Mid-frequency Band Dynamics of Large Space Structures

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.; Adams, Douglas S.

2004-01-01

High and low intensity dynamic environments experienced by a spacecraft during launch and on-orbit operations, respectively, induce structural loads and motions, which are difficult to reliably predict. Structural dynamics in low- and mid-frequency bands are sensitive to component interface uncertainty and non-linearity as evidenced in laboratory testing and flight operations. Analytical tools for prediction of linear system response are not necessarily adequate for reliable prediction of mid-frequency band dynamics and analysis of measured laboratory and flight data. A new MATLAB toolbox, designed to address the key challenges of mid-frequency band dynamics, is introduced in this paper. Finite-element models of major subassemblies are defined following rational frequency-wavelength guidelines. For computational efficiency, these subassemblies are described as linear, component mode models. The complete structural system model is composed of component mode subassemblies and linear or non-linear joint descriptions. Computation and display of structural dynamic responses are accomplished employing well-established, stable numerical methods, modern signal processing procedures and descriptive graphical tools. Parametric sensitivity and Monte-Carlo based system identification tools are used to reconcile models with experimental data and investigate the effects of uncertainties. Models and dynamic responses are exported for employment in applications, such as detailed structural integrity and mechanical-optical-control performance analyses.

Engineering Risk Assessment of Space Thruster Challenge Problem

NASA Technical Reports Server (NTRS)

Mathias, Donovan L.; Mattenberger, Christopher J.; Go, Susie

2014-01-01

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center utilizes dynamic models with linked physics-of-failure analyses to produce quantitative risk assessments of space exploration missions. This paper applies the ERA approach to the baseline and extended versions of the PSAM Space Thruster Challenge Problem, which investigates mission risk for a deep space ion propulsion system with time-varying thruster requirements and operations schedules. The dynamic mission is modeled using a combination of discrete and continuous-time reliability elements within the commercially available GoldSim software. Loss-of-mission (LOM) probability results are generated via Monte Carlo sampling performed by the integrated model. Model convergence studies are presented to illustrate the sensitivity of integrated LOM results to the number of Monte Carlo trials. A deterministic risk model was also built for the three baseline and extended missions using the Ames Reliability Tool (ART), and results are compared to the simulation results to evaluate the relative importance of mission dynamics. The ART model did a reasonable job of matching the simulation models for the baseline case, while a hybrid approach using offline dynamic models was required for the extended missions. This study highlighted that state-of-the-art techniques can adequately adapt to a range of dynamic problems.

Mapping the ecological networks of microbial communities.

PubMed

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K; Weiss, Scott T; Liu, Yang-Yu

2017-12-11

Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka-Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.

Evaluating reliability of WSN with sleep/wake-up interfering nodes

NASA Astrophysics Data System (ADS)

Distefano, Salvatore

2013-10-01

A wireless sensor network (WSN) (singular and plural of acronyms are spelled the same) is a distributed system composed of autonomous sensor nodes wireless connected and randomly scattered into a geographical area to cooperatively monitor physical or environmental conditions. Adequate techniques and strategies are required to manage a WSN so that it works properly, observing specific quantities and metrics to evaluate the WSN operational conditions. Among them, one of the most important is the reliability. Considering a WSN as a system composed of sensor nodes the system reliability approach can be applied, thus expressing the WSN reliability in terms of its nodes' reliability. More specifically, since often standby power management policies are applied at node level and interferences among nodes may arise, a WSN can be considered as a dynamic system. In this article we therefore consider the WSN reliability evaluation problem from the dynamic system reliability perspective. Static-structural interactions are specified by the WSN topology. Sleep/wake-up standby policies and interferences due to wireless communications can be instead considered as dynamic aspects. Thus, in order to represent and to evaluate the WSN reliability, we use dynamic reliability block diagrams and Petri nets. The proposed technique allows to overcome the limits of Markov models when considering non-linear discharge processes, since they cannot adequately represent the aging processes. In order to demonstrate the effectiveness of the technique, we investigate some specific WSN network topologies, providing guidelines for their representation and evaluation.

A Research Roadmap for Computation-Based Human Reliability Analysis

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

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is oftenmore » secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.« less

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

NASA Astrophysics Data System (ADS)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

Life and reliability modeling of bevel gear reductions

NASA Technical Reports Server (NTRS)

Savage, M.; Brikmanis, C. K.; Lewicki, D. G.; Coy, J. J.

1985-01-01

A reliability model is presented for bevel gear reductions with either a single input pinion or dual input pinions of equal size. The dual pinions may or may not have the same power applied for the analysis. The gears may be straddle mounted or supported in a bearing quill. The reliability model is based on the Weibull distribution. The reduction's basic dynamic capacity is defined as the output torque which may be applied for one million output rotations of the bevel gear with a 90 percent probability of reduction survival.

Reliability and Correlation of Static and Dynamic Foot Arch Measurement in a Healthy Pediatric Population.

PubMed

Scholz, Timo; Zech, Astrid; Wegscheider, Karl; Lezius, Susanne; Braumann, Klaus-Michael; Sehner, Susanne; Hollander, Karsten

2017-09-01

Measurement of the medial longitudinal foot arch in children is a controversial topic, as there are many different methods without a definite standard procedure. The purpose of this study was to 1) investigate intraday and interrater reliability regarding dynamic arch index and static arch height, 2) explore the correlation between both arch indices, and 3) examine the variation of the medial longitudinal arch at two different times of the day. Eighty-six children (mean ± SD age, 8.9 ± 1.9 years) participated in the study. Dynamic footprint data were captured with a pedobarographic platform. For static arch measurements, a specially constructed caliper was used to assess heel-to-toe length and dorsum height. A mixed model was established to determine reliability and variation. Reliability was found to be excellent for the static arch height index in sitting (intraday, 0.90; interrater, 0.80) and standing positions (0.88 and 0.85) and for the dynamic arch index (both 1.00). There was poor correlation between static and dynamic assessment of the medial longitudinal arch (standing dynamic arch index, r = -0.138; sitting dynamic arch index, r = -0.070). Static measurements were found to be significantly influenced by the time of day (P < .001), whereas the dynamic arch index was unchanged (P = .845). This study revealed some further important findings. The static arch height index is influenced by gender (P = .004), whereas dynamic arch index is influenced by side (P = .011) and body mass index (P < .001). Dynamic and static foot measurements are reliable for medial longitudinal foot arch assessment in children. The variation of static arch measurements during the day has to be kept in mind. For clinical purposes, static and dynamic arch data should be interpreted separately.

Spatially explicit dynamic N-mixture models

USGS Publications Warehouse

Zhao, Qing; Royle, Andy; Boomer, G. Scott

2017-01-01

Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.

Tracking reliability for space cabin-borne equipment in development by Crow model.

PubMed

Chen, J D; Jiao, S J; Sun, H L

2001-12-01

Objective. To study and track the reliability growth of manned spaceflight cabin-borne equipment in the course of its development. Method. A new technique of reliability growth estimation and prediction, which is composed of the Crow model and test data conversion (TDC) method was used. Result. The estimation and prediction value of the reliability growth conformed to its expectations. Conclusion. The method could dynamically estimate and predict the reliability of the equipment by making full use of various test information in the course of its development. It offered not only a possibility of tracking the equipment reliability growth, but also the reference for quality control in manned spaceflight cabin-borne equipment design and development process.

A fuzzy set approach for reliability calculation of valve controlling electric actuators

NASA Astrophysics Data System (ADS)

Karmachev, D. P.; Yefremov, A. A.; Luneva, E. E.

2017-02-01

The oil and gas equipment and electric actuators in particular frequently perform in various operational modes and under dynamic environmental conditions. These factors affect equipment reliability measures in a vague, uncertain way. To eliminate the ambiguity, reliability model parameters could be defined as fuzzy numbers. We suggest a technique that allows constructing fundamental fuzzy-valued performance reliability measures based on an analysis of electric actuators failure data in accordance with the amount of work, completed before the failure, instead of failure time. Also, this paper provides a computation example of fuzzy-valued reliability and hazard rate functions, assuming Kumaraswamy complementary Weibull geometric distribution as a lifetime (reliability) model for electric actuators.

An approximation formula for a class of fault-tolerant computers

NASA Technical Reports Server (NTRS)

White, A. L.

1986-01-01

An approximation formula is derived for the probability of failure for fault-tolerant process-control computers. These computers use redundancy and reconfiguration to achieve high reliability. Finite-state Markov models capture the dynamic behavior of component failure and system recovery, and the approximation formula permits an estimation of system reliability by an easy examination of the model.

Noise Propagation and Uncertainty Quantification in Hybrid Multiphysics Models: Initiation and Reaction Propagation in Energetic Materials

DTIC Science & Technology

2016-05-23

general model for heterogeneous granular media under compaction and (ii) the lack of a reliable multiscale discrete -to-continuum framework for...dynamics. These include a continuum- discrete model of heat dissipation/diffusion and a continuum- discrete model of compaction of a granular material with...the lack of a general model for het- erogeneous granular media under compac- tion and (ii) the lack of a reliable multi- scale discrete -to-continuum

When the Jeans Do Not Fit: How Stellar Feedback Drives Stellar Kinematics and Complicates Dynamical Modeling in Low-mass Galaxies

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

El-Badry, Kareem; Quataert, Eliot; Wetzel, Andrew R.

In low-mass galaxies, stellar feedback can drive gas outflows that generate non-equilibrium fluctuations in the gravitational potential. Using cosmological zoom-in baryonic simulations from the Feedback in Realistic Environments project, we investigate how these fluctuations affect stellar kinematics and the reliability of Jeans dynamical modeling in low-mass galaxies. We find that stellar velocity dispersion and anisotropy profiles fluctuate significantly over the course of galaxies’ starburst cycles. We therefore predict an observable correlation between star formation rate and stellar kinematics: dwarf galaxies with higher recent star formation rates should have systemically higher stellar velocity dispersions. This prediction provides an observational test ofmore » the role of stellar feedback in regulating both stellar and dark-matter densities in dwarf galaxies. We find that Jeans modeling, which treats galaxies as virialized systems in dynamical equilibrium, overestimates a galaxy’s dynamical mass during periods of post-starburst gas outflow and underestimates it during periods of net inflow. Short-timescale potential fluctuations lead to typical errors of ∼20% in dynamical mass estimates, even if full three-dimensional stellar kinematics—including the orbital anisotropy—are known exactly. When orbital anisotropy is not known a priori, typical mass errors arising from non-equilibrium fluctuations in the potential are larger than those arising from the mass-anisotropy degeneracy. However, Jeans modeling alone cannot reliably constrain the orbital anisotropy, and problematically, it often favors anisotropy models that do not reflect the true profile. If galaxies completely lose their gas and cease forming stars, fluctuations in the potential subside, and Jeans modeling becomes much more reliable.« less

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

Model-Based Heterogeneous Data Fusion for Reliable Force Estimation in Dynamic Structures under Uncertainties

PubMed Central

Khodabandeloo, Babak; Melvin, Dyan; Jo, Hongki

2017-01-01

Direct measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well. PMID:29149088

Dynamics of aesthetic appreciation

NASA Astrophysics Data System (ADS)

Carbon, Claus-Christian

2012-03-01

Aesthetic appreciation is a complex cognitive processing with inherent aspects of cold as well as hot cognition. Research from the last decades of empirical has shown that evaluations of aesthetic appreciation are highly reliable. Most frequently, facial attractiveness was used as the corner case for investigating aesthetic appreciation. Evaluating facial attractiveness shows indeed high internal consistencies and impressively high inter-rater reliabilities, even across cultures. Although this indicates general and stable mechanisms underlying aesthetic appreciation, it is also obvious that our taste for specific objects changes dynamically. Aesthetic appreciation on artificial object categories, such as fashion, design or art is inherently very dynamic. Gaining insights into the cognitive mechanisms that trigger and enable corresponding changes of aesthetic appreciation is of particular interest for research as this will provide possibilities to modeling aesthetic appreciation for longer durations and from a dynamic perspective. The present paper refers to a recent two-step model ("the dynamical two-step-model of aesthetic appreciation"), dynamically adapting itself, which accounts for typical dynamics of aesthetic appreciation found in different research areas such as art history, philosophy and psychology. The first step assumes singular creative sources creating and establishing innovative material towards which, in a second step, people adapt by integrating it into their visual habits. This inherently leads to dynamic changes of the beholders' aesthetic appreciation.

Tutorial: Advanced fault tree applications using HARP

NASA Technical Reports Server (NTRS)

Dugan, Joanne Bechta; Bavuso, Salvatore J.; Boyd, Mark A.

1993-01-01

Reliability analysis of fault tolerant computer systems for critical applications is complicated by several factors. These modeling difficulties are discussed and dynamic fault tree modeling techniques for handling them are described and demonstrated. Several advanced fault tolerant computer systems are described, and fault tree models for their analysis are presented. HARP (Hybrid Automated Reliability Predictor) is a software package developed at Duke University and NASA Langley Research Center that is capable of solving the fault tree models presented.

Reliability and Construct Validity of Limits of Stability Test in Adolescents Using a Portable Forceplate System.

PubMed

Alsalaheen, Bara; Haines, Jamie; Yorke, Amy; Broglio, Steven P

2015-12-01

To examine the reliability, convergent, and discriminant validity of the limits of stability (LOS) test to assess dynamic postural stability in adolescents using a portable forceplate system. Cross-sectional reliability observational study. School setting. Adolescents (N=36) completed all measures during the first session. To examine the reliability of the LOS test, a subset of 15 participants repeated the LOS test after 1 week. Not applicable. Outcome measurements included the LOS test, Balance Error Scoring System, Instrumented Balance Error Scoring System, and Modified Clinical Test for Sensory Interaction on Balance. A significant relation was observed among LOS composite scores (r=.36-.87, P<.05). However, no relation was observed between LOS and static balance outcome measurements. The reliability of the LOS composite scores ranged from moderate to good (intraclass correlation coefficient model 2,1=.73-.96). The results suggest that the LOS composite scores provide unique information about dynamic postural stability, and the LOS test completed at 100% of the theoretical limit appeared to be a reliable test of dynamic postural stability in adolescents. Clinicians should use dynamic balance measurement as part of their balance assessment and should not use static balance testing (eg, Balance Error Scoring System) to make inferences about dynamic balance, especially when balance assessment is used to determine rehabilitation outcomes, or when making return to play decisions after injury. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Distributed collaborative response surface method for mechanical dynamic assembly reliability design

NASA Astrophysics Data System (ADS)

Bai, Guangchen; Fei, Chengwei

2013-11-01

Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40˜4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.

Diminished neural network dynamics after moderate and severe traumatic brain injury.

PubMed

Gilbert, Nicholas; Bernier, Rachel A; Calhoun, Vincent D; Brenner, Einat; Grossner, Emily; Rajtmajer, Sarah M; Hillary, Frank G

2018-01-01

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain's subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network "states" that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics.

Diminished neural network dynamics after moderate and severe traumatic brain injury

PubMed Central

Gilbert, Nicholas; Bernier, Rachel A.; Calhoun, Vincent D.; Brenner, Einat; Grossner, Emily; Rajtmajer, Sarah M.

2018-01-01

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain’s subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network “states” that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics. PMID:29883447

Models of determining deformations

NASA Astrophysics Data System (ADS)

Gladilin, V. N.

2016-12-01

In recent years, a lot of functions designed to determine deformation values that occur mostly as a result of settlement of structures and industrial equipment. Some authors suggest such advanced mathematical functions approximating deformations as general methods for the determination of deformations. The article describes models of deformations as physical processes. When comparing static, cinematic and dynamic models, it was found that the dynamic model reflects the deformation of structures and industrial equipment most reliably.

Life and reliability models for helicopter transmissions

NASA Technical Reports Server (NTRS)

Savage, M.; Knorr, R. J.; Coy, J. J.

1982-01-01

Computer models of life and reliability are presented for planetary gear trains with a fixed ring gear, input applied to the sun gear, and output taken from the planet arm. For this transmission the input and output shafts are co-axial and the input and output torques are assumed to be coaxial with these shafts. Thrust and side loading are neglected. The reliability model is based on the Weibull distributions of the individual reliabilities of the in transmission components. The system model is also a Weibull distribution. The load versus life model for the system is a power relationship as the models for the individual components. The load-life exponent and basic dynamic capacity are developed as functions of the components capacities. The models are used to compare three and four planet, 150 kW (200 hp), 5:1 reduction transmissions with 1500 rpm input speed to illustrate their use.

Model-free inference of direct network interactions from nonlinear collective dynamics.

PubMed

Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

2017-12-19

The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

A reliability design method for a lithium-ion battery pack considering the thermal disequilibrium in electric vehicles

NASA Astrophysics Data System (ADS)

Xia, Quan; Wang, Zili; Ren, Yi; Sun, Bo; Yang, Dezhen; Feng, Qiang

2018-05-01

With the rapid development of lithium-ion battery technology in the electric vehicle (EV) industry, the lifetime of the battery cell increases substantially; however, the reliability of the battery pack is still inadequate. Because of the complexity of the battery pack, a reliability design method for a lithium-ion battery pack considering the thermal disequilibrium is proposed in this paper based on cell redundancy. Based on this method, a three-dimensional electric-thermal-flow-coupled model, a stochastic degradation model of cells under field dynamic conditions and a multi-state system reliability model of a battery pack are established. The relationships between the multi-physics coupling model, the degradation model and the system reliability model are first constructed to analyze the reliability of the battery pack and followed by analysis examples with different redundancy strategies. By comparing the reliability of battery packs of different redundant cell numbers and configurations, several conclusions for the redundancy strategy are obtained. More notably, the reliability does not monotonically increase with the number of redundant cells for the thermal disequilibrium effects. In this work, the reliability of a 6 × 5 parallel-series configuration is the optimal system structure. In addition, the effect of the cell arrangement and cooling conditions are investigated.

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

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

Boring, Ronald; Mandelli, Diego; Rasmussen, Martin

2016-06-01

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: •more » Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.« less

76 FR 66220 - Automatic Underfrequency Load Shedding and Load Shedding Plans Reliability Standards

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

..., EPRI Power Systems Dynamics Tutorial, Chapter 4 at page 4-78 (2009), available at http://www.epri.com.... Power systems consist of static components (e.g., transformers and transmission lines) and dynamic... decisions on simulations, both static and dynamic, using area power system models to meet requirements in...

[A reliability growth assessment method and its application in the development of equipment in space cabin].

PubMed

Chen, J D; Sun, H L

1999-04-01

Objective. To assess and predict reliability of an equipment dynamically by making full use of various test informations in the development of products. Method. A new reliability growth assessment method based on army material system analysis activity (AMSAA) model was developed. The method is composed of the AMSAA model and test data conversion technology. Result. The assessment and prediction results of a space-borne equipment conform to its expectations. Conclusion. It is suggested that this method should be further researched and popularized.

Analysis of Food Hub Commerce and Participation Using Agent-Based Modeling: Integrating Financial and Social Drivers.

PubMed

Krejci, Caroline C; Stone, Richard T; Dorneich, Michael C; Gilbert, Stephen B

2016-02-01

Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants. Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models. Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability. The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base. Results suggest that social factors, such as desire to support the community, can be more important than financial factors. An ABM of food hub dynamics, based on human factors data gathered from the field, can be a useful tool for policy decisions. Similar approaches can be used for modeling customer dynamics with other sustainable organizations. © 2015, Human Factors and Ergonomics Society.

On reliable control system designs. Ph.D. Thesis; [actuators

NASA Technical Reports Server (NTRS)

Birdwell, J. D.

1978-01-01

A mathematical model for use in the design of reliable multivariable control systems is discussed with special emphasis on actuator failures and necessary actuator redundancy levels. The model consists of a linear time invariant discrete time dynamical system. Configuration changes in the system dynamics are governed by a Markov chain that includes transition probabilities from one configuration state to another. The performance index is a standard quadratic cost functional, over an infinite time interval. The actual system configuration can be deduced with a one step delay. The calculation of the optimal control law requires the solution of a set of highly coupled Riccati-like matrix difference equations. Results can be used for off-line studies relating the open loop dynamics, required performance, actuator mean time to failure, and functional or identical actuator redundancy, with and without feedback gain reconfiguration strategies.

Dynamic analysis of space structures including elastic, multibody, and control behavior

NASA Technical Reports Server (NTRS)

Pinson, Larry; Soosaar, Keto

1989-01-01

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

Estimation of reliability and dynamic property for polymeric material at high strain rate using SHPB technique and probability theory

NASA Astrophysics Data System (ADS)

Kim, Dong Hyeok; Lee, Ouk Sub; Kim, Hong Min; Choi, Hye Bin

2008-11-01

A modified Split Hopkinson Pressure Bar technique with aluminum pressure bars and a pulse shaper technique to achieve a closer impedance match between the pressure bars and the specimen materials such as hot temperature degraded POM (Poly Oxy Methylene) and PP (Poly Propylene). The more distinguishable experimental signals were obtained to evaluate the more accurate dynamic deformation behavior of materials under a high strain rate loading condition. A pulse shaping technique is introduced to reduce the non-equilibrium on the dynamic material response by modulation of the incident wave during a short period of test. This increases the rise time of the incident pulse in the SHPB experiment. For the dynamic stress strain curve obtained from SHPB experiment, the Johnson-Cook model is applied as a constitutive equation. The applicability of this constitutive equation is verified by using the probabilistic reliability estimation method. Two reliability methodologies such as the FORM and the SORM have been proposed. The limit state function(LSF) includes the Johnson-Cook model and applied stresses. The LSF in this study allows more statistical flexibility on the yield stress than a paper published before. It is found that the failure probability estimated by using the SORM is more reliable than those of the FORM/ It is also noted that the failure probability increases with increase of the applied stress. Moreover, it is also found that the parameters of Johnson-Cook model such as A and n, and the applied stress are found to affect the failure probability more severely than the other random variables according to the sensitivity analysis.

Efficient finite element modelling for the investigation of the dynamic behaviour of a structure with bolted joints

NASA Astrophysics Data System (ADS)

Omar, R.; Rani, M. N. Abdul; Yunus, M. A.; Mirza, W. I. I. Wan Iskandar; Zin, M. S. Mohd

2018-04-01

A simple structure with bolted joints consists of the structural components, bolts and nuts. There are several methods to model the structures with bolted joints, however there is no reliable, efficient and economic modelling methods that can accurately predict its dynamics behaviour. Explained in this paper is an investigation that was conducted to obtain an appropriate modelling method for bolted joints. This was carried out by evaluating four different finite element (FE) models of the assembled plates and bolts namely the solid plates-bolts model, plates without bolt model, hybrid plates-bolts model and simplified plates-bolts model. FE modal analysis was conducted for all four initial FE models of the bolted joints. Results of the FE modal analysis were compared with the experimental modal analysis (EMA) results. EMA was performed to extract the natural frequencies and mode shapes of the test physical structure with bolted joints. Evaluation was made by comparing the number of nodes, number of elements, elapsed computer processing unit (CPU) time, and the total percentage of errors of each initial FE model when compared with EMA result. The evaluation showed that the simplified plates-bolts model could most accurately predict the dynamic behaviour of the structure with bolted joints. This study proved that the reliable, efficient and economic modelling of bolted joints, mainly the representation of the bolting, has played a crucial element in ensuring the accuracy of the dynamic behaviour prediction.

Large eddy simulation of spanwise rotating turbulent channel flow with dynamic variants of eddy viscosity model

NASA Astrophysics Data System (ADS)

Jiang, Zhou; Xia, Zhenhua; Shi, Yipeng; Chen, Shiyi

2018-04-01

A fully developed spanwise rotating turbulent channel flow has been numerically investigated utilizing large-eddy simulation. Our focus is to assess the performances of the dynamic variants of eddy viscosity models, including dynamic Vreman's model (DVM), dynamic wall adapting local eddy viscosity (DWALE) model, dynamic σ (Dσ ) model, and the dynamic volumetric strain-stretching (DVSS) model, in this canonical flow. The results with dynamic Smagorinsky model (DSM) and direct numerical simulations (DNS) are used as references. Our results show that the DVM has a wrong asymptotic behavior in the near wall region, while the other three models can correctly predict it. In the high rotation case, the DWALE can get reliable mean velocity profile, but the turbulence intensities in the wall-normal and spanwise directions show clear deviations from DNS data. DVSS exhibits poor predictions on both the mean velocity profile and turbulence intensities. In all three cases, Dσ performs the best.

Reimplementation of the Biome-BGC model to simulate successional change.

PubMed

Bond-Lamberty, Ben; Gower, Stith T; Ahl, Douglas E; Thornton, Peter E

2005-04-01

Biogeochemical process models are increasingly employed to simulate current and future forest dynamics, but most simulate only a single canopy type. This limitation means that mixed stands, canopy succession and understory dynamics cannot be modeled, severe handicaps in many forests. The goals of this study were to develop a version of Biome-BGC that supported multiple, interacting vegetation types, and to assess its performance and limitations by comparing modeled results to published data from a 150-year boreal black spruce (Picea mariana (Mill.) BSP) chronosequence in northern Manitoba, Canada. Model data structures and logic were modified to support an arbitrary number of interacting vegetation types; an explicit height calculation was necessary to prioritize radiation and precipitation interception. Two vegetation types, evergreen needle-leaf and deciduous broadleaf, were modeled based on site-specific meteorological and physiological data. The new version of Biome-BGC reliably simulated observed changes in leaf area, net primary production and carbon stocks, and should be useful for modeling the dynamics of mixed-species stands and ecological succession. We discuss the strengths and limitations of Biome-BGC for this application, and note areas in which further work is necessary for reliable simulation of boreal biogeochemical cycling at a landscape scale.

Yi Guo | NREL

Science.gov Websites

Yi is dedicated to research and development in dynamic modeling, reliability analysis, vibro systems and has published numerous impactful journal publications. Prior to NREL, she pursued her Ph.D . research at Ohio State University with specialization in dynamics, vibration, and acoustics of wind turbine

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

NASA Astrophysics Data System (ADS)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

On the use and the performance of software reliability growth models

NASA Technical Reports Server (NTRS)

Keiller, Peter A.; Miller, Douglas R.

1991-01-01

We address the problem of predicting future failures for a piece of software. The number of failures occurring during a finite future time interval is predicted from the number failures observed during an initial period of usage by using software reliability growth models. Two different methods for using the models are considered: straightforward use of individual models, and dynamic selection among models based on goodness-of-fit and quality-of-prediction criteria. Performance is judged by the relative error of the predicted number of failures over future finite time intervals relative to the number of failures eventually observed during the intervals. Six of the former models and eight of the latter are evaluated, based on their performance on twenty data sets. Many open questions remain regarding the use and the performance of software reliability growth models.

Use of measurement theory for operationalization and quantification of psychological constructs in systems dynamics modelling

NASA Astrophysics Data System (ADS)

Fitkov-Norris, Elena; Yeghiazarian, Ara

2016-11-01

The analytical tools available to social scientists have traditionally been adapted from tools originally designed for analysis of natural science phenomena. This article discusses the applicability of systems dynamics - a qualitative based modelling approach, as a possible analysis and simulation tool that bridges the gap between social and natural sciences. After a brief overview of the systems dynamics modelling methodology, the advantages as well as limiting factors of systems dynamics to the potential applications in the field of social sciences and human interactions are discussed. The issues arise with regards to operationalization and quantification of latent constructs at the simulation building stage of the systems dynamics methodology and measurement theory is proposed as a ready and waiting solution to the problem of dynamic model calibration, with a view of improving simulation model reliability and validity and encouraging the development of standardised, modular system dynamics models that can be used in social science research.

Model of ballistic targets' dynamics used for trajectory tracking algorithms

NASA Astrophysics Data System (ADS)

Okoń-FÄ fara, Marta; Kawalec, Adam; Witczak, Andrzej

2017-04-01

There are known only few ballistic object tracking algorithms. To develop such algorithms and to its further testing, it is necessary to implement possibly simple and reliable objects' dynamics model. The article presents the dynamics' model of a tactical ballistic missile (TBM) including the three stages of flight: the boost stage and two passive stages - the ascending one and the descending one. Additionally, the procedure of transformation from the local coordinate system to the polar-radar oriented and the global is presented. The prepared theoretical data may be used to determine the tracking algorithm parameters and to its further verification.

Modeling of human operator dynamics in simple manual control utilizing time series analysis. [tracking (position)

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Osafo-Charles, F.; Oneill, W. D.; Gottlieb, G. L.

1982-01-01

Time series analysis is applied to model human operator dynamics in pursuit and compensatory tracking modes. The normalized residual criterion is used as a one-step analytical tool to encompass the processes of identification, estimation, and diagnostic checking. A parameter constraining technique is introduced to develop more reliable models of human operator dynamics. The human operator is adequately modeled by a second order dynamic system both in pursuit and compensatory tracking modes. In comparing the data sampling rates, 100 msec between samples is adequate and is shown to provide better results than 200 msec sampling. The residual power spectrum and eigenvalue analysis show that the human operator is not a generator of periodic characteristics.

Synthesizing cognition in neuromorphic electronic systems

PubMed Central

Neftci, Emre; Binas, Jonathan; Rutishauser, Ueli; Chicca, Elisabetta; Indiveri, Giacomo; Douglas, Rodney J.

2013-01-01

The quest to implement intelligent processing in electronic neuromorphic systems lacks methods for achieving reliable behavioral dynamics on substrates of inherently imprecise and noisy neurons. Here we report a solution to this problem that involves first mapping an unreliable hardware layer of spiking silicon neurons into an abstract computational layer composed of generic reliable subnetworks of model neurons and then composing the target behavioral dynamics as a “soft state machine” running on these reliable subnets. In the first step, the neural networks of the abstract layer are realized on the hardware substrate by mapping the neuron circuit bias voltages to the model parameters. This mapping is obtained by an automatic method in which the electronic circuit biases are calibrated against the model parameters by a series of population activity measurements. The abstract computational layer is formed by configuring neural networks as generic soft winner-take-all subnetworks that provide reliable processing by virtue of their active gain, signal restoration, and multistability. The necessary states and transitions of the desired high-level behavior are then easily embedded in the computational layer by introducing only sparse connections between some neurons of the various subnets. We demonstrate this synthesis method for a neuromorphic sensory agent that performs real-time context-dependent classification of motion patterns observed by a silicon retina. PMID:23878215

EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks

PubMed Central

Courellis, Hristos; Mullen, Tim; Poizner, Howard; Cauwenberghs, Gert; Iversen, John R.

2017-01-01

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a “reach/saccade to spatial target” cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI. PMID:28566997

Modeling water, carbon, and nitrogen dynamics for two drained pine plantations under intensive management practices

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra Amatya; George M. Chescheir

2012-01-01

This paper reports results of a study to test the reliability of the DRAINMOD-FOREST model for predicting water, soil carbon (C) and nitrogen (N) dynamics in intensively managed forests. The study site, two adjacent loblolly pine (Pinus taeda L.) plantations (referred as D2 and D3), are located in the coastal plain of North Carolina, USA. Controlled drainage (with weir...

Data-driven modelling of vertical dynamic excitation of bridges induced by people running

NASA Astrophysics Data System (ADS)

Racic, Vitomir; Morin, Jean Benoit

2014-02-01

With increasingly popular marathon events in urban environments, structural designers face a great deal of uncertainty when assessing dynamic performance of bridges occupied and dynamically excited by people running. While the dynamic loads induced by pedestrians walking have been intensively studied since the infamous lateral sway of the London Millennium Bridge in 2000, reliable and practical descriptions of running excitation are still very rare and limited. This interdisciplinary study has addressed the issue by bringing together a database of individual running force signals recorded by two state-of-the-art instrumented treadmills and two attempts to mathematically describe the measurements. The first modelling strategy is adopted from the available design guidelines for human walking excitation of structures, featuring perfectly periodic and deterministic characterisation of pedestrian forces presentable via Fourier series. This modelling approach proved to be inadequate for running loads due to the inherent near-periodic nature of the measured signals, a great inter-personal randomness of the dominant Fourier amplitudes and the lack of strong correlation between the amplitudes and running footfall rate. Hence, utilising the database established and motivated by the existing models of wind and earthquake loading, speech recognition techniques and a method of replicating electrocardiogram signals, this paper finally presents a numerical generator of random near-periodic running force signals which can reliably simulate the measurements. Such a model is an essential prerequisite for future quality models of dynamic loading induced by individuals, groups and crowds running under a wide range of conditions, such as perceptibly vibrating bridges and different combinations of visual, auditory and tactile cues.

Software development predictors, error analysis, reliability models and software metric analysis

NASA Technical Reports Server (NTRS)

Basili, Victor

1983-01-01

The use of dynamic characteristics as predictors for software development was studied. It was found that there are some significant factors that could be useful as predictors. From a study on software errors and complexity, it was shown that meaningful results can be obtained which allow insight into software traits and the environment in which it is developed. Reliability models were studied. The research included the field of program testing because the validity of some reliability models depends on the answers to some unanswered questions about testing. In studying software metrics, data collected from seven software engineering laboratory (FORTRAN) projects were examined and three effort reporting accuracy checks were applied to demonstrate the need to validate a data base. Results are discussed.

Seals Research at AlliedSignal

NASA Technical Reports Server (NTRS)

Ullah, M. Rifat

1996-01-01

A consortium has been formed to address seal problems in the Aerospace sector of Allied Signal, Inc. The consortium is represented by makers of Propulsion Engines, Auxiliary Power Units, Gas Turbine Starters, etc. The goal is to improve Face Seal reliability, since Face Seals have become reliability drivers in many of our product lines. Several research programs are being implemented simultaneously this year. They include: Face Seal Modeling and Analysis Methodology; Oil Cooling of Seals; Seal Tracking Dynamics; Coking Formation & Prevention; and Seal Reliability Methods.

Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

NASA Technical Reports Server (NTRS)

White, Allan L.; Palumbo, Daniel L.

1991-01-01

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

Reliability Analysis of the Space Station Freedom Electrical Power System

DTIC Science & Technology

1989-08-01

Cleveland, Ohio, who assisted in obtaining related research materials and provided feedback on our efforts to produce a dynamic analysis tool useful to...System software that we used to do our analysis of the electrical power system. Thanks are due to Dr. Vira Chankong, my thesis advisor, for his...a frequency duration analysis . Using a transition rate matrix with a model of the photovoltaic and solar dynamic systems, they have one model that

TRIP-ID: A tool for a smart and interactive identification of Magic Formula tyre model parameters from experimental data acquired on track or test rig

NASA Astrophysics Data System (ADS)

Farroni, Flavio; Lamberti, Raffaele; Mancinelli, Nicolò; Timpone, Francesco

2018-03-01

Tyres play a key role in ground vehicles' dynamics because they are responsible for traction, braking and cornering. A proper tyre-road interaction model is essential for a useful and reliable vehicle dynamics model. In the last two decades Pacejka's Magic Formula (MF) has become a standard in simulation field. This paper presents a Tool, called TRIP-ID (Tyre Road Interaction Parameters IDentification), developed to characterize and to identify with a high grade of accuracy and reliability MF micro-parameters from experimental data deriving from telemetry or from test rig. The tool guides interactively the user through the identification process on the basis of strong diagnostic considerations about the experimental data made evident by the tool itself. A motorsport application of the tool is shown as a case study.

Investigations of FAK inhibitors: a combination of 3D-QSAR, docking, and molecular dynamics simulations studies.

PubMed

Cheng, Peng; Li, Jiaojiao; Wang, Juan; Zhang, Xiaoyun; Zhai, Honglin

2018-05-01

Focal adhesion kinase (FAK) is one kind of tyrosine kinases that modulates integrin and growth factor signaling pathways, which is a promising therapeutic target because of involving in cancer cell migration, proliferation, and survival. To investigate the mechanism between FAK and triazinic inhibitors and design high activity inhibitors, a molecular modeling integrated with 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy calculations was performed. The optimum CoMFA and CoMSIA models showed good reliability and satisfactory predictability (with Q 2  = 0.663, R 2  = 0.987, [Formula: see text] = 0.921 and Q 2  = 0.670, R 2  = 0.981, [Formula: see text] = 0.953). Its contour maps could provide structural features to improve inhibitory activity. Furthermore, a good consistency between contour maps, docking, and molecular dynamics simulations strongly demonstrates that the molecular modeling is reliable. Based on it, we designed several new compounds and their inhibitory activities were validated by the molecular models. We expect our studies could bring new ideas to promote the development of novel inhibitors with higher inhibitory activity for FAK.

Dynamic Loading of Substation Distribution Transformers: An Application for use in a Production Grade Environment

NASA Astrophysics Data System (ADS)

Zhang, Ming

Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can be achieved through the use of dynamic loading. A benefit of dynamic loading is that it allows better utilization of the transformer capacity, thus increasing the flexibility and reliability of the power system. This document presents the progress on a software application which can estimate the maximum time-varying loading capability of transformers. This information can be used to load devices closer to their limits without exceeding the manufacturer specified operating limits. The maximally efficient dynamic loading of transformers requires a model that can accurately predict both top-oil temperatures (TOTs) and hottest-spot temperatures (HSTs). In the previous work, two kinds of thermal TOT and HST models have been studied and used in the application: the IEEE TOT/HST models and the ASU TOT/HST models. And, several metrics have been applied to evaluate the model acceptability and determine the most appropriate models for using in the dynamic loading calculations. In this work, an investigation to improve the existing transformer thermal models performance is presented. Some factors that may affect the model performance such as improper fan status and the error caused by the poor performance of IEEE models are discussed. Additional methods to determine the reliability of transformer thermal models using metrics such as time constant and the model parameters are also provided. A new production grade application for real-time dynamic loading operating purpose is introduced. This application is developed by using an existing planning application, TTeMP, as a start point, which is designed for the dispatchers and load specialists. To overcome the limitations of TTeMP, the new application can perform dynamic loading under emergency conditions, such as loss-of transformer loading. It also has the capability to determine the emergency rating of the transformers for a real-time estimation.

Calibration and combination of dynamical seasonal forecasts to enhance the value of predicted probabilities for managing risk

NASA Astrophysics Data System (ADS)

Dutton, John A.; James, Richard P.; Ross, Jeremy D.

2013-06-01

Seasonal probability forecasts produced with numerical dynamics on supercomputers offer great potential value in managing risk and opportunity created by seasonal variability. The skill and reliability of contemporary forecast systems can be increased by calibration methods that use the historical performance of the forecast system to improve the ongoing real-time forecasts. Two calibration methods are applied to seasonal surface temperature forecasts of the US National Weather Service, the European Centre for Medium Range Weather Forecasts, and to a World Climate Service multi-model ensemble created by combining those two forecasts with Bayesian methods. As expected, the multi-model is somewhat more skillful and more reliable than the original models taken alone. The potential value of the multimodel in decision making is illustrated with the profits achieved in simulated trading of a weather derivative. In addition to examining the seasonal models, the article demonstrates that calibrated probability forecasts of weekly average temperatures for leads of 2-4 weeks are also skillful and reliable. The conversion of ensemble forecasts into probability distributions of impact variables is illustrated with degree days derived from the temperature forecasts. Some issues related to loss of stationarity owing to long-term warming are considered. The main conclusion of the article is that properly calibrated probabilistic forecasts possess sufficient skill and reliability to contribute to effective decisions in government and business activities that are sensitive to intraseasonal and seasonal climate variability.

Why preferring parametric forecasting to nonparametric methods?

PubMed

Jabot, Franck

2015-05-07

A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Daniel Laird | NREL

Science.gov Websites

the high-fidelity modeling, wind plant controls, and rotor dynamics focus areas. Prior to joining NREL , composite materials, and blade reliability. Education M.S. and Ph.D. in Mechanical Engineering, University

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

PubMed Central

2009-01-01

Background Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition. Results For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models. Conclusion We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models. PMID:19903354

A computational framework for prime implicants identification in noncoherent dynamic systems.

PubMed

Di Maio, Francesco; Baronchelli, Samuele; Zio, Enrico

2015-01-01

Dynamic reliability methods aim at complementing the capability of traditional static approaches (e.g., event trees [ETs] and fault trees [FTs]) by accounting for the system dynamic behavior and its interactions with the system state transition process. For this, the system dynamics is here described by a time-dependent model that includes the dependencies with the stochastic transition events. In this article, we present a novel computational framework for dynamic reliability analysis whose objectives are i) accounting for discrete stochastic transition events and ii) identifying the prime implicants (PIs) of the dynamic system. The framework entails adopting a multiple-valued logic (MVL) to consider stochastic transitions at discretized times. Then, PIs are originally identified by a differential evolution (DE) algorithm that looks for the optimal MVL solution of a covering problem formulated for MVL accident scenarios. For testing the feasibility of the framework, a dynamic noncoherent system composed of five components that can fail at discretized times has been analyzed, showing the applicability of the framework to practical cases. © 2014 Society for Risk Analysis.

Garter snake population dynamics from a 16-year study: considerations for ecological monitoring

Treesearch

Amy J. Lind; Hartwell H. Welsh Jr; David A. Tallmon

2005-01-01

Snakes have recently been proposed as model organisms for addressing both evolutionary and ecological questions. Because of their middle position in many food webs they may be useful indicators of trophic complexity and dynamics. However, reliable data on snake populations are rare due to the challenges of sampling these patchily distributed, cryptic, and often...

A Model for Predicting Integrated Man-Machine System Reliability: Model Logic and Description

DTIC Science & Technology

1974-11-01

3. Fatigue buildup curve. The common requirement of all tests on the Dynamic Strength factor is for the muscles involved to propel, support, or...move the body repeatedly or to support it continuously over time. The tests of our Static Strength factor emphasize the lifting power of the muscles ...or the pounds of pressure which the muscles can exert. ... In contrast to Dynamic Strength the force exerted is against external objects, rather

Safety and reliability analysis in a polyvinyl chloride batch process using dynamic simulator-case study: Loss of containment incident.

PubMed

Rizal, Datu; Tani, Shinichi; Nishiyama, Kimitoshi; Suzuki, Kazuhiko

2006-10-11

In this paper, a novel methodology in batch plant safety and reliability analysis is proposed using a dynamic simulator. A batch process involving several safety objects (e.g. sensors, controller, valves, etc.) is activated during the operational stage. The performance of the safety objects is evaluated by the dynamic simulation and a fault propagation model is generated. By using the fault propagation model, an improved fault tree analysis (FTA) method using switching signal mode (SSM) is developed for estimating the probability of failures. The timely dependent failures can be considered as unavailability of safety objects that can cause the accidents in a plant. Finally, the rank of safety object is formulated as performance index (PI) and can be estimated using the importance measures. PI shows the prioritization of safety objects that should be investigated for safety improvement program in the plants. The output of this method can be used for optimal policy in safety object improvement and maintenance. The dynamic simulator was constructed using Visual Modeler (VM, the plant simulator, developed by Omega Simulation Corp., Japan). A case study is focused on the loss of containment (LOC) incident at polyvinyl chloride (PVC) batch process which is consumed the hazardous material, vinyl chloride monomer (VCM).

Modeling Sensor Reliability in Fault Diagnosis Based on Evidence Theory

PubMed Central

Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

2016-01-01

Sensor data fusion plays an important role in fault diagnosis. Dempster–Shafer (D-R) evidence theory is widely used in fault diagnosis, since it is efficient to combine evidence from different sensors. However, under the situation where the evidence highly conflicts, it may obtain a counterintuitive result. To address the issue, a new method is proposed in this paper. Not only the statistic sensor reliability, but also the dynamic sensor reliability are taken into consideration. The evidence distance function and the belief entropy are combined to obtain the dynamic reliability of each sensor report. A weighted averaging method is adopted to modify the conflict evidence by assigning different weights to evidence according to sensor reliability. The proposed method has better performance in conflict management and fault diagnosis due to the fact that the information volume of each sensor report is taken into consideration. An application in fault diagnosis based on sensor fusion is illustrated to show the efficiency of the proposed method. The results show that the proposed method improves the accuracy of fault diagnosis from 81.19% to 89.48% compared to the existing methods. PMID:26797611

Camera-tracking gaming control device for evaluation of active wrist flexion and extension.

PubMed

Shefer Eini, Dalit; Ratzon, Navah Z; Rizzo, Albert A; Yeh, Shih-Ching; Lange, Belinda; Yaffe, Batia; Daich, Alexander; Weiss, Patrice L; Kizony, Rachel

Cross sectional. Measuring wrist range of motion (ROM) is an essential procedure in hand therapy clinics. To test the reliability and validity of a dynamic ROM assessment, the Camera Wrist Tracker (CWT). Wrist flexion and extension ROM of 15 patients with distal radius fractures and 15 matched controls were assessed with the CWT and with a universal goniometer. One-way model intraclass correlation coefficient analysis indicated high test-retest reliability for extension (ICC = 0.92) and moderate reliability for flexion (ICC = 0.49). Standard error for extension was 2.45° and for flexion was 4.07°. Repeated-measures analysis revealed a significant main effect for group; ROM was greater in the control group (F[1, 28] = 47.35; P < .001). The concurrent validity of the CWT was partially supported. The results indicate that the CWT may provide highly reliable scores for dynamic wrist extension ROM, and moderately reliable scores for flexion, in people recovering from a distal radius fracture. N/A. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

A locomotive-track coupled vertical dynamics model with gear transmissions

NASA Astrophysics Data System (ADS)

Chen, Zaigang; Zhai, Wanming; Wang, Kaiyun

2017-02-01

A gear transmission system is a key element in a locomotive for the transmission of traction or braking forces between the motor and the wheel-rail interface. Its dynamic performance has a direct effect on the operational reliability of the locomotive and its components. This paper proposes a comprehensive locomotive-track coupled vertical dynamics model, in which the locomotive is driven by axle-hung motors. In this coupled dynamics model, the dynamic interactions between the gear transmission system and the other components, e.g. motor and wheelset, are considered based on the detailed analysis of its structural properties and working mechanism. Thus, the mechanical transmission system for power delivery from the motor to the wheelset via gear transmission is coupled with a traditional locomotive-track dynamics system via the wheel-rail contact interface and the gear mesh interface. This developed dynamics model enables investigations of the dynamic performance of the entire dynamics system under the excitations from the wheel-rail contact interface and/or the gear mesh interface. Dynamic interactions are demonstrated by numerical simulations using this dynamics model. The results indicate that both of the excitations from the wheel-rail contact interface and the gear mesh interface have a significant effect on the dynamic responses of the components in this coupled dynamics system.

Force Project Technology Presentation to the NRCC

DTIC Science & Technology

2014-02-04

Functional Bridge components Smart Odometer Adv Pretreatment Smart Bridge Multi-functional Gap Crossing Fuel Automated Tracking System Adv...comprehensive matrix of candidate composite material systems and textile reinforcement architectures via modeling/analyses and testing. Product(s...Validated Dynamic Modeling tool based on parametric study using material models to reliably predict the textile mechanics of the hose

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change

NASA Astrophysics Data System (ADS)

Li, Qiaoling; Ishidaira, Hiroshi

2012-01-01

SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH potentially provides a powerful tool for simulating vegetation response to climate changes in the biosphere hydrological cycle.

Dynamic model updating based on strain mode shape and natural frequency using hybrid pattern search technique

NASA Astrophysics Data System (ADS)

Guo, Ning; Yang, Zhichun; Wang, Le; Ouyang, Yan; Zhang, Xinping

2018-05-01

Aiming at providing a precise dynamic structural finite element (FE) model for dynamic strength evaluation in addition to dynamic analysis. A dynamic FE model updating method is presented to correct the uncertain parameters of the FE model of a structure using strain mode shapes and natural frequencies. The strain mode shape, which is sensitive to local changes in structure, is used instead of the displacement mode for enhancing model updating. The coordinate strain modal assurance criterion is developed to evaluate the correlation level at each coordinate over the experimental and the analytical strain mode shapes. Moreover, the natural frequencies which provide the global information of the structure are used to guarantee the accuracy of modal properties of the global model. Then, the weighted summation of the natural frequency residual and the coordinate strain modal assurance criterion residual is used as the objective function in the proposed dynamic FE model updating procedure. The hybrid genetic/pattern-search optimization algorithm is adopted to perform the dynamic FE model updating procedure. Numerical simulation and model updating experiment for a clamped-clamped beam are performed to validate the feasibility and effectiveness of the present method. The results show that the proposed method can be used to update the uncertain parameters with good robustness. And the updated dynamic FE model of the beam structure, which can correctly predict both the natural frequencies and the local dynamic strains, is reliable for the following dynamic analysis and dynamic strength evaluation.

Rainfall Induced Landslides in Puerto Rico (Invited)

NASA Astrophysics Data System (ADS)

Lepore, C.; Kamal, S.; Arnone, E.; Noto, V.; Shanahan, P.; Bras, R. L.

2009-12-01

Landslides are a major geologic hazard in the United States, typically triggered by rainfall, earthquakes, volcanoes and human activity. Rainfall-induced landslides are the most common type in the island of Puerto Rico, with one or two large events per year. We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model capable of simulating landslides, tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. .Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides, which is used to predict the dynamic susceptibility of the basin to landslides.

Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

PubMed

Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

2018-01-01

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

Reliability of digital reactor protection system based on extenics.

PubMed

Zhao, Jing; He, Ya-Nan; Gu, Peng-Fei; Chen, Wei-Hua; Gao, Feng

2016-01-01

After the Fukushima nuclear accident, safety of nuclear power plants (NPPs) is widespread concerned. The reliability of reactor protection system (RPS) is directly related to the safety of NPPs, however, it is difficult to accurately evaluate the reliability of digital RPS. The method is based on estimating probability has some uncertainties, which can not reflect the reliability status of RPS dynamically and support the maintenance and troubleshooting. In this paper, the reliability quantitative analysis method based on extenics is proposed for the digital RPS (safety-critical), by which the relationship between the reliability and response time of RPS is constructed. The reliability of the RPS for CPR1000 NPP is modeled and analyzed by the proposed method as an example. The results show that the proposed method is capable to estimate the RPS reliability effectively and provide support to maintenance and troubleshooting of digital RPS system.

System life and reliability modeling for helicopter transmissions

NASA Technical Reports Server (NTRS)

Savage, M.; Brikmanis, C. K.

1986-01-01

A computer program which simulates life and reliability of helicopter transmissions is presented. The helicopter transmissions may be composed of spiral bevel gear units and planetary gear units - alone, in series or in parallel. The spiral bevel gear units may have either single or dual input pinions, which are identical. The planetary gear units may be stepped or unstepped and the number of planet gears carried by the planet arm may be varied. The reliability analysis used in the program is based on the Weibull distribution lives of the transmission components. The computer calculates the system lives and dynamic capacities of the transmission components and the transmission. The system life is defined as the life of the component or transmission at an output torque at which the probability of survival is 90 percent. The dynamic capacity of a component or transmission is defined as the output torque which can be applied for one million output shaft cycles for a probability of survival of 90 percent. A complete summary of the life and dynamic capacity results is produced by the program.

