-02-19

We study the nonlinear dynamics of solitary and optically injected two-element laser arrays with a range of waveguide structures. The analysis is performed with a detailed direct numerical simulation, where high-resolution dynamic maps are generated to identify regions of dynamic instability in the parameter space of interest. Our combined one- and two-parameter bifurcation analysis uncovers globally diverse dynamical regimes (steady-state, oscillation, and chaos) in the solitary laser arrays, which are greatly influenced by static design waveguiding structures, the amplitude-phase coupling factor of the electric field, i.e. the linewidth-enhancement factor, as well as the control parameter, e.g. the pump rate. When external optical injection is introduced to one element of the arrays, we show that the whole system can be either injection-locked simultaneously or display rich, different dynamics outside the locking region. The effect of optical injection is to significantly modify the nature and the regions of nonlinear dynamics from those found in the solitary case. We also show similarities and differences (asymmetry) between the oscillation amplitude of the two elements of the array in specific well-defined regions, which hold for all the waveguiding structures considered. Our findings pave the way to a better understanding of dynamic instability in large arrays of lasers.

A Generative Angular Model of Protein Structure Evolution

PubMed Central

Golden, Michael; García-Portugués, Eduardo; Sørensen, Michael; Mardia, Kanti V.; Hamelryck, Thomas; Hein, Jotun

2017-01-01

Abstract Recently described stochastic models of protein evolution have demonstrated that the inclusion of structural information in addition to amino acid sequences leads to a more reliable estimation of evolutionary parameters. We present a generative, evolutionary model of protein structure and sequence that is valid on a local length scale. The model concerns the local dependencies between sequence and structure evolution in a pair of homologous proteins. The evolutionary trajectory between the two structures in the protein pair is treated as a random walk in dihedral angle space, which is modeled using a novel angular diffusion process on the two-dimensional torus. Coupling sequence and structure evolution in our model allows for modeling both “smooth” conformational changes and “catastrophic” conformational jumps, conditioned on the amino acid changes. The model has interpretable parameters and is comparatively more realistic than previous stochastic models, providing new insights into the relationship between sequence and structure evolution. For example, using the trained model we were able to identify an apparent sequence–structure evolutionary motif present in a large number of homologous protein pairs. The generative nature of our model enables us to evaluate its validity and its ability to simulate aspects of protein evolution conditioned on an amino acid sequence, a related amino acid sequence, a related structure or any combination thereof. PMID:28453724

Perspectives on the Use of Algae as Biological Indicators for Monitoring and Protecting Aquatic Environments, with Special Reference to Malaysian Freshwater Ecosystems

PubMed Central

Omar, Wan Maznah Wan

2010-01-01

Algal communities possess many attributes as biological indicators of spatial and temporal environmental changes. Algal parameters, especially the community structural and functional variables that have been used in biological monitoring programs, are highlighted in this document. Biological indicators like algae have only recently been included in water quality assessments in some areas of Malaysia. The use of algal parameters in identifying various types of water degradation is essential and complementary to other environmental indicators. PMID:24575199

Damage detection of structures identified with deterministic-stochastic models using seismic data.

PubMed

Huang, Ming-Chih; Wang, Yen-Po; Chang, Ming-Lian

2014-01-01

A deterministic-stochastic subspace identification method is adopted and experimentally verified in this study to identify the equivalent single-input-multiple-output system parameters of the discrete-time state equation. The method of damage locating vector (DLV) is then considered for damage detection. A series of shaking table tests using a five-storey steel frame has been conducted. Both single and multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged counterpart has also been studied. This study gives further insights into the scheme in terms of effectiveness, robustness, and limitation for damage localization of frame systems.

Particle agglomerated 3-d nanostructures for photon absorption

NASA Astrophysics Data System (ADS)

Sivayoganathan, Mugunthan

The main objective of this thesis is to investigate the photon absorption properties of particle agglomerated 3-D structures that are synthesized through femtosecond laser ablation of solids. The size and morphology of these particle agglomerated 3-D structures, which can be tailored through adjusting laser parameters, determine the photon absorption property. A systematic theoretical and experimental study was performed to identify the effect of lasers on the size of the formed particles. The literature survey showed that the amount of supersaturation influences the growth rate as well as the nucleation rate of vapour condensed nanoparticles. Based on this theory, a mechanism was formed to explain the control of laser parameters over the size of formed particles. Further, a theoretical explanation was proposed from the experimental results for the transition of particle size distribution modals. These proposed mechanisms and explanations show the variation in particle size in the particle agglomerated 3-D nanostructures with laser parameters. The effect of laser parameters on the formed ring size was studied. Based on the previous studies, a mechanism was proposed for the formation of ring nanoclusters. The laser pulse intensity dependent ponderomotive force was the key force to define the formation of ring nanoclusters. Then the effect of laser parameters on ring size was studied. Structures fabricated on several materials such as graphite, aluminosilicate ceramic, zinc ingot, gold, and titanium were analyzed to show the influence of material properties, laser parameters, and the environmental conditions on the size of ring formed. The studies performed on the structures showed a minimum absorption of 0.75 A.U. in the bandwidth from UV to IR. The absorption spectrum is much wider compared to existing nanomaterials, such as silicon nanostructures and titanium dioxide nanostructures. To the best of the author's knowledge, it is a very competitive absorption rate when compared with the previous nanostructures used in photovoltaic conversion. Several features of nanostructures contribute to the enhancement of this light absorption. The special feature of the structure is that ease to fabricate and modify the properties by varying the laser parameters could make it competitive among other nanostructures available for solar cells.

Combination of volume and perfusion parameters reveals different types of grey matter changes in schizophrenia.

PubMed

Xu, Lixue; Qin, Wen; Zhuo, Chuanjun; Liu, Huaigui; Zhu, Jiajia; Yu, Chunshui

2017-03-27

Diverse brain structural and functional changes have been reported in schizophrenia. Identifying different types of brain changes may help to understand the neural mechanisms and to develop reliable biomarkers in schizophrenia. We aimed to categorize different grey matter changes in schizophrenia based on grey matter volume (GMV) and cerebral blood flow (CBF). Structural and perfusion magnetic resonance imaging data were acquired in 100 schizophrenia patients and 95 healthy comparison subjects. Voxel-based GMV comparison was used to show structural changes, CBF analysis was used to demonstrate functional changes. We identified three types of grey matter changes in schizophrenia: structural and functional impairments in the anterior cingulate cortex and insular cortex, displaying reduction in both GMV and CBF; structural impairment with preserved function in the frontal and temporal cortices, demonstrating decreased GMV with normal CBF; pure functional abnormality in the anterior cingulate cortex and lateral prefrontal cortex and putamen, showing altered CBF with normal GMV. By combination of GMV and CBF, we identified three types of grey matter changes in schizophrenia. These findings may help to understand the complex manifestations and to develop reliable biomarkers in schizophrenia.

Conformational Phase Diagram for Polymers Adsorbed on Ultrathin Nanowires

NASA Astrophysics Data System (ADS)

Vogel, Thomas; Bachmann, Michael

2010-05-01

We study the conformational behavior of a polymer adsorbed at an attractive stringlike nanowire and construct the complete structural phase diagram in dependence of the binding strength and effective thickness of the nanowire. For this purpose, Monte Carlo optimization techniques are employed to identify lowest-energy structures for a coarse-grained model of a polymer in contact with the nanowire. Among the representative conformations in the different phases are, for example, compact droplets attached to the wire and also nanotubelike monolayer films wrapping it in a very ordered way. We here systematically analyze low-energy shapes and structural order parameters to elucidate the transitions between the structural phases.

Conformational phase diagram for polymers adsorbed on ultrathin nanowires.

PubMed

Vogel, Thomas; Bachmann, Michael

2010-05-14

We study the conformational behavior of a polymer adsorbed at an attractive stringlike nanowire and construct the complete structural phase diagram in dependence of the binding strength and effective thickness of the nanowire. For this purpose, Monte Carlo optimization techniques are employed to identify lowest-energy structures for a coarse-grained model of a polymer in contact with the nanowire. Among the representative conformations in the different phases are, for example, compact droplets attached to the wire and also nanotubelike monolayer films wrapping it in a very ordered way. We here systematically analyze low-energy shapes and structural order parameters to elucidate the transitions between the structural phases.

Ultrasonic propagation properties of red oak

Treesearch

Donald E. Yuhas; Bruce G. Isaacson; Daniel L. Schmoldt; Eugene Wengert

1999-01-01

This work was motivated by the need to identify ultrasonic parameters that exhibit the greatest sensitivity to wood degradation as the result of bacterial infection; the so-called ?wetwood? condition. Wetwood infection creates microscopic changes to the wood structure, which then surface as checks and shake following drying. Slower drying schedules can often mitigate...

Probabilistic assessment of smart composite structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Shiao, Michael C.

1994-01-01

A composite wing with spars and bulkheads is used to demonstrate the effectiveness of probabilistic assessment of smart composite structures to control uncertainties in distortions and stresses. Results show that a smart composite wing can be controlled to minimize distortions and to have specified stress levels in the presence of defects. Structural responses such as changes in angle of attack, vertical displacements, and stress in the control and controlled plies are probabilistically assessed to quantify their respective uncertainties. Sensitivity factors are evaluated to identify those parameters that have the greatest influence on a specific structural response. Results show that smart composite structures can be configured to control both distortions and ply stresses to satisfy specified design requirements.

Appropriate evidence sources for populating decision analytic models within health technology assessment (HTA): a systematic review of HTA manuals and health economic guidelines.

PubMed

Zechmeister-Koss, Ingrid; Schnell-Inderst, Petra; Zauner, Günther

2014-04-01

An increasing number of evidence sources are relevant for populating decision analytic models. What is needed is detailed methodological advice on which type of data is to be used for what type of model parameter. We aim to identify standards in health technology assessment manuals and economic (modeling) guidelines on appropriate evidence sources and on the role different types of data play within a model. Documents were identified via a call among members of the International Network of Agencies for Health Technology Assessment and by hand search. We included documents from Europe, the United States, Canada, Australia, and New Zealand as well as transnational guidelines written in English or German. We systematically summarized in a narrative manner information on appropriate evidence sources for model parameters, their advantages and limitations, data identification methods, and data quality issues. A large variety of evidence sources for populating models are mentioned in the 28 documents included. They comprise research- and non-research-based sources. Valid and less appropriate sources are identified for informing different types of model parameters, such as clinical effect size, natural history of disease, resource use, unit costs, and health state utility values. Guidelines do not provide structured and detailed advice on this issue. The article does not include information from guidelines in languages other than English or German, and the information is not tailored to specific modeling techniques. The usability of guidelines and manuals for modeling could be improved by addressing the issue of evidence sources in a more structured and comprehensive format.

Structure-activity correlation in transfection promoted by pyridinium cationic lipids.

PubMed

Parvizi-Bahktar, P; Mendez-Campos, J; Raju, L; Khalique, N A; Jubeli, E; Larsen, H; Nicholson, D; Pungente, M D; Fyles, T M

2016-03-21

The efficiency of the transfection of a plasmid DNA encoding a galactosidase promoted by a series of pyridinium lipids in mixtures with other cationic lipids and neutral lipids was assessed in CHO-K1 cells. We identify key molecular parameters of the lipids in the mixture - clog P, lipid length, partial molar volume - to predict the morphology of the lipid-DNA lipoplex and then correlate these same parameters with transfection efficiency in an in vitro assay. We define a Transfection Index that provides a linear correlation with normalized transfection efficiency over a series of 90 different lipoplex compositions. We also explore the influence of the same set of molecular parameters on the cytotoxicity of the formulations.

Fatigue reassessment for lifetime extension of offshore wind monopile substructures

NASA Astrophysics Data System (ADS)

Ziegler, Lisa; Muskulus, Michael

2016-09-01

Fatigue reassessment is required to decide about lifetime extension of aging offshore wind farms. This paper presents a methodology to identify important parameters to monitor during the operational phase of offshore wind turbines. An elementary effects method is applied to analyze the global sensitivity of residual fatigue lifetimes to environmental, structural and operational parameters. Therefore, renewed lifetime simulations are performed for a case study which consists of a 5 MW turbine with monopile substructure in 20 m water depth. Results show that corrosion, turbine availability, and turbulence intensity are the most influential parameters. This can vary strongly for other settings (water depth, turbine size, etc.) making case-specific assessments necessary.

Parameter identification in ODE models with oscillatory dynamics: a Fourier regularization approach

NASA Astrophysics Data System (ADS)

Chiara D'Autilia, Maria; Sgura, Ivonne; Bozzini, Benedetto

2017-12-01

In this paper we consider a parameter identification problem (PIP) for data oscillating in time, that can be described in terms of the dynamics of some ordinary differential equation (ODE) model, resulting in an optimization problem constrained by the ODEs. In problems with this type of data structure, simple application of the direct method of control theory (discretize-then-optimize) yields a least-squares cost function exhibiting multiple ‘low’ minima. Since in this situation any optimization algorithm is liable to fail in the approximation of a good solution, here we propose a Fourier regularization approach that is able to identify an iso-frequency manifold {{ S}} of codimension-one in the parameter space \

Kinematic measures for upper limb robot-assisted therapy following stroke and correlations with clinical outcome measures: A review.

PubMed

Tran, Vi Do; Dario, Paolo; Mazzoleni, Stefano

2018-03-01

This review classifies the kinematic measures used to evaluate post-stroke motor impairment following upper limb robot-assisted rehabilitation and investigates their correlations with clinical outcome measures. An online literature search was carried out in PubMed, MEDLINE, Scopus and IEEE-Xplore databases. Kinematic parameters mentioned in the studies included were categorized into the International Classification of Functioning, Disability and Health (ICF) domains. The correlations between these parameters and the clinical scales were summarized. Forty-nine kinematic parameters were identified from 67 articles involving 1750 patients. The most frequently used parameters were: movement speed, movement accuracy, peak speed, number of speed peaks, and movement distance and duration. According to the ICF domains, 44 kinematic parameters were categorized into Body Functions and Structure, 5 into Activities and no parameters were categorized into Participation and Personal and Environmental Factors. Thirteen articles investigated the correlations between kinematic parameters and clinical outcome measures. Some kinematic measures showed a significant correlation coefficient with clinical scores, but most were weak or moderate. The proposed classification of kinematic measures into ICF domains and their correlations with clinical scales could contribute to identifying the most relevant ones for an integrated assessment of upper limb robot-assisted rehabilitation treatments following stroke. Increasing the assessment frequency by means of kinematic parameters could optimize clinical assessment procedures and enhance the effectiveness of rehabilitation treatments. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Robust simulation of buckled structures using reduced order modeling

NASA Astrophysics Data System (ADS)

Wiebe, R.; Perez, R. A.; Spottswood, S. M.

2016-09-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

Structure-based control of complex networks with nonlinear dynamics.

PubMed

Zañudo, Jorge Gomez Tejeda; Yang, Gang; Albert, Réka

2017-07-11

What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

Fine structure of modal focusing effect in a three dimensional plasma-sheath-lens formed by disk electrodes

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

Stamate, Eugen, E-mail: eust@dtu.dk; Venture Business Laboratory, Nagoya University, C3-1, Chikusa-ku, Nagoya 464-8603; Yamaguchi, Masahito

2015-08-31

Modal and discrete focusing effects associated with three-dimensional plasma-sheath-lenses show promising potential for applications in ion beam extraction, mass spectrometry, plasma diagnostics and for basic studies of plasma sheath. The ion focusing properties can be adjusted by controlling the geometrical structure of the plasma-sheath-lens and plasma parameters. The positive and negative ion kinetics within the plasma-sheath-lens are investigated both experimentally and theoretically and a modal focusing ring is identified on the surface of disk electrodes. The focusing ring is very sensitive to the sheath thickness and can be used to monitor very small changes in plasma parameters. Three dimensional simulationsmore » are found to be in very good agreement with experiments.« less

Investigation of Spectral Lag and Epeak as Joint Luminosity Indicators in GRBs

NASA Technical Reports Server (NTRS)

White, Nicholas E. (Technical Monitor); Norris, Jay P.

2003-01-01

Models for gamma-ray bursts which invoke jetted, colliding shells would appear to have at least two determinants for luminosity, e.g., observer viewing angle and Lorentz factor, or possibly shell mass. The latter two internal physical parameters may vary from pulse to pulse within a burst, and such variation might be reflected in evolution of observables such as spectral lag and peak in the spectral energy distribution. We analyze bright BATSE bursts using the 16-channel medium energy resolution (MER) data, with time resolutions of 16 and 64 ms, measuring spectral lags and peak energies for significant pulse structures within a burst, identified using a Bayesian block algorithm. We then explore correlations between the measured parameters and total flux for the individual pulse structures.

Thermodynamic, electronic and magnetic properties of intermetallic compounds through statistical models

NASA Astrophysics Data System (ADS)

Cadeville, M. C.; Pierron-Bohnes, V.; Bouzidi, L.; Sanchez, J. M.

1993-01-01

Local and average electronic and magnetic properties of transition metal alloys are strongly correlated to the distribution of atoms on the lattice sites. The ability of some systems to form long range ordered structures at low temperature allows to discuss their properties in term of well identified occupation operators as those related to long range order (LRO) parameters. We show that using theoretical determinations of these LRO parameters through statistical models like the cluster variation method (CVM) developed to simulate the experimental phase diagrams, we are able to reproduce a lot of physical properties. In this paper we focus on two points: (i) a comparison between CVM results and an experimental determination of the LRO parameter by NMR at 59Co in a CoPt3 compound, and (ii) the modelling of the resistivity of ferromagnetic and paramagnetic intermetallic compounds belonging to Co-Pt, Ni-Pt and Fe-Al systems. All experiments were performed on samples in identified thermodynamic states, implying that kinetic effects are thoroughly taken into account.

Dynamic Testing of a Pre-stretched Flexible Tube for Identifying the Factors Affecting Modal Parameter Estimation

NASA Astrophysics Data System (ADS)

Unnikrishnan, Madhusudanan; Rajan, Akash; Basanthvihar Raghunathan, Binulal; Kochupillai, Jayaraj

2017-08-01

Experimental modal analysis is the primary tool for obtaining the fundamental dynamic characteristics like natural frequency, mode shape and modal damping ratio that determine the behaviour of any structure under dynamic loading conditions. This paper discusses about a carefully designed experimental method for calculating the dynamic characteristics of a pre-stretched horizontal flexible tube made of polyurethane material. The factors that affect the modal parameter estimation like the application time of shaker excitation, pause time between successive excitation cycles, averaging and windowing of measured signal, as well as the precautions to be taken during the experiment are explained in detail. The modal parameter estimation is done using MEscopeVESTM software. A finite element based pre-stressed modal analysis of the flexible tube is also done using ANSYS ver.14.0 software. The experimental and analytical results agreed well. The proposed experimental methodology may be extended for carrying out the modal analysis of many flexible structures like inflatables, tires and membranes.

Wing optimization for space shuttle orbiter vehicles

NASA Technical Reports Server (NTRS)

Surber, T. E.; Bornemann, W. E.; Miller, W. D.

1972-01-01

The results were presented of a parametric study performed to determine the optimum wing geometry for a proposed space shuttle orbiter. The results of the study establish the minimum weight wing for a series of wing-fuselage combinations subject to constraints on aerodynamic heating, wing trailing edge sweep, and wing over-hang. The study consists of a generalized design evaluation which has the flexibility of arbitrarily varying those wing parameters which influence the vehicle system design and its performance. The study is structured to allow inputs of aerodynamic, weight, aerothermal, structural and material data in a general form so that the influence of these parameters on the design optimization process can be isolated and identified. This procedure displays the sensitivity of the system design of variations in wing geometry. The parameters of interest are varied in a prescribed fashion on a selected fuselage and the effect on the total vehicle weight is determined. The primary variables investigated are: wing loading, aspect ratio, leading edge sweep, thickness ratio, and taper ratio.

Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

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

Hura, Greg L.; Menon, Angeli L.; Hammel, Michal

2009-07-20

We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection and data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline and found that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes formore » 41 proteins. We believe that high-throughput SAXS is an enabling technology that may change the way that structural genomics research is done.« less

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

Thein, Pyi Soe, E-mail: pyisoethein@yahoo.com; Pramumijoyo, Subagyo; Wilopo, Wahyu

In this study, we investigated the strong ground motion characteristics under Palu City, Indonesia. The shear wave velocity structures evaluated by eight microtremors measurement are the most applicable to determine the thickness of sediments and average shear wave velocity with Vs ≤ 300 m/s. Based on subsurface underground structure models identified, earthquake ground motion was estimated in the future Palu-Koro earthquake by using statistical green’s function method. The seismic microzonation parameters were carried out by considering several significant controlling factors on ground response at January 23, 2005 earthquake.

Thermal Performance of Surface Wick Structures.

NASA Astrophysics Data System (ADS)

Chen, Yongkang; Tavan, Noel; Baker, John; Melvin, Lawrence; Weislogel, Mark

2010-03-01

Microscale surface wick structures that exploit capillary driven flow in interior corners have been designed. In this study we examine the interplay between capillary flow and evaporative heat transfer that effectively reduces the surface temperature. The tests are performed by raising the surface temperature to various levels before the flow is introduced to the surfaces. Certainly heat transfer weakens the capillary driven flow. It is observed, however, the surface temperature can be reduced significantly. The effects of geometric parameters and interconnectivity are to be characterized to identify optimal configurations.

Ab-initio study of pressure evolution of structural, mechanical and magnetic properties of cementite (Fe3C) phase

NASA Astrophysics Data System (ADS)

Gorai, S.; Ghosh, P. S.; Bhattacharya, C.; Arya, A.

2018-04-01

The pressure evolution of phase stability, structural and mechanical properties of Fe3C in ferro-magnetic (FM) and high pressure non magnetic (NM) phase is investigated from first principle calculations. The 2nd order FM to NM phase transition of Fe3C is identified around 60 GPa. Pressure (or density) variation of sound velocities from our ab-initio calculated single crystal elastic constants are determined to predict these parameters at Earth's outer core pressure.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Quantification of uncertainties in the performance of smart composite structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1993-01-01

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

Replica exchange Monte-Carlo simulations of helix bundle membrane proteins: rotational parameters of helices

NASA Astrophysics Data System (ADS)

Wu, H.-H.; Chen, C.-C.; Chen, C.-M.

2012-03-01

We propose a united-residue model of membrane proteins to investigate the structures of helix bundle membrane proteins (HBMPs) using coarse-grained (CG) replica exchange Monte-Carlo (REMC) simulations. To demonstrate the method, it is used to identify the ground state of HBMPs in a CG model, including bacteriorhodopsin (BR), halorhodopsin (HR), and their subdomains. The rotational parameters of transmembrane helices (TMHs) are extracted directly from the simulations, which can be compared with their experimental measurements from site-directed dichroism. In particular, the effects of amphiphilic interaction among the surfaces of TMHs on the rotational angles of helices are discussed. The proposed CG model gives a reasonably good structure prediction of HBMPs, as well as a clear physical picture for the packing, tilting, orientation, and rotation of TMHs. The root mean square deviation (RMSD) in coordinates of Cα atoms of the ground state CG structure from the X-ray structure is 5.03 Å for BR and 6.70 Å for HR. The final structure of HBMPs is obtained from the all-atom molecular dynamics simulations by refining the predicted CG structure, whose RMSD is 4.38 Å for BR and 5.70 Å for HR.

A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes.

PubMed

Miri, Mohammad Saleh; Abràmoff, Michael D; Kwon, Young H; Sonka, Milan; Garvin, Mona K

2017-07-01

Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Measuring this structural parameter requires identification of BMO locations within spectral domain-optical coherence tomography (SD-OCT) volumes. While most automated approaches for segmentation of the BMO either segment the 2D projection of BMO points or identify BMO points in individual B-scans, in this work, we propose a machine-learning graph-based approach for true 3D segmentation of BMO from glaucomatous SD-OCT volumes. The problem is formulated as an optimization problem for finding a 3D path within the SD-OCT volume. In particular, the SD-OCT volumes are transferred to the radial domain where the closed loop BMO points in the original volume form a path within the radial volume. The estimated location of BMO points in 3D are identified by finding the projected location of BMO points using a graph-theoretic approach and mapping the projected locations onto the Bruch's membrane (BM) surface. Dynamic programming is employed in order to find the 3D BMO locations as the minimum-cost path within the volume. In order to compute the cost function needed for finding the minimum-cost path, a random forest classifier is utilized to learn a BMO model, obtained by extracting intensity features from the volumes in the training set, and computing the required 3D cost function. The proposed method is tested on 44 glaucoma patients and evaluated using manual delineations. Results show that the proposed method successfully identifies the 3D BMO locations and has significantly smaller errors compared to the existing 3D BMO identification approaches. Published by Elsevier B.V.

Identification of subsurface structures using electromagnetic data and shape priors

NASA Astrophysics Data System (ADS)

Tveit, Svenn; Bakr, Shaaban A.; Lien, Martha; Mannseth, Trond

2015-03-01

We consider the inverse problem of identifying large-scale subsurface structures using the controlled source electromagnetic method. To identify structures in the subsurface where the contrast in electric conductivity can be small, regularization is needed to bias the solution towards preserving structural information. We propose to combine two approaches for regularization of the inverse problem. In the first approach we utilize a model-based, reduced, composite representation of the electric conductivity that is highly flexible, even for a moderate number of degrees of freedom. With a low number of parameters, the inverse problem is efficiently solved using a standard, second-order gradient-based optimization algorithm. Further regularization is obtained using structural prior information, available, e.g., from interpreted seismic data. The reduced conductivity representation is suitable for incorporation of structural prior information. Such prior information cannot, however, be accurately modeled with a gaussian distribution. To alleviate this, we incorporate the structural information using shape priors. The shape prior technique requires the choice of kernel function, which is application dependent. We argue for using the conditionally positive definite kernel which is shown to have computational advantages over the commonly applied gaussian kernel for our problem. Numerical experiments on various test cases show that the methodology is able to identify fairly complex subsurface electric conductivity distributions while preserving structural prior information during the inversion.

Design Considerations for Thermally Insulating Structural Sandwich Panels for Hypersonic Vehicles

NASA Technical Reports Server (NTRS)

Blosser, Max L.

2016-01-01

Simplified thermal/structural sizing equations were derived for the in-plane loading of a thermally insulating structural sandwich panel. Equations were developed for the strain in the inner and outer face sheets of a sandwich subjected to uniaxial mechanical loads and differences in face sheet temperatures. Simple equations describing situations with no viable solution were developed. Key design parameters, material properties, and design principles are identified. A numerical example illustrates using the equations for a preliminary feasibility assessment of various material combinations and an initial sizing for minimum mass of a sandwich panel.

Identifiability of PBPK Models with Applications to ...

EPA Pesticide Factsheets

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

Characterizing Uncertainty and Variability in PBPK Models ...

EPA Pesticide Factsheets

Mode-of-action based risk and safety assessments can rely upon tissue dosimetry estimates in animals and humans obtained from physiologically-based pharmacokinetic (PBPK) modeling. However, risk assessment also increasingly requires characterization of uncertainty and variability; such characterization for PBPK model predictions represents a continuing challenge to both modelers and users. Current practices show significant progress in specifying deterministic biological models and the non-deterministic (often statistical) models, estimating their parameters using diverse data sets from multiple sources, and using them to make predictions and characterize uncertainty and variability. The International Workshop on Uncertainty and Variability in PBPK Models, held Oct 31-Nov 2, 2006, sought to identify the state-of-the-science in this area and recommend priorities for research and changes in practice and implementation. For the short term, these include: (1) multidisciplinary teams to integrate deterministic and non-deterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through more complete documentation of the model structure(s) and parameter values, the results of sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include: (1) theoretic and practical methodological impro

Stochastic control system parameter identifiability

NASA Technical Reports Server (NTRS)

Lee, C. H.; Herget, C. J.

1975-01-01

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

Turbulent Flow and Sand Dune Dynamics: Identifying Controls on Aeolian Sediment Transport

NASA Astrophysics Data System (ADS)

Weaver, C. M.; Wiggs, G.

