Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

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

Huang, Renke; Jin, Shuangshuang; Chen, Yousu

This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

A new rate-dependent model for high-frequency tracking performance enhancement of piezoactuator system

NASA Astrophysics Data System (ADS)

Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

2017-05-01

Feedforward-feedback control is widely used in motion control of piezoactuator systems. Due to the phase lag caused by incomplete dynamics compensation, the performance of the composite controller is greatly limited at high frequency. This paper proposes a new rate-dependent model to improve the high-frequency tracking performance by reducing dynamics compensation error. The rate-dependent model is designed as a function of the input and input variation rate to describe the input-output relationship of the residual system dynamics which mainly performs as phase lag in a wide frequency band. Then the direct inversion of the proposed rate-dependent model is used to compensate the residual system dynamics. Using the proposed rate-dependent model as feedforward term, the open loop performance can be improved significantly at medium-high frequency. Then, combining the with feedback controller, the composite controller can provide enhanced close loop performance from low frequency to high frequency. At the frequency of 1 Hz, the proposed controller presents the same performance as previous methods. However, at the frequency of 900 Hz, the tracking error is reduced to be 30.7% of the decoupled approach.

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

NASA Astrophysics Data System (ADS)

Nash, C. J.; Cole, D. J.

2018-05-01

A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

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.

Multi-Topic Tracking Model for dynamic social network

NASA Astrophysics Data System (ADS)

Li, Yuhua; Liu, Changzheng; Zhao, Ming; Li, Ruixuan; Xiao, Hailing; Wang, Kai; Zhang, Jun

2016-07-01

The topic tracking problem has attracted much attention in the last decades. However, existing approaches rarely consider network structures and textual topics together. In this paper, we propose a novel statistical model based on dynamic bayesian network, namely Multi-Topic Tracking Model for Dynamic Social Network (MTTD). It takes influence phenomenon, selection phenomenon, document generative process and the evolution of textual topics into account. Specifically, in our MTTD model, Gibbs Random Field is defined to model the influence of historical status of users in the network and the interdependency between them in order to consider the influence phenomenon. To address the selection phenomenon, a stochastic block model is used to model the link generation process based on the users' interests to topics. Probabilistic Latent Semantic Analysis (PLSA) is used to describe the document generative process according to the users' interests. Finally, the dependence on the historical topic status is also considered to ensure the continuity of the topic itself in topic evolution model. Expectation Maximization (EM) algorithm is utilized to estimate parameters in the proposed MTTD model. Empirical experiments on real datasets show that the MTTD model performs better than Popular Event Tracking (PET) and Dynamic Topic Model (DTM) in generalization performance, topic interpretability performance, topic content evolution and topic popularity evolution performance.

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network based adaptive controller. While the fixed RBF network based controller which is tuned to compensate for control surface failures fails to achieve the same performance under modeling uncertainty and disturbances, the SORBFN is able to achieve good tracking convergence under all error conditions.

Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments

PubMed Central

Eisenhauer, Philipp; Heckman, James J.; Mosso, Stefano

2015-01-01

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic dataset and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM. PMID:26494926

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.

Control Performance, Aerodynamic Modeling, and Validation of Coupled Simulation Techniques for Guided Projectile Roll Dynamics

DTIC Science & Technology

2014-11-01

39–44) has been explored in depth in the literature. Of particular interest for this study are investigations into roll control. Isolating the...Control Performance, Aerodynamic Modeling, and Validation of Coupled Simulation Techniques for Guided Projectile Roll Dynamics by Jubaraj...Simulation Techniques for Guided Projectile Roll Dynamics Jubaraj Sahu, Frank Fresconi, and Karen R. Heavey Weapons and Materials Research

Effect of motor dynamics on nonlinear feedback robot arm control

NASA Technical Reports Server (NTRS)

Tarn, Tzyh-Jong; Li, Zuofeng; Bejczy, Antal K.; Yun, Xiaoping

1991-01-01

A nonlinear feedback robot controller that incorporates the robot manipulator dynamics and the robot joint motor dynamics is proposed. The manipulator dynamics and the motor dynamics are coupled to obtain a third-order-dynamic model, and differential geometric control theory is applied to produce a linearized and decoupled robot controller. The derived robot controller operates in the robot task space, thus eliminating the need for decomposition of motion commands into robot joint space commands. Computer simulations are performed to verify the feasibility of the proposed robot controller. The controller is further experimentally evaluated on the PUMA 560 robot arm. The experiments show that the proposed controller produces good trajectory tracking performances and is robust in the presence of model inaccuracies. Compared with a nonlinear feedback robot controller based on the manipulator dynamics only, the proposed robot controller yields conspicuously improved performance.

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Development and Integration of Control System Models

NASA Technical Reports Server (NTRS)

Kim, Young K.

1998-01-01

The computer simulation tool, TREETOPS, has been upgraded and used at NASA/MSFC to model various complicated mechanical systems and to perform their dynamics and control analysis with pointing control systems. A TREETOPS model of Advanced X-ray Astrophysics Facility - Imaging (AXAF-1) dynamics and control system was developed to evaluate the AXAF-I pointing performance for Normal Pointing Mode. An optical model of Shooting Star Experiment (SSE) was also developed and its optical performance analysis was done using the MACOS software.

Formation of an internal model of environment dynamics during upper limb reaching movements: a fuzzy approach.

PubMed

MacDonald, Chad; Moussavi, Zahra; Sarkodie-Gyan, Thompson

2007-01-01

This paper presents the development and simulation of a fuzzy logic based learning mechanism to emulate human motor learning. In particular, fuzzy inference was used to develop an internal model of a novel dynamic environment experienced during planar reaching movements with the upper limb. A dynamic model of the human arm was developed and a fuzzy if-then rule base was created to relate trajectory movement and velocity errors to internal model update parameters. An experimental simulation was performed to compare the fuzzy system's performance with that of human subjects. It was found that the dynamic model behaved as expected, and the fuzzy learning mechanism created an internal model that was capable of opposing the environmental force field to regain a trajectory closely resembling the desired ideal.

A modeling of dynamic storage assignment for order picking in beverage warehousing with Drive-in Rack system

NASA Astrophysics Data System (ADS)

Hadi, M. Z.; Djatna, T.; Sugiarto

2018-04-01

This paper develops a dynamic storage assignment model to solve storage assignment problem (SAP) for beverages order picking in a drive-in rack warehousing system to determine the appropriate storage location and space for each beverage products dynamically so that the performance of the system can be improved. This study constructs a graph model to represent drive-in rack storage position then combine association rules mining, class-based storage policies and an arrangement rule algorithm to determine an appropriate storage location and arrangement of the product according to dynamic orders from customers. The performance of the proposed model is measured as rule adjacency accuracy, travel distance (for picking process) and probability a product become expiry using Last Come First Serve (LCFS) queue approach. Finally, the proposed model is implemented through computer simulation and compare the performance for different storage assignment methods as well. The result indicates that the proposed model outperforms other storage assignment methods.

Dynamics Modelling of Biolistic Gene Guns

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

Zhang, M.; Tao, W.; Pianetta, P.A.

2009-06-04

The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model formore » improving and manipulating performance of the biolistic gene gun.« less

Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.

EPA Science Inventory

Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...

Analysis of Rail Transit Vehicle Dynamic Curving Performance

DOT National Transportation Integrated Search

1984-06-01

An analytical model is developed for determining the dynamic curving performance of rail transit vehicles. The dynamic wheel/rail interaction forces, vehicle suspension and body motions and track displacement are computed, as well as wheel and rail w...

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

NASA Astrophysics Data System (ADS)

Arabi, Ehsan; Gruenwald, Benjamin C.; Yucelen, Tansel; Nguyen, Nhan T.

2018-05-01

Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Modeling and simulation of continuous wave velocity radar based on third-order DPLL

NASA Astrophysics Data System (ADS)

Di, Yan; Zhu, Chen; Hong, Ma

2015-02-01

Second-order digital phase-locked-loop (DPLL) is widely used in traditional Continuous wave (CW) velocity radar with poor performance in high dynamic conditions. Using the third-order DPLL can improve the performance. Firstly, the echo signal model of CW radar is given. Secondly, theoretical derivations of the tracking performance in different velocity conditions are given. Finally, simulation model of CW radar is established based on Simulink tool. Tracking performance of the two kinds of DPLL in different acceleration and jerk conditions is studied by this model. The results show that third-order PLL has better performance in high dynamic conditions. This model provides a platform for further research of CW radar.

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Study on dynamic performance of SOFC

NASA Astrophysics Data System (ADS)

Zhan, Haiyang; Liang, Qianchao; Wen, Qiang; Zhu, Runkai

2017-05-01

In order to solve the problem of real-time matching of load and fuel cell power, it is urgent to study the dynamic response process of SOFC in the case of load mutation. The mathematical model of SOFC is constructed, and its performance is simulated. The model consider the influence factors such as polarization effect, ohmic loss. It also takes the diffusion effect, thermal effect, energy exchange, mass conservation, momentum conservation. One dimensional dynamic mathematical model of SOFC is constructed by using distributed lumped parameter method. The simulation results show that the I-V characteristic curves are in good agreement with the experimental data, and the accuracy of the model is verified. The voltage response curve, power response curve and the efficiency curve are obtained by this way. It lays a solid foundation for the research of dynamic performance and optimal control in power generation system of high power fuel cell stack.

Design and performance characterization strategy using modeling for biofiltration control of odorous hydrogen sulfide.

PubMed

Martin, Ronald W; Mihelcic, James R; Crittenden, John C

2004-07-01

Biofilter, dynamic modeling software characterizing contaminant removal via biofiltration, was used in the preliminary design of a biofilter to treat odorous hydrogen sulfide (H2S). Steady-state model simulations were run to generate performance plots for various influent concentrations, loadings, residence times, media sizes, and temperatures. Although elimination capacity and removal efficiency frequently are used to characterize biofilter performance, effluent concentration can be used to characterize performance when treating to a target effluent concentration. Model simulations illustrate that, at a given temperature, a biofilter cannot reduce H2S emissions below a minimum value, no matter how large the biofilter or how long the residence time. However, a higher biofilter temperature results in lower effluent H2S concentrations. Because dynamic model simulations show that shock loading can significantly increase the effluent concentration above values predicted by the steady-state model simulations, it is recommended that, to consistently meet treatment objectives, dynamic feed conditions should be considered. This study illustrates that modeling can serve as a valuable tool in the design and performance optimization of biofilters.

Prediction of Cognitive Performance and Subjective Sleepiness Using a Model of Arousal Dynamics.

PubMed

Postnova, Svetlana; Lockley, Steven W; Robinson, Peter A

2018-04-01

A model of arousal dynamics is applied to predict objective performance and subjective sleepiness measures, including lapses and reaction time on a visual Performance Vigilance Test (vPVT), performance on a mathematical addition task (ADD), and the Karolinska Sleepiness Scale (KSS). The arousal dynamics model is comprised of a physiologically based flip-flop switch between the wake- and sleep-active neuronal populations and a dynamic circadian oscillator, thus allowing prediction of sleep propensity. Published group-level experimental constant routine (CR) and forced desynchrony (FD) data are used to calibrate the model to predict performance and sleepiness. Only the studies using dim light (<15 lux) during alertness measurements and controlling for sleep and entrainment before the start of the protocol are selected for modeling. This is done to avoid the direct alerting effects of light and effects of prior sleep debt and circadian misalignment on the data. The results show that linear combination of circadian and homeostatic drives is sufficient to predict dynamics of a variety of sleepiness and performance measures during CR and FD protocols, with sleep-wake cycles ranging from 20 to 42.85 h and a 2:1 wake-to-sleep ratio. New metrics relating model outputs to performance and sleepiness data are developed and tested against group average outcomes from 7 (vPVT lapses), 5 (ADD), and 8 (KSS) experimental protocols, showing good quantitative and qualitative agreement with the data (root mean squared error of 0.38, 0.19, and 0.35, respectively). The weights of the homeostatic and circadian effects are found to be different between the measures, with KSS having stronger homeostatic influence compared with the objective measures of performance. Using FD data in addition to CR data allows us to challenge the model in conditions of both acute sleep deprivation and structured circadian misalignment, ensuring that the role of the circadian and homeostatic drives in performance is properly captured.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

PubMed Central

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

PubMed

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

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

PubMed

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

2018-02-01

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

Predicting Student Academic Performance in an Engineering Dynamics Course: A Comparison of Four Types of Predictive Mathematical Models

ERIC Educational Resources Information Center

Huang, Shaobo; Fang, Ning

2013-01-01

Predicting student academic performance has long been an important research topic in many academic disciplines. The present study is the first study that develops and compares four types of mathematical models to predict student academic performance in engineering dynamics--a high-enrollment, high-impact, and core course that many engineering…

The effects of a dynamic graphical model during simulation-based training of console operation skill

NASA Technical Reports Server (NTRS)

Farquhar, John D.; Regian, J. Wesley

1993-01-01

LOADER is a Windows-based simulation of a complex procedural task. The task requires subjects to execute long sequences of console-operation actions (e.g., button presses, switch actuations, dial rotations) to accomplish specific goals. The LOADER interface is a graphical computer-simulated console which controls railroad cars, tracks, and cranes in a fictitious railroad yard. We hypothesized that acquisition of LOADER performance skill would be supported by the representation of a dynamic graphical model linking console actions to goal and goal states in the 'railroad yard'. Twenty-nine subjects were randomly assigned to one of two treatments (i.e., dynamic model or no model). During training, both groups received identical text-based instruction in an instructional-window above the LOADER interface. One group, however, additionally saw a dynamic version of the bird's-eye view of the railroad yard. After training, both groups were tested under identical conditions. They were asked to perform the complete procedure without guidance and without access to either type of railroad yard representation. Results indicate that rather than becoming dependent on the animated rail yard model, subjects in the dynamic model condition apparently internalized the model, as evidenced by their performance after the model was removed.

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

Dynamic and Structural Gas Turbine Engine Modeling

NASA Technical Reports Server (NTRS)

Turso, James A.

2003-01-01

Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.

Design and performance evaluation of a simplified dynamic model for combined sewer overflows in pumped sewer systems

NASA Astrophysics Data System (ADS)

van Daal-Rombouts, Petra; Sun, Siao; Langeveld, Jeroen; Bertrand-Krajewski, Jean-Luc; Clemens, François

2016-07-01

Optimisation or real time control (RTC) studies in wastewater systems increasingly require rapid simulations of sewer systems in extensive catchments. To reduce the simulation time calibrated simplified models are applied, with the performance generally based on the goodness of fit of the calibration. In this research the performance of three simplified and a full hydrodynamic (FH) model for two catchments are compared based on the correct determination of CSO event occurrences and of the total discharged volumes to the surface water. Simplified model M1 consists of a rainfall runoff outflow (RRO) model only. M2 combines the RRO model with a static reservoir model for the sewer behaviour. M3 comprises the RRO model and a dynamic reservoir model. The dynamic reservoir characteristics were derived from FH model simulations. It was found that M2 and M3 are able to describe the sewer behaviour of the catchments, contrary to M1. The preferred model structure depends on the quality of the information (geometrical database and monitoring data) available for the design and calibration of the model. Finally, calibrated simplified models are shown to be preferable to uncalibrated FH models when performing optimisation or RTC studies.

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.

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.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

PubMed

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Palm: Easing the Burden of Analytical Performance Modeling

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

Tallent, Nathan R.; Hoisie, Adolfy

2014-06-01

Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexitymore » (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.« less

OISI dynamic end-to-end modeling tool

NASA Astrophysics Data System (ADS)

Kersten, Michael; Weidler, Alexander; Wilhelm, Rainer; Johann, Ulrich A.; Szerdahelyi, Laszlo

2000-07-01

The OISI Dynamic end-to-end modeling tool is tailored to end-to-end modeling and dynamic simulation of Earth- and space-based actively controlled optical instruments such as e.g. optical stellar interferometers. `End-to-end modeling' is meant to denote the feature that the overall model comprises besides optical sub-models also structural, sensor, actuator, controller and disturbance sub-models influencing the optical transmission, so that the system- level instrument performance due to disturbances and active optics can be simulated. This tool has been developed to support performance analysis and prediction as well as control loop design and fine-tuning for OISI, Germany's preparatory program for optical/infrared spaceborne interferometry initiated in 1994 by Dornier Satellitensysteme GmbH in Friedrichshafen.

Effect of Bearing Housings on Centrifugal Pump Rotor Dynamics

NASA Astrophysics Data System (ADS)

Yashchenko, A. S.; Rudenko, A. A.; Simonovskiy, V. I.; Kozlov, O. M.

2017-08-01

The article deals with the effect of a bearing housing on rotor dynamics of a barrel casing centrifugal boiler feed pump rotor. The calculation of the rotor model including the bearing housing has been performed by the method of initial parameters. The calculation of a rotor solid model including the bearing housing has been performed by the finite element method. Results of both calculations highlight the need to add bearing housings into dynamic analyses of the pump rotor. The calculation performed by modern software packages is more a time-taking process, at the same time it is a preferred one due to a graphic editor that is employed for creating a numerical model. When it is necessary to view many variants of design parameters, programs for beam modeling should be used.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter

2010-01-01

Under the NASA Fundamental Aeronautics Program the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero-Propulso-Servo-Elastic model and for propulsion efficiency studies.

Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter

2008-01-01

Under the NASA Fundamental Aeronautics Program, the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero-Propulso-Servo-Elastic model and for propulsion efficiency studies.

Volume Dynamics Propulsion System Modeling for Supersonics Vehicle Research

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Ma, Peter

2008-01-01

Under the NASA Fundamental Aeronautics Program the Supersonics Project is working to overcome the obstacles to supersonic commercial flight. The proposed vehicles are long slim body aircraft with pronounced aero-servo-elastic modes. These modes can potentially couple with propulsion system dynamics; leading to performance challenges such as aircraft ride quality and stability. Other disturbances upstream of the engine generated from atmospheric wind gusts, angle of attack, and yaw can have similar effects. In addition, for optimal propulsion system performance, normal inlet-engine operations are required to be closer to compressor stall and inlet unstart. To study these phenomena an integrated model is needed that includes both airframe structural dynamics as well as the propulsion system dynamics. This paper covers the propulsion system component volume dynamics modeling of a turbojet engine that will be used for an integrated vehicle Aero- Propulso-Servo-Elastic model and for propulsion efficiency studies.

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.

A Stewart isolator with high-static-low-dynamic stiffness struts based on negative stiffness magnetic springs

NASA Astrophysics Data System (ADS)

Zheng, Yisheng; Li, Qingpin; Yan, Bo; Luo, Yajun; Zhang, Xinong

2018-05-01

In order to improve the isolation performance of passive Stewart platforms, the negative stiffness magnetic spring (NSMS) is employed to construct high static low dynamic stiffness (HSLDS) struts. With the NSMS, the resonance frequencies of the platform can be reduced effectively without deteriorating its load bearing capacity. The model of the Stewart isolation platform with HSLDS struts is presented and the stiffness characteristic of its struts is studied firstly. Then the nonlinear dynamic model of the platform including both geometry nonlinearity and stiffness nonlinearity is established; and its simplified dynamic model is derived under the condition of small vibration. The effect of nonlinearity on the isolation performance is also evaluated. Finally, a prototype is built and the isolation performance is tested. Both simulated and experimental results demonstrate that, by using the NSMS, the resonance frequencies of the Stewart isolator are reduced and the isolation performance in all six directions is improved: the isolation frequency band is increased and extended to a lower-frequency level.

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.

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.

A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

PubMed

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

2018-01-15

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

Dynamic CFD Simulations of the Supersonic Inflatable Aerodynamic Decelerator (SIAD) Ballistic Range Tests

NASA Technical Reports Server (NTRS)

Brock, Joseph M; Stern, Eric

2016-01-01

Dynamic CFD simulations of the SIAD ballistic test model were performed using US3D flow solver. Motivation for performing these simulations is for the purpose of validation and verification of the US3D flow solver as a viable computational tool for predicting dynamic coefficients.

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

NASA Astrophysics Data System (ADS)

Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

2018-02-01

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower troposphere mass flux show good results in particular in the Northern Hemisphere. In the Southern Hemisphere, the model tends to produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation. We discuss possible reasons for these model biases as well as planned future model improvements and applications.

Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles

NASA Astrophysics Data System (ADS)

Wilcox, Zachary Donald

The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed controller is then applied to a HSV model, and a Lyapunov analysis is used to prove global exponential reference model tracking in the presence of uncertainty in the state and input matrices and exogenous disturbances. Simulations with a spectrum of gains and temperature profiles on the full nonlinear dynamic model of the HSV is used to illustrate the performance and robustness of the developed controller. In addition, this work considers how the performance of the developed controller varies over a wide variety of control gains and temperature profiles and are optimized with respect to different performance metrics. Specifically, various temperature profile models and related nonlinear temperature dependent disturbances are used to characterize the relative control performance and effort for each model. Examining such metrics as a function of temperature provides a potential inroad to examine the interplay between structural/thermal protection design and control development and has application for future HSV design and control implementation.

Specialized data analysis of SSME and advanced propulsion system vibration measurements

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Swanson, Wayne L.; Jong, Yen-Yi

1993-01-01

The basic objectives of this contract were to perform detailed analysis and evaluation of dynamic data obtained during Space Shuttle Main Engine (SSME) test and flight operations, including analytical/statistical assessment of component dynamic performance, and to continue the development and implementation of analytical/statistical models to effectively define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational conditions. This study was to provide timely assessment of engine component operational status, identify probable causes of malfunction, and define feasible engineering solutions. The work was performed under three broad tasks: (1) Analysis, Evaluation, and Documentation of SSME Dynamic Test Results; (2) Data Base and Analytical Model Development and Application; and (3) Development and Application of Vibration Signature Analysis Techniques.

Modeling of dielectric elastomer as electromechanical resonator

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

Li, Bo, E-mail: liboxjtu@mail.xjtu.edu.cn; Liu, Lei; Chen, Hualing

Dielectric elastomers (DEs) feature nonlinear dynamics resulting from an electromechanical coupling. Under alternating voltage, the DE resonates with tunable performances. We present an analysis of the nonlinear dynamics of a DE as electromechanical resonator (DEER) configured as a pure shear actuator. A theoretical model is developed to characterize the complex performance under different boundary conditions. Physical mechanisms are presented and discussed. Chaotic behavior is also predicted, illustrating instabilities in the dynamics. The results provide a guide to the design and application of DEER in haptic devices.

Dynamic Simulation of AN Helium Refrigerator

NASA Astrophysics Data System (ADS)

Deschildre, C.; Barraud, A.; Bonnay, P.; Briend, P.; Girard, A.; Poncet, J. M.; Roussel, P.; Sequeira, S. E.

2008-03-01

A dynamic simulation of a large scale existing refrigerator has been performed using the software Aspen Hysys®. The model comprises the typical equipments of a cryogenic system: heat exchangers, expanders, helium phase separators and cold compressors. It represents the 400 W @ 1.8 K Test Facility located at CEA—Grenoble. This paper describes the model development and shows the possibilities and limitations of the dynamic module of Aspen Hysys®. Then, comparison between simulation results and experimental data are presented; the simulation of cooldown process was also performed.

Output feedback regulator design for jet engine control systems

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1977-01-01

A multivariable control design procedure based on the output feedback regulator formulation is described and applied to turbofan engine model. Full order model dynamics, were incorporated in the example design. The effect of actuator dynamics on closed loop performance was investigaged. Also, the importance of turbine inlet temperature as an element of the dynamic feedback was studied. Step responses were given to indicate the improvement in system performance with this control. Calculation times for all experiments are given in CPU seconds for comparison purposes.

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

Space Suit Thermal Dynamics

NASA Technical Reports Server (NTRS)

Campbell, Anthony B.; Nair, Satish S.; Miles, John B.; Iovine, John V.; Lin, Chin H.

1998-01-01

The present NASA space suit (the Shuttle EMU) is a self-contained environmental control system, providing life support, environmental protection, earth-like mobility, and communications. This study considers the thermal dynamics of the space suit as they relate to astronaut thermal comfort control. A detailed dynamic lumped capacitance thermal model of the present space suit is used to analyze the thermal dynamics of the suit with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The observations from this study are being utilized in two future design efforts, automatic thermal comfort control design for the present space suit and design of future space suit systems for Space Station, Lunar, and Martian missions.

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

PubMed Central

Ayton, Ellyn; Porterfield, Katherine; Corley, Courtney D.

2017-01-01

This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data and the state-of-the-art machine learning models, we build and evaluate the predictive power of neural network architectures based on Long Short Term Memory (LSTMs) units capable of nowcasting (predicting in “real-time”) and forecasting (predicting the future) ILI dynamics in the 2011 – 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, embeddings, word ngrams, stylistic patterns, and communication behavior using hashtags and mentions. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks using a diverse set of evaluation metrics. Finally, we combine ILI and social media signals to build a joint neural network model for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance, specifically for military rather than general populations in 26 U.S. and six international locations., and analyze how model performance depends on the amount of social media data available per location. Our approach demonstrates several advantages: (a) Neural network architectures that rely on LSTM units trained on social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than stylistic and topic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns. (g) Model performance improves with more tweets available per geo-location e.g., the error gets lower and the Pearson score gets higher for locations with more tweets. PMID:29244814

Forecasting influenza-like illness dynamics for military populations using neural networks and social media.

PubMed

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine; Corley, Courtney D

2017-01-01

This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data and the state-of-the-art machine learning models, we build and evaluate the predictive power of neural network architectures based on Long Short Term Memory (LSTMs) units capable of nowcasting (predicting in "real-time") and forecasting (predicting the future) ILI dynamics in the 2011 - 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, embeddings, word ngrams, stylistic patterns, and communication behavior using hashtags and mentions. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks using a diverse set of evaluation metrics. Finally, we combine ILI and social media signals to build a joint neural network model for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance, specifically for military rather than general populations in 26 U.S. and six international locations., and analyze how model performance depends on the amount of social media data available per location. Our approach demonstrates several advantages: (a) Neural network architectures that rely on LSTM units trained on social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than stylistic and topic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns. (g) Model performance improves with more tweets available per geo-location e.g., the error gets lower and the Pearson score gets higher for locations with more tweets.

The role of model dynamics in ensemble Kalman filter performance for chaotic systems

USGS Publications Warehouse

Ng, G.-H.C.; McLaughlin, D.; Entekhabi, D.; Ahanin, A.

2011-01-01

The ensemble Kalman filter (EnKF) is susceptible to losing track of observations, or 'diverging', when applied to large chaotic systems such as atmospheric and ocean models. Past studies have demonstrated the adverse impact of sampling error during the filter's update step. We examine how system dynamics affect EnKF performance, and whether the absence of certain dynamic features in the ensemble may lead to divergence. The EnKF is applied to a simple chaotic model, and ensembles are checked against singular vectors of the tangent linear model, corresponding to short-term growth and Lyapunov vectors, corresponding to long-term growth. Results show that the ensemble strongly aligns itself with the subspace spanned by unstable Lyapunov vectors. Furthermore, the filter avoids divergence only if the full linearized long-term unstable subspace is spanned. However, short-term dynamics also become important as non-linearity in the system increases. Non-linear movement prevents errors in the long-term stable subspace from decaying indefinitely. If these errors then undergo linear intermittent growth, a small ensemble may fail to properly represent all important modes, causing filter divergence. A combination of long and short-term growth dynamics are thus critical to EnKF performance. These findings can help in developing practical robust filters based on model dynamics. ?? 2011 The Authors Tellus A ?? 2011 John Wiley & Sons A/S.

Integration of car-body flexibility into train-track coupling system dynamics analysis

NASA Astrophysics Data System (ADS)

Ling, Liang; Zhang, Qing; Xiao, Xinbiao; Wen, Zefeng; Jin, Xuesong

2018-04-01

The resonance vibration of flexible car-bodies greatly affects the dynamics performances of high-speed trains. In this paper, we report a three-dimensional train-track model to capture the flexible vibration features of high-speed train carriages based on the flexible multi-body dynamics approach. The flexible car-body is modelled using both the finite element method (FEM) and the multi-body dynamics (MBD) approach, in which the rigid motions are obtained by using the MBD theory and the structure deformation is calculated by the FEM and the modal superposition method. The proposed model is applied to investigate the influence of the flexible vibration of car-bodies on the dynamics performances of train-track systems. The dynamics performances of a high-speed train running on a slab track, including the car-body vibration behaviour, the ride comfort, and the running safety, calculated by the numerical models with rigid and flexible car-bodies are compared in detail. The results show that the car-body flexibility not only significantly affects the vibration behaviour and ride comfort of rail carriages, but also can has an important influence on the running safety of trains. The rigid car-body model underestimates the vibration level and ride comfort of rail vehicles, and ignoring carriage torsional flexibility in the curving safety evaluation of trains is conservative.

Analysis of dynamics and fit of diving suits

NASA Astrophysics Data System (ADS)

Mahnic Naglic, M.; Petrak, S.; Gersak, J.; Rolich, T.

2017-10-01

Paper presents research on dynamical behaviour and fit analysis of customised diving suits. Diving suits models are developed using the 3D flattening method, which enables the construction of a garment model directly on the 3D computer body model and separation of discrete 3D surfaces as well as transformation into 2D cutting parts. 3D body scanning of male and female test subjects was performed with the purpose of body measurements analysis in static and dynamic postures and processed body models were used for construction and simulation of diving suits prototypes. All necessary parameters, for 3D simulation were applied on obtained cutting parts, as well as parameters values for mechanical properties of neoprene material. Developed computer diving suits prototypes were used for stretch analysis on areas relevant for body dimensional changes according to dynamic anthropometrics. Garment pressures against the body in static and dynamic conditions was also analysed. Garments patterns for which the computer prototype verification was conducted were used for real prototype production. Real prototypes were also used for stretch and pressure analysis in static and dynamic conditions. Based on the obtained results, correlation analysis between body changes in dynamic positions and dynamic stress, determined on computer and real prototypes, was performed.

Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

2016-08-01

In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

4D Dynamic Required Navigation Performance Final Report

NASA Technical Reports Server (NTRS)

Finkelsztein, Daniel M.; Sturdy, James L.; Alaverdi, Omeed; Hochwarth, Joachim K.

2011-01-01

New advanced four dimensional trajectory (4DT) procedures under consideration for the Next Generation Air Transportation System (NextGen) require an aircraft to precisely navigate relative to a moving reference such as another aircraft. Examples are Self-Separation for enroute operations and Interval Management for in-trail and merging operations. The current construct of Required Navigation Performance (RNP), defined for fixed-reference-frame navigation, is not sufficiently specified to be applicable to defining performance levels of such air-to-air procedures. An extension of RNP to air-to-air navigation would enable these advanced procedures to be implemented with a specified level of performance. The objective of this research effort was to propose new 4D Dynamic RNP constructs that account for the dynamic spatial and temporal nature of Interval Management and Self-Separation, develop mathematical models of the Dynamic RNP constructs, "Required Self-Separation Performance" and "Required Interval Management Performance," and to analyze the performance characteristics of these air-to-air procedures using the newly developed models. This final report summarizes the activities led by Raytheon, in collaboration with GE Aviation and SAIC, and presents the results from this research effort to expand the RNP concept to a dynamic 4D frame of reference.

Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

PubMed Central

Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

2014-01-01

A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Calibration of Reduced Dynamic Models of Power Systems using Phasor Measurement Unit (PMU) Data

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

Zhou, Ning; Lu, Shuai; Singh, Ruchi

2011-09-23

Accuracy of a power system dynamic model is essential to the secure and efficient operation of the system. Lower confidence on model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, identification algorithms have been developed to calibrate parameters of individual components using measurement data from staged tests. To facilitate online dynamic studies for large power system interconnections, this paper proposes a model reduction and calibration approach using phasor measurement unit (PMU) data. First, a model reduction method is used to reduce the number of dynamic components. Then, a calibration algorithm is developed to estimatemore » parameters of the reduced model. This approach will help to maintain an accurate dynamic model suitable for online dynamic studies. The performance of the proposed method is verified through simulation studies.« less

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine, NASA Advanced Air Vehicles Program - Commercial Supersonic Technology Project - AeroServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Cheng, Larry

2015-01-01

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Dynamic ambulance reallocation for the reduction of ambulance response times using system status management.

PubMed

Lam, Sean Shao Wei; Zhang, Ji; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock

2015-02-01

Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly. Copyright © 2014 Elsevier Inc. All rights reserved.