High effective inverse dynamics modelling for dual-arm robot

NASA Astrophysics Data System (ADS)

Shen, Haoyu; Liu, Yanli; Wu, Hongtao

2018-05-01

To deal with the problem of inverse dynamics modelling for dual arm robot, a recursive inverse dynamics modelling method based on decoupled natural orthogonal complement is presented. In this model, the concepts and methods of Decoupled Natural Orthogonal Complement matrices are used to eliminate the constraint forces in the Newton-Euler kinematic equations, and the screws is used to express the kinematic and dynamics variables. On this basis, the paper has developed a special simulation program with symbol software of Mathematica and conducted a simulation research on the a dual-arm robot. Simulation results show that the proposed method based on decoupled natural orthogonal complement can save an enormous amount of CPU time that was spent in computing compared with the recursive Newton-Euler kinematic equations and the results is correct and reasonable, which can verify the reliability and efficiency of the method.

Reliability prediction of ontology-based service compositions using Petri net and time series models.

PubMed

Li, Jia; Xia, Yunni; Luo, Xin

2014-01-01

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy.

Identification of the contribution of the ankle and hip joints to multi-segmental balance control

PubMed Central

2013-01-01

Background Human stance involves multiple segments, including the legs and trunk, and requires coordinated actions of both. A novel method was developed that reliably estimates the contribution of the left and right leg (i.e., the ankle and hip joints) to the balance control of individual subjects. Methods The method was evaluated using simulations of a double-inverted pendulum model and the applicability was demonstrated with an experiment with seven healthy and one Parkinsonian participant. Model simulations indicated that two perturbations are required to reliably estimate the dynamics of a double-inverted pendulum balance control system. In the experiment, two multisine perturbation signals were applied simultaneously. The balance control system dynamic behaviour of the participants was estimated by Frequency Response Functions (FRFs), which relate ankle and hip joint angles to joint torques, using a multivariate closed-loop system identification technique. Results In the model simulations, the FRFs were reliably estimated, also in the presence of realistic levels of noise. In the experiment, the participants responded consistently to the perturbations, indicated by low noise-to-signal ratios of the ankle angle (0.24), hip angle (0.28), ankle torque (0.07), and hip torque (0.33). The developed method could detect that the Parkinson patient controlled his balance asymmetrically, that is, the right ankle and hip joints produced more corrective torque. Conclusion The method allows for a reliable estimate of the multisegmental feedback mechanism that stabilizes stance, of individual participants and of separate legs. PMID:23433148

Two-bead polarizable water models combined with a two-bead multipole force field (TMFF) for coarse-grained simulation of proteins.

PubMed

Li, Min; Zhang, John Z H

2017-03-08

The development of polarizable water models at coarse-grained (CG) levels is of much importance to CG molecular dynamics simulations of large biomolecular systems. In this work, we combined the newly developed two-bead multipole force field (TMFF) for proteins with the two-bead polarizable water models to carry out CG molecular dynamics simulations for benchmark proteins. In our simulations, two different two-bead polarizable water models are employed, the RTPW model representing five water molecules by Riniker et al. and the LTPW model representing four water molecules. The LTPW model is developed in this study based on the Martini three-bead polarizable water model. Our simulation results showed that the combination of TMFF with the LTPW model significantly stabilizes the protein's native structure in CG simulations, while the use of the RTPW model gives better agreement with all-atom simulations in predicting the residue-level fluctuation dynamics. Overall, the TMFF coupled with the two-bead polarizable water models enables one to perform an efficient and reliable CG dynamics study of the structural and functional properties of large biomolecules.

Test-retest reliability of effective connectivity in the face perception network.

PubMed

Frässle, Stefan; Paulus, Frieder Michel; Krach, Sören; Jansen, Andreas

2016-02-01

Computational approaches have great potential for moving neuroscience toward mechanistic models of the functional integration among brain regions. Dynamic causal modeling (DCM) offers a promising framework for inferring the effective connectivity among brain regions and thus unraveling the neural mechanisms of both normal cognitive function and psychiatric disorders. While the benefit of such approaches depends heavily on their reliability, systematic analyses of the within-subject stability are rare. Here, we present a thorough investigation of the test-retest reliability of an fMRI paradigm for DCM analysis dedicated to unraveling intra- and interhemispheric integration among the core regions of the face perception network. First, we examined the reliability of face-specific BOLD activity in 25 healthy volunteers, who performed a face perception paradigm in two separate sessions. We found good to excellent reliability of BOLD activity within the DCM-relevant regions. Second, we assessed the stability of effective connectivity among these regions by analyzing the reliability of Bayesian model selection and model parameter estimation in DCM. Reliability was excellent for the negative free energy and good for model parameter estimation, when restricting the analysis to parameters with substantial effect sizes. Third, even when the experiment was shortened, reliability of BOLD activity and DCM results dropped only slightly as a function of the length of the experiment. This suggests that the face perception paradigm presented here provides reliable estimates for both conventional activation and effective connectivity measures. We conclude this paper with an outlook on potential clinical applications of the paradigm for studying psychiatric disorders. Hum Brain Mapp 37:730-744, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Dynamic characteristics of motor-gear system under load saltations and voltage transients

NASA Astrophysics Data System (ADS)

Bai, Wenyu; Qin, Datong; Wang, Yawen; Lim, Teik C.

2018-02-01

In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

PubMed

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification

PubMed Central

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system. PMID:27918594

Shock and vibration effects on performance reliability and mechanical integrity of proton exchange membrane fuel cells: A critical review and discussion

NASA Astrophysics Data System (ADS)

Haji Hosseinloo, Ashkan; Ehteshami, Mohsen Mousavi

2017-10-01

Performance reliability and mechanical integrity are the main bottlenecks in mass commercialization of PEMFCs for applications with inherent harsh environment such as automotive and aerospace applications. Imparted shock and vibration to the fuel cell in such applications could bring about numerous issues including clamping torque loosening, gas leakage, increased electrical resistance, and structural damage and breakage. Here, we provide a comprehensive review and critique of the literature focusing on the effects of mechanically harsh environment on PEMFCs, and at the end, we suggest two main future directions in FC technology research that need immediate attention: (i) developing a generic and adequately accurate dynamic model of PEMFCs to assess the dynamic response of FC devices, and (ii) designing effective and robust shock and vibration protection systems based on the developed models in (i).

Non-Invasive Tension Measurement Devices for Parachute Cordage

NASA Technical Reports Server (NTRS)

Litteken, Douglas A.; Daum, Jared S.

2016-01-01

The need for lightweight and non-intrusive tension measurements has arisen alongside the development of high-fidelity computer models of textile and fluid dynamics. In order to validate these computer models, data must be gathered in the operational environment without altering the design, construction, or performance of the test article. Current measurement device designs rely on severing a cord and breaking the load path to introduce a load cell. These load cells are very reliable, but introduce an area of high stiffness in the load path, directly affecting the structural response, adding excessive weight, and possibly altering the dynamics of the parachute during a test. To capture the required data for analysis validation without affecting the response of the system, non-invasive measurement devices have been developed and tested by NASA. These tension measurement devices offer minimal impact to the mass, form, fit, and function of the test article, while providing reliable, axial tension measurements for parachute cordage.

Dynamic one-dimensional modeling of secondary settling tanks and system robustness evaluation.

PubMed

Li, Ben; Stenstrom, M K

2014-01-01

One-dimensional secondary settling tank models are widely used in current engineering practice for design and optimization, and usually can be expressed as a nonlinear hyperbolic or nonlinear strongly degenerate parabolic partial differential equation (PDE). Reliable numerical methods are needed to produce approximate solutions that converge to the exact analytical solutions. In this study, we introduced a reliable numerical technique, the Yee-Roe-Davis (YRD) method as the governing PDE solver, and compared its reliability with the prevalent Stenstrom-Vitasovic-Takács (SVT) method by assessing their simulation results at various operating conditions. The YRD method also produced a similar solution to the previously developed Method G and Enquist-Osher method. The YRD and SVT methods were also used for a time-to-failure evaluation, and the results show that the choice of numerical method can greatly impact the solution. Reliable numerical methods, such as the YRD method, are strongly recommended.

Enhanced Arctic Mean Sea Surface and Mean Dynamic Topography including retracked CryoSat-2 Data

NASA Astrophysics Data System (ADS)

Andersen, O. B.; Jain, M.; Stenseng, L.; Knudsen, P.

2014-12-01

A reliable mean sea surface (MSS) is essential to derive a good mean dynamic topography (MDT) and for the estimation of short and long-term changes in the sea surface. The lack of satellite radar altimetry observations above 82 degrees latitude means that existing mean sea surface models have been unreliable in the Arctic Ocean. We here present the latest DTU mean sea surface and mean dynamic topography models combining conventional altimetry with retracked CryoSat-2 data to improve the reliability in the Arctic Ocean. For the derivation of a mean dynamic topography the ESA GOCE derived geoid model have been used to constrain the longer wavelength. We present the retracking of C2 SAR data using various retrackes and how we have been able to combine data from various retrackers under various sea ice conditions. DTU13MSS and DTU13MDT are the newest state of the art global high-resolution models including CryoSat-2 data to extend the satellite radar altimetry coverage up to 88 degrees latitude and through combination with a GOCE geoid model completes coverage all the way to the North Pole. Furthermore the SAR and SARin capability of CryoSat-2 dramatically increases the amount of useable sea surface returns in sea-ice covered areas compared to conventional radar altimeters like ENVISAT and ERS-1/2. With the inclusion of CryoSat-2 data the new mean sea surface is improved by more than 20 cm above 82 degrees latitude compared with the previous generation of mean sea surfaces.

On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

NASA Astrophysics Data System (ADS)

Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

2017-10-01

With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

Measurement and modeling of intrinsic transcription terminators

PubMed Central

Cambray, Guillaume; Guimaraes, Joao C.; Mutalik, Vivek K.; Lam, Colin; Mai, Quynh-Anh; Thimmaiah, Tim; Carothers, James M.; Arkin, Adam P.; Endy, Drew

2013-01-01

The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used routinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode termination efficiencies across an ∼800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termination activity. We found that structures extending beyond the core terminator stem are likely to increase terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r = 0.9, n = 31) better than models trained on all terminators (r = 0.67, n = 54). The resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination. PMID:23511967

Review on the Modeling of Electrostatic MEMS

PubMed Central

Chuang, Wan-Chun; Lee, Hsin-Li; Chang, Pei-Zen; Hu, Yuh-Chung

2010-01-01

Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices. PMID:22219707

Monitoring Hurricane Rita Inland Storm Surge: Chapter 7J in Science and the storms-the USGS response to the hurricanes of 2005

USGS Publications Warehouse

McGee, Benton D.; Tollett, Roland W.; Goree, Burl B.

2007-01-01

Pressure transducers (sensors) are accurate, reliable, and cost-effective tools to measure and record the magnitude, extent, and timing of hurricane storm surge. Sensors record storm-surge peaks more accurately and reliably than do high-water marks. Data collected by sensors may be used in storm-surge models to estimate when, where, and to what degree stormsurge flooding will occur during future storm-surge events and to calibrate and verify stormsurge models, resulting in a better understanding of the dynamics of storm surge.

Cognitive mechanisms for explaining dynamics of aesthetic appreciation

PubMed Central

Carbon, Claus-Christian

2011-01-01

For many domains aesthetic appreciation has proven to be highly reliable. Evaluations of facial attractiveness, for instance, show high internal consistencies and impressively high inter-rater reliabilities, even across cultures. This indicates general mechanisms underlying such evaluations. It is, however, also obvious that our taste for specific objects is not always stable—in some realms such stability is hardly conceivable at all since aesthetic domains such as fashion, design, or art are inherently very dynamic. Gaining insights into the cognitive mechanisms that trigger and enable corresponding changes of aesthetic appreciation is of particular interest for psychologists as this will probably reveal essential mechanisms of aesthetic evaluations per se. The present paper develops a two-step model, dynamically adapting itself, which accounts for typical dynamics of aesthetic appreciation found in different research areas such as art history, philosophy, and psychology. The first step assumes singular creative sources creating and establishing innovative material towards which, in a second step, people adapt by integrating it into their visual habits. This inherently leads to dynamic changes of the beholders— aesthetic appreciation. PMID:23145254

Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission

NASA Astrophysics Data System (ADS)

Huang, Yuechen; Li, Haiyang

2018-06-01

This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.

Adaptive Sampling using Support Vector Machines

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

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Efficient loads analyses of Shuttle-payloads using dynamic models with linear or nonlinear interfaces

NASA Technical Reports Server (NTRS)

Spanos, P. D.; Cao, T. T.; Hamilton, D. A.; Nelson, D. A. R.

1989-01-01

An efficient method for the load analysis of Shuttle-payload systems with linear or nonlinear attachment interfaces is presented which allows the kinematics of the interface degrees of freedom at a given time to be evaluated without calculating the combined system modal representation of the Space Shuttle and its payload. For the case of a nonlinear dynamic model, an iterative procedure is employed to converge the nonlinear terms of the equations of motion to reliable values. Results are presented for a Shuttle abort landing event.

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

Sissa, Cristina; Delchiaro, Francesca; Di Maiolo, Francesco

Essential-state models efficiently describe linear and nonlinear spectral properties of different families of charge-transfer chromophores. Here, the essential-state machinery is applied to the calculation of the early-stage dynamics after ultrafast (coherent) excitation of polar and quadrupolar chromophores. The fully non-adiabatic treatment of coupled electronic and vibrational motion allows for a reliable description of the dynamics of these intriguing systems. In particular, the proposed approach is reliable even when the adiabatic and harmonic approximations do not apply, such as for quadrupolar dyes that show a multistable, broken-symmetry excited state. Our approach quite naturally leads to a clear picture for a dynamicalmore » Jahn-Teller effect in these systems. The recovery of symmetry due to dynamical effects is however disrupted in polar solvents where a static symmetry lowering is observed. More generally, thermal disorder in polar solvents is responsible for dephasing phenomena, damping the coherent oscillations with particularly important effects in the case of polar dyes.« less

Numerical modeling of local scour around hydraulic structure in sandy beds by dynamic mesh method

NASA Astrophysics Data System (ADS)

Fan, Fei; Liang, Bingchen; Bai, Yuchuan; Zhu, Zhixia; Zhu, Yanjun

2017-10-01

Local scour, a non-negligible factor in hydraulic engineering, endangers the safety of hydraulic structures. In this work, a numerical model for simulating local scour was constructed, based on the open source code computational fluid dynamics model OpenFOAM. We consider both the bedload and suspended load sediment transport in the scour model and adopt the dynamic mesh method to simulate the evolution of the bed elevation. We use the finite area method to project data between the three-dimensional flow model and the two-dimensional (2D) scour model. We also improved the 2D sand slide method and added it to the scour model to correct the bed bathymetry when the bed slope angle exceeds the angle of repose. Moreover, to validate our scour model, we conducted and compared the results of three experiments with those of the developed model. The validation results show that our developed model can reliably simulate local scour.

Real-time reliability measure-driven multi-hypothesis tracking using 2D and 3D features

NASA Astrophysics Data System (ADS)

Zúñiga, Marcos D.; Brémond, François; Thonnat, Monique

2011-12-01

We propose a new multi-target tracking approach, which is able to reliably track multiple objects even with poor segmentation results due to noisy environments. The approach takes advantage of a new dual object model combining 2D and 3D features through reliability measures. In order to obtain these 3D features, a new classifier associates an object class label to each moving region (e.g. person, vehicle), a parallelepiped model and visual reliability measures of its attributes. These reliability measures allow to properly weight the contribution of noisy, erroneous or false data in order to better maintain the integrity of the object dynamics model. Then, a new multi-target tracking algorithm uses these object descriptions to generate tracking hypotheses about the objects moving in the scene. This tracking approach is able to manage many-to-many visual target correspondences. For achieving this characteristic, the algorithm takes advantage of 3D models for merging dissociated visual evidence (moving regions) potentially corresponding to the same real object, according to previously obtained information. The tracking approach has been validated using video surveillance benchmarks publicly accessible. The obtained performance is real time and the results are competitive compared with other tracking algorithms, with minimal (or null) reconfiguration effort between different videos.

Parametric diagnosis of the adaptive gas path in the automatic control system of the aircraft engine

NASA Astrophysics Data System (ADS)

Kuznetsova, T. A.

2017-01-01

The paper dwells on the adaptive multimode mathematical model of the gas-turbine aircraft engine (GTE) embedded in the automatic control system (ACS). The mathematical model is based on the throttle performances, and is characterized by high accuracy of engine parameters identification in stationary and dynamic modes. The proposed on-board engine model is the state space linearized low-level simulation. The engine health is identified by the influence of the coefficient matrix. The influence coefficient is determined by the GTE high-level mathematical model based on measurements of gas-dynamic parameters. In the automatic control algorithm, the sum of squares of the deviation between the parameters of the mathematical model and real GTE is minimized. The proposed mathematical model is effectively used for gas path defects detecting in on-line GTE health monitoring. The accuracy of the on-board mathematical model embedded in ACS determines the quality of adaptive control and reliability of the engine. To improve the accuracy of identification solutions and sustainability provision, the numerical method of Monte Carlo was used. The parametric diagnostic algorithm based on the LPτ - sequence was developed and tested. Analysis of the results suggests that the application of the developed algorithms allows achieving higher identification accuracy and reliability than similar models used in practice.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Routing UAVs to Co-Optimize Mission Effectiveness and Network Performance with Dynamic Programming

DTIC Science & Technology

2011-03-01

Heuristics on Hexagonal Connected Dominating Sets to Model Routing Dissemination," in Communication Theory, Reliability, and Quality of Service (CTRQ...24] Matthew Capt. USAF Compton, Improving the Quality of Service and Security of Military Networks with a Network Tasking Order Process, 2010. [25...Wesley, 2006. [32] James Haught, "Adaptive Quality of Service Engine with Dynamic Queue Control," Air Force Institute of Technology, Wright

Reliability of the North America CORDEX and NARCCAP simulations in the context of uncertainty in regional climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.

2017-12-01

Ensembles of dynamically downscaled climate change simulations are routinely used to capture uncertainty in projections at regional scales. I assess the reliability of two such ensembles for North America - NARCCAP and NA-CORDEX - by investigating the impact of model selection on representing uncertainty in regional projections, and the ability of the regional climate models (RCMs) to provide reliable information. These aspects - discussed for the six regions used in the US National Climate Assessment - provide an important perspective on the interpretation of downscaled results. I show that selecting general circulation models for downscaling based on their equilibrium climate sensitivities is a reasonable choice, but the six models chosen for NA-CORDEX do a poor job at representing uncertainty in winter temperature and precipitation projections in many parts of the eastern US, which lead to overconfident projections. The RCM performance is highly variable across models, regions, and seasons and the ability of the RCMs to provide improved seasonal mean performance relative to their parent GCMs seems limited in both RCM ensembles. Additionally, the ability of the RCMs to simulate historical climates is not strongly related to their ability to simulate climate change across the ensemble. This finding suggests limited use of models' historical performance to constrain their projections. Given these challenges in dynamical downscaling, the RCM results should not be used in isolation. Information on how well the RCM ensembles represent known uncertainties in regional climate change projections discussed here needs to be communicated clearly to inform maagement decisions.

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders.

PubMed

Borotikar, Bhushan; Lempereur, Mathieu; Lelievre, Mathieu; Burdin, Valérie; Ben Salem, Douraied; Brochard, Sylvain

2017-01-01

To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function. The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Results for concurrent validity and reliability were categorized as poor, moderate, or excellent. Twenty articles fulfilled the inclusion criteria with a mean quality assessment score of 66% (±10.4%). Concurrent validity and/or reliability of eight dynamic MRI techniques were reported, with the knee being the most evaluated joint (seven studies). Moderate to excellent concurrent validity and reliability were reported for seven out of eight dynamic MRI techniques. Cine phase contrast and real-time MRI appeared to be the most valid and reliable techniques to evaluate joint motion, and spin tag for muscle motion. Dynamic MRI techniques are promising for the in vivo evaluation of musculoskeletal mechanics; however results should be evaluated with caution since validity and reliability have not been determined for all joints and muscles, nor for many pathological conditions.

Systematic study of 16O-induced fusion with the improved quantum molecular dynamics model

NASA Astrophysics Data System (ADS)

Wang, Ning; Zhao, Kai; Li, Zhuxia

2014-11-01

The heavy-ion fusion reactions with 16O bombarding on 62Ni,65Cu,74Ge,148Nd,180Hf,186W,208Pb,238U are systematically investigated with the improved quantum molecular dynamics model. The fusion cross sections at energies near and above the Coulomb barriers can be reasonably well reproduced by using this semiclassical microscopic transport model with the parameter sets SkP* and IQ3a. The dynamical nucleus-nucleus potentials and the influence of Fermi constraint on the fusion process are also studied simultaneously. In addition to the mean field, the Fermi constraint also plays a key role for the reliable description of the fusion process and for improving the stability of fragments in heavy-ion collisions.

Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models

PubMed Central

Li, Jia; Xia, Yunni; Luo, Xin

2014-01-01

OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy. PMID:24688429

Are there reliable constitutive laws for dynamic friction?

PubMed

Woodhouse, Jim; Putelat, Thibaut; McKay, Andrew

2015-09-28

Structural vibration controlled by interfacial friction is widespread, ranging from friction dampers in gas turbines to the motion of violin strings. To predict, control or prevent such vibration, a constitutive description of frictional interactions is inevitably required. A variety of friction models are discussed to assess their scope and validity, in the light of constraints provided by different experimental observations. Three contrasting case studies are used to illustrate how predicted behaviour can be extremely sensitive to the choice of frictional constitutive model, and to explore possible experimental paths to discriminate between and calibrate dynamic friction models over the full parameter range needed for real applications. © 2015 The Author(s).

A model of scientific attitudes assessment by observation in physics learning based scientific approach: case study of dynamic fluid topic in high school

NASA Astrophysics Data System (ADS)

Yusliana Ekawati, Elvin

2017-01-01

This study aimed to produce a model of scientific attitude assessment in terms of the observations for physics learning based scientific approach (case study of dynamic fluid topic in high school). Development of instruments in this study adaptation of the Plomp model, the procedure includes the initial investigation, design, construction, testing, evaluation and revision. The test is done in Surakarta, so that the data obtained are analyzed using Aiken formula to determine the validity of the content of the instrument, Cronbach’s alpha to determine the reliability of the instrument, and construct validity using confirmatory factor analysis with LISREL 8.50 program. The results of this research were conceptual models, instruments and guidelines on scientific attitudes assessment by observation. The construct assessment instruments include components of curiosity, objectivity, suspended judgment, open-mindedness, honesty and perseverance. The construct validity of instruments has been qualified (rated load factor > 0.3). The reliability of the model is quite good with the Alpha value 0.899 (> 0.7). The test showed that the model fits the theoretical models are supported by empirical data, namely p-value 0.315 (≥ 0.05), RMSEA 0.027 (≤ 0.08)

Dynamic Considerations for Control of Closed Life Support Systems

NASA Technical Reports Server (NTRS)

Babcock, P. S.; Auslander, D. M.; Spear, R. C.

1985-01-01

Reliability of closed life support systems depend on their ability to continue supplying the crew's needs during perturbations and equipment failures. The dynamic considerations interact with the basic static design through the sizing of storages, the specification of excess capacities in processors, and the choice of system initial state. A very simple system flow model was used to examine the possibilities for system failures even when there is sufficient storage to buffer the immediate effects of the perturbation. Two control schemes are shown which have different dynamic consequences in response to component failures.

Enhancing the Arctic Mean Sea Surface and Mean Dynamic Topography with CryoSat-2 Data

NASA Astrophysics Data System (ADS)

Stenseng, Lars; Andersen, Ole B.; Knudsen, Per

2014-05-01

A reliable mean sea surface (MSS) is essential to derive a good mean dynamic topography (MDT) and for the estimation of short and long-term changes in the sea surface. The lack of satellite radar altimetry observations above 82 degrees latitude means that existing mean sea surface models have been unreliable in the Arctic Ocean. We here present the latest DTU mean sea surface and mean dynamic topography models that includes CryoSat-2 data to improve the reliability in the Arctic Ocean. In an attempt to extrapolate across the gap above 82 degrees latitude the previously models included ICESat data, gravimetrical geoids, ocean circulation models and various combinations hereof. Unfortunately cloud cover and the short periods of operation has a negative effect on the number of ICESat sea surface observations. DTU13MSS and DTU13MDT are the new generation of state of the art global high-resolution models that includes CryoSat-2 data to extend the satellite radar altimetry coverage up to 88 degrees latitude. Furthermore the SAR and SARin capability of CryoSat-2 dramatically increases the amount of useable sea surface returns in sea-ice covered areas compared to conventional radar altimeters like ENVISAT and ERS-1/2. With the inclusion of CryoSat-2 data the new mean sea surface is improved by more than 20 cm above 82 degrees latitude compared with the previous generation of mean sea surfaces.

Structural Test Laboratory | Water Power | NREL

Science.gov Websites

Structural Test Laboratory Structural Test Laboratory NREL engineers design and configure structural components can validate models, demonstrate system reliability, inform design margins, and assess , including mass and center of gravity, to ensure compliance with design goals Dynamic Characterization Use

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run.

PubMed

Armeanu, Daniel; Andrei, Jean Vasile; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets.

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run

PubMed Central

Armeanu, Daniel; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets. PMID:28742100

Linking Structural Equation Modelling with Bayesian Network and Coastal Phytoplankton Dynamics in Bohai Bay

NASA Astrophysics Data System (ADS)

Chu, Jiangtao; Yang, Yue

2018-06-01

Bayesian networks (BN) have many advantages over other methods in ecological modelling and have become an increasingly popular modelling tool. However, BN are flawed in regard to building models based on inadequate existing knowledge. To overcome this limitation, we propose a new method that links BN with structural equation modelling (SEM). In this method, SEM is used to improve the model structure for BN. This method was used to simulate coastal phytoplankton dynamics in Bohai Bay. We demonstrate that this hybrid approach minimizes the need for expert elicitation, generates more reasonable structures for BN models and increases the BN model's accuracy and reliability. These results suggest that the inclusion of SEM for testing and verifying the theoretical structure during the initial construction stage improves the effectiveness of BN models, especially for complex eco-environment systems. The results also demonstrate that in Bohai Bay, while phytoplankton biomass has the greatest influence on phytoplankton dynamics, the impact of nutrients on phytoplankton dynamics is larger than the influence of the physical environment in summer. Furthermore, despite the Redfield ratio indicating that phosphorus should be the primary nutrient limiting factor, our results indicate that silicate plays the most important role in regulating phytoplankton dynamics in Bohai Bay.

Modeling capillary bridge dynamics and crack healing between surfaces of nanoscale roughness

NASA Astrophysics Data System (ADS)

Soylemez, Emrecan; de Boer, Maarten P.

2017-12-01

Capillary bridge formation between adjacent surfaces in humid environments is a ubiquitous phenomenon. It strongly influences tribological performance with respect to adhesion, friction and wear. Only a few studies, however, assess effects due to capillary dynamics. Here we focus on how capillary bridge evolution influences crack healing rates. Experimental results indicated a logarithmic decrease in average crack healing velocity as the energy release rate increases. Our objective is to model that trend. We assume that capillary dynamics involve two mechanisms: capillary bridge growth and subsequently nucleation followed by growth. We show that by incorporating interface roughness details and the presence of an adsorbed water layer, the behavior of capillary force dynamics can be understood quantitatively. We identify three important regimes that control the healing process, namely bridge growth, combined bridge growth and nucleation, and finally bridge nucleation. To fully capture the results, however, the theoretical model for nucleation time required an empirical modification. Our model enables significant insight into capillary bridge dynamics, with a goal of attaining a predictive capability for this important microelectromechanical systems (MEMS) reliability failure mechanism.

Dynamically induced cascading failures in power grids.

PubMed

Schäfer, Benjamin; Witthaut, Dirk; Timme, Marc; Latora, Vito

2018-05-17

Reliable functioning of infrastructure networks is essential for our modern society. Cascading failures are the cause of most large-scale network outages. Although cascading failures often exhibit dynamical transients, the modeling of cascades has so far mainly focused on the analysis of sequences of steady states. In this article, we focus on electrical transmission networks and introduce a framework that takes into account both the event-based nature of cascades and the essentials of the network dynamics. We find that transients of the order of seconds in the flows of a power grid play a crucial role in the emergence of collective behaviors. We finally propose a forecasting method to identify critical lines and components in advance or during operation. Overall, our work highlights the relevance of dynamically induced failures on the synchronization dynamics of national power grids of different European countries and provides methods to predict and model cascading failures.

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

PubMed Central

Isabelle, Boulangeat; Pauline, Philippe; Sylvain, Abdulhak; Roland, Douzet; Luc, Garraud; Sébastien, Lavergne; Sandra, Lavorel; Jérémie, Van Es; Pascal, Vittoz; Wilfried, Thuiller

2013-01-01

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling. PMID:24403847

A stochastic evolutionary model generating a mixture of exponential distributions

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Levene, Mark; Loizou, George

2016-02-01

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.

Methods for Calculating Frequency of Maintenance of Complex Information Security System Based on Dynamics of Its Reliability

NASA Astrophysics Data System (ADS)

Varlataya, S. K.; Evdokimov, V. E.; Urzov, A. Y.

2017-11-01

This article describes a process of calculating a certain complex information security system (CISS) reliability using the example of the technospheric security management model as well as ability to determine the frequency of its maintenance using the system reliability parameter which allows one to assess man-made risks and to forecast natural and man-made emergencies. The relevance of this article is explained by the fact the CISS reliability is closely related to information security (IS) risks. Since reliability (or resiliency) is a probabilistic characteristic of the system showing the possibility of its failure (and as a consequence - threats to the protected information assets emergence), it is seen as a component of the overall IS risk in the system. As it is known, there is a certain acceptable level of IS risk assigned by experts for a particular information system; in case of reliability being a risk-forming factor maintaining an acceptable risk level should be carried out by the routine analysis of the condition of CISS and its elements and their timely service. The article presents a reliability parameter calculation for the CISS with a mixed type of element connection, a formula of the dynamics of such system reliability is written. The chart of CISS reliability change is a S-shaped curve which can be divided into 3 periods: almost invariable high level of reliability, uniform reliability reduction, almost invariable low level of reliability. Setting the minimum acceptable level of reliability, the graph (or formula) can be used to determine the period of time during which the system would meet requirements. Ideally, this period should not be longer than the first period of the graph. Thus, the proposed method of calculating the CISS maintenance frequency helps to solve a voluminous and critical task of the information assets risk management.

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit. [inertial platforms

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

A control theoretical approach to crowd management. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Borzí, Alfio; Caponigro, Marco

2016-09-01

The formulation of mathematical models for crowd dynamics is one current challenge in many fields of applied sciences. It involves the modelization of the complex behavior of a large number of individuals. In particular, the difficulty lays in describing emerging collective behaviors by means of a relatively small number of local interaction rules between individuals in a crowd. Clearly, the individual's free will involved in decision making processes and in the management of the social interactions cannot be described by a finite number of deterministic rules. On the other hand, in large crowds, this individual indeterminacy can be considered as a local fluctuation averaged to zero by the size of the crowd. While at the microscopic scale, using a system of coupled ODEs, the free will should be included in the mathematical description (e.g. with a stochastic term), the mesoscopic and macroscopic scales, modeled by PDEs, represent a powerful modelling tool that allows to neglect this feature and provide a reliable description. In this sense, the work by Bellomo, Clarke, Gibelli, Townsend, and Vreugdenhil [2] represents a mathematical-epistemological contribution towards the design of a reliable model of human behavior.

A system model of the effects of exercise on plasma Interleukin-6 dynamics in healthy individuals: Role of skeletal muscle and adipose tissue.

PubMed

Morettini, Micaela; Palumbo, Maria Concetta; Sacchetti, Massimo; Castiglione, Filippo; Mazzà, Claudia

2017-01-01

Interleukin-6 (IL-6) has been recently shown to play a central role in glucose homeostasis, since it stimulates the production and secretion of Glucagon-like Peptide-1 (GLP-1) from intestinal L-cells and pancreas, leading to an enhanced insulin response. In resting conditions, IL-6 is mainly produced by the adipose tissue whereas, during exercise, skeletal muscle contractions stimulate a marked IL-6 secretion as well. Available mathematical models describing the effects of exercise on glucose homeostasis, however, do not account for this IL-6 contribution. This study aimed at developing and validating a system model of exercise's effects on plasma IL-6 dynamics in healthy humans, combining the contributions of both adipose tissue and skeletal muscle. A two-compartment description was adopted to model plasma IL-6 changes in response to oxygen uptake's variation during an exercise bout. The free parameters of the model were estimated by means of a cross-validation procedure performed on four different datasets. A low coefficient of variation (<10%) was found for each parameter and the physiologically meaningful parameters were all consistent with literature data. Moreover, plasma IL-6 dynamics during exercise and post-exercise were consistent with literature data from exercise protocols differing in intensity, duration and modality. The model successfully emulated the physiological effects of exercise on plasma IL-6 levels and provided a reliable description of the role of skeletal muscle and adipose tissue on the dynamics of plasma IL-6. The system model here proposed is suitable to simulate IL-6 response to different exercise modalities. Its future integration with existing models of GLP-1-induced insulin secretion might provide a more reliable description of exercise's effects on glucose homeostasis and hence support the definition of more tailored interventions for the treatment of type 2 diabetes.

Dynamic MRI to quantify musculoskeletal motion: A systematic review of concurrent validity and reliability, and perspectives for evaluation of musculoskeletal disorders

PubMed Central

Lempereur, Mathieu; Lelievre, Mathieu; Burdin, Valérie; Ben Salem, Douraied; Brochard, Sylvain

2017-01-01

Purpose To report evidence for the concurrent validity and reliability of dynamic MRI techniques to evaluate in vivo joint and muscle mechanics, and to propose recommendations for their use in the assessment of normal and impaired musculoskeletal function. Materials and methods The search was conducted on articles published in Web of science, PubMed, Scopus, Academic search Premier, and Cochrane Library between 1990 and August 2017. Studies that reported the concurrent validity and/or reliability of dynamic MRI techniques for in vivo evaluation of joint or muscle mechanics were included after assessment by two independent reviewers. Selected articles were assessed using an adapted quality assessment tool and a data extraction process. Results for concurrent validity and reliability were categorized as poor, moderate, or excellent. Results Twenty articles fulfilled the inclusion criteria with a mean quality assessment score of 66% (±10.4%). Concurrent validity and/or reliability of eight dynamic MRI techniques were reported, with the knee being the most evaluated joint (seven studies). Moderate to excellent concurrent validity and reliability were reported for seven out of eight dynamic MRI techniques. Cine phase contrast and real-time MRI appeared to be the most valid and reliable techniques to evaluate joint motion, and spin tag for muscle motion. Conclusion Dynamic MRI techniques are promising for the in vivo evaluation of musculoskeletal mechanics; however results should be evaluated with caution since validity and reliability have not been determined for all joints and muscles, nor for many pathological conditions. PMID:29232401

Cost-effective solutions to maintaining smart grid reliability

NASA Astrophysics Data System (ADS)

Qin, Qiu

As the aging power systems are increasingly working closer to the capacity and thermal limits, maintaining an sufficient reliability has been of great concern to the government agency, utility companies and users. This dissertation focuses on improving the reliability of transmission and distribution systems. Based on the wide area measurements, multiple model algorithms are developed to diagnose transmission line three-phase short to ground faults in the presence of protection misoperations. The multiple model algorithms utilize the electric network dynamics to provide prompt and reliable diagnosis outcomes. Computational complexity of the diagnosis algorithm is reduced by using a two-step heuristic. The multiple model algorithm is incorporated into a hybrid simulation framework, which consist of both continuous state simulation and discrete event simulation, to study the operation of transmission systems. With hybrid simulation, line switching strategy for enhancing the tolerance to protection misoperations is studied based on the concept of security index, which involves the faulted mode probability and stability coverage. Local measurements are used to track the generator state and faulty mode probabilities are calculated in the multiple model algorithms. FACTS devices are considered as controllers for the transmission system. The placement of FACTS devices into power systems is investigated with a criterion of maintaining a prescribed level of control reconfigurability. Control reconfigurability measures the small signal combined controllability and observability of a power system with an additional requirement on fault tolerance. For the distribution systems, a hierarchical framework, including a high level recloser allocation scheme and a low level recloser placement scheme, is presented. The impacts of recloser placement on the reliability indices is analyzed. Evaluation of reliability indices in the placement process is carried out via discrete event simulation. The reliability requirements are described with probabilities and evaluated from the empirical distributions of reliability indices.

Long-term potential and actual evapotranspiration of two different forests on the Atlantic Coastal Plain

Treesearch

Devendra Amatya; S. Tian; Z. Dai; Ge Sun

2016-01-01

A reliable estimate of potential evapotranspiration (PET) for a forest ecosystem is critical in ecohydrologic modeling related with water supply, vegetation dynamics, and climate change and yet is a challenging task due to its complexity. Based on long-term on-site measured hydro-climatic data and predictions from earlier validated hydrologic modeling studies...

Electron-Ion Dynamics with Time-Dependent Density Functional Theory: Towards Predictive Solar Cell Modeling: Final Technical Report

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

Maitra, Neepa

2016-07-14

This project investigates the accuracy of currently-used functionals in time-dependent density functional theory, which is today routinely used to predict and design materials and computationally model processes in solar energy conversion. The rigorously-based electron-ion dynamics method developed here sheds light on traditional methods and overcomes challenges those methods have. The fundamental research undertaken here is important for building reliable and practical methods for materials discovery. The ultimate goal is to use these tools for the computational design of new materials for solar cell devices of high efficiency.

Evaluating the application of multi-satellite observation in hydrologic modeling

USDA-ARS?s Scientific Manuscript database

When monitoring local or regional hydrosphere dynamics for applications such as agricultural productivity or drought and flooding events, it is necessary to have accurate, high-resolution estimates of terrestrial water and energy storages. Though in-situ observations provide reliable estimates of hy...

Earthquake Source Inversion Blindtest: Initial Results and Further Developments

NASA Astrophysics Data System (ADS)

Mai, P.; Burjanek, J.; Delouis, B.; Festa, G.; Francois-Holden, C.; Monelli, D.; Uchide, T.; Zahradnik, J.

2007-12-01

Images of earthquake ruptures, obtained from modelling/inverting seismic and/or geodetic data exhibit a high degree in spatial complexity. This earthquake source heterogeneity controls seismic radiation, and is determined by the details of the dynamic rupture process. In turn, such rupture models are used for studying source dynamics and for ground-motion prediction. But how reliable and trustworthy are these earthquake source inversions? Rupture models for a given earthquake, obtained by different research teams, often display striking disparities (see http://www.seismo.ethz.ch/srcmod) However, well resolved, robust, and hence reliable source-rupture models are an integral part to better understand earthquake source physics and to improve seismic hazard assessment. Therefore it is timely to conduct a large-scale validation exercise for comparing the methods, parameterization and data-handling in earthquake source inversions.We recently started a blind test in which several research groups derive a kinematic rupture model from synthetic seismograms calculated for an input model unknown to the source modelers. The first results, for an input rupture model with heterogeneous slip but constant rise time and rupture velocity, reveal large differences between the input and inverted model in some cases, while a few studies achieve high correlation between the input and inferred model. Here we report on the statistical assessment of the set of inverted rupture models to quantitatively investigate their degree of (dis-)similarity. We briefly discuss the different inversion approaches, their possible strength and weaknesses, and the use of appropriate misfit criteria. Finally we present new blind-test models, with increasing source complexity and ambient noise on the synthetics. The goal is to attract a large group of source modelers to join this source-inversion blindtest in order to conduct a large-scale validation exercise to rigorously asses the performance and reliability of current inversion methods and to discuss future developments.

Non-linear dynamic characteristics and optimal control of giant magnetostrictive film subjected to in-plane stochastic excitation

NASA Astrophysics Data System (ADS)

Zhu, Z. W.; Zhang, W. D.; Xu, J.

2014-03-01

The non-linear dynamic characteristics and optimal control of a giant magnetostrictive film (GMF) subjected to in-plane stochastic excitation were studied. Non-linear differential items were introduced to interpret the hysteretic phenomena of the GMF, and the non-linear dynamic model of the GMF subjected to in-plane stochastic excitation was developed. The stochastic stability was analysed, and the probability density function was obtained. The condition of stochastic Hopf bifurcation and noise-induced chaotic response were determined, and the fractal boundary of the system's safe basin was provided. The reliability function was solved from the backward Kolmogorov equation, and an optimal control strategy was proposed in the stochastic dynamic programming method. Numerical simulation shows that the system stability varies with the parameters, and stochastic Hopf bifurcation and chaos appear in the process; the area of the safe basin decreases when the noise intensifies, and the boundary of the safe basin becomes fractal; the system reliability improved through stochastic optimal control. Finally, the theoretical and numerical results were proved by experiments. The results are helpful in the engineering applications of GMF.

Dynamic behavior of a rolling housing

NASA Astrophysics Data System (ADS)

Gentile, A.; Messina, A. M.; Trentadue, Bartolo

1994-09-01

One of the major objectives of industry is to curtail costs. An element, among others, that enables to achieve such goal is the efficiency of the production cycle machines. Such efficiency lies in the reliability of the upkeeping operations. Among maintenance procedures, measuring and analyzing vibrations is a way to detect structure modifications over the machine's lifespan. Further, the availability of a mathematical model describing the influence of each individual part of the machine on the total dynamic behavior of the whole machine may help localizing breakdowns during diagnosis operations. The paper hereof illustrates an analytical-numerical model which can simulate the behavior of a rolling housing. The aforesaid mathematical model has been obtained by FEM techniques, the dynamic response by mode superposition and the synthesis of the vibration time sequence in the frequency versus by FFT numerical techniques.

Improved dynamical scaling analysis using the kernel method for nonequilibrium relaxation.

PubMed

Echinaka, Yuki; Ozeki, Yukiyasu

2016-10-01

The dynamical scaling analysis for the Kosterlitz-Thouless transition in the nonequilibrium relaxation method is improved by the use of Bayesian statistics and the kernel method. This allows data to be fitted to a scaling function without using any parametric model function, which makes the results more reliable and reproducible and enables automatic and faster parameter estimation. Applying this method, the bootstrap method is introduced and a numerical discrimination for the transition type is proposed.

Analysis of the Multi Strategy Goal Programming for Micro-Grid Based on Dynamic ant Genetic Algorithm

NASA Astrophysics Data System (ADS)

Qiu, J. P.; Niu, D. X.

Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.

A research perspective on white-tailed deer overabundance in the northeastern United States

Treesearch

William M. Healy; David S. deCalesta; Susan L. Stout

1997-01-01

Resolving issues of deer (Odocoileus spp.) over-abundance will require gaining more reliable knowledge about their role in ecosystem dynamics. Science can contribute by advancing knowledge in 4 overlapping spheres of research: model development, measurement techniques, population management, and human behavior.

Reduction of Dynamic Loads in Mine Lifting Installations

NASA Astrophysics Data System (ADS)

Kuznetsov, N. K.; Eliseev, S. V.; Perelygina, A. Yu

2018-01-01

Article is devoted to a problem of decrease in the dynamic loadings arising in transitional operating modes of the mine lifting installations leading to heavy oscillating motions of lifting vessels and decrease in efficiency and reliability of work. The known methods and means of decrease in dynamic loadings and oscillating motions of the similar equipment are analysed. It is shown that an approach based on the concept of the inverse problems of dynamics can be effective method of the solution of this problem. The article describes the design model of a one-ended lifting installation in the form of a two-mass oscillation system, in which the inertial elements are the mass of the lifting vessel and the reduced mass of the engine, reducer, drum and pulley. The simplified mathematical model of this system and results of an efficiency research of an active way of reduction of dynamic loadings of lifting installation on the basis of the concept of the inverse problems of dynamics are given.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

NASA Astrophysics Data System (ADS)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

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

Flueck, Alex

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform formore » modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to model three­phase and single­ phase networks and devices.« less

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

The dynamical analysis of modified two-compartment neuron model and FPGA implementation

NASA Astrophysics Data System (ADS)

Lin, Qianjin; Wang, Jiang; Yang, Shuangming; Yi, Guosheng; Deng, Bin; Wei, Xile; Yu, Haitao

2017-10-01

The complexity of neural models is increasing with the investigation of larger biological neural network, more various ionic channels and more detailed morphologies, and the implementation of biological neural network is a task with huge computational complexity and power consumption. This paper presents an efficient digital design using piecewise linearization on field programmable gate array (FPGA), to succinctly implement the reduced two-compartment model which retains essential features of more complicated models. The design proposes an approximate neuron model which is composed of a set of piecewise linear equations, and it can reproduce different dynamical behaviors to depict the mechanisms of a single neuron model. The consistency of hardware implementation is verified in terms of dynamical behaviors and bifurcation analysis, and the simulation results including varied ion channel characteristics coincide with the biological neuron model with a high accuracy. Hardware synthesis on FPGA demonstrates that the proposed model has reliable performance and lower hardware resource compared with the original two-compartment model. These investigations are conducive to scalability of biological neural network in reconfigurable large-scale neuromorphic system.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Acquisition Community Team Dynamics: The Tuckman Model vs. the DAU Model

DTIC Science & Technology

2007-04-30

courses . These student teams are used to enable the generation of more complex products and to prepare the students for the ...requirement for stage discreteness was met, I developed a stage-separation test that, when applied to the data representing the experience of a... test the reliability, and validate an improved questionnaire instrument that: – Redefines “Storming” with new storming questions Less focused

A stochastic population model for Lepidium papilliferum (Brassicaceae), a rare desert ephemeral with a persistent seed bank

Treesearch

Susan E. Meyer; Dana Quinney; Jay Weaver

2006-01-01

Population viability analysis (PVA) is a valuable tool for rare plant conservation, but PVA for plants with persistent seed banks is difficult without reliable information on seed bank processes. We modeled the population dynamics of the Snake River Plains ephemeral Lepidium papilliferum using data from an 11-yr artificial seed bank experiment to estimate age-specific...

A joint-space numerical model of metabolic energy expenditure for human multibody dynamic system.

PubMed

Kim, Joo H; Roberts, Dustyn

2015-09-01

Metabolic energy expenditure (MEE) is a critical performance measure of human motion. In this study, a general joint-space numerical model of MEE is derived by integrating the laws of thermodynamics and principles of multibody system dynamics, which can evaluate MEE without the limitations inherent in experimental measurements (phase delays, steady state and task restrictions, and limited range of motion) or muscle-space models (complexities and indeterminacies from excessive DOFs, contacts and wrapping interactions, and reliance on in vitro parameters). Muscle energetic components are mapped to the joint space, in which the MEE model is formulated. A constrained multi-objective optimization algorithm is established to estimate the model parameters from experimental walking data also used for initial validation. The joint-space parameters estimated directly from active subjects provide reliable MEE estimates with a mean absolute error of 3.6 ± 3.6% relative to validation values, which can be used to evaluate MEE for complex non-periodic tasks that may not be experimentally verifiable. This model also enables real-time calculations of instantaneous MEE rate as a function of time for transient evaluations. Although experimental measurements may not be completely replaced by model evaluations, predicted quantities can be used as strong complements to increase reliability of the results and yield unique insights for various applications. Copyright © 2015 John Wiley & Sons, Ltd.

A Comparative Data-Based Modeling Study on Respiratory CO2 Gas Exchange during Mechanical Ventilation

PubMed Central

Kim, Chang-Sei; Ansermino, J. Mark; Hahn, Jin-Oh

2016-01-01

The goal of this study is to derive a minimally complex but credible model of respiratory CO2 gas exchange that may be used in systematic design and pilot testing of closed-loop end-tidal CO2 controllers in mechanical ventilation. We first derived a candidate model that captures the essential mechanisms involved in the respiratory CO2 gas exchange process. Then, we simplified the candidate model to derive two lower-order candidate models. We compared these candidate models for predictive capability and reliability using experimental data collected from 25 pediatric subjects undergoing dynamically varying mechanical ventilation during surgical procedures. A two-compartment model equipped with transport delay to account for CO2 delivery between the lungs and the tissues showed modest but statistically significant improvement in predictive capability over the same model without transport delay. Aggregating the lungs and the tissues into a single compartment further degraded the predictive fidelity of the model. In addition, the model equipped with transport delay demonstrated superior reliability to the one without transport delay. Further, the respiratory parameters derived from the model equipped with transport delay, but not the one without transport delay, were physiologically plausible. The results suggest that gas transport between the lungs and the tissues must be taken into account to accurately reproduce the respiratory CO2 gas exchange process under conditions of wide-ranging and dynamically varying mechanical ventilation conditions. PMID:26870728

Editorial: Mathematical Methods and Modeling in Machine Fault Diagnosis

DOE PAGES

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua; ...

2014-12-18

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

A role for low-order system dynamics models in urban health policy making.

PubMed

Newell, Barry; Siri, José

2016-10-01

Cities are complex adaptive systems whose responses to policy initiatives emerge from feedback interactions between their parts. Urban policy makers must routinely deal with both detail and dynamic complexity, coupled with high levels of diversity, uncertainty and contingency. In such circumstances, it is difficult to generate reliable predictions of health-policy outcomes. In this paper we explore the potential for low-order system dynamics (LOSD) models to make a contribution towards meeting this challenge. By definition, LOSD models have few state variables (≤5), illustrate the non-linear effects caused by feedback and accumulation, and focus on endogenous dynamics generated within well-defined boundaries. We suggest that experience with LOSD models can help practitioners to develop an understanding of basic principles of system dynamics, giving them the ability to 'see with new eyes'. Because efforts to build a set of LOSD models can help a transdisciplinary group to develop a shared, coherent view of the problems that they seek to tackle, such models can also become the foundations of 'powerful ideas'. Powerful ideas are conceptual metaphors that provide the members of a policy-making group with the a priori shared context required for effective communication, the co-production of knowledge, and the collaborative development of effective public health policies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effective Dynamic Range and Retest Reliability of Dark-Adapted Two-Color Fundus-Controlled Perimetry in Patients With Macular Diseases.

PubMed

Pfau, Maximilian; Lindner, Moritz; Müller, Philipp L; Birtel, Johannes; Finger, Robert P; Harmening, Wolf M; Fleckenstein, Monika; Holz, Frank G; Schmitz-Valckenberg, Steffen

2017-05-01

To determine the effective dynamic range (EDR), retest reliability, and number of discriminable steps (DS) for mesopic and dark-adapted two-color fundus-controlled perimetry (FCP) using the S-MAIA (Scotopic-Macular Integrity Assessment) "micro-perimeter." In this prospective cross-sectional study, each of the 52 eyes of 52 subjects with various macular diseases (mean age 62.0 ± 16.9 years; range, 19.1-90.1 years) underwent duplicate mesopic (achromatic stimuli, 400-800 nm), dark-adapted cyan (505 nm), and dark-adapted red (627 nm) FCP using a grid of 61 stimuli covering 18° of the central retina. The EDR, the number of DS, and the retest reliability for point-wise sensitivity (PWS) were analyzed. The effects of fixation stability, sensitivity, and age on retest reliability were examined using mixed-effects models. The EDR was 10 to 30 dB with five DS for mesopic and 4 to 17 dB with four DS for dark-adapted cyan and red testing. PWS retest reliability was good among all three types of retinal sensitivity assessments (coefficient of repeatability ±5.79, ±4.72, and ±4.77 dB, respectively) and did not depend on fixation stability or age. PWS had no effect on retest variability in dark-adapted cyan and dark-adapted red testing but had a minor effect in mesopic testing. Combined mesopic and dark-adapted two-color FCP allows for reliable topographic testing of cone and rod function in patients with various macular diseases with and without foveal fixation. Retest reliability is homogeneous across eccentricities and various degrees of scotoma depth, including zones at risk for disease progression. These reliability estimates can serve for the design of future clinical trials.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological dynamic and processes, i. e. sample heterogeneity. For a same streamflow range corresponds different processes such as rising limbs or recession, where uncertainties are different. The dynamical approach improves reliability, skills and sharpness of forecasts and globally reduces confidence intervals width. When compared in details, the dynamical approach allows a noticeable reduction of confidence intervals during recessions where uncertainty is relatively lower and a slight increase of confidence intervals during rising limbs or snowmelt where uncertainty is greater. The dynamic approach, validated by forecaster's experience that considered the empirical approach not discriminative enough, improved forecaster's confidence and communication of uncertainties. Montanari, A. and Brath, A., (2004). A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40, W01106, doi:10.1029/2003WR002540. Schaefli, B., Balin Talamba, D. and Musy, A., (2007). Quantifying hydrological modeling errors through a mixture of normal distributions. Journal of Hydrology, 332, 303-315.