2007-12-01

Sediment transport models are founded on cubic power relationships between the transport rate and time averaged flow parameters. These models have achieved limited success and recent aeolian and fluvial research has focused on the modelling and measurement of sediment transport by temporally varying flow conditions. Studies have recognised turbulence as a driving force in sediment transport and have highlighted the importance of coherent flow structures in sediment transport systems. However, the exact mechanisms are still unclear. Furthermore, research in the fluvial environment has identified the significance of turbulent structures for bedform morphology and spacing. However, equivalent research in the aeolian domain is absent. This paper reports the findings of research carried out to characterise the importance of turbulent flow parameters in aeolian sediment transport and determine how turbulent energy and turbulent structures change in response to dune morphology. The relative importance of mean and turbulent wind parameters on aeolian sediment flux was examined in the Skeleton Coast, Namibia. Measurements of wind velocity (using sonic anemometers) and sand transport (using grain impact sensors) at a sampling frequency of 10 Hz were made across a flat surface and along transects on a 9 m high barchan dune. Mean wind parameters and mass sand flux were measured using cup anemometers and wedge-shaped sand traps respectively. Vertical profile data from the sonic anemometers were used to compute turbulence and turbulent stress (Reynolds stress; instantaneous horizontal and vertical fluctuations; coherent flow structures) and their relationship with respect to sand transport and evolving dune morphology. On the flat surface time-averaged parameters generally fail to characterise sand transport dynamics, particularly as the averaging interval is reduced. However, horizontal wind speed correlates well with sand transport even with short averaging times. Quadrant analysis revealed that turbulent events with a positive horizontal component, such as sweeps and outward interactions, were responsible for the majority of sand transport. On the dune surface results demonstrate the development and modification of turbulence and sediment flux in key regions: toe, crest and brink. Analysis suggests that these modifications are directly controlled by streamline curvature and flow acceleration. Conflicting models of dune development, morphology and stability arise when based upon either the dynamics of measured turbulent flow or mean flow.

Structural damage identification using damping: a compendium of uses and features

NASA Astrophysics Data System (ADS)

Cao, M. S.; Sha, G. G.; Gao, Y. F.; Ostachowicz, W.

2017-04-01

The vibration responses of structures under controlled or ambient excitation can be used to detect structural damage by correlating changes in structural dynamic properties extracted from responses with damage. Typical dynamic properties refer to modal parameters: natural frequencies, mode shapes, and damping. Among these parameters, natural frequencies and mode shapes have been investigated extensively for their use in damage characterization by associating damage with reduction in local stiffness of structures. In contrast, the use of damping as a dynamic property to represent structural damage has not been comprehensively elucidated, primarily due to the complexities of damping measurement and analysis. With advances in measurement technologies and analysis tools, the use of damping to identify damage is becoming a focus of increasing attention in the damage detection community. Recently, a number of studies have demonstrated that damping has greater sensitivity for characterizing damage than natural frequencies and mode shapes in various applications, but damping-based damage identification is still a research direction ‘in progress’ and is not yet well resolved. This situation calls for an overall survey of the state-of-the-art and the state-of-the-practice of using damping to detect structural damage. To this end, this study aims to provide a comprehensive survey of uses and features of applying damping in structural damage detection. First, we present various methods for damping estimation in different domains including the time domain, the frequency domain, and the time-frequency domain. Second, we investigate the features and applications of damping-based damage detection methods on the basis of two predominant infrastructure elements, reinforced concrete structures and fiber-reinforced composites. Third, we clarify the influential factors that can impair the capability of damping to characterize damage. Finally, we recommend future research directions for advancing damping-based damage detection. This work holds the promise of (a) helping researchers identify crucial components in damping-based damage detection theories, methods, and technologies, and (b) leading practitioners to better implement damping-based structural damage identification.

Comparing dynamic recording of infiltration by X-Ray tomography to the results of a dual porosity model for structured soils

NASA Astrophysics Data System (ADS)

Lissy, Anne-Sophie; Sammartino, Stephane; Di Pietro, Liliana; Lecompte, François; Ruy, Stephane

2017-04-01

With climate change, preferential flow phenomenon in soil could be predominant in Mediterranean zone. Understanding this phenomenon becomes a fundamental issue for preserving the water resource in quantity (drinking water) and quality (pesticide content). Non-invasive imaging technics, as X-ray tomography, allow studying water infiltration in laboratory with time-lapse imaging to visualize preferential flow path in soil columns (Sammartino et al. 2012). The modeling of water flow with a dual porosity model (matrix and macropores) integrates these fast flow phenomena (Ilhem 2014). These models, however needs more explicit links with the soil structure. The comparison of experimental results of infiltration (dynamics images and mass data) and modeling could improve our comprehension of preferential flow phenomenon and allow a better integration of the functional macroporosity (i.e. which drains water infiltration during a rain event) in such mass transfer models (Sammartino et al. 2015). Soil columns (Ø 12 cm - hauteur 13 cm, clay-loamy & medium sandy loam) have been sampled in the field to preserve their structure (field plowed or not). Several rains have been simulated in the laboratory and the last one was performed in an X-ray medical scanner (Siemens Somatom® 128 slices) at the CIRE platform (INRA, Centre - Val de Loire). Total and functional macro porosities were identified from time lapse tridimensional images. Water dynamics in the porosities was characterized from the identification and analysis of voxels filled by water. With an image resolution of 350μm only water in the largest macropores can be identified. The modeling of these experiments was carried out via the VirtualSoil platform (UMR Emmah, Avignon; www6.inra.fr/vsoil) using a water flow model coupling Darcy-Richards and KDW equations (Di Pietro et al., 2003). The simulated water flux drained by macropores is similar to the experimental hydrograph obtained for rainfalls on soils close to the saturation. The model reproduced well the flow dynamics: (1) breakthrough time (arrival time of the first drop at the bottom of the column) and (2) the total drained water quantity. A sensitivity analysis of this model is in progress in order to determine the influence of each KDW parameters (two kinematic parameters and one dispersion parameter) and to probe where the functional soil structure could be accounted for in the model structure or in the model parameters. First results show that the kinematic parameters modify the breakthrough time and the slope of the drainage curve. Keywords: functional macroporosity, modeling, RX tomography, infiltration, Richards and KDW equations. Sammartino et al., 2012. A novel method to visualize and characterize preferential flow in undisturbed soil cores by using multislice helical CT. Vadose Zone Journal. Sammartino et Lissy, 2015. Identifying the functional macropore network related to preferential flow in structured soils, Vadose Zone Journal, vol. 14, no. 10. Di Pietro et al. 2003. Predicting preferential water flow in soils by traveling-dispersive waves. Journal of Hydrology (278), pp.64-75. Adel Ilhem (2014) - Modélisation des transferts d'eau dans les sols hétérogènes (internship report)

Analysis of Family Structures Reveals Robustness or Sensitivity of Bursting Activity to Parameter Variations in a Half-Center Oscillator (HCO) Model.

PubMed

Doloc-Mihu, Anca; Calabrese, Ronald L

2016-01-01

The underlying mechanisms that support robustness in neuronal networks are as yet unknown. However, recent studies provide evidence that neuronal networks are robust to natural variations, modulation, and environmental perturbations of parameters, such as maximal conductances of intrinsic membrane and synaptic currents. Here we sought a method for assessing robustness, which might easily be applied to large brute-force databases of model instances. Starting with groups of instances with appropriate activity (e.g., tonic spiking), our method classifies instances into much smaller subgroups, called families, in which all members vary only by the one parameter that defines the family. By analyzing the structures of families, we developed measures of robustness for activity type. Then, we applied these measures to our previously developed model database, HCO-db, of a two-neuron half-center oscillator (HCO), a neuronal microcircuit from the leech heartbeat central pattern generator where the appropriate activity type is alternating bursting. In HCO-db, the maximal conductances of five intrinsic and two synaptic currents were varied over eight values (leak reversal potential also varied, five values). We focused on how variations of particular conductance parameters maintain normal alternating bursting activity while still allowing for functional modulation of period and spike frequency. We explored the trade-off between robustness of activity type and desirable change in activity characteristics when intrinsic conductances are altered and identified the hyperpolarization-activated (h) current as an ideal target for modulation. We also identified ensembles of model instances that closely approximate physiological activity and can be used in future modeling studies.

Nonlinear soil parameter effects on dynamic embedment of offshore pipeline on soft clay

NASA Astrophysics Data System (ADS)

Yu, Su Young; Choi, Han Suk; Lee, Seung Keon; Park, Kyu-Sik; Kim, Do Kyun

2015-06-01

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach

PubMed Central

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R.

2015-01-01

Motivation: Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. Results: In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: julio@iim.csic.es or saezrodriguez@ebi.ac.uk PMID:26002881

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.

PubMed

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2015-09-15

Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary data are available at Bioinformatics online. julio@iim.csic.es or saezrodriguez@ebi.ac.uk. © The Author 2015. Published by Oxford University Press.

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

DOE PAGES

Zimmermann, Nils E. R.; Horton, Matthew K.; Jain, Anubhav; ...

2017-11-13

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify thesemore » basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.« less

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

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

Zimmermann, Nils E. R.; Horton, Matthew K.; Jain, Anubhav

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify thesemore » basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.« less

Progression of trunk imbalance in adolescent idiopathic scoliosis with a thoracolumbar/lumbar curve: is it predictable at the initial visit?

PubMed

Hwang, Chang Ju; Lee, Choon Sung; Lee, Dong-Ho; Cho, Jae Hwan

2017-11-01

OBJECTIVE Progression of trunk imbalance is an important finding during follow-up of patients with adolescent idiopathic scoliosis (AIS). Nevertheless, no factors that predict progression of trunk imbalance have been identified. The purpose of this study was to identify parameters that predict progression of trunk imbalance in cases of AIS with a structural thoracolumbar/lumbar (TL/L) curve. METHODS This study included 105 patients with AIS and a structural TL/L curve who were followed up at an outpatient clinic. Patients with trunk imbalance (trunk shift ≥ 20 mm) at the initial visit were excluded. All patients were followed up for more than 2 years. Patients were divided into the following groups according to progression of trunk imbalance: 1) Group P, trunk shift ≥ 20 mm at the final visit and degree of progression ≥ 10 mm; and 2) Group NP, trunk shift < 20 mm at the final visit or degree of progression < 10 mm. Radiological parameters included Cobb angle, upper end vertebrae and lower end vertebrae (LEV), LEV tilt, disc wedge angle between LEV and LEV+1, trunk shift, apical vertebral translation, and apical vertebral rotation (AVR). Each parameter was compared between groups. Radiological parameters were assessed at every visit using whole-spine standing anteroposterior radiographs. RESULTS Among the 105 patients examined, 13 showed trunk imbalance with progression ≥ 10 mm at the final visit (Group P). Multivariate logistic regression analysis identified a lower Risser grade (p = 0.002) and a greater initial AVR (p = 0.020) as predictors of progressive trunk imbalance. A change in LEV tilt during follow-up was associated with trunk imbalance (p = 0.001). CONCLUSIONS Risser grade and AVR measured at the initial visit may predict progression of trunk imbalance. Surgeons should consider the risk of progressive trunk imbalance if patients show skeletal immaturity and a greater AVR at the initial visit.

CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS

PubMed Central

Shpitser, Ilya; Tchetgen, Eric Tchetgen

2017-01-01

Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl’s front-door criterion. PMID:28919652

CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.

PubMed

Shpitser, Ilya; Tchetgen, Eric Tchetgen

2016-12-01

Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl's front-door criterion.

Constitutive formulations for the mechanical investigation of colonic tissues.

PubMed

Carniel, Emanuele Luigi; Gramigna, Vera; Fontanella, Chiara Giulia; Stefanini, Cesare; Natali, Arturo N

2014-05-01

A constitutive framework is provided for the characterization of the mechanical behavior of colonic tissues, as a fundamental tool for the development of numerical models of the colonic structures. The constitutive analysis is performed by a multidisciplinary approach that requires the cooperation between experimental and computational competences. The preliminary investigation pertains to the review of the tissues histology. The complex structural configuration of the tissues and the specific distributions of fibrous elements entail the nonlinear mechanical behavior and the anisotropic response. The identification of the mechanical properties requires to perform mechanical tests according to different loading situations, as different loading directions. Because of the typical functionality of colon structures, the tissues mechanics is investigated by tensile tests, which are performed on taenia coli and haustra specimens from fresh pig colons. Accounting for the histological investigation and the results from the mechanical tests, a specific hyperelastic framework is provided within the theory of fiber-reinforced composite materials. Preliminary analytical formulations are defined to identify the constitutive parameters by the inverse analysis of the experimental tests. Finite element models of the specimens are developed accounting for the actual configuration of the colon structures to verify the quality of the results. The good agreement between experimental and numerical model results suggests the reliability of the constitutive formulations and parameters. Finally, the developed constitutive analysis makes it possible to identify the mechanical behavior and properties of the different colonic tissues. Copyright © 2013 Wiley Periodicals, Inc.

Controlling interferometric properties of nanoporous anodic aluminium oxide

PubMed Central

2012-01-01

A study of reflective interference spectroscopy [RIfS] properties of nanoporous anodic aluminium oxide [AAO] with the aim to develop a reliable substrate for label-free optical biosensing is presented. The influence of structural parameters of AAO including pore diameters, inter-pore distance, pore length, and surface modification by deposition of Au, Ag, Cr, Pt, Ni, and TiO2 on the RIfS signal (Fabry-Perot fringe) was explored. AAO with controlled pore dimensions was prepared by electrochemical anodization of aluminium using 0.3 M oxalic acid at different voltages (30 to 70 V) and anodization times (10 to 60 min). Results show the strong influence of pore structures and surface modifications on the interference signal and indicate the importance of optimisation of AAO pore structures for RIfS sensing. The pore length/pore diameter aspect ratio of AAO was identified as a suitable parameter to tune interferometric properties of AAO. Finally, the application of AAO with optimised pore structures for sensing of a surface binding reaction of alkanethiols (mercaptoundecanoic acid) on gold surface is demonstrated. PMID:22280884

Identification of capacitive MEMS accelerometer structure parameters for human body dynamics measurements.

PubMed

Benevicius, Vincas; Ostasevicius, Vytautas; Gaidys, Rimvydas

2013-08-22

Due to their small size, low weight, low cost and low energy consumption, MEMS accelerometers have achieved great commercial success in recent decades. The aim of this research work is to identify a MEMS accelerometer structure for human body dynamics measurements. Photogrammetry was used in order to measure possible maximum accelerations of human body parts and the bandwidth of the digital acceleration signal. As the primary structure the capacitive accelerometer configuration is chosen in such a way that sensing part measures on all three axes as it is 3D accelerometer and sensitivity on each axis is equal. Hill climbing optimization was used to find the structure parameters. Proof-mass displacements were simulated for all the acceleration range that was given by the optimization problem constraints. The final model was constructed in Comsol Multiphysics. Eigenfrequencies were calculated and model's response was found, when vibration stand displacement data was fed into the model as the base excitation law. Model output comparison with experimental data was conducted for all excitation frequencies used during the experiments.

The middeck 0-gravity dynamics experiment

NASA Technical Reports Server (NTRS)

Crawley, Edward F.; Vanschoor, Marthinus C.; Bokhour, Edward B.

1993-01-01

The Middeck 0-Gravity Dynamics Experiment (MODE), flown onboard the Shuttle STS-48 Mission, consists of three major elements: the Experiment Support Module, a dynamics test bed providing computer experiment control, analog signal conditioning, power conditioning, an operator interface consisting of a keypad and display, experiment electrical and thermal control, and archival data storage: the Fluid Test Article assembly, used to investigate the dynamics of fluid-structure interaction in 0-gravity; and the Structural Test Article for investigating the open-loop dynamics of structures in 0-gravity. Deployable, erectable, and rotary modules were assembled to form three one- and two-dimensional structures, in which variations in bracing wire and rotary joint preload could be introduced. Change in linear modal parameters as well as the change in nonlinear nature of the response is examined. Trends in modal parameters are presented as a function of force amplitude, joint preload, and ambient gravity. An experimental study of the lateral slosh behavior of contained fluids is also presented. A comparison of the measured earth and space results identifies and highlights the effects of gravity on the linear and nonlinear slosh behavior of these fluids.

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jędrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jedrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Mimicking bug-like surface structures and their fluid transport produced by ultrashort laser pulse irradiation of steel

NASA Astrophysics Data System (ADS)

Kirner, S. V.; Hermens, U.; Mimidis, A.; Skoulas, E.; Florian, C.; Hischen, F.; Plamadeala, C.; Baumgartner, W.; Winands, K.; Mescheder, H.; Krüger, J.; Solis, J.; Siegel, J.; Stratakis, E.; Bonse, J.

2017-12-01

Ultrashort laser pulses with durations in the fs-to-ps range were used for large area surface processing of steel aimed at mimicking the morphology and extraordinary wetting behaviour of bark bugs (Aradidae) found in nature. The processing was performed by scanning the laser beam over the surface of polished flat sample surfaces. A systematic variation of the laser processing parameters (peak fluence and effective number of pulses per spot diameter) allowed the identification of different regimes associated with characteristic surface morphologies (laser-induced periodic surface structures, i.e., LIPSS, grooves, spikes, etc.). Moreover, different laser processing strategies, varying laser wavelength, pulse duration, angle of incidence, irradiation atmosphere, and repetition rates, allowed to achieve a range of morphologies that resemble specific structures found on bark bugs. For identifying the ideal combination of parameters for mimicking bug-like structures, the surfaces were inspected by scanning electron microscopy. In particular, tilted micrometre-sized spikes are the best match for the structure found on bark bugs. Complementary to the morphology study, the wetting behaviour of the surface structures for water and oil was examined in terms of philic/phobic nature and fluid transport. These results point out a route towards reproducing complex surface structures inspired by nature and their functional response in technologically relevant materials.

Estimation of dynamic rotor loads for the rotor systems research aircraft: Methodology development and validation

NASA Technical Reports Server (NTRS)

Duval, R. W.; Bahrami, M.

1985-01-01

The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.

W3MAMCAT: a world wide web based tool for mammillary and catenary compartmental modeling and expert system distinguishability.

PubMed

Russell, Solomon; Distefano, Joseph J

2006-07-01

W(3)MAMCAT is a new web-based and interactive system for building and quantifying the parameters or parameter ranges of n-compartment mammillary and catenary model structures, with input and output in the first compartment, from unstructured multiexponential (sum-of-n-exponentials) models. It handles unidentifiable as well as identifiable models and, as such, provides finite parameter interval solutions for unidentifiable models, whereas direct parameter search programs typically do not. It also tutorially develops the theory of model distinguishability for same order mammillary versus catenary models, as did its desktop application predecessor MAMCAT+. This includes expert system analysis for distinguishing mammillary from catenary structures, given input and output in similarly numbered compartments. W(3)MAMCAT provides for universal deployment via the internet and enhanced application error checking. It uses supported Microsoft technologies to form an extensible application framework for maintaining a stable and easily updatable application. Most important, anybody, anywhere, is welcome to access it using Internet Explorer 6.0 over the internet for their teaching or research needs. It is available on the Biocybernetics Laboratory website at UCLA: www.biocyb.cs.ucla.edu.

Experimental investigation of the structural behavior of equine urethra.

PubMed

Natali, Arturo Nicola; Carniel, Emanuele Luigi; Frigo, Alessandro; Fontanella, Chiara Giulia; Rubini, Alessandro; Avital, Yochai; De Benedictis, Giulia Maria

2017-04-01

An integrated experimental and computational investigation was developed aiming to provide a methodology for characterizing the structural response of the urethral duct. The investigation provides information that are suitable for the actual comprehension of lower urinary tract mechanical functionality and the optimal design of prosthetic devices. Experimental activity entailed the execution of inflation tests performed on segments of horse penile urethras from both proximal and distal regions. Inflation tests were developed imposing different volumes. Each test was performed according to a two-step procedure. The tubular segment was inflated almost instantaneously during the first step, while volume was held constant for about 300s to allow the development of relaxation processes during the second step. Tests performed on the same specimen were interspersed by 600s of rest to allow the recovery of the specimen mechanical condition. Results from experimental activities were statistically analyzed and processed by means of a specific mechanical model. Such computational model was developed with the purpose of interpreting the general pressure-volume-time response of biologic tubular structures. The model includes parameters that interpret the elastic and viscous behavior of hollow structures, directly correlated with the results from the experimental activities. Post-processing of experimental data provided information about the non-linear elastic and time-dependent behavior of the urethral duct. In detail, statistically representative pressure-volume and pressure relaxation curves were identified, and summarized by structural parameters. Considering elastic properties, initial stiffness ranged between 0.677 ± 0.026kPa and 0.262 ± 0.006kPa moving from proximal to distal region of penile urethra. Viscous parameters showed typical values of soft biological tissues, as τ 1 =0.153±0.018s, τ 2 =17.458 ± 1.644s and τ 1 =0.201 ± 0.085, τ 2 = 8.514 ± 1.379s for proximal and distal regions respectively. A general procedure for the mechanical characterization of the urethral duct has been provided. The proposed methodology allows identifying mechanical parameters that properly express the mechanical behavior of the biological tube. The approach is especially suitable for evaluating the influence of degenerative phenomena on the lower urinary tract mechanical functionality. The information are mandatory for the optimal design of potential surgical procedures and devices. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated selection of computed tomography display parameters using neural networks

NASA Astrophysics Data System (ADS)

Zhang, Di; Neu, Scott; Valentino, Daniel J.

2001-07-01

A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.

A Benchmark Problem for Development of Autonomous Structural Modal Identification

NASA Technical Reports Server (NTRS)

Pappa, Richard S.; Woodard, Stanley E.; Juang, Jer-Nan

1996-01-01

This paper summarizes modal identification results obtained using an autonomous version of the Eigensystem Realization Algorithm on a dynamically complex, laboratory structure. The benchmark problem uses 48 of 768 free-decay responses measured in a complete modal survey test. The true modal parameters of the structure are well known from two previous, independent investigations. Without user involvement, the autonomous data analysis identified 24 to 33 structural modes with good to excellent accuracy in 62 seconds of CPU time (on a DEC Alpha 4000 computer). The modal identification technique described in the paper is the baseline algorithm for NASA's Autonomous Dynamics Determination (ADD) experiment scheduled to fly on International Space Station assembly flights in 1997-1999.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

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

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

Impact of line edge roughness on the performance of 14-nm FinFET: Device-circuit Co-design

NASA Astrophysics Data System (ADS)

Rathore, Rituraj Singh; Rana, Ashwani K.

2018-01-01

With the evolution of sub-20 nm FinFET technology, line edge roughness (LER) has been identified as a critical problem and may result in critical device parameter variation and performance limitation in the future VLSI circuit application. In the present work, an analytical model of fin-LER has been presented, which shows the impact of correlated and uncorrelated LER on FinFET structure. Further, the influence of correlated and uncorrelated fin- LER on all electrical performance parameters is thoroughly investigated using the three-dimensional (3-D) Technology Computer Aided Design (TCAD) simulations for 14-nm technology node. Moreover, the impact of all possible fin shapes on threshold voltage (VTH), drain induced barrier lowering (DIBL), on-current (ION), and off-current (IOFF) has been compared with the well calibrated rectangular FinFET structure. In addition, the influence of all possible fin geometries on the read stability of six-transistor (6-T) Static-Random-Access-Memory (SRAM) has been investigated. The study reveals that fin-LER plays a vital role as it directly governs the electrostatics of the FinFET structure. This has been found that there is a high degree of fluctuations in all performance parameters for uncorrelated fin-LER type FinFETs as compared to correlated fin-LER with respect to rectangular FinFET structure. This paper gives physical insight of FinFET design, especially in sub-20 nm technology nodes by concluding that the impact of LER on electrical parameters are minimum for correlated LER.

Immunoinformatic Analysis of Crimean Congo Hemorrhagic Fever Virus Glycoproteins and Epitope Prediction for Synthetic Peptide Vaccine.

PubMed

Tipu, Hamid Nawaz

2016-02-01

To determine the Crimean Congo Hemorrhagic Fever (CCHF) virus M segement glycoprotein's immunoinformatic parameters, and identify Human Leukocyte Antigen (HLA) class I binders as candidates for synthetic peptide vaccines. Cross-sectional study. Combined Military Hospital, Khuzdar Cantt, in May 2015. Data acquisition, antigenicity prediction, secondary and tertiary structure prediction, residue analysis were done using immunoinformatics tools. HLAclass I binders in glycoprotein's sequence were identified at nanomer length using NetMHC 3.4 and mapped onto tertiary structure. Docking was done for strongest binder against its corresponding allele with CABS-dock. HLAA*0101, 0201, 0301, 2402, 2601 and B*0702, 0801, 2705, 3901, 4001, 5801, 1501 were analyzed against two glycoprotein components of the virus. Atotal of 35 nanomers from GP1, and 3 from GP2 were identified. HLAB*0702 bound maximum number of peptides (6), while HLAB*4001 showed strongest binding affinity. HLAspecific glycoproteins epitope prediction can help identify synthetic peptide vaccine candidates.

Thermal design of composite materials high temperature attachments

NASA Technical Reports Server (NTRS)

1972-01-01

The thermal aspects of using filamentary composite materials as primary airframe structures on advanced atmospheric entry spacecraft such as the space shuttle vehicle were investigated to identify and evaluate potential design approaches for maintaining composite structures within allowable temperature limits at thermal protection system (TPS) attachments and/or penetrations. The investigation included: (1) definition of thermophysical data for composite material structures; (2) parametric characterization and identification of the influence of the aerodynamic heating and attachment design parameters on composite material temperatures; (3) conceptual design, evaluation, and detailed thermal analyses of temperature limiting design concepts; and (4) the development of experimental data for assessment of the thermal design methodologies and data used for evaluation of the temperature-limiting design concepts. Temperature suppression attachment concepts were examined for relative merit. The simple isolator was identified as the most weight-effective concept and was selected for detail design, thermal analysis, and testing. Tests were performed on TPS standoff attachments to boron/aluminum, boron/polyimide and graphite/epoxy composite structures.

A method to identify the main mode of machine tool under operating conditions

NASA Astrophysics Data System (ADS)

Wang, Daming; Pan, Yabing

2017-04-01

The identification of the modal parameters under experimental conditions is the most common procedure when solving the problem of machine tool structure vibration. However, the influence of each mode on the machine tool vibration in real working conditions remains unknown. In fact, the contributions each mode makes to the machine tool vibration during machining process are different. In this article, an active excitation modal analysis is applied to identify the modal parameters in operational condition, and the Operating Deflection Shapes (ODS) in frequencies of high level vibration that affect the quality of machining in real working conditions are obtained. Then, the ODS is decomposed by the mode shapes which are identified in operational conditions. So, the contributions each mode makes to machine tool vibration during machining process are got by decomposition coefficients. From the previous steps, we can find out the main modes which effect the machine tool more significantly in working conditions. This method was also verified to be effective by experiments.

Degree-of-Freedom Strengthened Cascade Array for DOD-DOA Estimation in MIMO Array Systems.

PubMed

Yao, Bobin; Dong, Zhi; Zhang, Weile; Wang, Wei; Wu, Qisheng

2018-05-14

In spatial spectrum estimation, difference co-array can provide extra degrees-of-freedom (DOFs) for promoting parameter identifiability and parameter estimation accuracy. For the sake of acquiring as more DOFs as possible with a given number of physical sensors, we herein design a novel sensor array geometry named cascade array. This structure is generated by systematically connecting a uniform linear array (ULA) and a non-uniform linear array, and can provide more DOFs than some exist array structures but less than the upper-bound indicated by minimum redundant array (MRA). We further apply this cascade array into multiple input multiple output (MIMO) array systems, and propose a novel joint direction of departure (DOD) and direction of arrival (DOA) estimation algorithm, which is based on a reduced-dimensional weighted subspace fitting technique. The algorithm is angle auto-paired and computationally efficient. Theoretical analysis and numerical simulations prove the advantages and effectiveness of the proposed array structure and the related algorithm.

A PREFERENCE-OPPORTUNITY-CHOICE FRAMEWORK WITH APPLICATIONS TO INTERGROUP FRIENDSHIP*

PubMed Central

Zeng, Zhen; Xie, Yu

2009-01-01

A longstanding objective of friendship research is to identify the effects of personal preference and structural opportunity on intergroup friendship choice. Although past studies have used various methods to separate preference from opportunity, researchers have not yet systematically compared the properties and implications of these methods. We put forward a general framework for discrete choice, where choice probability is specified as proportional to the product of preference and opportunity. To implement this framework, we propose a modification to the conditional logit model for estimating preference parameters free from the influence of opportunity structure. We then compare our approach to several alternative methods for separating preference and opportunity used in the friendship choice literature. As an empirical example, we test hypotheses of homophily and status asymmetry in friendship choice using data from the National Longitudinal Study of Adolescent Health. The example also demonstrates the approach of conducting a sensitivity analysis to examine how parameter estimates vary by specification of the opportunity structure. PMID:19569394

Initial planetary base construction techniques and machine implementation

NASA Technical Reports Server (NTRS)

Crockford, William W.