The Widom line and dynamical crossover in supercritical water: Popular water models versus experiments

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

Corradini, D.; Rovere, M.; Gallo, P., E-mail: gallop@fis.uniroma3.it

2015-09-21

In a previous study [Gallo et al., Nat. Commun. 5, 5806 (2014)], we have shown an important connection between thermodynamic and dynamical properties of water in the supercritical region. In particular, by analyzing the experimental viscosity and the diffusion coefficient obtained in simulations performed using the TIP4P/2005 model, we have found that the line of response function maxima in the one phase region, the Widom line, is connected to a crossover from a liquid-like to a gas-like behavior of the transport coefficients. This is in agreement with recent experiments concerning the dynamics of supercritical simple fluids. We here show howmore » different popular water models (TIP4P/2005, TIP4P, SPC/E, TIP5P, and TIP3P) perform in reproducing thermodynamic and dynamic experimental properties in the supercritical region. In particular, the comparison with experiments shows that all the analyzed models are able to qualitatively predict the dynamical crossover from a liquid-like to a gas-like behavior upon crossing the Widom line. Some of the models perform better in reproducing the pressure-temperature slope of the Widom line of supercritical water once a rigid shift of the phase diagram is applied to bring the critical points to coincide with the experimental ones.« less

A fully dynamic model of a multi-layer piezoelectric actuator incorporating the power amplifier

NASA Astrophysics Data System (ADS)

Zhu, Wei; Yang, Fufeng; Rui, Xiaoting

2017-12-01

The dynamic input-output characteristics of the multi-layer piezoelectric actuator (PA) are intrinsically rate-dependent and hysteresis. Meanwhile, aiming at the strong capacitive impedance of multi-layer PA, the power amplifier of the actuator can greatly affect the dynamic performances of the actuator. In this paper, a novel dynamic model that includes a model of the electric circuit providing voltage to the actuator, an inverse piezoelectric effect model describing the hysteresis and creep behavior of the actuator, and a mechanical model, in which the vibration characteristics of the multi-layer PA is described, is put forward. Validation experimental tests are conducted. Experimental results show that the proposed dynamic model can accurately predict the fully dynamic behavior of the multi-layer PA with different driving power.

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less

Performance analysis and dynamic modeling of a single-spool turbojet engine

NASA Astrophysics Data System (ADS)

Andrei, Irina-Carmen; Toader, Adrian; Stroe, Gabriela; Frunzulica, Florin

2017-01-01

The purposes of modeling and simulation of a turbojet engine are the steady state analysis and transient analysis. From the steady state analysis, which consists in the investigation of the operating, equilibrium regimes and it is based on appropriate modeling describing the operation of a turbojet engine at design and off-design regimes, results the performance analysis, concluded by the engine's operational maps (i.e. the altitude map, velocity map and speed map) and the engine's universal map. The mathematical model that allows the calculation of the design and off-design performances, in case of a single spool turbojet is detailed. An in house code was developed, its calibration was done for the J85 turbojet engine as the test case. The dynamic modeling of the turbojet engine is obtained from the energy balance equations for compressor, combustor and turbine, as the engine's main parts. The transient analysis, which is based on appropriate modeling of engine and its main parts, expresses the dynamic behavior of the turbojet engine, and further, provides details regarding the engine's control. The aim of the dynamic analysis is to determine a control program for the turbojet, based on the results provided by performance analysis. In case of the single-spool turbojet engine, with fixed nozzle geometry, the thrust is controlled by one parameter, which is the fuel flow rate. The design and management of the aircraft engine controls are based on the results of the transient analysis. The construction of the design model is complex, since it is based on both steady-state and transient analysis, further allowing the flight path cycle analysis and optimizations. This paper presents numerical simulations for a single-spool turbojet engine (J85 as test case), with appropriate modeling for steady-state and dynamic analysis.

Development of a High Fidelity Dynamic Module of the Advanced Resistive Exercise Device (ARED) Using Adams

NASA Technical Reports Server (NTRS)

Humphreys, B. T.; Thompson, W. K.; Lewandowski, B. E.; Cadwell, E. E.; Newby, N. J.; Fincke, R. S.; Sheehan, C.; Mulugeta, L.

2012-01-01

NASA's Digital Astronaut Project (DAP) implements well-vetted computational models to predict and assess spaceflight health and performance risks, and enhance countermeasure development. DAP provides expertise and computation tools to its research customers for model development, integration, or analysis. DAP is currently supporting the NASA Exercise Physiology and Countermeasures (ExPC) project by integrating their biomechanical models of specific exercise movements with dynamic models of the devices on which the exercises were performed. This presentation focuses on the development of a high fidelity dynamic module of the Advanced Resistive Exercise Device (ARED) on board the ISS. The ARED module, illustrated in the figure below, was developed using the Adams (MSC Santa Ana, California) simulation package. The Adams package provides the capabilities to perform multi rigid body, flexible body, and mixed dynamic analyses of complex mechanisms. These capabilities were applied to accurately simulate: Inertial and mass properties of the device such as the vibration isolation system (VIS) effects and other ARED components, Non-linear joint friction effects, The gas law dynamics of the vacuum cylinders and VIS components using custom written differential state equations, The ARED flywheel dynamics, including torque limiting clutch. Design data from the JSC ARED Engineering team was utilized in developing the model. This included solid modeling geometry files, component/system specifications, engineering reports and available data sets. The Adams ARED module is importable into LifeMOD (Life Modeler, Inc., San Clemente, CA) for biomechanical analyses of different resistive exercises such as squat and dead-lift. Using motion capture data from ground test subjects, the ExPC developed biomechanical exercise models in LifeMOD. The Adams ARED device module was then integrated with the exercise subject model into one integrated dynamic model. This presentation will describe the development of the Adams ARED module including its capabilities, limitations, and assumptions. Preliminary results, validation activities, and a practical application of the module to inform the relative effect of the flywheels on exercise will be discussed.

A Dynamic Model of Sustainment Investment

DTIC Science & Technology

2015-02-01

Sustainment System Dynamics Model 11 Figure 7: Core Structure of Sustainment Work 12 Figure 8: Bandwagon Effect Loop 13 Figure 9: Limits to Growth Loop 14...Dynamics Model sustainment capacity sustainment performance gap Bandwagon Effect R1 Limits to Growth B1 S Work Smarter B3 Work Bigger B2 desired...which is of concern primarily when using the model as a vehicle for research. Figure 8 depicts a reinforcing loop called the “ Bandwagon Effect

Nonlinear stability and control study of highly maneuverable high performance aircraft

NASA Technical Reports Server (NTRS)

Mohler, R. R.

1993-01-01

This project is intended to research and develop new nonlinear methodologies for the control and stability analysis of high-performance, high angle-of-attack aircraft such as HARV (F18). Past research (reported in our Phase 1, 2, and 3 progress reports) is summarized and more details of final Phase 3 research is provided. While research emphasis is on nonlinear control, other tasks such as associated model development, system identification, stability analysis, and simulation are performed in some detail as well. An overview of various models that were investigated for different purposes such as an approximate model reference for control adaptation, as well as another model for accurate rigid-body longitudinal motion is provided. Only a very cursory analysis was made relative to type 8 (flexible body dynamics). Standard nonlinear longitudinal airframe dynamics (type 7) with the available modified F18 stability derivatives, thrust vectoring, actuator dynamics, and control constraints are utilized for simulated flight evaluation of derived controller performance in all cases studied.

Quasi 1D Modeling of Mixed Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Paxson, Daniel E.; Woolwine, Kyle J.

2012-01-01

The AeroServoElasticity task under the NASA Supersonics Project is developing dynamic models of the propulsion system and the vehicle in order to conduct research for integrated vehicle dynamic performance. As part of this effort, a nonlinear quasi 1-dimensional model of the 2-dimensional bifurcated mixed compression supersonic inlet is being developed. The model utilizes computational fluid dynamics for both the supersonic and subsonic diffusers. The oblique shocks are modeled utilizing compressible flow equations. This model also implements variable geometry required to control the normal shock position. The model is flexible and can also be utilized to simulate other mixed compression supersonic inlet designs. The model was validated both in time and in the frequency domain against the legacy LArge Perturbation INlet code, which has been previously verified using test data. This legacy code written in FORTRAN is quite extensive and complex in terms of the amount of software and number of subroutines. Further, the legacy code is not suitable for closed loop feedback controls design, and the simulation environment is not amenable to systems integration. Therefore, a solution is to develop an innovative, more simplified, mixed compression inlet model with the same steady state and dynamic performance as the legacy code that also can be used for controls design. The new nonlinear dynamic model is implemented in MATLAB Simulink. This environment allows easier development of linear models for controls design for shock positioning. The new model is also well suited for integration with a propulsion system model to study inlet/propulsion system performance, and integration with an aero-servo-elastic system model to study integrated vehicle ride quality, vehicle stability, and efficiency.

Identification of the numerical model of FEM in reference to measurements in situ

NASA Astrophysics Data System (ADS)

Jukowski, Michał; Bec, Jarosław; Błazik-Borowa, Ewa

2018-01-01

The paper deals with the verification of various numerical models in relation to the pilot-phase measurements of a rail bridge subjected to dynamic loading. Three types of FEM models were elaborated for this purpose. Static, modal and dynamic analyses were performed. The study consisted of measuring the acceleration values of the structural components of the object at the moment of the train passing. Based on this, FFT analysis was performed, the main natural frequencies of the bridge were determined, the structural damping ratio and the dynamic amplification factor (DAF) were calculated and compared with the standard values. Calculations were made using Autodesk Simulation Multiphysics (Algor).

Dynamic load-sharing characteristic analysis of face gear power-split gear system based on tooth contact characteristics

NASA Astrophysics Data System (ADS)

Dong, Hao; Hu, Yahui

2018-04-01

The bend-torsion coupling dynamics load-sharing model of the helicopter face gear split torque transmission system is established by using concentrated quality standard, to analyzing the dynamic load-sharing characteristic. The mathematical models include nonlinear support stiffness, time-varying meshing stiffness, damping, gear backlash. The results showed that the errors collectively influenced the load sharing characteristics, only reduce a certain error, it is never fully reached the perfect loading sharing characteristics. The system load-sharing performance can be improved through floating shaft support. The above-method will provide a theoretical basis and data support for its dynamic performance optimization design.

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

NASA Technical Reports Server (NTRS)

Csank, Jeffrey; Zinnecker, Alicia

2014-01-01

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000(CMAPSS40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLABSimulink (The MathWorks, Inc.) environment.

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

NASA Technical Reports Server (NTRS)

Csank, Jeffrey Thomas; Zinnecker, Alicia Mae

2014-01-01

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment.

Space Shuttle Main Engine Low Pressure Oxidizer Turbo-Pump Inducer Dynamic Environment Characterization through Water Model and Hot-Fire Testing

NASA Technical Reports Server (NTRS)

Arellano, Patrick; Patton, Marc; Schwartz, Alan; Stanton, David

2006-01-01

The Low Pressure Oxidizer Turbopump (LPOTP) inducer on the Block II configuration Space Shuttle Main Engine (SSME) experienced blade leading edge ripples during hot firing. This undesirable condition led to a minor redesign of the inducer blades. This resulted in the need to evaluate the performance and the dynamic environment of the redesign, relative to the current configuration, as part of the design acceptance process. Sub-scale water model tests of the two inducer configurations were performed, with emphasis on the dynamic environment due to cavitation induced vibrations. Water model tests were performed over a wide range of inlet flow coefficient and pressure conditions, representative of the scaled operating envelope of the Block II SSME, both in flight and in ground hot-fire tests, including all power levels. The water test hardware, facility set-up, type and placement of instrumentation, the scope of the test program, specific test objectives, data evaluation process and water test results that characterize and compare the two SSME LPOTP inducers are discussed. In addition, dynamic characteristics of the two water models were compared to hot fire data from specially instrumented ground tests. In general, good agreement between the water model and hot fire data was found, which confirms the value of water model testing for dynamic characterization of rocket engine turbomachinery.

The dynamic and steady state behavior of a PEM fuel cell as an electric energy source

NASA Astrophysics Data System (ADS)

Costa, R. A.; Camacho, J. R.

The main objective of this work is to extract information on the internal behavior of three small polymer electrolyte membrane fuel cells under static and dynamic load conditions. A computational model was developed using Scilab [SCILAB 4, Scilab-a free scientific software package, http://www.scilab.org/, INRIA, France, December, 2005] to simulate the static and dynamic performance [J.M. Correa, A.F. Farret, L.N. Canha, An analysis of the dynamic performance of proton exchange membrane fuel cells using an electrochemical model, in: 27th Annual Conference of IEEE Industrial Electronics Society, 2001, pp. 141-146] of this particular type of fuel cell. This dynamic model is based on electrochemical equations and takes into consideration most of the chemical and physical characteristics of the device in order to generate electric power. The model takes into consideration the operating, design parameters and physical material properties. The results show the internal losses and concentration effects behavior, which are of interest for power engineers and researchers.

The Relationship of Learning Traits, Motivation and Performance-Learning Response Dynamics

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Chang, Chen-Bin; Chen, Gan-Jung

2004-01-01

This paper proposes a model of learning dynamics and learning energy, one that analyzes learning systems scientifically. This model makes response to the learner action by means of some equations relating to learning dynamics, learning energy, learning speed, learning force, and learning acceleration, which is analogous to the notion of Newtonian…

Aerodynamic analysis of the Darrieus wind turbines including dynamic-stall effects

NASA Astrophysics Data System (ADS)

Paraschivoiu, Ion; Allet, Azeddine

Experimental data for a 17-m wind turbine are compared with aerodynamic performance predictions obtained with two dynamic stall methods which are based on numerical correlations of the dynamic stall delay with the pitch rate parameter. Unlike the Gormont (1973) model, the MIT model predicts that dynamic stall does not occur in the downwind part of the turbine, although it does exist in the upwind zone. The Gormont model is shown to overestimate the aerodynamic coefficients relative to the MIT model. The MIT model is found to accurately predict the dynamic-stall regime, which is characterized by a plateau oscillating near values of the experimental data for the rotor power vs wind speed at the equator.

Closed-form dynamics of a hexarot parallel manipulator by means of the principle of virtual work

NASA Astrophysics Data System (ADS)

Pedrammehr, Siamak; Nahavandi, Saeid; Abdi, Hamid

2018-04-01

In this research, a systematic approach to solving the inverse dynamics of hexarot manipulators is addressed using the methodology of virtual work. For the first time, a closed form of the mathematical formulation of the standard dynamic model is presented for this class of mechanisms. An efficient algorithm for solving this closed-form dynamic model of the mechanism is developed and it is used to simulate the dynamics of the system for different trajectories. Validation of the proposed model is performed using SimMechanics and it is shown that the results of the proposed mathematical model match with the results obtained by the SimMechanics model.

Dynamic Smagorinsky model on anisotropic grids

NASA Technical Reports Server (NTRS)

Scotti, A.; Meneveau, C.; Fatica, M.

1996-01-01

Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Dynamic performance of accommodating intraocular lenses in a negative feedback control system: a simulation-based study.

PubMed

Schor, Clifton M; Bharadwaj, Shrikant R; Burns, Christopher D

2007-07-01

A dynamic model of ocular accommodation is used to simulate the stability and dynamic performance of accommodating intraocular lenses (A-IOLs) that replace the hardened natural ocular lens that is unable to change focus. Accommodation simulations of an older eye with A-IOL materials having biomechanical properties of a younger eye illustrate overshoots and oscillations resulting from decreased visco-elasticity of the A-IOL. Stable dynamics of an A-IOL are restored by adaptation of phasic and tonic neural-control properties of accommodation. Simulations indicate that neural control must be recalibrated to avoid unstable dynamic accommodation with A-IOLs. An interactive web-model of A-IOL illustrating these properties is available at http://schorlab.berkeley.edu.

Local dynamic subgrid-scale models in channel flow

NASA Technical Reports Server (NTRS)

Cabot, William H.

1994-01-01

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

Two Decades of WRF/CMAQ simulations over the continental United States: New approaches for performing dynamic model evaluation and determining confidence limits for ozone exceedances

EPA Science Inventory

Confidence in the application of models for forecasting and regulatory assessments is furthered by conducting four types of model evaluation: operational, dynamic, diagnostic, and probabilistic. Operational model evaluation alone does not reveal the confidence limits that can be ...

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

A dynamic model of stress and sustained attention

NASA Technical Reports Server (NTRS)

Hancock, P. A.; Warm, Joel S.

1989-01-01

Arguments are presented that an integrated view of stress and performance must consider the task demanding a sustained attention as a primary source of cognitive stress. A dynamic model is developed on the basis of the concept of adaptability in both physiological and psychological terms, that addresses the effects of stress on vigilance and, potentially, a wide variety of attention-demanding performance tasks. The model provides an insight into the failure of an operator under the driving influences of stress and opens a number of potential avenues through which solutions to the complex challenge of stress and performance might be posed.

Similarity Metrics for Closed Loop Dynamic Systems

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Yang, Lee C.; Bedrossian, Naz; Hall, Robert A.

2008-01-01

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Dynamic coal mine model. [Generic feedback-loop model

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

Hamilton, M.S.

1978-01-01

This study examines the determinants of the productive life cycle of a single hypothetical coal mine. The article addresses the questions of how long the mine will operate, what its annual production will be, and what percentage of the resource base will be recovered. As greatly expanded production requires capital investment, the investment decision is singled out as the principal determinant of the mine's dynamic behavior. A simple dynamic feedback loop model was constructed, the performance of which is compared with actual data to see how well the model can reproduce known behavior. Exogenous variables, such as the price ofmore » coal, the wage rate, operating costs, and the tax structure, are then changed to see how these changes affect the mine's performance.« less

Reducing the Dynamical Degradation by Bi-Coupling Digital Chaotic Maps

NASA Astrophysics Data System (ADS)

Liu, Lingfeng; Liu, Bocheng; Hu, Hanping; Miao, Suoxia

A chaotic map which is realized on a computer will suffer dynamical degradation. Here, a coupled chaotic model is proposed to reduce the dynamical degradation. In this model, the state variable of one digital chaotic map is used to control the parameter of the other digital map. This coupled model is universal and can be used for all chaotic maps. In this paper, two coupled models (one is coupled by two logistic maps, the other is coupled by Chebyshev map and Baker map) are performed, and the numerical experiments show that the performances of these two coupled chaotic maps are greatly improved. Furthermore, a simple pseudorandom bit generator (PRBG) based on coupled digital logistic maps is proposed as an application for our method.

The Interdictor’s Lot: A Dynamic Model of the Market for Drug Smuggling Services

DTIC Science & Technology

1988-02-01

A RAND NOTE The Interdictor’s Lot: A Dynamic Model of the 00 Market for Drug Smuggling Services Jonathan A. K. Cave, Peter Reuter February 1988. DTIC...Dynamic Model of the Interim Market for Drug Smuggling Services________________ 6. PERFORMING ORG. REPORT NUMBER 7, AUTHOR(s) s. CONTRACT OR GRANT...Economic Models - Narcotics,. Economic Analysis, Interdictions- Smuggling Law Enforcement U - Drugs. 20 ABSTRACT (Continue on ,e~erse side It necessary

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination.

PubMed

Panagou, Efstathios Z; Nychas, George-John E

2008-09-01

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

SSEM: A model for simulating runoff and erosion of saline-sodic soil slopes under coastal reclamation

NASA Astrophysics Data System (ADS)

Liu, Dongdong; She, Dongli

2018-06-01

Current physically based erosion models do not carefully consider the dynamic variations of soil properties during rainfall and are unable to simulate saline-sodic soil slope erosion processes. The aim of this work was to build upon a complete model framework, SSEM, to simulate runoff and erosion processes for saline-sodic soils by coupling dynamic saturated hydraulic conductivity Ks and soil erodibility Kτ. Sixty rainfall simulation rainfall experiments (2 soil textures × 5 sodicity levels × 2 slope gradients × 3 duplicates) provided data for model calibration and validation. SSEM worked very well for simulating the runoff and erosion processes of saline-sodic silty clay. The runoff and erosion processes of saline-sodic silt loam were more complex than those of non-saline soils or soils with higher clay contents; thus, SSEM did not perform very well for some validation events. We further examined the model performances of four concepts: Dynamic Ks and Kτ (Case 1, SSEM), Dynamic Ks and Constant Kτ (Case 2), Constant Ks and Dynamic Kτ (Case 3) and Constant Ks and Constant Kτ (Case 4). The results demonstrated that the model, which considers dynamic variations in soil saturated hydraulic conductivity and soil erodibility, can provide more reasonable runoff and erosion prediction results for saline-sodic soils.

HARP model rotor test at the DNW. [Hughes Advanced Rotor Program

NASA Technical Reports Server (NTRS)

Dawson, Seth; Jordan, David; Smith, Charles; Ekins, James; Silverthorn, Lou

1989-01-01

Data from a test of a dynamically scaled model of the Hughes Advanced Rotor Program (HARP) bearingless model main rotor and 369K tail rotor are reported. The history of the HARP program and its goals are reviewed, and the main and tail rotor models are described. The test facilities and instrumentation are described, and wind tunnel test data are presented on hover, forward flight performance, and blade-vortex interaction. Performance data, acoustic data, and dynamic data from near field/far field and shear layer studies are presented.

The internal model: A study of the relative contribution of proprioception and visual information to failure detection in dynamic systems. [sensitivity of operators versus monitors to failures

NASA Technical Reports Server (NTRS)

Kessel, C.; Wickens, C. D.

1978-01-01

The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.

Simulated Annealing-based Optimal Proportional-Integral-Derivative (PID) Controller Design: A Case Study on Nonlinear Quadcopter Dynamics

NASA Astrophysics Data System (ADS)

Nemirsky, Kristofer Kevin

In this thesis, the history and evolution of rotor aircraft with simulated annealing-based PID application were reviewed and quadcopter dynamics are presented. The dynamics of a quadcopter were then modeled, analyzed, and linearized. A cascaded loop architecture with PID controllers was used to stabilize the plant dynamics, which was improved upon through the application of simulated annealing (SA). A Simulink model was developed to test the controllers and verify the functionality of the proposed control system design. In addition, the data that the Simulink model provided were compared with flight data to present the validity of derived dynamics as a proper mathematical model representing the true dynamics of the quadcopter system. Then, the SA-based global optimization procedure was applied to obtain optimized PID parameters. It was observed that the tuned gains through the SA algorithm produced a better performing PID controller than the original manually tuned one. Next, we investigated the uncertain dynamics of the quadcopter setup. After adding uncertainty to the gyroscopic effects associated with pitch-and-roll rate dynamics, the controllers were shown to be robust against the added uncertainty. A discussion follows to summarize SA-based algorithm PID controller design and performance outcomes. Lastly, future work on SA application on multi-input-multi-output (MIMO) systems is briefly discussed.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Dynamic Mesh CFD Simulations of Orion Parachute Pendulum Motion During Atmospheric Entry

NASA Technical Reports Server (NTRS)

Halstrom, Logan D.; Schwing, Alan M.; Robinson, Stephen K.

2016-01-01

This paper demonstrates the usage of computational fluid dynamics to study the effects of pendulum motion dynamics of the NASAs Orion Multi-Purpose Crew Vehicle parachute system on the stability of the vehicles atmospheric entry and decent. Significant computational fluid dynamics testing has already been performed at NASAs Johnson Space Center, but this study sought to investigate the effect of bulk motion of the parachute, such as pitching, on the induced aerodynamic forces. Simulations were performed with a moving grid geometry oscillating according to the parameters observed in flight tests. As with the previous simulations, OVERFLOW computational fluid dynamics tool is used with the assumption of rigid, non-permeable geometry. Comparison to parachute wind tunnel tests is included for a preliminary validation of the dynamic mesh model. Results show qualitative differences in the flow fields of the static and dynamic simulations and quantitative differences in the induced aerodynamic forces, suggesting that dynamic mesh modeling of the parachute pendulum motion may uncover additional dynamic effects.

Software life cycle dynamic simulation model: The organizational performance submodel

NASA Technical Reports Server (NTRS)

Tausworthe, Robert C.

1985-01-01

The submodel structure of a software life cycle dynamic simulation model is described. The software process is divided into seven phases, each with product, staff, and funding flows. The model is subdivided into an organizational response submodel, a management submodel, a management influence interface, and a model analyst interface. The concentration here is on the organizational response model, which simulates the performance characteristics of a software development subject to external and internal influences. These influences emanate from two sources: the model analyst interface, which configures the model to simulate the response of an implementing organization subject to its own internal influences, and the management submodel that exerts external dynamic control over the production process. A complete characterization is given of the organizational response submodel in the form of parameterized differential equations governing product, staffing, and funding levels. The parameter values and functions are allocated to the two interfaces.

Modeling the Multi-Body System Dynamics of a Flexible Solar Sail Spacecraft

NASA Technical Reports Server (NTRS)

Kim, Young; Stough, Robert; Whorton, Mark

2005-01-01

Solar sail propulsion systems enable a wide range of space missions that are not feasible with current propulsion technology. Hardware concepts and analytical methods have matured through ground development to the point that a flight validation mission is now realizable. Much attention has been given to modeling the structural dynamics of the constituent elements, but to date an integrated system level dynamics analysis has been lacking. Using a multi-body dynamics and control analysis tool called TREETOPS, the coupled dynamics of the sailcraft bus, sail membranes, flexible booms, and control system sensors and actuators of a representative solar sail spacecraft are investigated to assess system level dynamics and control issues. With this tool, scaling issues and parametric trade studies can be performed to study achievable performance, control authority requirements, and control/structure interaction assessments.

Dynamic Evaluation of a Regional Air Quality Model: Assessing the Emissions-Induced Weekly Ozone Cycle

EPA Science Inventory

Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the community Mult...

Development and Calibration of Regional Dynamic Traffic Assignment Models for the Estimation of Traffic Performance Measures in Nevada

DOT National Transportation Integrated Search

2017-02-01

This project covered the development and calibration of a Dynamic Traffic Assignment (DTA) model and explained the procedures, constraints, and considerations for usage of this model for the Reno-Sparks area roadway network in Northern Nevada. A lite...

Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

ERIC Educational Resources Information Center

Levy, Roy

2014-01-01

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…

Software-Engineering Process Simulation (SEPS) model

NASA Technical Reports Server (NTRS)

Lin, C. Y.; Abdel-Hamid, T.; Sherif, J. S.

1992-01-01

The Software Engineering Process Simulation (SEPS) model is described which was developed at JPL. SEPS is a dynamic simulation model of the software project development process. It uses the feedback principles of system dynamics to simulate the dynamic interactions among various software life cycle development activities and management decision making processes. The model is designed to be a planning tool to examine tradeoffs of cost, schedule, and functionality, and to test the implications of different managerial policies on a project's outcome. Furthermore, SEPS will enable software managers to gain a better understanding of the dynamics of software project development and perform postmodern assessments.

An AD100 implementation of a real-time STOVL aircraft propulsion system

NASA Technical Reports Server (NTRS)

Ouzts, Peter J.; Drummond, Colin K.

1990-01-01

A real-time dynamic model of the propulsion system for a Short Take-Off and Vertical Landing (STOVL) aircraft was developed for the AD100 simulation environment. The dynamic model was adapted from a FORTRAN based simulation using the dynamic programming capabilities of the AD100 ADSIM simulation language. The dynamic model includes an aerothermal representation of a turbofan jet engine, actuator and sensor models, and a multivariable control system. The AD100 model was tested for agreement with the FORTRAN model and real-time execution performance. The propulsion system model was also linked to an airframe dynamic model to provide an overall STOVL aircraft simulation for the purposes of integrated flight and propulsion control studies. An evaluation of the AD100 system for use as an aircraft simulation environment is included.

Incentives and Their Dynamics in Public Sector Performance Management Systems

ERIC Educational Resources Information Center

Heinrich, Carolyn J.; Marschke, Gerald

2010-01-01

We use the principal-agent model as a focal theoretical frame for synthesizing what we know, both theoretically and empirically, about the design and dynamics of the implementation of performance management systems in the public sector. In this context, we review the growing body of evidence about how performance measurement and incentive systems…

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training

PubMed Central

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R.

2015-01-01

Background. Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. Methods. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Results. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. Conclusion. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines. PMID:26417378

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training.

PubMed

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R; Lorenzetti, Silvio

2015-01-01

Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines.

Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method

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

Deichmann, Gregor; Marcon, Valentina; Vegt, Nico F. A. van der, E-mail: vandervegt@csi.tu-darmstadt.de

Molecular simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodynamic properties can be quite accurately represented while the prediction of dynamic properties remains difficult, especially for multi-component systems. In this work, we use constraint molecular dynamics simulations for calculating dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived frommore » fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These molecular liquids are simulated with atomistic molecular dynamics, coarse-grained molecular dynamics, and DPD. We find that the CRW-DPD models reproduce the liquid structure and diffusive dynamics of the liquid systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads containing five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale separation can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics.« less

Impacts of Wake Effect and Time Delay on the Dynamic Analysis of Wind Farms Models

ERIC Educational Resources Information Center

El-Fouly, Tarek H. M.; El-Saadany, Ehab F.; Salama, Magdy M. A.

2008-01-01

This article investigates the impacts of proper modeling of the wake effects and wind speed delays, between different wind turbines' rows, on the dynamic performance accuracy of the wind farms models. Three different modeling scenarios were compared to highlight the impacts of wake effects and wind speed time-delay models. In the first scenario,…

Dynamic aspects of voluntary turnover: an integrated approach to curvilinearity in the performance-turnover relationship.

PubMed

Becker, William J; Cropanzano, Russell

2011-03-01

Previous research pertaining to job performance and voluntary turnover has been guided by 2 distinct theoretical perspectives. First, the push-pull model proposes that there is a quadratic or curvilinear relationship existing between these 2 variables. Second, the unfolding model of turnover posits that turnover is a dynamic process and that a downward performance change may increase the likelihood of organizational separation. Drawing on decision theory, we propose and test an integrative framework. This approach incorporates both of these earlier models. Specifically, we argue that individuals are most likely to voluntarily exit when they are below-average performers who are also experiencing a downward performance change. Furthermore, the interaction between this downward change and performance partially accounts for the curvilinear relationship proposed by the push-pull model. Findings from a longitudinal field study supported this integrative theory. PsycINFO Database Record (c) 2011 APA, all rights reserved.

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.

International Space Station Model Correlation Analysis

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Modeling, control, and dynamic performance analysis of a reverse osmosis desalination plant integrated within hybrid energy systems

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

Kim, Jong Suk; Chen, Jun; Garcia, Humberto E.

An RO (reverse osmosis) desalination plant is proposed as an effective, FLR (flexible load resource) to be integrated into HES (hybrid energy systems) to support various types of ancillary services to the electric grid, under variable operating conditions. To study the dynamic (transient) analysis of such system, among the various unit operations within HES, special attention is given here to the detailed dynamic modeling and control design of RO desalination process with a spiral-wound membrane module. The model incorporates key physical phenomena that have been investigated individually into a dynamic integrated model framework. In particular, the solution-diffusion model modified withmore » the concentration polarization theory is applied to predict RO performance over a large range of operating conditions. Simulation results involving several case studies suggest that an RO desalination plant, acting as a FLR, can provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess electrical energy. Here, the incorporation of additional commodity (fresh water) produced from a FLR allows a broader range of HES operations for maximizing overall system performance and profitability. For the purpose of assessing the incorporation of health assessment into process operations, an online condition monitoring approach for RO membrane fouling supervision is addressed in the case study presented.« less

Modeling, control, and dynamic performance analysis of a reverse osmosis desalination plant integrated within hybrid energy systems

DOE PAGES

Kim, Jong Suk; Chen, Jun; Garcia, Humberto E.

2016-06-17

An RO (reverse osmosis) desalination plant is proposed as an effective, FLR (flexible load resource) to be integrated into HES (hybrid energy systems) to support various types of ancillary services to the electric grid, under variable operating conditions. To study the dynamic (transient) analysis of such system, among the various unit operations within HES, special attention is given here to the detailed dynamic modeling and control design of RO desalination process with a spiral-wound membrane module. The model incorporates key physical phenomena that have been investigated individually into a dynamic integrated model framework. In particular, the solution-diffusion model modified withmore » the concentration polarization theory is applied to predict RO performance over a large range of operating conditions. Simulation results involving several case studies suggest that an RO desalination plant, acting as a FLR, can provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess electrical energy. Here, the incorporation of additional commodity (fresh water) produced from a FLR allows a broader range of HES operations for maximizing overall system performance and profitability. For the purpose of assessing the incorporation of health assessment into process operations, an online condition monitoring approach for RO membrane fouling supervision is addressed in the case study presented.« less

Dynamic Testing of a Subscale Sunshield for the Next Generation Space Telescope (NGST)

NASA Technical Reports Server (NTRS)

Lienard, Sebastien; Johnston, John D.; Ross, Brian; Smith, James; Brodeur, Steve (Technical Monitor)

2001-01-01

The NGST sunshield is a lightweight, flexible structure consisting of multiple layers of pretensioned, thin-film membranes supported by deployable booms. The structural dynamic behavior of the sunshield must be well understood in order to predict its influence on observatory performance. Ground tests were carried out in a vacuum environment to characterize the structural dynamic behavior of a one-tenth scale model of the sunshield. Results from the tests will be used to validate analytical modeling techniques that can be used in conjunction with scaling laws to predict the performance of the full-sized structure. This paper summarizes the ground tests and presents representative results for the dynamic behavior of the sunshield.

Rolling Maneuver Load Alleviation using active controls

NASA Technical Reports Server (NTRS)

Woods-Vedeler, Jessica A.; Pototzky, Anthony S.