Change Detection, Multiple Controllers, and Dynamic Environments: Insights from the Brain

ERIC Educational Resources Information Center

Pearson, John M.; Platt, Michael L.

2013-01-01

Foundational studies in decision making focused on behavior as the most accessible and reliable data on which to build theories of choice. More recent work, however, has incorporated neural data to provide insights unavailable from behavior alone. Among other contributions, these studies have validated reinforcement learning models by…

A Computational Model of Event Segmentation from Perceptual Prediction

ERIC Educational Resources Information Center

Reynolds, Jeremy R.; Zacks, Jeffrey M.; Braver, Todd S.

2007-01-01

People tend to perceive ongoing continuous activity as series of discrete events. This partitioning of continuous activity may occur, in part, because events correspond to dynamic patterns that have recurred across different contexts. Recurring patterns may lead to reliable sequential dependencies in observers' experiences, which then can be used…

Reliable Communication Models in Interdependent Critical Infrastructure Networks

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

Lee, Sangkeun; Chinthavali, Supriya; Shankar, Mallikarjun

Modern critical infrastructure networks are becoming increasingly interdependent where the failures in one network may cascade to other dependent networks, causing severe widespread national-scale failures. A number of previous efforts have been made to analyze the resiliency and robustness of interdependent networks based on different models. However, communication network, which plays an important role in today's infrastructures to detect and handle failures, has attracted little attention in the interdependency studies, and no previous models have captured enough practical features in the critical infrastructure networks. In this paper, we study the interdependencies between communication network and other kinds of critical infrastructuremore » networks with an aim to identify vulnerable components and design resilient communication networks. We propose several interdependency models that systematically capture various features and dynamics of failures spreading in critical infrastructure networks. We also discuss several research challenges in building reliable communication solutions to handle failures in these models.« less

Model structure identification for wastewater treatment simulation based on computational fluid dynamics.

PubMed

Alex, J; Kolisch, G; Krause, K

2002-01-01

The objective of this presented project is to use the results of an CFD simulation to automatically, systematically and reliably generate an appropriate model structure for simulation of the biological processes using CSTR activated sludge compartments. Models and dynamic simulation have become important tools for research but also increasingly for the design and optimisation of wastewater treatment plants. Besides the biological models several cases are reported about the application of computational fluid dynamics ICFD) to wastewater treatment plants. One aim of the presented method to derive model structures from CFD results is to exclude the influence of empirical structure selection to the result of dynamic simulations studies of WWTPs. The second application of the approach developed is the analysis of badly performing treatment plants where the suspicion arises that bad flow behaviour such as short cut flows is part of the problem. The method suggested requires as the first step the calculation of fluid dynamics of the biological treatment step at different loading situations by use of 3-dimensional CFD simulation. The result of this information is used to generate a suitable model structure for conventional dynamic simulation of the treatment plant by use of a number of CSTR modules with a pattern of exchange flows between the tanks automatically. The method is explained in detail and the application to the WWTP Wuppertal Buchenhofen is presented.

Engineering evaluation of SSME dynamic data from engine tests and SSV flights

NASA Technical Reports Server (NTRS)

1986-01-01

An engineering evaluation of dynamic data from SSME hot firing tests and SSV flights is summarized. The basic objective of the study is to provide analyses of vibration, strain and dynamic pressure measurements in support of MSFC performance and reliability improvement programs. A brief description of the SSME test program is given and a typical test evaluation cycle reviewed. Data banks generated to characterize SSME component dynamic characteristics are described and statistical analyses performed on these data base measurements are discussed. Analytical models applied to define the dynamic behavior of SSME components (such as turbopump bearing elements and the flight accelerometer safety cut-off system) are also summarized. Appendices are included to illustrate some typical tasks performed under this study.

Simulating the room-temperature dynamic motion of a ferromagnetic vortex in a bistable potential

NASA Astrophysics Data System (ADS)

Haber, E.; Badea, R.; Berezovsky, J.

2018-05-01

The ability to precisely and reliably control the dynamics of ferromagnetic (FM) vortices could lead to novel nonvolatile memory devices and logic gates. Intrinsic and fabricated defects in the FM material can pin vortices and complicate the dynamics. Here, we simulated switching a vortex between bistable pinning sites using magnetic field pulses. The dynamic motion was modeled with the Thiele equation for a massless, rigid vortex subject to room-temperature thermal noise. The dynamics were explored both when the system was at zero temperature and at room-temperature. The probability of switching for different pulses was calculated, and the major features are explained using the basins of attraction map of the two pinning sites.

Non-linear dynamic analysis of geared systems, part 2

NASA Technical Reports Server (NTRS)

Singh, Rajendra; Houser, Donald R.; Kahraman, Ahmet

1990-01-01

A good understanding of the steady state dynamic behavior of a geared system is required in order to design reliable and quiet transmissions. This study focuses on a system containing a spur gear pair with backlash and periodically time-varying mesh stiffness, and rolling element bearings with clearance type non-linearities. A dynamic finite element model of the linear time-invariant (LTI) system is developed. Effects of several system parameters, such as torsional and transverse flexibilities of the shafts and prime mover/load inertias, on free and force vibration characteristics are investigated. Several reduced order LTI models are developed and validated by comparing their eigen solution with the finite element model results. Several key system parameters such as mean load and damping ratio are identified and their effects on the non-linear frequency response are evaluated quantitatively. Other fundamental issues such as the dynamic coupling between non-linear modes, dynamic interactions between component non-linearities and time-varying mesh stiffness, and the existence of subharmonic and chaotic solutions including routes to chaos have also been examined in depth.

Extended applications of track irregularity probabilistic model and vehicle-slab track coupled model on dynamics of railway systems

NASA Astrophysics Data System (ADS)

Xu, Lei; Zhai, Wanming; Gao, Jianmin

2017-11-01

Track irregularities are inevitably in a process of stochastic evolution due to the uncertainty and continuity of wheel-rail interactions. For depicting the dynamic behaviours of vehicle-track coupling system caused by track random irregularities thoroughly, it is a necessity to develop a track irregularity probabilistic model to simulate rail surface irregularities with ergodic properties on amplitudes, wavelengths and probabilities, and to build a three-dimensional vehicle-track coupled model by properly considering the wheel-rail nonlinear contact mechanisms. In the present study, the vehicle-track coupled model is programmed by combining finite element method with wheel-rail coupling model firstly. Then, in light of the capability of power spectral density (PSD) in characterising amplitudes and wavelengths of stationary random signals, a track irregularity probabilistic model is presented to reveal and simulate the whole characteristics of track irregularity PSD. Finally, extended applications from three aspects, that is, extreme analysis, reliability analysis and response relationships between dynamic indices, are conducted to the evaluation and application of the proposed models.

Linear and evolutionary polynomial regression models to forecast coastal dynamics: Comparison and reliability assessment

NASA Astrophysics Data System (ADS)

Bruno, Delia Evelina; Barca, Emanuele; Goncalves, Rodrigo Mikosz; de Araujo Queiroz, Heithor Alexandre; Berardi, Luigi; Passarella, Giuseppe

2018-01-01

In this paper, the Evolutionary Polynomial Regression data modelling strategy has been applied to study small scale, short-term coastal morphodynamics, given its capability for treating a wide database of known information, non-linearly. Simple linear and multilinear regression models were also applied to achieve a balance between the computational load and reliability of estimations of the three models. In fact, even though it is easy to imagine that the more complex the model, the more the prediction improves, sometimes a "slight" worsening of estimations can be accepted in exchange for the time saved in data organization and computational load. The models' outcomes were validated through a detailed statistical, error analysis, which revealed a slightly better estimation of the polynomial model with respect to the multilinear model, as expected. On the other hand, even though the data organization was identical for the two models, the multilinear one required a simpler simulation setting and a faster run time. Finally, the most reliable evolutionary polynomial regression model was used in order to make some conjecture about the uncertainty increase with the extension of extrapolation time of the estimation. The overlapping rate between the confidence band of the mean of the known coast position and the prediction band of the estimated position can be a good index of the weakness in producing reliable estimations when the extrapolation time increases too much. The proposed models and tests have been applied to a coastal sector located nearby Torre Colimena in the Apulia region, south Italy.

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Reliable fuzzy H∞ control for active suspension of in-wheel motor driven electric vehicles with dynamic damping

NASA Astrophysics Data System (ADS)

Shao, Xinxin; Naghdy, Fazel; Du, Haiping

2017-03-01

A fault-tolerant fuzzy H∞ control design approach for active suspension of in-wheel motor driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The controller is designed based on the quarter-car active suspension model with a dynamic-damping-in-wheel-motor-driven-system, in which the suspended motor is operated as a dynamic absorber. The Takagi-Sugeno (T-S) fuzzy model is used to model this suspension with possible sprung mass variation. The parallel-distributed compensation (PDC) scheme is deployed to derive a fault-tolerant fuzzy controller for the T-S fuzzy suspension model. In order to reduce the motor wear caused by the dynamic force transmitted to the in-wheel motor, the dynamic force is taken as an additional controlled output besides the traditional optimization objectives such as sprung mass acceleration, suspension deflection and actuator saturation. The H∞ performance of the proposed controller is derived as linear matrix inequalities (LMIs) comprising three equality constraints which are solved efficiently by means of MATLAB LMI Toolbox. The proposed controller is applied to an electric vehicle suspension and its effectiveness is demonstrated through computer simulation.

A Historical Perspective on Dynamics Testing at the Langley Research Center

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Kvaternik, Raymond G.; Hanks, Brantley R.

2000-01-01

The experience and advancement of Structural dynamics testing for space system applications at the Langley Research Center of the National Aeronautics and Space Administration (NASA) over the past four decades is reviewed. This experience began in the 1960's with the development of a technology base using a variety of physical models to explore dynamic phenomena and to develop reliable analytical modeling capability for space systems. It continued through the 1970's and 80's with the development of rapid, computer-aided test techniques, the testing of low-natural frequency, gravity-sensitive systems, the testing of integrated structures with active flexible motion control, and orbital flight measurements, It extended into the 1990's where advanced computerized system identification methods were developed for estimating the dynamic states of complex, lightweight, flexible aerospace systems, The scope of discussion in this paper includes ground and flight tests and summarizes lessons learned in both successes and failures.

Thermal modal analysis of novel non-pneumatic mechanical elastic wheel based on FEM and EMA

NASA Astrophysics Data System (ADS)

Zhao, Youqun; Zhu, Mingmin; Lin, Fen; Xiao, Zhen; Li, Haiqing; Deng, Yaoji

2018-01-01

A combination of Finite Element Method (FEM) and Experiment Modal Analysis (EMA) have been employed here to characterize the structural dynamic response of mechanical elastic wheel (ME-Wheel) operating under a specific thermal environment. The influence of high thermal condition on the structural dynamic response of ME-Wheel is investigated. The obtained results indicate that the EMA results are in accordance with those obtained using the proposed Finite Element (FE) model, indicting the high reliability of this FE model applied in analyzing the modal of ME-Wheel working under practical thermal environment. It demonstrates that the structural dynamic response of ME-Wheel operating under a specific thermal condition can be predicted and evaluated using the proposed analysis method, which is beneficial for the dynamic optimization design of the wheel structure to avoid tire temperature related vibration failure and improve safety of tire.

Using 3D infrared imaging to calibrate and refine computational fluid dynamic modeling for large computer and data centers

NASA Astrophysics Data System (ADS)

Stockton, Gregory R.

2011-05-01

Over the last 10 years, very large government, military, and commercial computer and data center operators have spent millions of dollars trying to optimally cool data centers as each rack has begun to consume as much as 10 times more power than just a few years ago. In fact, the maximum amount of data computation in a computer center is becoming limited by the amount of available power, space and cooling capacity at some data centers. Tens of millions of dollars and megawatts of power are being annually spent to keep data centers cool. The cooling and air flows dynamically change away from any predicted 3-D computational fluid dynamic modeling during construction and as time goes by, and the efficiency and effectiveness of the actual cooling rapidly departs even farther from predicted models. By using 3-D infrared (IR) thermal mapping and other techniques to calibrate and refine the computational fluid dynamic modeling and make appropriate corrections and repairs, the required power for data centers can be dramatically reduced which reduces costs and also improves reliability.

A new modal-based approach for modelling the bump foil structure in the simultaneous solution of foil-air bearing rotor dynamic problems

NASA Astrophysics Data System (ADS)

Bin Hassan, M. F.; Bonello, P.

2017-05-01

Recently-proposed techniques for the simultaneous solution of foil-air bearing (FAB) rotor dynamic problems have been limited to a simple bump foil model in which the individual bumps were modelled as independent spring-damper (ISD) subsystems. The present paper addresses this limitation by introducing a modal model of the bump foil structure into the simultaneous solution scheme. The dynamics of the corrugated bump foil structure are first studied using the finite element (FE) technique. This study is experimentally validated using a purpose-made corrugated foil structure. Based on the findings of this study, it is proposed that the dynamics of the full foil structure, including bump interaction and foil inertia, can be represented by a modal model comprising a limited number of modes. This full foil structure modal model (FFSMM) is then adapted into the rotordynamic FAB problem solution scheme, instead of the ISD model. Preliminary results using the FFSMM under static and unbalance excitation conditions are proven to be reliable by comparison against the corresponding ISD foil model results and by cross-correlating different methods for computing the deflection of the full foil structure. The rotor-bearing model is also validated against experimental and theoretical results in the literature.

Study on dynamic response measurement of the submarine pipeline by full-term FBG sensors.

PubMed

Zhou, Jinghai; Sun, Li; Li, Hongnan

2014-01-01

The field of structural health monitoring is concerned with accurately and reliably assessing the integrity of a given structure to reduce ownership costs, increase operational lifetime, and improve safety. In structural health monitoring systems, fiber Bragg grating (FBG) is a promising measurement technology for its superior ability of explosion proof, immunity to electromagnetic interference, and high accuracy. This paper is a study on the dynamic characteristics of fiber Bragg grating (FBG) sensors applied to a submarine pipeline, as well as an experimental investigation on a laboratory model of the pipeline. The dynamic response of a submarine pipeline under seismic excitation is a coupled vibration of liquid and solid interaction. FBG sensors and strain gauges are used to monitor the dynamic response of a submarine pipeline model under a variety of dynamic loading conditions and the maximum working frequency of an FBG strain sensor is calculated according to its dynamic strain responses. Based on the theoretical and experimental results, it can be concluded that FBG sensor is superior to strain gauge and satisfies the demand of dynamic strain measurement.

Study on Dynamic Response Measurement of the Submarine Pipeline by Full-Term FBG Sensors

PubMed Central

Zhou, Jinghai; Sun, Li; Li, Hongnan

2014-01-01

The field of structural health monitoring is concerned with accurately and reliably assessing the integrity of a given structure to reduce ownership costs, increase operational lifetime, and improve safety. In structural health monitoring systems, fiber Bragg grating (FBG) is a promising measurement technology for its superior ability of explosion proof, immunity to electromagnetic interference, and high accuracy. This paper is a study on the dynamic characteristics of fiber Bragg grating (FBG) sensors applied to a submarine pipeline, as well as an experimental investigation on a laboratory model of the pipeline. The dynamic response of a submarine pipeline under seismic excitation is a coupled vibration of liquid and solid interaction. FBG sensors and strain gauges are used to monitor the dynamic response of a submarine pipeline model under a variety of dynamic loading conditions and the maximum working frequency of an FBG strain sensor is calculated according to its dynamic strain responses. Based on the theoretical and experimental results, it can be concluded that FBG sensor is superior to strain gauge and satisfies the demand of dynamic strain measurement. PMID:24971391

Improved reliability of wind turbine towers with active tuned mass dampers (ATMDs)

NASA Astrophysics Data System (ADS)

Fitzgerald, Breiffni; Sarkar, Saptarshi; Staino, Andrea

2018-04-01

Modern multi-megawatt wind turbines are composed of slender, flexible, and lightly damped blades and towers. These components exhibit high susceptibility to wind-induced vibrations. As the size, flexibility and cost of the towers have increased in recent years, the need to protect these structures against damage induced by turbulent aerodynamic loading has become apparent. This paper combines structural dynamic models and probabilistic assessment tools to demonstrate improvements in structural reliability when modern wind turbine towers are equipped with active tuned mass dampers (ATMDs). This study proposes a multi-modal wind turbine model for wind turbine control design and analysis. This study incorporates an ATMD into the tower of this model. The model is subjected to stochastically generated wind loads of varying speeds to develop wind-induced probabilistic demand models for towers of modern multi-megawatt wind turbines under structural uncertainty. Numerical simulations have been carried out to ascertain the effectiveness of the active control system to improve the structural performance of the wind turbine and its reliability. The study constructs fragility curves, which illustrate reductions in the vulnerability of towers to wind loading owing to the inclusion of the damper. Results show that the active controller is successful in increasing the reliability of the tower responses. According to the analysis carried out in this paper, a strong reduction of the probability of exceeding a given displacement at the rated wind speed has been observed.

Infrared imaging and acoustic sizing of a bubble inside a micro-electro-mechanical system piezo ink channel

NASA Astrophysics Data System (ADS)

van der Bos, Arjan; Segers, Tim; Jeurissen, Roger; van den Berg, Marc; Reinten, Hans; Wijshoff, Herman; Versluis, Michel; Lohse, Detlef

2011-08-01

Piezo drop-on-demand inkjet printers are used in an increasing number of applications because of their reliable deposition of droplets onto a substrate. Droplets of a few picoliters are ejected from an inkjet nozzle at frequencies of up to 100 kHz. However, the entrapment of an air microbubble in the ink channel can severely impede the productivity and reliability of the printing system. The air bubble disturbs the channel acoustics, resulting in disrupted drop formation or failure of the jetting process. Here we study a micro-electro-mechanical systems-based printhead. By using the actuating piezo transducer in receive mode, the acoustical field inside the channel was monitored, clearly identifying the presence of an air microbubble inside the channel during failure of the jetting process. The infrared visualization technique allowed for the accurate sizing of the bubble, including its dynamics, inside the intact printhead. A model was developed to calculate the mutual interaction between the channel acoustics and the bubble dynamics. The model was validated by simultaneous acoustical and infrared detection of the bubble. The model can predict the presence and size of entrapped air bubbles inside an operating ink channel purely from the acoustic response.

Efficient digital implementation of a conductance-based globus pallidus neuron and the dynamics analysis

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Wei, Xile; Deng, Bin; Liu, Chen; Li, Huiyan; Wang, Jiang

2018-03-01

Balance between biological plausibility of dynamical activities and computational efficiency is one of challenging problems in computational neuroscience and neural system engineering. This paper proposes a set of efficient methods for the hardware realization of the conductance-based neuron model with relevant dynamics, targeting reproducing the biological behaviors with low-cost implementation on digital programmable platform, which can be applied in wide range of conductance-based neuron models. Modified GP neuron models for efficient hardware implementation are presented to reproduce reliable pallidal dynamics, which decode the information of basal ganglia and regulate the movement disorder related voluntary activities. Implementation results on a field-programmable gate array (FPGA) demonstrate that the proposed techniques and models can reduce the resource cost significantly and reproduce the biological dynamics accurately. Besides, the biological behaviors with weak network coupling are explored on the proposed platform, and theoretical analysis is also made for the investigation of biological characteristics of the structured pallidal oscillator and network. The implementation techniques provide an essential step towards the large-scale neural network to explore the dynamical mechanisms in real time. Furthermore, the proposed methodology enables the FPGA-based system a powerful platform for the investigation on neurodegenerative diseases and real-time control of bio-inspired neuro-robotics.

Extreme learning machine for reduced order modeling of turbulent geophysical flows.

PubMed

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

NASA Astrophysics Data System (ADS)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Verification and Validation of the New Dynamic Mooring Modules Available in FAST v8: Preprint

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

Wendt, Fabian; Robertson, Amy; Jonkman, Jason

2016-08-01

The open-source aero-hydro-servo-elastic wind turbine simulation software, FAST v8, was recently coupled to two newly developed mooring dynamics modules: MoorDyn and FEAMooring. MoorDyn is a lumped-mass-based mooring dynamics module developed by the University of Maine, and FEAMooring is a finite-element-based mooring dynamics module developed by Texas A&M University. This paper summarizes the work performed to verify and validate these modules against other mooring models and measured test data to assess their reliability and accuracy. The quality of the fairlead load predictions by the open-source mooring modules MoorDyn and FEAMooring appear to be largely equivalent to what is predicted by themore » commercial tool OrcaFlex. Both mooring dynamic model predictions agree well with the experimental data, considering the given limitations in the accuracy of the platform hydrodynamic load calculation and the quality of the measurement data.« less

Verification and Validation of the New Dynamic Mooring Modules Available in FAST v8

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

Wendt, Fabian F.; Andersen, Morten T.; Robertson, Amy N.

2016-07-01

The open-source aero-hydro-servo-elastic wind turbine simulation software, FAST v8, was recently coupled to two newly developed mooring dynamics modules: MoorDyn and FEAMooring. MoorDyn is a lumped-mass-based mooring dynamics module developed by the University of Maine, and FEAMooring is a finite-element-based mooring dynamics module developed by Texas A&M University. This paper summarizes the work performed to verify and validate these modules against other mooring models and measured test data to assess their reliability and accuracy. The quality of the fairlead load predictions by the open-source mooring modules MoorDyn and FEAMooring appear to be largely equivalent to what is predicted by themore » commercial tool OrcaFlex. Both mooring dynamic model predictions agree well with the experimental data, considering the given limitations in the accuracy of the platform hydrodynamic load calculation and the quality of the measurement data.« less

Recent Developments at the NASA Langley Research Center National Transonic Facility

NASA Technical Reports Server (NTRS)

Paryz, Roman W.

2011-01-01

Several upgrade projects have been completed or are just getting started at the NASA Langley Research Center National Transonic Facility. These projects include a new high capacity semi-span balance, model dynamics damping system, semi-span model check load stand, data acquisition system upgrade, facility automation system upgrade and a facility reliability assessment. This presentation will give a brief synopsis of each of these efforts.

Using a Multivariate Multilevel Polytomous Item Response Theory Model to Study Parallel Processes of Change: The Dynamic Association between Adolescents' Social Isolation and Engagement with Delinquent Peers in the National Youth Survey

ERIC Educational Resources Information Center

Hsieh, Chueh-An; von Eye, Alexander A.; Maier, Kimberly S.

2010-01-01

The application of multidimensional item response theory models to repeated observations has demonstrated great promise in developmental research. It allows researchers to take into consideration both the characteristics of item response and measurement error in longitudinal trajectory analysis, which improves the reliability and validity of the…

Development of a clinical static and dynamic standing balance measurement tool appropriate for use in adolescents.

PubMed

Emery, Carolyn A; Cassidy, J David; Klassen, Terry P; Rosychuk, Rhonda J; Rowe, Brian B

2005-06-01

There is a need in sports medicine for a static and dynamic standing balance measure to quantify balance ability in adolescents. The purposes of this study were to determine the test-retest reliability of timed static (eyes open) and dynamic (eyes open and eyes closed) unipedal balance measurements and to examine factors associated with balance. Adolescents (n=123) were randomly selected from 10 Calgary high schools. This study used a repeated-measures design. One rater measured unipedal standing balance, including timed eyes-closed static (ECS), eyes-open dynamic (EOD), and eyes-closed dynamic (ECD) balance at baseline and 1 week later. Dynamic balance was measured on a foam surface. Reliability was examined using both intraclass correlation coefficients (ICCs) and Bland and Altman statistical techniques. Multiple linear regressions were used to examine other potentially influencing factors. Based on ICCs, test-retest reliability was adequate for ECS, EOD, and ECD balance (ICC=.69, .59, and .46, respectively). The results of Bland and Altman methods, however, suggest that caution is required in interpreting reliability based on ICCs alone. Although both ECS balance and ECD balance appear to demonstrate adequate test-retest reliability by ICC, Bland and Altman methods of agreement demonstrate sufficient reliability for ECD balance only. Thirty percent of the subjects reached the 180-second maximum on EOD balance, suggesting that this test is not appropriate for use in this population. Balance ability (ECS and ECD) was better in adolescents with no past history of lower-extremity injury. Timed ECD balance is an appropriate and reliable clinical measurement for use in adolescents and is influenced by previous injury.

Reliability and Concurrent Validity of Dynamic Rotator Stability Test-A Cross Sectional study.

PubMed

Binoy Mathew, K V; Eapen, Charu; Kumar, P Senthil

2012-01-01

To find intra rater and inter rater reliability of Dynamic Rotator Stability Test (DRST) and to find concurrent validity of Dynamic Rotator Stability Test (DRST) with University of Pennsylvania Shoulder Score (PENN) Scale. 40 subjects of either gender between the age group of 18-70 with painful shoulder conditions of musculoskeletal origin was selected through convenient sampling. Tester 1 and tester 2 administered DRST and PENN scale randomly. In a subgroup of 20 subjects DRST was administered by both the testers to find the inter rater reliability. 180° Standard Universal Goniometer was used to take measurements. For intra-rater reliability, all the test variables were showing highly significant correlation (p=.94 - 1). For inter -rater, with tester 2, test variables like position, ROM, force, direction of abnormal translation, pain during the test, compensatory movement during test were found to be significant (p=.71-1).only some variables of DRST showed significant correlation with PENN scale (P=.320-.450). Dynamic Rotator Stability Test has good intra rater and moderate inter rater reliability. Concurrent validity of Dynamic Rotator Stability Test was found to be poor when compared to PENN Shoulder Score.

Light curves for bump Cepheids computed with a dynamically zoned pulsation code

NASA Technical Reports Server (NTRS)

Adams, T. F.; Castor, J. I.; Davis, C. G.

1980-01-01

The dynamically zoned pulsation code developed by Castor, Davis, and Davison was used to recalculate the Goddard model and to calculate three other Cepheid models with the same period (9.8 days). This family of models shows how the bumps and other features of the light and velocity curves change as the mass is varied at constant period. The use of a code that is capable of producing reliable light curves demonstrates that the light and velocity curves for 9.8 day Cepheid models with standard homogeneous compositions do not show bumps like those that are observed unless the mass is significantly lower than the 'evolutionary mass.' The light and velocity curves for the Goddard model presented here are similar to those computed independently by Fischel, Sparks, and Karp. They should be useful as standards for future investigators.

Specific spice modeling of microcrystalline silicon TFTs

NASA Astrophysics Data System (ADS)

Moustapha, O.; Bui, V. D.; Bonnassieux, Y.; Parey, J. Y.

2008-03-01

In this paper we present a specific spice static and dynamic model of microcrystalline silicon (μc-Si) thin film transistors (TFTs) taking into account the access resistances and the capacitors contributions. The previously existing models of amorphous silicon and polysilicon TFTs were not completely suited, so we combined them to build a new specific model of μc-Si TFTs. The reliability of the model is then checked by the comparison of experimental measurements to simulations and by simulating the characteristics of some electronic devices (OLED pixels, inverters, and so on).

Non-linear dynamic characteristics and optimal control of giant magnetostrictive film subjected to in-plane stochastic excitation

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

Zhu, Z. W., E-mail: zhuzhiwen@tju.edu.cn; Tianjin Key Laboratory of Non-linear Dynamics and Chaos Control, 300072, Tianjin; Zhang, W. D., E-mail: zhangwenditju@126.com

2014-03-15

The non-linear dynamic characteristics and optimal control of a giant magnetostrictive film (GMF) subjected to in-plane stochastic excitation were studied. Non-linear differential items were introduced to interpret the hysteretic phenomena of the GMF, and the non-linear dynamic model of the GMF subjected to in-plane stochastic excitation was developed. The stochastic stability was analysed, and the probability density function was obtained. The condition of stochastic Hopf bifurcation and noise-induced chaotic response were determined, and the fractal boundary of the system's safe basin was provided. The reliability function was solved from the backward Kolmogorov equation, and an optimal control strategy was proposedmore » in the stochastic dynamic programming method. Numerical simulation shows that the system stability varies with the parameters, and stochastic Hopf bifurcation and chaos appear in the process; the area of the safe basin decreases when the noise intensifies, and the boundary of the safe basin becomes fractal; the system reliability improved through stochastic optimal control. Finally, the theoretical and numerical results were proved by experiments. The results are helpful in the engineering applications of GMF.« less

Inferring microbial interaction networks from metagenomic data using SgLV-EKF algorithm.

PubMed

Alshawaqfeh, Mustafa; Serpedin, Erchin; Younes, Ahmad Bani

2017-03-27

Inferring the microbial interaction networks (MINs) and modeling their dynamics are critical in understanding the mechanisms of the bacterial ecosystem and designing antibiotic and/or probiotic therapies. Recently, several approaches were proposed to infer MINs using the generalized Lotka-Volterra (gLV) model. Main drawbacks of these models include the fact that these models only consider the measurement noise without taking into consideration the uncertainties in the underlying dynamics. Furthermore, inferring the MIN is characterized by the limited number of observations and nonlinearity in the regulatory mechanisms. Therefore, novel estimation techniques are needed to address these challenges. This work proposes SgLV-EKF: a stochastic gLV model that adopts the extended Kalman filter (EKF) algorithm to model the MIN dynamics. In particular, SgLV-EKF employs a stochastic modeling of the MIN by adding a noise term to the dynamical model to compensate for modeling uncertainties. This stochastic modeling is more realistic than the conventional gLV model which assumes that the MIN dynamics are perfectly governed by the gLV equations. After specifying the stochastic model structure, we propose the EKF to estimate the MIN. SgLV-EKF was compared with two similarity-based algorithms, one algorithm from the integral-based family and two regression-based algorithms, in terms of the achieved performance on two synthetic data-sets and two real data-sets. The first data-set models the randomness in measurement data, whereas, the second data-set incorporates uncertainties in the underlying dynamics. The real data-sets are provided by a recent study pertaining to an antibiotic-mediated Clostridium difficile infection. The experimental results demonstrate that SgLV-EKF outperforms the alternative methods in terms of robustness to measurement noise, modeling errors, and tracking the dynamics of the MIN. Performance analysis demonstrates that the proposed SgLV-EKF algorithm represents a powerful and reliable tool to infer MINs and track their dynamics.

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

PubMed

Amozegar, M; Khorasani, K

2016-04-01

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identified by constructing three separate or individual dynamic neural network architectures. Specifically, a dynamic multi-layer perceptron (MLP), a dynamic radial-basis function (RBF) neural network, and a dynamic support vector machine (SVM) are trained to individually identify and represent the gas turbine engine dynamics. Next, three ensemble-based techniques are developed to represent the gas turbine engine dynamics, namely, two heterogeneous ensemble models and one homogeneous ensemble model. It is first shown that all ensemble approaches do significantly improve the overall performance and accuracy of the developed system identification scheme when compared to each of the stand-alone solutions. The best selected stand-alone model (i.e., the dynamic RBF network) and the best selected ensemble architecture (i.e., the heterogeneous ensemble) in terms of their performances in achieving an accurate system identification are then selected for solving the FDI task. The required residual signals are generated by using both a single model-based solution and an ensemble-based solution under various gas turbine engine health conditions. Our extensive simulation studies demonstrate that the fault detection and isolation task achieved by using the residuals that are obtained from the dynamic ensemble scheme results in a significantly more accurate and reliable performance as illustrated through detailed quantitative confusion matrix analysis and comparative studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a morphology-based modeling technique for tracking solid-body displacements: examining the reliability of a potential MRI-only approach for joint kinematics assessment.

PubMed

Mahato, Niladri K; Montuelle, Stephane; Cotton, John; Williams, Susan; Thomas, James; Clark, Brian

2016-05-18

Single or biplanar video radiography and Roentgen stereophotogrammetry (RSA) techniques used for the assessment of in-vivo joint kinematics involves application of ionizing radiation, which is a limitation for clinical research involving human subjects. To overcome this limitation, our long-term goal is to develop a magnetic resonance imaging (MRI)-only, three dimensional (3-D) modeling technique that permits dynamic imaging of joint motion in humans. Here, we present our initial findings, as well as reliability data, for an MRI-only protocol and modeling technique. We developed a morphology-based motion-analysis technique that uses MRI of custom-built solid-body objects to animate and quantify experimental displacements between them. The technique involved four major steps. First, the imaging volume was calibrated using a custom-built grid. Second, 3-D models were segmented from axial scans of two custom-built solid-body cubes. Third, these cubes were positioned at pre-determined relative displacements (translation and rotation) in the magnetic resonance coil and scanned with a T1 and a fast contrast-enhanced pulse sequences. The digital imaging and communications in medicine (DICOM) images were then processed for animation. The fourth step involved importing these processed images into an animation software, where they were displayed as background scenes. In the same step, 3-D models of the cubes were imported into the animation software, where the user manipulated the models to match their outlines in the scene (rotoscoping) and registered the models into an anatomical joint system. Measurements of displacements obtained from two different rotoscoping sessions were tested for reliability using coefficient of variations (CV), intraclass correlation coefficients (ICC), Bland-Altman plots, and Limits of Agreement analyses. Between-session reliability was high for both the T1 and the contrast-enhanced sequences. Specifically, the average CVs for translation were 4.31 % and 5.26 % for the two pulse sequences, respectively, while the ICCs were 0.99 for both. For rotation measures, the CVs were 3.19 % and 2.44 % for the two pulse sequences with the ICCs being 0.98 and 0.97, respectively. A novel biplanar imaging approach also yielded high reliability with mean CVs of 2.66 % and 3.39 % for translation in the x- and z-planes, respectively, and ICCs of 0.97 in both planes. This work provides basic proof-of-concept for a reliable marker-less non-ionizing-radiation-based quasi-dynamic motion quantification technique that can potentially be developed into a tool for real-time joint kinematics analysis.

Comparison of different incremental analysis update schemes in a realistic assimilation system with Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Yan, Y.; Barth, A.; Beckers, J. M.; Brankart, J. M.; Brasseur, P.; Candille, G.

2017-07-01

In this paper, three incremental analysis update schemes (IAU 0, IAU 50 and IAU 100) are compared in the same assimilation experiments with a realistic eddy permitting primitive equation model of the North Atlantic Ocean using the Ensemble Kalman Filter. The difference between the three IAU schemes lies on the position of the increment update window. The relevance of each IAU scheme is evaluated through analyses on both thermohaline and dynamical variables. The validation of the assimilation results is performed according to both deterministic and probabilistic metrics against different sources of observations. For deterministic validation, the ensemble mean and the ensemble spread are compared to the observations. For probabilistic validation, the continuous ranked probability score (CRPS) is used to evaluate the ensemble forecast system according to reliability and resolution. The reliability is further decomposed into bias and dispersion by the reduced centred random variable (RCRV) score. The obtained results show that 1) the IAU 50 scheme has the same performance as the IAU 100 scheme 2) the IAU 50/100 schemes outperform the IAU 0 scheme in error covariance propagation for thermohaline variables in relatively stable region, while the IAU 0 scheme outperforms the IAU 50/100 schemes in dynamical variables estimation in dynamically active region 3) in case with sufficient number of observations and good error specification, the impact of IAU schemes is negligible. The differences between the IAU 0 scheme and the IAU 50/100 schemes are mainly due to different model integration time and different instability (density inversion, large vertical velocity, etc.) induced by the increment update. The longer model integration time with the IAU 50/100 schemes, especially the free model integration, on one hand, allows for better re-establishment of the equilibrium model state, on the other hand, smooths the strong gradients in dynamically active region.

Modeling and experimental investigation of thermal-mechanical-electric coupling dynamics in a standing wave ultrasonic motor

NASA Astrophysics Data System (ADS)

Li, Xiang; Yao, Zhiyuan; He, Yigang; Dai, Shichao

2017-09-01

Ultrasonic motor operation relies on high-frequency vibration of a piezoelectric vibrator and interface friction between the stator and rotor/slider, which can cause temperature rise of the motor under continuous operation, and can affect motor parameters and performance in turn. In this paper, an integral model is developed to study the thermal-mechanical-electric coupling dynamics in a typical standing wave ultrasonic motor. Stick-slip motion at the contact interface and the temperature dependence of material parameters of the stator are taken into account in this model. The elastic, piezoelectric and dielectric material coefficients of the piezoelectric ceramic, as a function of temperature, are determined experimentally using a resonance method. The critical parameters in the model are identified via measured results. The resulting model can be used to evaluate the variation in output characteristics of the motor caused by the thermal-mechanical-electric coupling effects. Furthermore, the dynamic temperature rise of the motor can be accurately predicted under different input parameters using the developed model, which will contribute to improving the reliable life of a motor for long-term running.

Lewis Structures Technology, 1988. Volume 2: Structural Mechanics

NASA Technical Reports Server (NTRS)

1988-01-01

Lewis Structures Div. performs and disseminates results of research conducted in support of aerospace engine structures. These results have a wide range of applicability to practitioners of structural engineering mechanics beyond the aerospace arena. The engineering community was familiarized with the depth and range of research performed by the division and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive evaluation, constitutive models and experimental capabilities, dynamic systems, fatigue and damage, wind turbines, hot section technology (HOST), aeroelasticity, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics, and structural mechanics computer codes.

Mathematical models to characterize early epidemic growth: A Review

PubMed Central

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-01-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-15 Ebola epidemic in West Africa. PMID:27451336

Mathematical models to characterize early epidemic growth: A review

NASA Astrophysics Data System (ADS)

Chowell, Gerardo; Sattenspiel, Lisa; Bansal, Shweta; Viboud, Cécile

2016-09-01

There is a long tradition of using mathematical models to generate insights into the transmission dynamics of infectious diseases and assess the potential impact of different intervention strategies. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and to gain a better understanding of the mechanisms at play. Here, we review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data, and survey the types of mathematical formulations that are most useful for capturing a diversity of early epidemic growth profiles, ranging from sub-exponential to exponential growth dynamics. Specifically, we review mathematical models that incorporate spatial details or realistic population mixing structures, including meta-population models, individual-based network models, and simple SIR-type models that incorporate the effects of reactive behavior changes or inhomogeneous mixing. In this process, we also analyze simulation data stemming from detailed large-scale agent-based models previously designed and calibrated to study how realistic social networks and disease transmission characteristics shape early epidemic growth patterns, general transmission dynamics, and control of international disease emergencies such as the 2009 A/H1N1 influenza pandemic and the 2014-2015 Ebola epidemic in West Africa.

Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Thermal quantum time-correlation functions from classical-like dynamics

NASA Astrophysics Data System (ADS)

Hele, Timothy J. H.

2017-07-01

Thermal quantum time-correlation functions are of fundamental importance in quantum dynamics, allowing experimentally measurable properties such as reaction rates, diffusion constants and vibrational spectra to be computed from first principles. Since the exact quantum solution scales exponentially with system size, there has been considerable effort in formulating reliable linear-scaling methods involving exact quantum statistics and approximate quantum dynamics modelled with classical-like trajectories. Here, we review recent progress in the field with the development of methods including centroid molecular dynamics , ring polymer molecular dynamics (RPMD) and thermostatted RPMD (TRPMD). We show how these methods have recently been obtained from 'Matsubara dynamics', a form of semiclassical dynamics which conserves the quantum Boltzmann distribution. We also apply the Matsubara formalism to reaction rate theory, rederiving t → 0+ quantum transition-state theory (QTST) and showing that Matsubara-TST, like RPMD-TST, is equivalent to QTST. We end by surveying areas for future progress.

Statistical and dynamical assessment of land-ocean-atmosphere interactions across North Africa

NASA Astrophysics Data System (ADS)

Yu, Yan

North Africa is highly vulnerable to hydrologic variability and extremes, including impacts of climate change. The current understanding of oceanic versus terrestrial drivers of North African droughts and pluvials is largely model-based, with vast disagreement among models in terms of the simulated oceanic impacts and vegetation feedbacks. Regarding oceanic impacts, the relative importance of the tropical Pacific, tropical Indian, and tropical Atlantic Oceans in regulating the North African rainfall variability, as well as the underlying mechanism, remains debated among different modeling studies. Classic theory of land-atmosphere interactions across the Sahel ecotone, largely based on climate modeling experiments, has promoted positive vegetation-rainfall feedbacks associated with a dominant surface albedo mechanism. However, neither the proposed positive vegetation-rainfall feedback with its underlying albedo mechanism, nor its relative importance compared with oceanic drivers, has been convincingly demonstrated up to now using observational data. Here, the multivariate Generalized Equilibrium Feedback Assessment (GEFA) is applied in order to identify the observed oceanic and terrestrial drivers of North African climate and quantify their impacts. The reliability of the statistical GEFA method is first evaluated against dynamical experiments within the Community Earth System Model (CESM). In order to reduce the sampling error caused by short data records, the traditional GEFA approach is refined through stepwise GEFA, in which unimportant forcings are dropped through stepwise selection. In order to evaluate GEFA's reliability in capturing oceanic impacts, the atmospheric response to a sea-surface temperature (SST) forcing across the tropical Pacific, tropical Indian, and tropical Atlantic Ocean is estimated independently through ensembles of dynamical experiments and compared with GEFA-based assessments. Furthermore, GEFA's performance in capturing terrestrial impacts is evaluated through ensembles of fully coupled CESM dynamical experiments, with modified leaf area index (LAI) and soil moisture across the Sahel or West African Monsoon (WAM) region. The atmospheric responses to oceanic and terrestrial forcings are generally consistent between the dynamical experiments and statistical GEFA, confirming GEFA's capability of isolating the individual impacts of oceanic and terrestrial forcings on North African climate. Furthermore, with the incorporation of stepwise selection, GEFA can now provide reliable estimates of the oceanic and terrestrial impacts on the North African climate with the typical length of observational datasets, thereby enhancing the method's applicability. After the successful validation of GEFA, the key observed oceanic and terrestrial drivers of North African climate are identified through the application of GEFA to gridded observations, remote sensing products, and reanalyses. According to GEFA, oceanic drivers dominate over terrestrial drivers in terms of their observed impacts on North African climate in most seasons. Terrestrial impacts are comparable to, or more important than, oceanic impacts on rainfall during the post-monsoon across the Sahel and WAM region, and after the short rain across the Horn of Africa (HOA). The key ocean basins that regulate North African rainfall are typically located in the tropics. While the observed impacts of SST variability across the tropical Pacific and tropical Atlantic Oceans on the Sahel rainfall are largely consistent with previous model-based findings, minimal impacts from tropical Indian Ocean variability on Sahel rainfall are identified in observations, in contrast to previous modeling studies. The current observational analysis verifies model-hypothesized positive vegetation-rainfall feedback across the Sahel and HOA, which is confined to the post-monsoon and post-short rains season, respectively. However, the observed positive vegetation feedback to rainfall in the semi-arid Sahel and HOA is largely due to moisture recycling, rather than the classic albedo mechanism. Future projections of Sahel rainfall remain highly uncertain in terms of both sign and magnitude within phases three and five of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The GEFA-based observational analyses will provide a benchmark for evaluating climate models, which will facilitate effective process-based model weighting for more reliable projections of regional climate, as well as model development.

Lifetime Reliability Evaluation of Structural Ceramic Parts with the CARES/LIFE Computer Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), Weibull's normal stress averaging method (NSA), or Batdorf's theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating cyclic fatigue parameter estimation and component reliability analysis with proof testing are included.

Area 2: Inexpensive Monitoring and Uncertainty Assessment of CO2 Plume Migration using Injection Data

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

Srinivasan, Sanjay

2014-09-30

In-depth understanding of the long-term fate of CO₂ in the subsurface requires study and analysis of the reservoir formation, the overlaying caprock formation, and adjacent faults. Because there is significant uncertainty in predicting the location and extent of geologic heterogeneity that can impact the future migration of CO₂ in the subsurface, there is a need to develop algorithms that can reliably quantify this uncertainty in plume migration. This project is focused on the development of a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models thatmore » reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. Because only injection data is required, the method provides a very inexpensive method to map the migration of the plume and the associated uncertainty in migration paths. The model selection method developed as part of this project mainly consists of assessing the connectivity/dynamic characteristics of a large prior ensemble of models, grouping the models on the basis of their expected dynamic response, selecting the subgroup of models that most closely yield dynamic response closest to the observed dynamic data, and finally quantifying the uncertainty in plume migration using the selected subset of models. The main accomplishment of the project is the development of a software module within the SGEMS earth modeling software package that implements the model selection methodology. This software module was subsequently applied to analyze CO₂ plume migration in two field projects – the In Salah CO₂ Injection project in Algeria and CO₂ injection into the Utsira formation in Norway. These applications of the software revealed that the proxies developed in this project for quickly assessing the dynamic characteristics of the reservoir were highly efficient and yielded accurate grouping of reservoir models. The plume migration paths probabilistically assessed by the method were confirmed by field observations and auxiliary data. The report also documents the application of the software to answer practical questions such as the optimum location of monitoring wells to reliably assess the migration of CO₂ plume, the effect of CO₂-rock interactions on plume migration and the ability to detect the plume under those conditions and the effect of a slow, unresolved leak on the predictions of plume migration.« less

Dynamic SLA Negotiation in Autonomic Federated Environments

NASA Astrophysics Data System (ADS)

Rubach, Pawel; Sobolewski, Michael

Federated computing environments offer requestors the ability to dynamically invoke services offered by collaborating providers in the virtual service network. Without an efficient resource management that includes Dynamic SLA Negotiation, however, the assignment of providers to customer's requests cannot be optimized and cannot offer high reliability without relevant SLA guarantees. We propose a new SLA-based SERViceable Metacomputing Environment (SERVME) capable of matching providers based on QoS requirements and performing autonomic provisioning and deprovisioning of services according to dynamic requestor needs. This paper presents the SLA negotiation process that includes on-demand provisioning and uses an object-oriented SLA model for large-scale service-oriented systems supported by SERVME. An initial reference implementation in the SORCER environment is also described.

Reliability analysis and initial requirements for FC systems and stacks

NASA Astrophysics Data System (ADS)

Åström, K.; Fontell, E.; Virtanen, S.

In the year 2000 Wärtsilä Corporation started an R&D program to develop SOFC systems for CHP applications. The program aims to bring to the market highly efficient, clean and cost competitive fuel cell systems with rated power output in the range of 50-250 kW for distributed generation and marine applications. In the program Wärtsilä focuses on system integration and development. System reliability and availability are key issues determining the competitiveness of the SOFC technology. In Wärtsilä, methods have been implemented for analysing the system in respect to reliability and safety as well as for defining reliability requirements for system components. A fault tree representation is used as the basis for reliability prediction analysis. A dynamic simulation technique has been developed to allow for non-static properties in the fault tree logic modelling. Special emphasis has been placed on reliability analysis of the fuel cell stacks in the system. A method for assessing reliability and critical failure predictability requirements for fuel cell stacks in a system consisting of several stacks has been developed. The method is based on a qualitative model of the stack configuration where each stack can be in a functional, partially failed or critically failed state, each of the states having different failure rates and effects on the system behaviour. The main purpose of the method is to understand the effect of stack reliability, critical failure predictability and operating strategy on the system reliability and availability. An example configuration, consisting of 5 × 5 stacks (series of 5 sets of 5 parallel stacks) is analysed in respect to stack reliability requirements as a function of predictability of critical failures and Weibull shape factor of failure rate distributions.

The Influence of Dynamic Contact Angle on Wetting Dynamics

NASA Technical Reports Server (NTRS)

Rame, Enrique; Garoff, Steven

2005-01-01

When surface tension forces dominate, and regardless of whether the situation is static or dynamic, the contact angle (the angle the interface between two immiscible fluids makes when it contacts a solid) is the key parameter that determines the shape of a fluid-fluid interface. The static contact angle is easy to measure and implement in models predicting static capillary surface shapes and such associated quantities as pressure drops. By contrast, when the interface moves relative to the solid (as in dynamic wetting processes) the dynamic contact angle is not identified unambiguously because it depends on the geometry of the system Consequently, its determination becomes problematic and measurements in one geometry cannot be applied in another for prediction purposes. However, knowing how to measure and use the dynamic contact angle is crucial to determine such dynamics as a microsystem throughput reliably. In this talk we will present experimental and analytical efforts aimed at resolving modeling issues present in dynamic wetting. We will review experiments that show the inadequacy of the usual hydrodynamic model when a fluid-fluid meniscus moves over a solid surface such as the wall of a small tube or duct. We will then present analytical results that show how to parametrize these problems in a predictive manner. We will illustrate these ideas by showing how to implement the method in numerical fluid mechanical calculations.

An investigation into force-moment calibration techniques applicable to a magnetic suspension and balance system. M.S. Thesis

NASA Technical Reports Server (NTRS)

Eskins, Jonathan

1988-01-01

The problem of determining the forces and moments acting on a wind tunnel model suspended in a Magnetic Suspension and Balance System is addressed. Two calibration methods were investigated for three types of model cores, i.e., Alnico, Samarium-Cobalt, and a superconducting solenoid. Both methods involve calibrating the currents in the electromagnetic array against known forces and moments. The first is a static calibration method using calibration weights and a system of pulleys. The other method, dynamic calibration, involves oscillating the model and using its inertia to provide calibration forces and moments. Static calibration data, found to produce the most reliable results, is presented for three degrees of freedom at 0, 15, and -10 deg angle of attack. Theoretical calculations are hampered by the inability to represent iron-cored electromagnets. Dynamic calibrations, despite being quicker and easier to perform, are not as accurate as static calibrations. Data for dynamic calibrations at 0 and 15 deg is compared with the relevant static data acquired. Distortion of oscillation traces is cited as a major source of error in dynamic calibrations.