1987-01-01

Conceptual designs of (1) initial planetary base structures, and (2) an unmanned machine to perform the construction of these structures using materials local to the planet are presented. Rock melting is suggested as a possible technique to be used by the machine in fabricating roads, platforms, and interlocking bricks. Identification of problem areas in machine design and materials processing is accomplished. The feasibility of the designs is contingent upon favorable results of an analysis of the engineering behavior of the product materials. The analysis requires knowledge of several parameters for solution of the constitutive equations of the theory of elasticity. An initial collection of these parameters is presented which helps to define research needed to perform a realistic feasibility study. A qualitative approach to estimating power and mass lift requirements for the proposed machine is used which employs specifications of currently available equipment. An initial, unmanned mission scenario is discussed with emphasis on identifying uncompleted tasks and suggesting design considerations for vehicles and primitive structures which use the products of the machine processing.

On predicting monitoring system effectiveness

NASA Astrophysics Data System (ADS)

Cappello, Carlo; Sigurdardottir, Dorotea; Glisic, Branko; Zonta, Daniele; Pozzi, Matteo

2015-03-01

While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

Determination of protein secondary structure and solvent accessibility using site-directed fluorescence labeling. Studies of T4 lysozyme using the fluorescent probe monobromobimane.

PubMed

Mansoor, S E; McHaourab, H S; Farrens, D L

1999-12-07

We report an investigation of how much protein structural information could be obtained using a site-directed fluorescence labeling (SDFL) strategy. In our experiments, we used 21 consecutive single-cysteine substitution mutants in T4 lysozyme (residues T115-K135), located in a helix-turn-helix motif. The mutants were labeled with the fluorescent probe monobromobimane and subjected to an array of fluorescence measurements. Thermal stability measurements show that introduction of the label is substantially perturbing only when it is located at buried residue sites. At buried sites (solvent surface accessibility of <40 A(2)), the destabilizations are between 3 and 5.5 kcal/mol, whereas at more exposed sites, DeltaDeltaG values of < or = 1.5 kcal/mol are obtained. Of all the fluorescence parameters that were explored (excitation lambda(max), emission lambda(max), fluorescence lifetime, quantum yield, and steady-state anisotropy), the emission lambda(max) and the steady-state anisotropy values most accurately reflect the solvent surface accessibility at each site as calculated from the crystal structure of cysteine-less T4 lysozyme. The parameters we identify allow the classification of each site as buried, partially buried, or exposed. We find that the variations in these parameters as a function of residue number reflect the sequence-specific secondary structure, the determination of which is a key step for modeling a protein of unknown structure.

Metal Matrix Superconductor Composites for SMES-Driven, Ultra High Power BEP Applications: Part 2

NASA Astrophysics Data System (ADS)

Gross, Dan A.; Myrabo, Leik N.

2006-05-01

A 2.5 TJ superconducting magnetic energy storage (SMES) design presentation is continued from the preceding paper (Part 1) with electromagnetic and associated stress analysis. The application of interest is a rechargeable power-beaming infrastructure for manned microwave Lightcraft operations. It is demonstrated that while operational performance is within manageable parameter bounds, quench (loss of superconducting state) imposes enormous electrical stresses. Therefore, alternative multiple toroid modular configurations are identified, alleviating simultaneously all excessive stress conditions, operational and quench, in the structural, thermal and electromagnetic sense — at some reduction in specific energy, but presenting programmatic advantages for a lengthy technology development, demonstration and operation schedule. To this end several natural units, based on material properties and operating parameters are developed, in order to identify functional relationships and optimization paths more effectively.

Structured Light Plethysmography (SLP): Management and follow up of a paediatric patient with pneumonia.

PubMed

Ghezzi, Michele; Tenero, Laura; Piazza, Michele; Bodini, Alessandro; Piacentini, Giorgio

2017-01-01

Structured Light Plethysmography (SLP) is a non-invasive method to study chest and abdominal movement during breathing and can identify abnormal contributions of the different regions of the chest. M.D hospitalized for pneumonia, underwent SLP and spirometry at admission (T0), after 48 hours (T1), and after one month (T2). SLP parameters showed expiratory flow limitation, information consistent with the spirometric parameters collected, and reduced motion in the area effected by pneumonia, with improvement and normalization at T1 and T2. This method gave useful information about the contribution to the respiratory movement of the lung area affected by pneumonia so we can speculate a possible use in the follow-up of children affected by pneumonia or other respiratory diseases, and who are not able to perform a spirometric test.

Quantitative Phase Analysis of Plasma-Treated High-Silica Materials

NASA Astrophysics Data System (ADS)

Kosmachev, P. V.; Abzaev, Yu. A.; Vlasov, V. A.

2018-06-01

The paper presents the X-ray diffraction (XRD) analysis of the crystal structure of SiO2 in two modifications, namely quartzite and quartz sand before and after plasma treatment. Plasma treatment enables the raw material to melt and evaporate after which the material quenches and condenses to form nanoparticles. The Rietveld refinement method is used to identify the lattice parameters of SiO2 phases. It is found that after plasma treatment SiO2 oxides are in the amorphous state, which are modeled within the microcanonical ensemble. Experiments show that amorphous phases are stable, and model X-ray reflection intensities approximate the experimental XRD patterns with fine precision. Within the modeling, full information is obtained for SiO2 crystalline and amorphous phases, which includes atom arrangement, structural parameters, atomic population of silicon and oxygen atoms in lattice sites.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Constructive systems, load-bearing and enclosing structures of high-rise buildings

NASA Astrophysics Data System (ADS)

Anatol'evna Korol', Elena; Olegovna Kustikova, Yuliya

2018-03-01

As the height of the building increases, loads on load-carrying structures increase dramatically, and as a result of the development of high-rise construction, several structural systems of such buildings have been developed: frame, frame-frame, cross-wall, barrel, box-type, box-to-wall ("pipe in pipe", "Trumpet in the farm"), etc. In turn, the barrel systems have their own versions: cantilever support of the ceilings on the trunk, suspension of the outer part of the overlap to the upper carrying console "hanging house" or its support by means of the walls on the lower bearing cantilever, intermediate position of the supporting cantilevers in height to the floor, from a part of floors. The object of the study are the structural solutions of high-rise buildings. The subject of the study is the layout of structural schemes of high-rise buildings, taking into account the main parameters - altitude (height), natural climatic conditions of construction, materials of structural elements and their physical and mechanical characteristics. The purpose of the study is to identify the features and systematization of structural systems of high-rise buildings and the corresponding structural elements. The results of the research make it possible, at the stage of making design decisions, to establish rational parameters for the correspondence between the structural systems of high-rise buildings and their individual elements.

Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

PubMed

Arnold, Matthias

2017-12-02

The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

Towards Structural Analysis of Audio Recordings in the Presence of Musical Variations

NASA Astrophysics Data System (ADS)

Müller, Meinard; Kurth, Frank

2006-12-01

One major goal of structural analysis of an audio recording is to automatically extract the repetitive structure or, more generally, the musical form of the underlying piece of music. Recent approaches to this problem work well for music, where the repetitions largely agree with respect to instrumentation and tempo, as is typically the case for popular music. For other classes of music such as Western classical music, however, musically similar audio segments may exhibit significant variations in parameters such as dynamics, timbre, execution of note groups, modulation, articulation, and tempo progression. In this paper, we propose a robust and efficient algorithm for audio structure analysis, which allows to identify musically similar segments even in the presence of large variations in these parameters. To account for such variations, our main idea is to incorporate invariance at various levels simultaneously: we design a new type of statistical features to absorb microvariations, introduce an enhanced local distance measure to account for local variations, and describe a new strategy for structure extraction that can cope with the global variations. Our experimental results with classical and popular music show that our algorithm performs successfully even in the presence of significant musical variations.

General Platform for Systematic Quantitative Evaluation of Small-Molecule Permeability in Bacteria

PubMed Central

2015-01-01

The chemical features that impact small-molecule permeability across bacterial membranes are poorly understood, and the resulting lack of tools to predict permeability presents a major obstacle to the discovery and development of novel antibiotics. Antibacterials are known to have vastly different structural and physicochemical properties compared to nonantiinfective drugs, as illustrated herein by principal component analysis (PCA). To understand how these properties influence bacterial permeability, we have developed a systematic approach to evaluate the penetration of diverse compounds into bacteria with distinct cellular envelopes. Intracellular compound accumulation is quantitated using LC-MS/MS, then PCA and Pearson pairwise correlations are used to identify structural and physicochemical parameters that correlate with accumulation. An initial study using 10 sulfonyladenosines in Escherichia coli, Bacillus subtilis, and Mycobacterium smegmatis has identified nonobvious correlations between chemical structure and permeability that differ among the various bacteria. Effects of cotreatment with efflux pump inhibitors were also investigated. This sets the stage for use of this platform in larger prospective analyses of diverse chemotypes to identify global relationships between chemical structure and bacterial permeability that would enable the development of predictive tools to accelerate antibiotic drug discovery. PMID:25198656

Indistinguishability and identifiability of kinetic models for the MurC reaction in peptidoglycan biosynthesis.

PubMed

Hattersley, J G; Pérez-Velázquez, J; Chappell, M J; Bearup, D; Roper, D; Dowson, C; Bugg, T; Evans, N D

2011-11-01

An important question in Systems Biology is the design of experiments that enable discrimination between two (or more) competing chemical pathway models or biological mechanisms. In this paper analysis is performed between two different models describing the kinetic mechanism of a three-substrate three-product reaction, namely the MurC reaction in the cytoplasmic phase of peptidoglycan biosynthesis. One model involves ordered substrate binding and ordered release of the three products; the competing model also assumes ordered substrate binding, but with fast release of the three products. The two versions are shown to be distinguishable; however, if standard quasi-steady-state assumptions are made distinguishability cannot be determined. Once model structure uniqueness is ensured the experimenter must determine if it is possible to successfully recover rate constant values given the experiment observations, a process known as structural identifiability. Structural identifiability analysis is carried out for both models to determine which of the unknown reaction parameters can be determined uniquely, or otherwise, from the ideal system outputs. This structural analysis forms an integrated step towards the modelling of the full pathway of the cytoplasmic phase of peptidoglycan biosynthesis. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Identifying large scale structures at 1 AU using fluctuations and wavelets

NASA Astrophysics Data System (ADS)

Niembro, T.; Lara, A.

2016-12-01

The solar wind (SW) is inhomogeneous and it is dominated for two types of flows: one quasi-stationary and one related to large scale transients (such as coronal mass ejections and co-rotating interaction regions). The SW inhomogeneities can be study as fluctuations characterized by a wide range of length and time scales. We are interested in the study of the characteristic fluctuations caused by large scale transient events. To do so, we define the vector space F with the normalized moving monthly/annual deviations as the orthogonal basis. Then, we compute the norm in this space of the solar wind parameters (velocity, magnetic field, density and temperature) fluctuations using WIND data from August 1992 to August 2015. This norm gives important information about the presence of a large structure disturbance in the solar wind and by applying a wavelet transform to this norm, we are able to determine, without subjectivity, the duration of the compression regions of these large transient structures and, even more, to identify if the structure corresponds to a single or complex (or merged) event. With this method we have automatically detected most of the events identified and published by other authors.

Dynamic characterization of high damping viscoelastic materials from vibration test data

NASA Astrophysics Data System (ADS)

Martinez-Agirre, Manex; Elejabarrieta, María Jesús

2011-08-01

The numerical analysis and design of structural systems involving viscoelastic damping materials require knowledge of material properties and proper mathematical models. A new inverse method for the dynamic characterization of high damping and strong frequency-dependent viscoelastic materials from vibration test data measured by forced vibration tests with resonance is presented. Classical material parameter extraction methods are reviewed; their accuracy for characterizing high damping materials is discussed; and the bases of the new analysis method are detailed. The proposed inverse method minimizes the residue between the experimental and theoretical dynamic response at certain discrete frequencies selected by the user in order to identify the parameters of the material constitutive model. Thus, the material properties are identified in the whole bandwidth under study and not just at resonances. Moreover, the use of control frequencies makes the method insensitive to experimental noise and the efficiency is notably enhanced. Therefore, the number of tests required is drastically reduced and the overall process is carried out faster and more accurately. The effectiveness of the proposed method is demonstrated with the characterization of a CLD (constrained layer damping) cantilever beam. First, the elastic properties of the constraining layers are identified from the dynamic response of a metallic cantilever beam. Then, the viscoelastic properties of the core, represented by a four-parameter fractional derivative model, are identified from the dynamic response of a CLD cantilever beam.

Parametric Studies of Square Solar Sails Using Finite Element Analysis

NASA Technical Reports Server (NTRS)

Sleight, David W.; Muheim, Danniella M.

2004-01-01

Parametric studies are performed on two generic square solar sail designs to identify parameters of interest. The studies are performed on systems-level models of full-scale solar sails, and include geometric nonlinearity and inertia relief, and use a Newton-Raphson scheme to apply sail pre-tensioning and solar pressure. Computational strategies and difficulties encountered during the analyses are also addressed. The purpose of this paper is not to compare the benefits of one sail design over the other. Instead, the results of the parametric studies may be used to identify general response trends, and areas of potential nonlinear structural interactions for future studies. The effects of sail size, sail membrane pre-stress, sail membrane thickness, and boom stiffness on the sail membrane and boom deformations, boom loads, and vibration frequencies are studied. Over the range of parameters studied, the maximum sail deflection and boom deformations are a nonlinear function of the sail properties. In general, the vibration frequencies and modes are closely spaced. For some vibration mode shapes, local deformation patterns that dominate the response are identified. These localized patterns are attributed to the presence of negative stresses in the sail membrane that are artifacts of the assumption of ignoring the effects of wrinkling in the modeling process, and are not believed to be physically meaningful. Over the range of parameters studied, several regions of potential nonlinear modal interaction are identified.

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

Constrained maximum likelihood modal parameter identification applied to structural dynamics

NASA Astrophysics Data System (ADS)

El-Kafafy, Mahmoud; Peeters, Bart; Guillaume, Patrick; De Troyer, Tim

2016-05-01

A new modal parameter estimation method to directly establish modal models of structural dynamic systems satisfying two physically motivated constraints will be presented. The constraints imposed in the identified modal model are the reciprocity of the frequency response functions (FRFs) and the estimation of normal (real) modes. The motivation behind the first constraint (i.e. reciprocity) comes from the fact that modal analysis theory shows that the FRF matrix and therefore the residue matrices are symmetric for non-gyroscopic, non-circulatory, and passive mechanical systems. In other words, such types of systems are expected to obey Maxwell-Betti's reciprocity principle. The second constraint (i.e. real mode shapes) is motivated by the fact that analytical models of structures are assumed to either be undamped or proportional damped. Therefore, normal (real) modes are needed for comparison with these analytical models. The work done in this paper is a further development of a recently introduced modal parameter identification method called ML-MM that enables us to establish modal model that satisfies such motivated constraints. The proposed constrained ML-MM method is applied to two real experimental datasets measured on fully trimmed cars. This type of data is still considered as a significant challenge in modal analysis. The results clearly demonstrate the applicability of the method to real structures with significant non-proportional damping and high modal densities.

The methods of optical physics as a mean of the objects’ molecular structure identification (on the base of the research of dophamine and adrenaline molecules)

NASA Astrophysics Data System (ADS)

Elkin, M. D.; Alykova, O. M.; Smirnov, V. V.; Stefanova, G. P.

2017-01-01

Structural and dynamic models of dopamine and adrenaline are proposed on the basis of ab initio quantum calculations of the geometric and electronic structure. The parameters of the adiabatic potential are determined, a vibrational states interpretation of the test compound is proposed in this work. The analysis of the molecules conformational structure of the substance is made. A method for calculating the shifts of vibrational excitation frequencies in 1,2,4-threesubstituted of benzole is presented. It is based on second order perturbation theory. A choice of method and basis for calculation of a fundamental vibrations frequencies and intensities of the bands in the IR and Raman spectra is justified. The technique for evaluation of anharmonicity with cubic and quartic force constants is described. The paper presents the results of numerical experiments, geometric parameters of molecules, such as the valence bond lengths and angles between them. We obtain the frequency of the vibrational states and values of their integrated intensities. The interpretation of vibration of conformers is given. The results are in good agreement with experimental values. Proposed frequency can be used to identify the compounds of the vibrational spectra of molecules. The calculation was performed quantum density functional method DFT/B3LYP. It is shown that this method can be used to modeling the geometrical parameters molecular and electronic structure of various substituted of benzole. It allows us to construct the structural-dynamic models of this class of compounds by numerical calculations.

Genotyping by sequencing resolves shallow population structure to inform conservation of Chinook salmon (Oncorhynchus tshawytscha)

PubMed Central

Larson, Wesley A; Seeb, Lisa W; Everett, Meredith V; Waples, Ryan K; Templin, William D; Seeb, James E

2014-01-01

Recent advances in population genomics have made it possible to detect previously unidentified structure, obtain more accurate estimates of demographic parameters, and explore adaptive divergence, potentially revolutionizing the way genetic data are used to manage wild populations. Here, we identified 10 944 single-nucleotide polymorphisms using restriction-site-associated DNA (RAD) sequencing to explore population structure, demography, and adaptive divergence in five populations of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. Patterns of population structure were similar to those of past studies, but our ability to assign individuals back to their region of origin was greatly improved (>90% accuracy for all populations). We also calculated effective size with and without removing physically linked loci identified from a linkage map, a novel method for nonmodel organisms. Estimates of effective size were generally above 1000 and were biased downward when physically linked loci were not removed. Outlier tests based on genetic differentiation identified 733 loci and three genomic regions under putative selection. These markers and genomic regions are excellent candidates for future research and can be used to create high-resolution panels for genetic monitoring and population assignment. This work demonstrates the utility of genomic data to inform conservation in highly exploited species with shallow population structure. PMID:24665338

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

NASA Astrophysics Data System (ADS)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Tectonic Signals Deduced from Quantitative Analysis of Geomorphic Parameters in Bedrock Rivers and Structural Mapping: A case study from the Surai Khola Siwalik Section, Nepalese Himalaya

NASA Astrophysics Data System (ADS)

Bhattarai, I.; Gani, N. D.

2016-12-01

The Nepalese Himalaya is one of the most active regions within the Himalayan Mountain Belt, which is characterized by a thick succession of Siwalik sedimentary rocks deposited at its foreland basin. To date, much of the tectonic geomorphologic study in the Nepalese Siwalik is poorly understood, particularly in the Surai Khola section. Thus, the study of quantitative analysis of bedrock river parameters will provide crucial information regarding tectonic activities in the area. This study investigates geomorphic parameters of longitudinal river profiles from 54 watersheds within the Siwalik section of the Nepalese Himalaya. We extracted a total of 140 bedrock rivers from these watersheds using stream power-law function and 30-meter resolution ASTER DEM. In addition, we used 90-meter resolution SRTM DEM for structural mapping within the Surai Khola section. Our new results show presence of major and minor knickpoints that were classified on the basis of relief of the longitudinal profiles. We identified 180 major knickpoints out of 305 total knickpoints. Normalized steepness index (ksn) and concavity index values vary above and below these knicpoints. The ksn values range from 5.3 to 140.6 while concavity index of the streams in the study area ranges from as low as -12.1 to as high as 31.1. We also identified a total of 133 structural lineations that were mapped for the first time using various sun illumination angles and azimuths, and slope. Most of these structural lineations are likely faults that follow the similar east-west trends of the Main Frontal Thrust (MFT) Fault. The length of these faults ranges from 0.5 km to 8 km. We interpreted that a few measured knickpoints might be associated with our mapped mesoscale faults, while the majority of the knickpoints in the river profiles are locally adjusting to the MFT related uplift.

Probabilistic structural analysis of a truss typical for space station

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.

1990-01-01

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Modal testing with Asher's method using a Fourier analyzer and curve fitting

NASA Technical Reports Server (NTRS)

Gold, R. R.; Hallauer, W. L., Jr.

1979-01-01

An unusual application of the method proposed by Asher (1958) for structural dynamic and modal testing is discussed. Asher's method has the capability, using the admittance matrix and multiple-shaker sinusoidal excitation, of separating structural modes having indefinitely close natural frequencies. The present application uses Asher's method in conjunction with a modern Fourier analyzer system but eliminates the necessity of exciting the test structure simultaneously with several shakers. Evaluation of this approach with numerically simulated data demonstrated its effectiveness; the parameters of two modes having almost identical natural frequencies were accurately identified. Laboratory evaluation of this approach was inconclusive because of poor experimental input data.

Aerodynamic parameters of across-wind self-limiting vibration for square sections after lock-in in smooth flow

NASA Astrophysics Data System (ADS)

Wu, Jong-Cheng; Chang, Feng-Jung

2011-08-01

The paper aims to identify the across-wind aerodynamic parameters of two-dimensional square section structures after the lock-in stage from the response measurements of wind tunnel tests under smooth wind flow conditions. Firstly, a conceivable self-limiting model was selected from the existent literature and the revisit of the analytical solution shows that the aerodynamic parameters (linear and nonlinear aerodynamic dampings Y1 and ɛ, and aerodynamic stiffness Y2) are not only functions of the section shape and reduced wind velocity but also dependent on both the mass ratio ( mr) and structural damping ratio ( ξ) independently, rather than on the Scruton number as a whole. Secondly, the growth-to-resonance (GTR) method was adopted for identifying the aerodynamic parameters of four different square section models (DN1, DN2, DN3 and DN4) by varying the density ranging from 226 to 409 kg/m 3. To improve the accuracy of the results, numerical optimization of the curve-fitting for experimental and analytical response in time domain was performed to finalize the results. The experimental results of the across-wind self-limiting steady-state amplitudes after lock-in stage versus the reduced wind velocity show that, except the tail part of the DN1 case slightly decreases indicating a pure vortex-induced lock-in persists, the DN2, DN3 and DN4 cases have a trend of monotonically increasing with the reduced wind velocity, which shows an asymptotic combination with the galloping behavior. Due to such a combination effect, all three aerodynamic parameters decrease as the reduced wind velocity increases and asymptotically approaches to a constant at the high branch. In the DN1 case, the parameters Y1 and Y2 decrease as the reduced wind velocity increases while the parameter ɛ slightly reverses in the tail part. The 3-dimensional surface plot of the Y1, ɛ and Y2 curves further show that, excluding the DN1 case, the parameters in the DN2, DN3 and DN4 cases almost follow a symmetric concave-up distribution versus the density under the same reduced wind velocity. This indicates that the aerodynamic parameters in the DN3 case are the minima along the density distribution.

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

Seismic Travel Time Tomography in Modeling Low Velocity Anomalies between the Boreholes

NASA Astrophysics Data System (ADS)

Octova, A.; Sule, R.

2018-04-01

Travel time cross-hole seismic tomography is applied to describing the structure of the subsurface. The sources are placed at one borehole and some receivers are placed in the others. First arrival travel time data that received by each receiver is used as the input data in seismic tomography method. This research is devided into three steps. The first step is reconstructing the synthetic model based on field parameters. Field parameters are divided into 24 receivers and 45 receivers. The second step is applying inversion process for the field data that consists of five pairs bore holes. The last step is testing quality of tomogram with resolution test. Data processing using FAST software produces an explicit shape and resemble the initial model reconstruction of synthetic model with 45 receivers. The tomography processing in field data indicates cavities in several place between the bore holes. Cavities are identified on BH2A-BH1, BH4A-BH2A and BH4A-BH5 with elongated and rounded structure. In resolution tests using a checker-board, anomalies still can be identified up to 2 meter x 2 meter size. Travel time cross-hole seismic tomography analysis proves this mothod is very good to describing subsurface structure and boundary layer. Size and anomalies position can be recognized and interpreted easily.

Testing theoretical models of subdwarf B stars using multicolor photometry

NASA Astrophysics Data System (ADS)

Reed, Mike; Baran, Andrzej; Ostensen, Roy; O'Toole, Simon

2012-08-01

Pulsating stars allow a direct investigation of their structure and evolutionary history from the evaluation of pulsation modes. However, the observed pulsation frequencies must first be identified with spherical harmonics (modes). For subdwarfs B (sdB) stars, such identifications using white light photometry currently have significant limitations. We intend to use multicolor photometry to identify pulsation modes and constrain structure models. We propose to observe the pulsating sdB star PG0154+182 (BI Ari) with our multicolor instrument GT Cam. Our observations will be compared with perturbative atmospheric models (BRUCE/KYLIE) to identify the pulsation modes. This is part of our NSF grant to obtain seismic tools to test structure and evolution models; constraining stellar parameters including total mass, envelope mass, internal composition discontinuities and internal rotation. During winter/spring 2012, we were allocated three runs on the 2.1 m to collect multicolor data on other promising pulsating subdwarf B stars as part of this work. Those runs were very successful, prompting our continued proposals. In addition, we will obtain 3-color data using MAIA on the Mercator Telescope (using guaranteed institutional time).

Trading Time with Space - Development of subduction zone parameter database for a maximum magnitude correlation assessment

NASA Astrophysics Data System (ADS)

Schaefer, Andreas; Wenzel, Friedemann

2017-04-01

Subduction zones are generally the sources of the earthquakes with the highest magnitudes. Not only in Japan or Chile, but also in Pakistan, the Solomon Islands or for the Lesser Antilles, subduction zones pose a significant hazard for the people. To understand the behavior of subduction zones, especially to identify their capabilities to produce maximum magnitude earthquakes, various physical models have been developed leading to a large number of various datasets, e.g. from geodesy, geomagnetics, structural geology, etc. There have been various studies to utilize this data for the compilation of a subduction zone parameters database, but mostly concentrating on only the major zones. Here, we compile the largest dataset of subduction zone parameters both in parameter diversity but also in the number of considered subduction zones. In total, more than 70 individual sources have been assessed and the aforementioned parametric data have been combined with seismological data and many more sources have been compiled leading to more than 60 individual parameters. Not all parameters have been resolved for each zone, since the data completeness depends on the data availability and quality for each source. In addition, the 3D down-dip geometry of a majority of the subduction zones has been resolved using historical earthquake hypocenter data and centroid moment tensors where available and additionally compared and verified with results from previous studies. With such a database, a statistical study has been undertaken to identify not only correlations between those parameters to estimate a parametric driven way to identify potentials for maximum possible magnitudes, but also to identify similarities between the sources themselves. This identification of similarities leads to a classification system for subduction zones. Here, it could be expected if two sources share enough common characteristics, other characteristics of interest may be similar as well. This concept technically trades time with space, considering subduction zones where we have likely not observed the maximum possible event yet. However, by identifying sources of the same class, the not-yet observed temporal behavior can be replaced by spatial similarity among different subduction zones. This database aims to enhance the research and understanding of subduction zones and to quantify their potential in producing mega earthquakes considering potential strong motion impact on nearby cities and their tsunami potential.

Mechanical behavior and shape optimization of lining structure for subsea tunnel excavated in weathered slot

NASA Astrophysics Data System (ADS)

Li, Peng-fei; Zhou, Xiao-jun

2015-12-01

Subsea tunnel lining structures should be designed to sustain the loads transmitted from surrounding ground and groundwater during excavation. Extremely high pore-water pressure reduces the effective strength of the country rock that surrounds a tunnel, thereby lowering the arching effect and stratum stability of the structure. In this paper, the mechanical behavior and shape optimization of the lining structure for the Xiang'an tunnel excavated in weathered slots are examined. Eight cross sections with different geometric parameters are adopted to study the mechanical behavior and shape optimization of the lining structure. The hyperstatic reaction method is used through finite element analysis software ANSYS. The mechanical behavior of the lining structure is evidently affected by the geometric parameters of crosssectional shape. The minimum safety factor of the lining structure elements is set to be the objective function. The efficient tunnel shape to maximize the minimum safety factor is identified. The minimum safety factor increases significantly after optimization. The optimized cross section significantly improves the mechanical characteristics of the lining structure and effectively reduces its deformation. Force analyses of optimization process and program are conducted parametrically so that the method can be applied to the optimization design of other similar structures. The results obtained from this study enhance our understanding of the mechanical behavior of the lining structure for subsea tunnels. These results are also beneficial to the optimal design of lining structures in general.