1992-01-01

Rolling Maneuver Load Alleviation (RMLA) has been demonstrated on the Active Flexible Wing (AFW) wind tunnel model in the NASA Langley Transonic Dynamics Tunnel. The design objective was to develop a systematic approach for developing active control laws to alleviate wing incremental loads during roll maneuvers. Using linear load models for the AFW wind-tunnel model which were based on experimental measurements, two RMLA control laws were developed based on a single-degree-of-freedom roll model. The RMLA control laws utilized actuation of outboard control surface pairs to counteract incremental loads generated during rolling maneuvers and actuation of the trailing edge inboard control surface pairs to maintain roll performance. To evaluate the RMLA control laws, roll maneuvers were performed in the wind tunnel at dynamic pressures of 150, 200, and 250 psf and Mach numbers of 0.33, .38 and .44, respectively. Loads obtained during these maneuvers were compared to baseline maneuver loads. For both RMLA controllers, the incremental torsion moments were reduced by up to 60 percent at all dynamic pressures and performance times. Results for bending moment load reductions during roll maneuvers varied. In addition, in a multiple function test, RMLA and flutter suppression system control laws were operated simultaneously during roll maneuvers at dynamic pressures 11 percent above the open-loop flutter dynamic pressure.

Study on the dynamic recrystallization model and mechanism of nuclear grade 316LN austenitic stainless steel

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

Wang, Shenglong; Zhang, Mingxian; Wu, Huanchun

In this study, the dynamic recrystallization behaviors of a nuclear grade 316LN austenitic stainless steel were researched through hot compression experiment performed on a Gleeble-1500 simulator at temperatures of 900–1250 °C and strain rates of 0.01–1 s{sup −1}. By multiple linear regressions of the flow stress-strain data, the dynamic recrystallization mathematical models of this steel as functions of strain rate, strain and temperature were developed. Then these models were verified in a real experiment. Furthermore, the dynamic recrystallization mechanism of the steel was determined. The results indicated that the subgrains in this steel are formed through dislocations polygonization and thenmore » grow up through subgrain boundaries migration towards high density dislocation areas and subgrain coalescence mechanism. Dynamic recrystallization nucleation performs in grain boundary bulging mechanism and subgrain growth mechanism. The nuclei grow up through high angle grain boundaries migration. - Highlights: •Establish the DRX mathematical models of nuclear grade 316LN stainless steel •Determine the DRX mechanism of this steel •Subgrains are formed through dislocations polygonization. •Subgrains grow up through subgrain boundaries migration and coalescence mechanism. •DRX nucleation performs in grain boundary bulging mechanism and subgrain growth mechanism.« less

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

NASA Technical Reports Server (NTRS)

Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

2017-01-01

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2018-02-01

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 × 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmental Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation's performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.

Performance and Architecture Lab Modeling Tool

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

2014-06-19

Analytical application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult. Furthermore, models are frequently expressed in forms that are hard to distribute and validate. The Performance and Architecture Lab Modeling tool, or Palm, is a modeling tool designed to make application modeling easier. Palm provides a source code modeling annotation language. Not only does the modeling language divide the modeling task into sub problems, it formally links an application's source code with its model. This link is important because a model's purpose is to capture application behavior. Furthermore, this linkmore » makes it possible to define rules for generating models according to source code organization. Palm generates hierarchical models according to well-defined rules. Given an application, a set of annotations, and a representative execution environment, Palm will generate the same model. A generated model is a an executable program whose constituent parts directly correspond to the modeled application. Palm generates models by combining top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. A model's hierarchy is defined by static and dynamic source code structure. Because Palm coordinates models and source code, Palm's models are 'first-class' and reproducible. Palm automates common modeling tasks. For instance, Palm incorporates measurements to focus attention, represent constant behavior, and validate models. Palm's workflow is as follows. The workflow's input is source code annotated with Palm modeling annotations. The most important annotation models an instance of a block of code. Given annotated source code, the Palm Compiler produces executables and the Palm Monitor collects a representative performance profile. The Palm Generator synthesizes a model based on the static and dynamic mapping of annotations to program behavior. The model -- an executable program -- is a hierarchical composition of annotation functions, synthesized functions, statistics for runtime values, and performance measurements.« less

Mesoscale energy deposition footprint model for kiloelectronvolt cluster bombardment of solids.

PubMed

Russo, Michael F; Garrison, Barbara J

2006-10-15

Molecular dynamics simulations have been performed to model 5-keV C60 and Au3 projectile bombardment of an amorphous water substrate. The goal is to obtain detailed insights into the dynamics of motion in order to develop a straightforward and less computationally demanding model of the process of ejection. The molecular dynamics results provide the basis for the mesoscale energy deposition footprint model. This model provides a method for predicting relative yields based on information from less than 1 ps of simulation time.

A simple electric circuit model for proton exchange membrane fuel cells

NASA Astrophysics Data System (ADS)

Lazarou, Stavros; Pyrgioti, Eleftheria; Alexandridis, Antonio T.

A simple and novel dynamic circuit model for a proton exchange membrane (PEM) fuel cell suitable for the analysis and design of power systems is presented. The model takes into account phenomena like activation polarization, ohmic polarization, and mass transport effect present in a PEM fuel cell. The proposed circuit model includes three resistors to approach adequately these phenomena; however, since for the PEM dynamic performance connection or disconnection of an additional load is of crucial importance, the proposed model uses two saturable inductors accompanied by an ideal transformer to simulate the double layer charging effect during load step changes. To evaluate the effectiveness of the proposed model its dynamic performance under load step changes is simulated. Experimental results coming from a commercial PEM fuel cell module that uses hydrogen from a pressurized cylinder at the anode and atmospheric oxygen at the cathode, clearly verify the simulation results.

Structure and dynamics of complex liquid water: Molecular dynamics simulation

NASA Astrophysics Data System (ADS)

S, Indrajith V.; Natesan, Baskaran

2015-06-01

We have carried out detailed structure and dynamical studies of complex liquid water using molecular dynamics simulations. Three different model potentials, namely, TIP3P, TIP4P and SPC-E have been used in the simulations, in order to arrive at the best possible potential function that could reproduce the structure of experimental bulk water. All the simulations were performed in the NVE micro canonical ensemble using LAMMPS. The radial distribution functions, gOO, gOH and gHH and the self diffusion coefficient, Ds, were calculated for all three models. We conclude from our results that the structure and dynamical parameters obtained for SPC-E model matched well with the experimental values, suggesting that among the models studied here, the SPC-E model gives the best structure and dynamics of bulk water.

Dynamic modeling, experimental evaluation, optimal design and control of integrated fuel cell system and hybrid energy systems for building demands

NASA Astrophysics Data System (ADS)

Nguyen, Gia Luong Huu

Fuel cells can produce electricity with high efficiency, low pollutants, and low noise. With the advent of fuel cell technologies, fuel cell systems have since been demonstrated as reliable power generators with power outputs from a few watts to a few megawatts. With proper equipment, fuel cell systems can produce heating and cooling, thus increased its overall efficiency. To increase the acceptance from electrical utilities and building owners, fuel cell systems must operate more dynamically and integrate well with renewable energy resources. This research studies the dynamic performance of fuel cells and the integration of fuel cells with other equipment in three levels: (i) the fuel cell stack operating on hydrogen and reformate gases, (ii) the fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit, and (iii) the hybrid energy system consisting of photovoltaic panels, fuel cell system, and energy storage. In the first part, this research studied the steady-state and dynamic performance of a high temperature PEM fuel cell stack. Collaborators at Aalborg University (Aalborg, Denmark) conducted experiments on a high temperature PEM fuel cell short stack at steady-state and transients. Along with the experimental activities, this research developed a first-principles dynamic model of a fuel cell stack. The dynamic model developed in this research was compared to the experimental results when operating on different reformate concentrations. Finally, the dynamic performance of the fuel cell stack for a rapid increase and rapid decrease in power was evaluated. The dynamic model well predicted the performance of the well-performing cells in the experimental fuel cell stack. The second part of the research studied the dynamic response of a high temperature PEM fuel cell system consisting of a fuel reformer, a fuel cell stack, and a heat recovery unit with high thermal integration. After verifying the model performance with the obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.

A model for evaluating the social performance of construction waste management.

PubMed

Yuan, Hongping

2012-06-01

It has been determined by existing literature that a lot of research efforts have been made to the economic performance of construction waste management (CWM), but less attention is paid to investigation of the social performance of CWM. This study therefore attempts to develop a model for quantitatively evaluating the social performance of CWM by using a system dynamics (SD) approach. Firstly, major variables affecting the social performance of CWM are identified and a holistic system for assessing the social performance of CWM is formulated in line with feedback relationships underlying these variables. The developed system is then converted into a SD model through the software iThink. An empirical case study is finally conducted to demonstrate application of the model. Results of model validation indicate that the model is robust and reasonable to reflect the situation of the real system under study. Findings of the case study offer helpful insights into effectively promoting the social performance of CWM of the project investigated. Furthermore, the model exhibits great potential to function as an experimental platform for dynamically evaluating effects of management measures on improving the social performance of CWM of construction projects. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling and control of magnetorheological fluid dampers using neural networks

NASA Astrophysics Data System (ADS)

Wang, D. H.; Liao, W. H.

2005-02-01

Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.

Alignment dynamics of diffusive scalar gradient in a two-dimensional model flow

NASA Astrophysics Data System (ADS)

Gonzalez, M.

2018-04-01

The Lagrangian two-dimensional approach of scalar gradient kinematics is revisited accounting for molecular diffusion. Numerical simulations are performed in an analytic, parameterized model flow, which enables considering different regimes of scalar gradient dynamics. Attention is especially focused on the influence of molecular diffusion on Lagrangian statistical orientations and on the dynamics of scalar gradient alignment.

Mining the Dynamics of Student Utility and Strategy Use during Vocabulary Learning

ERIC Educational Resources Information Center

Pavlik, Philip I., Jr.

2013-01-01

This paper describes the development of a dynamical systems model of motivation and metacognition during learning, which explains some of the practically and theoretically important relationships among three student engagement constructs and performance metrics during learning. In order to better calibrate and understand the model, the model was…

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

PubMed

Yu, Kezi; Quirk, J Gerald; Djurić, Petar M

2017-01-01

In this paper, we propose an application of non-parametric Bayesian (NPB) models for classification of fetal heart rate (FHR) recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP) and the Chinese restaurant process with finite capacity (CRFC). Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR) recordings in a real-time setting.

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models

PubMed Central

Yu, Kezi; Quirk, J. Gerald

2017-01-01

In this paper, we propose an application of non-parametric Bayesian (NPB) models for classification of fetal heart rate (FHR) recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP) and the Chinese restaurant process with finite capacity (CRFC). Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR) recordings in a real-time setting. PMID:28953927

Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.

PubMed

Xue, Hongqi; Wu, Shuang; Wu, Yichao; Ramirez Idarraga, Juan C; Wu, Hulin

2018-05-02

Mechanism-driven low-dimensional ordinary differential equation (ODE) models are often used to model viral dynamics at cellular levels and epidemics of infectious diseases. However, low-dimensional mechanism-based ODE models are limited for modeling infectious diseases at molecular levels such as transcriptomic or proteomic levels, which is critical to understand pathogenesis of diseases. Although linear ODE models have been proposed for gene regulatory networks (GRNs), nonlinear regulations are common in GRNs. The reconstruction of large-scale nonlinear networks from time-course gene expression data remains an unresolved issue. Here, we use high-dimensional nonlinear additive ODEs to model GRNs and propose a 4-step procedure to efficiently perform variable selection for nonlinear ODEs. To tackle the challenge of high dimensionality, we couple the 2-stage smoothing-based estimation method for ODEs and a nonlinear independence screening method to perform variable selection for the nonlinear ODE models. We have shown that our method possesses the sure screening property and it can handle problems with non-polynomial dimensionality. Numerical performance of the proposed method is illustrated with simulated data and a real data example for identifying the dynamic GRN of Saccharomyces cerevisiae. Copyright © 2018 John Wiley & Sons, Ltd.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

A High Performance Computing Approach to the Simulation of Fluid Solid Interaction Problems with Rigid and Flexible Components (Open Access Publisher’s Version)

DTIC Science & Technology

2014-08-01

performance computing, smoothed particle hydrodynamics, rigid body dynamics, flexible body dynamics ARMAN PAZOUKI ∗, RADU SERBAN ∗, DAN NEGRUT ∗ A...HIGH PERFORMANCE COMPUTING APPROACH TO THE SIMULATION OF FLUID-SOLID INTERACTION PROBLEMS WITH RIGID AND FLEXIBLE COMPONENTS This work outlines a unified...are implemented to model rigid and flexible multibody dynamics. The two- way coupling of the fluid and solid phases is supported through use of

Simulating the Use of Alternative Fuels in a Turbofan Engine

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Chin, Jeffrey Chevoor; Liu, Yuan

2013-01-01

The interest in alternative fuels for aviation has created a need to evaluate their effect on engine performance. The use of dynamic turbofan engine simulations enables the comparative modeling of the performance of these fuels on a realistic test bed in terms of dynamic response and control compared to traditional fuels. The analysis of overall engine performance and response characteristics can lead to a determination of the practicality of using specific alternative fuels in commercial aircraft. This paper describes a procedure to model the use of alternative fuels in a large commercial turbofan engine, and quantifies their effects on engine and vehicle performance. In addition, the modeling effort notionally demonstrates that engine performance may be maintained by modifying engine control system software parameters to account for the alternative fuel.

Modelling the performance of the tapered artery heat pipe design for use in the radiator of the solar dynamic power system of the NASA Space Station

NASA Technical Reports Server (NTRS)

Evans, Austin Lewis

1988-01-01

The paper presents a computer program developed to model the steady-state performance of the tapered artery heat pipe for use in the radiator of the solar dynamic power system of the NASA Space Station. The program solves six governing equations to ascertain which one is limiting the maximum heat transfer rate of the heat pipe. The present model appeared to be slightly better than the LTV model in matching the 1-g data for the standard 15-ft test heat pipe.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Extraction-Separation Performance and Dynamic Modeling of Orion Test Vehicles with Adams Simulation: 2nd Edition

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Varela, Jose G.; Bernatovich, Michael A.

2015-01-01

NASA's Orion Capsule Parachute Assembly System (CPAS) project has advanced into the third generation of its parachute test campaign and requires technically comprehensive modeling capabilities to simulate multi-body dynamics (MBD) of test articles released from a C-17. Safely extracting a 30,000 lbm mated test article from a C-17 and performing stable mid-air separation maneuvers requires an understanding of the interaction between elements in the test configuration and how they are influenced by extraction parachute performance, aircraft dynamics, aerodynamics, separation dynamics, and kinetic energy experienced by the system. During the real-time extraction and deployment sequences, these influences can be highly unsteady and difficult to bound. An avionics logic window based on time, pitch, and pitch rate is used to account for these effects and target a favorable separation state in real time. The Adams simulation has been employed to fine-tune this window, as well as predict and reconstruct the coupled dynamics of the Parachute Test Vehicle (PTV) and Cradle Platform Separation System (CPSS) from aircraft extraction through the mid-air separation event. The test-technique for the extraction of CPAS test articles has evolved with increased complexity and requires new modeling concepts to ensure the test article is delivered to a stable test condition for the programmer phase. Prompted by unexpected dynamics and hardware malfunctions in drop tests, these modeling improvements provide a more accurate loads prediction by incorporating a spring-damper line-model derived from the material properties. The qualification phase of CPAS testing is on the horizon and modeling increasingly complex test-techniques with Adams is vital to successfully qualify the Orion parachute system for human spaceflight.

Two-Speed Gearbox Dynamic Simulation Predictions and Test Validation

NASA Technical Reports Server (NTRS)

Lewicki, David G.; DeSmidt, Hans; Smith, Edward C.; Bauman, Steven W.

2010-01-01

Dynamic simulations and experimental validation tests were performed on a two-stage, two-speed gearbox as part of the drive system research activities of the NASA Fundamental Aeronautics Subsonics Rotary Wing Project. The gearbox was driven by two electromagnetic motors and had two electromagnetic, multi-disk clutches to control output speed. A dynamic model of the system was created which included a direct current electric motor with proportional-integral-derivative (PID) speed control, a two-speed gearbox with dual electromagnetically actuated clutches, and an eddy current dynamometer. A six degree-of-freedom model of the gearbox accounted for the system torsional dynamics and included gear, clutch, shaft, and load inertias as well as shaft flexibilities and a dry clutch stick-slip friction model. Experimental validation tests were performed on the gearbox in the NASA Glenn gear noise test facility. Gearbox output speed and torque as well as drive motor speed and current were compared to those from the analytical predictions. The experiments correlate very well with the predictions, thus validating the dynamic simulation methodologies.

Canonical formalism for modelling and control of rigid body dynamics.

PubMed

Gurfil, P

2005-12-01

This paper develops a new paradigm for stabilization of rigid-body dynamics. The state-space model is formulated using canonical elements, known as the Serret-Andoyer (SA) variables, thus far scarcely used for engineering applications. The main feature of the SA formalism is the reduction of the dynamics via the underlying symmetry stemming from conservation of angular momentum and rotational kinetic energy. The controllability of the system model is examined using the notion of accessibility, and is shown to be accessible from all points. Based on the accessibility proof, two nonlinear asymptotic feedback stabilizers are developed: a damping feedback is designed based on the Jurdjevic-Quinn method, and a Hamiltonian controller is derived by using the Hamiltonian as a natural Lyapunov function for the closed-loop dynamics. It is shown that the Hamiltonian control is both passive and inverse optimal with respect to a meaningful performance index. The performance of the new controllers is examined and compared using simulations of realistic scenarios from the satellite attitude dynamics field.

A Dynamic Simulation Model of Organizational Culture and Business Strategy Effects on Performance

NASA Astrophysics Data System (ADS)

Trivellas, Panagiotis; Reklitis, Panagiotis; Konstantopoulos, Nikolaos

2007-12-01

In the past two decades, organizational culture literature has gained tremendous interest for both academic and practitioners. This is based not only on the suggestion that culture is related to performance, but also on the view that it is subject of direct managerial control and manipulation to the desired direction. In the present paper, we adopt Competing Values Framework (CVF) to operationalise organizational culture and Porter's typology to conceptualize business strategy (cost leadership, innovative and marketing differentiation, and focus). Although simulation of social events is a quite difficult task, since there are so many considerations (not all well understood) involved, in the present study we developed a dynamic model to simulate the organizational culture and strategy effects on financial performance. Data obtained from a six-year survey in the banking sector of a European developing economy was used for the proposed dynamic model development.

Variable friction device for structural control based on duo-servo vehicle brake: Modeling and experimental validation

NASA Astrophysics Data System (ADS)

Cao, Liang; Downey, Austin; Laflamme, Simon; Taylor, Douglas; Ricles, James

2015-07-01

Supplemental damping can be used as a cost-effective method to reduce structural vibrations. In particular, passive systems are now widely accepted and have numerous applications in the field. However, they are typically tuned to specific excitations and their performances are bandwidth-limited. A solution is to use semi-active devices, which have shown to be capable of substantially enhanced mitigation performance. The authors have recently proposed a new type of semi-active device, which consists of a variable friction mechanism based on a vehicle duo-servo drum brake, a mechanically robust and reliable technology. The theoretical performance of the proposed device has been previously demonstrated via numerical simulations. In this paper, we further the understanding of the device, termed Modified Friction Device (MFD) by fabricating a small scale prototype and characterizing its dynamic behavior. While the dynamics of friction is well understood for automotive braking technology, we investigate for the first time the dynamic behavior of this friction mechanism at low displacements and velocities, in both forward and backward directions, under various hydraulic pressures. A modified 3-stage dynamic model is introduced. A LuGre friction model is used to characterize the friction zone (Stage 1), and two pure stiffness regions to characterize the dynamics of the MFD once the rotation is reversed and the braking shoes are sticking to the drum (Stage 2) and the rapid build up of forces once the shoes are held by the anchor pin (Stage 3). The proposed model is identified experimentally by subjecting the prototype to harmonic excitations. It is found that the proposed model can be used to characterize the dynamics of the MFD, and that the largest fitting error arises at low velocity under low pressure input. The model is then verified by subjecting the MFD to two different earthquake excitations under different pressure inputs. The model is capable of tracking the device's response, despite a lower fitting performance under low pressure and small force output, as it was found in the harmonic tests due to the possible nonlinearity in Stage 2 of the model.

Simulating Effects of High Angle of Attack on Turbofan Engine Performance

NASA Technical Reports Server (NTRS)

Liu, Yuan; Claus, Russell W.; Litt, Jonathan S.; Guo, Ten-Huei

2013-01-01

A method of investigating the effects of high angle of attack (AOA) flight on turbofan engine performance is presented. The methodology involves combining a suite of diverse simulation tools. Three-dimensional, steady-state computational fluid dynamics (CFD) software is used to model the change in performance of a commercial aircraft-type inlet and fan geometry due to various levels of AOA. Parallel compressor theory is then applied to assimilate the CFD data with a zero-dimensional, nonlinear, dynamic turbofan engine model. The combined model shows that high AOA operation degrades fan performance and, thus, negatively impacts compressor stability margins and engine thrust. In addition, the engine response to high AOA conditions is shown to be highly dependent upon the type of control system employed.

Studies of turbulence models in a computational fluid dynamics model of a blood pump.

PubMed

Song, Xinwei; Wood, Houston G; Day, Steven W; Olsen, Don B

2003-10-01

Computational fluid dynamics (CFD) is used widely in design of rotary blood pumps. The choice of turbulence model is not obvious and plays an important role on the accuracy of CFD predictions. TASCflow (ANSYS Inc., Canonsburg, PA, U.S.A.) has been used to perform CFD simulations of blood flow in a centrifugal left ventricular assist device; a k-epsilon model with near-wall functions was used in the initial numerical calculation. To improve the simulation, local grids with special distribution to ensure the k-omega model were used. Iterations have been performed to optimize the grid distribution and turbulence modeling and to predict flow performance more accurately comparing to experimental data. A comparison of k-omega model and experimental measurements of the flow field obtained by particle image velocimetry shows better agreement than k-epsilon model does, especially in the near-wall regions.

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints. PMID:19003514

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Damage-mitigating control of aircraft for high performance and life extension

NASA Astrophysics Data System (ADS)

Caplin, Jeffrey

1998-12-01

A methodology is proposed for the synthesis of a Damage-Mitigating Control System for a high-performance fighter aircraft. The design of such a controller involves consideration of damage to critical points of the structure, as well as the performance requirements of the aircraft. This research is interdisciplinary, and brings existing knowledge in the fields of unsteady aerodynamics, structural dynamics, fracture mechanics, and control theory together to formulate a new approach towards aircraft flight controller design. A flexible wing model is formulated using the Finite Element Method, and the important mode shapes and natural frequencies are identified. The Doublet Lattice Method is employed to develop an unsteady flow model for computation of the unsteady aerodynamic loads acting on the wing due to rigid-body maneuvers and structural deformation. These two models are subsequently incorporated into a pre-existing nonlinear rigid-body aircraft flight-dynamic model. A family of robust Damage-Mitigating Controllers is designed using the Hinfinity-optimization and mu-synthesis method. In addition to weighting the error between the ideal performance and the actual performance of the aircraft, weights are also placed on the strain amplitude at the root of each wing. The results show significant savings in fatigue life of the wings while retaining the dynamic performance of the aircraft.

Application of the Tool for Turbine Engine Closed-Loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

NASA Technical Reports Server (NTRS)

Csank, Jeffrey T.; Zinnecker, Alicia M.

2014-01-01

The aircraft engine design process seeks to achieve the best overall system-level performance, weight, and cost for a given engine design. This is achieved by a complex process known as systems analysis, where steady-state simulations are used to identify trade-offs that should be balanced to optimize the system. The steady-state simulations and data on which systems analysis relies may not adequately capture the true performance trade-offs that exist during transient operation. Dynamic Systems Analysis provides the capability for assessing these trade-offs at an earlier stage of the engine design process. The concept of dynamic systems analysis and the type of information available from this analysis are presented in this paper. To provide this capability, the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) was developed. This tool aids a user in the design of a power management controller to regulate thrust, and a transient limiter to protect the engine model from surge at a single flight condition (defined by an altitude and Mach number). Results from simulation of the closed-loop system may be used to estimate the dynamic performance of the model. This enables evaluation of the trade-off between performance and operability, or safety, in the engine, which could not be done with steady-state data alone. A design study is presented to compare the dynamic performance of two different engine models integrated with the TTECTrA software.

A cable-driven parallel robots application: modelling and simulation of a dynamic cable model in Dymola

NASA Astrophysics Data System (ADS)

Othman, M. F.; Kurniawan, R.; Schramm, D.; Ariffin, A. K.

2018-05-01

Modeling a cable model in multibody dynamics simulation tool which dynamically varies in length, mass and stiffness is a challenging task. Simulation of cable-driven parallel robots (CDPR) for instance requires a cable model that can dynamically change in length for every desired pose of the platform. Thus, in this paper, a detailed procedure for modeling and simulation of a dynamic cable model in Dymola is proposed. The approach is also applicable for other types of Modelica simulation environments. The cable is modeled using standard mechanical elements like mass, spring, damper and joint. The parameters of the cable model are based on the factsheet of the manufacturer and experimental results. Its dynamic ability is tested by applying it on a complete planar CDPR model in which the parameters are based on a prototype named CABLAR, which is developed in Chair of Mechatronics, University of Duisburg-Essen. The prototype has been developed to demonstrate an application of CDPR as a goods storage and retrieval machine. The performance of the cable model during the simulation is analyzed and discussed.

On the dynamical vs. thermodynamical performance of a β-type Stirling engine

NASA Astrophysics Data System (ADS)

Reséndiz-Antonio, Margarita; Santillán, Moisés

2014-09-01

In this work we present a simple mathematical model for a β-type Stirling engine. Despite its simplicity, the model considers all the engine’s relevant thermodynamic and mechanical aspects. The dynamic behavior of the model equation of motion is analyzed in order to obtain the sufficient conditions for engine cycling and to study the stability of the stationary regime. The performance of the engine’s thermodynamic part is also investigated. As a matter of fact, we found that it corresponds to a Carnot engine.

A dynamic model of stress and sustained attention

NASA Technical Reports Server (NTRS)

Hancock, Peter A.; Warm, Joel S.

2003-01-01

This paper examines the effects of stress on sustained attention. With recognition of the task itself as the major source of cognitive stress, a dynamic model is presented that addresses the effects of stress on vigilance and, potentially, a wide variety of attention performance tasks.

Controlling aliased dynamics in motion systems? An identification for sampled-data control approach

NASA Astrophysics Data System (ADS)

Oomen, Tom

2014-07-01

Sampled-data control systems occasionally exhibit aliased resonance phenomena within the control bandwidth. The aim of this paper is to investigate the aspect of these aliased dynamics with application to a high performance industrial nano-positioning machine. This necessitates a full sampled-data control design approach, since these aliased dynamics endanger both the at-sample performance and the intersample behaviour. The proposed framework comprises both system identification and sampled-data control. In particular, the sampled-data control objective necessitates models that encompass the intersample behaviour, i.e., ideally continuous time models. Application of the proposed approach on an industrial wafer stage system provides a thorough insight and new control design guidelines for controlling aliased dynamics.

Dynamic analysis of Space Shuttle/RMS configuration using continuum approach

NASA Technical Reports Server (NTRS)

Ramakrishnan, Jayant; Taylor, Lawrence W., Jr.

1994-01-01

The initial assembly of Space Station Freedom involves the Space Shuttle, its Remote Manipulation System (RMS) and the evolving Space Station Freedom. The dynamics of this coupled system involves both the structural and the control system dynamics of each of these components. The modeling and analysis of such an assembly is made even more formidable by kinematic and joint nonlinearities. The current practice of modeling such flexible structures is to use finite element modeling in which the mass and interior dynamics is ignored between thousands of nodes, for each major component. The model characteristics of only tens of modes are kept out of thousands which are calculated. The components are then connected by approximating the boundary conditions and inserting the control system dynamics. In this paper continuum models are used instead of finite element models because of the improved accuracy, reduced number of model parameters, the avoidance of model order reduction, and the ability to represent the structural and control system dynamics in the same system of equations. Dynamic analysis of linear versions of the model is performed and compared with finite element model results. Additionally, the transfer matrix to continuum modeling is presented.

Parametric Study of the Effect of Membrane Tension on Sunshield Dynamics

NASA Technical Reports Server (NTRS)

Ross, Brian; Johnston, John D.; Smith, James

2002-01-01

The NGST sunshield is a lightweight, flexible structure consisting of pretensioned membranes supported by deployable booms. The structural dynamic behavior of the sunshield must be well understood in order to predict its influence on observatory performance. A 1/10th scale model of the sunshield has been developed for ground testing to provide data to validate modeling techniques for thin film membrane structures. The validated models can then be used to predict the behaviour of the full scale sunshield. This paper summarizes the most recent tests performed on the 1/10th scale sunshield to study the effect of membrane preload on sunshield dynamics. Topics to be covered include the test setup, procedures, and a summary of results.

Development of a Higher Fidelity Model for the Cascade Distillation Subsystem (CDS)

NASA Technical Reports Server (NTRS)

Perry, Bruce; Anderson, Molly

2014-01-01

Significant improvements have been made to the ACM model of the CDS, enabling accurate predictions of dynamic operations with fewer assumptions. The model has been utilized to predict how CDS performance would be impacted by changing operating parameters, revealing performance trade-offs and possibilities for improvement. CDS efficiency is driven by the THP coefficient of performance, which in turn is dependent on heat transfer within the system. Based on the remaining limitations of the simulation, priorities for further model development include: center dot Relaxing the assumption of total condensation center dot Incorporating dynamic simulation capability for the buildup of dissolved inert gasses in condensers center dot Examining CDS operation with more complex feeds center dot Extending heat transfer analysis to all surfaces

Standard representation and unified stability analysis for dynamic artificial neural network models.

PubMed

Kim, Kwang-Ki K; Patrón, Ernesto Ríos; Braatz, Richard D

2018-02-01

An overview is provided of dynamic artificial neural network models (DANNs) for nonlinear dynamical system identification and control problems, and convex stability conditions are proposed that are less conservative than past results. The three most popular classes of dynamic artificial neural network models are described, with their mathematical representations and architectures followed by transformations based on their block diagrams that are convenient for stability and performance analyses. Classes of nonlinear dynamical systems that are universally approximated by such models are characterized, which include rigorous upper bounds on the approximation errors. A unified framework and linear matrix inequality-based stability conditions are described for different classes of dynamic artificial neural network models that take additional information into account such as local slope restrictions and whether the nonlinearities within the DANNs are odd. A theoretical example shows reduced conservatism obtained by the conditions. Copyright © 2017. Published by Elsevier Ltd.

Observability and synchronization of neuron models.

PubMed

Aguirre, Luis A; Portes, Leonardo L; Letellier, Christophe

2017-10-01

Observability is the property that enables recovering the state of a dynamical system from a reduced number of measured variables. In high-dimensional systems, it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. The observability of a network of neuron models depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, to perform a study of observability using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, to study the emergence of phase synchronization in networks composed of neuron models. This is done performing multivariate singular spectrum analysis which, to the best of the authors' knowledge, has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization: (i) without having to measure all the state variables, but only one (that provides greatest observability) from each node and (ii) without having to estimate the phase.

Application of a new dynamic transport model to predict the evolution of performances throughout the nanofiltration of single salt solutions in concentration and diafiltration modes.

PubMed

Déon, Sébastien; Lam, Boukary; Fievet, Patrick

2018-06-01

Although many knowledge models describing the rejection of ionic compounds by nanofiltration membranes are available in literature, they are all used in full recycling mode. Indeed, both permeate and retentate streams are recycled in order to maintain constant concentrations in the feed solution. However, nanofiltration of real effluents is implemented either in concentration or diafiltration modes, for which the permeate stream is collected. In these conditions, concentrations progressively evolve during filtration and classical models fail to predict performances. In this paper, an improvement of the so called "Donnan Steric Pore Model", which includes both volume and concentration variations over time is proposed. This dynamic model is used here to predict the evolution of volumes and concentrations in both permeate and retentate streams during the filtration of salt solutions. This model was found to predict accurately the filtration performances with various salts whether the filtration is performed in concentration or diafiltration modes. The parameters of the usual model can be easily assessed from full batch experiments before being used in the dynamic version. Nevertheless, it is also highlighted that the variation of the membrane charge due to the evolution of feed concentration over time has to be taken into account in the model through the use of adsorption isotherms. Copyright © 2018 Elsevier Ltd. All rights reserved.