Dynamics and control of cable-suspended parallel robots for giant telescopes

NASA Astrophysics Data System (ADS)

Zhuang, Peng; Yao, Zhengqiu

2006-06-01

A cable-suspended parallel robot utilizes the basic idea of Stewart platform but replaces parallel links with cables and linear actuators with winches. It has many advantages over a conventional crane. The concept of applying a cable-suspended parallel robot into the construction and maintenance of giant telescope is presented in this paper. Compared with the mass and travel of the moving platform of the robot, the mass and deformation of the cables can be disregarded. Based on the premises, the kinematic and dynamic models of the robot are built. Through simulation, the inertia and gravity of moving platform are found to have dominant effect on the dynamic characteristic of the robot, while the dynamics of actuators can be disregarded, so a simplified dynamic model applicable to real-time control is obtained. Moreover, according to control-law partitioning approach and optimization theory, a workspace model-based controller is proposed considering the characteristic that the cables can only pull but not push. The simulation results indicate that the controller possesses good accuracy in pose and speed tracking, and keeps the cables in reliable tension by maintaining the minimum strain above a certain given value, thus ensures smooth motion and accurate localization for moving platform.

Shockless spalling damage of alumina ceramic

NASA Astrophysics Data System (ADS)

Erzar, B.; Buzaud, E.

2012-05-01

Ceramic materials are commonly used to build multi-layer armour. However reliable test data is needed to identify correctly models and to be able to perform accurate numerical simulation of the dynamic response of armour systems. In this work, isentropic loading waves have been applied to alumina samples to induce spalling damage. The technique employed allows assessing carefully the strain-rate at failure and the dynamic strength. Moreover, specimens have been recovered and analysed using SEM. In a damaged but unbroken specimen, interactions between cracks has been highlighted illustrating the fragmentation process.

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

Dynamical discrete/continuum linear response shells theory of solvation: convergence test for NH4+ and OH- ions in water solution using DFT and DFTB methods.

PubMed

de Lima, Guilherme Ferreira; Duarte, Hélio Anderson; Pliego, Josefredo R

2010-12-09

A new dynamical discrete/continuum solvation model was tested for NH(4)(+) and OH(-) ions in water solvent. The method is similar to continuum solvation models in a sense that the linear response approximation is used. However, different from pure continuum models, explicit solvent molecules are included in the inner shell, which allows adequate treatment of specific solute-solvent interactions present in the first solvation shell, the main drawback of continuum models. Molecular dynamics calculations coupled with SCC-DFTB method are used to generate the configurations of the solute in a box with 64 water molecules, while the interaction energies are calculated at the DFT level. We have tested the convergence of the method using a variable number of explicit water molecules and it was found that even a small number of waters (as low as 14) are able to produce converged values. Our results also point out that the Born model, often used for long-range correction, is not reliable and our method should be applied for more accurate calculations.

Assessment of change in dynamic psychotherapy.

PubMed

Høglend, P; Bøgwald, K P; Amlo, S; Heyerdahl, O; Sørbye, O; Marble, A; Sjaastad, M C; Bentsen, H

2000-01-01

Five scales have been developed to assess changes that are consistent with the therapeutic rationales and procedures of dynamic psychotherapy. Seven raters evaluated 50 patients before and 36 patients again after brief dynamic psychotherapy. A factor analysis indicated that the scales represent a dimension that is discriminable from general symptoms. A summary measure, Dynamic Capacity, was rated with acceptable reliability by a single rater. However, average scores of three raters were needed for good reliability of change ratings. The scales seem to be sufficiently fine-grained to capture statistically and clinically significant changes during brief dynamic psychotherapy.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

Estimation of dc transport dynamics in strongly correlated (La,Pr,Ca)MnO{sub 3} film using an insulator-metal composite model for terahertz conductivity

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

Nguyen, T. V. A.; Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531; Hattori, A. N.

2014-07-14

Temperature-dependent conductivities at dc and terahertz (THz) frequency region (σ{sub THz}(ω,T)) were obtained for a strongly correlated (La{sub 0.275}Pr{sub 0.35}Ca{sub 0.375})MnO{sub 3} (LPCMO) film using THz time domain spectroscopy. A composite model that describes σ{sub THz}(ω,T) for LPCMO through the insulator-metal transition (IMT) was established by incorporating Austin-Mott model characterizing the hopping of localized electrons and Drude model explaining the behavior of free electrons. This model enables us to reliably investigate the dc transport dynamics from THz conductivity measurement, i.e., simultaneously evaluate the dc conductivity and the competing composition of metal and insulator phases through the IMT, reflecting the changesmore » in microscopic conductivity of these phases.« less

Flows of Wet Foamsand Concentrated Emulsions

NASA Technical Reports Server (NTRS)

Nemer, Martin B.

2005-01-01

The aim of this project was is to advance a microstructural understanding of foam and emulsion flows. The dynamics of individual surfactant-covered drops and well as the collective behavior of dilute and concentrated was explored using numerical simulations. The long-range goal of this work is the formulation of reliable microphysically-based statistical models of emulsion flows.

Acceptability of the Kalman filter to monitor pronghorn population size

Treesearch

Raymond L. Czaplewski

1986-01-01

Pronghorn antelope are important components of grassland and steppe ecosystems in Wyoming. Monitoring data on the size and population dynamics of these herds are expensive and gathered only a few times each year. Reliable data include estimates of animals harvested and proportion of bucks, does, and fawns. A deterministic simulation model has been used to improve...

Representing pump-capacity relations in groundwater simulation models

USGS Publications Warehouse

Konikow, Leonard F.

2010-01-01

The yield (or discharge) of constant-speed pumps varies with the total dynamic head (or lift) against which the pump is discharging. The variation in yield over the operating range of the pump may be substantial. In groundwater simulations that are used for management evaluations or other purposes, where predictive accuracy depends on the reliability of future discharge estimates, model reliability may be enhanced by including the effects of head-capacity (or pump-capacity) relations on the discharge from the well. A relatively simple algorithm has been incorporated into the widely used MODFLOW groundwater flow model that allows a model user to specify head-capacity curves. The algorithm causes the model to automatically adjust the pumping rate each time step to account for the effect of drawdown in the cell and changing lift, and will shut the pump off if lift exceeds a critical value. The algorithm is available as part of a new multinode well package (MNW2) for MODFLOW.

Representing pump-capacity relations in groundwater simulati on models

USGS Publications Warehouse

Konikow, Leonard F.

2010-01-01

The yield (or discharge) of constant-speed pumps varies with the total dynamic head (or lift) against which the pump is discharging. The variation in yield over the operating range of the pump may be substantial. In groundwater simulations that are used for management evaluations or other purposes, where predictive accuracy depends on the reliability of future discharge estimates, model reliability may be enhanced by including the effects of head-capacity (or pump-capacity) relations on the discharge from the well. A relatively simple algorithm has been incorporated into the widely used MODFLOW groundwater flow model that allows a model user to specify head-capacity curves. The algorithm causes the model to automatically adjust the pumping rate each time step to account for the effect of drawdown in the cell and changing lift, and will shut the pump off if lift exceeds a critical value. The algorithm is available as part of a new multinode well package (MNW2) for MODFLOW. ?? 2009 National Ground Water Association.

Simple, stable and reliable modeling of gas properties of organic working fluids in aerodynamic designs of turbomachinery for ORC and VCC

NASA Astrophysics Data System (ADS)

Kawakubo, T.

2016-05-01

A simple, stable and reliable modeling of the real gas nature of the working fluid is required for the aerodesigns of the turbine in the Organic Rankine Cycle and of the compressor in the Vapor Compression Cycle. Although many modern Computational Fluid Dynamics tools are capable of incorporating real gas models, simulations with such a gas model tend to be more time-consuming than those with a perfect gas model and even can be unstable due to the simulation near the saturation boundary. Thus a perfect gas approximation is still an attractive option to stably and swiftly conduct a design simulation. In this paper, an effective method of the CFD simulation with a perfect gas approximation is discussed. A method of representing the performance of the centrifugal compressor or the radial-inflow turbine by means of each set of non-dimensional performance parameters and translating the fictitious perfect gas result to the actual real gas performance is presented.

Identifying Electricity Capacity at Risk to Changes in Climate and Water Resources in the United States

NASA Astrophysics Data System (ADS)

Miara, A.; Macknick, J.; Vorosmarty, C. J.; Corsi, F.; Fekete, B. M.; Newmark, R. L.; Tidwell, V. C.; Cohen, S. M.

2016-12-01

Thermoelectric plants supply 85% of electricity generation in the United States. Under a warming climate, the performance of these power plants may be reduced, as thermoelectric generation is dependent upon cool ambient temperatures and sufficient water supplies at adequate temperatures. In this study, we assess the vulnerability and reliability of 1,100 operational power plants (2015) across the contiguous United States under a comprehensive set of climate scenarios (five Global Circulation Models each with four Representative Concentration Pathways). We model individual power plant capacities using the Thermoelectric Power and Thermal Pollution model (TP2M) coupled with the Water Balance Model (WBM) at a daily temporal resolution and 5x5 km spatial resolution. Together, these models calculate power plant capacity losses that account for geophysical constraints and river network dynamics. Potential losses at the single-plant level are put into a regional energy security context by assessing the collective system-level reliability at the North-American Electricity Reliability Corporation (NERC) regions. Results show that the thermoelectric sector at the national level has low vulnerability under the contemporary climate and that system-level reliability in terms of available thermoelectric resources relative to thermoelectric demand is sufficient. Under future climates scenarios, changes in water availability and warm ambient temperatures lead to constraints on operational capacity and increased vulnerability at individual power plant sites across all regions in the United States. However, there is a strong disparity in regional vulnerability trends and magnitudes that arise from each region's climate, hydrology and technology mix. Despite increases in vulnerabilities at the individual power plant level, regional energy systems may still be reliable (with no system failures) due to sufficient back-up reserve capacities.

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

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

Li, Minjing; Gao, Yuqian; Qian, Wei-Jun

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different frommore » that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.« less

SIERRA - A 3-D device simulator for reliability modeling

NASA Astrophysics Data System (ADS)

Chern, Jue-Hsien; Arledge, Lawrence A., Jr.; Yang, Ping; Maeda, John T.

1989-05-01

SIERRA is a three-dimensional general-purpose semiconductor-device simulation program which serves as a foundation for investigating integrated-circuit (IC) device and reliability issues. This program solves the Poisson and continuity equations in silicon under dc, transient, and small-signal conditions. Executing on a vector/parallel minisupercomputer, SIERRA utilizes a matrix solver which uses an incomplete LU (ILU) preconditioned conjugate gradient square (CGS, BCG) method. The ILU-CGS method provides a good compromise between memory size and convergence rate. The authors have observed a 5x to 7x speedup over standard direct methods in simulations of transient problems containing highly coupled Poisson and continuity equations such as those found in reliability-oriented simulations. The application of SIERRA to parasitic CMOS latchup and dynamic random-access memory single-event-upset studies is described.

Time-dependent reliability analysis of ceramic engine components

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing either the power or Paris law relations. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating proof testing and fatigue parameter estimation are given.

Quantifying hypoxia in human cancers using static PET imaging.

PubMed

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G; Milosevic, Michael; Hedley, David W; Jaffray, David A

2016-11-21

Compared to FDG, the signal of 18 F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties-well-perfused without substantial necrosis or partitioning-for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in 'inter-corporal' transport properties-blood volume and clearance rate-as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3 , a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Quantifying hypoxia in human cancers using static PET imaging

NASA Astrophysics Data System (ADS)

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G.; Milosevic, Michael; Hedley, David W.; Jaffray, David A.

2016-11-01

Compared to FDG, the signal of 18F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties—well-perfused without substantial necrosis or partitioning—for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in ‘inter-corporal’ transport properties—blood volume and clearance rate—as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3, a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Delving Into Dissipative Quantum Dynamics: From Approximate to Numerically Exact Approaches

NASA Astrophysics Data System (ADS)

Chen, Hsing-Ta

In this thesis, I explore dissipative quantum dynamics of several prototypical model systems via various approaches, ranging from approximate to numerically exact schemes. In particular, in the realm of the approximate I explore the accuracy of Pade-resummed master equations and the fewest switches surface hopping (FSSH) algorithm for the spin-boson model, and non-crossing approximations (NCA) for the Anderson-Holstein model. Next, I develop new and exact Monte Carlo approaches and test them on the spin-boson model. I propose well-defined criteria for assessing the accuracy of Pade-resummed quantum master equations, which correctly demarcate the regions of parameter space where the Pade approximation is reliable. I continue the investigation of spin-boson dynamics by benchmark comparisons of the semiclassical FSSH algorithm to exact dynamics over a wide range of parameters. Despite small deviations from golden-rule scaling in the Marcus regime, standard surface hopping algorithm is found to be accurate over a large portion of parameter space. The inclusion of decoherence corrections via the augmented FSSH algorithm improves the accuracy of dynamical behavior compared to exact simulations, but the effects are generally not dramatic for the cases I consider. Next, I introduce new methods for numerically exact real-time simulation based on real-time diagrammatic Quantum Monte Carlo (dQMC) and the inchworm algorithm. These methods optimally recycle Monte Carlo information from earlier times to greatly suppress the dynamical sign problem. In the context of the spin-boson model, I formulate the inchworm expansion in two distinct ways: the first with respect to an expansion in the system-bath coupling and the second as an expansion in the diabatic coupling. In addition, a cumulant version of the inchworm Monte Carlo method is motivated by the latter expansion, which allows for further suppression of the growth of the sign error. I provide a comprehensive comparison of the performance of the inchworm Monte Carlo algorithms to other exact methodologies as well as a discussion of the relative advantages and disadvantages of each. Finally, I investigate the dynamical interplay between the electron-electron interaction and the electron-phonon coupling within the Anderson-Holstein model via two complementary NCAs: the first is constructed around the weak-coupling limit and the second around the polaron limit. The influence of phonons on spectral and transport properties is explored in equilibrium, for non-equilibrium steady state and for transient dynamics after a quench. I find the two NCAs disagree in nontrivial ways, indicating that more reliable approaches to the problem are needed. The complementary frameworks used here pave the way for numerically exact methods based on inchworm dQMC algorithms capable of treating open systems simultaneously coupled to multiple fermionic and bosonic baths.

Test Platforms for Model-Based Flight Research

NASA Astrophysics Data System (ADS)

Dorobantu, Andrei

Demonstrating the reliability of flight control algorithms is critical to integrating unmanned aircraft systems into the civilian airspace. For many potential applications, design and certification of these algorithms will rely heavily on mathematical models of the aircraft dynamics. Therefore, the aerospace community must develop flight test platforms to support the advancement of model-based techniques. The University of Minnesota has developed a test platform dedicated to model-based flight research for unmanned aircraft systems. This thesis provides an overview of the test platform and its research activities in the areas of system identification, model validation, and closed-loop control for small unmanned aircraft.

Hybrid learning in signalling games

NASA Astrophysics Data System (ADS)

Barrett, Jeffrey A.; Cochran, Calvin T.; Huttegger, Simon; Fujiwara, Naoki

2017-09-01

Lewis-Skyrms signalling games have been studied under a variety of low-rationality learning dynamics. Reinforcement dynamics are stable but slow and prone to evolving suboptimal signalling conventions. A low-inertia trial-and-error dynamical like win-stay/lose-randomise is fast and reliable at finding perfect signalling conventions but unstable in the context of noise or agent error. Here we consider a low-rationality hybrid of reinforcement and win-stay/lose-randomise learning that exhibits the virtues of both. This hybrid dynamics is reliable, stable and exceptionally fast.

Effects of turbulence modelling on prediction of flow characteristics in a bench-scale anaerobic gas-lift digester.

PubMed

Coughtrie, A R; Borman, D J; Sleigh, P A

2013-06-01

Flow in a gas-lift digester with a central draft-tube was investigated using computational fluid dynamics (CFD) and different turbulence closure models. The k-ω Shear-Stress-Transport (SST), Renormalization-Group (RNG) k-∊, Linear Reynolds-Stress-Model (RSM) and Transition-SST models were tested for a gas-lift loop reactor under Newtonian flow conditions validated against published experimental work. The results identify that flow predictions within the reactor (where flow is transitional) are particularly sensitive to the turbulence model implemented; the Transition-SST model was found to be the most robust for capturing mixing behaviour and predicting separation reliably. Therefore, Transition-SST is recommended over k-∊ models for use in comparable mixing problems. A comparison of results obtained using multiphase Euler-Lagrange and singlephase approaches are presented. The results support the validity of the singlephase modelling assumptions in obtaining reliable predictions of the reactor flow. Solver independence of results was verified by comparing two independent finite-volume solvers (Fluent-13.0sp2 and OpenFOAM-2.0.1). Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Yan, Ruqiang; Chen, Xuefeng; Li, Weihua

Modern mathematics has commonly been utilized as an effective tool to model mechanical equipment so that their dynamic characteristics can be studied analytically. This will help identify potential failures of mechanical equipment by observing change in the equipment’s dynamic parameters. On the other hand, dynamic signals are also important and provide reliable information about the equipment’s working status. Modern mathematics has also provided us with a systematic way to design and implement various signal processing methods, which are used to analyze these dynamic signals, and to enhance intrinsic signal components that are directly related to machine failures. This special issuemore » is aimed at stimulating not only new insights on mathematical methods for modeling but also recently developed signal processing methods, such as sparse decomposition with potential applications in machine fault diagnosis. Finally, the papers included in this special issue provide a glimpse into some of the research and applications in the field of machine fault diagnosis through applications of the modern mathematical methods.« less

Proof-of-Concept Demonstrations for Computation-Based Human Reliability Analysis. Modeling Operator Performance During Flooding Scenarios

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

Joe, Jeffrey Clark; Boring, Ronald Laurids; Herberger, Sarah Elizabeth Marie

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program has the overall objective to help sustain the existing commercial nuclear power plants (NPPs). To accomplish this program objective, there are multiple LWRS “pathways,” or research and development (R&D) focus areas. One LWRS focus area is called the Risk-Informed Safety Margin and Characterization (RISMC) pathway. Initial efforts under this pathway to combine probabilistic and plant multi-physics models to quantify safety margins and support business decisions also included HRA, but in a somewhat simplified manner. HRA experts at Idaho National Laboratory (INL) have been collaborating with othermore » experts to develop a computational HRA approach, called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), for inclusion into the RISMC framework. The basic premise of this research is to leverage applicable computational techniques, namely simulation and modeling, to develop and then, using RAVEN as a controller, seamlessly integrate virtual operator models (HUNTER) with 1) the dynamic computational MOOSE runtime environment that includes a full-scope plant model, and 2) the RISMC framework PRA models already in use. The HUNTER computational HRA approach is a hybrid approach that leverages past work from cognitive psychology, human performance modeling, and HRA, but it is also a significant departure from existing static and even dynamic HRA methods. This report is divided into five chapters that cover the development of an external flooding event test case and associated statistical modeling considerations.« less

Inverse problems and computational cell metabolic models: a statistical approach

NASA Astrophysics Data System (ADS)

Calvetti, D.; Somersalo, E.

2008-07-01

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

Developing Capture Mechanisms and High-Fidelity Dynamic Models for the MXER Tether System

NASA Technical Reports Server (NTRS)

Canfield, Steven L.

2007-01-01

A team consisting of collaborators from Tennessee Technological University (TTU), Marshall Space Flight Center, BD Systems, and the University of Delaware (herein called the TTU team) conducted specific research and development activities in MXER tether systems during the base period of May 15, 2004 through September 30, 2006 under contract number NNM04AB13C. The team addressed two primary topics related to the MXER tether system: 1) Development of validated high-fidelity dynamic models of an elastic rotating tether and 2) development of feasible mechanisms to enable reliable rendezvous and capture. This contractor report will describe in detail the activities that were performed during the base period of this cycle-2 MXER tether activity and will summarize the results of this funded activity. The primary deliverables of this project were the quad trap, a robust capture mechanism proposed, developed, tested, and demonstrated with a high degree of feasibility and the detailed development of a validated high-fidelity elastic tether dynamic model provided through multiple formulations.

Reliability and mass analysis of dynamic power conversion systems with parallel of standby redundancy

NASA Technical Reports Server (NTRS)

Juhasz, A. J.; Bloomfield, H. S.

1985-01-01

A combinatorial reliability approach is used to identify potential dynamic power conversion systems for space mission applications. A reliability and mass analysis is also performed, specifically for a 100 kWe nuclear Brayton power conversion system with parallel redundancy. Although this study is done for a reactor outlet temperature of 1100K, preliminary system mass estimates are also included for reactor outlet temperatures ranging up to 1500 K.

Charge-transfer modified embedded atom method dynamic charge potential for Li-Co-O system

NASA Astrophysics Data System (ADS)

Kong, Fantai; Longo, Roberto C.; Liang, Chaoping; Nie, Yifan; Zheng, Yongping; Zhang, Chenxi; Cho, Kyeongjae

2017-11-01

To overcome the limitation of conventional fixed charge potential methods for the study of Li-ion battery cathode materials, a dynamic charge potential method, charge-transfer modified embedded atom method (CT-MEAM), has been developed and applied to the Li-Co-O ternary system. The accuracy of the potential has been tested and validated by reproducing a variety of structural and electrochemical properties of LiCoO2. A detailed analysis on the local charge distribution confirmed the capability of this potential for dynamic charge modeling. The transferability of the potential is also demonstrated by its reliability in describing Li-rich Li2CoO2 and Li-deficient LiCo2O4 compounds, including their phase stability, equilibrium volume, charge states and cathode voltages. These results demonstrate that the CT-MEAM dynamic charge potential could help to overcome the challenge of modeling complex ternary transition metal oxides. This work can promote molecular dynamics studies of Li ion cathode materials and other important transition metal oxides systems that involve complex electrochemical and catalytic reactions.

Charge-transfer modified embedded atom method dynamic charge potential for Li-Co-O system.

PubMed

Kong, Fantai; Longo, Roberto C; Liang, Chaoping; Nie, Yifan; Zheng, Yongping; Zhang, Chenxi; Cho, Kyeongjae

2017-11-29

To overcome the limitation of conventional fixed charge potential methods for the study of Li-ion battery cathode materials, a dynamic charge potential method, charge-transfer modified embedded atom method (CT-MEAM), has been developed and applied to the Li-Co-O ternary system. The accuracy of the potential has been tested and validated by reproducing a variety of structural and electrochemical properties of LiCoO 2 . A detailed analysis on the local charge distribution confirmed the capability of this potential for dynamic charge modeling. The transferability of the potential is also demonstrated by its reliability in describing Li-rich Li 2 CoO 2 and Li-deficient LiCo 2 O 4 compounds, including their phase stability, equilibrium volume, charge states and cathode voltages. These results demonstrate that the CT-MEAM dynamic charge potential could help to overcome the challenge of modeling complex ternary transition metal oxides. This work can promote molecular dynamics studies of Li ion cathode materials and other important transition metal oxides systems that involve complex electrochemical and catalytic reactions.

Multi-Site λ-dynamics for simulated Structure-Activity Relationship studies

PubMed Central

Knight, Jennifer L.; Brooks, Charles L.

2011-01-01

Multi-Site λ-dynamics (MSλD) is a new free energy simulation method that is based on λ-dynamics. It has been developed to enable multiple substituents at multiple sites on a common ligand core to be modeled simultaneously and their free energies assessed. The efficacy of MSλD for estimating relative hydration free energies and relative binding affinties is demonstrated using three test systems. Model compounds representing multiple identical benzene, dihydroxybenzene and dimethoxybenzene molecules show total combined MSλD trajectory lengths of ~1.5 ns are sufficient to reliably achieve relative hydration free energy estimates within 0.2 kcal/mol and are less sensitive to the number of trajectories that are used to generate these estimates for hybrid ligands that contain up to ten substituents modeled at a single site or five substituents modeled at each of two sites. Relative hydration free energies among six benzene derivatives calculated from MSλD simulations are in very good agreement with those from alchemical free energy simulations (with average unsigned differences of 0.23 kcal/mol and R2=0.991) and experiment (with average unsigned errors of 1.8 kcal/mol and R2=0.959). Estimates of the relative binding affinities among 14 inhibitors of HIV-1 reverse transcriptase obtained from MSλD simulations are in reasonable agreement with those from traditional free energy simulations and experiment (average unsigned errors of 0.9 kcal/mol and R2=0.402). For the same level of accuracy and precision MSλD simulations are achieved ~20–50 times faster than traditional free energy simulations and thus with reliable force field parameters can be used effectively to screen tens to hundreds of compounds in structure-based drug design applications. PMID:22125476

How to assess the impact of a physical parameterization in simulations of moist convection?

NASA Astrophysics Data System (ADS)

Grabowski, Wojciech

2017-04-01

A numerical model capable in simulating moist convection (e.g., cloud-resolving model or large-eddy simulation model) consists of a fluid flow solver combined with required representations (i.e., parameterizations) of physical processes. The later typically include cloud microphysics, radiative transfer, and unresolved turbulent transport. Traditional approaches to investigate impacts of such parameterizations on convective dynamics involve parallel simulations with different parameterization schemes or with different scheme parameters. Such methodologies are not reliable because of the natural variability of a cloud field that is affected by the feedback between the physics and dynamics. For instance, changing the cloud microphysics typically leads to a different realization of the cloud-scale flow, and separating dynamical and microphysical impacts is difficult. This presentation will present a novel modeling methodology, the piggybacking, that allows studying the impact of a physical parameterization on cloud dynamics with confidence. The focus will be on the impact of cloud microphysics parameterization. Specific examples of the piggybacking approach will include simulations concerning the hypothesized deep convection invigoration in polluted environments, the validity of the saturation adjustment in modeling condensation in moist convection, and separation of physical impacts from statistical uncertainty in simulations applying particle-based Lagrangian microphysics, the super-droplet method.

Damage Mechanisms and Controlled Crack Propagation in a Hot Pressed Silicon Nitride Ceramic. Ph.D. Thesis - Northwestern Univ., 1993

NASA Technical Reports Server (NTRS)

Calomino, Anthony Martin

1994-01-01

The subcritical growth of cracks from pre-existing flaws in ceramics can severely affect the structural reliability of a material. The ability to directly observe subcritical crack growth and rigorously analyze its influence on fracture behavior is important for an accurate assessment of material performance. A Mode I fracture specimen and loading method has been developed which permits the observation of stable, subcritical crack extension in monolithic and toughened ceramics. The test specimen and procedure has demonstrated its ability to generate and stably propagate sharp, through-thickness cracks in brittle high modulus materials. Crack growth for an aluminum oxide ceramic was observed to be continuously stable throughout testing. Conversely, the fracture behavior of a silicon nitride ceramic exhibited crack growth as a series of subcritical extensions which are interrupted by dynamic propagation. Dynamic initiation and arrest fracture resistance measurements for the silicon nitride averaged 67 and 48 J/sq m, respectively. The dynamic initiation event was observed to be sudden and explosive. Increments of subcritical crack growth contributed to a 40 percent increase in fracture resistance before dynamic initiation. Subcritical crack growth visibly marked the fracture surface with an increase in surface roughness. Increments of subcritical crack growth loosen ceramic material near the fracture surface and the fracture debris is easily removed by a replication technique. Fracture debris is viewed as evidence that both crack bridging and subsurface microcracking may be some of the mechanisms contributing to the increase in fracture resistance. A Statistical Fracture Mechanics model specifically developed to address subcritical crack growth and fracture reliability is used together with a damaged zone of material at the crack tip to model experimental results. A Monte Carlo simulation of the actual experiments was used to establish a set of modeling input parameters. It was demonstrated that a single critical parameter does not characterize the conditions required for dynamic initiation. Experimental measurements for critical crack lengths, and the energy release rates exhibit significant scatter. The resulting output of the model produces good agreement with both the average values and scatter of experimental measurements.

Impact of an irregular friction formulation on dynamics of a minimal model for brake squeal

NASA Astrophysics Data System (ADS)

Stender, Merten; Tiedemann, Merten; Hoffmann, Norbert; Oberst, Sebastian

2018-07-01

Friction-induced vibrations are of major concern in the design of reliable, efficient and comfortable technical systems. Well-known examples for systems susceptible to self-excitation can be found in fluid structure interaction, disk brake squeal, rotor dynamics, hip implants noise and many more. While damping elements and amplitude reduction are well-understood in linear systems, nonlinear systems and especially self-excited dynamics still constitute a challenge for damping element design. Additionally, complex dynamical systems exhibit deterministic chaotic cores which add severe sensitivity to initial conditions to the system response. Especially the complex friction interface dynamics remain a challenging task for measurements and modeling. Today, mostly simple and regular friction models are investigated in the field of self-excited brake system vibrations. This work aims at investigating the effect of high-frequency irregular interface dynamics on the nonlinear dynamical response of a self-excited structure. Special focus is put on the characterization of the system response time series. A low-dimensional minimal model is studied which features self-excitation, gyroscopic effects and friction-induced damping. Additionally, the employed friction formulation exhibits temperature as inner variable and superposed chaotic fluctuations governed by a Lorenz attractor. The time scale of the irregular fluctuations is chosen one order smaller than the overall system dynamics. The influence of those fluctuations on the structural response is studied in various ways, i.e. in time domain and by means of recurrence analysis. The separate time scales are studied in detail and regimes of dynamic interactions are identified. The results of the irregular friction formulation indicate dynamic interactions on multiple time scales, which trigger larger vibration amplitudes as compared to regular friction formulations conventionally studied in the field of friction-induced vibrations.

An evaluation of Dynamic TOPMODEL for low flow simulation

NASA Astrophysics Data System (ADS)

Coxon, G.; Freer, J. E.; Quinn, N.; Woods, R. A.; Wagener, T.; Howden, N. J. K.

2015-12-01

Hydrological models are essential tools for drought risk management, often providing input to water resource system models, aiding our understanding of low flow processes within catchments and providing low flow predictions. However, simulating low flows and droughts is challenging as hydrological systems often demonstrate threshold effects in connectivity, non-linear groundwater contributions and a greater influence of water resource system elements during low flow periods. These dynamic processes are typically not well represented in commonly used hydrological models due to data and model limitations. Furthermore, calibrated or behavioural models may not be effectively evaluated during more extreme drought periods. A better understanding of the processes that occur during low flows and how these are represented within models is thus required if we want to be able to provide robust and reliable predictions of future drought events. In this study, we assess the performance of dynamic TOPMODEL for low flow simulation. Dynamic TOPMODEL was applied to a number of UK catchments in the Thames region using time series of observed rainfall and potential evapotranspiration data that captured multiple historic droughts over a period of several years. The model performance was assessed against the observed discharge time series using a limits of acceptability framework, which included uncertainty in the discharge time series. We evaluate the models against multiple signatures of catchment low-flow behaviour and investigate differences in model performance between catchments, model diagnostics and for different low flow periods. We also considered the impact of surface water and groundwater abstractions and discharges on the observed discharge time series and how this affected the model evaluation. From analysing the model performance, we suggest future improvements to Dynamic TOPMODEL to improve the representation of low flow processes within the model structure.

Gearbox Reliability Collaborative Research | Wind | NREL

Science.gov Websites

inception, the Gearbox Reliability Collaborative (GRC) has collected an extraordinary amount of experimental torque, steady state and dynamic non-torque loads, internal loads and deflections, and condition important data and conclusions such as the importance of non-torque loads, dynamic torque events, planetary

76 FR 66057 - North American Electric Reliability Corporation; Order Approving Regional Reliability Standard

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-25

... system conditions when the system experiences dynamic events such as low frequency oscillations, or... R8 requires that dynamic disturbance recorders function continuously. To capture system disturbance... recording capability necessary to monitor the response of the Bulk-Power System to system disturbances...

Linking 1D coastal ocean modelling to environmental management: an ensemble approach

NASA Astrophysics Data System (ADS)

Mussap, Giulia; Zavatarelli, Marco; Pinardi, Nadia

2017-12-01

The use of a one-dimensional interdisciplinary numerical model of the coastal ocean as a tool contributing to the formulation of ecosystem-based management (EBM) is explored. The focus is on the definition of an experimental design based on ensemble simulations, integrating variability linked to scenarios (characterised by changes in the system forcing) and to the concurrent variation of selected, and poorly constrained, model parameters. The modelling system used was previously specifically designed for the use in "data-rich" areas, so that horizontal dynamics can be resolved by a diagnostic approach and external inputs can be parameterised by nudging schemes properly calibrated. Ensembles determined by changes in the simulated environmental (physical and biogeochemical) dynamics, under joint forcing and parameterisation variations, highlight the uncertainties associated to the application of specific scenarios that are relevant to EBM, providing an assessment of the reliability of the predicted changes. The work has been carried out by implementing the coupled modelling system BFM-POM1D in an area of Gulf of Trieste (northern Adriatic Sea), considered homogeneous from the point of view of hydrological properties, and forcing it by changing climatic (warming) and anthropogenic (reduction of the land-based nutrient input) pressure. Model parameters affected by considerable uncertainties (due to the lack of relevant observations) were varied jointly with the scenarios of change. The resulting large set of ensemble simulations provided a general estimation of the model uncertainties related to the joint variation of pressures and model parameters. The information of the model result variability aimed at conveying efficiently and comprehensibly the information on the uncertainties/reliability of the model results to non-technical EBM planners and stakeholders, in order to have the model-based information effectively contributing to EBM.

Oculometric Assessment of Dynamic Visual Processing

NASA Technical Reports Server (NTRS)

Liston, Dorion Bryce; Stone, Lee

2014-01-01

Eye movements are the most frequent (3 per second), shortest-latency (150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model system to assess sensorimotor disturbances arising from trauma, fatigue, aging, or disease states (e.g., Diefendorf and Dodge, 1908). We developed a 15-minute behavioral tracking protocol consisting of randomized stepramp radial target motion to assess several aspects of the behavioral response to dynamic visual motion, including pursuit initiation, steadystate tracking, direction-tuning, and speed-tuning thresholds. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance (Stone and Krauzlis, 2003; Krukowski and Stone, 2005; Stone et al, 2009; Liston and Stone, 2014), and may prove to be a useful assessment tool for functional impairments of dynamic visual processing.

Measuring and modeling surface sorption dynamics of organophosphate flame retardants on impervious surfaces.

PubMed

Liang, Y; Liu, X; Allen, M R

2018-02-01

Understanding the sorption mechanisms for organophosphate flame retardants (OPFRs) on impervious surfaces is important to improve our knowledge of the fate and transport of OPFRs in indoor environments. The sorption processes of semivolatile organic compounds (SVOCs) on indoor surfaces are heterogeneous (multilayer sorption) or homogeneous (monolayer sorption). In this study, we adopted simplified Langmuir isotherm and Freundlich isotherm in a dynamic sink model to characterize the sorption dynamics of OPFRs on impervious surfaces such as stainless steel and made comparisons between the two models through a series of empty chamber studies. The tests involve two types of stainless steel chambers (53-L small chambers and 44-mL micro chambers) using tris(2-chloroethyl)phosphate (TCEP) and tris(1-chloro-2-propyl)phosphate (TCPP) as target compounds. Our test results show that the dynamic sink model using Freundlich isotherm can better represent the sorption process in the empty small chamber. Micro chamber test results from this study show that the sink model using both simplified Langmuir isotherm and Freundlich isotherm can well fit the measured gas-phase concentrations of OPFRs. We further applied both models and the parameters obtained to predict the gas phase concentrations of OPFRs in a small chamber with an emission source. Comparisons between model predictions and measurements demonstrate the reliability and applicability of the sorption parameters. Published by Elsevier Ltd.

Assessment of Change in Dynamic Psychotherapy

PubMed Central

Høglend, Per; Bøgwald, Kjell-Petter; Amlo, Svein; Heyerdahl, Oscar; Sørbye, Øystein; Marble, Alice; Sjaastad, Mary Cosgrove; Bentsen, Håvard

2000-01-01

Five scales have been developed to assess changes that are consistent with the therapeutic rationales and procedures of dynamic psychotherapy. Seven raters evaluated 50 patients before and 36 patients again after brief dynamic psychotherapy. A factor analysis indicated that the scales represent a dimension that is discriminable from general symptoms. A summary measure, Dynamic Capacity, was rated with acceptable reliability by a single rater. However, average scores of three raters were needed for good reliability of change ratings. The scales seem to be sufficiently fine-grained to capture statistically and clinically significant changes during brief dynamic psychotherapy. PMID:11069131

Validating clustering of molecular dynamics simulations using polymer models.

PubMed

Phillips, Joshua L; Colvin, Michael E; Newsam, Shawn

2011-11-14

Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers.

Validating clustering of molecular dynamics simulations using polymer models

PubMed Central

2011-01-01

Background Molecular dynamics (MD) simulation is a powerful technique for sampling the meta-stable and transitional conformations of proteins and other biomolecules. Computational data clustering has emerged as a useful, automated technique for extracting conformational states from MD simulation data. Despite extensive application, relatively little work has been done to determine if the clustering algorithms are actually extracting useful information. A primary goal of this paper therefore is to provide such an understanding through a detailed analysis of data clustering applied to a series of increasingly complex biopolymer models. Results We develop a novel series of models using basic polymer theory that have intuitive, clearly-defined dynamics and exhibit the essential properties that we are seeking to identify in MD simulations of real biomolecules. We then apply spectral clustering, an algorithm particularly well-suited for clustering polymer structures, to our models and MD simulations of several intrinsically disordered proteins. Clustering results for the polymer models provide clear evidence that the meta-stable and transitional conformations are detected by the algorithm. The results for the polymer models also help guide the analysis of the disordered protein simulations by comparing and contrasting the statistical properties of the extracted clusters. Conclusions We have developed a framework for validating the performance and utility of clustering algorithms for studying molecular biopolymer simulations that utilizes several analytic and dynamic polymer models which exhibit well-behaved dynamics including: meta-stable states, transition states, helical structures, and stochastic dynamics. We show that spectral clustering is robust to anomalies introduced by structural alignment and that different structural classes of intrinsically disordered proteins can be reliably discriminated from the clustering results. To our knowledge, our framework is the first to utilize model polymers to rigorously test the utility of clustering algorithms for studying biopolymers. PMID:22082218

Investigating the Intersession Reliability of Dynamic Brain-State Properties.

PubMed

Smith, Derek M; Zhao, Yrian; Keilholz, Shella D; Schumacher, Eric H

2018-06-01

Dynamic functional connectivity metrics have much to offer to the neuroscience of individual differences of cognition. Yet, despite the recent expansion in dynamic connectivity research, limited resources have been devoted to the study of the reliability of these connectivity measures. To address this, resting-state functional magnetic resonance imaging data from 100 Human Connectome Project subjects were compared across 2 scan days. Brain states (i.e., patterns of coactivity across regions) were identified by classifying each time frame using k means clustering. This was done with and without global signal regression (GSR). Multiple gauges of reliability indicated consistency in the brain-state properties across days and GSR attenuated the reliability of the brain states. Changes in the brain-state properties across the course of the scan were investigated as well. The results demonstrate that summary metrics describing the clustering of individual time frames have adequate test/retest reliability, and thus, these patterns of brain activation may hold promise for individual-difference research.

Few-Photon Model of the Optical Emission of Semiconductor Quantum Dots

NASA Astrophysics Data System (ADS)

Richter, Marten; Carmele, Alexander; Sitek, Anna; Knorr, Andreas

2009-08-01

The Jaynes-Cummings model provides a well established theoretical framework for single electron two level systems in a radiation field. Similar exactly solvable models for semiconductor light emitters such as quantum dots dominated by many particle interactions are not known. We access these systems by a generalized cluster expansion, the photon-probability cluster expansion: a reliable approach for few-photon dynamics in many body electron systems. As a first application, we discuss vacuum Rabi oscillations and show that their amplitude determines the number of electrons in the quantum dot.

Predicting the Dynamic Crushing Response of a Composite Honeycomb Energy Absorber Using Solid-Element-Based Models in LS-DYNA

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

2010-01-01

This paper describes an analytical study that was performed as part of the development of an externally deployable energy absorber (DEA) concept. The concept consists of a composite honeycomb structure that can be stowed until needed to provide energy attenuation during a crash event, much like an external airbag system. One goal of the DEA development project was to generate a robust and reliable Finite Element Model (FEM) of the DEA that could be used to accurately predict its crush response under dynamic loading. The results of dynamic crush tests of 50-, 104-, and 68-cell DEA components are presented, and compared with simulation results from a solid-element FEM. Simulations of the FEM were performed in LS-DYNA(Registered TradeMark) to compare the capabilities of three different material models: MAT 63 (crushable foam), MAT 26 (honeycomb), and MAT 126 (modified honeycomb). These material models are evaluated to determine if they can be used to accurately predict both the uniform crushing and final compaction phases of the DEA for normal and off-axis loading conditions

Optimal control of epidemic information dissemination over networks.

PubMed

Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

2014-12-01

Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

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

Wang, Bin; Huang, Rui; Wang, Yubo

2016-05-02

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimizationmore » module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.« less

A study of low-cost reliable actuators for light aircraft. Part A: Chapters 1-8

NASA Technical Reports Server (NTRS)

Eijsink, H.; Rice, M.

1978-01-01

An analysis involving electro-mechanical, electro-pneumatic, and electro-hydraulic actuators was performed to study which are compatible for use in the primary and secondary flight controls of a single engine light aircraft. Actuator characteristics under investigation include cost, reliability, weight, force, volumetric requirements, power requirements, response characteristics and heat accumulation characteristics. The basic types of actuators were compared for performance characteristics in positioning a control surface model and then were mathematically evaluated in an aircraft to get the closed loop dynamic response characteristics. Conclusions were made as to the suitability of each actuator type for use in an aircraft.

Chemical reacting flows

NASA Astrophysics Data System (ADS)

Lezberg, Erwin A.; Mularz, Edward J.; Liou, Meng-Sing

1991-03-01

The objectives and accomplishments of research in chemical reacting flows, including both experimental and computational problems are described. The experimental research emphasizes the acquisition of reliable reacting-flow data for code validation, the development of chemical kinetics mechanisms, and the understanding of two-phase flow dynamics. Typical results from two nonreacting spray studies are presented. The computational fluid dynamics (CFD) research emphasizes the development of efficient and accurate algorithms and codes, as well as validation of methods and modeling (turbulence and kinetics) for reacting flows. Major developments of the RPLUS code and its application to mixing concepts, the General Electric combustor, and the Government baseline engine for the National Aerospace Plane are detailed. Finally, the turbulence research in the newly established Center for Modeling of Turbulence and Transition (CMOTT) is described.

The FireBGCv2 landscape fire and succession model: a research simulation platform for exploring fire and vegetation dynamics

Treesearch

Robert E. Keane; Rachel A. Loehman; Lisa M. Holsinger

2011-01-01

Fire management faces important emergent issues in the coming years such as climate change, fire exclusion impacts, and wildland-urban development, so new, innovative means are needed to address these challenges. Field studies, while preferable and reliable, will be problematic because of the large time and space scales involved. Therefore, landscape simulation...

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

NASA Astrophysics Data System (ADS)

Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

2008-03-01

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

Bayesian parameter estimation for stochastic models of biological cell migration

NASA Astrophysics Data System (ADS)

Dieterich, Peter; Preuss, Roland

2013-08-01

Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

Toward more realistic projections of soil carbon dynamics by Earth system models

USGS Publications Warehouse

Luo, Y.; Ahlström, Anders; Allison, Steven D.; Batjes, Niels H.; Brovkin, V.; Carvalhais, Nuno; Chappell, Adrian; Ciais, Philippe; Davidson, Eric A.; Finzi, Adien; Georgiou, Katerina; Guenet, Bertrand; Hararuk, Oleksandra; Harden, Jennifer; He, Yujie; Hopkins, Francesca; Jiang, L.; Koven, Charles; Jackson, Robert B.; Jones, Chris D.; Lara, M.; Liang, J.; McGuire, A. David; Parton, William; Peng, Changhui; Randerson, J.; Salazar, Alejandro; Sierra, Carlos A.; Smith, Matthew J.; Tian, Hanqin; Todd-Brown, Katherine E. O; Torn, Margaret S.; van Groenigen, Kees Jan; Wang, Ying; West, Tristram O.; Wei, Yaxing; Wieder, William R.; Xia, Jianyang; Xu, Xia; Xu, Xiaofeng; Zhou, T.

2016-01-01

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Understanding Dynamic Model Validation of a Wind Turbine Generator and a Wind Power Plant: Preprint

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

Muljadi, Eduard; Zhang, Ying Chen; Gevorgian, Vahan

Regional reliability organizations require power plants to validate the dynamic models that represent them to ensure that power systems studies are performed to the best representation of the components installed. In the process of validating a wind power plant (WPP), one must be cognizant of the parameter settings of the wind turbine generators (WTGs) and the operational settings of the WPP. Validating the dynamic model of a WPP is required to be performed periodically. This is because the control parameters of the WTGs and the other supporting components within a WPP may be modified to comply with new grid codesmore » or upgrades to the WTG controller with new capabilities developed by the turbine manufacturers or requested by the plant owners or operators. The diversity within a WPP affects the way we represent it in a model. Diversity within a WPP may be found in the way the WTGs are controlled, the wind resource, the layout of the WPP (electrical diversity), and the type of WTGs used. Each group of WTGs constitutes a significant portion of the output power of the WPP, and their unique and salient behaviors should be represented individually. The objective of this paper is to illustrate the process of dynamic model validations of WTGs and WPPs, the available data recorded that must be screened before it is used for the dynamic validations, and the assumptions made in the dynamic models of the WTG and WPP that must be understood. Without understanding the correct process, the validations may lead to the wrong representations of the WTG and WPP modeled.« less

Precision and reliability of periodically and quasiperiodically driven integrate-and-fire neurons.

PubMed

Tiesinga, P H E

2002-04-01

Neurons in the brain communicate via trains of all-or-none electric events known as spikes. How the brain encodes information using spikes-the neural code-remains elusive. Here the robustness against noise of stimulus-induced neural spike trains is studied in terms of attractors and bifurcations. The dynamics of model neurons converges after a transient onto an attractor yielding a reproducible sequence of spike times. At a bifurcation point the spike times on the attractor change discontinuously when a parameter is varied. Reliability, the stability of the attractor against noise, is reduced when the neuron operates close to a bifurcation point. We determined using analytical spike-time maps the attractor and bifurcation structure of an integrate-and-fire model neuron driven by a periodic or a quasiperiodic piecewise constant current and investigated the stability of attractors against noise. The integrate-and-fire model neuron became mode locked to the periodic current with a rational winding number p/q and produced p spikes per q cycles. There were q attractors. p:q mode-locking regions formed Arnold tongues. In the model, reliability was the highest during 1:1 mode locking when there was only one attractor, as was also observed in recent experiments. The quasiperiodically driven neuron mode locked to either one of the two drive periods, or to a linear combination of both of them. Mode-locking regions were organized in Arnold tongues and reliability was again highest when there was only one attractor. These results show that neuronal reliability in response to the rhythmic drive generated by synchronized networks of neurons is profoundly influenced by the location of the Arnold tongues in parameter space.

Spatial surplus production modeling of Atlantic tunas and billfish.

PubMed

Carruthers, Thomas R; McAllister, Murdoch K; Taylor, Nathan G

2011-10-01

We formulate and simulation-test a spatial surplus production model that provides a basis with which to undertake multispecies, multi-area, stock assessment. Movement between areas is parameterized using a simple gravity model that includes a "residency" parameter that determines the degree of stock mixing among areas. The model is deliberately simple in order to (1) accommodate nontarget species that typically have fewer available data and (2) minimize computational demand to enable simulation evaluation of spatial management strategies. Using this model, we demonstrate that careful consideration of spatial catch and effort data can provide the basis for simple yet reliable spatial stock assessments. If simple spatial dynamics can be assumed, tagging data are not required to reliably estimate spatial distribution and movement. When applied to eight stocks of Atlantic tuna and billfish, the model tracks regional catch data relatively well by approximating local depletions and exchange among high-abundance areas. We use these results to investigate and discuss the implications of using spatially aggregated stock assessment for fisheries in which the distribution of both the population and fishing vary over time.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

PubMed

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

2017-02-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

PubMed Central

Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

2017-01-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge. PMID:28166222

SiC-VJFETs power switching devices: an improved model and parameter optimization technique

NASA Astrophysics Data System (ADS)

Ben Salah, T.; Lahbib, Y.; Morel, H.

2009-12-01

Silicon carbide junction field effect transistor (SiC-JFETs) is a mature power switch newly applied in several industrial applications. SiC-JFETs are often simulated by Spice model in order to predict their electrical behaviour. Although such a model provides sufficient accuracy for some applications, this paper shows that it presents serious shortcomings in terms of the neglect of the body diode model, among many others in circuit model topology. Simulation correction is then mandatory and a new model should be proposed. Moreover, this paper gives an enhanced model based on experimental dc and ac data. New devices are added to the conventional circuit model giving accurate static and dynamic behaviour, an effect not accounted in the Spice model. The improved model is implemented into VHDL-AMS language and steady-state dynamic and transient responses are simulated for many SiC-VJFETs samples. Very simple and reliable optimization algorithm based on the optimization of a cost function is proposed to extract the JFET model parameters. The obtained parameters are verified by comparing errors between simulations results and experimental data.

The long-term reliability of static and dynamic quantitative sensory testing in healthy individuals.

PubMed

Marcuzzi, Anna; Wrigley, Paul J; Dean, Catherine M; Adams, Roger; Hush, Julia M

2017-07-01

Quantitative sensory tests (QSTs) have been increasingly used to investigate alterations in somatosensory function in a wide range of painful conditions. The interpretation of these findings is based on the assumption that the measures are stable and reproducible. To date, reliability of QST has been investigated for short test-retest intervals. The aim of this study was to investigate the long-term reliability of a multimodal QST assessment in healthy people, with testing conducted on 3 occasions over 4 months. Forty-two healthy people were enrolled in the study. Static and dynamic tests were performed, including cold and heat pain threshold (CPT, HPT), mechanical wind-up [wind-up ratio (WUR)], pressure pain threshold (PPT), 2-point discrimination (TPD), and conditioned pain modulation (CPM). Systematic bias, relative reliability and agreement were analysed using repeated measure analysis of variance, intraclass correlation coefficients (ICCs3,1) and SE of the measurement (SEM), respectively. Static QST (CPT, HPT, PPT, and TPD) showed good-to-excellent reliability (ICCs: 0.68-0.90). Dynamic QST (WUR and CPM) showed poor-to-good reliability (ICCs: 0.35-0.61). A significant linear decrease over time was observed for mechanical QST at the back (PPT and TPD) and for CPM (P < 0.01). Static QST were stable over a period of 4 months; however, a small systematic decrease over time has been observed for mechanical QST. Dynamic QST showed considerable variability over time; in particular, CPM using PPT as the test stimulus did not show adequate reliability, suggesting that this test paradigm may be less useful for monitoring individuals over time.

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization

PubMed Central

Chen, Qingkui; Zhao, Deyu; Wang, Jingjuan

2017-01-01

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services. PMID:28777325

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization.

PubMed

Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan

2017-08-04

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

Transport and dielectric properties of water and the influence of coarse-graining: Comparing BMW, SPC/E, and TIP3P models

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

Braun, Daniel; Boresch, Stefan; Steinhauser, Othmar

Long-term molecular dynamics simulations are used to compare the single particle dipole reorientation time, the diffusion constant, the viscosity, and the frequency-dependent dielectric constant of the coarse-grained big multipole water (BMW) model to two common atomistic three-point water models, SPC/E and TIP3P. In particular, the agreement between the calculated viscosity of BMW and the experimental viscosity of water is satisfactory. We also discuss contradictory values for the static dielectric properties reported in the literature. Employing molecular hydrodynamics, we show that the viscosity can be computed from single particle dynamics, circumventing the slow convergence of the standard approaches. Furthermore, our datamore » indicate that the Kivelson relation connecting single particle and collective reorientation time holds true for all systems investigated. Since simulations with coarse-grained force fields often employ extremely large time steps, we also investigate the influence of time step on dynamical properties. We observe a systematic acceleration of system dynamics when increasing the time step. Carefully monitoring energy/temperature conservation is found to be a sufficient criterion for the reliable calculation of dynamical properties. By contrast, recommended criteria based on the ratio of fluctuations of total vs. kinetic energy are not sensitive enough.« less

Determination of dynamic variations in the optical properties of graphene oxide in response to gas exposure based on thin-film interference.