Special Workshop: Kolsky/Split Hopkinson Pressure Bar Testing of Ceramics

DTIC Science & Technology

2006-09-01

merit) control armor performance and how these properties are controlled/ influenced by intrinsic (crystal structure, phase transitions, and single...reproducibility uncertainties (estimates of precision) could be quantified and also identify key parameters that should be controlled in SHPB/Kolsky testing...control performance? Are there figures of merit? How are the mechanical properties influenced by intrinsic and extrinsic material characteristics

Multivariate Analysis of Two-Dimensional 1H, 13C Methyl NMR Spectra of Monoclonal Antibody Therapeutics To Facilitate Assessment of Higher Order Structure.

PubMed

Arbogast, Luke W; Delaglio, Frank; Schiel, John E; Marino, John P

2017-11-07

Two-dimensional (2D) 1 H- 13 C methyl NMR provides a powerful tool to probe the higher order structure (HOS) of monoclonal antibodies (mAbs), since spectra can readily be acquired on intact mAbs at natural isotopic abundance, and small changes in chemical environment and structure give rise to observable changes in corresponding spectra, which can be interpreted at atomic resolution. This makes it possible to apply 2D NMR spectral fingerprinting approaches directly to drug products in order to systematically characterize structure and excipient effects. Systematic collections of NMR spectra are often analyzed in terms of the changes in specifically identified peak positions, as well as changes in peak height and line widths. A complementary approach is to apply principal component analysis (PCA) directly to the matrix of spectral data, correlating spectra according to similarities and differences in their overall shapes, rather than according to parameters of individually identified peaks. This is particularly well-suited for spectra of mAbs, where some of the individual peaks might not be well resolved. Here we demonstrate the performance of the PCA method for discriminating structural variation among systematic sets of 2D NMR fingerprint spectra using the NISTmAb and illustrate how spectral variability identified by PCA may be correlated to structure.

Force-induced bone growth and adaptation: A system theoretical approach to understanding bone mechanotransduction

NASA Astrophysics Data System (ADS)

Maldonado, Solvey; Findeisen, Rolf

2010-06-01

The modeling, analysis, and design of treatment therapies for bone disorders based on the paradigm of force-induced bone growth and adaptation is a challenging task. Mathematical models provide, in comparison to clinical, medical and biological approaches an structured alternative framework to understand the concurrent effects of the multiple factors involved in bone remodeling. By now, there are few mathematical models describing the appearing complex interactions. However, the resulting models are complex and difficult to analyze, due to the strong nonlinearities appearing in the equations, the wide range of variability of the states, and the uncertainties in parameters. In this work, we focus on analyzing the effects of changes in model structure and parameters/inputs variations on the overall steady state behavior using systems theoretical methods. Based on an briefly reviewed existing model that describes force-induced bone adaptation, the main objective of this work is to analyze the stationary behavior and to identify plausible treatment targets for remodeling related bone disorders. Identifying plausible targets can help in the development of optimal treatments combining both physical activity and drug-medication. Such treatments help to improve/maintain/restore bone strength, which deteriorates under bone disorder conditions, such as estrogen deficiency.

A parameter optimization tool for evaluating the physical consistency of the plot-scale water budget of the integrated eco-hydrological model GEOtop in complex terrain

NASA Astrophysics Data System (ADS)

Bertoldi, Giacomo; Cordano, Emanuele; Brenner, Johannes; Senoner, Samuel; Della Chiesa, Stefano; Niedrist, Georg

2017-04-01

In mountain regions, the plot- and catchment-scale water and energy budgets are controlled by a complex interplay of different abiotic (i.e. topography, geology, climate) and biotic (i.e. vegetation, land management) controlling factors. When integrated, physically-based eco-hydrological models are used in mountain areas, there are a large number of parameters, topographic and boundary conditions that need to be chosen. However, data on soil and land-cover properties are relatively scarce and do not reflect the strong variability at the local scale. For this reason, tools for uncertainty quantification and optimal parameters identification are essential not only to improve model performances, but also to identify most relevant parameters to be measured in the field and to evaluate the impact of different assumptions for topographic and boundary conditions (surface, lateral and subsurface water and energy fluxes), which are usually unknown. In this contribution, we present the results of a sensitivity analysis exercise for a set of 20 experimental stations located in the Italian Alps, representative of different conditions in terms of topography (elevation, slope, aspect), land use (pastures, meadows, and apple orchards), soil type and groundwater influence. Besides micrometeorological parameters, each station provides soil water content at different depths, and in three stations (one for each land cover) eddy covariance fluxes. The aims of this work are: (I) To present an approach for improving calibration of plot-scale soil moisture and evapotranspiration (ET). (II) To identify the most sensitive parameters and relevant factors controlling temporal and spatial differences among sites. (III) Identify possible model structural deficiencies or uncertainties in boundary conditions. Simulations have been performed with the GEOtop 2.0 model, which is a physically-based, fully distributed integrated eco-hydrological model that has been specifically designed for mountain regions, since it considers the effect of topography on radiation and water fluxes and integrates a snow module. A new automatic sensitivity and optimization tool based on the Particle Swarm Optimization theory has been developed, available as R package on https://github.com/EURAC-Ecohydro/geotopOptim2. The model, once calibrated for soil and vegetation parameters, predicts the plot-scale temporal SMC dynamics of SMC and ET with a RMSE of about 0.05 m3/m3 and 40 W/m2, respectively. However, the model tends to underestimate ET during summer months over apple orchards. Results show how most sensitive parameters are both soil and canopy structural properties. However, ranking is affected by the choice of the target function and local topographic conditions. In particular, local slope/aspect influences results in stations located over hillslopes, but with marked seasonal differences. Results for locations in the valley floor are strongly controlled by the choice of the bottom water flux boundary condition. The poorer model performances in simulating ET over apple orchards could be explained by a model structural deficiency in representing the stomatal control on vapor pressure deficit for this particular type of vegetation. The results of this sensitivity could be extended to other physically distributed models, and also provide valuable insights for optimizing new experimental designs.

Parameters affecting mechanical and thermal responses in bone drilling: A review.

PubMed

Lee, JuEun; Chavez, Craig L; Park, Joorok

2018-04-11

Surgical bone drilling is performed variously to correct bone fractures, install prosthetics, or for therapeutic treatment. The primary concern in bone drilling is to extract donor bone sections and create receiving holes without damaging the bone tissue either mechanically or thermally. We review current results from experimental and theoretical studies to investigate the parameters related to such effects. This leads to a comprehensive understanding of the mechanical and thermal aspects of bone drilling to reduce their unwanted complications. This review examines the important bone-drilling parameters of bone structure, drill-bit geometry, operating conditions, and material evacuation, and considers the current techniques used in bone drilling. We then analyze the associated mechanical and thermal effects and their contributions to bone-drilling performance. In this review, we identify a favorable range for each parameter to reduce unwanted complications due to mechanical or thermal effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Theoretic aspects of the identification of the parameters in the optimal control model

NASA Technical Reports Server (NTRS)

Vanwijk, R. A.; Kok, J. J.

1977-01-01

The identification of the parameters of the optimal control model from input-output data of the human operator is considered. Accepting the basic structure of the model as a cascade of a full-order observer and a feedback law, and suppressing the inherent optimality of the human controller, the parameters to be identified are the feedback matrix, the observer gain matrix, and the intensity matrices of the observation noise and the motor noise. The identification of the parameters is a statistical problem, because the system and output are corrupted by noise, and therefore the solution must be based on the statistics (probability density function) of the input and output data of the human operator. However, based on the statistics of the input-output data of the human operator, no distinction can be made between the observation and the motor noise, which shows that the model suffers from overparameterization.

Synthesis, structural, thermal and Hirshfeld surface analysis of novel [1,2,4]triazolo[3,4-b][1,3,4] thiadiazine carrying 1,4-benzothiazine-3-one moiety

NASA Astrophysics Data System (ADS)

Shruthi, C.; Ravindrachary, V.; Guruswamy, B.; Lokanath, N. K.; Kumara, Karthik; Goveas, Janet

2018-05-01

Needle shaped single crystal of the title compound was grown by slow evaporation solution growth technique using ethanol as solvent. The grown single crystal was characterized using FT-IR, Single crystal XRD and Thermal analysis. The FT-IR spectrum confirms the molecular structure and identifies the different functional groups present in the compound. Single crystal XRD study reveals that the crystallized compound belongs to the monoclinic crystal system with P21/c space group and the corresponding cell parameters were identified. The thermal stability of the material was determined using both TGA and DTA analysis. The intermolecular interaction of each individual atom in the crystal lattice was estimated using Hirshfeld surface and finger print analysis.

Study of aircraft crashworthiness for fire protection

NASA Technical Reports Server (NTRS)

Cominsky, A.

1981-01-01

Impact-survivable postcrash fire accidents were surveyed. The data base developed includes foreign and domestic accidents involving airlines and jet aircraft. The emphasis was placed on domestic accidents, airlines, and jet aircraft due principally to availability of information. Only transport category aircraft in commercial service designed under FAR Part 25 were considered. A matrix was prepared to show the relationships between the accident characteristics and the fire fatalities. Typical postcrash fire scenaries were identified. Safety concepts were developed for three engineering categories: cabin interiors - cabin subsystems; power plant - engines and fuel systems; and structural mechanics - primary and secondary structures. The parameters identified for concept evaluation are cost, effectiveness, and societal concerns. Three concepts were selected for design definition and cost and effectiveness analysis: improved fire-resistant seat materials; anti-misting kerosene; and additional cabin emergency exits.

Identification of Arbitrary Zonation in Groundwater Parameters using the Level Set Method and a Parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lei, H.; Lu, Z.; Vesselinov, V. V.; Ye, M.

2017-12-01

Simultaneous identification of both the zonation structure of aquifer heterogeneity and the hydrogeological parameters associated with these zones is challenging, especially for complex subsurface heterogeneity fields. In this study, a new approach, based on the combination of the level set method and a parallel genetic algorithm is proposed. Starting with an initial guess for the zonation field (including both zonation structure and the hydraulic properties of each zone), the level set method ensures that material interfaces are evolved through the inverse process such that the total residual between the simulated and observed state variables (hydraulic head) always decreases, which means that the inversion result depends on the initial guess field and the minimization process might fail if it encounters a local minimum. To find the global minimum, the genetic algorithm (GA) is utilized to explore the parameters that define initial guess fields, and the minimal total residual corresponding to each initial guess field is considered as the fitness function value in the GA. Due to the expensive evaluation of the fitness function, a parallel GA is adapted in combination with a simulated annealing algorithm. The new approach has been applied to several synthetic cases in both steady-state and transient flow fields, including a case with real flow conditions at the chromium contaminant site at the Los Alamos National Laboratory. The results show that this approach is capable of identifying the arbitrary zonation structures of aquifer heterogeneity and the hydrogeological parameters associated with these zones effectively.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

How far are rheological parameters from amplitude sweep tests predictable using common physicochemical soil properties?

NASA Astrophysics Data System (ADS)

Stoppe, N.; Horn, R.

2017-01-01

A basic understanding of soil behavior on the mesoscale resp. macroscale (i.e. soil aggregates resp. bulk soil) requires knowledge of the processes at the microscale (i.e. particle scale), therefore rheological investigations of natural soils receive growing attention. In the present research homogenized and sieved (< 2 mm) samples from Marshland soils of the riparian zone of the River Elbe (North Germany) were analyzed with a modular compact rheometer MCR 300 (Anton Paar, Ostfildern, Germany) with a profiled parallel-plate measuring system. Amplitude sweep tests (AST) with controlled shear deformation were conducted to investigate the viscoelastic properties of the studied soils under oszillatory stress. The gradual depletion of microstructural stiffness during AST cannot only be characterized by the well-known rheological parameters G, G″ and tan δ but also by the dimensionless area parameter integral z, which quantifies the elasticity of microstructure. To discover the physicochemical parameters, which influences the microstructural stiffness, statistical tests were used taking the combined effects of these parameters into account. Although the influence of the individual factors varies depending on soil texture, the physicochemical features significantly affecting soil micro structure were identified. Based on the determined statistical relationships between rheological and physicochemical parameters, pedotransfer functions (PTF) have been developed, which allow a mathematical estimation of the rheological target value integral z. Thus, stabilizing factors are: soil organic matter, concentration of Ca2+, content of CaCO3 and pedogenic iron oxides; whereas the concentration of Na+ and water content represent structurally unfavorable factors.

Perception of Sexual Orientation from Facial Structure: A Study with Artificial Face Models.

PubMed

González-Álvarez, Julio

2017-07-01

Research has shown that lay people can perceive sexual orientation better than chance from face stimuli. However, the relation between facial structure and sexual orientation has been scarcely examined. Recently, an extensive morphometric study on a large sample of Canadian people (Skorska, Geniole, Vrysen, McCormick, & Bogaert, 2015) identified three (in men) and four (in women) facial features as unique multivariate predictors of sexual orientation in each sex group. The present study tested the perceptual validity of these facial traits with two experiments based on realistic artificial 3D face models created by manipulating the key parameters and presented to Spanish participants. Experiment 1 included 200 White and Black face models of both sexes. The results showed an overall accuracy (0.74) clearly above chance in a binary hetero/homosexual judgment task and significant differences depending on the race and sex of the face models. Experiment 2 produced five versions of 24 artificial faces of both sexes varying the key parameters in equal steps, and participants had to rate on a 1-7 scale how likely they thought that the depicted person had a homosexual sexual orientation. Rating scores displayed an almost perfect linear regression as a function of the parameter steps. In summary, both experiments demonstrated the perceptual validity of the seven multivariate predictors identified by Skorska et al. and open up new avenues for further research on this issue with artificial face models.

Practical identifiability analysis of a minimal cardiovascular system model.

PubMed

Pironet, Antoine; Docherty, Paul D; Dauby, Pierre C; Chase, J Geoffrey; Desaive, Thomas

2017-01-17

Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. Copyright © 2017. Published by Elsevier B.V.

On the crystal structure of the vaterite polymorph of CaCO3: a calcium-43 solid-state NMR and computational assessment.

PubMed

Burgess, Kevin M N; Bryce, David L

2015-02-01

The vaterite polymorph of CaCO3 has puzzled crystallographers for decades in part due to difficulties in obtaining single crystals. The multiple proposed structures for the vaterite polymorph of CaCO3 are assessed using a combined (43)Ca solid-state nuclear magnetic resonance (SSNMR) spectroscopic and computational approach. A combination of improved experimental and computational methods, along with a calibrated chemical shift scale and (43)Ca nuclear quadrupole moment, allow for improved insights relative to our earlier work (Bryce et al., J. Am. Chem. Soc. 2008, 130, 9282). Here, we synthesize a (43)Ca isotopically-enriched sample of vaterite and perform high-resolution quadrupolar SSNMR experiments including magic-angle spinning (MAS), double-rotation (DOR), and multiple-quantum (MQ) MAS experiments at magnetic field strengths of 9.4 and 21.1T. We identify one crystallographically unique Ca(2+) site in vaterite with a slight distribution in both chemical shifts and quadrupolar parameters. Both the experimental (43)Ca electric field gradient tensor and the isotropic chemical shift for vaterite are compared to those calculated with the gauge-including projector-augmented-wave (GIPAW) DFT method in an attempt to identify the model that best represents the crystal structure of vaterite. Simulations of (43)Ca DOR and MAS NMR spectra based on the NMR parameters computed for a total of 18 structural models for vaterite allow us to distinguish between these models. Among these 18, the P3221 and C2 structures provide simulated spectra and diffractograms in best agreement with all experimental data. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of the dominant hydrological process and appropriate model structure of a karst catchment through stepwise simplification of a complex conceptual model

NASA Astrophysics Data System (ADS)

Chang, Yong; Wu, Jichun; Jiang, Guanghui; Kang, Zhiqiang

2017-05-01

Conceptual models often suffer from the over-parameterization problem due to limited available data for the calibration. This leads to the problem of parameter nonuniqueness and equifinality, which may bring much uncertainty of the simulation result. How to find out the appropriate model structure supported by the available data to simulate the catchment is still a big challenge in the hydrological research. In this paper, we adopt a multi-model framework to identify the dominant hydrological process and appropriate model structure of a karst spring, located in Guilin city, China. For this catchment, the spring discharge is the only available data for the model calibration. This framework starts with a relative complex conceptual model according to the perception of the catchment and then this complex is simplified into several different models by gradually removing the model component. The multi-objective approach is used to compare the performance of these different models and the regional sensitivity analysis (RSA) is used to investigate the parameter identifiability. The results show this karst spring is mainly controlled by two different hydrological processes and one of the processes is threshold-driven which is consistent with the fieldwork investigation. However, the appropriate model structure to simulate the discharge of this spring is much simpler than the actual aquifer structure and hydrological processes understanding from the fieldwork investigation. A simple linear reservoir with two different outlets is enough to simulate this spring discharge. The detail runoff process in the catchment is not needed in the conceptual model to simulate the spring discharge. More complex model should need more other additional data to avoid serious deterioration of model predictions.

Energy Absorption in Chopped Carbon Fiber Compression Molded Composites

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

Starbuck, J.M.

2001-07-20

In passenger vehicles the ability to absorb energy due to impact and be survivable for the occupant is called the ''crashworthiness'' of the structure. To identify and quantify the energy absorbing mechanisms in candidate automotive composite materials, test methodologies were developed for conducting progressive crush tests on composite plate specimens. The test method development and experimental set-up focused on isolating the damage modes associated with the frond formation that occurs in dynamic testing of composite tubes. Quasi-static progressive crush tests were performed on composite plates manufactured from chopped carbon fiber with an epoxy resin system using compression molding techniques. Themore » carbon fiber was Toray T700 and the epoxy resin was YLA RS-35. The effect of various material and test parameters on energy absorption was evaluated by varying the following parameters during testing: fiber volume fraction, fiber length, fiber tow size, specimen width, profile radius, and profile constraint condition. It was demonstrated during testing that the use of a roller constraint directed the crushing process and the load deflection curves were similar to progressive crushing of tubes. Of all the parameters evaluated, the fiber length appeared to be the most critical material parameter, with shorter fibers having a higher specific energy absorption than longer fibers. The combination of material parameters that yielded the highest energy absorbing material was identified.« less

A review of parameters and heuristics for guiding metabolic pathfinding.

PubMed

Kim, Sarah M; Peña, Matthew I; Moll, Mark; Bennett, George N; Kavraki, Lydia E

2017-09-15

Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases. However, the recent rapid development of available metabolic information has enabled the development of automated approaches for identifying novel pathways. Computer-assisted pathfinding has the potential to save biochemists time in the initial discovery steps of metabolic engineering. In this paper, we review the parameters and heuristics used to guide the search in recent pathfinding algorithms. These parameters and heuristics capture information on the metabolic network structure, compound structures, reaction features, and organism-specificity of pathways. No one metabolic pathfinding algorithm or search parameter stands out as the best to use broadly for solving the pathfinding problem, as each method and parameter has its own strengths and shortcomings. As assisted pathfinding approaches continue to become more sophisticated, the development of better methods for visualizing pathway results and integrating these results into existing metabolic engineering practices is also important for encouraging wider use of these pathfinding methods.

Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports

PubMed Central

Yim, Wen-wai; Kwan, Sharon W; Johnson, Guy; Yetisgen, Meliha

2017-01-01

Cancer stage information is important for clinical research. However, they are not always explicitly noted in electronic medical records. In this paper, we present our work on automatic classification of hepatocellular carcinoma (HCC) stages from free-text clinical and radiology notes. To accomplish this, we defined 11 stage parameters used in the three HCC staging systems, American Joint Committee on Cancer (AJCC), Barcelona Clinic Liver Cancer (BCLC), and Cancer of the Liver Italian Program (CLIP). After aggregating stage parameters to the patient-level, the final stage classifications were achieved using an expert-created decision logic. Each stage parameter relevant for staging was extracted using several classification methods, e.g. sentence classification and automatic information structuring, to identify and normalize text as cancer stage parameter values. Stage parameter extraction for the test set performed at 0.81 F1. Cancer stage prediction for AJCC, BCLC, and CLIP stage classifications were 0.55, 0.50, and 0.43 F1.

Modeling of weak blast wave propagation in the lung.

PubMed

D'yachenko, A I; Manyuhina, O V

2006-01-01

Blast injuries of the lung are the most life-threatening after an explosion. The choice of physical parameters responsible for trauma is important to understand its mechanism. We developed a one-dimensional linear model of an elastic wave propagation in foam-like pulmonary parenchyma to identify the possible cause of edema due to the impact load. The model demonstrates different injury localizations for free and rigid boundary conditions. The following parameters were considered: strain, velocity, pressure in the medium and stresses in structural elements, energy dissipation, parameter of viscous criterion. Maximum underpressure is the most suitable wave parameter to be the criterion for edema formation in a rabbit lung. We supposed that observed scattering of experimental data on edema severity is induced by the physiological variety of rabbit lungs. The criterion and the model explain this scattering. The model outlines the demands for experimental data to make an unambiguous choice of physical parameters responsible for lung trauma due to impact load.

Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: the myoglobin case.

PubMed

Papaleo, Elena; Mereghetti, Paolo; Fantucci, Piercarlo; Grandori, Rita; De Gioia, Luca

2009-01-01

Several molecular dynamics (MD) simulations were used to sample conformations in the neighborhood of the native structure of holo-myoglobin (holo-Mb), collecting trajectories spanning 0.22 micros at 300 K. Principal component (PCA) and free-energy landscape (FEL) analyses, integrated by cluster analysis, which was performed considering the position and structures of the individual helices of the globin fold, were carried out. The coherence between the different structural clusters and the basins of the FEL, together with the convergence of parameters derived by PCA indicates that an accurate description of the Mb conformational space around the native state was achieved by multiple MD trajectories spanning at least 0.14 micros. The integration of FEL, PCA, and structural clustering was shown to be a very useful approach to gain an overall view of the conformational landscape accessible to a protein and to identify representative protein substates. This method could be also used to investigate the conformational and dynamical properties of Mb apo-, mutant, or delete versions, in which greater conformational variability is expected and, therefore identification of representative substates from the simulations is relevant to disclose structure-function relationship.

Swift heavy ion irradiation of Pt nanocrystals: II. Structural changes and H desorption

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

Giulian, R.; Araujo, L.L.; Kluth, P.

2014-09-24

The structural properties and H desorption from embedded Pt nanocrystals (NCs) following irradiation with swift heavy ions were investigated as a function of energy and fluence. From x-ray absorption near-edge spectroscopy analysis, Pt-H bonding was identified in NCs annealed in a forming gas (95% N{sub 2} + 5% H{sub 2}) ambient. The H content decreased upon irradiation and the desorption process was NC-size dependent such that larger NCs required a higher fluence to achieve a H-free state. Pt-H bonding and NC dissolution both perturbed the NC structural parameters (coordination number, bond-length and mean-square relative displacement) as determined with extended x-raymore » absorption fine structure measurements.« less

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

PubMed Central

Min, Kyung-Won; Kim, Junhee; Park, Sung-Ah; Park, Chan-Soo

2013-01-01

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper. PMID:24227999

How does pea architecture influence light sharing in virtual wheat–pea mixtures? A simulation study based on pea genotypes with contrasting architectures

PubMed Central

Barillot, Romain; Combes, Didier; Chevalier, Valérie; Fournier, Christian; Escobar-Gutiérrez, Abraham J.

2012-01-01

Background and aims Light interception is a key factor driving the functioning of wheat–pea intercrops. The sharing of light is related to the canopy structure, which results from the architectural parameters of the mixed species. In the present study, we characterized six contrasting pea genotypes and identified architectural parameters whose range of variability leads to various levels of light sharing within virtual wheat–pea mixtures. Methodology Virtual plants were derived from magnetic digitizations performed during the growing cycle in a greenhouse experiment. Plant mock-ups were used as inputs of a radiative transfer model in order to estimate light interception in virtual wheat–pea mixtures. The turbid medium approach, extended to well-mixed canopies, was used as a framework for assessing the effects of leaf area index (LAI) and mean leaf inclination on light sharing. Principal results Three groups of pea genotypes were distinguished: (i) early and leafy cultivars, (ii) late semi-leafless cultivars and (iii) low-development semi-leafless cultivars. Within open canopies, light sharing was well described by the turbid medium approach and was therefore determined by the architectural parameters that composed LAI and foliage inclination. When canopy closure started, the turbid medium approach was unable to properly infer light partitioning because of the vertical structure of the canopy. This was related to the architectural parameters that determine the height of pea genotypes. Light capture was therefore affected by the development of leaflets, number of branches and phytomers, as well as internode length. Conclusions This study provides information on pea architecture and identifies parameters whose variability can be used to drive light sharing within wheat–pea mixtures. These results could be used to build up the architecture of pea ideotypes adapted to multi-specific stands towards light competition. PMID:23240074

Efficient Interruption of Infection Chains by Targeted Removal of Central Holdings in an Animal Trade Network

PubMed Central

Büttner, Kathrin; Krieter, Joachim; Traulsen, Arne; Traulsen, Imke

2013-01-01

Centrality parameters in animal trade networks typically have right-skewed distributions, implying that these networks are highly resistant against the random removal of holdings, but vulnerable to the targeted removal of the most central holdings. In the present study, we analysed the structural changes of an animal trade network topology based on the targeted removal of holdings using specific centrality parameters in comparison to the random removal of holdings. Three different time periods were analysed: the three-year network, the yearly and the monthly networks. The aim of this study was to identify appropriate measures for the targeted removal, which lead to a rapid fragmentation of the network. Furthermore, the optimal combination of the removal of three holdings regardless of their centrality was identified. The results showed that centrality parameters based on ingoing trade contacts, e.g. in-degree, ingoing infection chain and ingoing closeness, were not suitable for a rapid fragmentation in all three time periods. More efficient was the removal based on parameters considering the outgoing trade contacts. In all networks, a maximum percentage of 7.0% (on average 5.2%) of the holdings had to be removed to reduce the size of the largest component by more than 75%. The smallest difference from the optimal combination for all three time periods was obtained by the removal based on out-degree with on average 1.4% removed holdings, followed by outgoing infection chain and outgoing closeness. The targeted removal using the betweenness centrality differed the most from the optimal combination in comparison to the other parameters which consider the outgoing trade contacts. Due to the pyramidal structure and the directed nature of the pork supply chain the most efficient interruption of the infection chain for all three time periods was obtained by using the targeted removal based on out-degree. PMID:24069293

Modeling, Modal Properties, and Mesh Stiffness Variation Instabilities of Planetary Gears

NASA Technical Reports Server (NTRS)

Parker, Robert G.; Lin, Jian; Krantz, Timothy L. (Technical Monitor)

2001-01-01

Planetary gear noise and vibration are primary concerns in their applications in helicopters, automobiles, aircraft engines, heavy machinery and marine vehicles. Dynamic analysis is essential to the noise and vibration reduction. This work analytically investigates some critical issues and advances the understanding of planetary gear dynamics. A lumped-parameter model is built for the dynamic analysis of general planetary gears. The unique properties of the natural frequency spectra and vibration modes are rigorously characterized. These special structures apply for general planetary gears with cyclic symmetry and, in practically important case, systems with diametrically opposed planets. The special vibration properties are useful for subsequent research. Taking advantage of the derived modal properties, the natural frequency and vibration mode sensitivities to design parameters are investigated. The key parameters include mesh stiffnesses, support/bearing stiffnesses, component masses, moments of inertia, and operating speed. The eigen-sensitivities are expressed in simple, closed-form formulae associated with modal strain and kinetic energies. As disorders (e.g., mesh stiffness variation. manufacturing and assembling errors) disturb the cyclic symmetry of planetary gears, their effects on the free vibration properties are quantitatively examined. Well-defined veering rules are derived to identify dramatic changes of natural frequencies and vibration modes under parameter variations. The knowledge of free vibration properties, eigen-sensitivities, and veering rules provide important information to effectively tune the natural frequencies and optimize structural design to minimize noise and vibration. Parametric instabilities excited by mesh stiffness variations are analytically studied for multi-mesh gear systems. The discrepancies of previous studies on parametric instability of two-stage gear chains are clarified using perturbation and numerical methods. The operating conditions causing parametric instabilities are expressed in closed-form suitable for design guidance. Using the well-defined modal properties of planetary gears, the effects of mesh parameters on parametric instability are analytically identified. Simple formulae are obtained to suppress particular instabilities by adjusting contact ratios and mesh phasing.