Action versus Result-Oriented Schemes in a Grassland Agroecosystem: A Dynamic Modelling Approach

PubMed Central

Sabatier, Rodolphe; Doyen, Luc; Tichit, Muriel

2012-01-01

Effects of agri-environment schemes (AES) on biodiversity remain controversial. While most AES are action-oriented, result-oriented and habitat-oriented schemes have recently been proposed as a solution to improve AES efficiency. The objective of this study was to compare action-oriented, habitat-oriented and result-oriented schemes in terms of ecological and productive performance as well as in terms of management flexibility. We developed a dynamic modelling approach based on the viable control framework to carry out a long term assessment of the three schemes in a grassland agroecosystem. The model explicitly links grazed grassland dynamics to bird population dynamics. It is applied to lapwing conservation in wet grasslands in France. We ran the model to assess the three AES scenarios. The model revealed the grazing strategies respecting ecological and productive constraints specific to each scheme. Grazing strategies were assessed by both their ecological and productive performance. The viable control approach made it possible to obtain the whole set of viable grazing strategies and therefore to quantify the management flexibility of the grassland agroecosystem. Our results showed that habitat and result-oriented scenarios led to much higher ecological performance than the action-oriented one. Differences in both ecological and productive performance between the habitat and result-oriented scenarios were limited. Flexibility of the grassland agroecosystem in the result-oriented scenario was much higher than in that of habitat-oriented scenario. Our model confirms the higher flexibility as well as the better ecological and productive performance of result-oriented schemes. A larger use of result-oriented schemes in conservation may also allow farmers to adapt their management to local conditions and to climatic variations. PMID:22496746

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

DOE PAGES

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine; ...

2017-12-15

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.« less

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

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

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.« less

Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

PubMed

Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

2014-04-02

The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

The development of an advanced generic solar dynamic heat receiver thermal model

NASA Technical Reports Server (NTRS)

Wu, Y. C.; Roschke, E. J.; Kohout, L.

1988-01-01

An advanced generic solar dynamic heat receiver thermal model under development which can analyze both orbital transient and orbital average conditions is discussed. This model can be used to study advanced receiver concepts, evaluate receiver concepts under development, analyze receiver thermal characteristics under various operational conditions, and evaluate solar dynamic system thermal performances in various orbit conditions. The model and the basic considerations that led to its creation are described, and results based on a set of baseline orbit, configuration, and operational conditions are presented to demonstrate the working of the receiver model.

Dynamic Analysis of Hammer Mechanism "Twin Hammer" of Impact Wrench

NASA Astrophysics Data System (ADS)

Konečný, M.; Slavík, J.

This paper describes function of the hammer mechanism "Twin hammer" the impact wrench, calculation of dynamic forces exerted on the mechanism and determining the contact pressures between the parts of the mechanism. The modelling of parts was performed in system Pro ENGINEER—standard. The simulation and finding dynamic forces was performed in advanced module Pro ENGINEER—mechanism design and finding contacts pressures in modul Pro ENGENEER—mechanica.

Thrust vector control algorithm design for the Cassini spacecraft

NASA Technical Reports Server (NTRS)

Enright, Paul J.

1993-01-01

This paper describes a preliminary design of the thrust vector control algorithm for the interplanetary spacecraft, Cassini. Topics of discussion include flight software architecture, modeling of sensors, actuators, and vehicle dynamics, and controller design and analysis via classical methods. Special attention is paid to potential interactions with structural flexibilities and propellant dynamics. Controller performance is evaluated in a simulation environment built around a multi-body dynamics model, which contains nonlinear models of the relevant hardware and preliminary versions of supporting attitude determination and control functions.

Dynamic performance and mechanical model analysis of a shear thickening fluid damper

NASA Astrophysics Data System (ADS)

Zhao, Qian; He, Yonghui; Yao, Hongliang; Wen, Bangchun

2018-07-01

This paper presents an experimental study of the dynamic performance of a self-developed shear thickening fluid (STF) damper and its mechanical model was proposed by nonlinear fitting. First, STF samples with different mass fraction and dispersion medium were fabricated by nano fumed silica and polyethylene glycol, and its rheological properties were investigated by a rheometer. Second, a smart STF damper was developed and manufactured. Its dynamic properties were experimentally investigated by establishing a vibration test bench, and results indicated that the STF damper can output variable damping force by controlling the loading frequency, loading amplitude and fluid gap. Third, the Bouc–Wen model was proposed to address the dynamic properties of STF damper, and mechanical model analysis was carried out by comparing several fitting functions. It verified that the Bouc–Wen hysteresis model can be better used to describe the nonlinear stiffness, nonlinear damping and rate-dependence characteristics of the STF damper. All these investigations can offer an effective guidance for further theoretical and application study of the smart STF damper in energy dissipation fields.

Dynamic imaging model and parameter optimization for a star tracker.

PubMed

Yan, Jinyun; Jiang, Jie; Zhang, Guangjun

2016-03-21

Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters.

Performance of Smagorinsky and dynamic models in near surface turbulence

NASA Astrophysics Data System (ADS)

Brasseur, James G.; Juneja, Anurag

1997-11-01

In LES of high-Reynolds-number wall bounded turbulence such as the atmospheric boundary layer (ABL), a viscous sublayer either does not exist or is within the first grid cell, and some integral scale motions are necessarily under-resolved at the first few grid locations. Here the subgrid terms dominate the evolution of resolved velocity and the SGS model performance becomes crucial. To develop improved closures for surface layer turbulence (under-resolved and anisotropic), we explore (a) why current SGS closures fail and (b) what needs to be fixed. We evaluate the performance of the Smagorinsky and dynamic models using DNS data from shear- and buoyancy-driven turbulence as a function of filter cutoff location. We find that the underlying assumption of good alignment between the subgrid stress and resolved strain-rate tensors is not correct in general. More importantly, the Smagorinsky model incorrectly predicts a strong preference in the direction of the SGS stress divergence vector, a spurious prediction that is directly related to the anisotropic structure of the resolved turbulence field. This, and its under-estimation of the SGS pressure gradient, are likely sources of the errors observed in LES of the ABL. Whereas the dynamic formulations do a better job predicting some SGS dynamics, the model fails when the filter cutoff is near an integral scale, and predicts unreasonable fluctuation levels-- although performance is sensitive to type of averaging. *supported by ARO grant DAAL03-92-0117.

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

NASA Technical Reports Server (NTRS)

Todling, Ricardo; Cohn, Stephen E.

1994-01-01

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Optimal design of high-speed loading spindle based on ABAQUS

NASA Astrophysics Data System (ADS)

Yang, Xudong; Dong, Yu; Ge, Qingkuan; Yang, Hai

2017-12-01

The three-dimensional model of high-speed loading spindle is established by using ABAQUS’s modeling module. A finite element analysis model of high-speed loading spindle was established by using spring element to simulate bearing boundary condition. The static and dynamic performance of the spindle structure with different specifications of the rectangular spline and the different diameter neck of axle are studied in depth, and the influence of different spindle span on the static and dynamic performance of the high-speed loading spindle is studied. Finally, the optimal structure of the high-speed loading spindle is obtained. The results provide a theoretical basis for improving the overall performance of the test-bed

Dynamic contraction behaviour of pneumatic artificial muscle

NASA Astrophysics Data System (ADS)

Doumit, Marc D.; Pardoel, Scott

2017-07-01

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

Application of the GRC Stirling Convertor System Dynamic Model

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.; Schreiber, Jeffrey G. (Technical Monitor)

2004-01-01

The GRC Stirling Convertor System Dynamic Model (SDM) has been developed to simulate dynamic performance of power systems incorporating free-piston Stirling convertors. This paper discusses its use in evaluating system dynamics and other systems concerns. Detailed examples are provided showing the use of the model in evaluation of off-nominal operating conditions. The many degrees of freedom in both the mechanical and electrical domains inherent in the Stirling convertor and the nonlinear dynamics make simulation an attractive analysis tool in conjunction with classical analysis. Application of SDM in studying the relationship of the size of the resonant circuit quality factor (commonly referred to as Q) in the various resonant mechanical and electrical sub-systems is discussed.

An evidence accumulation model for conflict detection performance in a simulated air traffic control task.

PubMed

Neal, Andrew; Kwantes, Peter J

2009-04-01

The aim of this article is to develop a formal model of conflict detection performance. Our model assumes that participants iteratively sample evidence regarding the state of the world and accumulate it over time. A decision is made when the evidence reaches a threshold that changes over time in response to the increasing urgency of the task. Two experiments were conducted to examine the effects of conflict geometry and timing on response proportions and response time. The model is able to predict the observed pattern of response times, including a nonmonotonic relationship between distance at point of closest approach and response time, as well as effects of angle of approach and relative velocity. The results demonstrate that evidence accumulation models provide a good account of performance on a conflict detection task. Evidence accumulation models are a form of dynamic signal detection theory, allowing for the analysis of response times as well as response proportions, and can be used for simulating human performance on dynamic decision tasks.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

NASA Astrophysics Data System (ADS)

Hong, S.-M.; Jung, B.-H.; Ruan, D.

2011-03-01

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

PubMed

Hong, S-M; Jung, B-H; Ruan, D

2011-03-21

Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively low observation rate. Sensitivity analysis indicates its robustness toward the choice of parameters. Its simplicity, robustness and low computation cost makes the proposed local dynamic model an attractive tool for real-time prediction with system latencies below 0.4 s.

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.

A comprehensive analytical model of rotorcraft aerodynamics and dynamics. Part 2: User's manual

NASA Technical Reports Server (NTRS)

Johnson, W.

1980-01-01

The use of a computer program for a comprehensive analytical model of rotorcraft aerodynamics and dynamics is described. The program calculates the loads and motion of helicopter rotors and airframe. First the trim solution is obtained, then the flutter, flight dynamics, and/or transient behavior can be calculated. Either a new job can be initiated or further calculations can be performed for an old job.

Dynamic performances analysis of a real vehicle driving

NASA Astrophysics Data System (ADS)

Abdullah, M. A.; Jamil, J. F.; Salim, M. A.

2015-12-01

Vehicle dynamic is the effects of movement of a vehicle generated from the acceleration, braking, ride and handling activities. The dynamic behaviours are determined by the forces from tire, gravity and aerodynamic which acting on the vehicle. This paper emphasizes the analysis of vehicle dynamic performance of a real vehicle. Real driving experiment on the vehicle is conducted to determine the effect of vehicle based on roll, pitch, and yaw, longitudinal, lateral and vertical acceleration. The experiment is done using the accelerometer to record the reading of the vehicle dynamic performance when the vehicle is driven on the road. The experiment starts with weighing a car model to get the center of gravity (COG) to place the accelerometer sensor for data acquisition (DAQ). The COG of the vehicle is determined by using the weight of the vehicle. A rural route is set to launch the experiment and the road conditions are determined for the test. The dynamic performance of the vehicle are depends on the road conditions and driving maneuver. The stability of a vehicle can be controlled by the dynamic performance analysis.

Editorial: Cognitive Architectures, Model Comparison and AGI

NASA Astrophysics Data System (ADS)

Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter

2010-12-01

Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to benchmarks of intelligent behavior such as human performance. Significant methodological challenges arise, however, when trying to extend approaches used to compare model and human performance from tightly controlled laboratory tasks to complex tasks involving more open-ended behavior. This paper describes a model comparison challenge built around a dynamic control task, the Dynamic Stocks and Flows. We present and discuss distinct approaches to evaluating performance and comparing models. Lessons drawn from this challenge are discussed in light of the challenge of using cognitive architectures to achieve Artificial General Intelligence.

Clinical time series prediction: Toward a hierarchical dynamical system framework.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-09-01

Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

Aeroelasticity and mechanical stability report, 0.27 Mach scale model of the YAH-64 advanced attack helicopter

NASA Technical Reports Server (NTRS)

Straub, F. K.; Johnston, R. A.

1987-01-01

A 27% dynamically scaled model of the YAH-64 Advanced Attack Helicopter main rotor and hub has been designed and fabricated. The model will be tested in the NASA Langley Research Center V/STOL wind tunnel using the General Rotor Model System (GRMS). This report documents the studies performed to ensure dynamic similarity of the model with its full scale parent. It also contains a preliminary aeroelastic and aeromechanical substantiation for the rotor installation in the wind tunnel. From the limited studies performed no aeroelastic stability or load problems are projected. To alleviate a projected ground resonance problem, a modification of the roll characteristics of the GRMS is recommended.

Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

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

Harrison, Thomas J.

2014-03-01

This report documents the efforts to perform dynamic model validation on the Eastern Interconnection (EI) by modeling governor deadband. An on-peak EI dynamic model is modified to represent governor deadband characteristics. Simulation results are compared with synchrophasor measurements collected by the Frequency Monitoring Network (FNET/GridEye). The comparison shows that by modeling governor deadband the simulated frequency response can closely align with the actual system response.

Parameterized Linear Longitudinal Airship Model

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph

2010-01-01

A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics

Design, testing, and performance of a hybrid micro vehicle---The Hopping Rotochute

NASA Astrophysics Data System (ADS)

Beyer, Eric W.

The Hopping Rotochute is a new hybrid micro vehicle that has been developed to robustly explore environments with rough terrain while minimizing energy consumption over long periods of time. The device consists of a small coaxial rotor system housed inside a lightweight cage. The vehicle traverses an area by intermittently powering a small electric motor which drives the rotor system, allowing the vehicle to hop over obstacles of various shapes and sizes. A movable internal mass controls the direction of travel while the egg-like exterior shape and low mass center allows the vehicle to passively reorient itself to an upright attitude when in contact with the ground. This dissertation presents the design, fabrication, and testing of a radio-controlled Hopping Rotochute prototype as well as an analytical study of the flight performance of the device. The conceptual design iterations are first outlined which were driven by the mission and system requirements assigned to the vehicle. The aerodynamic, mechanical, and electrical design of a prototype is then described, based on the final conceptual design, with particular emphasis on the fundamental trades that must be negotiated for this type of hopping vehicle. The fabrication and testing of this prototype is detailed as well as experimental results obtained from a motion capture system. Basic flight performance of the prototype are reported which demonstrates that the Hopping Rotochute satisfies all appointed system requirements. A dynamic model of the Hopping Rotochute is also developed in this thesis and employed to predict the flight performance of the vehicle. The dynamic model includes aerodynamic loads from the body and rotor system as well as a soft contact model to estimate the forces and moments during ground contact. The experimental methods used to estimate the dynamic model parameters are described while comparisons between measured and simulated motion are presented. Good correlation between these motions is shown to validate the dynamic model. Using the validated dynamic model, simulations were performed to better understand the dynamics of the device. In addition, key parameters such as system weight, rotor speed, internal mass weight and location, as well as battery capacity are varied to explore and optimize flight performance characteristics such as single hop height and range, number of hops, and total achievable range. The sensitivity of the Hopping Rotochute to atmospheric winds is also investigated as is the ability of the device to perform trajectory shaping.

A Dynamic Bayesian Network Based Structural Learning towards Automated Handwritten Digit Recognition

NASA Astrophysics Data System (ADS)

Pauplin, Olivier; Jiang, Jianmin

Pattern recognition using Dynamic Bayesian Networks (DBNs) is currently a growing area of study. In this paper, we present DBN models trained for classification of handwritten digit characters. The structure of these models is partly inferred from the training data of each class of digit before performing parameter learning. Classification results are presented for the four described models.

Dynamics and control of quadcopter using linear model predictive control approach

NASA Astrophysics Data System (ADS)

Islam, M.; Okasha, M.; Idres, M. M.

2017-12-01

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

Development of a multicomponent force and moment balance for water tunnel applications, volume 2

NASA Technical Reports Server (NTRS)

Suarez, Carlos J.; Malcolm, Gerald N.; Kramer, Brian R.; Smith, Brooke C.; Ayers, Bert F.

1994-01-01

The principal objective of this research effort was to develop a multicomponent strain gauge balance to measure forces and moments on models tested in flow visualization water tunnels. Static experiments (which are discussed in Volume 1 of this report) were conducted, and the results showed good agreement with wind tunnel data on similar configurations. Dynamic experiments, which are the main topic of this Volume, were also performed using the balance. Delta wing models and two F/A-18 models were utilized in a variety of dynamic tests. This investigation showed that, as expected, the values of the inertial tares are very small due to the low rotating rates required in a low-speed water tunnel and can, therefore, be ignored. Oscillations in pitch, yaw and roll showed hysteresis loops that compared favorably to data from dynamic wind tunnel experiments. Pitch-up and hold maneuvers revealed the long persistence, or time-lags, of some of the force components in response to the motion. Rotary-balance experiments were also successfully performed. The good results obtained in these dynamic experiments bring a whole new dimension to water tunnel testing and emphasize the importance of having the capability to perform simultaneous flow visualization and force/moment measurements during dynamic situations.

Dynamic Circadian Modulation in a Biomathematical Model for the Effects of Sleep and Sleep Loss on Waking Neurobehavioral Performance

PubMed Central

McCauley, Peter; Kalachev, Leonid V.; Mollicone, Daniel J.; Banks, Siobhan; Dinges, David F.; Van Dongen, Hans P. A.

2013-01-01

Recent experimental observations and theoretical advances have indicated that the homeostatic equilibrium for sleep/wake regulation—and thereby sensitivity to neurobehavioral impairment from sleep loss—is modulated by prior sleep/wake history. This phenomenon was predicted by a biomathematical model developed to explain changes in neurobehavioral performance across days in laboratory studies of total sleep deprivation and sustained sleep restriction. The present paper focuses on the dynamics of neurobehavioral performance within days in this biomathematical model of fatigue. Without increasing the number of model parameters, the model was updated by incorporating time-dependence in the amplitude of the circadian modulation of performance. The updated model was calibrated using a large dataset from three laboratory experiments on psychomotor vigilance test (PVT) performance, under conditions of sleep loss and circadian misalignment; and validated using another large dataset from three different laboratory experiments. The time-dependence of circadian amplitude resulted in improved goodness-of-fit in night shift schedules, nap sleep scenarios, and recovery from prior sleep loss. The updated model predicts that the homeostatic equilibrium for sleep/wake regulation—and thus sensitivity to sleep loss—depends not only on the duration but also on the circadian timing of prior sleep. This novel theoretical insight has important implications for predicting operator alertness during work schedules involving circadian misalignment such as night shift work. Citation: McCauley P; Kalachev LV; Mollicone DJ; Banks S; Dinges DF; Van Dongen HPA. Dynamic circadian modulation in a biomathematical model for the effects of sleep and sleep loss on waking neurobehavioral performance. SLEEP 2013;36(12):1987-1997. PMID:24293775

Effects of Four Different Regulatory Mechanisms on the Dynamics of Gene Regulatory Cascades

NASA Astrophysics Data System (ADS)

Hansen, Sabine; Krishna, Sandeep; Semsey, Szabolcs; Lo Svenningsen, Sine

2015-07-01

Gene regulatory cascades (GRCs) are common motifs in cellular molecular networks. A given logical function in these cascades, such as the repression of the activity of a transcription factor, can be implemented by a number of different regulatory mechanisms. The potential consequences for the dynamic performance of the GRC of choosing one mechanism over another have not been analysed systematically. Here, we report the construction of a synthetic GRC in Escherichia coli, which allows us for the first time to directly compare and contrast the dynamics of four different regulatory mechanisms, affecting the transcription, translation, stability, or activity of a transcriptional repressor. We developed a biologically motivated mathematical model which is sufficient to reproduce the response dynamics determined by experimental measurements. Using the model, we explored the potential response dynamics that the constructed GRC can perform. We conclude that dynamic differences between regulatory mechanisms at an individual step in a GRC are often concealed in the overall performance of the GRC, and suggest that the presence of a given regulatory mechanism in a certain network environment does not necessarily mean that it represents a single optimal evolutionary solution.

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

A coarse-grained model of microtubule self-assembly

NASA Astrophysics Data System (ADS)

Regmi, Chola; Cheng, Shengfeng

Microtubules play critical roles in cell structures and functions. They also serve as a model system to stimulate the next-generation smart, dynamic materials. A deep understanding of their self-assembly process and biomechanical properties will not only help elucidate how microtubules perform biological functions, but also lead to exciting insight on how microtubule dynamics can be altered or even controlled for specific purposes such as suppressing the division of cancer cells. Combining all-atom molecular dynamics (MD) simulations and the essential dynamics coarse-graining method, we construct a coarse-grained (CG) model of the tubulin protein, which is the building block of microtubules. In the CG model a tubulin dimer is represented as an elastic network of CG sites, the locations of which are determined by examining the protein dynamics of the tubulin and identifying the essential dynamic domains. Atomistic MD modeling is employed to directly compute the tubulin bond energies in the surface lattice of a microtubule, which are used to parameterize the interactions between CG building blocks. The CG model is then used to study the self-assembly pathways, kinetics, dynamics, and nanomechanics of microtubules.

A forward model-based validation of cardiovascular system identification

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.

2001-01-01

We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.

The dynamic model of enterprise revenue management

NASA Astrophysics Data System (ADS)

Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.

2017-01-01

The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.

Development of Novel PEM Membrane and Multiphase CD Modeling of PEM Fuel Cell

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

K. J. Berry; Susanta Das

2009-12-30

To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtainedmore » from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance. To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtained from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance.« less

On the Impact of Execution Models: A Case Study in Computational Chemistry

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

Chavarría-Miranda, Daniel; Halappanavar, Mahantesh; Krishnamoorthy, Sriram

2015-05-25

Efficient utilization of high-performance computing (HPC) platforms is an important and complex problem. Execution models, abstract descriptions of the dynamic runtime behavior of the execution stack, have significant impact on the utilization of HPC systems. Using a computational chemistry kernel as a case study and a wide variety of execution models combined with load balancing techniques, we explore the impact of execution models on the utilization of an HPC system. We demonstrate a 50 percent improvement in performance by using work stealing relative to a more traditional static scheduling approach. We also use a novel semi-matching technique for load balancingmore » that has comparable performance to a traditional hypergraph-based partitioning implementation, which is computationally expensive. Using this study, we found that execution model design choices and assumptions can limit critical optimizations such as global, dynamic load balancing and finding the correct balance between available work units and different system and runtime overheads. With the emergence of multi- and many-core architectures and the consequent growth in the complexity of HPC platforms, we believe that these lessons will be beneficial to researchers tuning diverse applications on modern HPC platforms, especially on emerging dynamic platforms with energy-induced performance variability.« less

A Flight Prediction for Performance of the SWAS Solar Array Deployment Mechanism

NASA Technical Reports Server (NTRS)

Seniderman, Gary; Daniel, Walter K.

1999-01-01

The focus of this paper is a comparison of ground-based solar array deployment tests with the on-orbit deployment. The discussion includes a summary of the mechanisms involved and the correlation of a dynamics model with ground based test results. Some of the unique characteristics of the mechanisms are explained through the analysis of force and angle data acquired from the test deployments. The correlated dynamics model is then used to predict the performance of the system in its flight application.

Design and Analysis of Precise Pointing Systems

NASA Technical Reports Server (NTRS)

Kim, Young K.

2000-01-01

The mathematical models of Glovebox Integrated Microgravity Isolation Technology (g- LIMIT) dynamics/control system, which include six degrees of freedom (DOF) equations of motion, mathematical models of position sensors, accelerometers and actuators, and acceleration and position controller, were developed using MATLAB and TREETOPS simulations. Optimal control parameters of G-LIMIT control system were determined through sensitivity studies and its performance were evaluated with the TREETOPS model of G-LIMIT dynamics and control system. The functional operation and performance of the Tektronix DTM920 digital thermometer were studied and the inputs to the crew procedures and training of the DTM920 were documented.

Adaption of a corrector module to the IMP dynamics program

NASA Technical Reports Server (NTRS)

1972-01-01

The corrector module of the RAEIOS program and the IMP dynamics computer program were combined to achieve a date-fitting capability with the more general spacecraft dynamics models of the IMP program. The IMP dynamics program presents models of spacecraft dynamics for satellites with long, flexible booms. The properties of the corrector are discussed and a description is presented of the performance criteria and search logic for parameter estimation. A description is also given of the modifications made to add the corrector to the IMP program. This includes subroutine descriptions, common definitions, definition of input, and a description of output.

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.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

PubMed Central

Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

Dynamics of safety performance and culture: a group model building approach.

PubMed

Goh, Yang Miang; Love, Peter E D; Stagbouer, Greg; Annesley, Chris

2012-09-01

The management of occupational health and safety (OHS) including safety culture interventions is comprised of complex problems that are often hard to scope and define. Due to the dynamic nature and complexity of OHS management, the concept of system dynamics (SD) is used to analyze accident prevention. In this paper, a system dynamics group model building (GMB) approach is used to create a causal loop diagram of the underlying factors influencing the OHS performance of a major drilling and mining contractor in Australia. While the organization has invested considerable resources into OHS their disabling injury frequency rate (DIFR) has not been decreasing. With this in mind, rich individualistic knowledge about the dynamics influencing the DIFR was acquired from experienced employees with operations, health and safety and training background using a GMB workshop. Findings derived from the workshop were used to develop a series of causal loop diagrams that includes a wide range of dynamics that can assist in better understanding the causal influences OHS performance. The causal loop diagram provides a tool for organizations to hypothesize the dynamics influencing effectiveness of OHS management, particularly the impact on DIFR. In addition the paper demonstrates that the SD GMB approach has significant potential in understanding and improving OHS management. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of the Structural Conditions of the San Clemente a Vomano Abbey

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

Benedettini, Francesco; Alaggio, Rocco; Fusco, Felice

2008-07-08

The simultaneous use of a Finite Element (FE) accurate modeling, dynamical tests, model updating and nonlinear analysis are used to describe the integrated approach used by the authors to assess the structural conditions and the seismic vulnerability of an historical masonry structure: the Abbey Church of San Clemente al Vomano, situated in the Notaresco territory (TE, Italy) commissioned by Ermengarda, daughter of the Emperor Ludovico II, and built at the end of IX century together with a monastery to host a monastic community. Dynamical tests 'in operational conditions' and modal identification have been used to perform the FE model validation.more » Both a simple and direct method as the kinematic analysis applied on meaningful sub-structures and a nonlinear 3D dynamic analysis conducted by using the FE model have been used to forecast the seismic performance of the Church.« less

Employment of CB models for non-linear dynamic analysis

NASA Technical Reports Server (NTRS)

Klein, M. R. M.; Deloo, P.; Fournier-Sicre, A.

1990-01-01

The non-linear dynamic analysis of large structures is always very time, effort and CPU consuming. Whenever possible the reduction of the size of the mathematical model involved is of main importance to speed up the computational procedures. Such reduction can be performed for the part of the structure which perform linearly. Most of the time, the classical Guyan reduction process is used. For non-linear dynamic process where the non-linearity is present at interfaces between different structures, Craig-Bampton models can provide a very rich information, and allow easy selection of the relevant modes with respect to the phenomenon driving the non-linearity. The paper presents the employment of Craig-Bampton models combined with Newmark direct integration for solving non-linear friction problems appearing at the interface between the Hubble Space Telescope and its solar arrays during in-orbit maneuvers. Theory, implementation in the FEM code ASKA, and practical results are shown.

Modeling and design of a high-performance hybrid actuator

NASA Astrophysics Data System (ADS)

Aloufi, Badr; Behdinan, Kamran; Zu, Jean

2016-12-01

This paper presents the model and design of a novel hybrid piezoelectric actuator which provides high active and passive performances for smart structural systems. The actuator is composed of a pair of curved pre-stressed piezoelectric actuators, so-called commercially THUNDER actuators, installed opposite each other using two clamping mechanisms constructed of in-plane fixable hinges, grippers and solid links. A fully mathematical model is developed to describe the active and passive dynamics of the actuator and investigate the effects of its geometrical parameters on the dynamic stiffness, free displacement and blocked force properties. Among the literature that deals with piezoelectric actuators in which THUNDER elements are used as a source of electromechanical power, the proposed study is unique in that it presents a mathematical model that has the ability to predict the actuator characteristics and achieve other phenomena, such as resonances, mode shapes, phase shifts, dips, etc. For model validation, the measurements of the free dynamic response per unit voltage and passive acceleration transmissibility of a particular actuator design are used to check the accuracy of the results predicted by the model. The results reveal that there is a good agreement between the model and experiment. Another experiment is performed to teste the linearity of the actuator system by examining the variation of the output dynamic responses with varying forces and voltages at different frequencies. From the results, it can be concluded that the actuator acts approximately as a linear system at frequencies up to 1000 Hz. A parametric study is achieved here by applying the developed model to analyze the influence of the geometrical parameters of the fixable hinges on the active and passive actuator properties. The model predictions in the frequency range of 0-1000 Hz show that the hinge thickness, radius, and opening angle parameters have great effects on the frequency dynamic responses, passive isolation characteristics and the locations of their peaks and dips. Furthermore, the output actuating force can be improved by increasing the hinge hardness, which is controlled by its dimensions, although increasing the hinge hardness may cause a decrease in the free displacement and passive insulation performance, particularly at low frequencies.

Low-energy fusion dynamics of weakly bound nuclei: A time dependent perspective

NASA Astrophysics Data System (ADS)

Diaz-Torres, A.; Boselli, M.

2016-05-01

Recent dynamical fusion models for weakly bound nuclei at low incident energies, based on a time-dependent perspective, are briefly presented. The main features of both the PLATYPUS model and a new quantum approach are highlighted. In contrast to existing timedependent quantum models, the present quantum approach separates the complete and incomplete fusion from the total fusion. Calculations performed within a toy model for 6Li + 209Bi at near-barrier energies show that converged excitation functions for total, complete and incomplete fusion can be determined with the time-dependent wavepacket dynamics.

Accurate Sloshing Modes Modeling: A New Analytical Solution and its Consequences on Control

NASA Astrophysics Data System (ADS)

Gonidou, Luc-Olivier; Desmariaux, Jean

2014-06-01

This study addresses the issue of sloshing modes modeling for GNC analyses purposes. On European launchers, equivalent mechanical systems are commonly used for modeling sloshing effects on launcher dynamics. The representativeness of such a methodology is discussed here. First an exact analytical formulation of the launcher dynamics fitted with sloshing modes is proposed and discrepancies with equivalent mechanical system approach are emphasized. Then preliminary comparative GNC analyses are performed using the different models of dynamics in order to evaluate the impact of the aforementioned discrepancies from GNC standpoint. Special attention is paid to system stability.

Mathematical multi-scale model of the cardiovascular system including mitral valve dynamics. Application to ischemic mitral insufficiency

PubMed Central

2011-01-01

Background Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions. Methods A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate "open on pressure, close on flow" law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle. Results Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends. Conclusions The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves. PMID:21942971

A nonlinear model for top fuel dragster dynamic performance assessment

NASA Astrophysics Data System (ADS)

Spanos, P. D.; Castillo, D. H.; Kougioumtzoglou, I. A.; Tapia, R. A.

2012-02-01

The top fuel dragster is the fastest and quickest vehicle in drag racing. This vehicle is capable of travelling a quarter mile in less than 4.5 s, reaching a final speed in excess of 330 miles per hour. The average power delivered by its engine exceeds 7000 Hp. To analyse and eventually increase the performance of a top fuel dragster, a dynamic model of the vehicle is developed. Longitudinal, vertical, and pitching chassis motions are considered, as well as drive-train dynamics. The aerodynamics of the vehicle, the engine characteristics, and the force due to the combustion gases are incorporated into the model. Further, a simplified model of the traction characteristics of the rear tyres is developed where the traction is calculated as a function of the slip ratio and the velocity. The resulting nonlinear, coupled differential equations of motion are solved using a fourth-order Runge-Kutta numerical integration scheme. Several simulation runs are made to investigate the effects of the aerodynamics and of the engine's initial torque in the performance of the vehicle. The results of the computational simulations are scrutinised by comparisons with data from actual dragster races. Ultimately, the proposed dynamic model of the dragster can be used to improve the aerodynamics, the engine and clutch set-ups of the vehicle, and possibly facilitate the redesign of the dragster.

Corruption dynamics model

NASA Astrophysics Data System (ADS)

Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

2017-07-01

The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

Estimation of changes in dynamic hydraulic force in a magnetically suspended centrifugal blood pump with transient computational fluid dynamics analysis.

PubMed

Masuzawa, Toru; Ohta, Akiko; Tanaka, Nobuatu; Qian, Yi; Tsukiya, Tomonori

2009-01-01

The effect of the hydraulic force on magnetically levitated (maglev) pumps should be studied carefully to improve the suspension performance and the reliability of the pumps. A maglev centrifugal pump, developed at Ibaraki University, was modeled with 926 376 hexahedral elements for computational fluid dynamics (CFD) analyses. The pump has a fully open six-vane impeller with a diameter of 72.5 mm. A self-bearing motor suspends the impeller in the radial direction. The maximum pressure head and flow rate were 250 mmHg and 14 l/min, respectively. First, a steady-state analysis was performed using commercial code STAR-CD to confirm the model's suitability by comparing the results with the real pump performance. Second, transient analysis was performed to estimate the hydraulic force on the levitated impeller. The impeller was rotated in steps of 1 degrees using a sliding mesh. The force around the impeller was integrated at every step. The transient analysis revealed that the direction of the radial force changed dynamically as the vane's position changed relative to the outlet port during one circulation, and the magnitude of this force was about 1 N. The current maglev pump has sufficient performance to counteract this hydraulic force. Transient CFD analysis is not only useful for observing dynamic flow conditions in a centrifugal pump but is also effective for obtaining information about the levitation dynamics of a maglev pump.

A systematic review of lumped-parameter equivalent circuit models for real-time estimation of lithium-ion battery states

NASA Astrophysics Data System (ADS)

Nejad, S.; Gladwin, D. T.; Stone, D. A.