PubMed

Tabassum, Shawana; Dong, Liang; Kumar, Ratnesh

2018-03-05

We present an effective yet simple approach to study the dynamic variations in optical properties (such as the refractive index (RI)) of graphene oxide (GO) when exposed to gases in the visible spectral region, using the thin-film interference method. The dynamic variations in the complex refractive index of GO in response to exposure to a gas is an important factor affecting the performance of GO-based gas sensors. In contrast to the conventional ellipsometry, this method alleviates the need of selecting a dispersion model from among a list of model choices, which is limiting if an applicable model is not known a priori. In addition, the method used is computationally simpler, and does not need to employ any functional approximations. Further advantage over ellipsometry is that no bulky optics is required, and as a result it can be easily integrated into the sensing system, thereby allowing the reliable, simple, and dynamic evaluation of the optical performance of any GO-based gas sensor. In addition, the derived values of the dynamically changing RI values of the GO layer obtained from the method we have employed are corroborated by comparing with the values obtained from ellipsometry.

Gateway-Assisted Retransmission for Lightweight and Reliable IoT Communications.

PubMed

Chang, Hui-Ling; Wang, Cheng-Gang; Wu, Mong-Ting; Tsai, Meng-Hsun; Lin, Chia-Ying

2016-09-22

Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) and Constrained Application Protocol (CoAP) are two protocols supporting publish/subscribe models for IoT devices to publish messages to interested subscribers. Retransmission mechanisms are introduced to compensate for the lack of data reliability. If the device does not receive the acknowledgement (ACK) before retransmission timeout (RTO) expires, the device will retransmit data. Setting an appropriate RTO is important because the delay may be large or retransmission may be too frequent when the RTO is inappropriate. We propose a Gateway-assisted CoAP (GaCoAP) to dynamically compute RTO for devices. Simulation models are proposed to investigate the performance of GaCoAP compared with four other methods. The experiment results show that GaCoAP is more suitable for IoT devices.

Gateway-Assisted Retransmission for Lightweight and Reliable IoT Communications

PubMed Central

Chang, Hui-Ling; Wang, Cheng-Gang; Wu, Mong-Ting; Tsai, Meng-Hsun; Lin, Chia-Ying

2016-01-01

Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) and Constrained Application Protocol (CoAP) are two protocols supporting publish/subscribe models for IoT devices to publish messages to interested subscribers. Retransmission mechanisms are introduced to compensate for the lack of data reliability. If the device does not receive the acknowledgement (ACK) before retransmission timeout (RTO) expires, the device will retransmit data. Setting an appropriate RTO is important because the delay may be large or retransmission may be too frequent when the RTO is inappropriate. We propose a Gateway-assisted CoAP (GaCoAP) to dynamically compute RTO for devices. Simulation models are proposed to investigate the performance of GaCoAP compared with four other methods. The experiment results show that GaCoAP is more suitable for IoT devices. PMID:27669243

A Comprehensive Structural Dynamic Analysis Approach for Multi Mission Earth Entry Vehicle (MMEEV) Development

NASA Technical Reports Server (NTRS)

Perino, Scott; Bayandor, Javid; Siddens, Aaron

2012-01-01

The anticipated NASA Mars Sample Return Mission (MSR) requires a simple and reliable method in which to return collected Martian samples back to earth for scientific analysis. The Multi-Mission Earth Entry Vehicle (MMEEV) is NASA's proposed solution to this MSR requirement. Key aspects of the MMEEV are its reliable and passive operation, energy absorbing foam-composite structure, and modular impact sphere (IS) design. To aid in the development of an EEV design that can be modified for various missions requirements, two fully parametric finite element models were developed. The first model was developed in an explicit finite element code and was designed to evaluate the impact response of the vehicle and payload during the final stage of the vehicle's return to earth. The second model was developed in an explicit code and was designed to evaluate the static and dynamic structural response of the vehicle during launch and reentry. In contrast to most other FE models, built through a Graphical User Interface (GUI) pre-processor, the current model was developed using a coding technique that allows the analyst to quickly change nearly all aspects of the model including: geometric dimensions, material properties, load and boundary conditions, mesh properties, and analysis controls. Using the developed design tool, a full range of proposed designs can quickly be analyzed numerically and thus the design trade space for the EEV can be fully understood. An engineer can then quickly reach the best design for a specific mission and also adapt and optimize the general design for different missions.

Allosteric mechanism of quinoline inhibitors for HIV RT-associated RNase with MD simulation and dynamics fluctuation network.

PubMed

Cai, Yi; Liu, Hao; Chen, Haifeng

2018-03-01

The human immunodeficiency virus (HIV) is a retrovirus which infects T lymphocyte of human body and causes immunodeficiency. Reverse transcriptase inhibitors (RTIs) can inhibit some functions of RT, preventing virus synthesis (double-stranded DNA), so that HIV virus replication can be reduced. Experimental results indicate a series of benzimidazole-based inhibitors which target HIV RT-associated RNase to inhibit the reverse transcription of HIV virus. However, the allosteric mechanism is still unclear. Here, molecular dynamics simulations and dynamics fluctuation network analysis were used to reveal the binding mode between the inhibitors and RT-associated RNase. The most active molecule has more hydrophobic and electrostatic interactions than the less active inhibitor. Dynamics correlation network analysis indicates that the most active inhibitor perturbs the network of RT-associated RNase and decreases the correlation of nodes. 3D-QSAR model suggests that two robust and reliable models were constructed and validated by independent test set. 3D-QSAR model also shows that bulky negatively charged or hydrophilic substituent is favorable to bioactivity. These results reveal the allosteric mechanism of quinoline inhibitors and help to improve the bioactivity. © 2017 John Wiley & Sons A/S.

Modeling and dynamic properties of dual-chamber solid and liquid mixture vibration isolator

NASA Astrophysics Data System (ADS)

Li, F. S.; Chen, Q.; Zhou, J. H.

2016-07-01

The dual-chamber solid and liquid mixture (SALiM) vibration isolator, mainly proposed for vibration isolation of heavy machines with low frequency, consists of four principle parts: SALiM working media including elastic elements and incompressible oil, multi-layers bellows container, rigid reservoir and the oil tube connecting the two vessels. The isolation system under study is governed by a two-degrees-of-freedom (2-DOF) nonlinear equation including quadratic damping. Simplifying the nonlinear damping into viscous damping, the equivalent stiffness and damping model is derived from the equation for the response amplitude. Theoretical analysis and numerical simulation reveal that the isolator's stiffness and damping have multiple properties with different parameters, among which the effects of exciting frequency, vibrating amplitude, quadratic damping coefficient and equivalent stiffness of the two chambers on the isolator's dynamics are discussed in depth. Based on the boundary characteristics of stiffness and damping and the main causes for stiffness hardening effect, improvement strategies are proposed to obtain better dynamic properties. At last, experiments were implemented and the test results were generally consistent with the theoretical ones, which verified the reliability of the nonlinear dynamic model.

A Spalart-Allmaras local correlation-based transition model for Thermo-fuid dynamics

NASA Astrophysics Data System (ADS)

D'Alessandro, V.; Garbuglia, F.; Montelpare, S.; Zoppi, A.

2017-11-01

The study of innovative energy systems often involves complex fluid flows problems and the Computational Fluid-Dynamics (CFD) is one of the main tools of analysis. It is important to put in evidence that in several energy systems the flow field experiences the laminar-to-turbulent transition. Direct Numerical Simulations (DNS) or Large Eddy Simulation (LES) are able to predict the flow transition but they are still inapplicable to the study of real problems due to the significant computational resources requirements. Differently standard Reynolds Averaged Navier Stokes (RANS) approaches are not always reliable since they assume a fully turbulent regime. In order to overcome this drawback in the recent years some locally formulated transition RANS models have been developed. In this work, we present a local correlation-based transition approach adding two equations that control the laminar-toturbulent transition process -γ and \\[\\overset{}{\\mathop{{{\\operatorname{Re}}θ, \\text{t}}}} \\] - to the well-known Spalart-Allmaras (SA) turbulence model. The new model was implemented within OpenFOAM code. The energy equation is also implemented in order to evaluate the model performance in thermal-fluid dynamics applications. In all the considered cases a very good agreement between numerical and experimental data was observed.

Modeling structured population dynamics using data from unmarked individuals

USGS Publications Warehouse

Grant, Evan H. Campbell; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew

2014-01-01

The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.

Integrated Tokamak modeling: When physics informs engineering and research planning

NASA Astrophysics Data System (ADS)

Poli, Francesca Maria

2018-05-01

Modeling tokamaks enables a deeper understanding of how to run and control our experiments and how to design stable and reliable reactors. We model tokamaks to understand the nonlinear dynamics of plasmas embedded in magnetic fields and contained by finite size, conducting structures, and the interplay between turbulence, magneto-hydrodynamic instabilities, and wave propagation. This tutorial guides through the components of a tokamak simulator, highlighting how high-fidelity simulations can guide the development of reduced models that can be used to understand how the dynamics at a small scale and short time scales affects macroscopic transport and global stability of plasmas. It discusses the important role that reduced models have in the modeling of an entire plasma discharge from startup to termination, the limits of these models, and how they can be improved. It discusses the important role that efficient workflows have in the coupling between codes, in the validation of models against experiments and in the verification of theoretical models. Finally, it reviews the status of integrated modeling and addresses the gaps and needs towards predictions of future devices and fusion reactors.

Integrated Tokamak modeling: When physics informs engineering and research planning

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

Poli, Francesca Maria

Modeling tokamaks enables a deeper understanding of how to run and control our experiments and how to design stable and reliable reactors. We model tokamaks to understand the nonlinear dynamics of plasmas embedded in magnetic fields and contained by finite size, conducting structures, and the interplay between turbulence, magneto-hydrodynamic instabilities, and wave propagation. This tutorial guides through the components of a tokamak simulator, highlighting how high-fidelity simulations can guide the development of reduced models that can be used to understand how the dynamics at a small scale and short time scales affects macroscopic transport and global stability of plasmas. Itmore » discusses the important role that reduced models have in the modeling of an entire plasma discharge from startup to termination, the limits of these models, and how they can be improved. It discusses the important role that efficient workflows have in the coupling between codes, in the validation of models against experiments and in the verification of theoretical models. Finally, it reviews the status of integrated modeling and addresses the gaps and needs towards predictions of future devices and fusion reactors.« less

Integrated Tokamak modeling: When physics informs engineering and research planning

DOE PAGES

Poli, Francesca Maria

2018-05-01

Modeling tokamaks enables a deeper understanding of how to run and control our experiments and how to design stable and reliable reactors. We model tokamaks to understand the nonlinear dynamics of plasmas embedded in magnetic fields and contained by finite size, conducting structures, and the interplay between turbulence, magneto-hydrodynamic instabilities, and wave propagation. This tutorial guides through the components of a tokamak simulator, highlighting how high-fidelity simulations can guide the development of reduced models that can be used to understand how the dynamics at a small scale and short time scales affects macroscopic transport and global stability of plasmas. Itmore » discusses the important role that reduced models have in the modeling of an entire plasma discharge from startup to termination, the limits of these models, and how they can be improved. It discusses the important role that efficient workflows have in the coupling between codes, in the validation of models against experiments and in the verification of theoretical models. Finally, it reviews the status of integrated modeling and addresses the gaps and needs towards predictions of future devices and fusion reactors.« less

Dynamic simulation of knee-joint loading during gait using force-feedback control and surrogate contact modelling.

PubMed

Walter, Jonathan P; Pandy, Marcus G

2017-10-01

The aim of this study was to perform multi-body, muscle-driven, forward-dynamics simulations of human gait using a 6-degree-of-freedom (6-DOF) model of the knee in tandem with a surrogate model of articular contact and force control. A forward-dynamics simulation incorporating position, velocity and contact force-feedback control (FFC) was used to track full-body motion capture data recorded for multiple trials of level walking and stair descent performed by two individuals with instrumented knee implants. Tibiofemoral contact force errors for FFC were compared against those obtained from a standard computed muscle control algorithm (CMC) with a 6-DOF knee contact model (CMC6); CMC with a 1-DOF translating hinge-knee model (CMC1); and static optimization with a 1-DOF translating hinge-knee model (SO). Tibiofemoral joint loads predicted by FFC and CMC6 were comparable for level walking, however FFC produced more accurate results for stair descent. SO yielded reasonable predictions of joint contact loading for level walking but significant differences between model and experiment were observed for stair descent. CMC1 produced the least accurate predictions of tibiofemoral contact loads for both tasks. Our findings suggest that reliable estimates of knee-joint loading may be obtained by incorporating position, velocity and force-feedback control with a multi-DOF model of joint contact in a forward-dynamics simulation of gait. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Prediction of Flutter Boundary Using Flutter Margin for The Discrete-Time System

NASA Astrophysics Data System (ADS)

Dwi Saputra, Angga; Wibawa Purabaya, R.

2018-04-01

Flutter testing in a wind tunnel is generally conducted at subcritical speeds to avoid damages. Hence, The flutter speed has to be predicted from the behavior some of its stability criteria estimated against the dynamic pressure or flight speed. Therefore, it is quite important for a reliable flutter prediction method to estimates flutter boundary. This paper summarizes the flutter testing of a wing cantilever model in a wind tunnel. The model has two degree of freedom; they are bending and torsion modes. The flutter test was conducted in a subsonic wind tunnel. The dynamic data responses was measured by two accelerometers that were mounted on leading edge and center of wing tip. The measurement was repeated while the wind speed increased. The dynamic responses were used to determine the parameter flutter margin for the discrete-time system. The flutter boundary of the model was estimated using extrapolation of the parameter flutter margin against the dynamic pressure. The parameter flutter margin for the discrete-time system has a better performance for flutter prediction than the modal parameters. A model with two degree freedom and experiencing classical flutter, the parameter flutter margin for the discrete-time system gives a satisfying result in prediction of flutter boundary on subsonic wind tunnel test.

A Passive System Reliability Analysis for a Station Blackout

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

Brunett, Acacia; Bucknor, Matthew; Grabaskas, David

2015-05-03

The latest iterations of advanced reactor designs have included increased reliance on passive safety systems to maintain plant integrity during unplanned sequences. While these systems are advantageous in reducing the reliance on human intervention and availability of power, the phenomenological foundations on which these systems are built require a novel approach to a reliability assessment. Passive systems possess the unique ability to fail functionally without failing physically, a result of their explicit dependency on existing boundary conditions that drive their operating mode and capacity. Argonne National Laboratory is performing ongoing analyses that demonstrate various methodologies for the characterization of passivemore » system reliability within a probabilistic framework. Two reliability analysis techniques are utilized in this work. The first approach, the Reliability Method for Passive Systems, provides a mechanistic technique employing deterministic models and conventional static event trees. The second approach, a simulation-based technique, utilizes discrete dynamic event trees to treat time- dependent phenomena during scenario evolution. For this demonstration analysis, both reliability assessment techniques are used to analyze an extended station blackout in a pool-type sodium fast reactor (SFR) coupled with a reactor cavity cooling system (RCCS). This work demonstrates the entire process of a passive system reliability analysis, including identification of important parameters and failure metrics, treatment of uncertainties and analysis of results.« less

Determination of Quantum Chemistry Based Force Fields for Molecular Dynamics Simulations of Aromatic Polymers

NASA Technical Reports Server (NTRS)

Jaffe, Richard; Langhoff, Stephen R. (Technical Monitor)

1995-01-01

Ab initio quantum chemistry calculations for model molecules can be used to parameterize force fields for molecular dynamics simulations of polymers. Emphasis in our research group is on using quantum chemistry-based force fields for molecular dynamics simulations of organic polymers in the melt and glassy states, but the methodology is applicable to simulations of small molecules, multicomponent systems and solutions. Special attention is paid to deriving reliable descriptions of the non-bonded and electrostatic interactions. Several procedures have been developed for deriving and calibrating these parameters. Our force fields for aromatic polyimide simulations will be described. In this application, the intermolecular interactions are the critical factor in determining many properties of the polymer (including its color).

Lewis Structures Technology, 1988. Volume 3: Structural Integrity Fatigue and Fracture Wind Turbines HOST

NASA Technical Reports Server (NTRS)

1988-01-01

The charter of the Structures Division is to perform and disseminate results of research conducted in support of aerospace engine structures. These results have a wide range of applicability to practioners of structural engineering mechanics beyond the aerospace arena. The specific purpose of the symposium was to familiarize the engineering structures community with the depth and range of research performed by the division and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive evaluation, constitutive models and experimental capabilities, dynamic systems, fatigue and damage, wind turbines, hot section technology (HOST), aeroelasticity, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics, and structural mechanics computer codes.

Image contrast mechanisms in dynamic friction force microscopy: Antimony particles on graphite

NASA Astrophysics Data System (ADS)

Mertens, Felix; Göddenhenrich, Thomas; Dietzel, Dirk; Schirmeisen, Andre

2017-01-01

Dynamic Friction Force Microscopy (DFFM) is a technique based on Atomic Force Microscopy (AFM) where resonance oscillations of the cantilever are excited by lateral actuation of the sample. During this process, the AFM tip in contact with the sample undergoes a complex movement which consists of alternating periods of sticking and sliding. Therefore, DFFM can give access to dynamic transition effects in friction that are not accessible by alternative techniques. Using antimony nanoparticles on graphite as a model system, we analyzed how combined influences of friction and topography can effect different experimental configurations of DFFM. Based on the experimental results, for example, contrast inversion between fractional resonance and band excitation imaging strategies to extract reliable tribological information from DFFM images are devised.

Climate variation drives dengue dynamics

PubMed Central

Xu, Lei; Stige, Leif C.; Chan, Kung-Sik; Zhou, Jie; Yang, Jun; Sang, Shaowei; Wang, Ming; Yang, Zhicong; Yan, Ziqiang; Jiang, Tong; Lu, Liang; Yue, Yujuan; Liu, Xiaobo; Lin, Hualiang; Xu, Jianguo; Liu, Qiyong; Stenseth, Nils Chr.

2017-01-01

Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005–2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics—years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies. PMID:27940911

Applying A Multi-Objective Based Procedure to SWAT Modelling in Alpine Catchments

NASA Astrophysics Data System (ADS)

Tuo, Y.; Disse, M.; Chiogna, G.

2017-12-01

In alpine catchments, water management practices can lead to conflicts between upstream and downstream stakeholders, like in the Adige river basin (Italy). A correct prediction of available water resources plays an important part, for example, in defining how much water can be stored for hydropower production in upstream reservoirs without affecting agricultural activities downstream. Snow is a crucial hydrological component that highly affects seasonal behavior of streamflow. Therefore, a realistic representation of snow dynamics is fundamental for water management operations in alpine catchments. The Soil and Water Assessment Tool (SWAT) model has been applied in alpine catchments worldwide. However, during model calibration of catchment scale applications, snow parameters were generally estimated based on streamflow records rather than on snow measurements. This may lead to streamflow predictions with wrong snow melt contribution. This work highlights the importance of considering snow measurements in the calibration of the SWAT model for alpine hydrology and compares various calibration methodologies. In addition to discharge records, snow water equivalent time series of both subbasin scale and monitoring station were also utilized to evaluate the model performance by comparing with the SWAT subbasin and elevation band snow outputs. Comparing model results obtained calibrating the model using discharge data only and discharge data along with snow water equivalent data, we show that the latter approach allows us to improve the reliability of snow simulations while maintaining good estimations of streamflow. With a more reliable representation of snow dynamics, the hydrological model can provide more accurate references for proposing adequate water management solutions. This study offers to the wide SWAT user community an effective approach to improve streamflow predictions in alpine catchments and hence support decision makers in water allocation.

Dynamical properties of water in living cells

NASA Astrophysics Data System (ADS)

Piazza, Irina; Cupane, Antonio; Barbier, Emmanuel L.; Rome, Claire; Collomb, Nora; Ollivier, Jacques; Gonzalez, Miguel A.; Natali, Francesca

2018-02-01

With the aim of studying the effect of water dynamics on the properties of biological systems, in this paper, we present a quasi-elastic neutron scattering study on three different types of living cells, differing both in their morphological and tumor properties. The measured scattering signal, which essentially originates from hydrogen atoms present in the investigated systems, has been analyzed using a global fitting strategy using an optimized theoretical model that considers various classes of hydrogen atoms and allows disentangling diffusive and rotational motions. The approach has been carefully validated by checking the reliability of the calculation of parameters and their 99% confidence intervals. We demonstrate that quasi-elastic neutron scattering is a suitable experimental technique to characterize the dynamics of intracellular water in the angstrom/picosecond space/time scale and to investigate the effect of water dynamics on cellular biodiversity.

A vacuum microgripping tool with integrated vibration releasing capability

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

Rong, Weibin; Fan, Zenghua, E-mail: zenghua-fan@163.com; Wang, Lefeng

2014-08-01

Pick-and-place of micro-objects is a basic task in various micromanipulation demands. Reliable releasing of micro-objects is usually disturbed due to strong scale effects. This paper focuses on a vacuum micro-gripper with vibration releasing functionality, which was designed and assembled for reliable micromanipulation tasks. Accordingly, a vibration releasing strategy of implementing a piezoelectric actuator on the vacuum microgripping tool is presented to address the releasing problem. The releasing mechanism was illustrated using a dynamic micro contact model. This model was developed via theoretical analysis, simulations and pull-off force measurement using atomic force microscopy. Micromanipulation experiments were conducted to verify the performancemore » of the vacuum micro-gripper. The results show that, with the assistance of the vibration releasing, the vacuum microgripping tool can achieve reliable release of micro-objects. A releasing location accuracy of 4.5±0.5 μm and a successful releasing rate of around 100% (which is based on 110 trials) were achieved for manipulating polystyrene microspheres with radius of 35–100 μm.« less

Predictive Coding of Dynamical Variables in Balanced Spiking Networks

PubMed Central

Boerlin, Martin; Machens, Christian K.; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. PMID:24244113

Slope-scale dynamic states of rockfalls

NASA Astrophysics Data System (ADS)

Agliardi, F.; Crosta, G. B.

2009-04-01

Rockfalls are common earth surface phenomena characterised by complex dynamics at the slope scale, depending on local block kinematics and slope geometry. We investigated the nature of this slope-scale dynamics by parametric 3D numerical modelling of rockfalls over synthetic slopes with different inclination, roughness and spatial resolution. Simulations were performed through an original code specifically designed for rockfall modeling, incorporating kinematic and hybrid algorithms with different damping functions available to model local energy loss by impact and pure rolling. Modelling results in terms of average velocity profiles suggest that three dynamic regimes (i.e. decelerating, steady-state and accelerating), previously recognized in the literature through laboratory experiments on granular flows, can set up at the slope scale depending on slope average inclination and roughness. Sharp changes in rock fall kinematics, including motion type and lateral dispersion of trajectories, are associated to the transition among different regimes. Associated threshold conditions, portrayed in "phase diagrams" as slope-roughness critical lines, were analysed depending on block size, impact/rebound angles, velocity and energy, and model spatial resolution. Motion in regime B (i.e. steady state) is governed by a slope-scale "viscous friction" with average velocity linearly related to the sine of slope inclination. This suggest an analogy between rockfall motion in regime B and newtonian flow, whereas in regime C (i.e. accelerating) an analogy with a dilatant flow was observed. Thus, although local behavior of single falling blocks is well described by rigid body dynamics, the slope scale dynamics of rockfalls seem to statistically approach that of granular media. Possible outcomes of these findings include a discussion of the transition from rockfall to granular flow, the evaluation of the reliability of predictive models, and the implementation of criteria for a preliminary evaluation of hazard assessment and countermeasure planning.

A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

USGS Publications Warehouse

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

NASA Astrophysics Data System (ADS)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-06-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Real-time stereo matching using orthogonal reliability-based dynamic programming.

PubMed

Gong, Minglun; Yang, Yee-Hong

2007-03-01

A novel algorithm is presented in this paper for estimating reliable stereo matches in real time. Based on the dynamic programming-based technique we previously proposed, the new algorithm can generate semi-dense disparity maps using as few as two dynamic programming passes. The iterative best path tracing process used in traditional dynamic programming is replaced by a local minimum searching process, making the algorithm suitable for parallel execution. Most computations are implemented on programmable graphics hardware, which improves the processing speed and makes real-time estimation possible. The experiments on the four new Middlebury stereo datasets show that, on an ATI Radeon X800 card, the presented algorithm can produce reliable matches for 60% approximately 80% of pixels at the rate of 10 approximately 20 frames per second. If needed, the algorithm can be configured for generating full density disparity maps.

Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

NASA Technical Reports Server (NTRS)

Mathias, Donovan L.; Go, Susie

2006-01-01

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool performs a Monte Carlo analysis to provide statistical estimates. Example results of an architecture system reliability study are summarized for an exploration system concept using heritage data from liquid-fueled expendable Saturn V/Apollo launch vehicles.

Design of RF MEMS switches without pull-in instability

NASA Astrophysics Data System (ADS)

Proctor, W. Cyrus; Richards, Gregory P.; Shen, Chongyi; Skorczewski, Tyler; Wang, Min; Zhang, Jingyan; Zhong, Peng; Massad, Jordan E.; Smith, Ralph

2010-04-01

Micro-electro-mechanical systems (MEMS) switches for radio-frequency (RF) signals have certain advantages over solid-state switches, such as lower insertion loss, higher isolation, and lower static power dissipation. Mechanical dynamics can be a determining factor for the reliability of RF MEMS. The RF MEMS ohmic switch discussed in this paper consists of a plate suspended over an actuation pad by four double-cantilever springs. Closing the switch with a simple step actuation voltage typically causes the plate to rebound from its electrical contacts. The rebound interrupts the signal continuity and degrades the performance, reliability and durability of the switch. The switching dynamics are complicated by a nonlinear, electrostatic pull-in instability that causes high accelerations. Slow actuation and tailored voltage control signals can mitigate switch bouncing and effects of the pull-in instability; however, slow switching speed and overly-complex input signals can significantly penalize overall system-level performance. Examination of a balanced and optimized alternative switching solution is sought. A step toward one solution is to consider a pull-in-free switch design. In this paper, determine how simple RC-circuit drive signals and particular structural properties influence the mechanical dynamics of an RF MEMS switch designed without a pull-in instability. The approach is to develop a validated modeling capability and subsequently study switch behavior for variable drive signals and switch design parameters. In support of project development, specifiable design parameters and constraints will be provided. Moreover, transient data of RF MEMS switches from laser Doppler velocimetry will be provided for model validation tasks. Analysis showed that a RF MEMS switch could feasibly be designed with a single pulse waveform and no pull-in instability and achieve comparable results to previous waveform designs. The switch design could reliably close in a timely manner, with small contact velocity, usually with little to no rebound even when considering manufacturing variability.

Non-linear dynamical classification of short time series of the rössler system in high noise regimes.

PubMed

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E; Poizner, Howard; Sejnowski, Terrence J

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson's disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to -30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A' under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data.

Non-Linear Dynamical Classification of Short Time Series of the Rössler System in High Noise Regimes

PubMed Central

Lainscsek, Claudia; Weyhenmeyer, Jonathan; Hernandez, Manuel E.; Poizner, Howard; Sejnowski, Terrence J.

2013-01-01

Time series analysis with delay differential equations (DDEs) reveals non-linear properties of the underlying dynamical system and can serve as a non-linear time-domain classification tool. Here global DDE models were used to analyze short segments of simulated time series from a known dynamical system, the Rössler system, in high noise regimes. In a companion paper, we apply the DDE model developed here to classify short segments of encephalographic (EEG) data recorded from patients with Parkinson’s disease and healthy subjects. Nine simulated subjects in each of two distinct classes were generated by varying the bifurcation parameter b and keeping the other two parameters (a and c) of the Rössler system fixed. All choices of b were in the chaotic parameter range. We diluted the simulated data using white noise ranging from 10 to −30 dB signal-to-noise ratios (SNR). Structure selection was supervised by selecting the number of terms, delays, and order of non-linearity of the model DDE model that best linearly separated the two classes of data. The distances d from the linear dividing hyperplane was then used to assess the classification performance by computing the area A′ under the ROC curve. The selected model was tested on untrained data using repeated random sub-sampling validation. DDEs were able to accurately distinguish the two dynamical conditions, and moreover, to quantify the changes in the dynamics. There was a significant correlation between the dynamical bifurcation parameter b of the simulated data and the classification parameter d from our analysis. This correlation still held for new simulated subjects with new dynamical parameters selected from each of the two dynamical regimes. Furthermore, the correlation was robust to added noise, being significant even when the noise was greater than the signal. We conclude that DDE models may be used as a generalizable and reliable classification tool for even small segments of noisy data. PMID:24379798

Stability, Nonlinearity and Reliability of Electrostatically Actuated MEMS Devices

PubMed Central

Zhang, Wen-Ming; Meng, Guang; Chen, Di

2007-01-01

Electrostatic micro-electro-mechanical system (MEMS) is a special branch with a wide range of applications in sensing and actuating devices in MEMS. This paper provides a survey and analysis of the electrostatic force of importance in MEMS, its physical model, scaling effect, stability, nonlinearity and reliability in detail. It is necessary to understand the effects of electrostatic forces in MEMS and then many phenomena of practical importance, such as pull-in instability and the effects of effective stiffness, dielectric charging, stress gradient, temperature on the pull-in voltage, nonlinear dynamic effects and reliability due to electrostatic forces occurred in MEMS can be explained scientifically, and consequently the great potential of MEMS technology could be explored effectively and utilized optimally. A simplified parallel-plate capacitor model is proposed to investigate the resonance response, inherent nonlinearity, stiffness softened effect and coupled nonlinear effect of the typical electrostatically actuated MEMS devices. Many failure modes and mechanisms and various methods and techniques, including materials selection, reasonable design and extending the controllable travel range used to analyze and reduce the failures are discussed in the electrostatically actuated MEMS devices. Numerical simulations and discussions indicate that the effects of instability, nonlinear characteristics and reliability subjected to electrostatic forces cannot be ignored and are in need of further investigation.

Forecasting infectious disease emergence subject to seasonal forcing.

PubMed

Miller, Paige B; O'Dea, Eamon B; Rohani, Pejman; Drake, John M

2017-09-06

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models. We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic. Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly. Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

Dielectric properties of organic solvents from non-polarizable molecular dynamics simulation with electronic continuum model and density functional theory.

PubMed

Lee, Sanghun; Park, Sung Soo

2011-11-03

Dielectric constants of electrolytic organic solvents are calculated employing nonpolarizable Molecular Dynamics simulation with Electronic Continuum (MDEC) model and Density Functional Theory. The molecular polarizabilities are obtained by the B3LYP/6-311++G(d,p) level of theory to estimate high-frequency refractive indices while the densities and dipole moment fluctuations are computed using nonpolarizable MD simulations. The dielectric constants reproduced from these procedures are evaluated to provide a reliable approach for estimating the experimental data. An additional feature, two representative solvents which have similar molecular weights but are different dielectric properties, i.e., ethyl methyl carbonate and propylene carbonate, are compared using MD simulations and the distinctly different dielectric behaviors are observed at short times as well as at long times.

Electromechanical coupling factor of capacitive micromachined ultrasonic transducers.

PubMed

Caronti, Alessandro; Carotenuto, Riccardo; Pappalardo, Massimo

2003-01-01

Recently, a linear, analytical distributed model for capacitive micromachined ultrasonic transducers (CMUTs) was presented, and an electromechanical equivalent circuit based on the theory reported was used to describe the behavior of the transducer [IEEE Trans. Ultrason. Ferroelectr. Freq. Control 49, 159-168 (2002)]. The distributed model is applied here to calculate the dynamic coupling factor k(w) of a lossless CMUT, based on a definition that involves the energies stored in a dynamic vibration cycle, and the results are compared with those obtained with a lumped model. A strong discrepancy is found between the two models as the bias voltage increases. The lumped model predicts an increasing dynamic k factor up to unity, whereas the distributed model predicts a more realistic saturation of this parameter to values substantially lower. It is demonstrated that the maximum value of k(w), corresponding to an operating point close to the diaphragm collapse, is 0.4 for a CMUT single cell with a circular membrane diaphragm and no parasitic capacitance (0.36 for a cell with a circular plate diaphragm). This means that the dynamic coupling factor of a CMUT is comparable to that of a piezoceramic plate oscillating in the thickness mode. Parasitic capacitance decreases the value of k(w), because it does not contribute to the energy conversion. The effective coupling factor k(eff) is also investigated, showing that this parameter coincides with k(w) within the lumped model approximation, but a quite different result is obtained if a computation is made with the more accurate distributed model. As a consequence, k(eff), which can be measured from the transducer electrical impedance, does not give a reliable value of the actual dynamic coupling factor.

Electromechanical coupling factor of capacitive micromachined ultrasonic transducers

NASA Astrophysics Data System (ADS)

Caronti, Alessandro; Carotenuto, Riccardo; Pappalardo, Massimo

2003-01-01

Recently, a linear, analytical distributed model for capacitive micromachined ultrasonic transducers (CMUTs) was presented, and an electromechanical equivalent circuit based on the theory reported was used to describe the behavior of the transducer [IEEE Trans. Ultrason. Ferroelectr. Freq. Control 49, 159-168 (2002)]. The distributed model is applied here to calculate the dynamic coupling factor kw of a lossless CMUT, based on a definition that involves the energies stored in a dynamic vibration cycle, and the results are compared with those obtained with a lumped model. A strong discrepancy is found between the two models as the bias voltage increases. The lumped model predicts an increasing dynamic k factor up to unity, whereas the distributed model predicts a more realistic saturation of this parameter to values substantially lower. It is demonstrated that the maximum value of kw, corresponding to an operating point close to the diaphragm collapse, is 0.4 for a CMUT single cell with a circular membrane diaphragm and no parasitic capacitance (0.36 for a cell with a circular plate diaphragm). This means that the dynamic coupling factor of a CMUT is comparable to that of a piezoceramic plate oscillating in the thickness mode. Parasitic capacitance decreases the value of kw, because it does not contribute to the energy conversion. The effective coupling factor keff is also investigated, showing that this parameter coincides with kw within the lumped model approximation, but a quite different result is obtained if a computation is made with the more accurate distributed model. As a consequence, keff, which can be measured from the transducer electrical impedance, does not give a reliable value of the actual dynamic coupling factor.

Numerical simulation of the pollution formed by exhaust jets at the ground running procedure

NASA Astrophysics Data System (ADS)

Korotaeva, T. A.; Turchinovich, A. O.

2016-10-01

The paper presents an approach that is new for aviation-related ecology. The approach allows defining spatial distribution of pollutant concentrations released at engine ground running procedure (GRP) using full gas-dynamic models. For the first time such a task is modeled in three-dimensional approximation in the framework of the numerical solution of the Navier-Stokes equations with taking into account a kinetic model of interaction between the components of engine exhaust and air. The complex pattern of gas-dynamic flow that occurs at the flow around an aircraft with the jet exhausts that interact with each other, air, jet blast deflector (JBD), and surface of the airplane has been studied in the present work. The numerical technique developed for calculating the concentrations of pollutants produced at the GRP stage permits to define level, character, and area of contamination more reliable and increase accuracy in definition of sanitary protection zones.

Issues associated with modelling of proton exchange membrane fuel cell by computational fluid dynamics

NASA Astrophysics Data System (ADS)

Bednarek, Tomasz; Tsotridis, Georgios

2017-03-01

The objective of the current study is to highlight possible limitations and difficulties associated with Computational Fluid Dynamics in PEM single fuel cell modelling. It is shown that an appropriate convergence methodology should be applied for steady-state solutions, due to inherent numerical instabilities. A single channel fuel cell model has been taken as numerical example. Results are evaluated for quantitative as well qualitative points of view. The contribution to the polarization curve of the different fuel cell components such as bi-polar plates, gas diffusion layers, catalyst layers and membrane was investigated via their effects on the overpotentials. Furthermore, the potential losses corresponding to reaction kinetics, due to ohmic and mas transport limitations and the effect of the exchange current density and open circuit voltage, were also investigated. It is highlighted that the lack of reliable and robust input data is one of the issues for obtaining accurate results.

Growing Land-Sea Temperature Contrast and the Intensification of Arctic Cyclones

NASA Astrophysics Data System (ADS)

Day, Jonathan J.; Hodges, Kevin I.

2018-04-01

Cyclones play an important role in the coupled dynamics of the Arctic climate system on a range of time scales. Modeling studies suggest that storminess will increase in Arctic summer due to enhanced land-sea thermal contrast along the Arctic coastline, in a region known as the Arctic Frontal Zone (AFZ). However, the climate models used in these studies are poor at reproducing the present-day Arctic summer cyclone climatology and so their projections of Arctic cyclones and related quantities, such as sea ice, may not be reliable. In this study we perform composite analysis of Arctic cyclone statistics using AFZ variability as an analog for climate change. High AFZ years are characterized both by increased cyclone frequency and dynamical intensity, compared to low years. Importantly, the size of the response in this analog suggests that General Circulation Models may underestimate the response of Arctic cyclones to climate change, given a similar change in baroclinicity.

Scale-free avalanches in the multifractal random walk

NASA Astrophysics Data System (ADS)

Bartolozzi, M.

2007-06-01

Avalanches, or Avalanche-like, events are often observed in the dynamical behaviour of many complex systems which span from solar flaring to the Earth's crust dynamics and from traffic flows to financial markets. Self-organized criticality (SOC) is one of the most popular theories able to explain this intermittent charge/discharge behaviour. Despite a large amount of theoretical work, empirical tests for SOC are still in their infancy. In the present paper we address the common problem of revealing SOC from a simple time series without having much information about the underlying system. As a working example we use a modified version of the multifractal random walk originally proposed as a model for the stock market dynamics. The study reveals, despite the lack of the typical ingredients of SOC, an avalanche-like dynamics similar to that of many physical systems. While, on one hand, the results confirm the relevance of cascade models in representing turbulent-like phenomena, on the other, they also raise the question about the current state of reliability of SOC inference from time series analysis.

A minimalistic approach to static and dynamic electron correlations: Amending generalized valence bond method with extended random phase approximation correlation correction

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

Chatterjee, Koushik; Jawulski, Konrad; Pastorczak, Ewa

A perfect-pairing generalized valence bond (GVB) approximation is known to be one of the simplest approximations, which allows one to capture the essence of static correlation in molecular systems. In spite of its attractive feature of being relatively computationally efficient, this approximation misses a large portion of dynamic correlation and does not offer sufficient accuracy to be generally useful for studying electronic structure of molecules. We propose to correct the GVB model and alleviate some of its deficiencies by amending it with the correlation energy correction derived from the recently formulated extended random phase approximation (ERPA). On the examples ofmore » systems of diverse electronic structures, we show that the resulting ERPA-GVB method greatly improves upon the GVB model. ERPA-GVB recovers most of the electron correlation and it yields energy barrier heights of excellent accuracy. Thanks to a balanced treatment of static and dynamic correlation, ERPA-GVB stays reliable when one moves from systems dominated by dynamic electron correlation to those for which the static correlation comes into play.« less

The study on dynamic properties of monolithic ball end mills with various slenderness

NASA Astrophysics Data System (ADS)

Wojciechowski, Szymon; Tabaszewski, Maciej; Krolczyk, Grzegorz M.; Maruda, Radosław W.

2017-10-01

The reliable determination of modal mass, damping and stiffness coefficient (modal parameters) for the particular machine-toolholder-tool system is essential for the accurate estimation of vibrations, stability and thus the machined surface finish formed during the milling process. Therefore, this paper focuses on the analysis of ball end mill's dynamical properties. The tools investigated during this study are monolithic ball end mills with different slenderness values, made of coated cemented carbide. These kinds of tools are very often applied during the precise milling of curvilinear surfaces. The research program included the impulse test carried out for the investigated tools clamped in the hydraulic toolholder. The obtained modal parameters were further applied in the developed tool's instantaneous deflection model, in order to estimate the tool's working part vibrations during precise milling. The application of the proposed dynamics model involved also the determination of instantaneous cutting forces on the basis of the mechanistic approach. The research revealed that ball end mill's slenderness can be considered as an important milling dynamics and machined surface quality indicator.

Optimization of an electromagnetic linear actuator using a network and a finite element model

NASA Astrophysics Data System (ADS)

Neubert, Holger; Kamusella, Alfred; Lienig, Jens

2011-03-01

Model based design optimization leads to robust solutions only if the statistical deviations of design, load and ambient parameters from nominal values are considered. We describe an optimization methodology that involves these deviations as stochastic variables for an exemplary electromagnetic actuator used to drive a Braille printer. A combined model simulates the dynamic behavior of the actuator and its non-linear load. It consists of a dynamic network model and a stationary magnetic finite element (FE) model. The network model utilizes lookup tables of the magnetic force and the flux linkage computed by the FE model. After a sensitivity analysis using design of experiment (DoE) methods and a nominal optimization based on gradient methods, a robust design optimization is performed. Selected design variables are involved in form of their density functions. In order to reduce the computational effort we use response surfaces instead of the combined system model obtained in all stochastic analysis steps. Thus, Monte-Carlo simulations can be applied. As a result we found an optimum system design meeting our requirements with regard to function and reliability.

Measuring Relativistic effects in the field of the Earth with Laser Ranged Satellites and the LARASE research program

NASA Astrophysics Data System (ADS)

Lucchesi, David; Anselmo, Luciano; Bassan, Massimo; Magnafico, Carmelo; Pardini, Carmen; Peron, Roberto; Pucacco, Giuseppe; Stanga, Ruggero; Visco, Massimo

2017-04-01

The main goal of the LARASE (LAser RAnged Satellites Experiment) research program is to obtain refined tests of Einstein's theory of General Relativity (GR) by means of very precise measurements of the round-trip time among a number of ground stations of the International Laser Ranging Service (ILRS) network and a set of geodetic satellites. These measurements are guaranteed by means of the powerful and precise Satellite Laser Ranging (SLR) technique. In particular, a big effort of LARASE is dedicated to improve the dynamical models of the LAGEOS, LAGEOS II and LARES satellites, with the objective to obtain a more precise and accurate determination of their orbit. These activities contribute to reach a final error budget that should be robust and reliable in the evaluation of the main systematic errors sources that come to play a major role in masking the relativistic precession on the orbit of these laser-ranged satellites. These error sources may be of gravitational and non-gravitational origin. It is important to stress that a more accurate and precise orbit determination, based on more reliable dynamical models, represents a fundamental prerequisite in order to reach a sub-mm precision in the root-mean-square of the SLR range residuals and, consequently, to gather benefits in the fields of geophysics and space geodesy, such as stations coordinates knowledge, geocenter determination and the realization of the Earth's reference frame. The results reached over the last year will be presented in terms of the improvements achieved in the dynamical model, in the orbit determination and, finally, in the measurement of the relativistic precessions that act on the orbit of the satellites considered.

Lattice Boltzmann modeling to explain volcano acoustic source.

PubMed

Brogi, Federico; Ripepe, Maurizio; Bonadonna, Costanza

2018-06-22

Acoustic pressure is largely used to monitor explosive activity at volcanoes and has become one of the most promising technique to monitor volcanoes also at large scale. However, no clear relation between the fluid dynamics of explosive eruptions and the associated acoustic signals has yet been defined. Linear acoustic has been applied to derive source parameters in the case of strong explosive eruptions which are well-known to be driven by large overpressure of the magmatic fluids. Asymmetric acoustic waveforms are generally considered as the evidence for supersonic explosive dynamics also for small explosive regimes. We have used Lattice-Boltzmann modeling of the eruptive fluid dynamics to analyse the acoustic wavefield produced by different flow regimes. We demonstrate that acoustic waveform well reproduces the flow dynamics of a subsonic fluid injection related to discrete explosive events. Different volumetric flow rate, at low-Mach regimes, can explain both the observed symmetric and asymmetric waveform. Hence, asymmetric waveforms are not necessarily related to the shock/supersonic fluid dynamics of the source. As a result, we highlight an ambiguity in the general interpretation of volcano acoustic signals for the retrieval of key eruption source parameters, necessary for a reliable volcanic hazard assessment.

Experimental investigations of visco-plastic properties of the aluminium and tungsten alloys used in KE projectiles

NASA Astrophysics Data System (ADS)

Kruszka, L.; Magier, M.

2012-08-01

The main aim of studies on dynamic behaviour of construction materials at high strain rates is to determine the variation of mechanical properties (strength, plasticity) in function of the strain rate and temperature. On the basis of results of dynamic tests on the properties of constructional materials the constitutive models are formulated to create numerical codes applied to solve constructional problems with computer simulation methods. In the case of military applications connected with the phenomena of gunshot and terminal ballistics it's particularly important to develop a model of strength and armour penetration with KE projectile founded on reliable results of dynamic experiments and constituting the base for further analyses and optimization of projectile designs in order to achieve required penetration depth. Static and dynamic results of strength investigations of the EN AW-7012 aluminium alloy (sabot) and tungsten alloy (penetrator) are discussed in this paper. Static testing was carried out with the INSTRON testing machine. Dynamic tests have been conducted using the split Hopkinson pressure bars technique at strain rates up to 1,2 ṡ 104s-1 (for aluminium alloy) and 6 ṡ 103s-1 (for tungsten alloy).

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform.

PubMed

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-08-14

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS(®); then, to analyze the system's kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB(®) SIMULINK(®) controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance.

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform

PubMed Central

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-01-01

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS®; then, to analyze the system’s kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB® SIMULINK® controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance. PMID:26287210

Observing Consistency in Online Communication Patterns for User Re-Identification.

PubMed

Adeyemi, Ikuesan Richard; Razak, Shukor Abd; Salleh, Mazleena; Venter, Hein S

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Dynamic cellular manufacturing system considering machine failure and workload balance

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Impact of coastal forcing and groundwater recharge on the growth of a fresh groundwater lens in a mega-scale beach nourishment

NASA Astrophysics Data System (ADS)

Huizer, Sebastian; Radermacher, Max; de Vries, Sierd; Oude Essink, Gualbert H. P.; Bierkens, Marc F. P.

2018-02-01

For a large beach nourishment called the Sand Engine - constructed in 2011 at the Dutch coast - we have examined the impact of coastal forcing (i.e. natural processes that drive coastal hydro- and morphodynamics) and groundwater recharge on the growth of a fresh groundwater lens between 2011 and 2016. Measurements of the morphological change and the tidal dynamics at the study site were incorporated in a calibrated three-dimensional and variable-density groundwater model of the study area. Simulations with this model showed that the detailed incorporation of both the local hydro- and morphodynamics and the actual recharge rate can result in a reliable reconstruction of the growth in fresh groundwater resources. In contrast, the neglect of tidal dynamics, land-surface inundations, and morphological changes in model simulations can result in considerable overestimations of the volume of fresh groundwater. In particular, wave runup and coinciding coastal erosion during storm surges limit the growth in fresh groundwater resources in dynamic coastal environments, and should be considered at potential nourishment sites to delineate the area that is vulnerable to salinization.

Difficult Decisions Made Easier

NASA Technical Reports Server (NTRS)

2006-01-01

NASA missions are extremely complex and prone to sudden, catastrophic failure if equipment falters or if an unforeseen event occurs. For these reasons, NASA trains to expect the unexpected. It tests its equipment and systems in extreme conditions, and it develops risk-analysis tests to foresee any possible problems. The Space Agency recently worked with an industry partner to develop reliability analysis software capable of modeling complex, highly dynamic systems, taking into account variations in input parameters and the evolution of the system over the course of a mission. The goal of this research was multifold. It included performance and risk analyses of complex, multiphase missions, like the insertion of the Mars Reconnaissance Orbiter; reliability analyses of systems with redundant and/or repairable components; optimization analyses of system configurations with respect to cost and reliability; and sensitivity analyses to identify optimal areas for uncertainty reduction or performance enhancement.

Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins.

PubMed

Langó, Tamás; Róna, Gergely; Hunyadi-Gulyás, Éva; Turiák, Lilla; Varga, Julia; Dobson, László; Várady, György; Drahos, László; Vértessy, Beáta G; Medzihradszky, Katalin F; Szakács, Gergely; Tusnády, Gábor E

2017-02-13

Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins.

Regional Geoid Modeling Compared to Ocean Surface Observations

NASA Astrophysics Data System (ADS)

Roman, D. R.; Saleh, J.; Wang, Y. M.

2007-05-01

Aerogravity over a limited coastal region of the northern Gulf of Mexico enhanced and rectified the local gravity field signal. In turn, these data improved the derived geoid height model based on comparison with dynamic ocean topography (DOT) and tide gage information at eleven stations. Additionally, lidar observations were analyzed along nearly 50 profiles to estimate the reliability of these models into the offshore region. The overall comparison shows dm-level agreement between the various geoid and DOT models and ocean surface observations. An approximate 30 cm bias must still be explained; however, the results of this study point to the potential for further cooperative studies between oceanographers and geodesists.

Modelling the energy balance of an anaerobic digester fed with cattle manure and renewable energy crops.

PubMed

Lübken, Manfred; Wichern, Marc; Schlattmann, Markus; Gronauer, Andreas; Horn, Harald

2007-10-01

Knowledge of the net energy production of anaerobic fermenters is important for reliable modelling of the efficiency of anaerobic digestion processes. By using the Anaerobic Digestion Model No. 1 (ADM1) the simulation of biogas production and composition is possible. This paper shows the application and modification of ADM1 to simulate energy production of the digestion of cattle manure and renewable energy crops. The paper additionally presents an energy balance model, which enables the dynamic calculation of the net energy production. The model was applied to a pilot-scale biogas reactor. It was found in a simulation study that a continuous feeding and splitting of the reactor feed into smaller heaps do not generally have a positive effect on the net energy yield. The simulation study showed that the ratio of co-substrate to liquid manure in the inflow determines the net energy production when the inflow load is split into smaller heaps. Mathematical equations are presented to calculate the increase of biogas and methane yield for the digestion of liquid manure and lipids for different feeding intervals. Calculations of different kinds of energy losses for the pilot-scale digester showed high dynamic variations, demonstrating the significance of using a dynamic energy balance model.