Parametric uncertainties in global model simulations of black carbon column mass concentration

NASA Astrophysics Data System (ADS)

Pearce, Hana; Lee, Lindsay; Reddington, Carly; Carslaw, Ken; Mann, Graham

2016-04-01

Previous studies have deduced that the annual mean direct radiative forcing from black carbon (BC) aerosol may regionally be up to 5 W m-2 larger than expected due to underestimation of global atmospheric BC absorption in models. We have identified the magnitude and important sources of parametric uncertainty in simulations of BC column mass concentration from a global aerosol microphysics model (GLOMAP-Mode). A variance-based uncertainty analysis of 28 parameters has been performed, based on statistical emulators trained on model output from GLOMAP-Mode. This is the largest number of uncertain model parameters to be considered in a BC uncertainty analysis to date and covers primary aerosol emissions, microphysical processes and structural parameters related to the aerosol size distribution. We will present several recommendations for further research to improve the fidelity of simulated BC. In brief, we find that the standard deviation around the simulated mean annual BC column mass concentration varies globally between 2.5 x 10-9 g cm-2 in remote marine regions and 1.25 x 10-6 g cm-2 near emission sources due to parameter uncertainty Between 60 and 90% of the variance over source regions is due to uncertainty associated with primary BC emission fluxes, including biomass burning, fossil fuel and biofuel emissions. While the contributions to BC column uncertainty from microphysical processes, for example those related to dry and wet deposition, are increased over remote regions, we find that emissions still make an important contribution in these areas. It is likely, however, that the importance of structural model error, i.e. differences between models, is greater than parametric uncertainty. We have extended our analysis to emulate vertical BC profiles at several locations in the mid-Pacific Ocean and identify the parameters contributing to uncertainty in the vertical distribution of black carbon at these locations. We will present preliminary comparisons of emulated BC vertical profiles from the AeroCom multi-model ensemble and Hiaper Pole-to-Pole (HIPPO) observations.

Hero's journey in bifurcation diagram

NASA Astrophysics Data System (ADS)

Monteiro, L. H. A.; Mustaro, P. N.

2012-06-01

The hero's journey is a narrative structure identified by several authors in comparative studies on folklore and mythology. This storytelling template presents the stages of inner metamorphosis undergone by the protagonist after being called to an adventure. In a simplified version, this journey is divided into three acts separated by two crucial moments. Here we propose a discrete-time dynamical system for representing the protagonist's evolution. The suffering along the journey is taken as the control parameter of this system. The bifurcation diagram exhibits stationary, periodic and chaotic behaviors. In this diagram, there are transition from fixed point to chaos and transition from limit cycle to fixed point. We found that the values of the control parameter corresponding to these two transitions are in quantitative agreement with the two critical moments of the three-act hero's journey identified in 10 movies appearing in the list of the 200 worldwide highest-grossing films.

Multi-excitonic emission from Stranski-Krastanov GaN/AlN quantum dots inside a nanoscale tip

NASA Astrophysics Data System (ADS)

Mancini, L.; Moyon, F.; Houard, J.; Blum, I.; Lefebvre, W.; Vurpillot, F.; Das, A.; Monroy, E.; Rigutti, L.

2017-12-01

Single-dot time-resolved micro-photoluminescence spectroscopy and correlated electron tomography (ET) have been performed on self-assembled GaN/AlN quantum dots isolated within a field-emission nanoscale tip by focused ion beam (FIB). Despite the effect of the FIB, the system conserves the capability of emitting light through multi-excitonic complexes. The optical spectroscopy data have then been correlated with the electronic structure and lifetime parameters that could be extracted using the structural parameters obtained by ET via a 6 band k.p model. A biexciton-exciton cascade could be identified and thoroughly analysed. The biexciton-exciton states exhibit a non-negligible polarization component along the [0001] polar crystal axis, indicating a significant valence band mixing, while the relationship between exciton energy and biexciton binding energy is consistent with a hybrid character of the biexciton.

Field-induced spin-density wave beyond hidden order in URu2Si2

NASA Astrophysics Data System (ADS)

Knafo, W.; Duc, F.; Bourdarot, F.; Kuwahara, K.; Nojiri, H.; Aoki, D.; Billette, J.; Frings, P.; Tonon, X.; Lelièvre-Berna, E.; Flouquet, J.; Regnault, L.-P.

2016-10-01

URu2Si2 is one of the most enigmatic strongly correlated electron systems and offers a fertile testing ground for new concepts in condensed matter science. In spite of >30 years of intense research, no consensus on the order parameter of its low-temperature hidden-order phase exists. A strong magnetic field transforms the hidden order into magnetically ordered phases, whose order parameter has also been defying experimental observation. Here, thanks to neutron diffraction under pulsed magnetic fields up to 40 T, we identify the field-induced phases of URu2Si2 as a spin-density-wave state. The transition to the spin-density wave represents a unique touchstone for understanding the hidden-order phase. An intimate relationship between this magnetic structure, the magnetic fluctuations and the Fermi surface is emphasized, calling for dedicated band-structure calculations.

Solid state parameters, structure elucidation, High Resolution X-Ray Diffraction (HRXRD), phase matching, thermal and impedance analysis on L-Proline trichloroacetate (L-PTCA) NLO single crystals.

PubMed

Kalaiselvi, P; Raj, S Alfred Cecil; Jagannathan, K; Vijayan, N; Bhagavannarayana, G; Kalainathan, S

2014-11-11

Nonlinear optical single crystal of L-Proline trichloroacetate (L-PTCA) was successfully grown by Slow Evaporation Solution Technique (SEST). The grown crystals were subjected to single crystal X-ray diffraction analysis to confirm the structure. From the single crystal XRD data, solid state parameters were determined for the grown crystal. The crystalline perfection has been evaluated using high resolution X-ray diffractometer. The frequencies of various functional groups were identified from FTIR spectral analysis. The percentage of transmittance was obtained from UV Visible spectral analysis. TGA-DSC measurements indicate the thermal stability of the crystal. The dielectric constant, dielectric loss and ac conductivity were measured by the impedance analyzer. The DC conductivity was calculated by the cole-cole plot method. Copyright © 2014 Elsevier B.V. All rights reserved.

Linear parameter varying identification of ankle joint intrinsic stiffness during imposed walking movements.

PubMed

Sobhani Tehrani, Ehsan; Jalaleddini, Kian; Kearney, Robert E

2013-01-01

This paper describes a novel model structure and identification method for the time-varying, intrinsic stiffness of human ankle joint during imposed walking (IW) movements. The model structure is based on the superposition of a large signal, linear, time-invariant (LTI) model and a small signal linear-parameter varying (LPV) model. The methodology is based on a two-step algorithm; the LTI model is first estimated using data from an unperturbed IW trial. Then, the LPV model is identified using data from a perturbed IW trial with the output predictions of the LTI model removed from the measured torque. Experimental results demonstrate that the method accurately tracks the continuous-time variation of normal ankle intrinsic stiffness when the joint position changes during the IW movement. Intrinsic stiffness gain decreases from full plantarflexion to near the mid-point of plantarflexion and then increases substantially as the ankle is dosriflexed.

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

Penalty-Based Finite Element Interface Technology for Analysis of Homogeneous and Composite Structures

NASA Technical Reports Server (NTRS)

Averill, Ronald C.

2002-01-01

An effective and robust interface element technology able to connect independently modeled finite element subdomains has been developed. This method is based on the use of penalty constraints and allows coupling of finite element models whose nodes do not coincide along their common interface. Additionally, the present formulation leads to a computational approach that is very efficient and completely compatible with existing commercial software. A significant effort has been directed toward identifying those model characteristics (element geometric properties, material properties, and loads) that most strongly affect the required penalty parameter, and subsequently to developing simple 'formulae' for automatically calculating the proper penalty parameter for each interface constraint. This task is especially critical in composite materials and structures, where adjacent sub-regions may be composed of significantly different materials or laminates. This approach has been validated by investigating a variety of two-dimensional problems, including composite laminates.

Two-dimensional and three-dimensional evaluation of the deformation relief

NASA Astrophysics Data System (ADS)

Alfyorova, E. A.; Lychagin, D. V.

2017-12-01

This work presents the experimental results concerning the research of the morphology of the face-centered cubic single crystal surface after compression deformation. Our aim is to identify the method of forming a quasiperiodic profile of single crystals with different crystal geometrical orientation and quantitative description of deformation structures. A set of modern methods such as optical and confocal microscopy is applied to determine the morphology of surface parameters. The results show that octahedral slip is an integral part of the formation of the quasiperiodic profile surface starting with initial strain. The similarity of the formation process of the surface profile at different scale levels is given. The size of consistent deformation regions is found. This is 45 µm for slip lines ([001]-single crystal) and 30 µm for mesobands ([110]-single crystal). The possibility of using two- and three-dimensional roughness parameters to describe the deformation structures was shown.

Combined electrochemical, heat generation, and thermal model for large prismatic lithium-ion batteries in real-time applications

NASA Astrophysics Data System (ADS)

Farag, Mohammed; Sweity, Haitham; Fleckenstein, Matthias; Habibi, Saeid

2017-08-01

Real-time prediction of the battery's core temperature and terminal voltage is very crucial for an accurate battery management system. In this paper, a combined electrochemical, heat generation, and thermal model is developed for large prismatic cells. The proposed model consists of three sub-models, an electrochemical model, heat generation model, and thermal model which are coupled together in an iterative fashion through physicochemical temperature dependent parameters. The proposed parameterization cycles identify the sub-models' parameters separately by exciting the battery under isothermal and non-isothermal operating conditions. The proposed combined model structure shows accurate terminal voltage and core temperature prediction at various operating conditions while maintaining a simple mathematical structure, making it ideal for real-time BMS applications. Finally, the model is validated against both isothermal and non-isothermal drive cycles, covering a broad range of C-rates, and temperature ranges [-25 °C to 45 °C].

Development of advanced techniques for rotorcraft state estimation and parameter identification

NASA Technical Reports Server (NTRS)

Hall, W. E., Jr.; Bohn, J. G.; Vincent, J. H.

1980-01-01

An integrated methodology for rotorcraft system identification consists of rotorcraft mathematical modeling, three distinct data processing steps, and a technique for designing inputs to improve the identifiability of the data. These elements are as follows: (1) a Kalman filter smoother algorithm which estimates states and sensor errors from error corrupted data. Gust time histories and statistics may also be estimated; (2) a model structure estimation algorithm for isolating a model which adequately explains the data; (3) a maximum likelihood algorithm for estimating the parameters and estimates for the variance of these estimates; and (4) an input design algorithm, based on a maximum likelihood approach, which provides inputs to improve the accuracy of parameter estimates. Each step is discussed with examples to both flight and simulated data cases.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Elastic, inelastic, and 1-nucleon transfer channels in the 7Li+120Sn system

NASA Astrophysics Data System (ADS)

Kundu, A.; Santra, S.; Pal, A.; Chattopadhyay, D.; Tripathi, R.; Roy, B. J.; Nag, T. N.; Nayak, B. K.; Saxena, A.; Kailas, S.

2017-03-01

Background: Simultaneous description of major outgoing channels for a nuclear reaction by coupled-channels calculations using the same set of potential and coupling parameters is one of the difficult tasks to accomplish in nuclear reaction studies. Purpose: To measure the elastic, inelastic, and transfer cross sections for as many channels as possible in 7Li+120Sn system at different beam energies and simultaneously describe them by a single set of model calculations using fresco. Methods: Projectile-like fragments were detected using six sets of Si-detector telescopes to measure the cross sections for elastic, inelastic, and 1-nucleon transfer channels at two beam energies of 28 and 30 MeV. Optical model analysis of elastic data and coupled-reaction-channels (CRC) calculations that include around 30 reaction channels coupled directly to the entrance channel, with respective structural parameters, were performed to understand the measured cross sections. Results: Structure information available in the literature for some of the identified states did not reproduce the present data. Cross sections obtained from CRC calculations using a modified but single set of potential and coupling parameters were able to describe simultaneously the measured data for all the channels at both the measured energies as well as the existing data for elastic and inelastic cross sections at 44 MeV. Conclusions: Non-reproduction of some of the cross sections using the structure information available in the literature which are extracted from reactions involving different projectiles indicates that such measurements are probe dependent. New structural parameters were assigned for such states as well as for several new transfer states whose spectroscopic factors were not known.

A review of model applications for structured soils: b) Pesticide transport.

PubMed

Köhne, John Maximilian; Köhne, Sigrid; Simůnek, Jirka

2009-02-16

The past decade has seen considerable progress in the development of models simulating pesticide transport in structured soils subject to preferential flow (PF). Most PF pesticide transport models are based on the two-region concept and usually assume one (vertical) dimensional flow and transport. Stochastic parameter sets are sometimes used to account for the effects of spatial variability at the field scale. In the past decade, PF pesticide models were also coupled with Geographical Information Systems (GIS) and groundwater flow models for application at the catchment and larger regional scales. A review of PF pesticide model applications reveals that the principal difficulty of their application is still the appropriate parameterization of PF and pesticide processes. Experimental solution strategies involve improving measurement techniques and experimental designs. Model strategies aim at enhancing process descriptions, studying parameter sensitivity, uncertainty, inverse parameter identification, model calibration, and effects of spatial variability, as well as generating model emulators and databases. Model comparison studies demonstrated that, after calibration, PF pesticide models clearly outperform chromatographic models for structured soils. Considering nonlinear and kinetic sorption reactions further enhanced the pesticide transport description. However, inverse techniques combined with typically available experimental data are often limited in their ability to simultaneously identify parameters for describing PF, sorption, degradation and other processes. On the other hand, the predictive capacity of uncalibrated PF pesticide models currently allows at best an approximate (order-of-magnitude) estimation of concentrations. Moreover, models should target the entire soil-plant-atmosphere system, including often neglected above-ground processes such as pesticide volatilization, interception, sorption to plant residues, root uptake, and losses by runoff. The conclusions compile progress, problems, and future research choices for modelling pesticide displacement in structured soils.

Experimental study of oscillating plates in viscous fluids: Qualitative and quantitative analysis of the flow physics and hydrodynamic forces

NASA Astrophysics Data System (ADS)

Shrestha, Bishwash; Ahsan, Syed N.; Aureli, Matteo

2018-01-01

In this paper, we present a comprehensive experimental study on harmonic oscillations of a submerged rigid plate in a quiescent, incompressible, Newtonian, viscous fluid. The fluid-structure interaction problem is analyzed from both qualitative and quantitative perspectives via a detailed particle image velocimetry (PIV) experimental campaign conducted over a broad range of oscillation frequency and amplitude parameters. Our primary goal is to identify the effect of the oscillation characteristics on the mechanisms of fluid-structure interaction and on the dynamics of vortex shedding and convection and to elucidate the behavior of hydrodynamic forces on the oscillating structure. Towards this goal, we study the flow in terms of qualitative aspects of its pathlines, vortex shedding, and symmetry breaking phenomena and identify distinct hydrodynamic regimes in the vicinity of the oscillating structure. Based on these experimental observations, we produce a novel phase diagram detailing the occurrence of distinct hydrodynamic regimes as a function of relevant governing nondimensional parameters. We further study the hydrodynamic forces associated with each regime using both PIV and direct force measurement via a load cell. Our quantitative results on experimental estimation of hydrodynamic forces show good agreement against predictions from the literature, where numerical and semi-analytical models are available. The findings and observations in this work shed light on the relationship between flow physics, vortex shedding, and convection mechanisms and the hydrodynamic forces acting on a rigid oscillating plate and, as such, have relevance to various engineering applications, including energy harvesting devices, biomimetic robotic system, and micro-mechanical sensors and actuators.

Framework for Uncertainty Assessment - Hanford Site-Wide Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Bergeron, M. P.; Cole, C. R.; Murray, C. J.; Thorne, P. D.; Wurstner, S. K.

2002-05-01

Pacific Northwest National Laboratory is in the process of development and implementation of an uncertainty estimation methodology for use in future site assessments that addresses parameter uncertainty as well as uncertainties related to the groundwater conceptual model. The long-term goals of the effort are development and implementation of an uncertainty estimation methodology for use in future assessments and analyses being made with the Hanford site-wide groundwater model. The basic approach in the framework developed for uncertainty assessment consists of: 1) Alternate conceptual model (ACM) identification to identify and document the major features and assumptions of each conceptual model. The process must also include a periodic review of the existing and proposed new conceptual models as data or understanding become available. 2) ACM development of each identified conceptual model through inverse modeling with historical site data. 3) ACM evaluation to identify which of conceptual models are plausible and should be included in any subsequent uncertainty assessments. 4) ACM uncertainty assessments will only be carried out for those ACMs determined to be plausible through comparison with historical observations and model structure identification measures. The parameter uncertainty assessment process generally involves: a) Model Complexity Optimization - to identify the important or relevant parameters for the uncertainty analysis; b) Characterization of Parameter Uncertainty - to develop the pdfs for the important uncertain parameters including identification of any correlations among parameters; c) Propagation of Uncertainty - to propagate parameter uncertainties (e.g., by first order second moment methods if applicable or by a Monte Carlo approach) through the model to determine the uncertainty in the model predictions of interest. 5)Estimation of combined ACM and scenario uncertainty by a double sum with each component of the inner sum (an individual CCDF) representing parameter uncertainty associated with a particular scenario and ACM and the outer sum enumerating the various plausible ACM and scenario combinations in order to represent the combined estimate of uncertainty (a family of CCDFs). A final important part of the framework includes identification, enumeration, and documentation of all the assumptions, which include those made during conceptual model development, required by the mathematical model, required by the numerical model, made during the spatial and temporal descretization process, needed to assign the statistical model and associated parameters that describe the uncertainty in the relevant input parameters, and finally those assumptions required by the propagation method. Pacific Northwest National Laboratory is operated for the U.S. Department of Energy under Contract DE-AC06-76RL01830.

Experimental validation of a numerical 3-D finite model applied to wind turbines design under vibration constraints: TREVISE platform

NASA Astrophysics Data System (ADS)

Sellami, Takwa; Jelassi, Sana; Darcherif, Abdel Moumen; Berriri, Hanen; Mimouni, Med Faouzi

2018-04-01

With the advancement of wind turbines towards complex structures, the requirement of trusty structural models has become more apparent. Hence, the vibration characteristics of the wind turbine components, like the blades and the tower, have to be extracted under vibration constraints. Although extracting the modal properties of blades is a simple task, calculating precise modal data for the whole wind turbine coupled to its tower/foundation is still a perplexing task. In this framework, this paper focuses on the investigation of the structural modeling approach of modern commercial micro-turbines. Thus, the structural model a complex designed wind turbine, which is Rutland 504, is established based on both experimental and numerical methods. A three-dimensional (3-D) numerical model of the structure was set up based on the finite volume method (FVM) using the academic finite element analysis software ANSYS. To validate the created model, experimental vibration tests were carried out using the vibration test system of TREVISE platform at ECAM-EPMI. The tests were based on the experimental modal analysis (EMA) technique, which is one of the most efficient techniques for identifying structures parameters. Indeed, the poles and residues of the frequency response functions (FRF), between input and output spectra, were calculated to extract the mode shapes and the natural frequencies of the structure. Based on the obtained modal parameters, the numerical designed model was up-dated.

Evolutionary snowdrift game incorporating costly punishment in structured populations

NASA Astrophysics Data System (ADS)

Chan, Nat W. H.; Xu, C.; Tey, Siew Kian; Yap, Yee Jiun; Hui, P. M.

2013-01-01

The role of punishment and the effects of a structured population in promoting cooperation are important issues. Within a recent model of snowdrift game (SG) incorporating a costly punishing strategy (P), we study the effects of a population connected through a square lattice. The punishers, who carry basically a cooperative (C) character, are willing to pay a cost α so as to punish a non-cooperative (D) opponent by β. Depending on α, β, the cost-to-benefit ratio r in SG, and the initial conditions, the system evolves into different phases that could be homogeneous or inhomogeneous. The spatial structure imposes geometrical constraint on how one agent is affected by neighboring agents. Results of extensive numerical simulations, both for the steady state and the dynamics, are presented. Possible phases are identified and discussed, and isolated phases in the r-β space are identified as special local structures of strategies that are stable due to the lattice structure. In contrast to a well-mixed population where punishers are suppressed due to the cost of punishment, the altruistic punishing strategy can flourish and prevail for appropriate values of the parameters, implying an enhancement in cooperation by imposing punishments in a structured population. The system could evolve to a phase corresponding to the coexistence of C, D, and P strategies at some particular payoff parameters, and such a phase is absent in a well-mixed population. The pair approximation, a commonly used analytic approach, is extended from a two-strategy system to a three-strategy system. We show that the pair approximation can, at best, capture the numerical results only qualitatively. Due to the improper way of including spatial correlation imposed by the lattice structure, the approximation does not give the frequencies of C, D, and P accurately and fails to give the homogeneous AllD and AllP phases.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

NASA Astrophysics Data System (ADS)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.

Structural Interface Parameters Are Discriminatory in Recognising Near-Native Poses of Protein-Protein Interactions

PubMed Central

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets. PMID:24498255

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

PubMed

Malhotra, Sony; Sankar, Kannan; Sowdhamini, Ramanathan

2014-01-01

Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native) structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation.

PubMed

Barton, Hugh A; Chiu, Weihsueh A; Setzer, R Woodrow; Andersen, Melvin E; Bailer, A John; Bois, Frédéric Y; Dewoskin, Robert S; Hays, Sean; Johanson, Gunnar; Jones, Nancy; Loizou, George; Macphail, Robert C; Portier, Christopher J; Spendiff, Martin; Tan, Yu-Mei

2007-10-01

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

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

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less

Building alternate protein structures using the elastic network model.

PubMed

Yang, Qingyi; Sharp, Kim A

2009-02-15

We describe a method for efficiently generating ensembles of alternate, all-atom protein structures that (a) differ significantly from the starting structure, (b) have good stereochemistry (bonded geometry), and (c) have good steric properties (absence of atomic overlap). The method uses reconstruction from a series of backbone framework structures that are obtained from a modified elastic network model (ENM) by perturbation along low-frequency normal modes. To ensure good quality backbone frameworks, the single force parameter ENM is modified by introducing two more force parameters to characterize the interaction between the consecutive carbon alphas and those within the same secondary structure domain. The relative stiffness of the three parameters is parameterized to reproduce B-factors, while maintaining good bonded geometry. After parameterization, violations of experimental Calpha-Calpha distances and Calpha-Calpha-Calpha pseudo angles along the backbone are reduced to less than 1%. Simultaneously, the average B-factor correlation coefficient improves to R = 0.77. Two applications illustrate the potential of the approach. (1) 102,051 protein backbones spanning a conformational space of 15 A root mean square deviation were generated from 148 nonredundant proteins in the PDB database, and all-atom models with minimal bonded and nonbonded violations were produced from this ensemble of backbone structures using the SCWRL side chain building program. (2) Improved backbone templates for homology modeling. Fifteen query sequences were each modeled on two targets. For each of the 30 target frameworks, dozens of improved templates could be produced In all cases, improved full atom homology models resulted, of which 50% could be identified blind using the D-Fire statistical potential. (c) 2008 Wiley-Liss, Inc.

Estimation of transversely isotropic material properties from magnetic resonance elastography using the optimised virtual fields method.

PubMed

Miller, Renee; Kolipaka, Arunark; Nash, Martyn P; Young, Alistair A

2018-03-12

Magnetic resonance elastography (MRE) has been used to estimate isotropic myocardial stiffness. However, anisotropic stiffness estimates may give insight into structural changes that occur in the myocardium as a result of pathologies such as diastolic heart failure. The virtual fields method (VFM) has been proposed for estimating material stiffness from image data. This study applied the optimised VFM to identify transversely isotropic material properties from both simulated harmonic displacements in a left ventricular (LV) model with a fibre field measured from histology as well as isotropic phantom MRE data. Two material model formulations were implemented, estimating either 3 or 5 material properties. The 3-parameter formulation writes the transversely isotropic constitutive relation in a way that dissociates the bulk modulus from other parameters. Accurate identification of transversely isotropic material properties in the LV model was shown to be dependent on the loading condition applied, amount of Gaussian noise in the signal, and frequency of excitation. Parameter sensitivity values showed that shear moduli are less sensitive to noise than the other parameters. This preliminary investigation showed the feasibility and limitations of using the VFM to identify transversely isotropic material properties from MRE images of a phantom as well as simulated harmonic displacements in an LV geometry. Copyright © 2018 John Wiley & Sons, Ltd.

A Novel Identification Methodology for the Coordinate Relationship between a 3D Vision System and a Legged Robot.

PubMed

Chai, Xun; Gao, Feng; Pan, Yang; Qi, Chenkun; Xu, Yilin

2015-04-22

Coordinate identification between vision systems and robots is quite a challenging issue in the field of intelligent robotic applications, involving steps such as perceiving the immediate environment, building the terrain map and planning the locomotion automatically. It is now well established that current identification methods have non-negligible limitations such as a difficult feature matching, the requirement of external tools and the intervention of multiple people. In this paper, we propose a novel methodology to identify the geometric parameters of 3D vision systems mounted on robots without involving other people or additional equipment. In particular, our method focuses on legged robots which have complex body structures and excellent locomotion ability compared to their wheeled/tracked counterparts. The parameters can be identified only by moving robots on a relatively flat ground. Concretely, an estimation approach is provided to calculate the ground plane. In addition, the relationship between the robot and the ground is modeled. The parameters are obtained by formulating the identification problem as an optimization problem. The methodology is integrated on a legged robot called "Octopus", which can traverse through rough terrains with high stability after obtaining the identification parameters of its mounted vision system using the proposed method. Diverse experiments in different environments demonstrate our novel method is accurate and robust.

Probabilistic assessment of the dynamic interaction between multiple pedestrians and vertical vibrations of footbridges

NASA Astrophysics Data System (ADS)

Tubino, Federica

2018-03-01

The effect of human-structure interaction in the vertical direction for footbridges is studied based on a probabilistic approach. The bridge is modeled as a continuous dynamic system, while pedestrians are schematized as moving single-degree-of-freedom systems with random dynamic properties. The non-dimensional form of the equations of motion allows us to obtain results that can be applied in a very wide set of cases. An extensive Monte Carlo simulation campaign is performed, varying the main non-dimensional parameters identified, and the mean values and coefficients of variation of the damping ratio and of the non-dimensional natural frequency of the coupled system are reported. The results obtained can be interpreted from two different points of view. If the characterization of pedestrians' equivalent dynamic parameters is assumed as uncertain, as revealed from a current literature review, then the paper provides a range of possible variations of the coupled system damping ratio and natural frequency as a function of pedestrians' parameters. Assuming that a reliable characterization of pedestrians' dynamic parameters is available (which is not the case at present, but could be in the future), the results presented can be adopted to estimate the damping ratio and natural frequency of the coupled footbridge-pedestrian system for a very wide range of real structures.

Remote synchronization of amplitudes across an experimental ring of non-linear oscillators

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

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it

In this paper, the emergence of remote synchronization in a ring of 32 unidirectionally coupled non-linear oscillators is reported. Each oscillator consists of 3 negative voltage gain stages connected in a loop to which two integrators are superimposed and receives input from its preceding neighbour via a “mixing” stage whose gains form the main system control parameters. Collective behaviour of the network is investigated numerically and experimentally, based on a custom-designed circuit board featuring 32 field-programmable analog arrays. A diverse set of synchronization patterns is observed depending on the control parameters. While phase synchronization ensues globally, albeit imperfectly, for certainmore » control parameter values, amplitudes delineate subsets of non-adjacent but preferentially synchronized nodes; this cannot be trivially explained by synchronization paths along sequences of structurally connected nodes and is therefore interpreted as representing a form of remote synchronization. Complex topology of functional synchronization thus emerges from underlying elementary structural connectivity. In addition to the Kuramoto order parameter and cross-correlation coefficient, other synchronization measures are considered, and preliminary findings suggest that generalized synchronization may identify functional relationships across nodes otherwise not visible. Further work elucidating the mechanism underlying this observation of remote synchronization is necessary, to support which experimental data and board design materials have been made freely downloadable.« less

Remote synchronization of amplitudes across an experimental ring of non-linear oscillators.