2016-06-01

This paper presents a systematic review for the most commonly used lumped-parameter equivalent circuit model structures in lithium-ion battery energy storage applications. These models include the Combined model, Rint model, two hysteresis models, Randles' model, a modified Randles' model and two resistor-capacitor (RC) network models with and without hysteresis included. Two variations of the lithium-ion cell chemistry, namely the lithium-ion iron phosphate (LiFePO4) and lithium nickel-manganese-cobalt oxide (LiNMC) are used for testing purposes. The model parameters and states are recursively estimated using a nonlinear system identification technique based on the dual Extended Kalman Filter (dual-EKF) algorithm. The dynamic performance of the model structures are verified using the results obtained from a self-designed pulsed-current test and an electric vehicle (EV) drive cycle based on the New European Drive Cycle (NEDC) profile over a range of operating temperatures. Analysis on the ten model structures are conducted with respect to state-of-charge (SOC) and state-of-power (SOP) estimation with erroneous initial conditions. Comparatively, both RC model structures provide the best dynamic performance, with an outstanding SOC estimation accuracy. For those cell chemistries with large inherent hysteresis levels (e.g. LiFePO4), the RC model with only one time constant is combined with a dynamic hysteresis model to further enhance the performance of the SOC estimator.

Review of CTF s Fuel Rod Modeling Using FRAPCON-4.0 s Centerline Temperature Predictions

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

Toptan, Aysenur; Salko, Robert K; Avramova, Maria

Coolant Boiling in Rod Arrays Two Fluid (COBRA-TF), or CTF1 [1], is a nuclear thermal hydraulic subchannel code used throughout academia and industry. CTF s fuel rod modeling is originally developed for VIPRE code [2]. Its methodology is based on GAPCON [3] and FRAP [4] fuel performance codes, and material properties are included from MATPRO handbook [5]. This work focuses on review of CTF s fuel rod modeling to address shortcomings in CTF s temperature predictions. CTF is compared to FRAPCON which is U.S. NRC s steady-state fuel performance code for light-water reactor fuel rods. FRAPCON calculates the changes inmore » fuel rod variables and temperatures including the eects of cladding hoop strain, cladding oxidation, hydriding, fuel irradiation swelling, densification, fission gas release and rod internal gas pressure. It uses fuel, clad and gap material properties from MATPRO. Additionally, it has its own models for fission gas release, cladding corrosion and cladding hydrogen pickup. It allows finite dierence or finite element approaches for its mechanical model. In this study, FRAPCON-4.0 [6] is used as a reference fuel performance code. In comparison, Halden Reactor Data for IFA432 Rod 1 and Rod 3. CTF simulations are performed in two ways; informing CTF with gap conductance value from FRAPCON, and using CTF s dynamic gap conductance model. First case is chosen to show temperature is predicted correctly with CTF s models for thermal and cladding conductivities once gap conductance is provided. Latter is to review CTF s dynamic gap conductance model. These Halden test cases are selected to be representative of cases with and without any physical contact between fuel-pellet and clad while reviewing functionality of CTF s dynamic gap conductance model. Improving the CTF s dynamic gap conductance model will allow prediction of fuel and cladding thermo-mechanical behavior under irradiation, and better temperature feedbacks from CTF in transient calculations.« less

Development of a Stirling System Dynamic Model With Enhanced Thermodynamics

NASA Technical Reports Server (NTRS)

Regan, Timothy F.; Lewandowski, Edward J.

2005-01-01

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

Development of a Stirling System Dynamic Model with Enhanced Thermodynamics

NASA Astrophysics Data System (ADS)

Regan, Timothy F.; Lewandowski, Edward J.

2005-02-01

The Stirling Convertor System Dynamic Model developed at NASA Glenn Research Center is a software model developed from first principles that includes the mechanical and mounting dynamics, the thermodynamics, the linear alternator, and the controller of a free-piston Stirling power convertor, along with the end user load. As such it represents the first detailed modeling tool for fully integrated Stirling convertor-based power systems. The thermodynamics of the model were originally a form of the isothermal Stirling cycle. In some situations it may be desirable to improve the accuracy of the Stirling cycle portion of the model. An option under consideration is to enhance the SDM thermodynamics by coupling the model with Gedeon Associates' Sage simulation code. The result will be a model that gives a more accurate prediction of the performance and dynamics of the free-piston Stirling convertor. A method of integrating the Sage simulation code with the System Dynamic Model is described. Results of SDM and Sage simulation are compared to test data. Model parameter estimation and model validation are discussed.

On Parallelizing Single Dynamic Simulation Using HPC Techniques and APIs of Commercial Software

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

Diao, Ruisheng; Jin, Shuangshuang; Howell, Frederic

Time-domain simulations are heavily used in today’s planning and operation practices to assess power system transient stability and post-transient voltage/frequency profiles following severe contingencies to comply with industry standards. Because of the increased modeling complexity, it is several times slower than real time for state-of-the-art commercial packages to complete a dynamic simulation for a large-scale model. With the growing stochastic behavior introduced by emerging technologies, power industry has seen a growing need for performing security assessment in real time. This paper presents a parallel implementation framework to speed up a single dynamic simulation by leveraging the existing stability model librarymore » in commercial tools through their application programming interfaces (APIs). Several high performance computing (HPC) techniques are explored such as parallelizing the calculation of generator current injection, identifying fast linear solvers for network solution, and parallelizing data outputs when interacting with APIs in the commercial package, TSAT. The proposed method has been tested on a WECC planning base case with detailed synchronous generator models and exhibits outstanding scalable performance with sufficient accuracy.« less

Political dynamics determined by interactions between political leaders and voters.

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

Bernard, Michael Lewis; Bier, Asmeret; Backus, George A.

2010-03-01

The political dynamics associated with an election are typically a function of the interplay between political leaders and voters, as well as endogenous and exogenous factors that impact the perceptions and goals of the electorate. This paper describes an effort by Sandia National Laboratories to model the attitudes and behaviors of various political groups along with that population's primary influencers, such as government leaders. To accomplish this, Sandia National Laboratories is creating a hybrid system dynamics-cognitive model to simulate systems- and individual-level political dynamics in a hypothetical society. The model is based on well-established psychological theory, applied to both individualsmore » and groups within the modeled society. Confidence management processes are being incorporated into the model design process to increase the utility of the tool and assess its performance. This project will enhance understanding of how political dynamics are determined in democratic society.« less

An ICAI architecture for troubleshooting in complex, dynamic systems

NASA Technical Reports Server (NTRS)

Fath, Janet L.; Mitchell, Christine M.; Govindaraj, T.

1990-01-01

Ahab, an intelligent computer-aided instruction (ICAI) program, illustrates an architecture for simulator-based ICAI programs to teach troubleshooting in complex, dynamic environments. The architecture posits three elements of a computerized instructor: the task model, the student model, and the instructional module. The task model is a prescriptive model of expert performance that uses symptomatic and topographic search strategies to provide students with directed problem-solving aids. The student model is a descriptive model of student performance in the context of the task model. This student model compares the student and task models, critiques student performance, and provides interactive performance feedback. The instructional module coordinates information presented by the instructional media, the task model, and the student model so that each student receives individualized instruction. Concept and metaconcept knowledge that supports these elements is contained in frames and production rules, respectively. The results of an experimental evaluation are discussed. They support the hypothesis that training with an adaptive online system built using the Ahab architecture produces better performance than training using simulator practice alone, at least with unfamiliar problems. It is not sufficient to develop an expert strategy and present it to students using offline materials. The training is most effective if it adapts to individual student needs.

Motion performance and mooring system of a floating offshore wind turbine

NASA Astrophysics Data System (ADS)

Zhao, Jing; Zhang, Liang; Wu, Haitao

2012-09-01

The development of offshore wind farms was originally carried out in shallow water areas with fixed (seabed mounted) structures. However, countries with limited shallow water areas require innovative floating platforms to deploy wind turbines offshore in order to harness wind energy to generate electricity in deep seas. The performances of motion and mooring system dynamics are vital to designing a cost effective and durable floating platform. This paper describes a numerical model to simulate dynamic behavior of a new semi-submersible type floating offshore wind turbine (FOWT) system. The wind turbine was modeled as a wind block with a certain thrust coefficient, and the hydrodynamics and mooring system dynamics of the platform were calculated by SESAM software. The effect of change in environmental conditions on the dynamic response of the system under wave and wind loading was examined. The results indicate that the semi-submersible concept has excellent performance and SESAM could be an effective tool for floating wind turbine design and analysis.

Proton exchange membrane fuel cell model for aging predictions: Simulated equivalent active surface area loss and comparisons with durability tests

NASA Astrophysics Data System (ADS)

Robin, C.; Gérard, M.; Quinaud, M.; d'Arbigny, J.; Bultel, Y.

2016-09-01

The prediction of Proton Exchange Membrane Fuel Cell (PEMFC) lifetime is one of the major challenges to optimize both material properties and dynamic control of the fuel cell system. In this study, by a multiscale modeling approach, a mechanistic catalyst dissolution model is coupled to a dynamic PEMFC cell model to predict the performance loss of the PEMFC. Results are compared to two 2000-h experimental aging tests. More precisely, an original approach is introduced to estimate the loss of an equivalent active surface area during an aging test. Indeed, when the computed Electrochemical Catalyst Surface Area profile is fitted on the experimental measures from Cyclic Voltammetry, the computed performance loss of the PEMFC is underestimated. To be able to predict the performance loss measured by polarization curves during the aging test, an equivalent active surface area is obtained by a model inversion. This methodology enables to successfully find back the experimental cell voltage decay during time. The model parameters are fitted from the polarization curves so that they include the global degradation. Moreover, the model captures the aging heterogeneities along the surface of the cell observed experimentally. Finally, a second 2000-h durability test in dynamic operating conditions validates the approach.

Dynamic Cognitive Tracing: Towards Unified Discovery of Student and Cognitive Models

ERIC Educational Resources Information Center

Gonzalez-Brenes, Jose P.; Mostow, Jack

2012-01-01

This work describes a unified approach to two problems previously addressed separately in Intelligent Tutoring Systems: (i) Cognitive Modeling, which factorizes problem solving steps into the latent set of skills required to perform them; and (ii) Student Modeling, which infers students' learning by observing student performance. The practical…

Contact force history and dynamic response due to the impact of a soft projectile

NASA Technical Reports Server (NTRS)

Grady, J. E.

1988-01-01

A series of ballistic impact tests on several different instrumented targets was performed to characterize the dynamic contact force history resulting from the impact of a compliant projectile. The results show that the variation of contact force history with impact velocity does not follow the trends predicted by classical impact models. An empirical model was therefore developed to describe this behavior. This model was then used in a finite-element analysis to estimate the force history and calculate the resulting dynamic strain response in a transversely impacted composite laminate.

Acquisition and production of skilled behavior in dynamic decision-making tasks

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1993-01-01

Summaries of the four projects completed during the performance of this research are included. The four projects described are: Perceptual Augmentation Aiding for Situation Assessment, Perceptual Augmentation Aiding for Dynamic Decision-Making and Control, Action Advisory Aiding for Dynamic Decision-Making and Control, and Display Design to Support Time-Constrained Route Optimization. Papers based on each of these projects are currently in preparation. The theoretical framework upon which the first three projects are based, Ecological Task Analysis, was also developed during the performance of this research, and is described in a previous report. A project concerned with modeling strategies in human control of a dynamic system was also completed during the performance of this research.

Data Intensive Systems (DIS) Benchmark Performance Summary

DTIC Science & Technology

2003-08-01

models assumed by today’s conventional architectures. Such applications include model- based Automatic Target Recognition (ATR), synthetic aperture...radar (SAR) codes, large scale dynamic databases/battlefield integration, dynamic sensor- based processing, high-speed cryptanalysis, high speed...distributed interactive and data intensive simulations, data-oriented problems characterized by pointer- based and other highly irregular data structures

Scalable Online Network Modeling and Simulation

DTIC Science & Technology

2005-08-01

ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski , Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...performance for a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature ...a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature interactions

Modeling Ullage Dynamics of Tank Pressure Control Experiment during Jet Mixing in Microgravity

NASA Technical Reports Server (NTRS)

Kartuzova, O.; Kassemi, M.

2016-01-01

A CFD model for simulating the fluid dynamics of the jet induced mixing process is utilized in this paper to model the pressure control portion of the Tank Pressure Control Experiment (TPCE) in microgravity1. The Volume of Fluid (VOF) method is used for modeling the dynamics of the interface during mixing. The simulations were performed at a range of jet Weber numbers from non-penetrating to fully penetrating. Two different initial ullage positions were considered. The computational results for the jet-ullage interaction are compared with still images from the video of the experiment. A qualitative comparison shows that the CFD model was able to capture the main features of the interfacial dynamics, as well as the jet penetration of the ullage.

Trade-offs between pasture production and farmland bird conservation: exploration of options using a dynamic farm model.

PubMed

Sabatier, R; Teillard, F; Rossing, W A H; Doyen, L; Tichit, M

2015-05-01

In European grassland landscapes, grazing and mowing play a key role for the maintenance of high-quality habitats that host important bird populations. As grasslands are also key resources for cattle feeding, there is a need to develop management strategies that achieve the double objective of production and biodiversity conservation. The objective of this study was to use a modelling approach to generate recognisable patterns of bird dynamics in farms composed of different land use proportions, and to compare their production and ecological dimensions. We developed a dynamic model, which linked grassland management to bird population dynamics at the field and farm levels. The model was parameterised for two types of suckling farms corresponding to contrasting levels of grassland intensification and for two bird species of high conservation value. A viability algorithm was used to define and assess viable management strategies for production and ecological performance so as to draw the shape of the relationship between both types of performances for the two types of farms. Our results indicated that, at the farm level, there was a farming system effect with a negative and non-linear relationship linking performance. Improving bird population maintenance was less costly in extensive farms compared with intensive farms. At the field level, the model predicted the timing and intensity of land use, maximising either production or ecological performance. The results suggested that multi-objective grassland management would benefit from public policies that consider levels of organisation higher than the field level, such as the farm or the landscape.

Mesoscopic modelling and simulation of soft matter.

PubMed

Schiller, Ulf D; Krüger, Timm; Henrich, Oliver

2017-12-20

The deformability of soft condensed matter often requires modelling of hydrodynamical aspects to gain quantitative understanding. This, however, requires specialised methods that can resolve the multiscale nature of soft matter systems. We review a number of the most popular simulation methods that have emerged, such as Langevin dynamics, dissipative particle dynamics, multi-particle collision dynamics, sometimes also referred to as stochastic rotation dynamics, and the lattice-Boltzmann method. We conclude this review with a short glance at current compute architectures for high-performance computing and community codes for soft matter simulation.

Dynamics of internal models in game players

NASA Astrophysics Data System (ADS)

Taiji, Makoto; Ikegami, Takashi

1999-10-01

A new approach for the study of social games and communications is proposed. Games are simulated between cognitive players who build the opponent’s internal model and decide their next strategy from predictions based on the model. In this paper, internal models are constructed by the recurrent neural network (RNN), and the iterated prisoner’s dilemma game is performed. The RNN allows us to express the internal model in a geometrical shape. The complicated transients of actions are observed before the stable mutually defecting equilibrium is reached. During the transients, the model shape also becomes complicated and often experiences chaotic changes. These new chaotic dynamics of internal models reflect the dynamical and high-dimensional rugged landscape of the internal model space.

Robust control of combustion instabilities

NASA Astrophysics Data System (ADS)

Hong, Boe-Shong

Several interactive dynamical subsystems, each of which has its own time-scale and physical significance, are decomposed to build a feedback-controlled combustion- fluid robust dynamics. On the fast-time scale, the phenomenon of combustion instability is corresponding to the internal feedback of two subsystems: acoustic dynamics and flame dynamics, which are parametrically dependent on the slow-time-scale mean-flow dynamics controlled for global performance by a mean-flow controller. This dissertation constructs such a control system, through modeling, analysis and synthesis, to deal with model uncertainties, environmental noises and time- varying mean-flow operation. Conservation law is decomposed as fast-time acoustic dynamics and slow-time mean-flow dynamics, served for synthesizing LPV (linear parameter varying)- L2-gain robust control law, in which a robust observer is embedded for estimating and controlling the internal status, while achieving trade- offs among robustness, performances and operation. The robust controller is formulated as two LPV-type Linear Matrix Inequalities (LMIs), whose numerical solver is developed by finite-element method. Some important issues related to physical understanding and engineering application are discussed in simulated results of the control system.

Advanced and innovative wind energy concept development: Dynamic inducer system

NASA Astrophysics Data System (ADS)

Lissaman, P. B. S.; Zalay, A. D.; Hibbs, B. H.

1981-05-01

The performance benefits of the dynamic inducer tip vane system was demonstrated Tow-tests conducted on a three-bladed, 3.6-meter diameter rotor show that a dynamic inducer can achieve a power coefficient (based pon power blade swept area) of 0.5, which exceeds that of a plain rotor by about 35%. Wind tunnel tests conducted on a one-third scale model of the dynamic inducer achieved a power coefficient of 0.62 which exceeded that of a plain rotor by about 70%. The dynamic inducer substantially improves the performance of conventional rotors and indications are that higher power coefficients can be achieved through additional aerodynamic optimization.

Effect of temperature- and frequency-dependent dynamic properties of rail pads on high-speed vehicle-track coupled vibrations

NASA Astrophysics Data System (ADS)

Wei, Kai; Wang, Feng; Wang, Ping; Liu, Zi-xuan; Zhang, Pan

2017-03-01

The soft under baseplate pad of WJ-8 rail fastener frequently used in China's high-speed railways was taken as the study subject, and a laboratory test was performed to measure its temperature and frequency-dependent dynamic performance at 0.3 Hz and at -60°C to 20°C with intervals of 2.5°C. Its higher frequency-dependent results at different temperatures were then further predicted based on the time-temperature superposition (TTS) and Williams-Landel-Ferry (WLF) formula. The fractional derivative Kelvin-Voigt (FDKV) model was used to represent the temperature- and frequency-dependent dynamic properties of the tested rail pad. By means of the FDKV model for rail pads and vehicle-track coupled dynamic theory, high-speed vehicle-track coupled vibrations due to temperature- and frequency-dependent dynamic properties of rail pads was investigated. Finally, further combining with the measured frequency-dependent dynamic performance of vehicle's rubber primary suspension, the high-speed vehicle-track coupled vibration responses were discussed. It is found that the storage stiffness and loss factor of the tested rail pad are sensitive to low temperatures or high frequencies. The proposed FDKV model for the frequency-dependent storage stiffness and loss factors of the tested rail pad can basically meet the fitting precision, especially at ordinary temperatures. The numerical simulation results indicate that the vertical vibration levels of high-speed vehicle-track coupled systems calculated with the FDKV model for rail pads in time domain are higher than those calculated with the ordinary Kelvin-Voigt (KV) model for rail pads. Additionally, the temperature- and frequency-dependent dynamic properties of the tested rail pads would alter the vertical vibration acceleration levels (VALs) of the car body and bogie in 1/3 octave frequencies above 31.5 Hz, especially enlarge the vertical VALs of the wheel set and rail in 1/3 octave frequencies of 31.5-100 Hz and above 315 Hz, which are the dominant frequencies of ground vibration acceleration and rolling noise (or bridge noise) caused by high-speed railways respectively. Since the fractional derivative value of the adopted rubber primary suspension, unlike the tested rail pad, is very close to 1, its frequency-dependent dynamic performance has little effect on high-speed vehicle-track coupled vibration responses.

Performance comparison for Barnes model 12-1000, Exotech model 100, and Ideas Inc. Biometer Mark 2

NASA Technical Reports Server (NTRS)

Robinson, B. (Principal Investigator)

1981-01-01

Results of tests show that all channels of all instruments, except channel 3 of the Biometer Mark 2, were stable in response to input signals were linear, and were adequately stable in response to temperature changes. The Biometer Mark 2 is labelled with an inappropriate description of the units measured and the dynamic range is a inappropriate for field measurements causing unnecessarily high fractional errors. This instrument is, therefore, quantization limited. The dynamic range and noise performance of the Model 12-1000 are appropriate for remote sensing field research. The field of view and performance of the Model 100A and the Model 12-1000 are satisfactory. The Biometer Mark 2 has not, as yet, been satisfactorily equipped with an acceptable field of view determining device. Neither the widely used aperture plate nor the 24 deg cone are acceptable.

Computational analysis of Variable Thrust Engine (VTE) performance

NASA Technical Reports Server (NTRS)

Giridharan, M. G.; Krishnan, A.; Przekwas, A. J.

1993-01-01

The Variable Thrust Engine (VTE) of the Orbital Maneuvering Vehicle (OMV) uses a hypergolic propellant combination of Monomethyl Hydrazine (MMH) and Nitrogen Tetroxide (NTO) as fuel and oxidizer, respectively. The performance of the VTE depends on a number of complex interacting phenomena such as atomization, spray dynamics, vaporization, turbulent mixing, convective/radiative heat transfer, and hypergolic combustion. This study involved the development of a comprehensive numerical methodology to facilitate detailed analysis of the VTE. An existing Computational Fluid Dynamics (CFD) code was extensively modified to include the following models: a two-liquid, two-phase Eulerian-Lagrangian spray model; a chemical equilibrium model; and a discrete ordinate radiation heat transfer model. The modified code was used to conduct a series of simulations to assess the effects of various physical phenomena and boundary conditions on the VTE performance. The details of the models and the results of the simulations are presented.

Performance Guaranteed Inertia Emulation forDiesel-Wind System Feed Microgrid via ModelReference Control

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

Melin, Alexander M.; Zhang, Yichen; Djouadi, Seddik

In this paper, a model reference control based inertia emulation strategy is proposed. Desired inertia can be precisely emulated through this control strategy so that guaranteed performance is ensured. A typical frequency response model with parametrical inertia is set to be the reference model. A measurement at a specific location delivers the information of disturbance acting on the diesel-wind system to the referencemodel. The objective is for the speed of the diesel-wind system to track the reference model. Since active power variation is dominantly governed by mechanical dynamics and modes, only mechanical dynamics and states, i.e., a swing-engine-governor system plusmore » a reduced-order wind turbine generator, are involved in the feedback control design. The controller is implemented in a three-phase diesel-wind system feed microgrid. The results show exact synthetic inertia is emulated, leading to guaranteed performance and safety bounds.« less

System Dynamics Model and Simulation of Employee Work-Family Conflict in the Construction Industry

PubMed Central

Wu, Guangdong; Duan, Kaifeng; Zuo, Jian; Yang, Jianlin; Wen, Shiping

2016-01-01

The construction industry is a demanding work environment where employees’ work-family conflict is particularly prominent. This conflict has a significant impact on job and family satisfaction and performance of employees. In order to analyze the dynamic evolution of construction industry employee’s work-family conflict between work and family domains, this paper constructs a bi-directional dynamic model framework of work-family conflict by referring to the relevant literature. Consequently, a system dynamics model of employee’s work-family conflict in the construction industry is established, and a simulation is conducted. The simulation results indicate that construction industry employees experience work interference with family conflict (WIFC) levels which are significantly greater than the family interference with work conflict (FIWC) levels. This study also revealed that improving work flexibility and organizational support can have a positive impact on the satisfaction and performance of construction industry employees from a work and family perspective. Furthermore, improving family support can only significantly improve employee job satisfaction. PMID:27801857

System Dynamics Model and Simulation of Employee Work-Family Conflict in the Construction Industry.

PubMed

Wu, Guangdong; Duan, Kaifeng; Zuo, Jian; Yang, Jianlin; Wen, Shiping

2016-10-28

The construction industry is a demanding work environment where employees' work-family conflict is particularly prominent. This conflict has a significant impact on job and family satisfaction and performance of employees. In order to analyze the dynamic evolution of construction industry employee's work-family conflict between work and family domains, this paper constructs a bi-directional dynamic model framework of work-family conflict by referring to the relevant literature. Consequently, a system dynamics model of employee's work-family conflict in the construction industry is established, and a simulation is conducted. The simulation results indicate that construction industry employees experience work interference with family conflict (WIFC) levels which are significantly greater than the family interference with work conflict (FIWC) levels. This study also revealed that improving work flexibility and organizational support can have a positive impact on the satisfaction and performance of construction industry employees from a work and family perspective. Furthermore, improving family support can only significantly improve employee job satisfaction.

Large eddy simulations of time-dependent and buoyancy-driven channel flows

NASA Technical Reports Server (NTRS)

Cabot, William H.

1993-01-01

The primary goal of this work has been to assess the performance of the dynamic SGS model in the large eddy simulation (LES) of channel flows in a variety of situations, viz., in temporal development of channel flow turned by a transverse pressure gradient and especially in buoyancy-driven turbulent flows such as Rayleigh-Benard and internally heated channel convection. For buoyancy-driven flows, there are additional buoyant terms that are possible in the base models, and one objective has been to determine if the dynamic SGS model results are sensitive to such terms. The ultimate goal is to determine the minimal base model needed in the dynamic SGS model to provide accurate results in flows with more complicated physical features. In addition, a program of direct numerical simulation (DNS) of fully compressible channel convection has been undertaken to determine stratification and compressibility effects. These simulations are intended to provide a comparative base for performing the LES of compressible (or highly stratified, pseudo-compressible) convection at high Reynolds number in the future.

A holistic approach to movement education in sport and fitness: a systems based model.

PubMed

Polsgrove, Myles Jay

2012-01-01

The typical model used by movement professionals to enhance performance relies on the notion that a linear increase in load results in steady and progressive gains, whereby, the greater the effort, the greater the gains in performance. Traditional approaches to movement progression typically rely on the proper sequencing of extrinsically based activities to facilitate the individual in reaching performance objectives. However, physical rehabilitation or physical performance rarely progresses in such a linear fashion; instead they tend to evolve non-linearly and rather unpredictably. A dynamic system can be described as an entity that self-organizes into increasingly complex forms. Applying this view to the human body, practitioners could facilitate non-linear performance gains through a systems based programming approach. Utilizing a dynamic systems view, the Holistic Approach to Movement Education (HADME) is a model designed to optimize performance by accounting for non-linear and self-organizing traits associated with human movement. In this model, gains in performance occur through advancing individual perspectives and through optimizing sub-system performance. This inward shift of the focus of performance creates a sharper self-awareness and may lead to more optimal movements. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling Unsteady Cavitation and Dynamic Loads in Turbopumps

NASA Technical Reports Server (NTRS)

Hosangadi, Ashvin; Ahuja, Vineet; Ungewitter, Ronald; Dash, Sanford M.

2009-01-01

A computational fluid dynamics (CFD) model that includes representations of effects of unsteady cavitation and associated dynamic loads has been developed to increase the accuracy of simulations of the performances of turbopumps. Although the model was originally intended to serve as a means of analyzing preliminary designs of turbopumps that supply cryogenic propellant liquids to rocket engines, the model could also be applied to turbopumping of other liquids: this can be considered to have been already demonstrated, in that the validation of the model was performed by comparing results of simulations performed by use of the model with results of sub-scale experiments in water. The need for this or a similar model arises as follows: Cavitation instabilities in a turbopump are generated as inlet pressure drops and vapor cavities grow on inducer blades, eventually becoming unsteady. The unsteady vapor cavities lead to rotation cavitation, in which the cavities detach from the blades and become part of a fluid mass that rotates relative to the inducer, thereby generating a fluctuating load. Other instabilities (e.g., surge instabilities) can couple with cavitation instabilities, thereby compounding the deleterious effects of unsteadiness on other components of the fluid-handling system of which the turbopump is a part and thereby, further, adversely affecting the mechanical integrity and safety of the system. Therefore, an ability to predict cavitation- instability-induced dynamic pressure loads on the blades, the shaft, and other pump parts would be valuable in helping to quantify safe margins of inducer operation and in contributing to understanding of design compromises. Prior CFD models do not afford this ability. Heretofore, the primary parameter used in quantifying cavitation performance of a turbopump inducer has been the critical suction specific speed at which head breakdown occurs. This parameter is a mean quantity calculated on the basis of assumed steady-state operation of the inducer; it does not account for dynamic pressure loads associated with unsteady flow caused by instabilities. Because cavitation instabilities occur well before mean breakdown in inducers, engineers have, until now, found it necessary to use conservative factors of safety when analyzing the results of numerical simulations of flows in turbopumps.

A Lagrangian dynamic subgrid-scale model turbulence

NASA Technical Reports Server (NTRS)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

A micromechanical constitutive model for the dynamic response of brittle materials "Dynamic response of marble"

NASA Astrophysics Data System (ADS)

Haberman, Keith

2001-07-01

A micromechanically based constitutive model for the dynamic inelastic behavior of brittle materials, specifically "Dionysus-Pentelicon marble" with distributed microcracking is presented. Dionysus-Pentelicon marble was used in the construction of the Parthenon, in Athens, Greece. The constitutive model is a key component in the ability to simulate this historic explosion and the preceding bombardment form cannon fire that occurred at the Parthenon in 1678. Experiments were performed by Rosakis (1999) that characterized the static and dynamic response of this unique material. A micromechanical constitutive model that was previously successfully used to model the dynamic response of granular brittle materials is presented. The constitutive model was fitted to the experimental data for marble and reproduced the experimentally observed basic uniaxial dynamic behavior quite well. This micromechanical constitutive model was then implemented into the three dimensional nonlinear lagrangain finite element code Dyna3d(1998). Implementing this methodology into the three dimensional nonlinear dynamic finite element code allowed the model to be exercised on several preliminary impact experiments. During future simulations, the model is to be used in conjunction with other numerical techniques to simulate projectile impact and blast loading on the Dionysus-Pentelicon marble and on the structure of the Parthenon.

Bayesian dynamic modeling of time series of dengue disease case counts

PubMed Central

López-Quílez, Antonio; Torres-Prieto, Alexander

2017-01-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health. PMID:28671941

Automating the generation of finite element dynamical cores with Firedrake

NASA Astrophysics Data System (ADS)

Ham, David; Mitchell, Lawrence; Homolya, Miklós; Luporini, Fabio; Gibson, Thomas; Kelly, Paul; Cotter, Colin; Lange, Michael; Kramer, Stephan; Shipton, Jemma; Yamazaki, Hiroe; Paganini, Alberto; Kärnä, Tuomas

2017-04-01

The development of a dynamical core is an increasingly complex software engineering undertaking. As the equations become more complete, the discretisations more sophisticated and the hardware acquires ever more fine-grained parallelism and deeper memory hierarchies, the problem of building, testing and modifying dynamical cores becomes increasingly complex. Here we present Firedrake, a code generation system for the finite element method with specialist features designed to support the creation of geoscientific models. Using Firedrake, the dynamical core developer writes the partial differential equations in weak form in a high level mathematical notation. Appropriate function spaces are chosen and time stepping loops written at the same high level. When the programme is run, Firedrake generates high performance C code for the resulting numerics which are executed in parallel. Models in Firedrake typically take a tiny fraction of the lines of code required by traditional hand-coding techniques. They support more sophisticated numerics than are easily achieved by hand, and the resulting code is frequently higher performance. Critically, debugging, modifying and extending a model written in Firedrake is vastly easier than by traditional methods due to the small, highly mathematical code base. Firedrake supports a wide range of key features for dynamical core creation: A vast range of discretisations, including both continuous and discontinuous spaces and mimetic (C-grid-like) elements which optimally represent force balances in geophysical flows. High aspect ratio layered meshes suitable for ocean and atmosphere domains. Curved elements for high accuracy representations of the sphere. Support for non-finite element operators, such as parametrisations. Access to PETSc, a world-leading library of programmable linear and nonlinear solvers. High performance adjoint models generated automatically by symbolically reasoning about the forward model. This poster will present the key features of the Firedrake system, as well as those of Gusto, an atmospheric dynamical core, and Thetis, a coastal ocean model, both of which are written in Firedrake.

Perturbation analysis of 6DoF flight dynamics and passive dynamic stability of hovering fruit fly Drosophila melanogaster.

PubMed

Gao, Na; Aono, Hikaru; Liu, Hao

2011-02-07

Insects exhibit exquisite control of their flapping flight, capable of performing precise stability and steering maneuverability. Here we develop an integrated computational model to investigate flight dynamics of insect hovering based on coupling the equations of 6 degree of freedom (6DoF) motion with the Navier-Stokes (NS) equations. Unsteady aerodynamics is resolved by using a biology-inspired dynamic flight simulator that integrates models of realistic wing-body morphology and kinematics, and a NS solver. We further develop a dynamic model to solve the rigid body equations of 6DoF motion by using a 4th-order Runge-Kutta method. In this model, instantaneous forces and moments based on the NS-solutions are represented in terms of Fourier series. With this model, we perform a systematic simulation-based analysis on the passive dynamic stability of a hovering fruit fly, Drosophila melanogaster, with a specific focus on responses of state variables to six one-directional perturbation conditions during latency period. Our results reveal that the flight dynamics of fruit fly hovering does not have a straightforward dynamic stability in a conventional sense that perturbations damp out in a manner of monotonous convergence. However, it is found to exist a transient interval containing an initial converging response observed for all the six perturbation variables and a terminal instability that at least one state variable subsequently tends to diverge after several wing beat cycles. Furthermore, our results illustrate that a fruit fly does have sufficient time to apply some active mediation to sustain a steady hovering before losing body attitudes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Dynamics of aircraft antiskid braking systems. [conducted at the Langley aircraft landing loads and traction facility

NASA Technical Reports Server (NTRS)

Tanner, J. A.; Stubbs, S. M.; Dreher, R. C.; Smith, E. G.