Non-hydrostatic general circulation model of the Venus atmosphere

NASA Astrophysics Data System (ADS)

Rodin, Alexander V.; Mingalev, Igor; Orlov, Konstantin; Ignatiev, Nikolay

We present the first non-hydrostatic global circulation model of the Venus atmosphere based on the complete set of gas dynamics equations. The model employs a spatially uniform triangular mesh that allows to avoid artificial damping of the dynamical processes in the polar regions, with altitude as a vertical coordinate. Energy conversion from the solar flux into atmospheric motion is described via explicitly specified heating and cooling rates or, alternatively, with help of the radiation block based on comprehensive treatment of the Venus atmosphere spectroscopy, including line mixing effects in CO2 far wing absorption. Momentum equations are integrated using the semi-Lagrangian explicit scheme that provides high accuracy of mass and energy conservation. Due to high vertical grid resolution required by gas dynamics calculations, the model is integrated on the short time step less than one second. The model reliably repro-duces zonal superrotation, smoothly extending far below the cloud layer, tidal patterns at the cloud level and above, and non-rotating, sun-synchronous global convective cell in the upper atmosphere. One of the most interesting features of the model is the development of the polar vortices resembling those observed by Venus Express' VIRTIS instrument. Initial analysis of the simulation results confirms the hypothesis that it is thermal tides that provides main driver for the superrotation.

Simulations of magnetic nanoparticle Brownian motion

PubMed Central

Reeves, Daniel B.; Weaver, John B.

2012-01-01

Magnetic nanoparticles are useful in many medical applications because they interact with biology on a cellular level thus allowing microenvironmental investigation. An enhanced understanding of the dynamics of magnetic particles may lead to advances in imaging directly in magnetic particle imaging or through enhanced MRI contrast and is essential for nanoparticle sensing as in magnetic spectroscopy of Brownian motion. Moreover, therapeutic techniques like hyperthermia require information about particle dynamics for effective, safe, and reliable use in the clinic. To that end, we have developed and validated a stochastic dynamical model of rotating Brownian nanoparticles from a Langevin equation approach. With no field, the relaxation time toward equilibrium matches Einstein's model of Brownian motion. In a static field, the equilibrium magnetization agrees with the Langevin function. For high frequency or low amplitude driving fields, behavior characteristic of the linearized Debye approximation is reproduced. In a higher field regime where magnetic saturation occurs, the magnetization and its harmonics compare well with the effective field model. On another level, the model has been benchmarked against experimental results, successfully demonstrating that harmonics of the magnetization carry enough information to infer environmental parameters like viscosity and temperature. PMID:23319830

Mathematical Simulation of Perturbations of Attack Angle of Asymmetric Nanosatellite Passing through Resonance

NASA Astrophysics Data System (ADS)

Lyubimov, V. V.; Kurkina, E. V.

2018-05-01

The authors consider the problem of a dynamic system passing through a low-order resonance, describing an uncontrolled atmospheric descent of an asymmetric nanosatellite in the Earth's atmosphere. The authors perform mathematical and numerical modeling of the motion of the nanosatellite with a small mass-aerodynamic asymmetry relative to the center of mass. The aim of the study is to obtain new reliable approximate analytical estimates of perturbations of the angle of attack of a nanosatellite passing through resonance at angles of attack of not more than 0.5π. By using the stationary phase method, the authors were able to investigate a discontinuous perturbation in the angle of attack of a nanosatellite passing through a resonance with two different nanosatellite designs. Comparison of the results of the numerical modeling and new approximate analytical estimates of the perturbation of the angle of attack confirms the reliability of the said estimates.

Modeling, simulation, and high-autonomy control of a Martian oxygen production plant

NASA Technical Reports Server (NTRS)

Schooley, L. C.; Cellier, F. E.; Wang, F.-Y.; Zeigler, B. P.

1992-01-01

Progress on a project for the development of a high-autonomy intelligent command and control architecture for process plants used to produce oxygen from local planetary resources is reported. A distributed command and control architecture is being developed and implemented so that an oxygen production plant, or other equipment, can be reliably commanded and controlled over an extended time period in a high-autonomy mode with high-level task-oriented teleoperation from one or several remote locations. During the reporting period, progress was made at all levels of the architecture. At the remote site, several remote observers can now participate in monitoring the plant. At the local site, a command and control center was introduced for increased flexibility, reliability, and robustness. The local control architecture was enhanced to control multiple tubes in parallel, and was refined for increased robustness. The simulation model was enhanced to full dynamics descriptions.

Reconstruction of missing daily streamflow data using dynamic regression models

NASA Astrophysics Data System (ADS)

Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

2015-12-01

River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

A Motor Speech Assessment for Children with Severe Speech Disorders: Reliability and Validity Evidence

ERIC Educational Resources Information Center

Strand, Edythe A.; McCauley, Rebecca J.; Weigand, Stephen D.; Stoeckel, Ruth E.; Baas, Becky S.

2013-01-01

Purpose: In this article, the authors report reliability and validity evidence for the Dynamic Evaluation of Motor Speech Skill (DEMSS), a new test that uses dynamic assessment to aid in the differential diagnosis of childhood apraxia of speech (CAS). Method: Participants were 81 children between 36 and 79 months of age who were referred to the…

The Achievement of Therapeutic Objectives Scale: Interrater Reliability and Sensitivity to Change in Short-Term Dynamic Psychotherapy and Cognitive Therapy

ERIC Educational Resources Information Center

Valen, Jakob; Ryum, Truls; Svartberg, Martin; Stiles, Tore C.; McCullough, Leigh

2011-01-01

This study examined interrater reliability and sensitivity to change of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough, Larsen, et al., 2003) in short-term dynamic psychotherapy (STDP) and cognitive therapy (CT). The ATOS is a process scale originally developed to assess patients' achievements of treatment objectives in STDP,…

Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

NASA Astrophysics Data System (ADS)

Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

2014-12-01

The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multiscale model evaluation. It was found that the proposed wavelet-based performance measures, namely the MNSC (Multiscale Nash-Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash-Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration.

Reconciling Streamflow Uncertainty Estimation and River Bed Morphology Dynamics. Insights from a Probabilistic Assessment of Streamflow Uncertainties Using a Reliability Diagram

NASA Astrophysics Data System (ADS)

Morlot, T.; Mathevet, T.; Perret, C.; Favre Pugin, A. C.

2014-12-01

Streamflow uncertainty estimation has recently received a large attention in the literature. A dynamic rating curve assessment method has been introduced (Morlot et al., 2014). This dynamic method allows to compute a rating curve for each gauging and a continuous streamflow time-series, while calculating streamflow uncertainties. Streamflow uncertainty takes into account many sources of uncertainty (water level, rating curve interpolation and extrapolation, gauging aging, etc.) and produces an estimated distribution of streamflow for each days. In order to caracterise streamflow uncertainty, a probabilistic framework has been applied on a large sample of hydrometric stations of the Division Technique Générale (DTG) of Électricité de France (EDF) hydrometric network (>250 stations) in France. A reliability diagram (Wilks, 1995) has been constructed for some stations, based on the streamflow distribution estimated for a given day and compared to a real streamflow observation estimated via a gauging. To build a reliability diagram, we computed the probability of an observed streamflow (gauging), given the streamflow distribution. Then, the reliability diagram allows to check that the distribution of probabilities of non-exceedance of the gaugings follows a uniform law (i.e., quantiles should be equipropables). Given the shape of the reliability diagram, the probabilistic calibration is caracterised (underdispersion, overdispersion, bias) (Thyer et al., 2009). In this paper, we present case studies where reliability diagrams have different statistical properties for different periods. Compared to our knowledge of river bed morphology dynamic of these hydrometric stations, we show how reliability diagram gives us invaluable information on river bed movements, like a continuous digging or backfilling of the hydraulic control due to erosion or sedimentation processes. Hence, the careful analysis of reliability diagrams allows to reconcile statistics and long-term river bed morphology processes. This knowledge improves our real-time management of hydrometric stations, given a better caracterisation of erosion/sedimentation processes and the stability of hydrometric station hydraulic control.

Motion-based threat detection using microrods: experiments and numerical simulations.

PubMed

Ezhilan, Barath; Gao, Wei; Pei, Allen; Rozen, Isaac; Dong, Renfeng; Jurado-Sanchez, Beatriz; Wang, Joseph; Saintillan, David

2015-05-07

Motion-based chemical sensing using microscale particles has attracted considerable recent attention. In this paper, we report on new experiments and Brownian dynamics simulations that cast light on the dynamics of both passive and active microrods (gold wires and gold-platinum micromotors) in a silver ion gradient. We demonstrate that such microrods can be used for threat detection in the form of a silver ion source, allowing for the determination of both the location of the source and concentration of silver. This threat detection strategy relies on the diffusiophoretic motion of both passive and active microrods in the ionic gradient and on the speed acceleration of the Au-Pt micromotors in the presence of silver ions. A Langevin model describing the microrod dynamics and accounting for all of these effects is presented, and key model parameters are extracted from the experimental data, thereby providing a reliable estimate for the full spatiotemporal distribution of the silver ions in the vicinity of the source.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.

PubMed

Onojima, Takayuki; Goto, Takahiro; Mizuhara, Hiroaki; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.

Dynamics and regulation of locomotion of a human swing leg as a double-pendulum considering self-impact joint constraint.

PubMed

Bazargan-Lari, Y; Eghtesad, M; Khoogar, A; Mohammad-Zadeh, A

2014-09-01

Despite some successful dynamic simulation of self-impact double pendulum (SIDP)-as humanoid robots legs or arms- studies, there is limited information available about the control of one leg locomotion. The main goal of this research is to improve the reliability of the mammalians leg locomotion and building more elaborated models close to the natural movements, by modeling the swing leg as a SIDP. This paper also presents the control design for a SIDP by a nonlinear model-based control method. To achieve this goal, the available data of normal human gait will be taken as the desired trajectories of the hip and knee joints. The model is characterized by the constraint that occurs at the knee joint (the lower joint of the model) in both dynamic modeling and control design. Since the system dynamics is nonlinear, the MIMO Input-Output Feedback Linearization method will be employed for control purposes. The first constraint in forward impact simulation happens at 0.5 rad where the speed of the upper link is increased to 2.5 rad/sec. and the speed of the lower link is reduced to -5 rad/sec. The subsequent constraints occur rather moderately. In the case of both backward and forward constraints simulation, the backward impact occurs at -0.5 rad and the speeds of the upper and lower links increase to 2.2 and 1.5 rad/sec., respectively. The designed controller performed suitably well and regulated the system accurately.

Bibliography on Cold Regions Science and Technology. Cumulative Author Index. Volumes 28-32, Cumulative Subject Index. Volumes 28-32, Parts 1 and 2

DTIC Science & Technology

1978-12-01

Jr. 52-58, rusl 29.1345 Arctic ice model basin - design , construction, and operating experience Mathematical modelling of long-term non -stationary...crane KS-6362KhL designed for the North [1974, p.3-4, F11ppov, A.M. rusl 29-266 Experimental study of the dynamics of ice-jam formation in talwaters of... experimental data on glass fiber insulating materials and their France. filrej 32-4349de ~preenseltritie use for a reliable design of insulations at

Modelling the aggregation process of cellular slime mold by the chemical attraction.

PubMed

Atangana, Abdon; Vermeulen, P D

2014-01-01

We put into exercise a comparatively innovative analytical modus operandi, the homotopy decomposition method (HDM), for solving a system of nonlinear partial differential equations arising in an attractor one-dimensional Keller-Segel dynamics system. Numerical solutions are given and some properties show evidence of biologically practical reliance on the parameter values. The reliability of HDM and the reduction in computations give HDM a wider applicability.

Robotics-based synthesis of human motion.

PubMed

Khatib, O; Demircan, E; De Sapio, V; Sentis, L; Besier, T; Delp, S

2009-01-01

The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research. Task-based methods used in robotics may be leveraged to provide novel musculoskeletal modeling methods and physiologically accurate performance predictions. In this paper, we present (i) a new method for the real-time reconstruction of human motion trajectories using direct marker tracking, (ii) a task-driven muscular effort minimization criterion and (iii) new human performance metrics for dynamic characterization of athletic skills. Dynamic motion reconstruction is achieved through the control of a simulated human model to follow the captured marker trajectories in real-time. The operational space control and real-time simulation provide human dynamics at any configuration of the performance. A new criteria of muscular effort minimization has been introduced to analyze human static postures. Extensive motion capture experiments were conducted to validate the new minimization criterion. Finally, new human performance metrics were introduced to study in details an athletic skill. These metrics include the effort expenditure and the feasible set of operational space accelerations during the performance of the skill. The dynamic characterization takes into account skeletal kinematics as well as muscle routing kinematics and force generating capacities. The developments draw upon an advanced musculoskeletal modeling platform and a task-oriented framework for the effective integration of biomechanics and robotics methods.

An energy-efficient rate adaptive media access protocol (RA-MAC) for long-lived sensor networks.

PubMed

Hu, Wen; Chen, Quanjun; Corke, Peter; O'Rourke, Damien

2010-01-01

We introduce an energy-efficient Rate Adaptive Media Access Control (RA-MAC) algorithm for long-lived Wireless Sensor Networks (WSNs). Previous research shows that the dynamic and lossy nature of wireless communications is one of the major challenges to reliable data delivery in WSNs. RA-MAC achieves high link reliability in such situations by dynamically trading off data rate for channel gain. The extra gain that can be achieved reduces the packet loss rate which contributes to reduced energy expenditure through a reduced numbers of retransmissions. We achieve this at the expense of raw bit rate which generally far exceeds the application's link requirement. To minimize communication energy consumption, RA-MAC selects the optimal data rate based on the estimated link quality at each data rate and an analytical model of the energy consumption. Our model shows how the selected data rate depends on different channel conditions in order to minimize energy consumption. We have implemented RA-MAC in TinyOS for an off-the-shelf sensor platform (the TinyNode) on top of a state-of-the-art WSN Media Access Control Protocol, SCP-MAC, and evaluated its performance by comparing our implementation with the original SCP-MAC using both simulation and experiment.

Computation of heats of transport in crystalline solids: II

NASA Astrophysics Data System (ADS)

Grout, P. J.; Lidiard, A. B.

2008-10-01

This paper explores the application of classical molecular dynamics to the computation of the heat of transport of Au atoms in a model of solid gold at several elevated temperatures above the Debye temperature. It is assumed that the solid shows vacancy disorder. The work shows that to obtain consistent and reliable results it is necessary (a) to use very small time steps (≈1 fs) in the molecular dynamics integration routine and (b) to take averages over a very large number of vacancy displacements—a number which varies with temperature but which is of the order of 105. The results for the reduced heat of transport for the Au atoms show that: (1) it is positive in sign, i.e. that the diffusion of Au atoms in a temperature gradient is biassed towards the cold region or equivalently that the vacancies tend to migrate towards the hotter region; (2) it is predicted to fall as the average temperature increases and that the variation is closely linear in (1/T); (3) its value at high T relative to the energy of activation for vacancy movement is close to the corresponding ratio of experimental quantities. Analysis of these results indicates that the method and model may allow reliable predictions for other metals having the face centred cubic structure.

Using meta-quality to assess the utility of volunteered geographic information for science.

PubMed

Langley, Shaun A; Messina, Joseph P; Moore, Nathan

2017-11-06

Volunteered geographic information (VGI) has strong potential to be increasingly valuable to scientists in collaboration with non-scientists. The abundance of mobile phones and other wireless forms of communication open up significant opportunities for the public to get involved in scientific research. As these devices and activities become more abundant, questions of uncertainty and error in volunteer data are emerging as critical components for using volunteer-sourced spatial data. Here we present a methodology for using VGI and assessing its sensitivity to three types of error. More specifically, this study evaluates the reliability of data from volunteers based on their historical patterns. The specific context is a case study in surveillance of tsetse flies, a health concern for being the primary vector of African Trypanosomiasis. Reliability, as measured by a reputation score, determines the threshold for accepting the volunteered data for inclusion in a tsetse presence/absence model. Higher reputation scores are successful in identifying areas of higher modeled tsetse prevalence. A dynamic threshold is needed but the quality of VGI will improve as more data are collected and the errors in identifying reliable participants will decrease. This system allows for two-way communication between researchers and the public, and a way to evaluate the reliability of VGI. Boosting the public's ability to participate in such work can improve disease surveillance and promote citizen science. In the absence of active surveillance, VGI can provide valuable spatial information given that the data are reliable.

Time-dependent density functional theory for open systems with a positivity-preserving decomposition scheme for environment spectral functions

NASA Astrophysics Data System (ADS)

Wang, RuLin; Zheng, Xiao; Kwok, YanHo; Xie, Hang; Chen, GuanHua; Yam, ChiYung

2015-04-01

Understanding electronic dynamics on material surfaces is fundamentally important for applications including nanoelectronics, inhomogeneous catalysis, and photovoltaics. Practical approaches based on time-dependent density functional theory for open systems have been developed to characterize the dissipative dynamics of electrons in bulk materials. The accuracy and reliability of such approaches depend critically on how the electronic structure and memory effects of surrounding material environment are accounted for. In this work, we develop a novel squared-Lorentzian decomposition scheme, which preserves the positive semi-definiteness of the environment spectral matrix. The resulting electronic dynamics is guaranteed to be both accurate and convergent even in the long-time limit. The long-time stability of electronic dynamics simulation is thus greatly improved within the current decomposition scheme. The validity and usefulness of our new approach are exemplified via two prototypical model systems: quasi-one-dimensional atomic chains and two-dimensional bilayer graphene.

Probabilistic assessment of dynamic system performance. Part 3

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

Belhadj, Mohamed

1993-01-01

Accurate prediction of dynamic system failure behavior can be important for the reliability and risk analyses of nuclear power plants, as well as for their backfitting to satisfy given constraints on overall system reliability, or optimization of system performance. Global analysis of dynamic systems through investigating the variations in the structure of the attractors of the system and the domains of attraction of these attractors as a function of the system parameters is also important for nuclear technology in order to understand the fault-tolerance as well as the safety margins of the system under consideration and to insure a safemore » operation of nuclear reactors. Such a global analysis would be particularly relevant to future reactors with inherent or passive safety features that are expected to rely on natural phenomena rather than active components to achieve and maintain safe shutdown. Conventionally, failure and global analysis of dynamic systems necessitate the utilization of different methodologies which have computational limitations on the system size that can be handled. Using a Chapman-Kolmogorov interpretation of system dynamics, a theoretical basis is developed that unifies these methodologies as special cases and which can be used for a comprehensive safety and reliability analysis of dynamic systems.« less

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

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

Dumitrescu, Eugene; Humble, Travis S.

The accurate and reliable characterization of quantum dynamical processes underlies efforts to validate quantum technologies, where discrimination between competing models of observed behaviors inform efforts to fabricate and operate qubit devices. We present a protocol for quantum channel discrimination that leverages advances in direct characterization of quantum dynamics (DCQD) codes. We demonstrate that DCQD codes enable selective process tomography to improve discrimination between entangling and correlated quantum dynamics. Numerical simulations show selective process tomography requires only a few measurement configurations to achieve a low false alarm rate and that the DCQD encoding improves the resilience of the protocol to hiddenmore » sources of noise. Lastly, our results show that selective process tomography with DCQD codes is useful for efficiently distinguishing sources of correlated crosstalk from uncorrelated noise in current and future experimental platforms.« less

Coupling long and short term decisions in the design of urban water supply infrastructure for added reliability and flexibility

NASA Astrophysics Data System (ADS)

Marques, G.; Fraga, C. C. S.; Medellin-Azuara, J.

2016-12-01

The expansion and operation of urban water supply systems under growing demands, hydrologic uncertainty and water scarcity requires a strategic combination of supply sources for reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources involves integration of long and short term planning to determine what and when to expand, and how much to use of each supply source accounting for interest rates, economies of scale and hydrologic variability. This research presents an integrated methodology coupling dynamic programming optimization with quadratic programming to optimize the expansion (long term) and operations (short term) of multiple water supply alternatives. Lagrange Multipliers produced by the short-term model provide a signal about the marginal opportunity cost of expansion to the long-term model, in an iterative procedure. A simulation model hosts the water supply infrastructure and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions; (b) evaluation of water transfers between urban supply systems; and (c) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion.

Influence of spatial variation of phenomenological parameters on the modeling of boundary conditions for flows with dynamic wetting

NASA Astrophysics Data System (ADS)

Hizumi, Yuka; Omori, Takeshi; Yamaguchi, Yasutaka; Kajisima, Takeo

2014-11-01

For reliable prediction of multiphase flows in micro- and nano-scales, continuum models are expected to account for small scale physics near the contact line (CL) region. Some existing works (for example the series of papers by the group of Qian and Ren) have been successful in deriving continuum models and corresponding boundary conditions which reproduce well the molecular dynamics (MD) simulation results. Their studies, however, did not fully address the issue of adsorption layer especially in the CL region, and it is still not clear if general conclusion can be deduced from their results. In the present study we investigate in detail the local viscosity and the corresponding stress tensor formulation in the solid-liquid interface and in the CL region of immiscible two-phase Couette flows by means of MD simulation. The application limit of the generalized Navier boundary condition and the continuum model with uniform viscosity is addressed by systematic coarse-graining of sampling bins.

Opportunities and constraints of presently used thermal manikins for thermo-physiological simulation of the human body.

PubMed

Psikuta, Agnes; Kuklane, Kalev; Bogdan, Anna; Havenith, George; Annaheim, Simon; Rossi, René M

2016-03-01

Combining the strengths of an advanced mathematical model of human physiology and a thermal manikin is a new paradigm for simulating thermal behaviour of humans. However, the forerunners of such adaptive manikins showed some substantial limitations. This project aimed to determine the opportunities and constraints of the existing thermal manikins when dynamically controlled by a mathematical model of human thermal physiology. Four thermal manikins were selected and evaluated for their heat flux measurement uncertainty including lateral heat flows between manikin body parts and the response of each sector to the frequent change of the set-point temperature typical when using a physiological model for control. In general, all evaluated manikins are suitable for coupling with a physiological model with some recommendations for further improvement of manikin dynamic performance. The proposed methodology is useful to improve the performance of the adaptive manikins and help to provide a reliable and versatile tool for the broad research and development domain of clothing, automotive and building engineering.

Dynamic cardiac PET imaging: extraction of time-activity curves using ICA and a generalized Gaussian distribution model.

PubMed

Mabrouk, Rostom; Dubeau, François; Bentabet, Layachi

2013-01-01

Kinetic modeling of metabolic and physiologic cardiac processes in small animals requires an input function (IF) and a tissue time-activity curves (TACs). In this paper, we present a mathematical method based on independent component analysis (ICA) to extract the IF and the myocardium's TACs directly from dynamic positron emission tomography (PET) images. The method assumes a super-Gaussian distribution model for the blood activity, and a sub-Gaussian distribution model for the tissue activity. Our appreach was applied on 22 PET measurement sets of small animals, which were obtained from the three most frequently used cardiac radiotracers, namely: desoxy-fluoro-glucose ((18)F-FDG), [(13)N]-ammonia, and [(11)C]-acetate. Our study was extended to PET human measurements obtained with the Rubidium-82 ((82) Rb) radiotracer. The resolved mathematical IF values compare favorably to those derived from curves extracted from regions of interest (ROI), suggesting that the procedure presents a reliable alternative to serial blood sampling for small-animal cardiac PET studies.

Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

NASA Astrophysics Data System (ADS)

Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

2015-03-01

We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

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.

CARES/LIFE Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

2003-01-01

This manual describes the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction (CARES/LIFE) computer program. The program calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. CARES/LIFE is an extension of the CARES (Ceramic Analysis and Reliability Evaluation of Structures) computer program. The program uses results from MSC/NASTRAN, ABAQUS, and ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker law. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled by using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. The probabilistic time-dependent theories used in CARES/LIFE, along with the input and output for CARES/LIFE, are described. Example problems to demonstrate various features of the program are also included.

Image-Based Computational Fluid Dynamics in Blood Vessel Models: Toward Developing a Prognostic Tool to Assess Cardiovascular Function Changes in Prolonged Space Flights

NASA Technical Reports Server (NTRS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2004-01-01

One of NASA's objectives is to be able to perform a complete, pre-flight, evaluation of cardiovascular changes in astronauts scheduled for prolonged space missions. Computational fluid dynamics (CFD) has shown promise as a method for estimating cardiovascular function during reduced gravity conditions. For this purpose, MRI can provide geometrical information, to reconstruct vessel geometries, and measure all spatial velocity components, providing location specific boundary conditions. The objective of this study was to investigate the reliability of MRI-based model reconstruction and measured boundary conditions for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T Siemens MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction (slice thickness 3 and 5 mm; pixel size 1x1 and 0.5x0.5 square millimeters). Velocity acquisitions provided measured inlet boundary conditions and localized three-directional steady-flow velocity data (0.7-3.0 L/min). The vessel walls were isolated using NIH provided software (ImageJ) and lofted to form the geometric surface. Constructed and idealized geometries were imported into a commercial CFD code for meshing and simulation. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with less than 10% differences in the local velocity values. CFD results on models reconstructed from different MRI resolution settings showed insignificant differences (less than 5%). This study illustrated, quantitatively, that reliable CFD simulations can be performed with MRI reconstructed models and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system alteration during space travel is feasible.

A comparison of quantitative methods for clinical imaging with hyperpolarized (13)C-pyruvate.

PubMed

Daniels, Charlie J; McLean, Mary A; Schulte, Rolf F; Robb, Fraser J; Gill, Andrew B; McGlashan, Nicholas; Graves, Martin J; Schwaiger, Markus; Lomas, David J; Brindle, Kevin M; Gallagher, Ferdia A

2016-04-01

Dissolution dynamic nuclear polarization (DNP) enables the metabolism of hyperpolarized (13)C-labelled molecules, such as the conversion of [1-(13)C]pyruvate to [1-(13)C]lactate, to be dynamically and non-invasively imaged in tissue. Imaging of this exchange reaction in animal models has been shown to detect early treatment response and correlate with tumour grade. The first human DNP study has recently been completed, and, for widespread clinical translation, simple and reliable methods are necessary to accurately probe the reaction in patients. However, there is currently no consensus on the most appropriate method to quantify this exchange reaction. In this study, an in vitro system was used to compare several kinetic models, as well as simple model-free methods. Experiments were performed using a clinical hyperpolarizer, a human 3 T MR system, and spectroscopic imaging sequences. The quantitative methods were compared in vivo by using subcutaneous breast tumours in rats to examine the effect of pyruvate inflow. The two-way kinetic model was the most accurate method for characterizing the exchange reaction in vitro, and the incorporation of a Heaviside step inflow profile was best able to describe the in vivo data. The lactate time-to-peak and the lactate-to-pyruvate area under the curve ratio were simple model-free approaches that accurately represented the full reaction, with the time-to-peak method performing indistinguishably from the best kinetic model. Finally, extracting data from a single pixel was a robust and reliable surrogate of the whole region of interest. This work has identified appropriate quantitative methods for future work in the analysis of human hyperpolarized (13)C data. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

Image-based computational fluid dynamics in blood vessel models: toward developing a prognostic tool to assess cardiovascular function changes in prolonged space flights

NASA Astrophysics Data System (ADS)

Chatzimavroudis, George P.; Spirka, Thomas A.; Setser, Randolph M.; Myers, Jerry G.

2005-04-01

One of NASA"s objectives is to be able to perform a complete pre-flight evaluation of possible cardiovascular changes in astronauts scheduled for prolonged space missions. Blood flow is an important component of cardiovascular function. Lately, attention has focused on using computational fluid dynamics (CFD) to analyze flow with realistic vessel geometries. MRI can provide detailed geometrical information and is the only clinical technique to measure all three spatial velocity components. The objective of this study was to investigate the reliability of MRI-based model reconstruction for CFD simulations. An aortic arch model and a carotid bifurcation model were scanned in a 1.5T MRI scanner. Axial MRI acquisitions provided images for geometry reconstruction using different resolution settings. The vessel walls were identified and the geometry was reconstructed using existing software. The geometry was then imported into a commercial CFD package for meshing and numerical solution. MRI velocity acquisitions provided true inlet boundary conditions for steady flow, as well as three-directional velocity data at several locations. In addition, an idealized version of each geometry was created from the model drawings. Contour and vector plots of the velocity showed identical features between the MRI velocity data, the MRI-based CFD data, and the idealized-geometry CFD data, with mean differences <10%. CFD results from different MRI resolution settings did not show significant differences (<5%). This study showed quantitatively that reliable CFD simulations can be performed in models reconstructed from MRI acquisitions and gives evidence that a future, subject-specific, computational evaluation of the cardiovascular system is possible.

Investigation of sliding DNA clamp dynamics by single-molecule fluorescence, mass spectrometry and structure-based modeling

PubMed Central

Gadkari, Varun V; Harvey, Sophie R; Raper, Austin T; Chu, Wen-Ting; Wang, Jin; Wysocki, Vicki H; Suo, Zucai

2018-01-01

Abstract Proliferating cell nuclear antigen (PCNA) is a trimeric ring-shaped clamp protein that encircles DNA and interacts with many proteins involved in DNA replication and repair. Despite extensive structural work to characterize the monomeric, dimeric, and trimeric forms of PCNA alone and in complex with interacting proteins, no structure of PCNA in a ring-open conformation has been published. Here, we use a multidisciplinary approach, including single-molecule Förster resonance energy transfer (smFRET), native ion mobility-mass spectrometry (IM-MS), and structure-based computational modeling, to explore the conformational dynamics of a model PCNA from Sulfolobus solfataricus (Sso), an archaeon. We found that Sso PCNA samples ring-open and ring-closed conformations even in the absence of its clamp loader complex, replication factor C, and transition to the ring-open conformation is modulated by the ionic strength of the solution. The IM-MS results corroborate the smFRET findings suggesting that PCNA dynamics are maintained in the gas phase and further establishing IM-MS as a reliable strategy to investigate macromolecular motions. Our molecular dynamic simulations agree with the experimental data and reveal that ring-open PCNA often adopts an out-of-plane left-hand geometry. Collectively, these results implore future studies to define the roles of PCNA dynamics in DNA loading and other PCNA-mediated interactions. PMID:29529283

The experimental identification of magnetorheological dampers and evaluation of their controllers

NASA Astrophysics Data System (ADS)

Metered, H.; Bonello, P.; Oyadiji, S. O.

2010-05-01

Magnetorheological (MR) fluid dampers are semi-active control devices that have been applied over a wide range of practical vibration control applications. This paper concerns the experimental identification of the dynamic behaviour of an MR damper and the use of the identified parameters in the control of such a damper. Feed-forward and recurrent neural networks are used to model both the direct and inverse dynamics of the damper. Training and validation of the proposed neural networks are achieved by using the data generated through dynamic tests with the damper mounted on a tensile testing machine. The validation test results clearly show that the proposed neural networks can reliably represent both the direct and inverse dynamic behaviours of an MR damper. The effect of the cylinder's surface temperature on both the direct and inverse dynamics of the damper is studied, and the neural network model is shown to be reasonably robust against significant temperature variation. The inverse recurrent neural network model is introduced as a damper controller and experimentally evaluated against alternative controllers proposed in the literature. The results reveal that the neural-based damper controller offers superior damper control. This observation and the added advantages of low-power requirement, extended service life of the damper and the minimal use of sensors, indicate that a neural-based damper controller potentially offers the most cost-effective vibration control solution among the controllers investigated.

Numerical simulations of earthquakes and the dynamics of fault systems using the Finite Element method.

NASA Astrophysics Data System (ADS)

Kettle, L. M.; Mora, P.; Weatherley, D.; Gross, L.; Xing, H.

2006-12-01

Simulations using the Finite Element method are widely used in many engineering applications and for the solution of partial differential equations (PDEs). Computational models based on the solution of PDEs play a key role in earth systems simulations. We present numerical modelling of crustal fault systems where the dynamic elastic wave equation is solved using the Finite Element method. This is achieved using a high level computational modelling language, escript, available as open source software from ACcESS (Australian Computational Earth Systems Simulator), the University of Queensland. Escript is an advanced geophysical simulation software package developed at ACcESS which includes parallel equation solvers, data visualisation and data analysis software. The escript library was implemented to develop a flexible Finite Element model which reliably simulates the mechanism of faulting and the physics of earthquakes. Both 2D and 3D elastodynamic models are being developed to study the dynamics of crustal fault systems. Our final goal is to build a flexible model which can be applied to any fault system with user-defined geometry and input parameters. To study the physics of earthquake processes, two different time scales must be modelled, firstly the quasi-static loading phase which gradually increases stress in the system (~100years), and secondly the dynamic rupture process which rapidly redistributes stress in the system (~100secs). We will discuss the solution of the time-dependent elastic wave equation for an arbitrary fault system using escript. This involves prescribing the correct initial stress distribution in the system to simulate the quasi-static loading of faults to failure; determining a suitable frictional constitutive law which accurately reproduces the dynamics of the stick/slip instability at the faults; and using a robust time integration scheme. These dynamic models generate data and information that can be used for earthquake forecasting.

E-Governance and Service Oriented Computing Architecture Model

NASA Astrophysics Data System (ADS)

Tejasvee, Sanjay; Sarangdevot, S. S.

2010-11-01

E-Governance is the effective application of information communication and technology (ICT) in the government processes to accomplish safe and reliable information lifecycle management. Lifecycle of the information involves various processes as capturing, preserving, manipulating and delivering information. E-Governance is meant to transform of governance in better manner to the citizens which is transparent, reliable, participatory, and accountable in point of view. The purpose of this paper is to attempt e-governance model, focus on the Service Oriented Computing Architecture (SOCA) that includes combination of information and services provided by the government, innovation, find out the way of optimal service delivery to citizens and implementation in transparent and liable practice. This paper also try to enhance focus on the E-government Service Manager as a essential or key factors service oriented and computing model that provides a dynamically extensible structural design in which all area or branch can bring in innovative services. The heart of this paper examine is an intangible model that enables E-government communication for trade and business, citizen and government and autonomous bodies.

Dynamic Loads Generation for Multi-Point Vibration Excitation Problems

NASA Technical Reports Server (NTRS)

Shen, Lawrence

2011-01-01

A random-force method has been developed to predict dynamic loads produced by rocket-engine random vibrations for new rocket-engine designs. The method develops random forces at multiple excitation points based on random vibration environments scaled from accelerometer data obtained during hot-fire tests of existing rocket engines. This random-force method applies random forces to the model and creates expected dynamic response in a manner that simulates the way the operating engine applies self-generated random vibration forces (random pressure acting on an area) with the resulting responses that we measure with accelerometers. This innovation includes the methodology (implementation sequence), the computer code, two methods to generate the random-force vibration spectra, and two methods to reduce some of the inherent conservatism in the dynamic loads. This methodology would be implemented to generate the random-force spectra at excitation nodes without requiring the use of artificial boundary conditions in a finite element model. More accurate random dynamic loads than those predicted by current industry methods can then be generated using the random force spectra. The scaling method used to develop the initial power spectral density (PSD) environments for deriving the random forces for the rocket engine case is based on the Barrett Criteria developed at Marshall Space Flight Center in 1963. This invention approach can be applied in the aerospace, automotive, and other industries to obtain reliable dynamic loads and responses from a finite element model for any structure subject to multipoint random vibration excitations.

Rock Physical Interpretation of the Relationship between Dynamic and Static Young's Moduli of Sedimentary Rocks

NASA Astrophysics Data System (ADS)

Takahashi, T.

2017-12-01

The static Young's modulus (deformability) of a rock is indispensable for designing and constructing tunnels, dams and underground caverns in civil engineering. Static Young's modulus which is an elastic modulus at large strain level is usually obtained with the laboratory tests of rock cores sampled in boreholes drilled in a rock mass. A deformability model of the entire rock mass is then built by extrapolating the measurements based on a rock mass classification obtained in geological site characterization. However, model-building using data obtained from a limited number of boreholes in the rock mass, especially a complex rock mass, may cause problems in the accuracy and reliability of the model. On the other hand, dynamic Young's modulus which is the modulus at small strain level can be obtained from seismic velocity. If dynamic Young's modulus can be rationally converted to static one, a seismic velocity model by the seismic method can be effectively used to build a deformability model of the rock mass. In this study, we have, therefore, developed a rock physics model (Mavko et al., 2009) to estimate static Young's modulus from dynamic one for sedimentary rocks. The rock physics model has been generally applied to seismic properties at small strain level. In the proposed model, however, the sandy shale model, one of rock physics models, is extended for modeling the static Young's modulus at large strain level by incorporating the mixture of frictional and frictionless grain contacts into the Hertz-Mindlin model. The proposed model is verified through its application to the dynamic Young's moduli derived from well log velocities and static Young's moduli measured in the tri-axial compression tests of rock cores sampled in the same borehole as the logs were acquired. This application proves that the proposed rock physics model can be possibly used to estimate static Young's modulus (deformability) which is required in many types of civil engineering applications from seismically derived dynamic Young's modulus. References:Mavko, G., Mukerji, T. and Dvorkin, J., 2009, The Rock Physics Handbook, 2nd Edition, Cambridge University Press, Cambridge.

Modelling of Rainfall Induced Landslides in Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Sivandran, G.; Noto, L. V.; Bras, R. L.

2010-12-01

We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model, Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator with VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico and validated against in-situ measurements. A slope-failure module has been added to tRIBS-VEGGIE’s framework, after analyzing several failure criterions to identify the most suitable for our application; the module is used to predict the location and timing of landsliding events. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides.

Flow Mapping in a Gas-Solid Riser via Computer Automated Radioactive Particle Tracking (CARPT)

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

Muthanna Al-Dahhan; Milorad P. Dudukovic; Satish Bhusarapu

2005-06-04

Statement of the Problem: Developing and disseminating a general and experimentally validated model for turbulent multiphase fluid dynamics suitable for engineering design purposes in industrial scale applications of riser reactors and pneumatic conveying, require collecting reliable data on solids trajectories, velocities ? averaged and instantaneous, solids holdup distribution and solids fluxes in the riser as a function of operating conditions. Such data are currently not available on the same system. Multiphase Fluid Dynamics Research Consortium (MFDRC) was established to address these issues on a chosen example of circulating fluidized bed (CFB) reactor, which is widely used in petroleum and chemicalmore » industry including coal combustion. This project addresses the problem of lacking reliable data to advance CFB technology. Project Objectives: The objective of this project is to advance the understanding of the solids flow pattern and mixing in a well-developed flow region of a gas-solid riser, operated at different gas flow rates and solids loading using the state-of-the-art non-intrusive measurements. This work creates an insight and reliable database for local solids fluid-dynamic quantities in a pilot-plant scale CFB, which can then be used to validate/develop phenomenological models for the riser. This study also attempts to provide benchmark data for validation of Computational Fluid Dynamic (CFD) codes and their current closures. Technical Approach: Non-Invasive Computer Automated Radioactive Particle Tracking (CARPT) technique provides complete Eulerian solids flow field (time average velocity map and various turbulence parameters such as the Reynolds stresses, turbulent kinetic energy, and eddy diffusivities). It also gives directly the Lagrangian information of solids flow and yields the true solids residence time distribution (RTD). Another radiation based technique, Computed Tomography (CT) yields detailed time averaged local holdup profiles at various planes. Together, these two techniques can provide the needed local solids flow dynamic information for the same setup under identical operating conditions, and the data obtained can be used as a benchmark for development, and refinement of the appropriate riser models. For the above reasons these two techniques were implemented in this study on a fully developed section of the riser. To derive the global mixing information in the riser, accurate solids RTD is needed and was obtained by monitoring the entry and exit of a single radioactive tracer. Other global parameters such as Cycle Time Distribution (CTD), overall solids holdup in the riser, solids recycle percentage at the bottom section of the riser were evaluated from different solids travel time distributions. Besides, to measure accurately and in-situ the overall solids mass flux, a novel method was applied.« less

Modelling Southern Ocean ecosystems: krill, the food-web, and the impacts of harvesting.

PubMed

Hill, S L; Murphy, E J; Reid, K; Trathan, P N; Constable, A J

2006-11-01

The ecosystem approach to fisheries recognises the interdependence between harvested species and other ecosystem components. It aims to account for the propagation of the effects of harvesting through the food-web. The formulation and evaluation of ecosystem-based management strategies requires reliable models of ecosystem dynamics to predict these effects. The krill-based system in the Southern Ocean was the focus of some of the earliest models exploring such effects. It is also a suitable example for the development of models to support the ecosystem approach to fisheries because it has a relatively simple food-web structure and progress has been made in developing models of the key species and interactions, some of which has been motivated by the need to develop ecosystem-based management. Antarctic krill, Euphausia superba, is the main target species for the fishery and the main prey of many top predators. It is therefore critical to capture the processes affecting the dynamics and distribution of krill in ecosystem dynamics models. These processes include environmental influences on recruitment and the spatially variable influence of advection. Models must also capture the interactions between krill and its consumers, which are mediated by the spatial structure of the environment. Various models have explored predator-prey population dynamics with simplistic representations of these interactions, while others have focused on specific details of the interactions. There is now a pressing need to develop plausible and practical models of ecosystem dynamics that link processes occurring at these different scales. Many studies have highlighted uncertainties in our understanding of the system, which indicates future priorities in terms of both data collection and developing methods to evaluate the effects of these uncertainties on model predictions. We propose a modelling approach that focuses on harvested species and their monitored consumers and that evaluates model uncertainty by using alternative structures and functional forms in a Monte Carlo framework.

Validation of coupled atmosphere-fire behavior models

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

Bossert, J.E.; Reisner, J.M.; Linn, R.R.

1998-12-31

Recent advances in numerical modeling and computer power have made it feasible to simulate the dynamical interaction and feedback between the heat and turbulence induced by wildfires and the local atmospheric wind and temperature fields. At Los Alamos National Laboratory, the authors have developed a modeling system that includes this interaction by coupling a high resolution atmospheric dynamics model, HIGRAD, with a fire behavior model, BEHAVE, to predict the spread of wildfires. The HIGRAD/BEHAVE model is run at very high resolution to properly resolve the fire/atmosphere interaction. At present, these coupled wildfire model simulations are computationally intensive. The additional complexitymore » of these models require sophisticated methods for assuring their reliability in real world applications. With this in mind, a substantial part of the research effort is directed at model validation. Several instrumented prescribed fires have been conducted with multi-agency support and participation from chaparral, marsh, and scrub environments in coastal areas of Florida and inland California. In this paper, the authors first describe the data required to initialize the components of the wildfire modeling system. Then they present results from one of the Florida fires, and discuss a strategy for further testing and improvement of coupled weather/wildfire models.« less

Protein modeling and molecular dynamics simulation of the two novel surfactant proteins SP-G and SP-H.

PubMed

Rausch, Felix; Schicht, Martin; Bräuer, Lars; Paulsen, Friedrich; Brandt, Wolfgang

2014-11-01

Surfactant proteins are well known from the human lung where they are responsible for the stability and flexibility of the pulmonary surfactant system. They are able to influence the surface tension of the gas-liquid interface specifically by directly interacting with single lipids. This work describes the generation of reliable protein structure models to support the experimental characterization of two novel putative surfactant proteins called SP-G and SP-H. The obtained protein models were complemented by predicted posttranslational modifications and placed in a lipid model system mimicking the pulmonary surface. Molecular dynamics simulations of these protein-lipid systems showed the stability of the protein models and the formation of interactions between protein surface and lipid head groups on an atomic scale. Thereby, interaction interface and strength seem to be dependent on orientation and posttranslational modification of the protein. The here presented modeling was fundamental for experimental localization studies and the simulations showed that SP-G and SP-H are theoretically able to interact with lipid systems and thus are members of the surfactant protein family.

The interaction of cannibalism and omnivory: consequences for community dynamics.

PubMed

Rudolf, Volker H W

2007-11-01

Although cannibalism is ubiquitous in food webs and frequent in systems where a predator and its prey also share a common resource (intraguild predation, IGP), its impacts on species interactions and the dynamics and structure of communities are still poorly understood. In addition, the few existing studies on cannibalism have generally focused on cannibalism in the top-predator, ignoring that it is frequent at intermediate trophic levels. A set of structured models shows that cannibalism can completely alter the dynamics and structure of three-species IGP systems depending on the trophic position where cannibalism occurs. Contrary to the expectations of simple models, the IG predator can exploit the resources more efficiently when it is cannibalistic, enabling the predator to persist at lower resource densities than the IG prey. Cannibalism in the IG predator can also alter the effect of enrichment, preventing predator-mediated extinction of the IG prey at high productivities predicted by simple models. Cannibalism in the IG prey can reverse the effect of top-down cascades, leading to an increase in the resource with decreasing IG predator density. These predictions are consistent with current data. Overall, cannibalism promotes the coexistence of the IG predator and IG prey. These results indicate that including cannibalism in current models can overcome the discrepancy between theory and empirical data. Thus, we need to measure and account for cannibalistic interactions to reliably predict the structure and dynamics of communities.

DynaMiTES - A dynamic cell culture platform for in vitro drug testing PART 1 - Engineering of microfluidic system and technical simulations.

PubMed

Mattern, Kai; Beißner, Nicole; Reichl, Stephan; Dietzel, Andreas

2018-05-01

Conventional safety and efficacy test models, such as animal experiments or static in vitro cell culture models, can often not reliably predict the most promising drug candidates. Therefore, a novel microfluidic cell culture platform, called Dynamic Micro Tissue Engineering System (DynaMiTES), was designed to allow online analysis of drugs permeating through barrier forming tissues under dynamic conditions combined with monitoring of the transepithelial electrical resistance (TEER) by electrodes optimized for homogeneous current distribution. A variety of pre-cultivated cell culture inserts can be integrated and exposed to well controlled dynamic micro flow conditions, resulting in a tightly regulated exposure of the cells to tested drugs, drug formulations and shear forces. With these qualities, the new system can provide more relevant information compared to static measurements. As a first in vitro model, a three-dimensional hemicornea construct consisting of human keratocytes (HCK-Ca) and epithelial cells (HCE-T) was successfully tested in the DynaMiTES. Thereby, we were able to demonstrate the functionality and cell compatibility of this new organ on chip test platform. The modular design of the DynaMiTES allows fast adaptation suitable for the investigation of drug permeation through other important cellular barriers. Copyright © 2017. Published by Elsevier B.V.

Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

Identification of Potent Virtual Leads Specific to S1' Loop of ADAMTS4: Pharmacophore Modeling, 3D-QSAR, Molecular Docking and Dynamic Studies.

PubMed

Suganya, P Rathi; Kalva, Sukesh; Saleena, Lilly M

2016-01-01

ADAMTS4 (Aggrecanase-1) is an important enzyme, which belongs to ADAMTS family. Aggrecanase-1 is involved in aggrecan degradation of articular cartilage in osteoarthritis and rheumatoid arthritis. Overall variability of S1' domain of ADAMTS4 has been the main selectivity determinant to design the unique inhibitors. 34 inhibitors from Binding database and literature were used to develop the pharmacophore model. The five featured pharmacophore model AHHRR had the best survival score of 3.493 and post-hoc score of 2.545, indicating that the model is highly reliable. The 3D-QSAR acquired had excellent r(2) value of 0.99 and GH score of 0.839. The validated pharmacophore model was used for insilico screening of Asinex and ZINC database for finding the potential lead compounds. ZINC00987406 and ASN04459656 which pose high glide score i.e >7 Kcal/mol and H-bond and hydrophobic interactions in the S1'loop residues of ADAMTS4 were subjected to Molecular Dynamics Simulation studies. Molecular dynamic simulation result indicates that the RMSD and RMSF of backbone atoms for the above complexes were within the limit of 2.0 A˚. These compounds can be potential candidates for osteoarthritis by inhibiting ADAMTS4.

Model Improvement by Assimilating Observations of Storm-Induced Coastal Change

NASA Astrophysics Data System (ADS)

Long, J. W.; Plant, N. G.; Sopkin, K.

2010-12-01

Discrete, large scale, meteorological events such as hurricanes can cause wide-spread destruction of coastal islands, habitats, and infrastructure. The effects can vary significantly along the coast depending on the configuration of the coastline, variable dune elevations, changes in geomorphology (sandy beach vs. marshland), and alongshore variations in storm hydrodynamic forcing. There are two primary methods of determining the changing state of a coastal system. Process-based numerical models provide highly resolved (in space and time) representations of the dominant dynamics in a physical system but must employ certain parameterizations due to computational limitations. The predictive capability may also suffer from the lack of reliable initial or boundary conditions. On the other hand, observations of coastal topography before and after the storm allow the direct quantification of cumulative storm impacts. Unfortunately these measurements suffer from instrument noise and a lack of necessary temporal resolution. This research focuses on the combination of these two pieces of information to make more reliable forecasts of storm-induced coastal change. Of primary importance is the development of a data assimilation strategy that is efficient, applicable for use with highly nonlinear models, and able to quantify the remaining forecast uncertainty based on the reliability of each individual piece of information used in the assimilation process. We concentrate on an event time-scale and estimate/update unobserved model information (boundary conditions, free parameters, etc.) by assimilating direct observations of coastal change with those simulated by the model. The data assimilation can help estimate spatially varying quantities (e.g. friction coefficients) that are often modeled as homogeneous and identify processes inadequately characterized in the model.

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

2002-01-01

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Achieving Reliable Communication in Dynamic Emergency Responses

PubMed Central

Chipara, Octav; Plymoth, Anders N.; Liu, Fang; Huang, Ricky; Evans, Brian; Johansson, Per; Rao, Ramesh; Griswold, William G.

2011-01-01

Emergency responses require the coordination of first responders to assess the condition of victims, stabilize their condition, and transport them to hospitals based on the severity of their injuries. WIISARD is a system designed to facilitate the collection of medical information and its reliable dissemination during emergency responses. A key challenge in WIISARD is to deliver data with high reliability as first responders move and operate in a dynamic radio environment fraught with frequent network disconnections. The initial WIISARD system employed a client-server architecture and an ad-hoc routing protocol was used to exchange data. The system had low reliability when deployed during emergency drills. In this paper, we identify the underlying causes of unreliability and propose a novel peer-to-peer architecture that in combination with a gossip-based communication protocol achieves high reliability. Empirical studies show that compared to the initial WIISARD system, the redesigned system improves reliability by as much as 37% while reducing the number of transmitted packets by 23%. PMID:22195075

Computational models of aortic coarctation in hypoplastic left heart syndrome: considerations on validation of a detailed 3D model.

PubMed

Biglino, Giovanni; Corsini, Chiara; Schievano, Silvia; Dubini, Gabriele; Giardini, Alessandro; Hsia, Tain-Yen; Pennati, Giancarlo; Taylor, Andrew M

2014-05-01

Reliability of computational models for cardiovascular investigations strongly depends on their validation against physical data. This study aims to experimentally validate a computational model of complex congenital heart disease (i.e., surgically palliated hypoplastic left heart syndrome with aortic coarctation) thus demonstrating that hemodynamic information can be reliably extrapolated from the model for clinically meaningful investigations. A patient-specific aortic arch model was tested in a mock circulatory system and the same flow conditions were re-created in silico, by setting an appropriate lumped parameter network (LPN) attached to the same three-dimensional (3D) aortic model (i.e., multi-scale approach). The model included a modified Blalock-Taussig shunt and coarctation of the aorta. Different flow regimes were tested as well as the impact of uncertainty in viscosity. Computational flow and pressure results were in good agreement with the experimental signals, both qualitatively, in terms of the shape of the waveforms, and quantitatively (mean aortic pressure 62.3 vs. 65.1 mmHg, 4.8% difference; mean aortic flow 28.0 vs. 28.4% inlet flow, 1.4% difference; coarctation pressure drop 30.0 vs. 33.5 mmHg, 10.4% difference), proving the reliability of the numerical approach. It was observed that substantial changes in fluid viscosity or using a turbulent model in the numerical simulations did not significantly affect flows and pressures of the investigated physiology. Results highlighted how the non-linear fluid dynamic phenomena occurring in vitro must be properly described to ensure satisfactory agreement. This study presents methodological considerations for using experimental data to preliminarily set up a computational model, and then simulate a complex congenital physiology using a multi-scale approach.