PubMed

Minati, Ludovico

2015-12-01

In this paper, the emergence of remote synchronization in a ring of 32 unidirectionally coupled non-linear oscillators is reported. Each oscillator consists of 3 negative voltage gain stages connected in a loop to which two integrators are superimposed and receives input from its preceding neighbour via a "mixing" stage whose gains form the main system control parameters. Collective behaviour of the network is investigated numerically and experimentally, based on a custom-designed circuit board featuring 32 field-programmable analog arrays. A diverse set of synchronization patterns is observed depending on the control parameters. While phase synchronization ensues globally, albeit imperfectly, for certain control parameter values, amplitudes delineate subsets of non-adjacent but preferentially synchronized nodes; this cannot be trivially explained by synchronization paths along sequences of structurally connected nodes and is therefore interpreted as representing a form of remote synchronization. Complex topology of functional synchronization thus emerges from underlying elementary structural connectivity. In addition to the Kuramoto order parameter and cross-correlation coefficient, other synchronization measures are considered, and preliminary findings suggest that generalized synchronization may identify functional relationships across nodes otherwise not visible. Further work elucidating the mechanism underlying this observation of remote synchronization is necessary, to support which experimental data and board design materials have been made freely downloadable.

Clinical application of optical coherence tomography in combination with functional diagnostics: advantages and limitations for diagnosis and assessment of therapy outcome in central serous chorioretinopathy.

PubMed

Schliesser, Joshua A; Gallimore, Gary; Kunjukunju, Nancy; Sabates, Nelson R; Koulen, Peter; Sabates, Felix N

2014-01-01

While identifying functional and structural parameters of the retina in central serous chorioretinopathy (CSCR) patients, this study investigated how an optical coherence tomography (OCT)-based diagnosis can be significantly supplemented with functional diagnostic tools and to what degree the determination of disease severity and therapy outcome can benefit from diagnostics complementary to OCT. CSCR patients were evaluated prospectively with microperimetry (MP) and spectral domain optical coherence tomography (SD-OCT) to determine retinal sensitivity function and retinal thickness as outcome measures along with measures of visual acuity (VA). Patients received clinical care that involved focal laser photocoagulation or pharmacotherapy targeting inflammation and neovascularization. Correlation of clinical parameters with a focus on functional parameters, VA, and mean retinal sensitivity, as well as on the structural parameter mean retinal thickness, showed that functional measures were similar in diagnostic power. A moderate correlation was found between OCT data and the standard functional assessment of VA; however, a strong correlation between OCT and MP data showed that diagnostic measures cannot always be used interchangeably, but that complementary use is of higher clinical value. The study indicates that integrating SD-OCT with MP provides a more complete diagnosis with high clinical relevance for complex, difficult to quantify diseases such as CSCR.

The design of low cost structures for extensive ground arrays

NASA Technical Reports Server (NTRS)

Franklin, H. A.; Leonard, R. S.

1980-01-01

The development of conceptual designs of solar array support structures and their foundations including considerations of the use of concrete, steel, aluminum, or timber are reported. Some cost trends were examined by varying selected parameters to determine optimum configurations. Detailed civil/structural design criteria were developed. Using these criteria, eight detailed designs for support structures and foundations were developed and cost estimates were made. As a result of the study wind was identified as the major loading experienced by these low height structures, whose arrays are likely to extend over large tracts of land. Proper wind load estimating is considered essential to developing realistic structural designs and achieving minimum cost support structures. Wind tunnel testing of a conceptual array field was undertaken and some of the resulting wind design criteria are presented. The SPS rectenna system designs may be less sensitive to wind load estimates, but consistent design criteria remain important.

Protein structure similarity from Principle Component Correlation analysis.

PubMed

Zhou, Xiaobo; Chou, James; Wong, Stephen T C

2006-01-25

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC) analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum eigenvalues can be highly effective in clustering structurally or topologically similar proteins. We believe that the PCC analysis of interaction matrix is highly flexible in adopting various structural parameters for protein structure comparison.

Biological mechanisms of normal tissue damage: importance for the design of NTCP models.

PubMed

Trott, Klaus-Rüdiger; Doerr, Wolfgang; Facoetti, Angelica; Hopewell, John; Langendijk, Johannes; van Luijk, Peter; Ottolenghi, Andrea; Smyth, Vere

2012-10-01

The normal tissue complication probability (NTCP) models that are currently being proposed for estimation of risk of harm following radiotherapy are mainly based on simplified empirical models, consisting of dose distribution parameters, possibly combined with clinical or other treatment-related factors. These are fitted to data from retrospective or prospective clinical studies. Although these models sometimes provide useful guidance for clinical practice, their predictive power on individuals seems to be limited. This paper examines the radiobiological mechanisms underlying the most important complications induced by radiotherapy, with the aim of identifying the essential parameters and functional relationships needed for effective predictive NTCP models. The clinical features of the complications are identified and reduced as much as possible into component parts. In a second step, experimental and clinical data are considered in order to identify the gross anatomical structures involved, and which dose distributions lead to these complications. Finally, the pathogenic pathways and cellular and more specific anatomical parameters that have to be considered in this pathway are determined. This analysis is carried out for some of the most critical organs and sites in radiotherapy, i.e. spinal cord, lung, rectum, oropharynx and heart. Signs and symptoms of severe late normal tissue complications present a very variable picture in the different organs at risk. Only in rare instances is the entire organ the critical target which elicits the particular complication. Moreover, the biological mechanisms that are involved in the pathogenesis differ between the different complications, even in the same organ. Different mechanisms are likely to be related to different shapes of dose effect relationships and different relationships between dose per fraction, dose rate, and overall treatment time and effects. There is good reason to conclude that each type of late complication after radiotherapy depends on its own specific mechanism which is triggered by the radiation exposure of particular structures or sub-volumes of (or related to) the respective organ at risk. Hence each complication will need the development of an NTCP model designed to accommodate this structure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Using hyperspectral imaging technology to identify diseased tomato leaves

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

2016-11-01

In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

Intelligent Method for Diagnosing Structural Faults of Rotating Machinery Using Ant Colony Optimization

PubMed Central

Li, Ke; Chen, Peng

2011-01-01

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called “relative ratio symptom parameters” are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

Segmentation and Quantification for Angle-Closure Glaucoma Assessment in Anterior Segment OCT.

PubMed

Fu, Huazhu; Xu, Yanwu; Lin, Stephen; Zhang, Xiaoqin; Wong, Damon Wing Kee; Liu, Jiang; Frangi, Alejandro F; Baskaran, Mani; Aung, Tin

2017-09-01

Angle-closure glaucoma is a major cause of irreversible visual impairment and can be identified by measuring the anterior chamber angle (ACA) of the eye. The ACA can be viewed clearly through anterior segment optical coherence tomography (AS-OCT), but the imaging characteristics and the shapes and locations of major ocular structures can vary significantly among different AS-OCT modalities, thus complicating image analysis. To address this problem, we propose a data-driven approach for automatic AS-OCT structure segmentation, measurement, and screening. Our technique first estimates initial markers in the eye through label transfer from a hand-labeled exemplar data set, whose images are collected over different patients and AS-OCT modalities. These initial markers are then refined by using a graph-based smoothing method that is guided by AS-OCT structural information. These markers facilitate segmentation of major clinical structures, which are used to recover standard clinical parameters. These parameters can be used not only to support clinicians in making anatomical assessments, but also to serve as features for detecting anterior angle closure in automatic glaucoma screening algorithms. Experiments on Visante AS-OCT and Cirrus high-definition-OCT data sets demonstrate the effectiveness of our approach.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC.

PubMed

Molina-Viedma, Ángel Jesús; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-02-02

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers.

Intermediate surface structure between step bunching and step flow in SrRuO3 thin film growth

NASA Astrophysics Data System (ADS)

Bertino, Giulia; Gura, Anna; Dawber, Matthew

We performed a systematic study of SrRuO3 thin films grown on TiO2 terminated SrTiO3 substrates using off-axis magnetron sputtering. We investigated the step bunching formation and the evolution of the SRO film morphology by varying the step size of the substrate, the growth temperature and the film thickness. The thin films were characterized using Atomic Force Microscopy and X-Ray Diffraction. We identified single and multiple step bunching and step flow growth regimes as a function of the growth parameters. Also, we clearly observe a stronger influence of the step size of the substrate on the evolution of the SRO film surface with respect to the other growth parameters. Remarkably, we observe the formation of a smooth, regular and uniform ``fish skin'' structure at the transition between one regime and another. We believe that the fish skin structure results from the merging of 2D flat islands predicted by previous models. The direct observation of this transition structure allows us to better understand how and when step bunching develops in the growth of SrRuO3 thin films.

Modal Parameters Evaluation in a Full-Scale Aircraft Demonstrator under Different Environmental Conditions Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.; Rodríguez-Ahlquist, Javier; Iglesias-Vallejo, Manuel

2018-01-01

In real aircraft structures the comfort and the occupational performance of crewmembers and passengers are affected by the presence of noise. In this sense, special attention is focused on mechanical and material design for isolation and vibration control. Experimental characterization and, in particular, experimental modal analysis, provides information for adequate cabin noise control. Traditional sensors employed in the aircraft industry for this purpose are invasive and provide a low spatial resolution. This paper presents a methodology for experimental modal characterization of a front fuselage full-scale demonstrator using high-speed 3D digital image correlation, which is non-invasive, ensuring that the structural response is unperturbed by the instrumentation mass. Specifically, full-field measurements on the passenger window area were conducted when the structure was excited using an electrodynamic shaker. The spectral analysis of the measured time-domain displacements made it possible to identify natural frequencies and full-field operational deflection shapes. Changes in the modal parameters due to cabin pressurization and the behavior of different local structural modifications were assessed using this methodology. The proposed full-field methodology allowed the characterization of relevant dynamic response patterns, complementing the capabilities provided by accelerometers. PMID:29393897

Theoretical Study of Electronic Structure and Thermoelectric Properties of Doped CuAlO2

NASA Astrophysics Data System (ADS)

Poopanya, P.; Yangthaisong, A.; Rattanapun, C.; Wichainchai, A.

2011-05-01

The doping level dependence of thermoelectric properties of delafossite CuAlO2 has been investigated in the constant scattering time ( τ) approximation, starting from the first principles of electronic structure. In particular, the lattice parameters and the energy band structure were calculated using the total energy plane-wave pseudopotential method. It was found that the lattice parameters of CuAlO2 are a = 2.802 Å and c = 16.704 Å, and the internal parameter is u = 0.1097. CuAlO2 has an indirect band gap of 2.17 eV and a direct gap of 3.31 eV. The calculated energy band structures were then used to calculate the electrical transport coefficients of CuAlO2. By considering the effects of doping level and temperature, it was found that the Seebeck coefficient S( T) increases with increasing acceptor doping ( A d) level. The values of S( T) in our experiments correspond to an A d level at 0.262 eV, which is identified as the Fermi level of CuAlO2. Based on our experimental Seebeck coefficient and the electrical conductivity, the constant relaxation time is estimated to be 1 × 10-16 s. The power factor is large for a low A d level and increases with temperature. It is suggested that delafossite CuAlO2 can be considered as a promising thermoelectric oxide material at high doping and high temperature.

Effect of chromium doping on the structural and vibrational properties of Mn-Zn ferrites

NASA Astrophysics Data System (ADS)

Saleem, M.; Varshney, Dinesh

2018-05-01

The synthesis of Mn0.5Zn0.5-xCrxFe2O4 (x = 0.0, 0.1, 0.2 and 0.5) via sol-gel Auto-combustion technique is reported. The x-ray diffraction spectra analysis revealed the cubic spinel structure for all the prepared spinel ferrite samples with the space group Fd3m. The structural studies identify the decrease of lattice parameter however the crystallite size decreases on increasing the Cr concentration. The Raman spectrum reveals five active phonon modes at room temperature and shifting of modes toward the higher frequency side on moving from Mn-ZnFe2O4 to Mn-CrFe2O4.

On the saturation of the refractive index structure function. II - Influence of the correlation length on astronomical 'seeing'

NASA Technical Reports Server (NTRS)

Venkatakrishnan, P.

1987-01-01

A physical length scale in the wavefront corresponding to the parameter (r sub 0) characterizing the loss in detail in a long exposure image is identified, and the influence of the correlation scale of turbulence as r sub 0 approaches this scale is shown. Allowing for the effect of 2-point correlations in the fluctuations of the refractive index, Venkatakrishnan and Chatterjee (1987) proposed a modified law for the phase structure function. It is suggested that the departure of the phase structure function from the 5/3 power law for length scales in the wavefront approaching the correlation scale of turbulence may lead to better 'seeing' at longer wavelengths.

Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.

PubMed

Ring, Caroline L; Pearce, Robert G; Setzer, R Woodrow; Wetmore, Barbara A; Wambaugh, John F

2017-09-01

The thousands of chemicals present in the environment (USGAO, 2013) must be triaged to identify priority chemicals for human health risk research. Most chemicals have little of the toxicokinetic (TK) data that are necessary for relating exposures to tissue concentrations that are believed to be toxic. Ongoing efforts have collected limited, in vitro TK data for a few hundred chemicals. These data have been combined with biomonitoring data to estimate an approximate margin between potential hazard and exposure. The most "at risk" 95th percentile of adults have been identified from simulated populations that are generated either using standard "average" adult human parameters or very specific cohorts such as Northern Europeans. To better reflect the modern U.S. population, we developed a population simulation using physiologies based on distributions of demographic and anthropometric quantities from the most recent U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES) data. This allowed incorporation of inter-individual variability, including variability across relevant demographic subgroups. Variability was analyzed with a Monte Carlo approach that accounted for the correlation structure in physiological parameters. To identify portions of the U.S. population that are more at risk for specific chemicals, physiologic variability was incorporated within an open-source high-throughput (HT) TK modeling framework. We prioritized 50 chemicals based on estimates of both potential hazard and exposure. Potential hazard was estimated from in vitro HT screening assays (i.e., the Tox21 and ToxCast programs). Bioactive in vitro concentrations were extrapolated to doses that produce equivalent concentrations in body tissues using a reverse dosimetry approach in which generic TK models are parameterized with: 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. For risk-based prioritization of chemicals, predicted bioactive equivalent doses were compared to demographic-specific inferences of exposure rates that were based on NHANES urinary analyte biomonitoring data. The inclusion of NHANES-derived inter-individual variability decreased predicted bioactive equivalent doses by 12% on average for the total population when compared to previous methods. However, for some combinations of chemical and demographic groups the margin was reduced by as much as three quarters. This TK modeling framework allows targeted risk prioritization of chemicals for demographic groups of interest, including potentially sensitive life stages and subpopulations. Published by Elsevier Ltd.

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Modeling the thermal conductivities of the zinc antimonides ZnSb and Zn4Sb3

NASA Astrophysics Data System (ADS)

Bjerg, Lasse; Iversen, Bo B.; Madsen, Georg K. H.

2014-01-01

ZnSb and Zn4Sb3 are interesting as thermoelectric materials because of their low cost and low thermal conductivity. We introduce a model of the lattice thermal conductivity which is independent of fitting parameters and takes the full phonon dispersions into account. The model is found to give thermal conductivities with the correct relative magnitudes and in reasonable quantitative agreement with experiment for a number of semiconductor structures. The thermal conductivities of the zinc antimonides are reviewed and the relatively large effect of nanostructuring on the zinc antimonides is rationalized in terms of the mean free paths of the heat carrying phonons. The very low thermal conductivity of Zn4Sb3 is found to be intrinsic to the structure. However, the low-lying optical modes are observed in both Zn-Sb structures and involve both Zn and Sb vibrations, thereby strongly questioning dumbbell rattling. A mechanism for the very low thermal conductivity observed in Zn4Sb3 is identified. The large Grüneisen parameter of this compound is traced to the Sb atoms which coordinate only Zn atoms.

Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models

NASA Astrophysics Data System (ADS)

Klotz, D.; Herrnegger, M.; Schulz, K.

2017-11-01

Current concepts for parameter regionalization of spatially distributed rainfall-runoff models rely on the a priori definition of transfer functions that globally map land surface characteristics (such as soil texture, land use, and digital elevation) into the model parameter space. However, these transfer functions are often chosen ad hoc or derived from small-scale experiments. This study proposes and tests an approach for inferring the structure and parametrization of possible transfer functions from runoff data to potentially circumvent these difficulties. The concept uses context-free grammars to generate possible proposition for transfer functions. The resulting structure can then be parametrized with classical optimization techniques. Several virtual experiments are performed to examine the potential for an appropriate estimation of transfer function, all of them using a very simple conceptual rainfall-runoff model with data from the Austrian Mur catchment. The results suggest that a priori defined transfer functions are in general well identifiable by the method. However, the deduction process might be inhibited, e.g., by noise in the runoff observation data, often leading to transfer function estimates of lower structural complexity.

Vibrational spectra, DFT quantum chemical calculations and conformational analysis of P-iodoanisole.

PubMed

Arivazhagan, M; Anitha Rexalin, D; Geethapriya, J

2013-09-01

The solid phase FT-IR and FT-Raman spectra of P-iodoanisole (P-IA) have been recorded in the regions 400-4000 and 50-4000 cm(-1), respectively. The spectra were interpreted in terms of fundamentals modes, combination and overtone bands. The structure of the molecule was optimized and the structural characteristics were determined by ab initio (HF) and density functional theory (B3LYP) methods with LanL2DZ as basis set. The potential energy surface scan for the selected dihedral angle of P-IA has been performed to identify stable conformer. The optimized structure parameters and vibrational wavenumbers of stable conformer have been predicted by density functional B3LYP method with LanL2DZ (with effective core potential representations of electrons near the nuclei for post-third row atoms) basis set. The nucleophilic and electrophilic sites obtained from the molecular electrostatic potential (MEP) surface were calculated. The temperature dependence of thermodynamic properties has been analyzed. Several thermodynamic parameters have been calculated using B3LYP with LanL2DZ basis set. Copyright © 2013 Elsevier B.V. All rights reserved.

Effect of environmental parameters on habitat structural weight and cost

NASA Technical Reports Server (NTRS)

Bock, E.; Lambrou, F., Jr.; Simon, M.

1979-01-01

Space-settlement conceptual designs were previously accomplished using earth-normal physiological conditions. The habitat weight and cost penalties associated with this conservative design approach are quantified. These penalties are identified by comparison of conservative earth-normal designs with habitats designed to less than earth-normal conditions. Physiological research areas are also recommended as a necessary prerequisite to realizing these potential weight and cost savings. Major habitat structural elements, that is, pressure shell and radiation shielding, for populations of 100, 10,000, and 1,000,000, are evaluated for effects of atmospheric pressure, pseudogravity level, radiation shielding thickness, and habitat configuration.

Evaluation of existing knowledge of the tectonic history and lithospheric structure of South America

NASA Technical Reports Server (NTRS)

Keller, G. R.; Lidiak, E. G. (Principal Investigator)

1980-01-01

While data is available on the lithospheric and crustal structure of the Andes region of South America, there is limited knowledge of these aspects of the eastern portion of the continent. For this reason, a surface wave dispersion study of the area was initiated. Long period seismograms were obtained for a tripartite analysis of dispersion. A flow chart of the analysis to be conducted is presented along with a preliminary geologic/tectonic map that was prepared. Efforts to characterize the provinces identified in terms of their geological and geophysical parameters continue.

Modeling human target acquisition in ground-to-air weapon systems

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Mohr, R. L.; Vikmanis, M.; Wei, K. C.

1982-01-01

The problems associated with formulating and validating mathematical models for describing and predicting human target acquisition response are considered. In particular, the extension of the human observer model to include the acquisition phase as well as the tracking segment is presented. Relationship of the Observer model structure to the more complex Standard Optimal Control model formulation and to the simpler Transfer Function/Noise representation is discussed. Problems pertinent to structural identifiability and the form of the parameterization are elucidated. A systematic approach toward the identification of the observer acquisition model parameters from ensemble tracking error data is presented.

Behavior of single lap composite bolted joint under traction loading: Experimental investigation

NASA Astrophysics Data System (ADS)

Awadhani, L. V.; Bewoor, Anand

2018-04-01

Composite bolted joints are preferred connection in the composite structures to facilitate the dismantling for the replacements/ maintenance work. The joint behavior under tractive forces has been studied in order to understand the safety of the structure designed. The main objective of this paper is to investigate the behavior of single-lap joints in carbon fiber reinforced epoxy composites under traction loading conditions. The experiments were designed to identify the effect of bolt diameter, stacking sequence and loading rate on the properties of the joint. The experimental results show that the parameters influence the joint performance significantly.

Computing with volatile memristors: an application of non-pinched hysteresis

NASA Astrophysics Data System (ADS)

Pershin, Y. V.; Shevchenko, S. N.

2017-02-01

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication. Specific regions of parameter space realizing useful logic functions are identified. Our results are applicable to other realizations of volatile memory devices, such as certain NEMS switches.

Information processing occurs via critical avalanches in a model of the primary visual cortex

NASA Astrophysics Data System (ADS)

Bortolotto, G. S.; Girardi-Schappo, M.; Gonsalves, J. J.; Pinto, L. T.; Tragtenberg, M. H. R.

2016-01-01

We study a new biologically motivated model for the Macaque monkey primary visual cortex which presents power-law avalanches after a visual stimulus. The signal propagates through all the layers of the model via avalanches that depend on network structure and synaptic parameter. We identify four different avalanche profiles as a function of the excitatory postsynaptic potential. The avalanches follow a size-duration scaling relation and present critical exponents that match experiments. The structure of the network gives rise to a regime of two characteristic spatial scales, one of which vanishes in the thermodynamic limit.

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

Yu, Qi; Zhu, Fang-Yuan; Cheng, Li-Qian

Crystallographic structure of sol-gel-processed lead-free (K,Na)NbO{sub 3} (KNN) epitaxial films on [100]-cut SrTiO{sub 3} single-crystalline substrates was investigated for a deeper understanding of its piezoelectric response. Lattice parameter measurement by high-resolution X-ray diffraction and transmission electron microscopy revealed that the orthorhombic KNN films on SrTiO{sub 3} (100) surfaces are [010] oriented (b-axis-oriented) rather than commonly identified c-axis orientation. Based on the crystallographic orientation and corresponding ferroelectric domain structure investigated by piezoresponse force microscopy, the superior piezoelectric property along b-axis of epitaxial KNN films than other orientations can be explained.

Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.

PubMed

Bian, Zijian; Tan, Wenjun; Yang, Jinzhu; Liu, Jiren; Zhao, Dazhe

2014-01-01

The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality.

Structure-based control of complex networks with nonlinear dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Yang, Gang; Albert, Reka

What can we learn about controlling a system solely from its underlying network structure? Here we use a framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system towards any of its natural long term dynamic behaviors, regardless of the dynamic details and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of classical structural control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case, but not in specific model instances. This work was supported by NSF Grants PHY 1205840 and IIS 1160995. JGTZ is a recipient of a Stand Up To Cancer - The V Foundation Convergence Scholar Award.

Two-compartment modeling of tissue microcirculation revisited.

PubMed

Brix, Gunnar; Salehi Ravesh, Mona; Griebel, Jürgen

2017-05-01

Conventional two-compartment modeling of tissue microcirculation is used for tracer kinetic analysis of dynamic contrast-enhanced (DCE) computed tomography or magnetic resonance imaging studies although it is well-known that the underlying assumption of an instantaneous mixing of the administered contrast agent (CA) in capillaries is far from being realistic. It was thus the aim of the present study to provide theoretical and computational evidence in favor of a conceptually alternative modeling approach that makes it possible to characterize the bias inherent to compartment modeling and, moreover, to approximately correct for it. Starting from a two-region distributed-parameter model that accounts for spatial gradients in CA concentrations within blood-tissue exchange units, a modified lumped two-compartment exchange model was derived. It has the same analytical structure as the conventional two-compartment model, but indicates that the apparent blood flow identifiable from measured DCE data is substantially overestimated, whereas the three other model parameters (i.e., the permeability-surface area product as well as the volume fractions of the plasma and interstitial distribution space) are unbiased. Furthermore, a simple formula was derived to approximately compute a bias-corrected flow from the estimates of the apparent flow and permeability-surface area product obtained by model fitting. To evaluate the accuracy of the proposed modeling and bias correction method, representative noise-free DCE curves were analyzed. They were simulated for 36 microcirculation and four input scenarios by an axially distributed reference model. As analytically proven, the considered two-compartment exchange model is structurally identifiable from tissue residue data. The apparent flow values estimated for the 144 simulated tissue/input scenarios were considerably biased. After bias-correction, the deviations between estimated and actual parameter values were (11.2 ± 6.4) % (vs. (105 ± 21) % without correction) for the flow, (3.6 ± 6.1) % for the permeability-surface area product, (5.8 ± 4.9) % for the vascular volume and (2.5 ± 4.1) % for the interstitial volume; with individual deviations of more than 20% being the exception and just marginal. Increasing the duration of CA administration only had a statistically significant but opposite effect on the accuracy of the estimated flow (declined) and intravascular volume (improved). Physiologically well-defined tissue parameters are structurally identifiable and accurately estimable from DCE data by the conceptually modified two-compartment model in combination with the bias correction. The accuracy of the bias-corrected flow is nearly comparable to that of the three other (theoretically unbiased) model parameters. As compared to conventional two-compartment modeling, this feature constitutes a major advantage for tracer kinetic analysis of both preclinical and clinical DCE imaging studies. © 2017 American Association of Physicists in Medicine.

Classification of reaches in the Missouri and lower Yellowstone Rivers based on flow characteristics

USGS Publications Warehouse

Pegg, Mark A.; Pierce, Clay L.

2002-01-01

Several aspects of flow have been shown to be important determinants of biological community structure and function in streams, yet direct application of this approach to large rivers has been limited. Using a multivariate approach, we grouped flow gauges into hydrologically similar units in the Missouri and lower Yellowstone Rivers and developed a model based on flow variability parameters that could be used to test hypotheses about the role of flow in determining aquatic community structure. This model could also be used for future comparisons as the hydrological regime changes. A suite of hydrological parameters for the recent, post-impoundment period (1 October 1966–30 September 1996) for each of 15 gauges along the Missouri and lower Yellowstone Rivers were initially used. Preliminary graphical exploration identified five variables for use in further multivariate analyses. Six hydrologically distinct units composed of gauges exhibiting similar flow characteristics were then identified using cluster analysis. Discriminant analyses identified the three most influential variables as flow per unit drainage area, coefficient of variation of mean annual flow, and flow constancy. One surprising result was the relative similarity of flow regimes between the two uppermost and three lowermost gauges, despite large differences in magnitude of flow and separation by roughly 3000 km. Our results synthesize, simplify and interpret the complex changes in flow occurring along the Missouri and lower Yellowstone Rivers, and provide an objective grouping for future tests of how these changes may affect biological communities. 

On the selection of user-defined parameters in data-driven stochastic subspace identification

NASA Astrophysics Data System (ADS)

Priori, C.; De Angelis, M.; Betti, R.

2018-02-01

The paper focuses on the time domain output-only technique called Data-Driven Stochastic Subspace Identification (DD-SSI); in order to identify modal models (frequencies, damping ratios and mode shapes), the role of its user-defined parameters is studied, and rules to determine their minimum values are proposed. Such investigation is carried out using, first, the time histories of structural responses to stationary excitations, with a large number of samples, satisfying the hypothesis on the input imposed by DD-SSI. Then, the case of non-stationary seismic excitations with a reduced number of samples is considered. In this paper, partitions of the data matrix different from the one proposed in the SSI literature are investigated, together with the influence of different choices of the weighting matrices. The study is carried out considering two different applications: (1) data obtained from vibration tests on a scaled structure and (2) in-situ tests on a reinforced concrete building. Referring to the former, the identification of a steel frame structure tested on a shaking table is performed using its responses in terms of absolute accelerations to a stationary (white noise) base excitation and to non-stationary seismic excitations of low intensity. Black-box and modal models are identified in both cases and the results are compared with those from an input-output subspace technique. With regards to the latter, the identification of a complex hospital building is conducted using data obtained from ambient vibration tests.

Damage Model and Progressive Failure Analyses for Filament Wound Composite Laminates

NASA Astrophysics Data System (ADS)

Ribeiro, Marcelo Leite; Vandepitte, Dirk; Tita, Volnei

2013-10-01

Recent improvements in manufacturing processes and materials properties associated with excellent mechanical characteristics and low weight have made composite materials very attractive for application on civil aircraft structures. However, even new designs are still very conservative, because the composite failure phenomenon is very complex. Several failure criteria and theories have been developed to describe the damage process and how it evolves, but the solution of the problem is still open. Moreover, modern filament winding techniques have been used to produce a wide variety of structural shapes not only cylindrical parts, but also “flat” laminates. Therefore, this work presents the development of a damage model and its application to simulate the progressive failure of flat composite laminates made using a filament winding process. The damage model was implemented as a UMAT (User Material Subroutine), in ABAQUSTM Finite Element (FE) framework. Progressive failure analyses were carried out using FE simulation in order to simulate the failure of flat filament wound composite structures under different loading conditions. In addition, experimental tests were performed in order to identify parameters related to the material model, as well as to evaluate both the potential and the limitations of the model. The difference between numerical and the average experimental results in a four point bending set-up is only 1.6 % at maximum load amplitude. Another important issue is that the model parameters are not so complicated to be identified. This characteristic makes this model very attractive to be applied in an industrial environment.