1982-01-01

A computer study was performed to assess the accuracy of three brake pressure-torque mathematical models. The investigation utilized one main gear wheel, brake, and tire assembly of a McDonnell Douglas DC-9 series 10 airplane. The investigation indicates that the performance of aircraft antiskid braking systems is strongly influenced by tire characteristics, dynamic response of the antiskid control valve, and pressure-torque response of the brake. The computer study employed an average torque error criterion to assess the accuracy of the models. The results indicate that a variable nonlinear spring with hysteresis memory function models the pressure-torque response of the brake more accurately than currently used models.

Dynamic modeling of brushless dc motor-power conditioner unit for electromechanical actuator application

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Nehl, T. W.

1979-01-01

A comprehensive digital model for the analysis of the dynamic-instantaneous performance of a power conditioner fed samarium-cobalt permanent magnet brushless DC motor is presented. The particular power conditioner-machine system at hand, for which this model was developed, is a component of an actual prototype electromechanical actuator built for NASA-JSC as a possible alternative to hydraulic actuators as part of feasibility studies for the shuttle orbiter applications. Excellent correlation between digital simulated and experimentally obtained performance data was achieved for this specific prototype. This is reported on in this paper. Details of one component of the model, its applications and the corresponding results are given in this paper.

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

Dissertation Defense Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

NASA Technical Reports Server (NTRS)

Groves, Curtis Edward

2014-01-01

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Dissertation Defense: Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

NASA Technical Reports Server (NTRS)

Groves, Curtis Edward

2014-01-01

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System spacecraft system.Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

NASA Technical Reports Server (NTRS)

Groves, Curtis E.

2013-01-01

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Inertance Tube Modeling and the Effects of Temperature

DTIC Science & Technology

2010-01-01

fluid dynamics. In one application in multistage cryocoolers , the performance of inertance tubes at the cryogenic temperatures is of interest. One... cryocoolers , the performance of inertance tubes at the cryogenic temperatures is of interest. One purpose of this paper is to understand how...acoustic power. KEYWORDS: Inertance tube, cryocoolers , pulse tube refrigerators, oscillating flow, computational fluid dynamics INTRODUCTION Pulse

Perceived Control and Hedonic Tone Dynamics during Performance in Elite Shooters

ERIC Educational Resources Information Center

Robazza, Claudio; Bertollo, Maurizio; Filho, Edson; Hanin, Yuri; Bortoli, Laura

2016-01-01

Purpose: The purpose of the study was to investigate the individuals' dynamics of perceived control and hedonic tone over time, with respect to the 4 performance states as conceptualized within the multiaction plan (MAP) model. We expected to find idiosyncratic and differentiated trends over time in the scores of perceived control and hedonic…

Modeling to predict pilot performance during CDTI-based in-trail following experiments

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1984-01-01

A mathematical model was developed of the flight system with the pilot using a cockpit display of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. Both in-trail and vertical dynamics were included. The nominal spacing was based on one of three criteria (Constant Time Predictor; Constant Time Delay; or Acceleration Cue). This model was used to simulate digitally the dynamics of a string of multiple following aircraft, including response to initial position errors. The simulation was used to predict the outcome of a series of in-trail following experiments, including pilot performance in maintaining correct longitudinal spacing and vertical position. The experiments were run in the NASA Ames Research Center multi-cab cockpit simulator facility. The experimental results were then used to evaluate the model and its prediction accuracy. Model parameters were adjusted, so that modeled performance matched experimental results. Lessons learned in this modeling and prediction study are summarized.

Propulsion System Dynamic Modeling for the NASA Supersonic Concept Vehicle: AeroPropulsoServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph; Seidel, Jonathan

2014-01-01

A summary of the propulsion system modeling under NASA's High Speed Project (HSP) AeroPropulsoServoElasticity (APSE) task is provided with a focus on the propulsion system for the low-boom supersonic configuration developed by Lockheed Martin and referred to as the N+2 configuration. This summary includes details on the effort to date to develop computational models for the various propulsion system components. The objective of this paper is to summarize the model development effort in this task, while providing more detail in the modeling areas that have not been previously published. The purpose of the propulsion system modeling and the overall APSE effort is to develop an integrated dynamic vehicle model to conduct appropriate unsteady analysis of supersonic vehicle performance. This integrated APSE system model concept includes the propulsion system model, and the vehicle structural-aerodynamics model. The development to date of such a preliminary integrated model will also be summarized in this report.propulsion system dynamics, the structural dynamics, and aerodynamics.

Redundancy, Self-Motion, and Motor Control

PubMed Central

Martin, V.; Scholz, J. P.; Schöner, G.

2011-01-01

Outside the laboratory, human movement typically involves redundant effector systems. How the nervous system selects among the task-equivalent solutions may provide insights into how movement is controlled. We propose a process model of movement generation that accounts for the kinematics of goal-directed pointing movements performed with a redundant arm. The key element is a neuronal dynamics that generates a virtual joint trajectory. This dynamics receives input from a neuronal timer that paces end-effector motion along its path. Within this dynamics, virtual joint velocity vectors that move the end effector are dynamically decoupled from velocity vectors that do not. Moreover, the sensed real joint configuration is coupled back into this neuronal dynamics, updating the virtual trajectory so that it yields to task-equivalent deviations from the dynamic movement plan. Experimental data from participants who perform in the same task setting as the model are compared in detail to the model predictions. We discover that joint velocities contain a substantial amount of self-motion that does not move the end effector. This is caused by the low impedance of muscle joint systems and by coupling among muscle joint systems due to multiarticulatory muscles. Back-coupling amplifies the induced control errors. We establish a link between the amount of self-motion and how curved the end-effector path is. We show that models in which an inverse dynamics cancels interaction torques predict too little self-motion and too straight end-effector paths. PMID:19718817

A Dynamic Model of Human and Livestock Tuberculosis Spread and Control in Urumqi, Xinjiang, China

PubMed Central

Liu, Shan; Li, Aiqiao; Feng, Xiaomei; Zhang, Xueliang

2016-01-01

We establish a dynamical model for tuberculosis of humans and cows. For the model, we firstly give the basic reproduction number R 0. Furthermore, we discuss the dynamical behaviors of the model. By epidemiological investigation of tuberculosis among humans and livestock from 2007 to 2014 in Urumqi, Xinjiang, China, we estimate the parameters of the model and study the transmission trend of the disease in Urumqi, Xinjiang, China. The reproduction number in Urumqi for the model is estimated to be 0.1811 (95% confidence interval: 0.123–0.281). Finally, we perform some sensitivity analysis of several model parameters and give some useful comments on controlling the transmission of tuberculosis. PMID:27525034

U1108 performance model

NASA Technical Reports Server (NTRS)

Trachta, G.

1976-01-01

A model of Univac 1108 work flow has been developed to assist in performance evaluation studies and configuration planning. Workload profiles and system configurations are parameterized for ease of experimental modification. Outputs include capacity estimates and performance evaluation functions. The U1108 system is conceptualized as a service network; classical queueing theory is used to evaluate network dynamics.

Comparison of Static and Dynamic Assessment Procedures and Their Relation to Independent Performance.

ERIC Educational Resources Information Center

Day, Jeanne D.; And Others

1997-01-01

Relationships between pretraining skills, learning, and posttest performance were studied in spatial and verbal tasks for 84 preschool children. The measurement model that fit the data best maintained separate verbal and spatial domains. The best structural model included paths from pretest and learning assessments to posttest performance within…

Effect of hole size on fluid dynamics of a posterior-chamber phakic intraocular lens with a central perforation by using computational fluid dynamics.

PubMed

Kawamorita, Takushi; Shimizu, Kimiya; Shoji, Nobuyuki

2016-04-01

A modified implantable collamer lens (ICL) with a central hole with a diameter of 0.36 mm, referred to as a hole-ICL, was created to improve aqueous humour circulation. The aim of this study is to investigate the ideal hole size in a hole-ICL from the standpoint of the fluid dynamic characteristics of the aqueous humour using computational fluid dynamics. Fluid dynamics simulation using an ICL was performed with thermal-hydraulic analysis software FloEFD V 12.2 (Mentor Graphics Corp.). In the simulation, three-dimensional eye models based on a modified Liou-Brennan model eye with a conventional ICL (Model ICM, Staar Surgical) and a hole-ICL were used. The hole-ICL was -9.0 dioptres (D) and 12.0 mm in length, with an optic zone of 5.5 mm. The vaulting was 0.50 mm. The quantity of aqueous humour produced by the ciliary body was set at 2.80 μL/min. Flow distribution between the anterior surface of the crystalline lens and the posterior surface of the ICL was calculated, and trajectory analysis was performed. With an increase in the central hole size, the velocity of the aqueous humour increased, with the peak velocity occurring at a diameter of approximately 0.4 mm. Once the diameter had increased above 0.4 mm, the velocity then decreased. The velocity difference between the cases of a central hole size of 0.1 mm and 0.2 mm was significant. The desirable central hole size was 0.2 mm or larger in terms of flow dynamics. The current model, based on a central hole size of 0.36 mm, was close to ideal. The optimisation of the hole size should be performed based on results from a long-term clinical study so as to analyse the incidence rate of secondary cataract and optical performance.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Analysis of structural dynamic data from Skylab. Volume 1: Technical discussion

NASA Technical Reports Server (NTRS)

Demchak, L.; Harcrow, H.

1976-01-01

A compendium of Skylab structural dynamics analytical and test programs is presented. These programs are assessed to identify lessons learned from the structural dynamic prediction effort and to provide guidelines for future analysts and program managers of complex spacecraft systems. It is a synopsis of the structural dynamic effort performed under the Skylab Integration contract and specifically covers the development, utilization, and correlation of Skylab Dynamic Orbital Models.

Web-based dynamic Delphi: a new survey instrument

NASA Astrophysics Data System (ADS)

Yao, JingTao; Liu, Wei-Ning

2006-04-01

We present a mathematical model for a dynamic Delphi survey method which takes advantages of Web technology. A comparative study on the performance of the conventional Delphi method and the dynamic Delphi instrument is conducted. It is suggested that a dynamic Delphi survey may form a consensus quickly. However, the result may not be robust due to the judgement leaking issues.

Dynamic Stability Instrumentation System (DSIS). Volume 3; User Manual

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Boyden, Richmond P.; Dress, David A.; Jordan, Thomas L.

1996-01-01

The paper is an operating manual for the Dynamic Stability Instrumentation System in specific NASA Langley wind tunnels. The instrumentation system performs either a synchronous demodulation or a Fast Fourier Transform on dynamic balance strain gage signals, and ultimately computes aerodynamic coefficients. The dynamic balance converts sting motor rotation into pitch or yaw plane or roll axis oscillation, with timing information provided by a shaft encoder. Additional instruments control model attitude and balance temperature and monitor sting vibrations. Other instruments perform self-calibration and diagnostics. Procedures for conducting calibrations and wind-off and wind-on tests are listed.

Evaluation of subgrid-scale models in large-eddy simulations of turbulent flow in a centrifugal pump impeller

NASA Astrophysics Data System (ADS)

Yang, Zhengjun; Wang, Fujun; Zhou, Peijian

2012-09-01

The current research of large eddy simulation (LES) of turbulent flow in pumps mainly concentrates in applying conventional subgrid-scale (SGS) model to simulate turbulent flow, which aims at obtaining the flow field in pump. The selection of SGS model is usually not considered seriously, so the accuracy and efficiency of the simulation cannot be ensured. Three SGS models including Smagorinsky-Lilly model, dynamic Smagorinsky model and dynamic mixed model are comparably studied by using the commercial CFD code Fluent combined with its user define function. The simulations are performed for the turbulent flow in a centrifugal pump impeller. The simulation results indicate that the mean flows predicted by the three SGS models agree well with the experimental data obtained from the test that detailed measurements of the flow inside the rotating passages of a six-bladed shrouded centrifugal pump impeller performed using particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). The comparable results show that dynamic mixed model gives the most accurate results for mean flow in the centrifugal pump impeller. The SGS stress of dynamic mixed model is decompose into the scale similar part and the eddy viscous part. The scale similar part of SGS stress plays a significant role in high curvature regions, such as the leading edge and training edge of pump blade. It is also found that the dynamic mixed model is more adaptive to compute turbulence in the pump impeller. The research results presented is useful to improve the computational accuracy and efficiency of LES for centrifugal pumps, and provide important reference for carrying out simulation in similar fluid machineries.

A computational cognitive model of self-efficacy and daily adherence in mHealth.

PubMed

Pirolli, Peter

2016-12-01

Mobile health (mHealth) applications provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting day-to-day health behavior change dynamics. A computational predictive model (ACT-R-DStress) is presented and fit to individual daily adherence in 28-day mHealth exercise programs. The ACT-R-DStress model refines the psychological construct of self-efficacy. To explain and predict the dynamics of self-efficacy and predict individual performance of targeted behaviors, the self-efficacy construct is implemented as a theory-based neurocognitive simulation of the interaction of behavioral goals, memories of past experiences, and behavioral performance.

Data management system performance modeling

NASA Technical Reports Server (NTRS)

Kiser, Larry M.

1993-01-01

This paper discusses analytical techniques that have been used to gain a better understanding of the Space Station Freedom's (SSF's) Data Management System (DMS). The DMS is a complex, distributed, real-time computer system that has been redesigned numerous times. The implications of these redesigns have not been fully analyzed. This paper discusses the advantages and disadvantages for static analytical techniques such as Rate Monotonic Analysis (RMA) and also provides a rationale for dynamic modeling. Factors such as system architecture, processor utilization, bus architecture, queuing, etc. are well suited for analysis with a dynamic model. The significance of performance measures for a real-time system are discussed.

Extended Kalman Filter for Estimation of Parameters in Nonlinear State-Space Models of Biochemical Networks

PubMed Central

Sun, Xiaodian; Jin, Li; Xiong, Momiao

2008-01-01

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

García-Algarra, Javier; Galeano, Javier; Pastor, Juan Manuel; Iriondo, José María; Ramasco, José J

2014-12-21

Mutualistic communities have an internal structure that makes them resilient to external perturbations. Late research has focused on their stability and the topology of the relations between the different organisms to explain the reasons of the system robustness. Much less attention has been invested in analyzing the systems dynamics. The main population models in use are modifications of the r-K formulation of logistic equation with additional terms to account for the benefits produced by the interspecific interactions. These models have shortcomings as the so-called r-K formulation diverges under some conditions. In this work, we introduce a model for population dynamics under mutualism that preserves the original logistic formulation. It is mathematically simpler than the widely used type II models, although it shows similar complexity in terms of fixed points and stability of the dynamics. We perform an analytical stability analysis and numerical simulations to study the model behavior in general interaction scenarios including tests of the resilience of its dynamics under external perturbations. Despite its simplicity, our results indicate that the model dynamics shows an important richness that can be used to gain further insights in the dynamics of mutualistic communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

Theory and Programs for Dynamic Modeling of Tree Rings from Climate

Treesearch

Paul C. van Deusen; Jennifer Koretz

1988-01-01

Computer programs written in GAUSS(TM) for IBM compatible personal computers are described that perform dynamic tree ring modeling with climate data; the underlying theory is also described. The programs and a separate users manual are available from the authors, although users must have the GAUSS software package on their personal computer. An example application of...

Measuring, managing and maximizing refinery performance

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

Bascur, O.A.; Kennedy, J.P.

1996-01-01

Implementing continuous quality improvement is a confluence of total quality management, people empowerment, performance indicators and information engineering. Supporting information technologies allow a refiner to narrow the gap between management objectives and the process control level. Dynamic performance monitoring benefits come from production cost savings, improved communications and enhanced decision making. A refinery workgroup information flow model helps automate continuous improvement of processes, performance and the organization. The paper discusses the rethinking of refinery operations, dynamic performance monitoring, continuous process improvement, the knowledge coordinator and repository manager, an integrated plant operations workflow, and successful implementation.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Modelling, simulation and applications of longitudinal train dynamics

NASA Astrophysics Data System (ADS)

Cole, Colin; Spiryagin, Maksym; Wu, Qing; Sun, Yan Quan

2017-10-01

Significant developments in longitudinal train simulation and an overview of the approaches to train models and modelling vehicle force inputs are firstly presented. The most important modelling task, that of the wagon connection, consisting of energy absorption devices such as draft gears and buffers, draw gear stiffness, coupler slack and structural stiffness is then presented. Detailed attention is given to the modelling approaches for friction wedge damped and polymer draft gears. A significant issue in longitudinal train dynamics is the modelling and calculation of the input forces - the co-dimensional problem. The need to push traction performances higher has led to research and improvement in the accuracy of traction modelling which is discussed. A co-simulation method that combines longitudinal train simulation, locomotive traction control and locomotive vehicle dynamics is presented. The modelling of other forces, braking propulsion resistance, curve drag and grade forces are also discussed. As extensions to conventional longitudinal train dynamics, lateral forces and coupler impacts are examined in regards to interaction with wagon lateral and vertical dynamics. Various applications of longitudinal train dynamics are then presented. As an alternative to the tradition single wagon mass approach to longitudinal train dynamics, an example incorporating fully detailed wagon dynamics is presented for a crash analysis problem. Further applications of starting traction, air braking, distributed power, energy analysis and tippler operation are also presented.

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

Reducing calibration parameters to increase insight in catchment organization and similarity

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Onof, Christian

2013-04-01

Ideally, hydrological models should be built from equations parameterised from observed catchment characteristics and data. This state of affairs may never be reached, but a governing principle in hydrological modelling should be to keep the number of calibration parameters to a minimum. A reduced number of parameters to be calibrated, while maintaining the accuracy and detail required by modern hydrological models, will reduce parameter and model structure uncertainty and improve model diagnostics. The dynamics of runoff for small catchments are derived from the distribution of distances from points in the catchments to the nearest stream in a catchment. This distribution is unique for each catchment and can be determined from a geographical information system (GIS). The distribution of distances, will, when a celerity of (subsurface) flow is introduced, provide a distribution of travel times, or a unit hydrograph (UH). For spatially varying levels of saturation deficit we have different celerities and, hence, different UHs. Runoff is derived from the super-positioning of the different UHs. This study shows how celerities can be estimated if we assume that recession events represent the superpositioned UH for different levels of saturation deficit. The performance of the DDD (Distance Distribution Dynamics) model is compared to that of the Swedish HBV model and is found to perform equally well for eight Norwegian catchments although the number of parameters to be calibrated in the module concerning soil moisture and runoff dynamics is reduced from 7 in the HBV model to 1 in the DDD model. It is also shown that the DDD model has a more realistic representation of the subsurface hydrology. The transparency of the DDD model makes model diagnostics more easy and experience with DDD shows that differences in model performance may be related to differences in catchment characteristics. More specifically, it appears that the hydrological dynamics of bogs have to be taken especially into account when modelling Norwegian catchments.

Dynamical simulation of E-ELT segmented primary mirror

NASA Astrophysics Data System (ADS)

Sedghi, B.; Muller, M.; Bauvir, B.

2011-09-01

The dynamical behavior of the primary mirror (M1) has an important impact on the control of the segments and the performance of the telescope. Control of large segmented mirrors with a large number of actuators and sensors and multiple control loops in real life is a challenging problem. In virtual life, modeling, simulation and analysis of the M1 bears similar difficulties and challenges. In order to capture the dynamics of the segment subunits (high frequency modes) and the telescope back structure (low frequency modes), high order dynamical models with a very large number of inputs and outputs need to be simulated. In this paper, different approaches for dynamical modeling and simulation of the M1 segmented mirror subject to various perturbations, e.g. sensor noise, wind load, vibrations, earthquake are presented.

Simulation of noisy dynamical system by Deep Learning

NASA Astrophysics Data System (ADS)

Yeo, Kyongmin

2017-11-01

Deep learning has attracted huge attention due to its powerful representation capability. However, most of the studies on deep learning have been focused on visual analytics or language modeling and the capability of the deep learning in modeling dynamical systems is not well understood. In this study, we use a recurrent neural network to model noisy nonlinear dynamical systems. In particular, we use a long short-term memory (LSTM) network, which constructs internal nonlinear dynamics systems. We propose a cross-entropy loss with spatial ridge regularization to learn a non-stationary conditional probability distribution from a noisy nonlinear dynamical system. A Monte Carlo procedure to perform time-marching simulations by using the LSTM is presented. The behavior of the LSTM is studied by using noisy, forced Van der Pol oscillator and Ikeda equation.

Clinical time series prediction: towards a hierarchical dynamical system framework

PubMed Central

Liu, Zitao; Hauskrecht, Milos

2014-01-01

Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. PMID:25534671

Towards a Population Dynamics Theory for Evolutionary Computing: Learning from Biological Population Dynamics in Nature

NASA Astrophysics Data System (ADS)

Ma, Zhanshan (Sam)

In evolutionary computing (EC), population size is one of the critical parameters that a researcher has to deal with. Hence, it was no surprise that the pioneers of EC, such as De Jong (1975) and Holland (1975), had already studied the population sizing from the very beginning of EC. What is perhaps surprising is that more than three decades later, we still largely depend on the experience or ad-hoc trial-and-error approach to set the population size. For example, in a recent monograph, Eiben and Smith (2003) indicated: "In almost all EC applications, the population size is constant and does not change during the evolutionary search." Despite enormous research on this issue in recent years, we still lack a well accepted theory for population sizing. In this paper, I propose to develop a population dynamics theory forEC with the inspiration from the population dynamics theory of biological populations in nature. Essentially, the EC population is considered as a dynamic system over time (generations) and space (search space or fitness landscape), similar to the spatial and temporal dynamics of biological populations in nature. With this conceptual mapping, I propose to 'transplant' the biological population dynamics theory to EC via three steps: (i) experimentally test the feasibility—whether or not emulating natural population dynamics improves the EC performance; (ii) comparatively study the underlying mechanisms—why there are improvements, primarily via statistical modeling analysis; (iii) conduct theoretical analysis with theoretical models such as percolation theory and extended evolutionary game theory that are generally applicable to both EC and natural populations. This article is a summary of a series of studies we have performed to achieve the general goal [27][30]-[32]. In the following, I start with an extremely brief introduction on the theory and models of natural population dynamics (Sections 1 & 2). In Sections 4 to 6, I briefly discuss three categories of population dynamics models: deterministic modeling with Logistic chaos map as an example, stochastic modeling with spatial distribution patterns as an example, as well as survival analysis and extended evolutionary game theory (EEGT) modeling. Sample experiment results with Genetic algorithms (GA) are presented to demonstrate the applications of these models. The proposed EC population dynamics approach also makes survival selection largely unnecessary or much simplified since the individuals are naturally selected (controlled) by the mathematical models for EC population dynamics.

Attitude determination using an adaptive multiple model filtering Scheme

NASA Technical Reports Server (NTRS)

Lam, Quang; Ray, Surendra N.

1995-01-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

Attitude determination using an adaptive multiple model filtering Scheme

NASA Astrophysics Data System (ADS)

Lam, Quang; Ray, Surendra N.

1995-05-01

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

A Model Comparison for Characterizing Protein Motions from Structure

NASA Astrophysics Data System (ADS)

David, Charles; Jacobs, Donald

2011-10-01

A comparative study is made using three computational models that characterize native state dynamics starting from known protein structures taken from four distinct SCOP classifications. A geometrical simulation is performed, and the results are compared to the elastic network model and molecular dynamics. The essential dynamics is quantified by a direct analysis of a mode subspace constructed from ANM and a principal component analysis on both the FRODA and MD trajectories using root mean square inner product and principal angles. Relative subspace sizes and overlaps are visualized using the projection of displacement vectors on the model modes. Additionally, a mode subspace is constructed from PCA on an exemplar set of X-ray crystal structures in order to determine similarly with respect to the generated ensembles. Quantitative analysis reveals there is significant overlap across the three model subspaces and the model independent subspace. These results indicate that structure is the key determinant for native state dynamics.

Roll and pitch independently tuned interconnected suspension: modelling and dynamic analysis

NASA Astrophysics Data System (ADS)

Xu, Guangzhong; Zhang, Nong; Roser, Holger M.

2015-12-01

In this paper, a roll and pitch independently tuned hydraulically interconnected passive suspension is presented. Due to decoupling of vibration modes and the improved lateral and longitudinal stability, the stiffness of individual suspension spring can be reduced for improving ride comfort and road grip. A generalised 14 degree-of-freedom nonlinear vehicle model with anti-roll bars is established to investigate the vehicle ride and handling dynamic responses. The nonlinear fluidic model of the hydraulically interconnected suspension is developed and integrated with the full vehicle model to investigate the anti-roll and anti-pitch characteristics. Time domain analysis of the vehicle model with the proposed suspension is conducted under different road excitations and steering/braking manoeuvres. The dynamic responses are compared with conventional suspensions to demonstrate the potential of enhanced ride and handling performance. The results illustrate the model-decoupling property of the hydraulically interconnected system. The anti-roll and anti-pitch performance could be tuned independently by the interconnected systems. With the improved anti-roll and anti-pitch characteristics, the bounce stiffness and ride damping can be optimised for better ride comfort and tyre grip.

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

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

Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU

NASA Astrophysics Data System (ADS)

Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji

2016-12-01

Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.

Modeling the dynamic stiffness of cracked reinforced concrete beams under low-amplitude vibration loads

NASA Astrophysics Data System (ADS)

Xu, Tengfei; Castel, Arnaud

2016-04-01

In this paper, a model, initially developed to calculate the stiffness of cracked reinforced concrete beams under static loading, is used to assess the dynamic stiffness. The model allows calculating the average inertia of cracked beams by taking into account the effect of bending cracks (primary cracks) and steel-concrete bond damage (i.e. interfacial microcracks). Free and forced vibration experiments are used to assess the performance of the model. The respective influence of bending cracks and steel-concrete bond damage on both static and dynamic responses is analyzed. The comparison between experimental and simulated deflections confirms that the effects of both bending cracks and steel-concrete bond loss should be taken into account to assess reinforced concrete stiffness under service static loading. On the contrary, comparison of experimental and calculated dynamic responses reveals that localized steel-concrete bond damages do not influence significantly the dynamic stiffness and the fundamental frequency.

Sliding-Mode Control Applied for Robust Control of a Highly Unstable Aircraft

NASA Technical Reports Server (NTRS)

Vetter, Travis Kenneth

2002-01-01

An investigation into the application of an observer based sliding mode controller for robust control of a highly unstable aircraft and methods of compensating for actuator dynamics is performed. After a brief overview of some reconfigurable controllers, sliding mode control (SMC) is selected because of its invariance properties and lack of need for parameter identification. SMC is reviewed and issues with parasitic dynamics, which cause system instability, are addressed. Utilizing sliding manifold boundary layers, the nonlinear control is converted to a linear control and sliding manifold design is performed in the frequency domain. An additional feedback form of model reference hedging is employed which is similar to a prefilter and has large benefits to system performance. The effects of inclusion of actuator dynamics into the designed plant is heavily investigated. Multiple Simulink models of the full longitudinal dynamics and wing deflection modes of the forward swept aero elastic vehicle (FSAV) are constructed. Additionally a linear state space models to analyze effects from various system parameters. The FSAV has a pole at +7 rad/sec and is non-minimum phase. The use of 'model actuators' in the feedback path, and varying there design, is heavily investigated for the resulting effects on plant robustness and tolerance to actuator failure. The use of redundant actuators is also explored and improved robustness is shown. All models are simulated with severe failure and excellent tracking, and task dependent handling qualities, and low pilot induced oscillation tendency is shown.

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic

PubMed Central

de Groot, Maartje H.; van Campen, Jos P.; Beijnen, Jos H.; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C. J.

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares–Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified ‘pace’, ‘variability’, and ‘coordination’ as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients’ fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics. PMID:28575126

Gait dynamics to optimize fall risk assessment in geriatric patients admitted to an outpatient diagnostic clinic.

PubMed

Kikkert, Lisette H J; de Groot, Maartje H; van Campen, Jos P; Beijnen, Jos H; Hortobágyi, Tibor; Vuillerme, Nicolas; Lamoth, Claudine C J

2017-01-01

Fall prediction in geriatric patients remains challenging because the increased fall risk involves multiple, interrelated factors caused by natural aging and/or pathology. Therefore, we used a multi-factorial statistical approach to model categories of modifiable fall risk factors among geriatric patients to identify fallers with highest sensitivity and specificity with a focus on gait performance. Patients (n = 61, age = 79; 41% fallers) underwent extensive screening in three categories: (1) patient characteristics (e.g., handgrip strength, medication use, osteoporosis-related factors) (2) cognitive function (global cognition, memory, executive function), and (3) gait performance (speed-related and dynamic outcomes assessed by tri-axial trunk accelerometry). Falls were registered prospectively (mean follow-up 8.6 months) and one year retrospectively. Principal Component Analysis (PCA) on 11 gait variables was performed to determine underlying gait properties. Three fall-classification models were then built using Partial Least Squares-Discriminant Analysis (PLS-DA), with separate and combined analyses of the fall risk factors. PCA identified 'pace', 'variability', and 'coordination' as key properties of gait. The best PLS-DA model produced a fall classification accuracy of AUC = 0.93. The specificity of the model using patient characteristics was 60% but reached 80% when cognitive and gait outcomes were added. The inclusion of cognition and gait dynamics in fall classification models reduced misclassification. We therefore recommend assessing geriatric patients' fall risk using a multi-factorial approach that incorporates patient characteristics, cognition, and gait dynamics.

A Dynamic Network Model to Explain the Development of Excellent Human Performance

PubMed Central

Den Hartigh, Ruud J. R.; Van Dijk, Marijn W. G.; Steenbeek, Henderien W.; Van Geert, Paul L. C.

2016-01-01

Across different domains, from sports to science, some individuals accomplish excellent levels of performance. For over 150 years, researchers have debated the roles of specific nature and nurture components to develop excellence. In this article, we argue that the key to excellence does not reside in specific underlying components, but rather in the ongoing interactions among the components. We propose that excellence emerges out of dynamic networks consisting of idiosyncratic mixtures of interacting components such as genetic endowment, motivation, practice, and coaching. Using computer simulations we demonstrate that the dynamic network model accurately predicts typical properties of excellence reported in the literature, such as the idiosyncratic developmental trajectories leading to excellence and the highly skewed distributions of productivity present in virtually any achievement domain. Based on this novel theoretical perspective on excellent human performance, this article concludes by suggesting policy implications and directions for future research. PMID:27148140

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

Quasi One-Dimensional Unsteady Modeling of External Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Kratz, Jonathan

2012-01-01

The AeroServoElasticity task under the NASA Supersonics Project is developing dynamic models of the propulsion system and the vehicle in order to conduct research for integrated vehicle dynamic performance. As part of this effort, a nonlinear quasi 1-dimensional model of an axisymmetric external compression supersonic inlet is being developed. The model utilizes compressible flow computational fluid dynamics to model the internal inlet segment as well as the external inlet portion between the cowl lip and normal shock, and compressible flow relations with flow propagation delay to model the oblique shocks upstream of the normal shock. The external compression portion between the cowl-lip and the normal shock is also modeled with leaking fluxes crossing the sonic boundary, with a moving CFD domain at the normal shock boundary. This model has been verified in steady state against tunnel inlet test data and it s a first attempt towards developing a more comprehensive model for inlet dynamics.