Specialized data analysis for the Space Shuttle Main Engine and diagnostic evaluation of advanced propulsion system components

NASA Technical Reports Server (NTRS)

1993-01-01

The Marshall Space Flight Center is responsible for the development and management of advanced launch vehicle propulsion systems, including the Space Shuttle Main Engine (SSME), which is presently operational, and the Space Transportation Main Engine (STME) under development. The SSME's provide high performance within stringent constraints on size, weight, and reliability. Based on operational experience, continuous design improvement is in progress to enhance system durability and reliability. Specialized data analysis and interpretation is required in support of SSME and advanced propulsion system diagnostic evaluations. Comprehensive evaluation of the dynamic measurements obtained from test and flight operations is necessary to provide timely assessment of the vibrational characteristics indicating the operational status of turbomachinery and other critical engine components. Efficient performance of this effort is critical due to the significant impact of dynamic evaluation results on ground test and launch schedules, and requires direct familiarity with SSME and derivative systems, test data acquisition, and diagnostic software. Detailed analysis and evaluation of dynamic measurements obtained during SSME and advanced system ground test and flight operations was performed including analytical/statistical assessment of component dynamic behavior, and the development and implementation of analytical/statistical models to efficiently define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational condition. In addition, the SSME and J-2 data will be applied to develop vibroacoustic environments for advanced propulsion system components, as required. This study will provide timely assessment of engine component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. This contract will be performed through accomplishment of negotiated task orders.

Application of Dynamic Analysis in Semi-Analytical Finite Element Method.

PubMed

Liu, Pengfei; Xing, Qinyan; Wang, Dawei; Oeser, Markus

2017-08-30

Analyses of dynamic responses are significantly important for the design, maintenance and rehabilitation of asphalt pavement. In order to evaluate the dynamic responses of asphalt pavement under moving loads, a specific computational program, SAFEM, was developed based on a semi-analytical finite element method. This method is three-dimensional and only requires a two-dimensional FE discretization by incorporating Fourier series in the third dimension. In this paper, the algorithm to apply the dynamic analysis to SAFEM was introduced in detail. Asphalt pavement models under moving loads were built in the SAFEM and commercial finite element software ABAQUS to verify the accuracy and efficiency of the SAFEM. The verification shows that the computational accuracy of SAFEM is high enough and its computational time is much shorter than ABAQUS. Moreover, experimental verification was carried out and the prediction derived from SAFEM is consistent with the measurement. Therefore, the SAFEM is feasible to reliably predict the dynamic response of asphalt pavement under moving loads, thus proving beneficial to road administration in assessing the pavement's state.

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

Raymond, David W.; Blankenship, Douglas A.; Buerger, Stephen

The dynamic stability of deep drillstrings is challenged by an inability to impart controllability with ever-changing conditions introduced by geology, depth, structural dynamic properties and operating conditions. A multi-organizational LDRD project team at Sandia National Laboratories successfully demonstrated advanced technologies for mitigating drillstring vibrations to improve the reliability of drilling systems used for construction of deep, high-value wells. Using computational modeling and dynamic substructuring techniques, the benefit of controllable actuators at discrete locations in the drillstring is determined. Prototype downhole tools were developed and evaluated in laboratory test fixtures simulating the structural dynamic response of a deep drillstring. A laboratory-basedmore » drilling applicability demonstration was conducted to demonstrate the benefit available from deployment of an autonomous, downhole tool with self-actuation capabilities in response to the dynamic response of the host drillstring. A concept is presented for a prototype drilling tool based upon the technical advances. The technology described herein is the subject of U.S. Patent Application No. 62219481, entitled "DRILLING SYSTEM VIBRATION SUPPRESSION SYSTEMS AND METHODS", filed September 16, 2015.« less

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

PubMed

Knapp, B; Frantal, S; Cibena, M; Schreiner, W; Bauer, P

2011-08-01

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

Hybrid time-variant reliability estimation for active control structures under aleatory and epistemic uncertainties

NASA Astrophysics Data System (ADS)

Wang, Lei; Xiong, Chuang; Wang, Xiaojun; Li, Yunlong; Xu, Menghui

2018-04-01

Considering that multi-source uncertainties from inherent nature as well as the external environment are unavoidable and severely affect the controller performance, the dynamic safety assessment with high confidence is of great significance for scientists and engineers. In view of this, the uncertainty quantification analysis and time-variant reliability estimation corresponding to the closed-loop control problems are conducted in this study under a mixture of random, interval, and convex uncertainties. By combining the state-space transformation and the natural set expansion, the boundary laws of controlled response histories are first confirmed with specific implementation of random items. For nonlinear cases, the collocation set methodology and fourth Rounge-Kutta algorithm are introduced as well. Enlightened by the first-passage model in random process theory as well as by the static probabilistic reliability ideas, a new definition of the hybrid time-variant reliability measurement is provided for the vibration control systems and the related solution details are further expounded. Two engineering examples are eventually presented to demonstrate the validity and applicability of the methodology developed.

Reliability evaluation of oil pipelines operating in aggressive environment

NASA Astrophysics Data System (ADS)

Magomedov, R. M.; Paizulaev, M. M.; Gebel, E. S.

2017-08-01

In connection with modern increased requirements for ecology and safety, the development of diagnostic services complex is obligatory and necessary enabling to ensure the reliable operation of the gas transportation infrastructure. Estimation of oil pipelines technical condition should be carried out not only to establish the current values of the equipment technological parameters in operation, but also to predict the dynamics of changes in the physical and mechanical characteristics of the material, the appearance of defects, etc. to ensure reliable and safe operation. In the paper, existing Russian and foreign methods for evaluation of the oil pipelines reliability are considered, taking into account one of the main factors leading to the appearance of crevice in the pipeline material, i.e. change the shape of its cross-section, - corrosion. Without compromising the generality of the reasoning, the assumption of uniform corrosion wear for the initial rectangular cross section has been made. As a result a formula for calculation the probability of failure-free operation was formulated. The proposed mathematical model makes it possible to predict emergency situations, as well as to determine optimal operating conditions for oil pipelines.

Computational modeling of the effective Young's modulus values of fullerene molecules: a combined molecular dynamics simulation and continuum shell model.

PubMed

Ghavanloo, Esmaeal; Izadi, Razie; Nayebi, Ali

2018-02-28

Estimating the Young's modulus of a structure in the nanometer size range is a difficult task. The reliable determination of this parameter is, however, important in both basic and applied research. In this study, by combining molecular dynamics (MD) simulations and continuum shell theory, we designed a new approach to determining the Young's modulus values of different spherical fullerenes. The results indicate that the Young's modulus values of fullerene molecules decrease nonlinearly with increasing molecule size and understandably tend to the Young's modulus of an ideal flat graphene sheet at large molecular radii. To the best of our knowledge, this is first time that a combined atomistic-continuum method which can predict the Young's modulus values of fullerene molecules with high precision has been reported.

Use of Synchronized Phasor Measurements for Model Validation in ERCOT

NASA Astrophysics Data System (ADS)

Nuthalapati, Sarma; Chen, Jian; Shrestha, Prakash; Huang, Shun-Hsien; Adams, John; Obadina, Diran; Mortensen, Tim; Blevins, Bill

2013-05-01

This paper discusses experiences in the use of synchronized phasor measurement technology in Electric Reliability Council of Texas (ERCOT) interconnection, USA. Implementation of synchronized phasor measurement technology in the region is a collaborative effort involving ERCOT, ONCOR, AEP, SHARYLAND, EPG, CCET, and UT-Arlington. As several phasor measurement units (PMU) have been installed in ERCOT grid in recent years, phasor data with the resolution of 30 samples per second is being used to monitor power system status and record system events. Post-event analyses using recorded phasor data have successfully verified ERCOT dynamic stability simulation studies. Real time monitoring software "RTDMS"® enables ERCOT to analyze small signal stability conditions by monitoring the phase angles and oscillations. The recorded phasor data enables ERCOT to validate the existing dynamic models of conventional and/or wind generator.

A road map for integrating eco-evolutionary processes into biodiversity models.

PubMed

Thuiller, Wilfried; Münkemüller, Tamara; Lavergne, Sébastien; Mouillot, David; Mouquet, Nicolas; Schiffers, Katja; Gravel, Dominique

2013-05-01

The demand for projections of the future distribution of biodiversity has triggered an upsurge in modelling at the crossroads between ecology and evolution. Despite the enthusiasm around these so-called biodiversity models, most approaches are still criticised for not integrating key processes known to shape species ranges and community structure. Developing an integrative modelling framework for biodiversity distribution promises to improve the reliability of predictions and to give a better understanding of the eco-evolutionary dynamics of species and communities under changing environments. In this article, we briefly review some eco-evolutionary processes and interplays among them, which are essential to provide reliable projections of species distributions and community structure. We identify gaps in theory, quantitative knowledge and data availability hampering the development of an integrated modelling framework. We argue that model development relying on a strong theoretical foundation is essential to inspire new models, manage complexity and maintain tractability. We support our argument with an example of a novel integrated model for species distribution modelling, derived from metapopulation theory, which accounts for abiotic constraints, dispersal, biotic interactions and evolution under changing environmental conditions. We hope such a perspective will motivate exciting and novel research, and challenge others to improve on our proposed approach. © 2013 John Wiley & Sons Ltd/CNRS.

Changes in J-SOAP-II and SAVRY Scores Over the Course of Residential, Cognitive-Behavioral Treatment for Adolescent Sexual Offending

PubMed Central

Viljoen, Jodi L.; Gray, Andrew L.; Shaffer, Catherine; Latzman, Natasha E.; Scalora, Mario J.; Ullman, Daniel

2018-01-01

Although the Juvenile Sex Offender Assessment Protocol–II (J-SOAP-II) and the Structured Assessment of Violence Risk in Youth (SAVRY) include an emphasis on dynamic, or modifiable factors, there has been little research on dynamic changes on these tools. To help address this gap, we compared admission and discharge scores of 163 adolescents who attended a residential, cognitive-behavioral treatment program for sexual offending. Based on reliable change indices, one half of youth showed a reliable decrease on the J-SOAP-II Dynamic Risk Total Score and one third of youth showed a reliable decrease on the SAVRY Dynamic Risk Total Score. Contrary to expectations, decreases in risk factors and increases in protective factors did not predict reduced sexual, violent nonsexual, or any reoffending. In addition, no associations were found between scores on the Psychopathy Checklist:Youth Version and levels of change. Overall, the J-SOAP-II and the SAVRY hold promise in measuring change, but further research is needed. PMID:26199271

Changes in J-SOAP-II and SAVRY Scores Over the Course of Residential, Cognitive-Behavioral Treatment for Adolescent Sexual Offending.

PubMed

Viljoen, Jodi L; Gray, Andrew L; Shaffer, Catherine; Latzman, Natasha E; Scalora, Mario J; Ullman, Daniel

2017-06-01

Although the Juvenile Sex Offender Assessment Protocol-II (J-SOAP-II) and the Structured Assessment of Violence Risk in Youth (SAVRY) include an emphasis on dynamic, or modifiable factors, there has been little research on dynamic changes on these tools. To help address this gap, we compared admission and discharge scores of 163 adolescents who attended a residential, cognitive-behavioral treatment program for sexual offending. Based on reliable change indices, one half of youth showed a reliable decrease on the J-SOAP-II Dynamic Risk Total Score and one third of youth showed a reliable decrease on the SAVRY Dynamic Risk Total Score. Contrary to expectations, decreases in risk factors and increases in protective factors did not predict reduced sexual, violent nonsexual, or any reoffending. In addition, no associations were found between scores on the Psychopathy Checklist:Youth Version and levels of change. Overall, the J-SOAP-II and the SAVRY hold promise in measuring change, but further research is needed.

Toward more realistic projections of soil carbon dynamics by Earth system models

DOE PAGES

Luo, Yiqi; Ahlstrom, Anders; Allison, Steven D.; ...

2016-01-21

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe themore » environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. Furthermore, we recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.« less

Non-linear dynamic analysis of geared systems. Final Report Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Singh, Rajendra; Houser, Donald R.; Kahraman, Ahmet

1990-01-01

Under driving conditions, a typical geared system may be subjected to large dynamic loads. Also, the vibration level of the geared system is directly related to the noise radiated from the gear box. The steady state dynamic behavior of the system is examined in order to design reliable and quiet transmissions. The scope is limited to a system containing a spur gear pair with backlash and periodically time varying mesh stiffness, and rolling element bearings with clearance type nonlinearities. The internal static transmission error at the gear mesh, which is of importance from high frequency noise and vibration control view point, is considered in the formulation in sinusoidal or periodic form. A dynamic finite element model of the linear time invariant (LTI) system is developed. Effects of several system parameters, such as torsional and transverse flexibilities of the shafts and prime mover/load inertias, on free and forced vibration characteristics are investigated. Several reduced order LTI models are developed and validated by comparing their eigen solutions with the finite element model results. Using the reduced order formulations, a three degree of freedom dynamic model is developed which includes nonlinearities associated with radical clearances in the radial rolling element bearings, backlash between a spur gear pair and periodically varying gear mesh stiffness. As a limiting case, a single degree of freedom model of the spur gear pair with backlash is considered and mathematical conditions for tooth separation and back collision are defined. Both digital simulation technique and analytical models such as method of harmonic balance and the method of multiple scales were used to develop the steady state frequency response characteristics for various nonlinear and/or time varying cases.

Is it growing exponentially fast? -- Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics.

PubMed

Chowell, Gerardo; Viboud, Cécile

2016-10-01

The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing models that capture the baseline transmission characteristics in order to generate reliable epidemic forecasts. Improved models for epidemic forecasting could be achieved by identifying signature features of epidemic growth, which could inform the design of models of disease spread and reveal important characteristics of the transmission process. In particular, it is often taken for granted that the early growth phase of different growth processes in nature follow early exponential growth dynamics. In the context of infectious disease spread, this assumption is often convenient to describe a transmission process with mass action kinetics using differential equations and generate analytic expressions and estimates of the reproduction number. In this article, we carry out a simulation study to illustrate the impact of incorrectly assuming an exponential-growth model to characterize the early phase (e.g., 3-5 disease generation intervals) of an infectious disease outbreak that follows near-exponential growth dynamics. Specifically, we assess the impact on: 1) goodness of fit, 2) bias on the growth parameter, and 3) the impact on short-term epidemic forecasts. Designing transmission models and statistical approaches that more flexibly capture the profile of epidemic growth could lead to enhanced model fit, improved estimates of key transmission parameters, and more realistic epidemic forecasts.

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

Luo, Yiqi; Ahlström, Anders; Allison, Steven D.

Soil carbon (C) is a critical component of Earth system models (ESMs) and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the 3rd to 5th assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe themore » environmental conditions that soils experience. Firstly, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by 1st-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic SOC dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Secondly, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based datasets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Thirdly, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable datasets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.« less

Impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing pulmonary dynamic contrast-enhanced MR imaging.

PubMed

Tokuda, Junichi; Mamata, Hatsuho; Gill, Ritu R; Hata, Nobuhiko; Kikinis, Ron; Padera, Robert F; Lenkinski, Robert E; Sugarbaker, David J; Hatabu, Hiroto

2011-04-01

To investigates the impact of nonrigid motion correction on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in patients with solitary pulmonary nodules (SPNs). Misalignment of focal lesions due to respiratory motion in free-breathing dynamic contrast-enhanced MRI (DCE-MRI) precludes obtaining reliable time-intensity curves, which are crucial for pharmacokinetic analysis for tissue characterization. Single-slice 2D DCE-MRI was obtained in 15 patients. Misalignments of SPNs were corrected using nonrigid B-spline image registration. Pixel-wise pharmacokinetic parameters K(trans) , v(e) , and k(ep) were estimated from both original and motion-corrected DCE-MRI by fitting the two-compartment pharmacokinetic model to the time-intensity curve obtained in each pixel. The "goodness-of-fit" was tested with χ(2) -test in pixel-by-pixel basis to evaluate the reliability of the parameters. The percentages of reliable pixels within the SPNs were compared between the original and motion-corrected DCE-MRI. In addition, the parameters obtained from benign and malignant SPNs were compared. The percentage of reliable pixels in the motion-corrected DCE-MRI was significantly larger than the original DCE-MRI (P = 4 × 10(-7) ). Both K(trans) and k(ep) derived from the motion-corrected DCE-MRI showed significant differences between benign and malignant SPNs (P = 0.024, 0.015). The study demonstrated the impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing DCE-MRI in SPNs. Copyright © 2011 Wiley-Liss, Inc.

Increased Drought Impacts on Temperate Rainforests from Southern South America: Results of a Process-Based, Dynamic Forest Model

PubMed Central

Gutiérrez, Alvaro G.; Armesto, Juan J.; Díaz, M. Francisca; Huth, Andreas

2014-01-01

Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S). The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area). We compared the responses of a young stand (YS, ca. 60 years-old) and an old-growth forest (OG, >500 years-old) in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests. PMID:25068869

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Increased drought impacts on temperate rainforests from southern South America: results of a process-based, dynamic forest model.

PubMed

Gutiérrez, Alvaro G; Armesto, Juan J; Díaz, M Francisca; Huth, Andreas

2014-01-01

Increased droughts due to regional shifts in temperature and rainfall regimes are likely to affect forests in temperate regions in the coming decades. To assess their consequences for forest dynamics, we need predictive tools that couple hydrologic processes, soil moisture dynamics and plant productivity. Here, we developed and tested a dynamic forest model that predicts the hydrologic balance of North Patagonian rainforests on Chiloé Island, in temperate South America (42°S). The model incorporates the dynamic linkages between changing rainfall regimes, soil moisture and individual tree growth. Declining rainfall, as predicted for the study area, should mean up to 50% less summer rain by year 2100. We analysed forest responses to increased drought using the model proposed focusing on changes in evapotranspiration, soil moisture and forest structure (above-ground biomass and basal area). We compared the responses of a young stand (YS, ca. 60 years-old) and an old-growth forest (OG, >500 years-old) in the same area. Based on detailed field measurements of water fluxes, the model provides a reliable account of the hydrologic balance of these evergreen, broad-leaved rainforests. We found higher evapotranspiration in OG than YS under current climate. Increasing drought predicted for this century can reduce evapotranspiration by 15% in the OG compared to current values. Drier climate will alter forest structure, leading to decreases in above ground biomass by 27% of the current value in OG. The model presented here can be used to assess the potential impacts of climate change on forest hydrology and other threats of global change on future forests such as fragmentation, introduction of exotic tree species, and changes in fire regimes. Our study expands the applicability of forest dynamics models in remote and hitherto overlooked regions of the world, such as southern temperate rainforests.

Use of dynamic weight bearing as a novel end-point for the assessment of abdominal pain in the LPS-induced peritonitis model in the rat.

PubMed

Gruen, Michael; Laux-Biehlmann, Alexis; Zollner, Thomas M; Nagel, Jens

2014-07-30

Chronic pelvic pain (CPP) is defined as long-lasting and severe pelvic pain persisting over six months in cyclic or non-cyclic chronic manner. Various pathologic conditions like endometriosis, abdominal infections, intra-peritoneal adhesions or infection, underlie CPP which is often the leading symptom of the associated diseases. Pharmacological approaches addressing CPP are hampered by the absence of a straight-forward, objective, and reliable method for the assessment of CPP in rodents. In the presented study, the dynamic weight bearing system (DWB) was employed for the first time for the evaluation of pelvic pain in a rat model of LPS-induced peritonitis. Rats were pretreated with the COX-2 inhibitor rofecoxib and PGE2 levels were evaluated in peritoneal lavage. DWB analysis revealed that rats treated with LPS showed a relief posture by a significantly increased weight distribution to the front when compared to vehicle-treated animals. This effect was prevented by rofecoxib treatment indicating the sensitivity of the model for pelvic pain related to peritonitis. Analysis of the PGE2 levels in the peritoneal fluid indicated a correlation with the relief posture intensity. In contrast to others weight bearing approaches, the use of DWB allows evaluation of spontaneous posture changes as a consequence of pelvic pain. Taken together, we were able to show, that DWB combined with LPS-induced peritonitis may deliver a new reliable animal model addressing pelvic pain with high construct validity (peritoneal inflammation), and face validity (pain related relief posture). Copyright © 2014 Elsevier B.V. All rights reserved.

Multi-step cure kinetic model of ultra-thin glass fiber epoxy prepreg exhibiting both autocatalytic and diffusion-controlled regimes under isothermal and dynamic-heating conditions

NASA Astrophysics Data System (ADS)

Kim, Ye Chan; Min, Hyunsung; Hong, Sungyong; Wang, Mei; Sun, Hanna; Park, In-Kyung; Choi, Hyouk Ryeol; Koo, Ja Choon; Moon, Hyungpil; Kim, Kwang J.; Suhr, Jonghwan; Nam, Jae-Do

2017-08-01

As packaging technologies are demanded that reduce the assembly area of substrate, thin composite laminate substrates require the utmost high performance in such material properties as the coefficient of thermal expansion (CTE), and stiffness. Accordingly, thermosetting resin systems, which consist of multiple fillers, monomers and/or catalysts in thermoset-based glass fiber prepregs, are extremely complicated and closely associated with rheological properties, which depend on the temperature cycles for cure. For the process control of these complex systems, it is usually required to obtain a reliable kinetic model that could be used for the complex thermal cycles, which usually includes both the isothermal and dynamic-heating segments. In this study, an ultra-thin prepreg with highly loaded silica beads and glass fibers in the epoxy/amine resin system was investigated as a model system by isothermal/dynamic heating experiments. The maximum degree of cure was obtained as a function of temperature. The curing kinetics of the model prepreg system exhibited a multi-step reaction and a limited conversion as a function of isothermal curing temperatures, which are often observed in epoxy cure system because of the rate-determining diffusion of polymer chain growth. The modified kinetic equation accurately described the isothermal behavior and the beginning of the dynamic-heating behavior by integrating the obtained maximum degree of cure into the kinetic model development.

Dynamic footprint measurement collection technique and intrarater reliability: ink mat, paper pedography, and electronic pedography.

PubMed

Fascione, Jeanna M; Crews, Ryan T; Wrobel, James S

2012-01-01

Identifying the variability of footprint measurement collection techniques and the reliability of footprint measurements would assist with appropriate clinical foot posture appraisal. We sought to identify relationships between these measures in a healthy population. On 30 healthy participants, midgait dynamic footprint measurements were collected using an ink mat, paper pedography, and electronic pedography. The footprints were then digitized, and the following footprint indices were calculated with photo digital planimetry software: footprint index, arch index, truncated arch index, Chippaux-Smirak Index, and Staheli Index. Differences between techniques were identified with repeated-measures analysis of variance with post hoc test of Scheffe. In addition, to assess practical similarities between the different methods, intraclass correlation coefficients (ICCs) were calculated. To assess intrarater reliability, footprint indices were calculated twice on 10 randomly selected ink mat footprint measurements, and the ICC was calculated. Dynamic footprint measurements collected with an ink mat significantly differed from those collected with paper pedography (ICC, 0.85-0.96) and electronic pedography (ICC, 0.29-0.79), regardless of the practical similarities noted with ICC values (P = .00). Intrarater reliability for dynamic ink mat footprint measurements was high for the footprint index, arch index, truncated arch index, Chippaux-Smirak Index, and Staheli Index (ICC, 0.74-0.99). Footprint measurements collected with various techniques demonstrate differences. Interchangeable use of exact values without adjustment is not advised. Intrarater reliability of a single method (ink mat) was found to be high.

Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Brenner, Martin J.; Prazenica, Richard J.

2003-01-01

Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.

Shelf-life extension of gilthead seabream fillets by osmotic treatment and antimicrobial agents.

PubMed

Tsironi, T N; Taoukis, P S

2012-02-01

The objectives of the study were to evaluate the effect of selected antimicrobial agents on the shelf life of osmotically pretreated gilthead seabream and to establish reliable kinetic equations for shelf-life determination validated in dynamic conditions. Fresh gilthead seabream (Sparus aurata) fillets were osmotically treated with 50% high dextrose equivalent maltodextrin (HDM, DE 47) plus 5% NaCl and 0·5% carvacrol, 0·5% glucono-δ-lactone or 1% Citrox (commercial antimicrobial mix). Untreated and treated slices were aerobically packed and stored isothermally (0-15°C). Microbial growth and quality-related chemical indices were modelled as functions of temperature. Models were validated at dynamic storage conditions. Osmotic pretreatment with the use of antimicrobials led to significant shelf-life extension of fillets, in terms of microbial growth and organoleptic deterioration. The shelf life was 7 days for control samples at 5°C. The osmotic pretreatment with carvacrol, glucono-δ-lactone and Citrox allowed for shelf-life extension by 8, 10 and 5 days at 5°C, respectively. The results of the study show the potential of adding carvacrol, glucono-δ-lactone or Citrox in the osmotic solution to extend the shelf life and improve commercial value of chilled osmotically pretreated fish products. The developed models can be a reliable tool for predicting the shelf life of fresh or minimally processed gilthead seabream fillets in the real chill chain. © 2012 The Authors. Journal of Applied Microbiology © 2012 The Society for Applied Microbiology.

Statistical and dynamical forecast of regional precipitation after mature phase of ENSO

NASA Astrophysics Data System (ADS)

Sohn, S.; Min, Y.; Lee, J.; Tam, C.; Ahn, J.

2010-12-01

While the seasonal predictability of general circulation models (GCMs) has been improved, the current model atmosphere in the mid-latitude does not respond correctly to external forcing such as tropical sea surface temperature (SST), particularly over the East Asia and western North Pacific summer monsoon regions. In addition, the time-scale of prediction scope is considerably limited and the model forecast skill still is very poor beyond two weeks. Although recent studies indicate that coupled model based multi-model ensemble (MME) forecasts show the better performance, the long-lead forecasts exceeding 9 months still show a dramatic decrease of the seasonal predictability. This study aims at diagnosing the dynamical MME forecasts comprised of the state of art 1-tier models as well as comparing them with the statistical model forecasts, focusing on the East Asian summer precipitation predictions after mature phase of ENSO. The lagged impact of El Nino as major climate contributor on the summer monsoon in model environments is also evaluated, in the sense of the conditional probabilities. To evaluate the probability forecast skills, the reliability (attributes) diagram and the relative operating characteristics following the recommendations of the World Meteorological Organization (WMO) Standardized Verification System for Long-Range Forecasts are used in this study. The results should shed light on the prediction skill for dynamical model and also for the statistical model, in forecasting the East Asian summer monsoon rainfall with a long-lead time.

Recent Enhancements to the National Transonic Facility

NASA Technical Reports Server (NTRS)

Kilgore, W. A.; Balakrishna, S.; Bobbitt, C. W.; Underwood, P.

2003-01-01

The National Transonic Facility continues to make enhancements to provide quality data in a safe, efficient and cost effective method for aerodynamic ground testing. Recent enhancements discussed in this paper include the restoration of reliability and improved performance of the heat exchanger systems resulting in the expansion of the NTF air operations envelope. Additionally, results are presented from a continued effort to reduce model dynamics through the use of a new stiffer balance and sting

In-Vivo Human Skin to Textiles Friction Measurements

NASA Astrophysics Data System (ADS)

Pfarr, Lukas; Zagar, Bernhard

2017-10-01

We report on a measurement system to determine highly reliable and accurate friction properties of textiles as needed for example as input to garment simulation software. Our investigations led to a set-up that allows to characterize not just textile to textile but also textile to in-vivo human skin tribological properties and thus to fundamental knowledge about genuine wearer interaction in garments. The method of test conveyed in this paper is measuring concurrently and in a highly time resolved manner the normal force as well as the resulting shear force caused by a friction subject intending to slide out of the static friction regime and into the dynamic regime on a test bench. Deeper analysis of various influences is enabled by extending the simple model following Coulomb's law for rigid body friction to include further essential parameters such as contact force, predominance in the yarn's orientation and also skin hydration. This easy-to-use system enables to measure reliably and reproducibly both static and dynamic friction for a variety of friction partners including human skin with all its variability there might be.

PSHFT - COMPUTERIZED LIFE AND RELIABILITY MODELLING FOR TURBOPROP TRANSMISSIONS

NASA Technical Reports Server (NTRS)

Savage, M.

1994-01-01

The computer program PSHFT calculates the life of a variety of aircraft transmissions. A generalized life and reliability model is presented for turboprop and parallel shaft geared prop-fan aircraft transmissions. The transmission life and reliability model is a combination of the individual reliability models for all the bearings and gears in the main load paths. The bearing and gear reliability models are based on the statistical two parameter Weibull failure distribution method and classical fatigue theories. The computer program developed to calculate the transmission model is modular. In its present form, the program can analyze five different transmissions arrangements. Moreover, the program can be easily modified to include additional transmission arrangements. PSHFT uses the properties of a common block two-dimensional array to separate the component and transmission property values from the analysis subroutines. The rows correspond to specific components with the first row containing the values for the entire transmission. Columns contain the values for specific properties. Since the subroutines (which determine the transmission life and dynamic capacity) interface solely with this property array, they are separated from any specific transmission configuration. The system analysis subroutines work in an identical manner for all transmission configurations considered. Thus, other configurations can be added to the program by simply adding component property determination subroutines. PSHFT consists of a main program, a series of configuration specific subroutines, generic component property analysis subroutines, systems analysis subroutines, and a common block. The main program selects the routines to be used in the analysis and sequences their operation. The series of configuration specific subroutines input the configuration data, perform the component force and life analyses (with the help of the generic component property analysis subroutines), fill the property array, call up the system analysis routines, and finally print out the analysis results for the system and components. PSHFT is written in FORTRAN 77 and compiled on a MicroSoft FORTRAN compiler. The program will run on an IBM PC AT compatible with at least 104k bytes of memory. The program was developed in 1988.

Prediction and forecast of Suspended Sediment Concentration (SSC) on the Upper Yangtze basin

NASA Astrophysics Data System (ADS)

Matos, José Pedro; Hassan, Marwan; Lu, Xixi; Franca, Mário J.

2017-04-01

Sediment transport in suspension may represent 90% or more of the global annual flux of sediment. For instance, more than 99% of the sediment supplied to the sea by the Yangtze River is suspended load. Suspended load is an important component for understanding channel dynamics and landscape evolution. Sediments transported in suspension are a major source of nutrients for aquatic organisms in riparian and floodplain habitats, and play a beneficial role acting as a sink in the carbon cycle. Excess of fine sediments may also have adverse effects. It can impair fish spawning by riverbed clogging, disturb foraging efficiency of hunting of river fauna, cause algae and benthos scouring, reduce or inhibit exchanges through the hyporheic region. Accumulation of fine sediments in reservoirs reduces storage capacity. Although fine sediment dynamics has been the focus of many studies, the current knowledge of sediment sources, transfer, and storage is inadequate to address fine sediment dynamics in the landscape. The theoretical derivation of a complete model for suspended sediment transport at the basin scale, incorporating small scale processes of production and transport, is hindered because the underlying mechanisms are produced at different non-similar scales. Availability of long-term reliable data on suspended sediment dynamics is essential to improve our knowledge on transport processes and to develop reliable sediment prediction models. Over the last 60 years, the Yangtze River Commission has been measuring the daily Suspended Sediment Concentration (SSC) at the Pingshan station. This dataset provides a unique opportunity to examine temporal variability and controls of fine sediment dynamics in the Upper Yangtze basin. The objective of this study is to describe temporal variation of fine sediment dynamics at the Pingshan station making use of the extensive sediment monitoring program undertaken at that location. We test several strategies of prediction and forecast applied to the long time series of SSC and streamflow. By changing the base variables between strategies, we improve our understanding of the phenomena driving SSC. Prediction and forecasts are obtained from the various input data sets based on a novel probabilistic data-driven technique, the Generalized Pareto Uncertainty (GPU), which requires very little parametrization. Addressing uncertainty explicitly, this methodology recognizes the stochastic nature of SSC. The GPU was inspired in machine learning concepts and benefits from advances in multi-objective optimization techniques to discard most explicit assumptions about the nature of the uncertainty being modeled. Assumptions that do remain are the need to specify a model for eventual non-stationarity of the series and that there are enough observations to conveniently model the uncertainty. In this contribution, several models are tested with conditioned inputs to focus on specific processes leading affecting SSC. For example, the influence of seasonal and local contributions to SSC can be separated by conditioning the probability estimation on seasonal and local drivers. Probabilistic forecasting models for SSC that account for different drivers of the phenomena are discussed.

Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

NASA Astrophysics Data System (ADS)

Ding, Yulin; Lin, Hui; Li, Rongrong

2016-06-01

Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.

Towards a comprehensive framework for cosimulation of dynamic models with an emphasis on time stepping

NASA Astrophysics Data System (ADS)

Hoepfer, Matthias

Over the last two decades, computer modeling and simulation have evolved as the tools of choice for the design and engineering of dynamic systems. With increased system complexities, modeling and simulation become essential enablers for the design of new systems. Some of the advantages that modeling and simulation-based system design allows for are the replacement of physical tests to ensure product performance, reliability and quality, the shortening of design cycles due to the reduced need for physical prototyping, the design for mission scenarios, the invoking of currently nonexisting technologies, and the reduction of technological and financial risks. Traditionally, dynamic systems are modeled in a monolithic way. Such monolithic models include all the data, relations and equations necessary to represent the underlying system. With increased complexity of these models, the monolithic model approach reaches certain limits regarding for example, model handling and maintenance. Furthermore, while the available computer power has been steadily increasing according to Moore's Law (a doubling in computational power every 10 years), the ever-increasing complexities of new models have negated the increased resources available. Lastly, modern systems and design processes are interdisciplinary, enforcing the necessity to make models more flexible to be able to incorporate different modeling and design approaches. The solution to bypassing the shortcomings of monolithic models is cosimulation. In a very general sense, co-simulation addresses the issue of linking together different dynamic sub-models to a model which represents the overall, integrated dynamic system. It is therefore an important enabler for the design of interdisciplinary, interconnected, highly complex dynamic systems. While a basic co-simulation setup can be very easy, complications can arise when sub-models display behaviors such as algebraic loops, singularities, or constraints. This work frames the co-simulation approach to modeling and simulation. It lays out the general approach to dynamic system co-simulation, and gives a comprehensive overview of what co-simulation is and what it is not. It creates a taxonomy of the requirements and limits of co-simulation, and the issues arising with co-simulating sub-models. Possible solutions towards resolving the stated problems are investigated to a certain depth. A particular focus is given to the issue of time stepping. It will be shown that for dynamic models, the selection of the simulation time step is a crucial issue with respect to computational expense, simulation accuracy, and error control. The reasons for this are discussed in depth, and a time stepping algorithm for co-simulation with unknown dynamic sub-models is proposed. Motivations and suggestions for the further treatment of selected issues are presented.

Intrarater test-retest reliability of static and dynamic stability indexes measurement using the Biodex Stability System during unilateral stance.

PubMed

Arifin, Nooranida; Abu Osman, Noor Azuan; Wan Abas, Wan Abu Bakar

2014-04-01

The measurements of postural balance often involve measurement error, which affects the analysis and interpretation of the outcomes. In most of the existing clinical rehabilitation research, the ability to produce reliable measures is a prerequisite for an accurate assessment of an intervention after a period of time. Although clinical balance assessment has been performed in previous study, none has determined the intrarater test-retest reliability of static and dynamic stability indexes during dominant single stance. In this study, one rater examined 20 healthy university students (female=12, male=8) in two sessions separated by 7 day intervals. Three stability indexes--the overall stability index (OSI), anterior/posterior stability index (APSI), and medial/ lateral stability index (MLSI) in static and dynamic conditions--were measured during single dominant stance. Intraclass correlation coefficient (ICC), standard error measurement (SEM) and 95% confidence interval (95% CI) were calculated. Test-retest ICCs for OSI, APSI, and MLSI were 0.85, 0.78, and 0.84 during static condition and were 0.77, 0.77, and 0.65 during dynamic condition, respectively. We concluded that the postural stability assessment using Biodex stability system demonstrates good-to-excellent test-retest reliability over a 1 week time interval.

Toward a 3D dynamic model of a faulty duplex ball bearing

NASA Astrophysics Data System (ADS)

Kogan, Gideon; Klein, Renata; Kushnirsky, Alex; Bortman, Jacob

2015-03-01

Bearings are vital components for safe and proper operation of machinery. Increasing efficiency of bearing diagnostics usually requires training of health and usage monitoring systems via expensive and time-consuming ground calibration tests. The main goal of this research, therefore, is to improve bearing dynamics modeling tools in order to reduce the time and budget needed to implement the health and usage monitoring approach. The proposed three-dimensional ball bearing dynamic model is based on the classic dynamic and kinematic equations. Interactions between the bodies are simulated using non-linear springs combined with dampers described by Hertz-type contact relation. The force friction is simulated using the hyperbolic-tangent function. The model allows simulation of a wide range of mechanical faults. It is validated by comparison to known bearing behavior and to experimental results. The model results are verified by demonstrating numerical convergence. The model results for the two cases of single and duplex angular ball bearings with axial deformation in the outer ring are presented. The qualitative investigation provides insight into bearing dynamics, the sensitivity study generalizes the qualitative findings for similar cases, and the comparison to the test results validates model reliability. The article demonstrates the variety of the cases that the 3D bearing model can simulate and the findings to which it may lead. The research allowed the identification of new patterns generated by single and duplex bearings with axially deformed outer race. It also enlightened the difference between single and duplex bearing manifestation. In the current research the dynamic model enabled better understanding of the physical behavior of the faulted bearings. Therefore, it is expected that the modeling approach has the potential to simplify and improve the development process of diagnostic algorithms. • A deformed outer race of a single axially loaded bearing is simulated. • The model results are subjected to a sensitivity study. • Duplex bearing with deformed outer race is simulated as well as tested. • The simulation results are in a good agreement with the experimental results.

Spur, helical, and spiral bevel transmission life modeling

NASA Technical Reports Server (NTRS)

Savage, Michael; Rubadeux, Kelly L.; Coe, Harold H.; Coy, John J.

1994-01-01

A computer program, TLIFE, which estimates the life, dynamic capacity, and reliability of aircraft transmissions, is presented. The program enables comparisons of transmission service life at the design stage for optimization. A variety of transmissions may be analyzed including: spur, helical, and spiral bevel reductions as well as series combinations of these reductions. The basic spur and helical reductions include: single mesh, compound, and parallel path plus revert star and planetary gear trains. A variety of straddle and overhung bearing configurations on the gear shafts are possible as is the use of a ring gear for the output. The spiral bevel reductions include single and dual input drives with arbitrary shaft angles. The program is written in FORTRAN 77 and has been executed both in the personal computer DOS environment and on UNIX workstations. The analysis may be performed in either the SI metric or the English inch system of units. The reliability and life analysis is based on the two-parameter Weibull distribution lives of the component gears and bearings. The program output file describes the overall transmission and each constituent transmission, its components, and their locations, capacities, and loads. Primary output is the dynamic capacity and 90-percent reliability and mean lives of the unit transmissions and the overall system which can be used to estimate service overhaul frequency requirements. Two examples are presented to illustrate the information available for single element and series transmissions.

Inter-operator Reliability of Magnetic Resonance Image-Based Computational Fluid Dynamics Prediction of Cerebrospinal Fluid Motion in the Cervical Spine.

PubMed

Martin, Bryn A; Yiallourou, Theresia I; Pahlavian, Soroush Heidari; Thyagaraj, Suraj; Bunck, Alexander C; Loth, Francis; Sheffer, Daniel B; Kröger, Jan Robert; Stergiopulos, Nikolaos

2016-05-01

For the first time, inter-operator dependence of MRI based computational fluid dynamics (CFD) modeling of cerebrospinal fluid (CSF) in the cervical spinal subarachnoid space (SSS) is evaluated. In vivo MRI flow measurements and anatomy MRI images were obtained at the cervico-medullary junction of a healthy subject and a Chiari I malformation patient. 3D anatomies of the SSS were reconstructed by manual segmentation by four independent operators for both cases. CFD results were compared at nine axial locations along the SSS in terms of hydrodynamic and geometric parameters. Intraclass correlation (ICC) assessed the inter-operator agreement for each parameter over the axial locations and coefficient of variance (CV) compared the percentage of variance for each parameter between the operators. Greater operator dependence was found for the patient (0.19 < ICC < 0.99) near the craniovertebral junction compared to the healthy subject (ICC > 0.78). For the healthy subject, hydraulic diameter and Womersley number had the least variance (CV = ~2%). For the patient, peak diastolic velocity and Reynolds number had the smallest variance (CV = ~3%). These results show a high degree of inter-operator reliability for MRI-based CFD simulations of CSF flow in the cervical spine for healthy subjects and a lower degree of reliability for patients with Type I Chiari malformation.

Reduced Uncertainties in the Flutter Analysis of the Aerostructures Test Wing

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Lung, Shun-fat

2010-01-01

Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. A test validated finite element model can provide a reliable flutter analysis to define the flutter placard speed to which the aircraft can be flown prior to flight flutter testing. Minimizing the difference between numerical and experimental results is a type of optimization problem. Through the use of the National Aeronautics and Space Administration Dryden Flight Research Center s (Edwards, California, USA) multidisciplinary design, analysis, and optimization tool to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes are matched to the target data and the mass matrix orthogonality is retained. The approach in this study has been applied to minimize the model uncertainties for the structural dynamic model of the aerostructures test wing, which was designed, built, and tested at the National Aeronautics and Space Administration Dryden Flight Research Center. A 25-percent change in flutter speed has been shown after reducing the uncertainties

Memory recall and spike-frequency adaptation

NASA Astrophysics Data System (ADS)

Roach, James P.; Sander, Leonard M.; Zochowski, Michal R.

2016-05-01

The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored patterns that contain the memory. However, it is unclear how the behavior is controlled by the brain so that after convergence to one configuration, it can proceed with recognition of another one. In the Hopfield model, this happens only through unrealistic changes of an effective global temperature that destabilizes all stored configurations. Here we show that spike-frequency adaptation (SFA), a common mechanism affecting neuron activation in the brain, can provide state-dependent control of pattern retrieval. We demonstrate this in a Hopfield network modified to include SFA, and also in a model network of biophysical neurons. In both cases, SFA allows for selective stabilization of attractors with different basins of attraction, and also for temporal dynamics of attractor switching that is not possible in standard autoassociative schemes. The dynamics of our models give a plausible account of different sorts of memory retrieval.

Test of a foraging-bioenergetics model to evaluate growth dynamics of endangered pallid sturgeon (Scaphirhynchus albus)

USGS Publications Warehouse

Deslauriers, David; Heironimus, Laura B.; Chipps, Steven R.

2016-01-01

Factors affecting feeding and growth of early life stages of the federally endangered pallid sturgeon (Scaphirhynchus albus) are not fully understood, owing to their scarcity in the wild. In this study was we evaluated the performance of a combined foraging-bioenergetics model as a tool for assessing growth of age-0 pallid sturgeon in the Missouri River. In the laboratory, three size classes of sturgeon larvae (18–44 mm; 0.027–0.329 g) were grown for 7 to 14 days under differing temperature (14–24 °C) and prey density (0–9 Chironomidae larvae/d) regimes. After accounting for effects of water temperature and prey density on fish activity, we compared observed final weight, final length, and number of prey consumed to values generated from the foraging-bioenergetics model. When confronted with an independent dataset, the combined model provided reliable estimates (within 13% of observations) of fish growth and prey consumption, underscoring the usefulness of the modeling approach for evaluating growth dynamics of larval fish when empirical data are lacking.

Reduced Uncertainties in the Flutter Analysis of the Aerostructures Test Wing

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun Fat

2011-01-01

Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. A test validated finite element model can provide a reliable flutter analysis to define the flutter placard speed to which the aircraft can be flown prior to flight flutter testing. Minimizing the difference between numerical and experimental results is a type of optimization problem. Through the use of the National Aeronautics and Space Administration Dryden Flight Research Center's (Edwards, California) multidisciplinary design, analysis, and optimization tool to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes are matched to the target data, and the mass matrix orthogonality is retained. The approach in this study has been applied to minimize the model uncertainties for the structural dynamic model of the aerostructures test wing, which was designed, built, and tested at the National Aeronautics and Space Administration Dryden Flight Research Center. A 25 percent change in flutter speed has been shown after reducing the uncertainties.

Sliding Mode Approaches for Robust Control, State Estimation, Secure Communication, and Fault Diagnosis in Nuclear Systems

NASA Astrophysics Data System (ADS)

Ablay, Gunyaz

Using traditional control methods for controller design, parameter estimation and fault diagnosis may lead to poor results with nuclear systems in practice because of approximations and uncertainties in the system models used, possibly resulting in unexpected plant unavailability. This experience has led to an interest in development of robust control, estimation and fault diagnosis methods. One particularly robust approach is the sliding mode control methodology. Sliding mode approaches have been of great interest and importance in industry and engineering in the recent decades due to their potential for producing economic, safe and reliable designs. In order to utilize these advantages, sliding mode approaches are implemented for robust control, state estimation, secure communication and fault diagnosis in nuclear plant systems. In addition, a sliding mode output observer is developed for fault diagnosis in dynamical systems. To validate the effectiveness of the methodologies, several nuclear plant system models are considered for applications, including point reactor kinetics, xenon concentration dynamics, an uncertain pressurizer model, a U-tube steam generator model and a coupled nonlinear nuclear reactor model.

Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise.

PubMed

Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J

2017-10-10

Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.

Dynamic Leidenfrost temperature on micro-textured surfaces: Acoustic wave absorption into thin vapor layer

NASA Astrophysics Data System (ADS)

Jerng, Dong Wook; Kim, Dong Eok

2018-01-01

The dynamic Leidenfrost phenomenon is governed by three types of pressure potentials induced via vapor hydrodynamics, liquid dynamic pressure, and the water hammer effect resulting from the generation of acoustic waves at the liquid-vapor interface. The prediction of the Leidenfrost temperature for a dynamic droplet needs quantitative evaluation and definition for each of the pressure fields. In particular, the textures on a heated surface can significantly affect the vapor hydrodynamics and the water hammer pressure. We present a quantitative model for evaluating the water hammer pressure on micro-textured surfaces taking into account the absorption of acoustic waves into the thin vapor layer. The model demonstrates that the strength of the acoustic flow into the liquid droplet, which directly contributes to the water hammer pressure, depends on the magnitude of the acoustic resistance (impedance) in the droplet and the vapor region. In consequence, the micro-textures of the surface and the increased spacing between them reduce the water hammer coefficient ( kh ) defined as the ratio of the acoustic flow into the droplet to total generated flow. Aided by numerical calculations that solve the laminar Navier-Stokes equation for the vapor flow, we also predict the dynamic Leidenfrost temperature on a micro-textured surface with reliable accuracy consistent with the experimental data.

Analysis on pseudo excitation of random vibration for structure of time flight counter

NASA Astrophysics Data System (ADS)

Wu, Qiong; Li, Dapeng

2015-03-01

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure. Pseudo Excitation Method(PEM) is an effective method for calculation of random vibration. Due to complicated and coupling random vibration in rocket or shuttle launching, the new staging white noise mathematical model is deduced according to the practical launch environment. This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter(ToFC). The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level. Considering stiffness of fixture structure, the random vibration experiments are conducted in three directions to compare with the revised PEM. The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained. The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results. The maximum error is within 9%. The reasons of errors are analyzed to improve reliability of calculation. This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

Molecular Modeling of Nucleic Acid Structure: Electrostatics and Solvation

PubMed Central

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E.

2014-01-01

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand the structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as means to sample conformational space for a better understanding of the relevance of a given model. From this discussion, the major limitations with modeling, in general, were highlighted. These are the difficult issues in sampling conformational space effectively—the multiple minima or conformational sampling problems—and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These are discussed in detail in this unit. PMID:18428877

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

PubMed

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

Prospectus: towards the development of high-fidelity models of wall turbulence at large Reynolds number

NASA Astrophysics Data System (ADS)

Klewicki, J. C.; Chini, G. P.; Gibson, J. F.

2017-03-01

Recent and on-going advances in mathematical methods and analysis techniques, coupled with the experimental and computational capacity to capture detailed flow structure at increasingly large Reynolds numbers, afford an unprecedented opportunity to develop realistic models of high Reynolds number turbulent wall-flow dynamics. A distinctive attribute of this new generation of models is their grounding in the Navier-Stokes equations. By adhering to this challenging constraint, high-fidelity models ultimately can be developed that not only predict flow properties at high Reynolds numbers, but that possess a mathematical structure that faithfully captures the underlying flow physics. These first-principles models are needed, for example, to reliably manipulate flow behaviours at extreme Reynolds numbers. This theme issue of Philosophical Transactions of the Royal Society A provides a selection of contributions from the community of researchers who are working towards the development of such models. Broadly speaking, the research topics represented herein report on dynamical structure, mechanisms and transport; scale interactions and self-similarity; model reductions that restrict nonlinear interactions; and modern asymptotic theories. In this prospectus, the challenges associated with modelling turbulent wall-flows at large Reynolds numbers are briefly outlined, and the connections between the contributing papers are highlighted.

Exploration of an urban lake management model to simulate chlorine interference based on the ecological relationships among aquatic species.

PubMed

Yan, Zhiqiang; Wang, Yafei; Wu, Di; Xia, Beicheng

2018-05-29

In eutrophic lakes, algae are known to be sensitive to chlorine, but the impact of chlorine on the wider ecosystem has not been investigated. To quantitatively investigate the effects of chlorine on the urban lake ecosystem and analyze the changes in the aquatic ecosystem structure, a dynamic response model of aquatic species to chlorine was constructed based on the biomass density dynamics of aquatic species of submerged macrophytes, phytoplankton, zooplankton, periphyton, and benthos. The parameters were calibrated using data from the literature and two simulative experiments. The model was then validated using field data from an urban lake with a surface area of approximately 8000 m 2 located in the downtown area of Guangzhou, South China. The correlation coefficient (R), root mean square error-observations standard deviation ratio (RSR) and index of agreement (IOA) were used to evaluate the accuracy and reliability of the model and the results were consistent with the observations (0.446 R < 0.985, RSR < 0.7, IOA > 0.6). Comparisons between the simulated and observed trends confirmed the feasibility of using this model to investigate the dynamics of aquatic species under chlorine interference. The model can help managers apply a modest amount of chlorine to control eutrophication and provides scientific support for the management of urban lakes.

Reliable binary cell-fate decisions based on oscillations

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2014-02-01

Biological systems have often to perform binary decisions under highly dynamic and noisy environments, such as during cell-fate determination. These decisions can be implemented by two main bifurcation mechanisms based on the transitions from either monostability or oscillation to bistability. We compare these two mechanisms by using stochastic models with time-varying fields and by establishing asymptotic formulas for the choice probabilities. Different scaling laws for decision sensitivity with respect to noise strength and signal timescale are obtained, supporting a role for oscillatory dynamics in performing noise-robust and temporally tunable binary decision-making. This result provides a rationale for recent experimental evidences showing that oscillatory expression of proteins often precedes binary cell-fate decisions.