Towards an Ultrasonic Guided Wave Procedure for Health Monitoring of Composite Vessels: Application to Hydrogen-Powered Aircraft

PubMed Central

Yaacoubi, Slah; McKeon, Peter; Ke, Weina; Declercq, Nico F.; Dahmene, Fethi

2017-01-01

This paper presents an overview and description of the approach to be used to investigate the behavior and the defect sensitivity of various ultrasonic guided wave (UGW) modes propagating specifically in composite cylindrical vessels in the framework of the safety of hydrogen energy transportation such as hydrogen-powered aircrafts. These structures which consist of thick and multi-layer composites are envisioned for housing hydrogen gas at high pressures. Due to safety concerns associated with a weakened structure, structural health monitoring techniques are needed. A procedure for optimizing damage detection in these structural types is presented. It is shown that a finite element method can help identify useful experimental parameters including frequency range, excitation type, and receiver placement. PMID:28925961

Search for and Study of Nearly Periodic Orbits in the Plane Problem of Three Equal-Mass Bodies

NASA Astrophysics Data System (ADS)

Martynova, A. I.; Orlov, V. V.

2005-09-01

We analyze nearly periodic solutions in the plane problem of three equal-mass bodies by numerically simulating the dynamics of triple systems. We identify families of orbits in which all three points are on one straight line (syzygy) at the initial time. In this case, at fixed total energy of a triple system, the set of initial conditions is a bounded region in four-dimensional parameter space. We scan this region and identify sets of trajectories in which the coordinates and velocities of all bodies are close to their initial values at certain times (which are approximately multiples of the period). We classify the nearly periodic orbits by the structure of trajectory loops over one period. We have found the families of orbits generated by von Schubart’s stable periodic orbit revealed in the rectilinear three-body problem. We have also found families of hierarchical, nearly periodic trajectories with prograde and retrograde motions. In the orbits with prograde motions, the trajectory loops of two close bodies form looplike structures. The trajectories with retrograde motions are characterized by leafed structures. Orbits with central and axial symmetries are identified among the families found.

Al2O3-ZrO2 Finely Structured Multilayer Architectures from Suspension Plasma Spraying

NASA Astrophysics Data System (ADS)

Tingaud, Olivier; Montavon, Ghislain; Denoirjean, Alain; Coudert, Jean-François; Rat, Vincent; Fauchais, Pierre

2010-01-01

Suspension plasma spraying (SPS) is an alternative to conventional atmospheric plasma spraying (APS) aiming at manufacturing thinner layers (i.e., 10-100 μm) due to the specific size of the feedstock particles, from a few tens of nanometers to a few micrometers. The staking of lamellae and particles, which present a diameter ranging from 0.1 to 2.0 μm and an average thickness from 20 to 300 nm, permits to manufacture finely structured layers. Moreover, it appears as a versatile process able to manufacture different coating architectures according to the operating parameters (suspension properties, injection configuration, plasma properties, spray distance, torch scan velocity, scanning step, etc.). However, the different parameters controlling the properties of the coating, and their interdependences, are not yet fully identified. Thus, the aim of this paper is, on the one hand, to better understand the influence of operating parameters on the coating manufacturing mechanisms (in particular, the plasma gas mixture effect) and, on the other hand, to produce Al2O3-ZrO2 finely structured layers with large varieties of architectures. For this purpose, a simple theoretical model was used to describe the plasma torch operating conditions at the nozzle exit, based on experimental data (mass enthalpy, arc current intensity, thermophysical properties of plasma forming gases, etc.) and the influences of the spray parameters were determined by mean of the study of sizes and shapes of spray beads. The results enabled then to reach a better understanding of involved phenomena and their interactions on the final coating architectures permitting to manufacture several types of microstructures.

AAA gunnermodel based on observer theory. [predicting a gunner's tracking response

NASA Technical Reports Server (NTRS)

Kou, R. S.; Glass, B. C.; Day, C. N.; Vikmanis, M. M.

1978-01-01

The Luenberger observer theory is used to develop a predictive model of a gunner's tracking response in antiaircraft artillery systems. This model is composed of an observer, a feedback controller and a remnant element. An important feature of the model is that the structure is simple, hence a computer simulation requires only a short execution time. A parameter identification program based on the least squares curve fitting method and the Gauss Newton gradient algorithm is developed to determine the parameter values of the gunner model. Thus, a systematic procedure exists for identifying model parameters for a given antiaircraft tracking task. Model predictions of tracking errors are compared with human tracking data obtained from manned simulation experiments. Model predictions are in excellent agreement with the empirical data for several flyby and maneuvering target trajectories.

The Impact Of Surface Shape Of Chip-Breaker On Machined Surface

NASA Astrophysics Data System (ADS)

Šajgalík, Michal; Czán, Andrej; Martinček, Juraj; Varga, Daniel; Hemžský, Pavel; Pitela, David

2015-12-01

Machined surface is one of the most used indicators of workpiece quality. But machined surface is influenced by several factors such as cutting parameters, cutting material, shape of cutting tool or cutting insert, micro-structure of machined material and other known as technological parameters. By improving of these parameters, we can improve machined surface. In the machining, there is important to identify the characteristics of main product of these processes - workpiece, but also the byproduct - the chip. Size and shape of chip has impact on lifetime of cutting tools and its inappropriate form can influence the machine functionality and lifetime, too. This article deals with elimination of long chip created when machining of shaft in automotive industry and with impact of shape of chip-breaker on shape of chip in various cutting conditions based on production requirements.

Experimental analysis of thread movement in bolted connections due to vibrations

NASA Technical Reports Server (NTRS)

Ramey, G. ED; Jenkins, Robert C.

1994-01-01

The objective of this study was to identify the main design parameters contributing to loosening of bolts due to vibration and to identify their relative importance and degree of contribution to bolt loosening. Vibration testing was conducted on a shaketable with a controlled-random input in the dynamic testing laboratory of the Structural Test Division of MSFC. Test specimens which contained one test bolt were vibrated for a fixed amount of time and percentage of pre-load loss was measured. Each specimen tested implemented some combination of eleven design parameters as dictated by the design of experiment methodology employed. The eleven design parameters were: bolt size (diameter), lubrication on bolt, hole tolerance, initial pre-load, nut locking device, grip length, thread pitch, lubrication between mating materials, class of fit, joint configuration and mass of configuration. These parameters were chosen for this experiment because they are believed to be the design parameters having the greatest impact on bolt loosening. Two values of each design parameter were used and each combination of parameters tested was subjected to two different directions of vibration and two different g-levels of vibration. One replication was made for each test to gain some indication of experimental error and repeatability and to give some degree of statistical credibility to the data, resulting in a total of 96 tests being performed. The results of the investigation indicated that nut locking devices, joint configuration, fastener size, and mass of configuration were significant in bolt loosening due to vibration. The results of this test can be utilized to further research the complex problem of bolt loosening due to vibration.

Integration of reflectances and thermography imagery for transport infrastructures diagnostics

NASA Astrophysics Data System (ADS)

Pignatti, S.; Palombo, A.; Pascucci, S.; Santini, F.

2012-04-01

The integrated use of reflectances and thermography to study and diagnostic of transport infrastructures has been applied on the Musumeci Bridge (Potenza, Italy) test site as a fast and non-destructive tool in the framework of the Integrated System for Transport Infrastructures surveillance and Monitoring by Electromagnetic Sensing (ISTIMES) project, funded by the European Commission in the frame of a joint Call "ICT and Security" of the Seventh Framework Programme, in order to extract appropriate information and make useful decisions [1]. The applied hyperspectral imagery is primarily suited for the detection and characterization of alterations and defects in the structures' surface, whereas by means of thermography it is possible to attain near real-time information about the internal structure such as a bridge. Hyperspectral data is able to discriminate materials on the basis of their different patterns of wavelength-specific absorption; in fact, they are successfully used for identifying minerals and rocks, as well as detecting surface materials properties [2]. For this study we used the HySpex VNIR-1600 and the SWIR-320 hyperspectral scanners (see details in Table 1) located beneath the Musmeci Bridge thus being able to acquire the structure. The hyperspectral data processing has allowed to derive indication/parameters related to the status of the structure surface, i.e. by means of the detection of the surface weathering status of the iron (i.e. iron oxides such as limonite/goethite) used to reinforce the cement structure and the occurring detachments of the cement covering the iron. This assessment can be used to foresee more severe damages of the armed concrete. Concerning the rationale for using a high sensitivity Infrared camera in the MWIR range (3.5-5 micron; see Table 1) for the Musumeci test site is based on the fact that the high radiometric resolution of the thermal images time series allows analyzing the structure homogeneity and the cohesion of the cement structure layer with the substrate. As favorable environmental condition were satisfied: (a) the inner structure is thermally connected to the external surface of the bridge structure and (b) the thermal gradient at the surface does not depend on the atmospheric conditions (e.g., sun, rain, wind and so on), it was possible for the Musumeci Bridge to detect with a good accuracy the underlying structure. More specifically, the thermal series measuring sessions were executed during the night time in order to record and understand the diurnal/nocturnal thermal behavior of the structure according to the diurnal heating of the structure. Principal Components (PC) analysis and the assessment of the parameters describing the thermal decay were used. For this study the parameter that better describes the thermal decay of the bridge corresponded to the angular coefficient of the curve better interpolating the temperature decay ramp that for a limited interval of time could be approximated to a linear decay. The jointly use of the two non-destructive techniques applied for this project is encouraged by the technical and operative characteristics of the observation systems at disposal that are able to observe the variables, physical and optical parameters in near real-time and connected to the transport infrastructures status. In particular, the hyperspectral imagery processing results show that such methodology is suitable to identify reliable parameters related to the structure surface by detecting anomalies and identifying the specific signature of the material of interest. The thermal long time series processing, i.e. both the PCA and decay coefficients images, has allowed to highlight the real inner structure of the bridge. From the proposed non-destructive monitoring approach on the Musumeci test site experiences, we can conclude that the integrated use of the two sensing techniques is a valid support for a rapid and low cost evaluation of the bridge structure and also with respect to the rapidity of the sensing the output of this technology represents a powerful tool to build the first informative level in the framework of an operative decision-support system. Table 1. Characteristics of sensors used for the study. Spectral RegionSpectral ResolutionSpectral RangeIFOV Characteristics Hyspex VNIR-1600 VIS-NIR 3.7 nm 0.4÷1.0μm 0.75 mrad160 bands (1600 pixels) HySpex SWIR-320mSWIR 5.0 nm 1.3÷2.5μm 0.75 mrad240 bands (320 pixels) FLIR SC7000 MWIR integrated 3.5÷5.0μm 1.20 mrad640 - 512 (5÷300 ° C) 1

Reconstruction of biofilm images: combining local and global structural parameters

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

Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk

2014-10-20

Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parametersmore » into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.« less

Thermoelectric Properties of a Ferromagnetic Semiconductor Based on a Dirac Semimetal (Cd3As2) under High Pressure

NASA Astrophysics Data System (ADS)

Melnikova, N. V.; Tebenkov, A. V.; Sukhanova, G. V.; Babushkin, A. N.; Saipulaeva, L. A.; Zakhvalinskii, V. S.; Gabibov, S. F.; Alibekov, A. G.; Mollaev, A. Yu.

2018-03-01

The pressure dependences of thermal emf (a parameter that ranks among the most sensitive to phase transformations) are studied for the purpose of identifying baric phase transitions in the 10-50 GPa interval in the Cd3As2 + MnAs (44.7% MnAs) structure formed by ferromagnetic MnAs granules in a semiconductor Cd3As2 matrix.

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

The Simple Lamb Wave Analysis to Characterize Concrete Wide Beams by the Practical MASW Test

PubMed Central

Lee, Young Hak; Oh, Taekeun

2016-01-01

In recent years, the Lamb wave analysis by the multi-channel analysis of surface waves (MASW) for concrete structures has been an effective nondestructive evaluation, such as the condition assessment and dimension identification by the elastic wave velocities and their reflections from boundaries. This study proposes an effective Lamb wave analysis by the practical application of MASW to concrete wide beams in an easy and simple manner in order to identify the dimension and elastic wave velocity (R-wave) for the condition assessment (e.g., the estimation of elastic properties). This is done by identifying the zero-order antisymmetric (A0) and first-order symmetric (S1) modes among multimodal Lamb waves. The MASW data were collected on eight concrete wide beams and compared to the actual depth and to the pressure (P-) wave velocities collected for the same specimen. Information is extracted from multimodal Lamb wave dispersion curves to obtain the elastic stiffness parameters and the thickness of the concrete structures. Due to the simple and cost-effective procedure associated with the MASW processing technique, the characteristics of several fundamental modes in the experimental Lamb wave dispersion curves could be measured. Available reference data are in good agreement with the parameters that were determined by our analysis scheme. PMID:28773562

Be discs in coplanar circular binaries: Phase-locked variations of emission lines

NASA Astrophysics Data System (ADS)

Panoglou, Despina; Faes, Daniel M.; Carciofi, Alex C.; Okazaki, Atsuo T.; Baade, Dietrich; Rivinius, Thomas; Borges Fernandes, Marcelo

2018-01-01

In this paper, we present the first results of radiative transfer calculations on decretion discs of binary Be stars. A smoothed particle hydrodynamics code computes the structure of Be discs in coplanar circular binary systems for a range of orbital and disc parameters. The resulting disc configuration consists of two spiral arms, and this can be given as input into a Monte Carlo code, which calculates the radiative transfer along the line of sight for various observational coordinates. Making use of the property of steady disc structure in coplanar circular binaries, observables are computed as functions of the orbital phase. Some orbital-phase series of line profiles are given for selected parameter sets under various viewing angles, to allow comparison with observations. Flat-topped profiles with and without superimposed multiple structures are reproduced, showing, for example, that triple-peaked profiles do not have to be necessarily associated with warped discs and misaligned binaries. It is demonstrated that binary tidal effects give rise to phase-locked variability of the violet-to-red (V/R) ratio of hydrogen emission lines. The V/R ratio exhibits two maxima per cycle; in certain cases those maxima are equal, leading to a clear new V/R cycle every half orbital period. This study opens a way to identifying binaries and to constraining the parameters of binary systems that exhibit phase-locked variations induced by tidal interaction with a companion star.

The structured ancestral selection graph and the many-demes limit.

PubMed

Slade, Paul F; Wakeley, John

2005-02-01

We show that the unstructured ancestral selection graph applies to part of the history of a sample from a population structured by restricted migration among subpopulations, or demes. The result holds in the limit as the number of demes tends to infinity with proportionately weak selection, and we have also made the assumptions of island-type migration and that demes are equivalent in size. After an instantaneous sample-size adjustment, this structured ancestral selection graph converges to an unstructured ancestral selection graph with a mutation parameter that depends inversely on the migration rate. In contrast, the selection parameter for the population is independent of the migration rate and is identical to the selection parameter in an unstructured population. We show analytically that estimators of the migration rate, based on pairwise sequence differences, derived under the assumption of neutrality should perform equally well in the presence of weak selection. We also modify an algorithm for simulating genealogies conditional on the frequencies of two selected alleles in a sample. This permits efficient simulation of stronger selection than was previously possible. Using this new algorithm, we simulate gene genealogies under the many-demes ancestral selection graph and identify some situations in which migration has a strong effect on the time to the most recent common ancestor of the sample. We find that a similar effect also increases the sensitivity of the genealogy to selection.

Effect of injection parameters on mechanical and physical properties of super ultra-thin wall propylene packaging by Taguchi method

NASA Astrophysics Data System (ADS)

Ginghtong, Thatchanok; Nakpathomkun, Natthapon; Pechyen, Chiravoot

2018-06-01

The parameters of the plastic injection molding process have been investigated for the manufacture of a 64 oz. ultra-thin polypropylene bucket. The 3 main parameters, such as injection speed, melting temperature, holding pressure, were investigated to study their effect on the physical appearance and compressive strength. The orthogonal array of Taguchi's L9 (33) was used to carry out the experimental plan. The physical properties were measured and the compressive strength was determined using linear regression analysis. The differential scanning calorimeter (DSC) was used to analyze the crystalline structure of the product. The optimization results show that the proposed approach can help engineers identify optimal process parameters and achieve competitive advantages of energy consumption and product quality. In addition, the injection molding of the product includes 24 mm of shot stroke, 1.47 mm position transfer, 268 rpm screw speed, injection speed 100 mm/s, 172 ton clamping force, 800 kgf holding pressure, 0.9 s holding time and 1.4 s cooling time, make the products in the shape and proportion of the product satisfactory. The parameters of influence are injection speed 71.07%, melting temperature 23.31% and holding pressure 5.62%, respectively. The compressive strength of the product was able to withstand a pressure of up to 839 N before the product became plastic. The low melting temperature was caused by the superior crystalline structure of the super-ultra-thin wall product which leads to a lower compressive strength.

Optical gradients in a-Si:H thin films detected using real-time spectroscopic ellipsometry with virtual interface analysis

NASA Astrophysics Data System (ADS)

Junda, Maxwell M.; Karki Gautam, Laxmi; Collins, Robert W.; Podraza, Nikolas J.

2018-04-01

Virtual interface analysis (VIA) is applied to real time spectroscopic ellipsometry measurements taken during the growth of hydrogenated amorphous silicon (a-Si:H) thin films using various hydrogen dilutions of precursor gases and on different substrates during plasma enhanced chemical vapor deposition. A procedure is developed for optimizing VIA model configurations by adjusting sampling depth into the film and the analyzed spectral range such that model fits with the lowest possible error function are achieved. The optimal VIA configurations are found to be different depending on hydrogen dilution, substrate composition, and instantaneous film thickness. A depth profile in the optical properties of the films is then extracted that results from a variation in an optical absorption broadening parameter in a parametric a-Si:H model as a function of film thickness during deposition. Previously identified relationships are used linking this broadening parameter to the overall shape of the optical properties. This parameter is observed to converge after about 2000-3000 Å of accumulated thickness in all layers, implying that similar order in the a-Si:H network can be reached after sufficient thicknesses. In the early stages of growth, however, significant variations in broadening resulting from substrate- and processing-induced order are detected and tracked as a function of bulk layer thickness yielding an optical property depth profile in the final film. The best results are achieved with the simplest film-on-substrate structures while limitations are identified in cases where films have been deposited on more complex substrate structures.

Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

2016-08-01

In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

A comparative assessment of different frequency based damage detection in unidirectional composite plates using MFC sensors

NASA Astrophysics Data System (ADS)

de Medeiros, Ricardo; Sartorato, Murilo; Vandepitte, Dirk; Tita, Volnei

2016-11-01

The basic concept of the vibration based damage identification methods is that the dynamic behaviour of a structure can change if damage occurs. Damage in a structure can alter the structural integrity, and therefore, the physical properties like stiffness, mass and/or damping may change. The dynamic behaviour of a structure is a function of these physical properties and will, therefore, directly be affected by the damage. The dynamic behaviour can be described in terms of time, frequency and modal domain parameters. The changes in these parameters (or properties derived from these parameters) are used as indicators of damage. Hence, this work has two main objectives. The first one is to provide an overview of the structural vibration based damage identification methods. For this purpose, a fundamental description of the structural vibration based damage identification problem is given, followed by a short literature overview of the damage features, which are commonly addressed. The second objective is to create a damage identification method for detection of the damage in composite structures. To aid in this process, two basic principles are discussed, namely the effect of the potential damage case on the dynamic behaviour, and the consequences involved with the information reduction in the signal processing. Modal properties from the structural dynamic output response are obtained. In addition, experimental and computational results are presented for the application of modal analysis techniques applied to composite specimens with and without damage. The excitation of the structures is performed using an impact hammer and, for measuring the output data, accelerometers as well as piezoelectric sensors. Finite element models are developed by shell elements, and numerical results are compared to experimental data, showing good correlation for the response of the specimens in some specific frequency range. Finally, FRFs are analysed using suitable metrics, including a new one, which are compared in terms of their capability for damage identification. The experimental and numerical results show that the vibration-based damage methods combined to the metrics can be used in Structural Health Monitoring (SHM) systems to identify the damage in the structure.

Characterizing hydrophobicity at the nanoscale: a molecular dynamics simulation study.

PubMed

Bandyopadhyay, Dibyendu; Choudhury, Niharendu

2012-06-14

We use molecular dynamics (MD) simulations of water near nanoscopic surfaces to characterize hydrophobic solute-water interfaces. By using nanoscopic paraffin like plates as model solutes, MD simulations in isothermal-isobaric ensemble have been employed to identify characteristic features of such an interface. Enhanced water correlation, density fluctuations, and position dependent compressibility apart from surface specific hydrogen bond distribution and molecular orientations have been identified as characteristic features of such interfaces. Tetrahedral order parameter that quantifies the degree of tetrahedrality in the water structure and an orientational order parameter, which quantifies the orientational preferences of the second solvation shell water around a central water molecule, have also been calculated as a function of distance from the plate surface. In the vicinity of the surface these two order parameters too show considerable sensitivity to the surface hydrophobicity. The potential of mean force (PMF) between water and the surface as a function of the distance from the surface has also been analyzed in terms of direct interaction and induced contribution, which shows unusual effect of plate hydrophobicity on the solvent induced PMF. In order to investigate hydrophobic nature of these plates, we have also investigated interplate dewetting when two such plates are immersed in water.

A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

PubMed Central

Yin, Shibin; Ren, Yongjie; Zhu, Jigui; Yang, Shourui; Ye, Shenghua

2013-01-01

A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system. PMID:24300597

Sensitivity study and parameter optimization of OCD tool for 14nm finFET process

NASA Astrophysics Data System (ADS)

Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping

2016-03-01

Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.

A Multiphase Model for the Intracluster Medium

NASA Technical Reports Server (NTRS)

Nagai, Daisuke; Sulkanen, Martin E.; Evrard, August E.

1999-01-01

Constraints on the clustered mass density of the universe derived from the observed population mean intracluster gas fraction of x-ray clusters may be biased by reliance on a single-phase assumption for the thermodynamic structure of the intracluster medium (ICM). We propose a descriptive model for multiphase structure in which a spherically symmetric ICM contains isobaric density perturbations with a radially dependent variance. Fixing the x-ray emission and emission weighted temperature, we explore two independently observable signatures of the model in the parameter space. For bremsstrahlung dominated emission, the central Sunyaev-Zel'dovich (SZ) decrement in the multiphase case is increased over the single-phase case and multiphase x-ray spectra in the range 0.1-20 keV are flatter in the continuum and exhibit stronger low energy emission lines than their single-phase counterpart. We quantify these effects for a fiducial 10e8 K cluster and demonstrate how the combination of SZ and x-ray spectroscopy can be used to identify a preferred location in the plane of the model parameter space. From these parameters the correct value of mean intracluster gas fraction in the multiphase model results, allowing an unbiased estimate of clustered mass density to he recovered.

A 3D Image Filter for Parameter-Free Segmentation of Macromolecular Structures from Electron Tomograms

PubMed Central

Ali, Rubbiya A.; Landsberg, Michael J.; Knauth, Emily; Morgan, Garry P.; Marsh, Brad J.; Hankamer, Ben

2012-01-01

3D image reconstruction of large cellular volumes by electron tomography (ET) at high (≤5 nm) resolution can now routinely resolve organellar and compartmental membrane structures, protein coats, cytoskeletal filaments, and macromolecules. However, current image analysis methods for identifying in situ macromolecular structures within the crowded 3D ultrastructural landscape of a cell remain labor-intensive, time-consuming, and prone to user-bias and/or error. This paper demonstrates the development and application of a parameter-free, 3D implementation of the bilateral edge-detection (BLE) algorithm for the rapid and accurate segmentation of cellular tomograms. The performance of the 3D BLE filter has been tested on a range of synthetic and real biological data sets and validated against current leading filters—the pseudo 3D recursive and Canny filters. The performance of the 3D BLE filter was found to be comparable to or better than that of both the 3D recursive and Canny filters while offering the significant advantage that it requires no parameter input or optimisation. Edge widths as little as 2 pixels are reproducibly detected with signal intensity and grey scale values as low as 0.72% above the mean of the background noise. The 3D BLE thus provides an efficient method for the automated segmentation of complex cellular structures across multiple scales for further downstream processing, such as cellular annotation and sub-tomogram averaging, and provides a valuable tool for the accurate and high-throughput identification and annotation of 3D structural complexity at the subcellular level, as well as for mapping the spatial and temporal rearrangement of macromolecular assemblies in situ within cellular tomograms. PMID:22479430

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

Uzun, Suzan; Ilavsky, Jan; Padua, Graciela Wild

Zein, a protein of corn, has an amphiphilic molecule capable of self-assembly into distinctly different structures. In this work, ultra-small-angle X-ray scattering (USAXS) was applied to investigate the formation of self-assembled zein structures in binary solvent systems of ethanol and water. Our study included observing structural changes due to aging. Three hierarchical structures were identified in zein-solvent systems, molecular zein 2D films, believed to be formed by zein rods assembled first into one-dimensional fibers and then into two-dimensional films, and 3D spherical aggregates. Aging did not change the size or shape of primary units, but promoted their self-assembly into intermediatemore » 2D structures and shaped 3D structures into well19 defined spheres. We found that the rheological parameters, consistency index (K) and behavior index (n), storage and loss moduli (G’ and G”) were also measured. K and n, changed markedly with aging, from nearly Newtonian low consistency fresh samples to highly viscous pseudoplastic aged samples. G’ and G” increased with aging for all samples reflecting increased interactions among zein self-assembled structures. Furthermore, viscoelastic parameters indicated that zein dispersions formed gels upon aging. It was observed that USAX reported on molecular scale self-assembly processes, while rheological measurements reported on the macroscale interaction between self-assembled particles. Raman spectra suggested that α-helix to β-sheet transformations prompted zein self-assembly, which influenced the size and morphology of molecular assemblies and ultimately the rheological properties of zein dispersions.« less

Preliminary design approach for large high precision segmented reflectors

NASA Technical Reports Server (NTRS)

Mikulas, Martin M., Jr.; Collins, Timothy J.; Hedgepeth, John M.

1990-01-01

A simplified preliminary design capability for erectable precision segmented reflectors is presented. This design capability permits a rapid assessment of a wide range of reflector parameters as well as new structural concepts and materials. The preliminary design approach was applied to a range of precision reflectors from 10 meters to 100 meters in diameter while considering standard design drivers. The design drivers considered were: weight, fundamental frequency, launch packaging volume, part count, and on-orbit assembly time. For the range of parameters considered, on-orbit assembly time was identified as the major design driver. A family of modular panels is introduced which can significantly reduce the number of reflector parts and the on-orbit assembly time.

Heavyweight cement concrete with high stability of strength parameters

NASA Astrophysics Data System (ADS)

Kudyakov, Konstantin; Nevsky, Andrey; Danke, Ilia; Kudyakov, Aleksandr; Kudyakov, Vitaly

2016-01-01

The present paper establishes regularities of basalt fibers distribution in movable cement concrete mixes under different conditions of their preparation and their selective introduction into mixer during the mixing process. The optimum content of basalt fibers was defined as 0.5% of the cement weight, which provides a uniform distribution of fibers in the concrete volume. It allows increasing compressive strength up to 51.2% and increasing tensile strength up to 28.8%. Micro-structural analysis identified new formations on the surface of basalt fibers, which indicates the good adhesion of hardened cement paste to the fibers. Stability of concrete strength parameters has significantly increased with introduction of basalt fibers into concrete mix.