Deterministic processes guide long-term synchronised population dynamics in replicate anaerobic digesters

PubMed Central

Vanwonterghem, Inka; Jensen, Paul D; Dennis, Paul G; Hugenholtz, Philip; Rabaey, Korneel; Tyson, Gene W

2014-01-01

A replicate long-term experiment was conducted using anaerobic digestion (AD) as a model process to determine the relative role of niche and neutral theory on microbial community assembly, and to link community dynamics to system performance. AD is performed by a complex network of microorganisms and process stability relies entirely on the synergistic interactions between populations belonging to different functional guilds. In this study, three independent replicate anaerobic digesters were seeded with the same diverse inoculum, supplied with a model substrate, α-cellulose, and operated for 362 days at a 10-day hydraulic residence time under mesophilic conditions. Selective pressure imposed by the operational conditions and model substrate caused large reproducible changes in community composition including an overall decrease in richness in the first month of operation, followed by synchronised population dynamics that correlated with changes in reactor performance. This included the synchronised emergence and decline of distinct Ruminococcus phylotypes at day 148, and emergence of a Clostridium and Methanosaeta phylotype at day 178, when performance became stable in all reactors. These data suggest that many dynamic functional niches are predictably filled by phylogenetically coherent populations over long time scales. Neutral theory would predict that a complex community with a high degree of recognised functional redundancy would lead to stochastic changes in populations and community divergence over time. We conclude that deterministic processes may play a larger role in microbial community dynamics than currently appreciated, and under controlled conditions it may be possible to reliably predict community structural and functional changes over time. PMID:24739627

Transport dissipative particle dynamics model for mesoscopic advection-diffusion-reaction problems

PubMed Central

Yazdani, Alireza; Tartakovsky, Alexandre; Karniadakis, George Em

2015-01-01

We present a transport dissipative particle dynamics (tDPD) model for simulating mesoscopic problems involving advection-diffusion-reaction (ADR) processes, along with a methodology for implementation of the correct Dirichlet and Neumann boundary conditions in tDPD simulations. tDPD is an extension of the classic dissipative particle dynamics (DPD) framework with extra variables for describing the evolution of concentration fields. The transport of concentration is modeled by a Fickian flux and a random flux between tDPD particles, and the advection is implicitly considered by the movements of these Lagrangian particles. An analytical formula is proposed to relate the tDPD parameters to the effective diffusion coefficient. To validate the present tDPD model and the boundary conditions, we perform three tDPD simulations of one-dimensional diffusion with different boundary conditions, and the results show excellent agreement with the theoretical solutions. We also performed two-dimensional simulations of ADR systems and the tDPD simulations agree well with the results obtained by the spectral element method. Finally, we present an application of the tDPD model to the dynamic process of blood coagulation involving 25 reacting species in order to demonstrate the potential of tDPD in simulating biological dynamics at the mesoscale. We find that the tDPD solution of this comprehensive 25-species coagulation model is only twice as computationally expensive as the conventional DPD simulation of the hydrodynamics only, which is a significant advantage over available continuum solvers. PMID:26156459

Extended cooperative control synthesis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1994-01-01

This paper reports on research for extending the Cooperative Control Synthesis methodology to include a more accurate modeling of the pilot's controller dynamics. Cooperative Control Synthesis (CCS) is a methodology that addresses the problem of how to design control laws for piloted, high-order, multivariate systems and/or non-conventional dynamic configurations in the absence of flying qualities specifications. This is accomplished by emphasizing the parallel structure inherent in any pilot-controlled, augmented vehicle. The original CCS methodology is extended to include the Modified Optimal Control Model (MOCM), which is based upon the optimal control model of the human operator developed by Kleinman, Baron, and Levison in 1970. This model provides a modeling of the pilot's compensation dynamics that is more accurate than the simplified pilot dynamic representation currently in the CCS methodology. Inclusion of the MOCM into the CCS also enables the modeling of pilot-observation perception thresholds and pilot-observation attention allocation affects. This Extended Cooperative Control Synthesis (ECCS) allows for the direct calculation of pilot and system open- and closed-loop transfer functions in pole/zero form and is readily implemented in current software capable of analysis and design for dynamic systems. Example results based upon synthesizing an augmentation control law for an acceleration command system in a compensatory tracking task using the ECCS are compared with a similar synthesis performed by using the original CCS methodology. The ECCS is shown to provide augmentation control laws that yield more favorable, predicted closed-loop flying qualities and tracking performance than those synthesized using the original CCS methodology.

Modelling Ni-mH battery using Cauer and Foster structures

NASA Astrophysics Data System (ADS)

Kuhn, E.; Forgez, C.; Lagonotte, P.; Friedrich, G.

This paper deals with dynamic models of Ni-mH battery and focuses on the development of the equivalent electric models. We propose two equivalent electric models, using Cauer and Foster structures, able to relate both dynamic and energetic behavior of the battery. These structures are well adapted to real time applications (e.g. Battery Management Systems) or system simulations. A special attention will be brought to the influence of the complexity of the equivalent electric scheme on the precision of the model. Experimental validations allow to discuss about performances of proposed models.

Optimal blood glucose control in diabetes mellitus treatment using dynamic programming based on Ackerman’s linear model

NASA Astrophysics Data System (ADS)

Pradanti, Paskalia; Hartono

2018-03-01

Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.

Thermal characterization assessment of rigid and flexible water models in a nanogap using molecular dynamics

NASA Astrophysics Data System (ADS)

Akıner, Tolga; Mason, Jeremy; Ertürk, Hakan

2017-11-01

The thermal properties of the TIP3P and TIP5P water models are investigated using equilibrium and non-equilibrium molecular dynamics techniques in the presence of solid surfaces. The performance of the non-equilibrium technique for rigid molecules is found to depend significantly on the distribution of atomic degrees of freedom. An improved approach to distribute atomic degrees of freedom is proposed for which the thermal conductivity of the TIP5P model agrees more closely with equilibrium molecular dynamics and experimental results than the existing state of the art.

A comprehensive analytical model of rotorcraft aerodynamics and dynamics. Part 3: Program manual

NASA Technical Reports Server (NTRS)

Johnson, W.

1980-01-01

The computer program for a comprehensive analytical model of rotorcraft aerodynamics and dynamics is described. This analysis is designed to calculate rotor performance, loads, and noise; the helicopter vibration and gust response; the flight dynamics and handling qualities; and the system aeroelastic stability. The analysis is a combination of structural, inertial, and aerodynamic models that is applicable to a wide range of problems and a wide class of vehicles. The analysis is intended for use in the design, testing, and evaluation of rotors and rotorcraft and to be a basis for further development of rotary wing theories.

NetFlow Dynamics

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

Corbet Jr., Thomas F; Beyeler, Walter E; Vanwestrienen, Dirk

NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows aremore » dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored at each node of the network. In the petroleum models, the flowing materials are crude oil and refined products that can be stored at tank farms, refineries, or terminals (i.e. the nodes of the network). Examples of other network models that could be simulated are currency flowing in a financial network, agricultural products moving to market, or natural gas flowing on a pipeline network.« less

Molecular dynamics on diffusive time scales from the phase-field-crystal equation.

PubMed

Chan, Pak Yuen; Goldenfeld, Nigel; Dantzig, Jon

2009-03-01

We extend the phase-field-crystal model to accommodate exact atomic configurations and vacancies by requiring the order parameter to be non-negative. The resulting theory dictates the number of atoms and describes the motion of each of them. By solving the dynamical equation of the model, which is a partial differential equation, we are essentially performing molecular dynamics simulations on diffusive time scales. To illustrate this approach, we calculate the two-point correlation function of a fluid.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Dynamic electrical response of solar cells

NASA Technical Reports Server (NTRS)

Catani, J. P.

1981-01-01

The dynamic response of a solar generator is of primary importance as much for the design and development of electrical power conditioning hardware as for the analysis of electromagnetic compatibility. A mathematical model of photo-batteries was developed on the basis of impedance measurements performed under differing conditions of temperature, light intensity, before and after irradiation. This model was compared with that derived from PN junction theory and to static measurements. These dynamic measurements enabled the refinement of an integration method capable of determining, under normal laboratory conditions, the dynamic response of a generator to operational lighting conditions.

Development of a solid propellant viscoelastic dynamic model

NASA Technical Reports Server (NTRS)

Hufferd, W. L.; Fitzgerald, J. E.

1976-01-01

The results of a one year study to develop a dynamic response model for the Space Shuttle Solid Rocket Motor (SRM) propellant are presented. An extensive literature survey was conducted, from which it was concluded that the only significant variables affecting the dynamic response of the SRM propellant are temperature and frequency. Based on this study, and experimental data on propellants related to the SRM propellant, a dynamic constitutive model was developed in the form of a simple power law with temperature incorporated in the form of a modified power law. A computer program was generated which performs a least-squares curve-fit of laboratory data to determine the model parameters and it calculates dynamic moduli at any desired temperature and frequency. Additional studies investigated dynamic scaling laws and the extent of coupling between the SRM propellant and motor cases. It was found, in agreement with other investigations, that the propellant provides all of the mass and damping characteristics whereas the case provides all of the stiffness.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

6DOF Testing of the SLS Inertial Navigation Unit

NASA Technical Reports Server (NTRS)

Geohagan, Kevin W.; Bernard, William P.; Oliver, T. Emerson; Strickland, Dennis J.; Leggett, Jared O.

2018-01-01

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Dynamic system simulation of small satellite projects

NASA Astrophysics Data System (ADS)

Raif, Matthias; Walter, Ulrich; Bouwmeester, Jasper

2010-11-01

A prerequisite to accomplish a system simulation is to have a system model holding all necessary project information in a centralized repository that can be accessed and edited by all parties involved. At the Institute of Astronautics of the Technische Universitaet Muenchen a modular approach for modeling and dynamic simulation of satellite systems has been developed called dynamic system simulation (DySyS). DySyS is based on the platform independent description language SysML to model a small satellite project with respect to the system composition and dynamic behavior. A library of specific building blocks and possible relations between these blocks have been developed. From this library a system model of the satellite of interest can be created. A mapping into a C++ simulation allows the creation of an executable system model with which simulations are performed to observe the dynamic behavior of the satellite. In this paper DySyS is used to model and simulate the dynamic behavior of small satellites, because small satellite projects can act as a precursor to demonstrate the feasibility of a system model since they are less complex compared to a large scale satellite project.

Self similarities in desalination dynamics and performance using capacitive deionization.

PubMed

Ramachandran, Ashwin; Hemmatifar, Ali; Hawks, Steven A; Stadermann, Michael; Santiago, Juan G

2018-09-01

Charge transfer and mass transport are two underlying mechanisms which are coupled in desalination dynamics using capacitive deionization (CDI). We developed simple reduced-order models based on a mixed reactor volume principle which capture the coupled dynamics of CDI operation using closed-form semi-analytical and analytical solutions. We use the models to identify and explore self-similarities in the dynamics among flow rate, current, and voltage for CDI cell operation including both charging and discharging cycles. The similarity approach identifies the specific combination of cell (e.g. capacitance, resistance) and operational parameters (e.g. flow rate, current) which determine a unique effluent dynamic response. We here demonstrate self-similarity using a conventional flow between CDI (fbCDI) architecture, and we hypothesize that our similarity approach has potential application to a wide range of designs. We performed an experimental study of these dynamics and used well-controlled experiments of CDI cell operation to validate and explore limits of the model. For experiments, we used a CDI cell with five electrode pairs and a standard flow between (electrodes) architecture. Guided by the model, we performed a series of experiments that demonstrate natural response of the CDI system. We also identify cell parameters and operation conditions which lead to self-similar dynamics under a constant current forcing function and perform a series of experiments by varying flowrate, currents, and voltage thresholds to demonstrate self-similarity. Based on this study, we hypothesize that the average differential electric double layer (EDL) efficiency (a measure of ion adsorption rate to EDL charging rate) is mainly dependent on user-defined voltage thresholds, whereas flow efficiency (measure of how well desalinated water is recovered from inside the cell) depends on cell volumes flowed during charging, which is determined by flowrate, current and voltage thresholds. Results of experiments strongly support this hypothesis. Results show that cycle efficiency and salt removal for a given flowrate and current are maximum when average EDL and flow efficiencies are approximately equal. We further explored a range of CC operations with varying flowrates, currents, and voltage thresholds using our similarity variables to highlight trade-offs among salt removal, energy, and throughput performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

FDNS CFD Code Benchmark for RBCC Ejector Mode Operation

NASA Technical Reports Server (NTRS)

Holt, James B.; Ruf, Joe

1999-01-01

Computational Fluid Dynamics (CFD) analysis results are compared with benchmark quality test data from the Propulsion Engineering Research Center's (PERC) Rocket Based Combined Cycle (RBCC) experiments to verify fluid dynamic code and application procedures. RBCC engine flowpath development will rely on CFD applications to capture the multi-dimensional fluid dynamic interactions and to quantify their effect on the RBCC system performance. Therefore, the accuracy of these CFD codes must be determined through detailed comparisons with test data. The PERC experiments build upon the well-known 1968 rocket-ejector experiments of Odegaard and Stroup by employing advanced optical and laser based diagnostics to evaluate mixing and secondary combustion. The Finite Difference Navier Stokes (FDNS) code was used to model the fluid dynamics of the PERC RBCC ejector mode configuration. Analyses were performed for both Diffusion and Afterburning (DAB) and Simultaneous Mixing and Combustion (SMC) test conditions. Results from both the 2D and the 3D models are presented.

The dynamic simulation of the Progetto Energia combined cycle power plants

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

Giglio, R.; Cerabolini, M.; Pisacane, F.

1996-12-31

Over the next four years, the Progetto Energia project is building several cogeneration plants to satisfy the increasing demands of Italy`s industrial complex and the country`s demand for electrical power. Located at six different sites within Italy`s borders these Combined Cycle Cogeneration Plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50 MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipmentmore » performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam de-superheating performance. Simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The paper discusses the Combined Cycle plant configuration, its operating modes and control system, the dynamic model representation, the simulation results and project benefits.« less

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

High-Order Shock-Capturing Methods for Modeling Dynamics of the Solar Atmosphere

NASA Technical Reports Server (NTRS)

Bryson, Steve; Kosovichev, Alexander; Levy, Doron

2004-01-01

We use one-dimensional high-order central shock capturing numerical methods to study the response of various model solar atmospheres to forcing at the solar surface. The dynamics of the atmosphere is modeled with the Euler equations in a variable-sized flux tube in the presence of gravity. We study dynamics of the atmosphere suggestive of spicule formation and coronal oscillations. These studies are performed on observationally-derived model atmospheres above the quiet sun and above sunspots. To perform these simulations, we provide a new extension of existing second- and third- order shock-capturing methods to irregular grids. We also solve the problem of numerically maintaining initial hydrostatic balance via the introduction of new variables in the model equations and a careful initialization mechanism. We find several striking results: all model atmospheres respond to a single impulsive perturbation with several strong shock waves consistent with the rebound-shock model. These shock waves lift material and the transition region well into the initial corona, and the sensitivity of this lift to the initial impulse depends non-linearly on the details of the atmosphere model. We also reproduce an observed 3-minute coronal oscillation above sunspots compared to 5-minute oscillations above the quiet sun.

Predictive and Reactive Distribution of Vaccines and Antivirals during Cross-Regional Pandemic Outbreaks

PubMed Central

Uribe-Sánchez, Andrés; Savachkin, Alex

2011-01-01

As recently pointed out by the Institute of Medicine, the existing pandemic mitigation models lack the dynamic decision support capability. We develop a large-scale simulation-driven optimization model for generating dynamic predictive distribution of vaccines and antivirals over a network of regional pandemic outbreaks. The model incorporates measures of morbidity, mortality, and social distancing, translated into the cost of lost productivity and medical expenses. The performance of the strategy is compared to that of the reactive myopic policy, using a sample outbreak in Fla, USA, with an affected population of over four millions. The comparison is implemented at different levels of vaccine and antiviral availability and administration capacity. Sensitivity analysis is performed to assess the impact of variability of some critical factors on policy performance. The model is intended to support public health policy making for effective distribution of limited mitigation resources. PMID:23074658

Slow Dynamics Model of Compressed Air Energy Storage and Battery Storage Technologies for Automatic Generation Control

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

Krishnan, Venkat; Das, Trishna

Increasing variable generation penetration and the consequent increase in short-term variability makes energy storage technologies look attractive, especially in the ancillary market for providing frequency regulation services. This paper presents slow dynamics model for compressed air energy storage and battery storage technologies that can be used in automatic generation control studies to assess the system frequency response and quantify the benefits from storage technologies in providing regulation service. The paper also represents the slow dynamics model of the power system integrated with storage technologies in a complete state space form. The storage technologies have been integrated to the IEEE 24more » bus system with single area, and a comparative study of various solution strategies including transmission enhancement and combustion turbine have been performed in terms of generation cycling and frequency response performance metrics.« less

Modeling carbon dynamics in mangrove ecosystems in North America and Eastern Africa

NASA Astrophysics Data System (ADS)

Trettin, C.; Dai, Z.; Birdsey, R.; Frolking, S. E.

2016-12-01

Assessing carbon (C) dynamics in mangroves is fundamental to understand their role in mitigating climate change as well as the myriad of ecosystems derived the wetland forest. A spatially-explicit process model, MCAT (Mangrove-Carbon-Assessment-Tool), was developed to estimate (1) C dynamics in mangrove ecosystems, including biomass, burial C, dissolved inorganic and organic C (DIC and DOC), particulate organic C (POC), and CH4 and soil CO2 fluxes, and (2) impacts of disturbances, including storms, fire, insects and harvesting, on C sequestration in mangrove ecosystems. MCAT was tested using observations from eight plots in Everglades National Park (ENP) in Florida of USA and the World Heritage site in Mexican Caribbean in Quintana Roo (QR). The model was applied for assessing C dynamics in mangrove forests with different eco-environmental conditions in Northern America and Eastern Africa. The metrics from the four model evaluation statistics, determination coefficient (R2=0.99), model performance efficiency (E=0.98), percent bias (PBIAS=1.06%), and the ratio of the root mean squared error to standard deviation (RRS=0.11) showed that the model performed well for assessing mangrove C at these plots with a high model performance efficiency. The simulated biomass for ENP and QR was in good agreement with observations although there are large differences in canopy stature among those plots, ranging from tall to dwarf mangroves. The simulated aboveground net primary productivity, burial C, DIC, DOC, POC and CH4 for the plot at ENP approximated the reported values. There are substantial differences in C sequestration and fluxes in mangroves to atmosphere and water place-to-place due to differences in ecological drivers. Climate and soils are key factors that impact C dynamics in mangrove ecosystems, including temperature and salinity, such that there are differences in C sequestration rates among these mangrove sites in southeastern USA, Mexican Caribbean and Zambezi River Delta of Mozambique.

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 1. Trajectories of life function priorities and genetic scaling.

PubMed

Martin, O; Sauvant, D

2010-12-01

The prediction of the control of nutrient partitioning, particularly energy, is a major issue in modelling dairy cattle performance. The proportions of energy channelled to physiological functions (growth, maintenance, gestation and lactation) change as the animal ages and reproduces, and according to its genotype and nutritional environment. This is the first of two papers describing a teleonomic model of individual performance during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. The conceptual framework is based on the coupling of a regulating sub-model providing teleonomic drives to govern the work of an operating sub-model scaled with genetic parameters. The regulating sub-model describes the dynamic partitioning of a mammal female's priority between life functions targeted to growth (G), ageing (A), balance of body reserves (R) and nutrient supply of the unborn (U), newborn (N) and suckling (S) calf. The so-called GARUNS dynamic pattern defines a trajectory of relative priorities, goal directed towards the survival of the individual for the continuation of the specie. The operating sub-model describes changes in body weight (BW) and composition, foetal growth, milk yield and composition and food intake in dairy cows throughout their lifespan, that is, during growth, over successive reproductive cycles and through ageing. This dynamic pattern of performance defines a reference trajectory of a cow under normal husbandry conditions and feed regimen. Genetic parameters are incorporated in the model to scale individual performance and simulate differences within and between breeds. The model was calibrated for dairy cows with literature data. The model was evaluated by comparison with simulations of previously published empirical equations of BW, body condition score, milk yield and composition and feed intake. This evaluation showed that the model adequately simulates these production variables throughout the lifespan, and across a range of dairy cattle genotypes.

Topographies and dynamics on multidimensional potential energy surfaces

NASA Astrophysics Data System (ADS)

Ball, Keith Douglas

The stochastic master equation is a valuable tool for elucidating potential energy surface (PES) details that govern structural relaxation in clusters, bulk systems, and protein folding. This work develops a comprehensive framework for studying non-equilibrium relaxation dynamics using the master equation. Since our master equations depend upon accurate partition function models for use in Rice-Ramsperger-Kassel-Marcus (RRK(M) transition state theory, this work introduces several such models employing various harmonic and anharmonic approximations and compares their predicted equilibrium population distributions with those determined from molecular dynamics. This comparison is performed for the fully-delineated surfaces (KCl)5 and Ar9 to evaluate model performance for potential surfaces with long- and short-range interactions, respectively. For each system, several models perform better than a simple harmonic approximation. While no model gives acceptable results for all minima, and optimal modeling strategies differ for (KCl)5 and Ar9, a particular one-parameter model gives the best agreement with simulation for both systems. We then construct master equations from these models and compare their isothermal relaxation predictions for (KCl)5 and Ar9 with molecular dynamics simulations. This is the first comprehensive test of the kinetic performance of partition function models of its kind. Our results show that accurate modeling of transition-state partition functions is more important for (KCl)5 than for Ar9 in reproducing simulation results, due to a marked stiffening anharmonicity in the transition-state normal modes of (KCl)5. For both systems, several models yield qualitative agreement with simulation over a large temperature range. To examine the robustness of the master equation when applied to larger systems, for which full topographical descriptions would be either impossible or infeasible, we compute relaxation predictions for Ar11 using a master equation constructed from data representing the full PES, and compare these predictions to those of reduced master equations based on statistical samples of the full PES. We introduce a sampling method which generates random, Boltzmann-weighted, energetically 'downhill' sequences. The study reveals that, at moderate temperatures, the slowest relaxation timescale converges as the number of sequences in a sample grows to ~1000. Furthermore, the asymptotic timescale is comparable to the full-PES value.

Reactivating dynamics for the susceptible-infected-susceptible model: a simple method to simulate the absorbing phase

NASA Astrophysics Data System (ADS)

Macedo-Filho, A.; Alves, G. A.; Costa Filho, R. N.; Alves, T. F. A.

2018-04-01

We investigated the susceptible-infected-susceptible model on a square lattice in the presence of a conjugated field based on recently proposed reactivating dynamics. Reactivating dynamics consists of reactivating the infection by adding one infected site, chosen randomly when the infection dies out, avoiding the dynamics being trapped in the absorbing state. We show that the reactivating dynamics can be interpreted as the usual dynamics performed in the presence of an effective conjugated field, named the reactivating field. The reactivating field scales as the inverse of the lattice number of vertices n, which vanishes at the thermodynamic limit and does not affect any scaling properties including ones related to the conjugated field.

Research on Turbofan Engine Model above Idle State Based on NARX Modeling Approach

NASA Astrophysics Data System (ADS)

Yu, Bing; Shu, Wenjun

2017-03-01

The nonlinear model for turbofan engine above idle state based on NARX is studied. Above all, the data sets for the JT9D engine from existing model are obtained via simulation. Then, a nonlinear modeling scheme based on NARX is proposed and several models with different parameters are built according to the former data sets. Finally, the simulations have been taken to verify the precise and dynamic performance the models, the results show that the NARX model can well reflect the dynamics characteristic of the turbofan engine with high accuracy.

Dynamics modeling and loads analysis of an offshore floating wind turbine

NASA Astrophysics Data System (ADS)

Jonkman, Jason Mark

The vast deepwater wind resource represents a potential to use offshore floating wind turbines to power much of the world with renewable energy. Many floating wind turbine concepts have been proposed, but dynamics models, which account for the wind inflow, aerodynamics, elasticity, and controls of the wind turbine, along with the incident waves, sea current, hydrodynamics, and platform and mooring dynamics of the floater, were needed to determine their technical and economic feasibility. This work presents the development of a comprehensive simulation tool for modeling the coupled dynamic response of offshore floating wind turbines, the verification of the simulation tool through model-to-model comparisons, and the application of the simulation tool to an integrated loads analysis for one of the promising system concepts. A fully coupled aero-hydro-servo-elastic simulation tool was developed with enough sophistication to address the limitations of previous frequency- and time-domain studies and to have the features required to perform loads analyses for a variety of wind turbine, support platform, and mooring system configurations. The simulation capability was tested using model-to-model comparisons. The favorable results of all of the verification exercises provided confidence to perform more thorough analyses. The simulation tool was then applied in a preliminary loads analysis of a wind turbine supported by a barge with catenary moorings. A barge platform was chosen because of its simplicity in design, fabrication, and installation. The loads analysis aimed to characterize the dynamic response and to identify potential loads and instabilities resulting from the dynamic couplings between the turbine and the floating barge in the presence of combined wind and wave excitation. The coupling between the wind turbine response and the barge-pitch motion, in particular, produced larger extreme loads in the floating turbine than experienced by an equivalent land-based turbine. Instabilities were also found in the system. The influence of conventional wind turbine blade-pitch control actions on the pitch damping of the floating turbine was also assessed. Design modifications for reducing the platform motions, improving the turbine response, and eliminating the instabilities are suggested. These suggestions are aimed at obtaining cost-effective designs that achieve favorable performance while maintaining structural integrity.

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

Fundamental Properties of Soils for Complex Dynamic Loadings: Dynamic Constitutive Modeling of Sandy Soils.

DTIC Science & Technology

1983-04-01

1.0 INTRODUCTION AND SCOPE 1 2.0 PROGRESS SUMMARY 3 2.1 Soil Element Model Development 3 2.2 U.S. Any Engineer Waterways Experiment Station (WES...LABORATORY BEHAVIOR OF SAND 8 3.1 Introduction 8 3.2 Material Description 8 3.3 Laboratory Tests Performed 9 3.4 Laboratory Test Results 14 4.0 MODELING THE... INTRODUCTION AND SCOPE The subject of this annual report is constitutive modeling of cohesionless soil, for both laboratory standard static test conditions

Tempo and mode of performance evolution across multiple independent origins of adhesive toe pads in lizards.

PubMed

Hagey, Travis J; Uyeda, Josef C; Crandell, Kristen E; Cheney, Jorn A; Autumn, Kellar; Harmon, Luke J

2017-10-01

Understanding macroevolutionary dynamics of trait evolution is an important endeavor in evolutionary biology. Ecological opportunity can liberate a trait as it diversifies through trait space, while genetic and selective constraints can limit diversification. While many studies have examined the dynamics of morphological traits, diverse morphological traits may yield the same or similar performance and as performance is often more proximately the target of selection, examining only morphology may give an incomplete understanding of evolutionary dynamics. Here, we ask whether convergent evolution of pad-bearing lizards has followed similar evolutionary dynamics, or whether independent origins are accompanied by unique constraints and selective pressures over macroevolutionary time. We hypothesized that geckos and anoles each have unique evolutionary tempos and modes. Using performance data from 59 species, we modified Brownian motion (BM) and Ornstein-Uhlenbeck (OU) models to account for repeated origins estimated using Bayesian ancestral state reconstructions. We discovered that adhesive performance in geckos evolved in a fashion consistent with Brownian motion with a trend, whereas anoles evolved in bounded performance space consistent with more constrained evolution (an Ornstein-Uhlenbeck model). Our results suggest that convergent phenotypes can have quite distinctive evolutionary patterns, likely as a result of idiosyncratic constraints or ecological opportunities. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

PDEMOD: Software for control/structures optimization

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr.; Zimmerman, David

1991-01-01

Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.

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.

Order reduction, identification and localization studies of dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Xianghong

In this thesis methods are developed for performing order reduction, system identification and induction of nonlinear localization in complex mechanical dynamic systems. General techniques are proposed for constructing low-order models of linear and nonlinear mechanical systems; in addition, novel mechanical designs are considered for inducing nonlinear localization phenomena for the purpose of enhancing their dynamical performance. The thesis is in three major parts. In the first part, the transient dynamics of an impulsively loaded multi-bay truss is numerically computed by employing the Direct Global Matrix (DGM) approach. The approach is applicable to large-scale flexible structures with periodicity. Karhunen-Loeve (K-L) decomposition is used to discretize the dynamics of the truss and to create the low-order models of the truss. The leading order K-L modes are recovered by an experiment, which shows the feasibility of K-L based order reduction technique. In the second part of the thesis, nonlinear localization in dynamical systems is studied through two applications. In the seismic base isolation study, it is shown that the dynamics are sensitive to the presence of nonlinear elements and that passive motion confinement can be induced under proper design. In the coupled rod system, numerical simulation of the transient dynamics shows that a nonlinear backlash spring can induce either nonlinear localization or delocalization in the form of beat phenomena. K-L decomposition and poincare maps are utilized to study the nonlinear effects. The study shows that nonlinear localization can be induced in complex structures through backlash. In the third and final part of the thesis, a new technique based on Green!s function method is proposed to identify the dynamics of practical bolted joints. By modeling the difference between the dynamics of the bolted structure and the corresponding unbolted one, one constructs a nonparametric model for the joint dynamics. Two applications are given with a bolted beam and a truss joint in order to show the applicability of the technique.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

Modeling socio-cultural processes in network-centric environments

NASA Astrophysics Data System (ADS)

Santos, Eunice E.; Santos, Eugene, Jr.; Korah, John; George, Riya; Gu, Qi; Kim, Keumjoo; Li, Deqing; Russell, Jacob; Subramanian, Suresh

2012-05-01

The major focus in the field of modeling & simulation for network centric environments has been on the physical layer while making simplifications for the human-in-the-loop. However, the human element has a big impact on the capabilities of network centric systems. Taking into account the socio-behavioral aspects of processes such as team building, group decision-making, etc. are critical to realistically modeling and analyzing system performance. Modeling socio-cultural processes is a challenge because of the complexity of the networks, dynamism in the physical and social layers, feedback loops and uncertainty in the modeling data. We propose an overarching framework to represent, model and analyze various socio-cultural processes within network centric environments. The key innovation in our methodology is to simultaneously model the dynamism in both the physical and social layers while providing functional mappings between them. We represent socio-cultural information such as friendships, professional relationships and temperament by leveraging the Culturally Infused Social Network (CISN) framework. The notion of intent is used to relate the underlying socio-cultural factors to observed behavior. We will model intent using Bayesian Knowledge Bases (BKBs), a probabilistic reasoning network, which can represent incomplete and uncertain socio-cultural information. We will leverage previous work on a network performance modeling framework called Network-Centric Operations Performance and Prediction (N-COPP) to incorporate dynamism in various aspects of the physical layer such as node mobility, transmission parameters, etc. We validate our framework by simulating a suitable scenario, incorporating relevant factors and providing analyses of the results.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan W.

2014-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan Walker

2015-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

A novel unscented predictive filter for relative position and attitude estimation of satellite formation

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Xiaoqian; Misra, Arun K.

2015-07-01

This paper presents a novel sigma-point unscented predictive filter (UPF) for relative position and attitude estimation of satellite formation taking into account the influence of J2. A coupled relative translational dynamics model is formulated to represent orbital motion of arbitrary feature points on the deputy spacecraft, and the relative attitude motion is formulated by considering a rotational dynamics for a satellite without gyros. Based on the proposed coupled dynamic model, the UPF is developed based on unscented transformation technique, extending the capability of a traditional predictive filter (PF). The algorithm flow of the UPF is described first. Then it is demonstrated that the estimation accuracy of the model error and system state for UPF is higher than that of the traditional PF. In addition, the unscented Kalman filter (UKF) is also employed in order to compare the performance of the proposed UPF with that of the UKF. Several different scenarios are simulated to validate the effectiveness of the coupled dynamics model and the performance of the proposed UPF. Through comparisons, the proposed UPF is shown to yield highly accurate estimation of relative position and attitude during satellite formation flying.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems.

PubMed

Su, Weixing; Chen, Hanning; Liu, Fang; Lin, Na; Jing, Shikai; Liang, Xiaodan; Liu, Wei

2017-03-01

There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC) for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell's pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

Synergia: an accelerator modeling tool with 3-D space charge

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

Amundson, James F.; Spentzouris, P.; /Fermilab

2004-07-01

High precision modeling of space-charge effects, together with accurate treatment of single-particle dynamics, is essential for designing future accelerators as well as optimizing the performance of existing machines. We describe Synergia, a high-fidelity parallel beam dynamics simulation package with fully three dimensional space-charge capabilities and a higher order optics implementation. We describe the computational techniques, the advanced human interface, and the parallel performance obtained using large numbers of macroparticles. We also perform code benchmarks comparing to semi-analytic results and other codes. Finally, we present initial results on particle tune spread, beam halo creation, and emittance growth in the Fermilab boostermore » accelerator.« less

Preliminary dynamic tests of a flight-type ejector

NASA Technical Reports Server (NTRS)

Drummond, Colin K.

1992-01-01

A thrust augmenting ejector was tested to provide experimental data to assist in the assessment of theoretical models to predict duct and ejector fluid-dynamic characteristics. Eleven full-scale thrust augmenting ejector tests were conducted in which a rapid increase in the ejector nozzle pressure ratio was effected through a unique facility, bypass/burst-disk subsystem. The present work examines two cases representative of the test performance window. In the first case, the primary nozzle pressure ration (NPR) increased 36 percent from one unchoked (NPR = 1.29) primary flow condition to another (NPR = 1.75) over a 0.15 second interval. The second case involves choked primary flow conditions, where a 17 percent increase in primary nozzle flowrate (from NPR = 2.35 to NPR = 2.77) occurred over approximately 0.1 seconds. Although the real-time signal measurements support qualitative remarks on ejector performance, extracting quantitative ejector dynamic response was impeded by excessive aerodynamic noise and thrust stand dynamic (resonance) characteristics. It does appear, however, that a quasi-steady performance assumption is valid for this model with primary nozzle pressure increased on the order of 50 lb(sub f)/s. Transient signal treatment of the present dataset is discussed and initial interpretations of the results are compared with theoretical predictions for a similar Short Takeoff and Vertical Landing (STOVL) ejector model.