Discrimination of correlated and entangling quantum channels with selective process tomography

DOE PAGES

Dumitrescu, Eugene; Humble, Travis S.

2016-10-10

The accurate and reliable characterization of quantum dynamical processes underlies efforts to validate quantum technologies, where discrimination between competing models of observed behaviors inform efforts to fabricate and operate qubit devices. We present a protocol for quantum channel discrimination that leverages advances in direct characterization of quantum dynamics (DCQD) codes. We demonstrate that DCQD codes enable selective process tomography to improve discrimination between entangling and correlated quantum dynamics. Numerical simulations show selective process tomography requires only a few measurement configurations to achieve a low false alarm rate and that the DCQD encoding improves the resilience of the protocol to hiddenmore » sources of noise. Lastly, our results show that selective process tomography with DCQD codes is useful for efficiently distinguishing sources of correlated crosstalk from uncorrelated noise in current and future experimental platforms.« less

Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

NASA Astrophysics Data System (ADS)

Cui, Ling-xiao; Long, Wen

2016-11-01

Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

Assurance of reliability and safety in liquid hydrocarbons marine transportation and storing

NASA Astrophysics Data System (ADS)

Korshunov, G. I.; Polyakov, S. L.; Shunmin, Li

2017-10-01

The problems of assurance of safety and reliability in the liquid hydrocarbons marine transportation and storing are described. The requirements of standard IEC61511 have to be fulfilled for the load/unload in tanker’s system under dynamic loads on the pipeline system. The safety zones for fires of the type “fireball” and the spillage have to be determined when storing the liquid hydrocarbons. An example of the achieved necessary safety level of the duplicated load system, the conditions of the pipelines reliable operation under dynamic loads, the principles of the method of the liquid hydrocarbons storage safety zones under possible accident conditions are represented.

Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen.

PubMed

Malerba, Martino E; Heimann, Kirsten; Connolly, Sean R

2016-09-07

Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computation of physiological human vocal fold parameters by mathematical optimization of a biomechanical model

PubMed Central

Yang, Anxiong; Stingl, Michael; Berry, David A.; Lohscheller, Jörg; Voigt, Daniel; Eysholdt, Ulrich; Döllinger, Michael

2011-01-01

With the use of an endoscopic, high-speed camera, vocal fold dynamics may be observed clinically during phonation. However, observation and subjective judgment alone may be insufficient for clinical diagnosis and documentation of improved vocal function, especially when the laryngeal disease lacks any clear morphological presentation. In this study, biomechanical parameters of the vocal folds are computed by adjusting the corresponding parameters of a three-dimensional model until the dynamics of both systems are similar. First, a mathematical optimization method is presented. Next, model parameters (such as pressure, tension and masses) are adjusted to reproduce vocal fold dynamics, and the deduced parameters are physiologically interpreted. Various combinations of global and local optimization techniques are attempted. Evaluation of the optimization procedure is performed using 50 synthetically generated data sets. The results show sufficient reliability, including 0.07 normalized error, 96% correlation, and 91% accuracy. The technique is also demonstrated on data from human hemilarynx experiments, in which a low normalized error (0.16) and high correlation (84%) values were achieved. In the future, this technique may be applied to clinical high-speed images, yielding objective measures with which to document improved vocal function of patients with voice disorders. PMID:21877808

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. PMID:27918593

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2016-10-01

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic Response of Functionally Graded Carbon Nanotube Reinforced Sandwich Plate

NASA Astrophysics Data System (ADS)

Mehar, Kulmani; Panda, Subrata Kumar

2018-03-01

In this article, the dynamic response of the carbon nanotube-reinforced functionally graded sandwich composite plate has been studied numerically with the help of finite element method. The face sheets of the sandwich composite plate are made of carbon nanotube- reinforced composite for two different grading patterns whereas the core phase is taken as isotropic material. The final properties of the structure are calculated using the rule of mixture. The geometrical model of the sandwich plate is developed and discretized suitably with the help of available shell element in ANSYS library. Subsequently, the corresponding numerical dynamic responses computed via batch input technique (parametric design language code in ANSYS) of ANSYS including Newmark’s integration scheme. The stability of the sandwich structural numerical model is established through the proper convergence study. Further, the reliability of the sandwich model is checked by comparison study between present and available results from references. As a final point, some numerical problems have been solved to examine the effect of different design constraints (carbon nanotube distribution pattern, core to face thickness ratio, volume fractions of the nanotube, length to thickness ratio, aspect ratio and constraints at edges) on the time-responses of sandwich plate.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

PubMed

Zomorodian, Mehdi; Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method

PubMed Central

Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system. PMID:29216200

Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach

PubMed Central

Zhang, Kefeng; Bosch-Serra, Angela D.; Boixadera, Jaume; Thompson, Andrew J.

2015-01-01

Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm3 cm-3 and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha-l for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was discussed. PMID:26098946

Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

PubMed

Zhang, Kefeng; Bosch-Serra, Angela D; Boixadera, Jaume; Thompson, Andrew J

2015-01-01

Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3) cm(-3) and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l) for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was discussed.

An integrated system dynamics model developed for managing lake water quality at the watershed scale.

PubMed

Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng

2015-05-15

A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Update on SU(2) gauge theory with NF = 2 fundamental flavours.

NASA Astrophysics Data System (ADS)

Drach, Vincent; Janowski, Tadeusz; Pica, Claudio

2018-03-01

We present a non perturbative study of SU(2) gauge theory with two fundamental Dirac flavours. This theory provides a minimal template which is ideal for a wide class of Standard Model extensions featuring novel strong dynamics, such as a minimal realization of composite Higgs models. We present an update on the status of the meson spectrum and decay constants based on increased statistics on our existing ensembles and the inclusion of new ensembles with lighter pion masses, resulting in a more reliable chiral extrapolation. Preprint: CP3-Origins-2017-048 DNRF90

On the stochastic dissemination of faults in an admissible network

NASA Technical Reports Server (NTRS)

Kyrala, A.

1987-01-01

The dynamic distribution of faults in a general type network is discussed. The starting point is a uniquely branched network in which each pair of nodes is connected by a single branch. Mathematical expressions for the uniquely branched network transition matrix are derived to show that sufficient stationarity exists to ensure the validity of the use of the Markov Chain model to analyze networks. In addition the conditions for the use of Semi-Markov models are discussed. General mathematical expressions are derived in an examination of branch redundancy techniques commonly used to increase reliability.

Radioisotope Power System Pool Concept

NASA Technical Reports Server (NTRS)

Rusick, Jeffrey J.; Bolotin, Gary S.

2015-01-01

Advanced Radioisotope Power Systems (RPS) for NASA deep space science missions have historically used static thermoelectric-based designs because they are highly reliable, and their radioisotope heat sources can be passively cooled throughout the mission life cycle. Recently, a significant effort to develop a dynamic RPS, the Advanced Stirling Radioisotope Generator (ASRG), was conducted by NASA and the Department of Energy, because Stirling based designs offer energy conversion efficiencies four times higher than heritage thermoelectric designs; and the efficiency would proportionately reduce the amount of radioisotope fuel needed for the same power output. However, the long term reliability of a Stirling based design is a concern compared to thermoelectric designs, because for certain Stirling system architectures the radioisotope heat sources must be actively cooled via the dynamic operation of Stirling converters throughout the mission life cycle. To address this reliability concern, a new dynamic Stirling cycle RPS architecture is proposed called the RPS Pool Concept.

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

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

A reliability analysis of the revised competitiveness index.

PubMed

Harris, Paul B; Houston, John M

2010-06-01

This study examined the reliability of the Revised Competitiveness Index by investigating the test-retest reliability, interitem reliability, and factor structure of the measure based on a sample of 280 undergraduates (200 women, 80 men) ranging in age from 18 to 28 years (M = 20.1, SD = 2.1). The findings indicate that the Revised Competitiveness Index has high test-retest reliability, high inter-item reliability, and a stable factor structure. The results support the assertion that the Revised Competitiveness Index assesses competitiveness as a stable trait rather than a dynamic state.

Long-Period Tidal Variations in the Length of Day

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Erofeeva, Svetlana Y.

2014-01-01

A new model of long-period tidal variations in length of day is developed. The model comprises 80 spectral lines with periods between 18.6 years and 4.7 days, and it consistently includes effects of mantle anelasticity and dynamic ocean tides for all lines. The anelastic properties followWahr and Bergen; experimental confirmation for their results now exists at the fortnightly period, but there remains uncertainty when extrapolating to the longest periods. The ocean modeling builds on recent work with the fortnightly constituent, which suggests that oceanic tidal angular momentum can be reliably predicted at these periods without data assimilation. This is a critical property when modeling most long-period tides, for which little observational data exist. Dynamic ocean effects are quite pronounced at shortest periods as out-of-phase rotation components become nearly as large as in-phase components. The model is tested against a 20 year time series of space geodetic measurements of length of day. The current international standard model is shown to leave significant residual tidal energy, and the new model is found to mostly eliminate that energy, with especially large variance reduction for constituents Sa, Ssa, Mf, and Mt.

Reliability model generator

NASA Technical Reports Server (NTRS)

Cohen, Gerald C. (Inventor); McMann, Catherine M. (Inventor)

1991-01-01

An improved method and system for automatically generating reliability models for use with a reliability evaluation tool is described. The reliability model generator of the present invention includes means for storing a plurality of low level reliability models which represent the reliability characteristics for low level system components. In addition, the present invention includes means for defining the interconnection of the low level reliability models via a system architecture description. In accordance with the principles of the present invention, a reliability model for the entire system is automatically generated by aggregating the low level reliability models based on the system architecture description.

Imitative modeling automatic system Control of steam pressure in the main steam collector with the influence on the main Servomotor steam turbine

NASA Astrophysics Data System (ADS)

Andriushin, A. V.; Zverkov, V. P.; Kuzishchin, V. F.; Ryzhkov, O. S.; Sabanin, V. R.

2017-11-01

The research and setting results of steam pressure in the main steam collector “Do itself” automatic control system (ACS) with high-speed feedback on steam pressure in the turbine regulating stage are presented. The ACS setup is performed on the simulation model of the controlled object developed for this purpose with load-dependent static and dynamic characteristics and a non-linear control algorithm with pulse control of the turbine main servomotor. A method for tuning nonlinear ACS with a numerical algorithm for multiparametric optimization and a procedure for separate dynamic adjustment of control devices in a two-loop ACS are proposed and implemented. It is shown that the nonlinear ACS adjusted with the proposed method with the regulators constant parameters ensures reliable and high-quality operation without the occurrence of oscillations in the transient processes the operating range of the turbine loads.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

A system framework of inter-enterprise machining quality control based on fractal theory

NASA Astrophysics Data System (ADS)

Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng

2014-03-01

In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.

Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters

NASA Astrophysics Data System (ADS)

Lee, Da Young; Lee, Gi Wook; Yoon, Kyu; Chun, Byoungjin; Jung, Hyun Wook

2018-01-01

Flows through porous filter walls of wall-flow diesel particulate filter are investigated using the lattice Boltzmann method (LBM). The microscopic model of the realistic filter wall is represented by randomly overlapped arrays of solid spheres. The LB simulation results are first validated by comparison to those from previous hydrodynamic theories and constitutive models for flows in porous media with simple regular and random solid-wall configurations. We demonstrate that the newly designed randomly overlapped array structures of porous walls allow reliable and accurate simulations for the porous wall-flow dynamics in a wide range of solid volume fractions from 0.01 to about 0.8, which is beyond the maximum random packing limit of 0.625. The permeable performance of porous media is scrutinized by changing the solid volume fraction and particle Reynolds number using Darcy's law and Forchheimer's extension in the laminar flow region.

Status and prospects of computational fluid dynamics for unsteady transonic viscous flows

NASA Technical Reports Server (NTRS)

Mccroskey, W. J.; Kutler, P.; Bridgeman, J. O.

1984-01-01

Applications of computational aerodynamics to aeronautical research, design, and analysis have increased rapidly over the past decade, and these applications offer significant benefits to aeroelasticians. The past developments are traced by means of a number of specific examples, and the trends are projected over the next several years. The crucial factors that limit the present capabilities for unsteady analyses are identified; they include computer speed and memory, algorithm and solution methods, grid generation, turbulence modeling, vortex modeling, data processing, and coupling of the aerodynamic and structural dynamic analyses. The prospects for overcoming these limitations are presented, and many improvements appear to be readily attainable. If so, a complete and reliable numerical simulation of the unsteady, transonic viscous flow around a realistic fighter aircraft configuration could become possible within the next decade. The possibilities of using artificial intelligence concepts to hasten the achievement of this goal are also discussed.

Progress Towards Spectroscopic Diagnostics of Plasma Parameters and Neutral Dynamics in Helicon Plasmas

NASA Astrophysics Data System (ADS)

Green, Jonathan; Schmitz, Oliver; Severn, Greg; van Ruremonde, Lars; Winters, Victoria

2017-10-01

The MARIA device at the UW-Madison is used primarily to investigate the dynamics and fueling of neutral particles in helicon discharges. A new systematic method is in development to measure key plasma and neutral particle parameters by spectroscopic methods. The setup relies on spectroscopic line ratios for investigating basic plasma parameters and extrapolation to other states using a collisional radiative model. Active pumping using a Nd:YAG pumped dye laser is used to benchmark and correct the underlying atomic data for the collisional radiative model. First results show a matching linear dependence between electron density and laser induced fluorescence on the magnetic field above 500G. This linear dependence agrees with the helicon dispersion relation and implies MARIA can reliably support the helicon mode and support future measurements. This work was funded by the NSF CAREER award PHY-1455210.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

Designing an architectural style for Pervasive Healthcare systems.

PubMed

Rafe, Vahid; Hajvali, Masoumeh

2013-04-01

Nowadays, the Pervasive Healthcare (PH) systems are considered as an important research area. These systems have a dynamic structure and configuration. Therefore, an appropriate method for designing such systems is necessary. The Publish/Subscribe Architecture (pub/sub) is one of the convenient architectures to support such systems. PH systems are safety critical; hence, errors can bring disastrous results. To prevent such problems, a powerful analytical tool is required. So using a proper formal language like graph transformation systems for developing of these systems seems necessary. But even if software engineers use such high level methodologies, errors may occur in the system under design. Hence, it should be investigated automatically and formally that whether this model of system satisfies all their requirements or not. In this paper, a dynamic architectural style for developing PH systems is presented. Then, the behavior of these systems is modeled and evaluated using GROOVE toolset. The results of the analysis show its high reliability.

A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana.

PubMed

Kotir, Julius H; Smith, Carl; Brown, Greg; Marshall, Nadine; Johnstone, Ron

2016-12-15

In a rapidly changing water resources system, dynamic models based on the notion of systems thinking can serve as useful analytical tools for scientists and policy-makers to study changes in key system variables over time. In this paper, an integrated system dynamics simulation model was developed using a system dynamics modelling approach to examine the feedback processes and interaction between the population, the water resource, and the agricultural production sub-sectors of the Volta River Basin in West Africa. The objective of the model is to provide a learning tool for policy-makers to improve their understanding of the long-term dynamic behaviour of the basin, and as a decision support tool for exploring plausible policy scenarios necessary for sustainable water resource management and agricultural development. Structural and behavioural pattern tests, and statistical test were used to evaluate and validate the performance of the model. The results showed that the simulated outputs agreed well with the observed reality of the system. A sensitivity analysis also indicated that the model is reliable and robust to uncertainties in the major parameters. Results of the business as usual scenario showed that total population, agricultural, domestic, and industrial water demands will continue to increase over the simulated period. Besides business as usual, three additional policy scenarios were simulated to assess their impact on water demands, crop yield, and net-farm income. These were the development of the water infrastructure (scenario 1), cropland expansion (scenario 2) and dry conditions (scenario 3). The results showed that scenario 1 would provide the maximum benefit to people living in the basin. Overall, the model results could help inform planning and investment decisions within the basin to enhance food security, livelihoods development, socio-economic growth, and sustainable management of natural resources. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Testing with the NSWC Three-Degree-of-Freedom Gas Bearing

DTIC Science & Technology

1982-03-08

aerodynamic effects caused by the rate of change of angular variables. The three- degree-of-freedom gas bearing support was designed to permit the...Because the model is spinning, a mechanical Initiator woild be unduly complicated. The air jet has been found to be en entirely reliable and effective ...used for all data reduction. The only other diff 1- culty experienced was binding (intermittent stator/ rotor contact) Ln the gas bear- * Lug after

Predicting the recruitment of established regeneration into the sapling size class following partial cutting in the Acadian Forest Region: Using long-term observations to assess the performance of FVS-NE

Treesearch

David Ray; Chad Keyser; Robert Seymour; John Brissette

2008-01-01

Forest managers are increasingly called upon to provide long-term predictions of forest development. The dynamics of regeneration establishment, survival and subsequent recruitment of established seedlings to larger size classes is a critical component of these forecasts, yet remains a weak link in available models. To test the reliability of FVS-NE for simulating...

A Novel Solution-Technique Applied to a Novel WAAS Architecture

NASA Technical Reports Server (NTRS)

Bavuso, J.

1998-01-01

The Federal Aviation Administration has embarked on an historic task of modernizing and significantly improving the national air transportation system. One system that uses the Global Positioning System (GPS) to determine aircraft navigational information is called the Wide Area Augmentation System (WAAS). This paper describes a reliability assessment of one candidate system architecture for the WAAS. A unique aspect of this study regards the modeling and solution of a candidate system that allows a novel cold sparing scheme. The cold spare is a WAAS communications satellite that is fabricated and launched after a predetermined number of orbiting satellite failures have occurred and after some stochastic fabrication time transpires. Because these satellites are complex systems with redundant components, they exhibit an increasing failure rate with a Weibull time to failure distribution. Moreover, the cold spare satellite build-time is Weibull and upon launch is considered to be a good-as-new system with an increasing failure rate and a Weibull time to failure distribution as well. The reliability model for this system is non-Markovian because three distinct system clocks are required: the time to failure of the orbiting satellites, the build time for the cold spare, and the time to failure for the launched spare satellite. A powerful dynamic fault tree modeling notation and Monte Carlo simulation technique with importance sampling are shown to arrive at a reliability prediction for a 10 year mission.

The Trunk Impairment Scale - modified to ordinal scales in the Norwegian version.

PubMed

Gjelsvik, Bente; Breivik, Kyrre; Verheyden, Geert; Smedal, Tori; Hofstad, Håkon; Strand, Liv Inger

2012-01-01

To translate the Trunk Impairment Scale (TIS), a measure of trunk control in patients after stroke, into Norwegian (TIS-NV), and to explore its construct validity, internal consistency, intertester and test-retest reliability. TIS was translated according to international guidelines. The validity study was performed on data from 201 patients with acute stroke. Fifty patients with stroke and acquired brain injury were recruited to examine intertester and test-retest reliability. Construct validity was analyzed with exploratory and confirmatory factor analysis and item response theory, internal consistency with Cronbach's alpha test, and intertester and test-retest reliability with kappa and intraclass correlation coefficient tests. The back-translated version of TIS-NV was validated by the original developer. The subscale Static sitting balance was removed. By combining items from the subscales Dynamic sitting balance and Coordination, six ordinal superitems (testlets) were constructed. The TIS-NV was renamed the modified TIS-NV (TIS-modNV). After modifications the TIS-modNV fitted well to a locally dependent unidimensional item response theory model. It demonstrated good construct validity, excellent internal consistency, and high intertester and test-retest reliability for the total score. This study supports that the TIS-modNV is a valid and reliable scale for use in clinical practice and research.

Reliability analysis of airship remote sensing system

NASA Astrophysics Data System (ADS)

Qin, Jun

1998-08-01

Airship Remote Sensing System (ARSS) for obtain the dynamic or real time images in the remote sensing of the catastrophe and the environment, is a mixed complex system. Its sensor platform is a remote control airship. The achievement of a remote sensing mission depends on a series of factors. For this reason, it is very important for us to analyze reliability of ARSS. In first place, the system model was simplified form multi-stage system to two-state system on the basis of the result of the failure mode and effect analysis and the failure tree failure mode effect and criticality analysis. The failure tree was created after analyzing all factors and their interrelations. This failure tree includes four branches, e.g. engine subsystem, remote control subsystem, airship construction subsystem, flying metrology and climate subsystem. By way of failure tree analysis and basic-events classing, the weak links were discovered. The result of test running shown no difference in comparison with theory analysis. In accordance with the above conclusions, a plan of the reliability growth and reliability maintenance were posed. System's reliability are raised from 89 percent to 92 percent with the reformation of the man-machine interactive interface, the augmentation of the secondary better-groupie and the secondary remote control equipment.

Simulation, measurement, and emulation of photovoltaic modules using high frequency and high power density power electronic circuits

NASA Astrophysics Data System (ADS)

Erkaya, Yunus

The number of solar photovoltaic (PV) installations is growing exponentially, and to improve the energy yield and the efficiency of PV systems, it is necessary to have correct methods for simulation, measurement, and emulation. PV systems can be simulated using PV models for different configurations and technologies of PV modules. Additionally, different environmental conditions of solar irradiance, temperature, and partial shading can be incorporated in the model to accurately simulate PV systems for any given condition. The electrical measurement of PV systems both prior to and after making electrical connections is important for attaining high efficiency and reliability. Measuring PV modules using a current-voltage (I-V) curve tracer allows the installer to know whether the PV modules are 100% operational. The installed modules can be properly matched to maximize performance. Once installed, the whole system needs to be characterized similarly to detect mismatches, partial shading, or installation damage before energizing the system. This will prevent any reliability issues from the onset and ensure the system efficiency will remain high. A capacitive load is implemented in making I-V curve measurements with the goal of minimizing the curve tracer volume and cost. Additionally, the increase of measurement resolution and accuracy is possible via the use of accurate voltage and current measurement methods and accurate PV models to translate the curves to standard testing conditions. A move from mechanical relays to solid-state MOSFETs improved system reliability while significantly reducing device volume and costs. Finally, emulating PV modules is necessary for testing electrical components of a PV system. PV emulation simplifies and standardizes the tests allowing for different irradiance, temperature and partial shading levels to be easily tested. Proper emulation of PV modules requires an accurate and mathematically simple PV model that incorporates all known system variables so that any PV module can be emulated as the design requires. A non-synchronous buck converter is proposed for the emulation of a single, high-power PV module using traditional silicon devices. With the proof-of-concept working and improvements in efficiency, power density and steady-state errors made, dynamic tests were performed using an inverter connected to the PV emulator. In order to improve the dynamic characteristics, a synchronous buck converter topology is proposed along with the use of advanced GaNFET devices which resulted in very high power efficiency and improved dynamic response characteristics when emulating PV modules.

An evaluation of Dynamic TOPMODEL in natural and human-impacted catchments for low flow simulation

NASA Astrophysics Data System (ADS)

Coxon, Gemma; Freer, Jim; Lane, Rosanna; Musuuza, Jude; Woods, Ross; Wagener, Thorsten; Howden, Nicholas

2017-04-01

Models of catchment hydrology are essential tools for drought risk management, often providing input to water resource system models, aiding our understanding of low flow processes within catchments and providing low flow simulations and predictions. However, simulating low flows is challenging as hydrological systems often demonstrate threshold effects in connectivity, non-linear groundwater contributions and a greater influence of anthropogenic modifications such as surface and ground water abstractions during low flow periods. These processes are typically not well represented in commonly used hydrological models due to knowledge, data and model limitations. Hence, a better understanding of the natural and human processes that occur during low flows, how these are represented within models and how they could be improved is required to be able to provide robust and reliable predictions of future drought events. The aim of this study is to assess the skill of dynamic TOPMODEL during low flows for both natural and human-impacted catchments. Dynamic TOPMODEL was chosen for this study as it is able to explicitly characterise connectivity and fluxes across landscapes using hydrological response units (HRU's) while still maintaining flexibility in how spatially complex the model is configured and what specific functions (i.e. abstractions or groundwater stores) are represented. We apply dynamic TOPMODEL across the River Thames catchment using daily time series of observed rainfall and potential evapotranspiration data for the period 1999 - 2014, covering two major droughts in the Thames catchment. Significantly, to assess the impact of abstractions on low flows across the Thames catchment, we incorporate functions to characterise over 3,500 monthly surface water and ground water abstractions covering the simulation period into dynamic TOPMODEL. We evaluate dynamic TOPMODEL at over 90 gauging stations across the Thames catchment against multiple signatures of catchment low-flow behaviour in a 'limits of acceptability' GLUE framework. We investigate differences in model performance between signatures, different low flow periods and for natural and human impacted catchments to better understand the ability of dynamic TOPMODEL to represent low flows in space and time. Finally, we discuss future developments of dynamic TOPMODEL to improve low flow simulation and the implications of these results for modelling hydrological extremes in natural and human impacted catchments across the UK and the world.

The Mechanisms for Within-Host Influenza Virus Control Affect Model-Based Assessment and Prediction of Antiviral Treatment

PubMed Central

Cao, Pengxing

2017-01-01

Models of within-host influenza viral dynamics have contributed to an improved understanding of viral dynamics and antiviral effects over the past decade. Existing models can be classified into two broad types based on the mechanism of viral control: models utilising target cell depletion to limit the progress of infection and models which rely on timely activation of innate and adaptive immune responses to control the infection. In this paper, we compare how two exemplar models based on these different mechanisms behave and investigate how the mechanistic difference affects the assessment and prediction of antiviral treatment. We find that the assumed mechanism for viral control strongly influences the predicted outcomes of treatment. Furthermore, we observe that for the target cell-limited model the assumed drug efficacy strongly influences the predicted treatment outcomes. The area under the viral load curve is identified as the most reliable predictor of drug efficacy, and is robust to model selection. Moreover, with support from previous clinical studies, we suggest that the target cell-limited model is more suitable for modelling in vitro assays or infection in some immunocompromised/immunosuppressed patients while the immune response model is preferred for predicting the infection/antiviral effect in immunocompetent animals/patients. PMID:28933757

Benchmark model correction of monitoring system based on Dynamic Load Test of Bridge

NASA Astrophysics Data System (ADS)

Shi, Jing-xian; Fan, Jiang

2018-03-01

Structural health monitoring (SHM) is a field of research in the area, and it’s designed to achieve bridge safety and reliability assessment, which needs to be carried out on the basis of the accurate simulation of the finite element model. Bridge finite element model is simplified of the structural section form, support conditions, material properties and boundary condition, which is based on the design and construction drawings, and it gets the calculation models and the results.But according to the design and specification requirements established finite element model due to its cannot fully reflect the true state of the bridge, so need to modify the finite element model to obtain the more accurate finite element model. Based on Da-guan river crossing of Ma - Zhao highway in Yunnan province as the background to do the dynamic load test test, we find that the impact coefficient of the theoretical model of the bridge is very different from the coefficient of the actual test, and the change is different; according to the actual situation, the calculation model is adjusted to get the correct frequency of the bridge, the revised impact coefficient found that the modified finite element model is closer to the real state, and provides the basis for the correction of the finite model.

THE DYNAMIC LEAP AND BALANCE TEST (DLBT): A TEST-RETEST RELIABILITY STUDY

PubMed Central

Newman, Thomas M.; Smith, Brent I.; John Miller, Sayers

2017-01-01

Background There is a need for new clinical assessment tools to test dynamic balance during typical functional movements. Common methods for assessing dynamic balance, such as the Star Excursion Balance Test, which requires controlled movement of body segments over an unchanged base of support, may not be an adequate measure for testing typical functional movements that involve controlled movement of body segments along with a change in base of support. Purpose/hypothesis The purpose of this study was to determine the reliability of the Dynamic Leap and Balance Test (DLBT) by assessing its test-retest reliability. It was hypothesized that there would be no statistically significant differences between testing days in time taken to complete the test. Study Design Reliability study Methods Thirty healthy college aged individuals participated in this study. Participants performed a series of leaps in a prescribed sequence, unique to the DLBT test. Time required by the participants to complete the 20-leap task was the dependent variable. Subjects leaped back and forth from peripheral to central targets alternating weight bearing from one leg to the other. Participants landed on the central target with the tested limb and were required to stabilize for two seconds before leaping to the next target. Stability was based upon qualitative measures similar to Balance Error Scoring System. Each assessment was comprised of three trials and performed on two days with a separation of at least six days. Results Two-way mixed ANOVA was used to analyze the differences in time to complete the sequence between the three trial averages of the two testing sessions. Intraclass Correlation Coefficient (ICC3,1) was used to establish between session test-retest reliability of the test trial averages. Significance was set a priori at p ≤ 0.05. No significant differences (p > 0.05) were detected between the two testing sessions. The ICC was 0.93 with a 95% confidence interval from 0.84 to 0.96. Conclusion This test is a cost-effective, easy to administer and clinically relevant novel measure for assessing dynamic balance that has excellent test-retest reliability. Clinical relevance As a new measure of dynamic balance, the DLBT has the potential to be a cost-effective, challenging and functional tool for clinicians. Level of Evidence 2b PMID:28900556

Intelligent control of a planning system for astronaut training.

PubMed

Ortiz, J; Chen, G

1999-07-01

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

Evaluation of the Pseudostatic Analyses of Earth Dams Using FE Simulation and Observed Earthquake-Induced Deformations: Case Studies of Upper San Fernando and Kitayama Dams

PubMed Central

Akhlaghi, Tohid

2014-01-01

Evaluation of the accuracy of the pseudostatic approach is governed by the accuracy with which the simple pseudostatic inertial forces represent the complex dynamic inertial forces that actually exist in an earthquake. In this study, the Upper San Fernando and Kitayama earth dams, which have been designed using the pseudostatic approach and damaged during the 1971 San Fernando and 1995 Kobe earthquakes, were investigated and analyzed. The finite element models of the dams were prepared based on the detailed available data and results of in situ and laboratory material tests. Dynamic analyses were conducted to simulate the earthquake-induced deformations of the dams using the computer program Plaxis code. Then the pseudostatic seismic coefficient used in the design and analyses of the dams were compared with the seismic coefficients obtained from dynamic analyses of the simulated model as well as the other available proposed pseudostatic correlations. Based on the comparisons made, the accuracy and reliability of the pseudostatic seismic coefficients are evaluated and discussed. PMID:24616636

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data

PubMed Central

Goto, Takahiro; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results. PMID:29337999

How does higher frequency monitoring data affect the calibration of a process-based water quality model?

NASA Astrophysics Data System (ADS)

Jackson-Blake, Leah; Helliwell, Rachel

2015-04-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto-calibrated was lower for the fortnightly data, with a physically unrealistic TDP simulation being produced when too many parameters were allowed to vary during model calibration. Parameters should not therefore be varied spatially for models such as INCA-P unless there is solid evidence that this is appropriate, or there is a real need to do so for the model to fulfil its purpose. This study highlights the potential pitfalls of using low frequency timeseries of observed water quality to calibrate complex process-based models. For reliable model calibrations to be produced, monitoring programmes need to be designed which capture system variability, in particular nutrient dynamics during high flow events. In addition, there is a need for simpler models, so that all model parameters can be included in auto-calibration and uncertainty analysis, and to reduce the data needs during calibration.

Numerical modelling of multiphase multicomponent reactive transport in the Earth's interior

NASA Astrophysics Data System (ADS)

Oliveira, Beñat; Afonso, Juan Carlos; Zlotnik, Sergio; Diez, Pedro

2018-01-01

We present a conceptual and numerical approach to model processes in the Earth's interior that involve multiple phases that simultaneously interact thermally, mechanically and chemically. The approach is truly multiphase in the sense that each dynamic phase is explicitly modelled with an individual set of mass, momentum, energy and chemical mass balance equations coupled via interfacial interaction terms. It is also truly multicomponent in the sense that the compositions of the system and its constituent phases are expressed by a full set of fundamental chemical components (e.g. SiO2, Al2O3, MgO, etc.) rather than proxies. These chemical components evolve, react with and partition into different phases according to an internally consistent thermodynamic model. We combine concepts from Ensemble Averaging and Classical Irreversible Thermodynamics to obtain sets of macroscopic balance equations that describe the evolution of systems governed by multiphase multicomponent reactive transport (MPMCRT). Equilibrium mineral assemblages, their compositions and physical properties, and closure relations for the balance equations are obtained via a `dynamic' Gibbs free-energy minimization procedure (i.e. minimizations are performed on-the-fly as needed by the simulation). Surface tension and surface energy contributions to the dynamics and energetics of the system are taken into account. We show how complex rheologies, that is, visco-elasto-plastic, and/or different interfacial models can be incorporated into our MPMCRT ensemble-averaged formulation. The resulting model provides a reliable platform to study the dynamics and nonlinear feedbacks of MPMCRT systems of different nature and scales, as well as to make realistic comparisons with both geophysical and geochemical data sets. Several numerical examples are presented to illustrate the benefits and limitations of the model.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Complexities’ day-to-day dynamic evolution analysis and prediction for a Didi taxi trip network based on complex network theory

NASA Astrophysics Data System (ADS)

Zhang, Lin; Lu, Jian; Zhou, Jialin; Zhu, Jinqing; Li, Yunxuan; Wan, Qian

2018-03-01

Didi Dache is the most popular taxi order mobile app in China, which provides online taxi-hailing service. The obtained big database from this app could be used to analyze the complexities’ day-to-day dynamic evolution of Didi taxi trip network (DTTN) from the level of complex network dynamics. First, this paper proposes the data cleaning and modeling methods for expressing Nanjing’s DTTN as a complex network. Second, the three consecutive weeks’ data are cleaned to establish 21 DTTNs based on the proposed big data processing technology. Then, multiple topology measures that characterize the complexities’ day-to-day dynamic evolution of these networks are provided. Third, these measures of 21 DTTNs are calculated and subsequently explained with actual implications. They are used as a training set for modeling the BP neural network which is designed for predicting DTTN complexities evolution. Finally, the reliability of the designed BP neural network is verified by comparing with the actual data and the results obtained from ARIMA method simultaneously. Because network complexities are the basis for modeling cascading failures and conducting link prediction in complex system, this proposed research framework not only provides a novel perspective for analyzing DTTN from the level of system aggregated behavior, but can also be used to improve the DTTN management level.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

NASA Astrophysics Data System (ADS)

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-12-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10-3 s-1 to 1 s-1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, Tβ (880 890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above Tβ, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

PubMed Central

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

Abstract This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10−3 s−1 to 1 s−1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region. PMID:29152021

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure.

PubMed

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10 -3  s -1 to 1 s -1 ) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β , continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+ β ) region.

Ecology and Evolution in the RNA World Dynamics and Stability of Prebiotic Replicator Systems.

PubMed

Szilágyi, András; Zachar, István; Scheuring, István; Kun, Ádám; Könnyű, Balázs; Czárán, Tamás

2017-11-27

As of today, the most credible scientific paradigm pertaining to the origin of life on Earth is undoubtedly the RNA World scenario. It is built on the assumption that catalytically active replicators (most probably RNA-like macromolecules) may have been responsible for booting up life almost four billion years ago. The many different incarnations of nucleotide sequence (string) replicator models proposed recently are all attempts to explain on this basis how the genetic information transfer and the functional diversity of prebiotic replicator systems may have emerged, persisted and evolved into the first living cell. We have postulated three necessary conditions for an RNA World model system to be a dynamically feasible representation of prebiotic chemical evolution: (1) it must maintain and transfer a sufficient diversity of information reliably and indefinitely, (2) it must be ecologically stable and (3) it must be evolutionarily stable. In this review, we discuss the best-known prebiotic scenarios and the corresponding models of string-replicator dynamics and assess them against these criteria. We suggest that the most popular of prebiotic replicator systems, the hypercycle, is probably the worst performer in almost all of these respects, whereas a few other model concepts (parabolic replicator, open chaotic flows, stochastic corrector, metabolically coupled replicator system) are promising candidates for development into coherent models that may become experimentally accessible in the future.

Ecology and Evolution in the RNA World Dynamics and Stability of Prebiotic Replicator Systems

PubMed Central

Szilágyi, András; Kun, Ádám; Könnyű, Balázs; Czárán, Tamás

2017-01-01

As of today, the most credible scientific paradigm pertaining to the origin of life on Earth is undoubtedly the RNA World scenario. It is built on the assumption that catalytically active replicators (most probably RNA-like macromolecules) may have been responsible for booting up life almost four billion years ago. The many different incarnations of nucleotide sequence (string) replicator models proposed recently are all attempts to explain on this basis how the genetic information transfer and the functional diversity of prebiotic replicator systems may have emerged, persisted and evolved into the first living cell. We have postulated three necessary conditions for an RNA World model system to be a dynamically feasible representation of prebiotic chemical evolution: (1) it must maintain and transfer a sufficient diversity of information reliably and indefinitely, (2) it must be ecologically stable and (3) it must be evolutionarily stable. In this review, we discuss the best-known prebiotic scenarios and the corresponding models of string-replicator dynamics and assess them against these criteria. We suggest that the most popular of prebiotic replicator systems, the hypercycle, is probably the worst performer in almost all of these respects, whereas a few other model concepts (parabolic replicator, open chaotic flows, stochastic corrector, metabolically coupled replicator system) are promising candidates for development into coherent models that may become experimentally accessible in the future. PMID:29186916

Modeling and Quantification of Team Performance in Human Reliability Analysis for Probabilistic Risk Assessment

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

Jeffrey C. JOe; Ronald L. Boring

Probabilistic Risk Assessment (PRA) and Human Reliability Assessment (HRA) are important technical contributors to the United States (U.S.) Nuclear Regulatory Commission’s (NRC) risk-informed and performance based approach to regulating U.S. commercial nuclear activities. Furthermore, all currently operating commercial NPPs in the U.S. are required by federal regulation to be staffed with crews of operators. Yet, aspects of team performance are underspecified in most HRA methods that are widely used in the nuclear industry. There are a variety of "emergent" team cognition and teamwork errors (e.g., communication errors) that are 1) distinct from individual human errors, and 2) important to understandmore » from a PRA perspective. The lack of robust models or quantification of team performance is an issue that affects the accuracy and validity of HRA methods and models, leading to significant uncertainty in estimating HEPs. This paper describes research that has the objective to model and quantify team dynamics and teamwork within NPP control room crews for risk informed applications, thereby improving the technical basis of HRA, which improves the risk-informed approach the NRC uses to regulate the U.S. commercial nuclear industry.« less

A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve

NASA Astrophysics Data System (ADS)

Yang, Duo; Zhang, Xu; Pan, Rui; Wang, Yujie; Chen, Zonghai

2018-04-01

The state-of-health (SOH) estimation is always a crucial issue for lithium-ion batteries. In order to provide an accurate and reliable SOH estimation, a novel Gaussian process regression (GPR) model based on charging curve is proposed in this paper. Different from other researches where SOH is commonly estimated by cycle life, in this work four specific parameters extracted from charging curves are used as inputs of the GPR model instead of cycle numbers. These parameters can reflect the battery aging phenomenon from different angles. The grey relational analysis method is applied to analyze the relational grade between selected features and SOH. On the other hand, some adjustments are made in the proposed GPR model. Covariance function design and the similarity measurement of input variables are modified so as to improve the SOH estimate accuracy and adapt to the case of multidimensional input. Several aging data from NASA data repository are used for demonstrating the estimation effect by the proposed method. Results show that the proposed method has high SOH estimation accuracy. Besides, a battery with dynamic discharging profile is used to verify the robustness and reliability of this method.

Conformational Spread in the Flagellar Motor Switch: A Model Study

PubMed Central

Maini, Philip K.; Berry, Richard M.; Bai, Fan

2012-01-01

The reliable response to weak biological signals requires that they be amplified with fidelity. In E. coli, the flagellar motors that control swimming can switch direction in response to very small changes in the concentration of the signaling protein CheY-P, but how this works is not well understood. A recently proposed allosteric model based on cooperative conformational spread in a ring of identical protomers seems promising as it is able to qualitatively reproduce switching, locked state behavior and Hill coefficient values measured for the rotary motor. In this paper we undertook a comprehensive simulation study to analyze the behavior of this model in detail and made predictions on three experimentally observable quantities: switch time distribution, locked state interval distribution, Hill coefficient of the switch response. We parameterized the model using experimental measurements, finding excellent agreement with published data on motor behavior. Analysis of the simulated switching dynamics revealed a mechanism for chemotactic ultrasensitivity, in which cooperativity is indispensable for realizing both coherent switching and effective amplification. These results showed how cells can combine elements of analog and digital control to produce switches that are simultaneously sensitive and reliable. PMID:22654654

Stress and reliability analyses of multilayered composite cylinder under thermal and mechanical loads

NASA Astrophysics Data System (ADS)

Wang, Xiaohua

The coupling resulting from the mutual influence of material thermal and mechanical parameters is examined in the thermal stress analysis of a multilayered isotropic composite cylinder subjected to sudden axisymmetric external and internal temperature. The method of complex frequency response functions together with the Fourier transform technique is utilized. Because the coupling parameters for some composite materials, such as carbon-carbon, are very small, the effect of coupling is neglected in the orthotropic thermal stress analysis. The stress distributions in multilayered orthotropic cylinders subjected to sudden axisymmetric temperature loading combined with dynamic pressure as well as asymmetric temperature loading are also obtained. The method of Fourier series together with the Laplace transform is utilized in solving the heat conduction equation and thermal stress analysis. For brittle materials, like carbon-carbon composites, the strength variability is represented by two or three parameter Weibull distributions. The 'weakest link' principle which takes into account both the carbon-carbon composite cylinders. The complex frequency response analysis is performed on a multilayered orthotropic cylinder under asymmetrical thermal load. Both deterministic and random thermal stress and reliability analyses can be based on the results of this frequency response analysis. The stress and displacement distributions and reliability of rocket motors under static or dynamic line loads are analyzed by an elasticity approach. Rocket motors are modeled as long hollow multilayered cylinders with an air core, a thick isotropic propellant inner layer and a thin orthotropic kevlar-epoxy case. The case is treated as a single orthotropic layer or a ten layered orthotropic structure. Five material properties and the load are treated as random variable with normal distributions when the reliability of the rocket motor is analyzed by the first-order, second-moment method (FOSM).

Preventing chatter vibrations in heavy-duty turning operations in large horizontal lathes

NASA Astrophysics Data System (ADS)

Urbikain, G.; Campa, F.-J.; Zulaika, J.-J.; López de Lacalle, L.-N.; Alonso, M.-A.; Collado, V.

2015-03-01

Productivity and surface finish are typical user manufacturer requirements that are restrained by chatter vibrations sooner or later in every machining operation. Thus, manufacturers are interested in knowing, before building the machine, the dynamic behaviour of each machine structure with respect to another. Stability lobe graphs are the most reliable approach to analyse the dynamic performance. During heavy rough turning operations a model containing (a) several modes, or (b) modes with non-conventional (Cartesian) orientations is necessary. This work proposes two methods which are combined with multimode analysis to predict chatter in big horizontal lathes. First, a traditional single frequency model (SFM) is used. Secondly, the modern collocation method based on the Chebyshev polynomials (CCM) is alternatively studied. The models can be used to identify the machine design features limiting lathe productivity, as well as the threshold values for choosing good cutting parameters. The results have been compared with experimental tests in a horizontal turning centre. Besides the model and approach, this work offers real worthy values for big lathes, difficult to be got from literature.

Analytical and molecular dynamics studies on the impact loading of single-layered graphene sheet by fullerene

NASA Astrophysics Data System (ADS)

Hosseini-Hashemi, Shahrokh; Sepahi-Boroujeni, Amin; Sepahi-Boroujeni, Saeid

2018-04-01

Normal impact performance of a system including a fullerene molecule and a single-layered graphene sheet is studied in the present paper. Firstly, through a mathematical approach, a new contact law is derived to describe the overall non-bonding interaction forces of the "hollow indenter-target" system. Preliminary verifications show that the derived contact law gives a reliable picture of force field of the system which is in good agreements with the results of molecular dynamics (MD) simulations. Afterwards, equation of the transversal motion of graphene sheet is utilized on the basis of both the nonlocal theory of elasticity and the assumptions of classical plate theory. Then, to derive dynamic behavior of the system, a set including the proposed contact law and the equations of motion of both graphene sheet and fullerene molecule is solved numerically. In order to evaluate outcomes of this method, the problem is modeled by MD simulation. Despite intrinsic differences between analytical and MD methods as well as various errors arise due to transient nature of the problem, acceptable agreements are established between analytical and MD outcomes. As a result, the proposed analytical method can be reliably used to address similar impact problems. Furthermore, it is found that a single-layered graphene sheet is capable of trapping fullerenes approaching with low velocities. Otherwise, in case of rebound, the sheet effectively absorbs predominant portion of fullerene energy.

Response statistics of rotating shaft with non-linear elastic restoring forces by path integration

NASA Astrophysics Data System (ADS)

Gaidai, Oleg; Naess, Arvid; Dimentberg, Michael

2017-07-01

Extreme statistics of random vibrations is studied for a Jeffcott rotor under uniaxial white noise excitation. Restoring force is modelled as elastic non-linear; comparison is done with linearized restoring force to see the force non-linearity effect on the response statistics. While for the linear model analytical solutions and stability conditions are available, it is not generally the case for non-linear system except for some special cases. The statistics of non-linear case is studied by applying path integration (PI) method, which is based on the Markov property of the coupled dynamic system. The Jeffcott rotor response statistics can be obtained by solving the Fokker-Planck (FP) equation of the 4D dynamic system. An efficient implementation of PI algorithm is applied, namely fast Fourier transform (FFT) is used to simulate dynamic system additive noise. The latter allows significantly reduce computational time, compared to the classical PI. Excitation is modelled as Gaussian white noise, however any kind distributed white noise can be implemented with the same PI technique. Also multidirectional Markov noise can be modelled with PI in the same way as unidirectional. PI is accelerated by using Monte Carlo (MC) estimated joint probability density function (PDF) as initial input. Symmetry of dynamic system was utilized to afford higher mesh resolution. Both internal (rotating) and external damping are included in mechanical model of the rotor. The main advantage of using PI rather than MC is that PI offers high accuracy in the probability distribution tail. The latter is of critical importance for e.g. extreme value statistics, system reliability, and first passage probability.

Autonomous Robot Navigation in Human-Centered Environments Based on 3D Data Fusion

NASA Astrophysics Data System (ADS)

Steinhaus, Peter; Strand, Marcus; Dillmann, Rüdiger

2007-12-01

Efficient navigation of mobile platforms in dynamic human-centered environments is still an open research topic. We have already proposed an architecture (MEPHISTO) for a navigation system that is able to fulfill the main requirements of efficient navigation: fast and reliable sensor processing, extensive global world modeling, and distributed path planning. Our architecture uses a distributed system of sensor processing, world modeling, and path planning units. In this arcticle, we present implemented methods in the context of data fusion algorithms for 3D world modeling and real-time path planning. We also show results of the prototypic application of the system at the museum ZKM (center for art and media) in Karlsruhe.

Transonic Blunt Body Aerodynamic Coefficients Computation

NASA Astrophysics Data System (ADS)

Sancho, Jorge; Vargas, M.; Gonzalez, Ezequiel; Rodriguez, Manuel

2011-05-01

In the framework of EXPERT (European Experimental Re-entry Test-bed) accurate transonic aerodynamic coefficients are of paramount importance for the correct trajectory assessment and parachute deployment. A combined CFD (Computational Fluid Dynamics) modelling and experimental campaign strategy was selected to obtain accurate coefficients. A preliminary set of coefficients were obtained by CFD Euler inviscid computation. Then experimental campaign was performed at DNW facilities at NLR. A profound review of the CFD modelling was done lighten up by WTT results, aimed to obtain reliable values of the coefficients in the future (specially the pitching moment). Study includes different turbulence modelling and mesh sensitivity analysis. Comparison with the WTT results is explored, and lessons learnt are collected.

Building Reliable Forecasts of Solar Activity

NASA Technical Reports Server (NTRS)

Kitiashvili, Irina; Wray, Alan; Mansour, Nagi

2017-01-01

Solar ionizing radiation critically depends on the level of the Sun’s magnetic activity. For robust physics-based forecasts, we employ the procedure of data assimilation, which combines theoretical modeling and observational data such that uncertainties in both the model and the observations are taken into account. Currently we are working in two major directions: 1) development of a new long-term forecast procedure on time-scales of the 11-year solar cycle, using a 2-dimensional mean-field dynamo model and synoptic magnetograms; 2) development of 3-dimensional radiative MHD (Magnetohydrodynamic) simulations to investigate the origin and precursors of local manifestations of magnetic activity, such as the formation of magnetic structures and eruptive dynamics.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

Atmospheric Spray Freeze-Drying: Numerical Modeling and Comparison With Experimental Measurements.

PubMed

Borges Sebastião, Israel; Robinson, Thomas D; Alexeenko, Alina

2017-01-01

Atmospheric spray freeze-drying (ASFD) represents a novel approach to dry thermosensitive solutions via sublimation. Tests conducted with a second-generation ASFD equipment, developed for pharmaceutical applications, have focused initially on producing a light, fine, high-grade powder consistently and reliably. To better understand the heat and mass transfer physics and drying dynamics taking place within the ASFD chamber, 3 analytical models describing the key processes are developed and validated. First, by coupling the dynamics and heat transfer of single droplets sprayed into the chamber, the velocity, temperature, and phase change evolutions of these droplets are estimated for actual operational conditions. This model reveals that, under typical operational conditions, the sprayed droplets require less than 100 ms to freeze. Second, because understanding the heat transfer throughout the entire freeze-drying process is so important, a theoretical model is proposed to predict the time evolution of the chamber gas temperature. Finally, a drying model, calibrated with hygrometer measurements, is used to estimate the total time required to achieve a predefined final moisture content. Results from these models are compared with experimental data. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

[Mass Transfer Kinetics Model of Ultrasonic Extraction of Pomegranate Peel Polyphenols].

PubMed

Wang, Zhan-yi; Zhang, Li-hua; Wang, Yu-hai; Zhang, Yuan-hu; Ma, Li; Zheng, Dan-dan

2015-05-01

The dynamic mathematical model of ultrasonic extraction of polyphenols from pomegranate peel was constructed with the Fick's second law as the theoretical basis. The spherical model was selected, with mass concentrations of pomegranate peel polyphenols as the index, 50% ethanol as the extraction solvent and ultrasonic extraction as the extraction method. In different test conditions including the liquid ratio, extraction temperature and extraction time, a series of kinetic parameters were solved, such as the extraction process (k), relative raffinate rate, surface diffusion coefficient(D(S)), half life (t½) and the apparent activation energy (E(a)). With the extraction temperature increasing, k and D(S) were gradually increased with t½ decreasing,which indicated that the elevated temperature was favorable to the extraction of pomegranate peel polyphenols. The exponential equation of relative raffinate rate showed that the established numerical dynamics model fitted the extraction of pomegranate peel polyphenols, and the relationship between the reaction conditions and pomegranate peel polyphenols concentration was well reflected by the model. Based on the experimental results, a feasible and reliable kinetic model for ultrasonic extraction of polyphenols from pomegranate peel is established, which can be used for the optimization control of engineering magnifying production.