Quantifying networks complexity from information geometry viewpoint

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

Felice, Domenico, E-mail: domenico.felice@unicam.it; Mancini, Stefano; INFN-Sezione di Perugia, Via A. Pascoli, I-06123 Perugia

We consider a Gaussian statistical model whose parameter space is given by the variances of random variables. Underlying this model we identify networks by interpreting random variables as sitting on vertices and their correlations as weighted edges among vertices. We then associate to the parameter space a statistical manifold endowed with a Riemannian metric structure (that of Fisher-Rao). Going on, in analogy with the microcanonical definition of entropy in Statistical Mechanics, we introduce an entropic measure of networks complexity. We prove that it is invariant under networks isomorphism. Above all, considering networks as simplicial complexes, we evaluate this entropy onmore » simplexes and find that it monotonically increases with their dimension.« less

Variation of Supergranule Parameters with Solar Cycles: Results from Century-long Kodaikanal Digitized Ca ii K Data

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

Chatterjee, Subhamoy; Mandal, Sudip; Banerjee, Dipankar, E-mail: dipu@iiap.res.in

The Ca ii K spectroheliograms spanning over a century (1907–2007) from Kodaikanal Solar Observatory, India, have recently been digitized and calibrated. Applying a fully automated algorithm (which includes contrast enhancement and the “Watershed method”) to these data, we have identified the supergranules and calculated the associated parameters, such as scale, circularity, and fractal dimension. We have segregated the quiet and active regions and obtained the supergranule parameters separately for these two domains. In this way, we have isolated the effect of large-scale and small-scale magnetic fields on these structures and find a significantly different behavior of the supergranule parameters overmore » solar cycles. These differences indicate intrinsic changes in the physical mechanism behind the generation and evolution of supergranules in the presence of small-scale and large-scale magnetic fields. This also highlights the need for further studies using solar dynamo theory along with magneto-convection models.« less

Gray-level co-occurrence matrix analysis of several cell types in mouse brain using resolution-enhanced photothermal microscopy

NASA Astrophysics Data System (ADS)

Kobayashi, Takayoshi; Sundaram, Durga; Nakata, Kazuaki; Tsurui, Hiromichi

2017-03-01

Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

PubMed

Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p < 0.0001) and day 1-3 (p = 0.0012). The biparietal width and the transcerebellar diameter were related to Burdjalov Score on day 1 (p = 0.0111; p = 0.0002). The final multiple regression analysis revealed independent predictors of neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

Structural Design Methodology Based on Concepts of Uncertainty

NASA Technical Reports Server (NTRS)

Lin, K. Y.; Du, Jiaji; Rusk, David

2000-01-01

In this report, an approach to damage-tolerant aircraft structural design is proposed based on the concept of an equivalent "Level of Safety" that incorporates past service experience in the design of new structures. The discrete "Level of Safety" for a single inspection event is defined as the compliment of the probability that a single flaw size larger than the critical flaw size for residual strength of the structure exists, and that the flaw will not be detected. The cumulative "Level of Safety" for the entire structure is the product of the discrete "Level of Safety" values for each flaw of each damage type present at each location in the structure. Based on the definition of "Level of Safety", a design procedure was identified and demonstrated on a composite sandwich panel for various damage types, with results showing the sensitivity of the structural sizing parameters to the relative safety of the design. The "Level of Safety" approach has broad potential application to damage-tolerant aircraft structural design with uncertainty.

A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation.

PubMed

Layton, D M; Bundschuh, R

2005-01-01

Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already that for changes corresponding to the actual experimental error to which these parameters have been determined, 30% of the structure are falsely predicted whereas the ground state structure is preserved under parameter perturbation in only 5% of all the cases. We establish that base-pairing probabilities calculated in a thermal ensemble are viable although not a perfect measure for the reliability of the prediction of individual structure elements. Here, a new measure of stability using parameter perturbation is proposed, and its limitations are discussed.

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

PubMed Central

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography. PMID:28740757

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels.

PubMed

Lessios, Nicolas

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike's information criterion (AIC c ) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis , the branchiopod water flea, Daphnia magna , normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus , which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei . The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.

A quantification model for the structure of clay materials.

PubMed

Tang, Liansheng; Sang, Haitao; Chen, Haokun; Sun, Yinlei; Zhang, Longjian

2016-07-04

In this paper, the quantification for clay structure is explicitly explained, and the approach and goals of quantification are also discussed. The authors consider that the purpose of the quantification for clay structure is to determine some parameters that can be used to quantitatively characterize the impact of clay structure on the macro-mechanical behaviour. According to the system theory and the law of energy conservation, a quantification model for the structure characteristics of clay materials is established and three quantitative parameters (i.e., deformation structure potential, strength structure potential and comprehensive structure potential) are proposed. And the corresponding tests are conducted. The experimental results show that these quantitative parameters can accurately reflect the influence of clay structure on the deformation behaviour, strength behaviour and the relative magnitude of structural influence on the above two quantitative parameters, respectively. These quantitative parameters have explicit mechanical meanings, and can be used to characterize the structural influences of clay on its mechanical behaviour.

Modeling global vector fields of chaotic systems from noisy time series with the aid of structure-selection techniques.

PubMed

Xu, Daolin; Lu, Fangfang

2006-12-01

We address the problem of reconstructing a set of nonlinear differential equations from chaotic time series. A method that combines the implicit Adams integration and the structure-selection technique of an error reduction ratio is proposed for system identification and corresponding parameter estimation of the model. The structure-selection technique identifies the significant terms from a pool of candidates of functional basis and determines the optimal model through orthogonal characteristics on data. The technique with the Adams integration algorithm makes the reconstruction available to data sampled with large time intervals. Numerical experiment on Lorenz and Rossler systems shows that the proposed strategy is effective in global vector field reconstruction from noisy time series.

The search for loci under selection: trends, biases and progress.

PubMed

Ahrens, Collin W; Rymer, Paul D; Stow, Adam; Bragg, Jason; Dillon, Shannon; Umbers, Kate D L; Dudaniec, Rachael Y

2018-03-01

Detecting genetic variants under selection using F ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics. © 2018 John Wiley & Sons Ltd.

Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics.

PubMed

Aliev, Abil E; Kulke, Martin; Khaneja, Harmeet S; Chudasama, Vijay; Sheppard, Tom D; Lanigan, Rachel M

2014-02-01

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use (13) C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Copyright © 2013 Wiley Periodicals, Inc.

Distinct taxonomic and functional composition of soil microbiomes along the gradient forest-restinga-mangrove in southeastern Brazil.

PubMed

Mendes, Lucas William; Tsai, Siu Mui

2018-01-01

Soil microorganisms play crucial roles in ecosystem functioning, and the central goal in microbial ecology studies is to elucidate which factors shape community structure. A better understanding of the relationship between microbial diversity, functions and environmental parameters would increase our ability to set conservation priorities. Here, the bacterial and archaeal community structure in Atlantic Forest, restinga and mangrove soils was described and compared based on shotgun metagenomics. We hypothesized that each distinct site would harbor a distinct taxonomic and functional soil community, which is influenced by environmental parameters. Our data showed that the microbiome is shaped by soil properties, with pH, base saturation, boron and iron content significantly correlated to overall community structure. When data of specific phyla were correlated to specific soil properties, we demonstrated that parameters such as boron, copper, sulfur, potassium and aluminum presented significant correlation with the most number of bacterial groups. Mangrove soil was the most distinct site and presented the highest taxonomic and functional diversity in comparison with forest and restinga soils. From the total 34 microbial phyla identified, 14 were overrepresented in mangrove soils, including several archaeal groups. Mangrove soils hosted a high abundance of sequences related to replication, survival and adaptation; forest soils included high numbers of sequences related to the metabolism of nutrients and other composts; while restinga soils included abundant genes related to the metabolism of carbohydrates. Overall, our finds show that the microbial community structure and functional potential were clearly different across the environmental gradient, followed by functional adaptation and both were related to the soil properties.

Low-energy tautomers and conformers of neutral and protonated arginine.

PubMed

Rak, J; Skurski, P; Simons, J; Gutowski, M

2001-11-28

The relative stabilities of zwitterionic and canonical forms of neutral arginine and of its protonated derivative were studied by using ab initio electronic structure methods. Trial structures were first identified at the PM3 level of theory with use of a genetic algorithm to systematically vary geometrical parameters. Further geometry optimizations of these structures were performed at the MP2 and B3LYP levels of theory with basis sets of the 6-31++G** quality. The final energies were determined at the CCSD/6-31++G** level and corrected for thermal effects determined at the B3LYP level. Two new nonzwitterionic structures of the neutral were identified, and one of them is the lowest energy structure found so far. The five lowest energy structures of neutral arginine are all nonzwitterionic in nature and are clustered within a narrow energy range of 2.3 kcal/mol. The lowest energy zwitterion structure is less stable than the lowest nonzwitterion structure by 4.0 kcal/mol. For no level of theory is a zwitterion structure suggested to be the global minimum. The calculated proton affinity of 256.3 kcal/mol and gas-phase basicity of 247.8 kcal/mol of arginine are in reasonable agreement with the measured values of 251.2 and 240.6 kcal/mol, respectively. The calculated vibrational characteristics of the low-energy structures of neutral arginine provide an alternative interpretation of the IR-CRLAS spectrum (Chapo et al. J. Am. Chem. Soc. 1998, 120, 12956-12957).

A Novel Identification Methodology for the Coordinate Relationship between a 3D Vision System and a Legged Robot

PubMed Central

Chai, Xun; Gao, Feng; Pan, Yang; Qi, Chenkun; Xu, Yilin

2015-01-01

Coordinate identification between vision systems and robots is quite a challenging issue in the field of intelligent robotic applications, involving steps such as perceiving the immediate environment, building the terrain map and planning the locomotion automatically. It is now well established that current identification methods have non-negligible limitations such as a difficult feature matching, the requirement of external tools and the intervention of multiple people. In this paper, we propose a novel methodology to identify the geometric parameters of 3D vision systems mounted on robots without involving other people or additional equipment. In particular, our method focuses on legged robots which have complex body structures and excellent locomotion ability compared to their wheeled/tracked counterparts. The parameters can be identified only by moving robots on a relatively flat ground. Concretely, an estimation approach is provided to calculate the ground plane. In addition, the relationship between the robot and the ground is modeled. The parameters are obtained by formulating the identification problem as an optimization problem. The methodology is integrated on a legged robot called “Octopus”, which can traverse through rough terrains with high stability after obtaining the identification parameters of its mounted vision system using the proposed method. Diverse experiments in different environments demonstrate our novel method is accurate and robust. PMID:25912350

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Investigation on sense of control parameters for joystick interface in remote operated container crane application

NASA Astrophysics Data System (ADS)

Abdullah, U. N. N.; Handroos, H.

2017-09-01

Introduction: This paper presents the study of sense of control parameters to improve the lack of direct motion feeling through remote operated container crane station (ROCCS) joystick interface. The investigations of the parameters in this study are important to develop the engineering parameters related to the sense of control goal in the next design process. Methodology: Structured interviews and observations were conducted to obtain the user experience data from thirteen remote container crane operators from two international terminals. Then, interview analysis, task analysis, activity analysis and time line analysis were conducted to compare and contrast the results from interviews and observations. Results: Four experience parameters were identified to support the sense of control goal in the later design improvement of the ROCC joystick interface. The significance of difficulties to control, unsynchronized movements, facilitate in control and decision making in unexpected situation as parameters to the sense of control goal were validated by' feedbacks from operators as well as analysis. Contribution: This study provides feedback directly from end users towards developing a sustainable control interface for ROCCS in specific and remote operated off-road vehicles in general.

[Incentive for Regional Risk Selection in the German Risk Structure Compensation Scheme].

PubMed

Wende, Danny

2017-10-01

The introduction of the new law GKV-FQWG strengthens the competition between statutory health insurance. If incentives for risk selection exist, they may force a battle for cheap customers. This study aims to document and discuss incentives for regional risk selection in the German risk structure compensation scheme. Identify regional autocorrelation with Moran's l on financial parameters of the risk structure compensation schema. Incentives for regional risk selection do indeed exist. The risk structure compensation schema reduces 91% of the effect and helps to reduce risk selection. Nevertheless, a connection between regional situation and competition could be shown (correlation: 69.5%). Only the integration of regional control variables into the risk compensation eliminates regional autocorrelation. The actual risk structure compensation is leading to regional inequalities and as a consequence to risk selection and distortion in competition. © Georg Thieme Verlag KG Stuttgart · New York.

Advances in parameter estimation techniques applied to flexible structures

NASA Technical Reports Server (NTRS)

Maben, Egbert; Zimmerman, David C.

1994-01-01

In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.

Surface structure determines dynamic wetting.

PubMed

Wang, Jiayu; Do-Quang, Minh; Cannon, James J; Yue, Feng; Suzuki, Yuji; Amberg, Gustav; Shiomi, Junichiro

2015-02-16

Liquid wetting of a surface is omnipresent in nature and the advance of micro-fabrication and assembly techniques in recent years offers increasing ability to control this phenomenon. Here, we identify how surface roughness influences the initial dynamic spreading of a partially wetting droplet by studying the spreading on a solid substrate patterned with microstructures just a few micrometers in size. We reveal that the roughness influence can be quantified in terms of a line friction coefficient for the energy dissipation rate at the contact line, and that this can be described in a simple formula in terms of the geometrical parameters of the roughness and the line-friction coefficient of the planar surface. We further identify a criterion to predict if the spreading will be controlled by this surface roughness or by liquid inertia. Our results point to the possibility of selectively controlling the wetting behavior by engineering the surface structure.

A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

NASA Astrophysics Data System (ADS)

Gronewold, A.; Alameddine, I.; Anderson, R. M.

2009-12-01

Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United States Environmental Protection Agency (USEPA) total maximum daily load (TMDL) program, as well as those addressing coastal population dynamics and sea level rise. Our approach has several advantages, including the propagation of parameter uncertainty through a nonparametric probability distribution which avoids common pitfalls of fitting parameters and model error structure to a predetermined parametric distribution function. In addition, by explicitly acknowledging correlation between model parameters (and reflecting those correlations in our predictive model) our model yields relatively efficient prediction intervals (unlike those in the current literature which are often unnecessarily large, and may lead to overly-conservative management actions). Finally, our model helps improve understanding of the rainfall-runoff process by identifying model parameters (and associated catchment attributes) which are most sensitive to current and future land use change patterns. Disclaimer: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.

Intrasystem Analysis Program (IAP) Structural Design Study.

DTIC Science & Technology

1981-06-01

accuracy constraints, and user competence . This report is designed to serve as a guide in con- structing procedures and identifying those aspects of the...parameters. 3.3.3 Userability The term "Userability" refers here to the level of competence assumed for an IAP analyst in need of a procedure. There...media the wires pass through is homogeneous along the length of the wires. Under these assumptions the wave propagation is predominantly tranverse

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

Kim, Sang Beom; Dsilva, Carmeline J.; Debenedetti, Pablo G., E-mail: pdebene@princeton.edu

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories inmore » a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.« less

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna; Ruggieri, Fabrizio

2014-08-01

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above "local" models and retention times of triazines are modelled with accuracy generally better than 7%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discovery of a Kelch-like ECH-associated protein 1-inhibitory tetrapeptide and its structural characterization

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

Sogabe, Satoshi; Sakamoto, Kotaro; Kamada, Yusuke

Keap1 constitutively binds to the transcription factor Nrf2 to promote its degradation, resulting in negative modulation of genes involved in cellular protection against oxidative stress. Keap1 is increasingly recognized as an attractive target for treating diseases involving oxidative stress, including cancer, atherosclerosis, diabetes, arthritis, and neurodegeneration. We used phage-display peptide screening to identify a tetrapeptide showing moderate binding affinity, which inhibits the interaction between Nrf2 and Keap1. The tetrapeptide does not include an ETGE motif, which is a commonly found consensus sequence in known peptidic inhibitors. In addition to affinity parameters, IC{sub 50}, K{sub D}, and thermodynamic parameters, the crystalmore » structure of the complex was determined to elucidate the binding conformation. The binding interactions resemble those of known small-molecule inhibitors as opposed to those of substrates and peptidic inhibitors. Although the tetrapeptide's affinity is not very high, our results may help facilitate the designing of small-molecule inhibitors during lead generation in drug discovery. - Highlights: • Keap1 inhibitory tetrapeptide with moderate affinity was discovered. • Crystal structure of the complex showed the unique binding mode. • Structural information gives a valuable insight for design of therapeutic compounds.« less

Noise, gain, and capture probability of p-type InAs-GaAs quantum-dot and quantum dot-in-well infrared photodetectors

NASA Astrophysics Data System (ADS)

Wolde, Seyoum; Lao, Yan-Feng; Unil Perera, A. G.; Zhang, Y. H.; Wang, T. M.; Kim, J. O.; Schuler-Sandy, Ted; Tian, Zhao-Bing; Krishna, S.

2017-06-01

We report experimental results showing how the noise in a Quantum-Dot Infrared photodetector (QDIP) and Quantum Dot-in-a-well (DWELL) varies with the electric field and temperature. At lower temperatures (below ˜100 K), the noise current of both types of detectors is dominated by generation-recombination (G-R) noise which is consistent with a mechanism of fluctuations driven by the electric field and thermal noise. The noise gain, capture probability, and carrier life time for bound-to-continuum or quasi-bound transitions in DWELL and QDIP structures are discussed. The capture probability of DWELL is found to be more than two times higher than the corresponding QDIP. Based on the analysis, structural parameters such as the numbers of active layers, the surface density of QDs, and the carrier capture or relaxation rate, type of material, and electric field are some of the optimization parameters identified to improve the gain of devices.

A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2016-08-01

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

Multiverse understanding of cosmological coincidences

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

Bousso, Raphael; Hall, Lawrence J.; Nomura, Yasunori

2009-09-15

There is a deep cosmological mystery: although dependent on very different underlying physics, the time scales of structure formation, of galaxy cooling (both radiatively and against the CMB), and of vacuum domination do not differ by many orders of magnitude, but are all comparable to the present age of the universe. By scanning four landscape parameters simultaneously, we show that this quadruple coincidence is resolved. We assume only that the statistical distribution of parameter values in the multiverse grows towards certain catastrophic boundaries we identify, across which there are drastic regime changes. We find order-of-magnitude predictions for the cosmological constant,more » the primordial density contrast, the temperature at matter-radiation equality, the typical galaxy mass, and the age of the universe, in terms of the fine structure constant and the electron, proton and Planck masses. Our approach permits a systematic evaluation of measure proposals; with the causal patch measure, we find no runaway of the primordial density contrast and the cosmological constant to large values.« less

Unique spin-polarized transmission effects in a QD ring structure

NASA Astrophysics Data System (ADS)

Hedin, Eric; Joe, Yong

2010-10-01

Spintronics is an emerging field in which the spin of the electron is used for switching purposes and to communicate information. In order to obtain spin-polarized electron transmission, the Zeeman effect is employed to produce spin-split energy states in quantum dots which are embedded in the arms of a mesoscopic Aharonov-Bohm (AB) ring heterostructure. The Zeeman splitting of the QD energy levels can be induced by a parallel magnetic field, or by a perpendicular field which also produces AB-effects. The combination of these effects on the transmission resonances of the structure is studied analytically and several parameter regimes are identified which produce a high degree of spin-polarized output. Contour and line plots of the weighted spin polarization as a function of electron energy and magnetic field are presented to visualize the degree of spin-polarization. Taking advantage of these unique parameter regimes shows the potential promise of such devices for producing spin-polarized currents.

Nature of the tensor order in Cd 2 Re 2 O 7

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

Di Matteo, S.; Norman, M. R.

The pyrochlore metal Cd 2Re 2O 7 has been recently investigated by second-harmonic generation (SHG) reflectivity. In this paper, we develop a general formalism that allows for the identification of the relevant tensor components of the SHG from azimuthal scans. We demonstrate that the secondary order parameter identified by SHG at the structural phase transition is the x 2 - y 2 component of the axial toroidal quadrupole. This differs from the 3z 2 - r 2 symmetry of the atomic displacements associated with the I4m2 crystal structure that was previously thought to be its origin. Within the same formalism,more » we suggest that the primary order parameter detected in the SHG experiment is the 3z 2 - r 2 component of the magnetic quadrupole. We discuss the general mechanism driving the phase transition in our proposed framework, and suggest experiments, particularly resonant x-ray scattering ones, that could clarify this issue.« less

The Nature and Origin of Time-Asymmetric Spacetime Structures

NASA Astrophysics Data System (ADS)

Zeh, H. Dieter

Time-asymmetric spacetime structures, in particular those representing black holes and the expansion of the universe, are intimately related to other arrows of time, such as the second law and the retardation of radiation. The nature of the quantum arrow, often attributed to a collapse of the wave function, is essential, in particular, for understanding the much discussed black hole information loss paradox. This paradox assumes a new form and can possibly be avoided in a consistent causal treatment that may be able to avoid horizons and singularities. The master arrow that would combine all arrows of time does not have to be identified with a direction of the formal time parameter that serves to formulate the dynamics as a succession of global states (a trajectory in configuration or Hilbert space). It may even change direction with respect to a fundamental physical clock such as the cosmic expansion parameter if this was formally extended either into a future contraction era or to negative pre-big-bang values.

Structural response of a rotating bladed disk to rotor whirl

NASA Technical Reports Server (NTRS)

Crawley, E. F.

1985-01-01

A set of high speed rotating whirl experiments were performed in the vacuum of the MIT Blowdown Compressor Facility on the MIT Aeroelastic Rotor, which is structurally typical of a modern high bypass ratio turbofan stage. These tests identified the natural frequencies of whirl of the rotor system by forcing its response using an electromagnetic shaker whirl excitation system. The excitation was slowly swept in frequency at constant amplitude for several constant rotor speeds in both a forward and backward whirl direction. The natural frequencies of whirl determined by these experiments were compared to those predicted by an analytical 6 DOF model of a flexible blade-rigid disk-flexible shaft rotor. The model is also presented in terms of nondimensional parameters in order to assess the importance of the interation between the bladed disk dynamics and the shaft-disk dynamics. The correlation between the experimental and predicted natural frequencies is reasonable, given the uncertainty involved in determining the stiffness parameters of the system.

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

Clustering network layers with the strata multilayer stochastic block model.

PubMed

Stanley, Natalie; Shai, Saray; Taylor, Dane; Mucha, Peter J

2016-01-01

Multilayer networks are a useful data structure for simultaneously capturing multiple types of relationships between a set of nodes. In such networks, each relational definition gives rise to a layer. While each layer provides its own set of information, community structure across layers can be collectively utilized to discover and quantify underlying relational patterns between nodes. To concisely extract information from a multilayer network, we propose to identify and combine sets of layers with meaningful similarities in community structure. In this paper, we describe the "strata multilayer stochastic block model" (sMLSBM), a probabilistic model for multilayer community structure. The central extension of the model is that there exist groups of layers, called "strata", which are defined such that all layers in a given stratum have community structure described by a common stochastic block model (SBM). That is, layers in a stratum exhibit similar node-to-community assignments and SBM probability parameters. Fitting the sMLSBM to a multilayer network provides a joint clustering that yields node-to-community and layer-to-stratum assignments, which cooperatively aid one another during inference. We describe an algorithm for separating layers into their appropriate strata and an inference technique for estimating the SBM parameters for each stratum. We demonstrate our method using synthetic networks and a multilayer network inferred from data collected in the Human Microbiome Project.

Evaluating the Spatio-Temporal Factors that Structure Network Parameters of Plant-Herbivore Interactions

PubMed Central

López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor

2014-01-01

Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790

Effect of temperature and thermal history on borosilicate glass structure

NASA Astrophysics Data System (ADS)

Angeli, Frédéric; Villain, Olivier; Schuller, Sophie; Charpentier, Thibault; de Ligny, Dominique; Bressel, Lena; Wondraczek, Lothar

2012-02-01

The influence of the temperature and quenching rate on the structure of a borosilicate glass was studied by high-resolution solid-state 11B, 23Na, 29Si nuclear magnetic resonance (NMR) and high-temperature Raman spectroscopy. Data were obtained for glass in the solid state after annealing and quenching at cooling rates covering four orders of magnitude as well as in the liquid state from Raman experiments and from calorimetry and rheological data. Nuclear magnetic resonance measurements were used to calibrate the Raman spectra in order to quantify the change in boron coordination with temperature. This result can then be used to determine the fictive temperature of the glass directly from the boron coordination. The fictive temperature, heat capacity, and configurational entropy are extracted from calorimetry and viscosity measurements. Changes in the boron coordination account for only 25% of the configurational heat capacity of the liquid. The structural parameters capable of accounting for the remaining quantity are discussed on the basis of structural data, both local (inhomogeneity of the sodium distribution) and medium-range (from NMR parameter distribution). It has thus been shown that, although the B-O-B angular distributions of the boroxol rings (and probably the Si-O-Si distributions) are not affected by temperature, a structural disorder is identified through the angular distributions of the bonds linking borate and silicate groups.

Clustering network layers with the strata multilayer stochastic block model

PubMed Central

Stanley, Natalie; Shai, Saray; Taylor, Dane; Mucha, Peter J.

2016-01-01

Multilayer networks are a useful data structure for simultaneously capturing multiple types of relationships between a set of nodes. In such networks, each relational definition gives rise to a layer. While each layer provides its own set of information, community structure across layers can be collectively utilized to discover and quantify underlying relational patterns between nodes. To concisely extract information from a multilayer network, we propose to identify and combine sets of layers with meaningful similarities in community structure. In this paper, we describe the “strata multilayer stochastic block model” (sMLSBM), a probabilistic model for multilayer community structure. The central extension of the model is that there exist groups of layers, called “strata”, which are defined such that all layers in a given stratum have community structure described by a common stochastic block model (SBM). That is, layers in a stratum exhibit similar node-to-community assignments and SBM probability parameters. Fitting the sMLSBM to a multilayer network provides a joint clustering that yields node-to-community and layer-to-stratum assignments, which cooperatively aid one another during inference. We describe an algorithm for separating layers into their appropriate strata and an inference technique for estimating the SBM parameters for each stratum. We demonstrate our method using synthetic networks and a multilayer network inferred from data collected in the Human Microbiome Project. PMID:28435844

Self-assembled metal nano-multilayered film prepared by co-sputtering method

NASA Astrophysics Data System (ADS)

Xie, Tianle; Fu, Licai; Qin, Wen; Zhu, Jiajun; Yang, Wulin; Li, Deyi; Zhou, Lingping

2018-03-01

Nano-multilayered film is usually prepared by the arrangement deposition of different materials. In this paper, a self-assembled nano-multilayered film was deposited by simultaneous sputtering of Cu and W. The Cu/W nano-multilayered film was accumulated by W-rich layer and Cu-rich layer. Smooth interfaces with consecutive composition variation and semi-coherent even coherent relationship were identified, indicating that a spinodal-like structure with a modulation wavelength of about 20 nm formed during co-deposition process. The participation of diffusion barrier element, such as W, is believed the essential to obtain the nano-multilayered structure besides the technological parameters.

The structure of protostellar accretion disks and the origin of bipolar flows

NASA Technical Reports Server (NTRS)

Wardle, Mark; Koenigl, Arieh

1993-01-01

Equations are obtained which govern the disk-wind structure and identify the physical parameters relevant to circumstellar disks. The system of equations is analyzed in the thin-disk approximation, and it is shown that the system can be consistently reduced to a set of ordinary differential equations in z. Representative solutions are presented, and it is shown that the apparent paradox discussed by Shu (1991) is resolved when the finite thickness of the disk is taken into account. Implications of the results for the origin of bipolar flows in young stellar objects and possible application to active galactic nuclei are discussed.

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

Continuous-Flow MOVPE of Ga-Polar GaN Column Arrays and Core-Shell LED Structures

NASA Astrophysics Data System (ADS)

Wang, Xue; Li, Shunfeng; Mohajerani, Matin Sadat; Ledig, Johannes; Wehmann, Hergo-Heinrich; Mandl, Martin; Strassburg, Martin; Steegmüller, Ulrich; Jahn, Uwe; Lähnemann, Jonas; Riechert, Henning; Griffiths, Ian; Cherns, David; Waag, Andreas

2013-06-01

Arrays of dislocation free uniform Ga-polar GaN columns have been realized on patterned SiOx/GaN/sapphire templates by metal organic vapor phase epitaxy using a continuous growth mode. The key parameters and the physical principles of growth of Ga-polar GaN three-dimensional columns are identified, and their potential for manipulating the growth process is discussed. High aspect ratio columns have been achieved using silane during the growth, leading to n-type columns. The vertical growth rate increases with increasing silane flow. In a core-shell columnar LED structure, the shells of InGaN/GaN multi quantum wells and p-GaN have been realized on a core of n-doped GaN column. Cathodoluminescence gives insight into the inner structure of these core-shell LED structures.