Research on Zheng Classification Fusing Pulse Parameters in Coronary Heart Disease

PubMed Central

Guo, Rui; Wang, Yi-Qin; Xu, Jin; Yan, Hai-Xia; Yan, Jian-Jun; Li, Fu-Feng; Xu, Zhao-Xia; Xu, Wen-Jie

2013-01-01

This study was conducted to illustrate that nonlinear dynamic variables of Traditional Chinese Medicine (TCM) pulse can improve the performances of TCM Zheng classification models. Pulse recordings of 334 coronary heart disease (CHD) patients and 117 normal subjects were collected in this study. Recurrence quantification analysis (RQA) was employed to acquire nonlinear dynamic variables of pulse. TCM Zheng models in CHD were constructed, and predictions using a novel multilabel learning algorithm based on different datasets were carried out. Datasets were designed as follows: dataset1, TCM inquiry information including inspection information; dataset2, time-domain variables of pulse and dataset1; dataset3, RQA variables of pulse and dataset1; and dataset4, major principal components of RQA variables and dataset1. The performances of the different models for Zheng differentiation were compared. The model for Zheng differentiation based on RQA variables integrated with inquiry information had the best performance, whereas that based only on inquiry had the worst performance. Meanwhile, the model based on time-domain variables of pulse integrated with inquiry fell between the above two. This result showed that RQA variables of pulse can be used to construct models of TCM Zheng and improve the performance of Zheng differentiation models. PMID:23737839

On-line implementation of nonlinear parameter estimation for the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

Buckland, Julia H.; Musgrave, Jeffrey L.; Walker, Bruce K.

1992-01-01

We investigate the performance of a nonlinear estimation scheme applied to the estimation of several parameters in a performance model of the Space Shuttle Main Engine. The nonlinear estimator is based upon the extended Kalman filter which has been augmented to provide estimates of several key performance variables. The estimated parameters are directly related to the efficiency of both the low pressure and high pressure fuel turbopumps. Decreases in the parameter estimates may be interpreted as degradations in turbine and/or pump efficiencies which can be useful measures for an online health monitoring algorithm. This paper extends previous work which has focused on off-line parameter estimation by investigating the filter's on-line potential from a computational standpoint. ln addition, we examine the robustness of the algorithm to unmodeled dynamics. The filter uses a reduced-order model of the engine that includes only fuel-side dynamics. The on-line results produced during this study are comparable to off-line results generated previously. The results show that the parameter estimates are sensitive to dynamics not included in the filter model. Off-line results using an extended Kalman filter with a full order engine model to address the robustness problems of the reduced-order model are also presented.

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

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

Gong, Jian; Stewart, Mark L.; Zelenyuk, Alla

The state-of-the-art multiscale modeling of GPFs including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtration on a singlemore » channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. The microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.« less

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

DOE PAGES

Gong, Jian; Stewart, Mark L.; Zelenyuk, Alla; ...

2018-01-03

The state-of-the-art multiscale modeling of gasoline particulate filter (GPF) including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtrationmore » on a single channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. In conclusion, the microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.« less

Importance of filter’s microstructure in dynamic filtration modeling of gasoline particulate filters (GPFs): Inhomogeneous porosity and pore size distribution

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

Gong, Jian; Stewart, Mark L.; Zelenyuk, Alla

The state-of-the-art multiscale modeling of gasoline particulate filter (GPF) including channel scale, wall scale, and pore scale is described. The microstructures of two GPFs were experimentally characterized. The pore size distributions of the GPFs were determined by mercury porosimetry. The porosity was measured by X-ray computed tomography (CT) and found to be inhomogeneous across the substrate wall. The significance of pore size distribution with respect to filtration performance was analyzed. The predictions of filtration efficiency were improved by including the pore size distribution in the filtration model. A dynamic heterogeneous multiscale filtration (HMF) model was utilized to simulate particulate filtrationmore » on a single channel particulate filter with realistic particulate emissions from a spark-ignition direct-injection (SIDI) gasoline engine. The dynamic evolution of filter’s microstructure and macroscopic filtration characteristics including mass- and number-based filtration efficiencies and pressure drop were predicted and discussed. In conclusion, the microstructure of the GPF substrate including inhomogeneous porosity and pore size distribution is found to significantly influence local particulate deposition inside the substrate and macroscopic filtration performance and is recommended to be resolved in the filtration model to simulate and evaluate the filtration performance of GPFs.« less

Integration of Gravitational Torques in Cerebellar Pathways Allows for the Dynamic Inverse Computation of Vertical Pointing Movements of a Robot Arm

PubMed Central

Gentili, Rodolphe J.; Papaxanthis, Charalambos; Ebadzadeh, Mehdi; Eskiizmirliler, Selim; Ouanezar, Sofiane; Darlot, Christian

2009-01-01

Background Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). Methodology/Principal Findings This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. Conclusions/Significance This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field. PMID:19384420

Improved prescribed performance control for air-breathing hypersonic vehicles with unknown deadzone input nonlinearity.

PubMed

Wang, Yingyang; Hu, Jianbo

2018-05-19

An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

A comparison of Coulomb and pseudo-Coulomb friction implementations: Application to the table contact phase of gymnastics vaulting.

PubMed

Jackson, M I; Hiley, M J; Yeadon, M R

2011-10-13

In the table contact phase of gymnastics vaulting both dynamic and static friction act. The purpose of this study was to develop a method of simulating Coulomb friction that incorporated both dynamic and static phases and to compare the results with those obtained using a pseudo-Coulomb implementation of friction when applied to the table contact phase of gymnastics vaulting. Kinematic data were obtained from an elite level gymnast performing handspring straight somersault vaults using a Vicon optoelectronic motion capture system. An angle-driven computer model of vaulting that simulated the interaction between a seven segment gymnast and a single segment vaulting table during the table contact phase of the vault was developed. Both dynamic and static friction were incorporated within the model by switching between two implementations of the tangential frictional force. Two vaulting trials were used to determine the model parameters using a genetic algorithm to match simulations to recorded performances. A third independent trial was used to evaluate the model and close agreement was found between the simulation and the recorded performance with an overall difference of 13.5%. The two-state simulation model was found to be capable of replicating performance at take-off and also of replicating key contact phase features such as the normal and tangential motion of the hands. The results of the two-state model were compared to those using a pseudo-Coulomb friction implementation within the simulation model. The two-state model achieved similar overall results to those of the pseudo-Coulomb model but obtained solutions more rapidly. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Performance limitations of bilateral force reflection imposed by operator dynamic characteristics

NASA Technical Reports Server (NTRS)

Chapel, Jim D.

1989-01-01

A linearized, single-axis model is presented for bilateral force reflection which facilitates investigation into the effects of manipulator, operator, and task dynamics, as well as time delay and gain scaling. Structural similarities are noted between this model and impedance control. Stability results based upon this model impose requirements upon operator dynamic characteristics as functions of system time delay and environmental stiffness. An experimental characterization reveals the limited capabilities of the human operator to meet these requirements. A procedure is presented for determining the force reflection gain scaling required to provide stability and acceptable operator workload. This procedure is applied to a system with dynamics typical of a space manipulator, and the required gain scaling is presented as a function of environmental stiffness.

Identification of Dynamic Simulation Models for Variable Speed Pumped Storage Power Plants

NASA Astrophysics Data System (ADS)

Moreira, C.; Fulgêncio, N.; Silva, B.; Nicolet, C.; Béguin, A.

2017-04-01

This paper addresses the identification of reduced order models for variable speed pump-turbine plants, including the representation of the dynamic behaviour of the main components: hydraulic system, turbine governors, electromechanical equipment and power converters. A methodology for the identification of appropriated reduced order models both for turbine and pump operating modes is presented and discussed. The methodological approach consists of three main steps: 1) detailed pumped-storage power plant modelling in SIMSEN; 2) reduced order models identification and 3) specification of test conditions for performance evaluation.

MODEL CORRELATION STUDY OF A RETRACTABLE BOOM FOR A SOLAR SAIL SPACECRAFT

NASA Technical Reports Server (NTRS)

Adetona, O.; Keel, L. H.; Oakley, J. D.; Kappus, K.; Whorton, M. S.; Kim, Y. K.; Rakpczy, J. M.

2005-01-01

To realize design concepts, predict dynamic behavior and develop appropriate control strategies for high performance operation of a solar-sail spacecraft, we developed a simple analytical model that represents dynamic behavior of spacecraft with various sizes. Since motion of the vehicle is dominated by retractable booms that support the structure, our study concentrates on developing and validating a dynamic model of a long retractable boom. Extensive tests with various configurations were conducted for the 30 Meter, light-weight, retractable, lattice boom at NASA MSFC that is structurally and dynamically similar to those of a solar-sail spacecraft currently under construction. Experimental data were then compared with the corresponding response of the analytical model. Though mixed results were obtained, the analytical model emulates several key characteristics of the boom. The paper concludes with a detailed discussion of issues observed during the study.

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

Mathematical model for adaptive control system of ASEA robot at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Zia, Omar

1989-01-01

The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.

Spin glass model for dynamics of cell reprogramming

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2015-03-01

Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming.

Dynamic deformable models for 3D MRI heart segmentation

NASA Astrophysics Data System (ADS)

Zhukov, Leonid; Bao, Zhaosheng; Gusikov, Igor; Wood, John; Breen, David E.

2002-05-01

Automated or semiautomated segmentation of medical images decreases interstudy variation, observer bias, and postprocessing time as well as providing clincally-relevant quantitative data. In this paper we present a new dynamic deformable modeling approach to 3D segmentation. It utilizes recently developed dynamic remeshing techniques and curvature estimation methods to produce high-quality meshes. The approach has been implemented in an interactive environment that allows a user to specify an initial model and identify key features in the data. These features act as hard constraints that the model must not pass through as it deforms. We have employed the method to perform semi-automatic segmentation of heart structures from cine MRI data.

Influence of backup bearings and support structure dynamics on the behavior of rotors with active supports

NASA Technical Reports Server (NTRS)

Flowers, George T.

1995-01-01

This semiannual status report lists specific accomplishments made on the research of the influence of backup bearings and support structure dynamics on the behavior of rotors with active supports. Papers have been presented representing work done on the T-501 engine model; an experimental/simulation study of auxiliary bearing rotordynamics; and a description of a rotordynamical model for a magnetic bearing supported rotor system, including auxiliary bearing effects. A finite element model for a foil bearing has been developed. Additional studies of rotor/bearing/housing dynamics are currently being performed as are studies of the effects of sideloading on auxiliary bearing rotordynamics using the magnetic bearing supported rotor model.

Development of a severe local storm prediction system: A 60-day test of a mesoscale primitive equation model

NASA Technical Reports Server (NTRS)

Paine, D. A.; Zack, J. W.; Kaplan, M. L.

1979-01-01

The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.

Dynamic and fluid-structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models

NASA Astrophysics Data System (ADS)

Hsu, Ming-Chen; Kamensky, David; Xu, Fei; Kiendl, Josef; Wang, Chenglong; Wu, Michael C. H.; Mineroff, Joshua; Reali, Alessandro; Bazilevs, Yuri; Sacks, Michael S.

2015-06-01

This paper builds on a recently developed immersogeometric fluid-structure interaction (FSI) methodology for bioprosthetic heart valve (BHV) modeling and simulation. It enhances the proposed framework in the areas of geometry design and constitutive modeling. With these enhancements, BHV FSI simulations may be performed with greater levels of automation, robustness and physical realism. In addition, the paper presents a comparison between FSI analysis and standalone structural dynamics simulation driven by prescribed transvalvular pressure, the latter being a more common modeling choice for this class of problems. The FSI computation achieved better physiological realism in predicting the valve leaflet deformation than its standalone structural dynamics counterpart.

Dynamic large eddy simulation: Stability via realizability

NASA Astrophysics Data System (ADS)

Mokhtarpoor, Reza; Heinz, Stefan

2017-10-01

The concept of dynamic large eddy simulation (LES) is highly attractive: such methods can dynamically adjust to changing flow conditions, which is known to be highly beneficial. For example, this avoids the use of empirical, case dependent approximations (like damping functions). Ideally, dynamic LES should be local in physical space (without involving artificial clipping parameters), and it should be stable for a wide range of simulation time steps, Reynolds numbers, and numerical schemes. These properties are not trivial, but dynamic LES suffers from such problems over decades. We address these questions by performing dynamic LES of periodic hill flow including separation at a high Reynolds number Re = 37 000. For the case considered, the main result of our studies is that it is possible to design LES that has the desired properties. It requires physical consistency: a PDF-realizable and stress-realizable LES model, which requires the inclusion of the turbulent kinetic energy in the LES calculation. LES models that do not honor such physical consistency can become unstable. We do not find support for the previous assumption that long-term correlations of negative dynamic model parameters are responsible for instability. Instead, we concluded that instability is caused by the stable spatial organization of significant unphysical states, which are represented by wall-type gradient streaks of the standard deviation of the dynamic model parameter. The applicability of our realizability stabilization to other dynamic models (including the dynamic Smagorinsky model) is discussed.

Nonlinear modelling of high-speed catenary based on analytical expressions of cable and truss elements

NASA Astrophysics Data System (ADS)

Song, Yang; Liu, Zhigang; Wang, Hongrui; Lu, Xiaobing; Zhang, Jing

2015-10-01

Due to the intrinsic nonlinear characteristics and complex structure of the high-speed catenary system, a modelling method is proposed based on the analytical expressions of nonlinear cable and truss elements. The calculation procedure for solving the initial equilibrium state is proposed based on the Newton-Raphson iteration method. The deformed configuration of the catenary system as well as the initial length of each wire can be calculated. Its accuracy and validity of computing the initial equilibrium state are verified by comparison with the separate model method, absolute nodal coordinate formulation and other methods in the previous literatures. Then, the proposed model is combined with a lumped pantograph model and a dynamic simulation procedure is proposed. The accuracy is guaranteed by the multiple iterative calculations in each time step. The dynamic performance of the proposed model is validated by comparison with EN 50318, the results of the finite element method software and SIEMENS simulation report, respectively. At last, the influence of the catenary design parameters (such as the reserved sag and pre-tension) on the dynamic performance is preliminarily analysed by using the proposed model.

Slushy weightings for the optimal pilot model. [considering visual tracking task

NASA Technical Reports Server (NTRS)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Structure and Dynamics of End-to-End Loop Formation of the Penta-Peptide Cys-Ala-Gly-Gln-Trp in Implicit Solvents

DTIC Science & Technology

2009-01-01

implicit solvents on peptide structure and dynamics , we performed extensive molecular dynamics simulations on the penta-peptide Cys-Ala-Gly-Gln-Trp. Two...end-to-end distances and dihedral angles obtained from molecular dynamics simulations with implicit solvent models were in a good agreement with those...to maintain the temperature of the systems. Introduction Molecular dynamics (MD) simulation techniques are widely used to study structure and

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.

Investigation of dynamic noise affecting geodynamics information in a tethered subsatellite

NASA Technical Reports Server (NTRS)

Gullahorn, G. E.

1985-01-01

Work performed as part of an investigation of noise affecting instrumentation in a tethered subsatellite, was studied. The following specific topics were addressed during the reporting period: a method for stabilizing the subsatellite against the rotational effects of atmospheric perturbation was developed; a variety of analytic studies of tether dynamics aimed at elucidating dynamic noise processes were performed; a novel mechanism for coupling longitudinal and latitudinal oscillations of the tether was discovered, and random vibration analysis for modeling the tethered subsatellite under atmospheric perturbation were studied.

A dynamical systems model for nuclear power plant risk

NASA Astrophysics Data System (ADS)

Hess, Stephen Michael

The recent transition to an open access generation marketplace has forced nuclear plant operators to become much more cost conscious and focused on plant performance. Coincidentally, the regulatory perspective also is in a state of transition from a command and control framework to one that is risk-informed and performance-based. Due to these structural changes in the economics and regulatory system associated with commercial nuclear power plant operation, there is an increased need for plant management to explicitly manage nuclear safety risk. Application of probabilistic risk assessment techniques to model plant hardware has provided a significant contribution to understanding the potential initiating events and equipment failures that can lead to core damage accidents. Application of the lessons learned from these analyses has supported improved plant operation and safety over the previous decade. However, this analytical approach has not been nearly as successful in addressing the impact of plant processes and management effectiveness on the risks of plant operation. Thus, the research described in this dissertation presents a different approach to address this issue. Here we propose a dynamical model that describes the interaction of important plant processes among themselves and their overall impact on nuclear safety risk. We first provide a review of the techniques that are applied in a conventional probabilistic risk assessment of commercially operating nuclear power plants and summarize the typical results obtained. The limitations of the conventional approach and the status of research previously performed to address these limitations also are presented. Next, we present the case for the application of an alternative approach using dynamical systems theory. This includes a discussion of previous applications of dynamical models to study other important socio-economic issues. Next, we review the analytical techniques that are applicable to analysis of these models. Details of the development of the mathematical risk model are presented. This includes discussion of the processes included in the model and the identification of significant interprocess interactions. This is followed by analysis of the model that demonstrates that its dynamical evolution displays characteristics that have been observed at commercially operating plants. The model is analyzed using the previously described techniques from dynamical systems theory. From this analysis, several significant insights are obtained with respect to the effective control of nuclear safety risk. Finally, we present conclusions and recommendations for further research.

The synergistic use of models and observations: understanding the mechanisms behind observed biomass dynamics at 14 Amazonian field sites and the implications for future biomass change

NASA Astrophysics Data System (ADS)

Levine, N. M.; Galbraith, D.; Christoffersen, B. J.; Imbuzeiro, H. A.; Restrepo-Coupe, N.; Malhi, Y.; Saleska, S. R.; Costa, M. H.; Phillips, O.; Andrade, A.; Moorcroft, P. R.

2011-12-01

The Amazonian rainforests play a vital role in global water, energy and carbon cycling. The sensitivity of this system to natural and anthropogenic disturbances therefore has important implications for the global climate. Some global models have predicted large-scale forest dieback and the savannization of Amazonia over the next century [Meehl et al., 2007]. While several studies have demonstrated the sensitivity of dynamic global vegetation models to changes in temperature, precipitation, and dry season length [e.g. Galbraith et al., 2010; Good et al., 2011], the ability of these models to accurately reproduce ecosystem dynamics of present-day transitional or low biomass tropical forests has not been demonstrated. A model-data intercomparison was conducted with four state-of-the-art terrestrial ecosystem models to evaluate the ability of these models to accurately represent structure, function, and long-term biomass dynamics over a range of Amazonian ecosystems. Each modeling group conducted a series of simulations for 14 sites including mature forest, transitional forest, savannah, and agricultural/pasture sites. All models were run using standard physical parameters and the same initialization procedure. Model results were compared against forest inventory and dendrometer data in addition to flux tower measurements. While the models compared well against field observations for the mature forest sites, significant differences were observed between predicted and measured ecosystem structure and dynamics for the transitional forest and savannah sites. The length of the dry season and soil sand content were good predictors of model performance. In addition, for the big leaf models, model performance was highest for sites dominated by late successional trees and lowest for sites with predominantly early and mid-successional trees. This study provides insight into tropical forest function and sensitivity to environmental conditions that will aid in predictions of the response of the Amazonian rainforest to future anthropogenically induced changes.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

Simulation modeling of route guidance concept

DOT National Transportation Integrated Search

1997-01-01

The methodology of a simulation model developed at the University of New South Wales, Australia, for the evaluation of performance of Dynamic Route Guidance Systems (DRGS) is described. The microscopic simulation model adopts the event update simulat...

Three dimensional modeling and dynamic analysis of four-wheel-steering vehicles

NASA Astrophysics Data System (ADS)

Hu, Haiyan; Han, Qiang

2003-02-01

The paper presents a nonlinear dynamic model of 9 degrees of freedom for four-wheel-steering vehicles. Compared with those in previous studies, this model includes the pitch and roll of the vehicle body, the motion of 4 wheels in the accelerating or braking process, the nonlinear coupling of vehicle body and unsprung part, as well as the air drag and wind effect. As a result, the model can be used for the analysis of various maneuvers of the four-wheel-steering vehicles. In addition, the previous models can be considered as a special case of this model. The paper gives some case studies for the dynamic performance of a four-wheel-steering vehicle under step input and saw-tooth input of steering angle applied on the front wheels, respectively.

Closed loop performance of a brushless dc motor powered electromechanical actuator for flight control applications. [computerized simulation for Shuttle Orbiter applications

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Nehl, T. W.

1980-01-01

A comprehensive digital model for the analysis and possible optimization of the closed loop dynamic (instantaneous) performance of a power conditioner fed, brushless dc motor powered, electromechanical actuator system (EMA) is presented. This model was developed for the simulation of the dynamic performance of an actual prototype EMA built for NASA-JSC as a possible alternative to hydraulic actuators for consideration in Space Shuttle Orbiter applications. Excellent correlation was achieved between numerical model simulation and experimental test results obtained from the actual hardware. These results include: various current and voltage waveforms in the machine-power conditioner (MPC) unit, flap position as well as other control loop variables in response to step commands of change of flap position. These results with consequent conclusions are detailed in the paper.

Application of tire dynamics to aircraft landing gear design analysis

NASA Technical Reports Server (NTRS)

Black, R. J.

1983-01-01

The tire plays a key part in many analyses used for design of aircraft landing gear. Examples include structural design of wheels, landing gear shimmy, brake whirl, chatter and squeal, complex combination of chatter and shimmy on main landing gear (MLG) systems, anti-skid performance, gear walk, and rough terrain loads and performance. Tire parameters needed in the various analyses are discussed. Two tire models are discussed for shimmy analysis, the modified Moreland approach and the von Schlippe-Dietrich approach. It is shown that the Moreland model can be derived from the Von Schlippe-Dietrich model by certain approximations. The remaining analysis areas are discussed in general terms and the tire parameters needed for each are identified. Accurate tire data allows more accurate design analysis and the correct prediction of dynamic performance of aircraft landing gear.

SVDS plume impingement modeling development. Sensitivity analysis supporting level B requirements

NASA Technical Reports Server (NTRS)

Chiu, P. B.; Pearson, D. J.; Muhm, P. M.; Schoonmaker, P. B.; Radar, R. J.

1977-01-01

A series of sensitivity analyses (trade studies) performed to select features and capabilities to be implemented in the plume impingement model is described. Sensitivity analyses were performed in study areas pertaining to geometry, flowfield, impingement, and dynamical effects. Recommendations based on these analyses are summarized.

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Genetic programming for evolving due-date assignment models in job shop environments.

PubMed

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

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.

A nonlinear kinematic and dynamic modeling of Macpherson suspension systems with a magneto-rheological damper

NASA Astrophysics Data System (ADS)

Dutta, Saikat; Choi, Seung-Bok

2016-03-01

It is well known that Macpherson strut suspension systems are widely used in light and medium weight vehicles. The performance of these suspension systems can be enriched by incorporating magneto-rheological (MR) dampers and an appropriate dynamic model is required in order to find out the ride comfort and other performances properly in the sense of practical environment conditions. Therefore, in this work the kinematic and dynamic modeling of Macpherson strut suspension system with MR damper is presented and its responses are evaluated. The governing equations are formulated using the kinematic properties of the suspension system and adopting Lagrange’s equation. In the formulation of the model, both the rotation of the wheel assembly and the lateral stiffness of the tire are considered to represent the nonlinear characteristic of Macpherson type suspension system. The formulated mathematical model is then compared with equivalent conventional quarter car suspension model and the different dynamic responses such as the displacement of the sprung mass are compared to emphasize the effectiveness of the proposed model. Additionally, in this work the important kinematic properties of suspension system such as camber angle, king-pin angle and track width alteration, which cannot be obtained from conventional quarter car suspension model, are evaluated in time and frequency domains. Finally, vibration control responses of the proposed suspension system are presented in time and frequency domains which are achieved from the semi-active sky-hook controller.

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest

USGS Publications Warehouse

Wylie, Bruce K.; Rigge, Matthew B.; Brisco, Brian; Mrnaghan, Kevin; Rover, Jennifer R.; Long, Jordan

2014-01-01

A warming climate influences boreal forest productivity, dynamics, and disturbance regimes. We used ecosystem models and 250 m satellite Normalized Difference Vegetation Index (NDVI) data averaged over the growing season (GSN) to model current, and estimate future, ecosystem performance. We modeled Expected Ecosystem Performance (EEP), or anticipated productivity, in undisturbed stands over the 2000–2008 period from a variety of abiotic data sources, using a rule-based piecewise regression tree. The EEP model was applied to a future climate ensemble A1B projection to quantify expected changes to mature boreal forest performance. Ecosystem Performance Anomalies (EPA), were identified as the residuals of the EEP and GSN relationship and represent performance departures from expected performance conditions. These performance data were used to monitor successional events following fire. Results suggested that maximum EPA occurs 30–40 years following fire, and deciduous stands generally have higher EPA than coniferous stands. Mean undisturbed EEP is projected to increase 5.6% by 2040 and 8.7% by 2070, suggesting an increased deciduous component in boreal forests. Our results contribute to the understanding of boreal forest successional dynamics and its response to climate change. This information enables informed decisions to prepare for, and adapt to, climate change in the Yukon River Basin forest.

Dynamical network interactions in distributed control of robots

NASA Astrophysics Data System (ADS)

Buscarino, Arturo; Fortuna, Luigi; Frasca, Mattia; Rizzo, Alessandro

2006-03-01

In this paper the dynamical network model of the interactions within a group of mobile robots is investigated and proposed as a possible strategy for controlling the robots without central coordination. Motivated by the results of the analysis of our simple model, we show that the system performance in the presence of noise can be improved by including long-range connections between the robots. Finally, a suitable strategy based on this model to control exploration and transport is introduced.

The architecture of dynamic reservoir in the echo state network

NASA Astrophysics Data System (ADS)

Cui, Hongyan; Liu, Xiang; Li, Lixiang

2012-09-01

Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

Influence of the piezoelectric parameters on the dynamics of an active rotor

NASA Astrophysics Data System (ADS)

Gawryluk, Jarosław; Mitura, Andrzej; Teter, Andrzej

2018-01-01

The main aim of this paper is an experimental and numerical analysis of the dynamic behavior of an active rotor with three composite blades. The study focuses on developing an effective FE modeling technique of a macro fiber composite element (denoted as MFC or active element) for the dynamic tests of active structures. The active rotor under consideration consists of a hub with a drive shaft, three grips and three glass-epoxy laminate blades with embedded active elements. A simplified FE model of the macro fiber composite element exhibiting the d33 piezoelectric effect is developed using the Abaqus software package. The discussed transducer is modeled as quasi-homogeneous piezoelectric material, and voltage is applied to the opposite faces of the element. In this case, the effective (equivalent) piezoelectric constant d33* is specified. Both static and dynamic tests are performed to verify the proposed model. First, static deflections of the active blade caused by the voltage signal are determined by numerical and experimental analyses. Next, a numerical modal analysis of the active rotor is performed. The eigenmodes and corresponding eigenfrequencies are determined by the Lanczos method. The influence of the model parameters (i.e., the effective piezoelectric constant d33 *, voltage signal, angular velocity) on the dynamics of the active rotor is examined. Finally, selected numerical results are validated in experimental tests. The experimental findings demonstrate that the structural stiffening effect caused by the active element strongly depends on the value of the effective piezoelectric constant.

Performance recovery of a class of uncertain non-affine systems with unmodelled dynamics: an indirect dynamic inversion method

NASA Astrophysics Data System (ADS)

Yi, Bowen; Lin, Shuyi; Yang, Bo; Zhang, Weidong

2018-02-01

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples.

Active load control during rolling maneuvers. [performed in the Langley Transonic Dynamics Tunnel

NASA Technical Reports Server (NTRS)

Woods-Vedeler, Jessica A.; Pototzky, Anthony S.; Hoadley, Sherwood T.

1994-01-01

A rolling maneuver load alleviation (RMLA) system has been demonstrated on the active flexible wing (AFW) wind tunnel model in the Langley Transonic Dynamics Tunnel (TDT). The objective was to develop a systematic approach for designing active control laws to alleviate wing loads during rolling maneuvers. Two RMLA control laws were developed that utilized outboard control-surface pairs (leading and trailing edge) to counteract the loads and that used inboard trailing-edge control-surface pairs to maintain roll performance. Rolling maneuver load tests were performed in the TDT at several dynamic pressures that included two below and one 11 percent above open-loop flutter dynamic pressure. The RMLA system was operated simultaneously with an active flutter suppression system above open-loop flutter dynamic pressure. At all dynamic pressures for which baseline results were obtained, torsion-moment loads were reduced for both RMLA control laws. Results for bending-moment load reductions were mixed; however, design equations developed in this study provided conservative estimates of load reduction in all cases.

A dynamic regularized gradient model of the subgrid-scale stress tensor for large-eddy simulation

NASA Astrophysics Data System (ADS)

Vollant, A.; Balarac, G.; Corre, C.

2016-02-01

Large-eddy simulation (LES) solves only the large scales part of turbulent flows by using a scales separation based on a filtering operation. The solution of the filtered Navier-Stokes equations requires then to model the subgrid-scale (SGS) stress tensor to take into account the effect of scales smaller than the filter size. In this work, a new model is proposed for the SGS stress model. The model formulation is based on a regularization procedure of the gradient model to correct its unstable behavior. The model is developed based on a priori tests to improve the accuracy of the modeling for both structural and functional performances, i.e., the model ability to locally approximate the SGS unknown term and to reproduce enough global SGS dissipation, respectively. LES is then performed for a posteriori validation. This work is an extension to the SGS stress tensor of the regularization procedure proposed by Balarac et al. ["A dynamic regularized gradient model of the subgrid-scale scalar flux for large eddy simulations," Phys. Fluids 25(7), 075107 (2013)] to model the SGS scalar flux. A set of dynamic regularized gradient (DRG) models is thus made available for both the momentum and the scalar equations. The second objective of this work is to compare this new set of DRG models with direct numerical simulations (DNS), filtered DNS in the case of classic flows simulated with a pseudo-spectral solver and with the standard set of models based on the dynamic Smagorinsky model. Various flow configurations are considered: decaying homogeneous isotropic turbulence, turbulent plane jet, and turbulent channel flows. These tests demonstrate the stable behavior provided by the regularization procedure, along with substantial improvement for velocity and scalar statistics predictions.

Transport dissipative particle dynamics model for mesoscopic advection- diffusion-reaction problems

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

Zhen, Li; Yazdani, Alireza; Tartakovsky, Alexandre M.

2015-07-07

We present a transport dissipative particle dynamics (tDPD) model for simulating mesoscopic problems involving advection-diffusion-reaction (ADR) processes, along with a methodology for implementation of the correct Dirichlet and Neumann boundary conditions in tDPD simulations. tDPD is an extension of the classic DPD framework with extra variables for describing the evolution of concentration fields. The transport of concentration is modeled by a Fickian flux and a random flux between particles, and an analytical formula is proposed to relate the mesoscopic concentration friction to the effective diffusion coefficient. To validate the present tDPD model and the boundary conditions, we perform three tDPDmore » simulations of one-dimensional diffusion with different boundary conditions, and the results show excellent agreement with the theoretical solutions. We also performed two-dimensional simulations of ADR systems and the tDPD simulations agree well with the results obtained by the spectral element method. Finally, we present an application of the tDPD model to the dynamic process of blood coagulation involving 25 reacting species in order to demonstrate the potential of tDPD in simulating biological dynamics at the mesoscale. We find that the tDPD solution of this comprehensive 25-species coagulation model is only twice as computationally expensive as the DPD simulation of the hydrodynamics only, which is a significant advantage over available continuum solvers.« less

Aeroelastic Analyses of the SemiSpan SuperSonic Transport (S4T) Wind Tunnel Model at Mach 0.95

NASA Technical Reports Server (NTRS)

Hur, Jiyoung

2014-01-01

Detailed aeroelastic analyses of the SemiSpan SuperSonic Transport (S4T) wind tunnel model at Mach 0.95 with a 1.75deg fixed angle of attack are presented. First, a numerical procedure using the Computational Fluids Laboratory 3-Dimensional (CFL3D) Version 6.4 flow solver is investigated. The mesh update method for structured multi-block grids was successfully applied to the Navier-Stokes simulations. Second, the steady aerodynamic analyses with a rigid structure of the S4T wind tunnel model are reviewed in transonic flow. Third, the static analyses were performed for both the Euler and Navier-Stokes equations. Both the Euler and Navier-Stokes equations predicted a significant increase of lift forces, compared to the results from the rigid structure of the S4T wind-tunnel model, over various dynamic pressures. Finally, dynamic aeroelastic analyses were performed to investigate the flutter condition of the S4T wind tunnel model at the transonic Mach number. The condition of flutter was observed at a dynamic pressure of approximately 75.0-psf for the Navier-Stokes simulations. However, it was observed that the flutter condition occurred a dynamic pressure of approximately 47.27-psf for the Euler simulations. Also, the computational efficiency of the aeroelastic analyses for the S4T wind tunnel model has been assessed.

Rapid performance modeling and parameter regression of geodynamic models

NASA Astrophysics Data System (ADS)

Brown, J.; Duplyakin, D.

2016-12-01

Geodynamic models run in a parallel environment have many parameters with complicated effects on performance and scientifically-relevant functionals. Manually choosing an efficient machine configuration and mapping out the parameter space requires a great deal of expert knowledge and time-consuming experiments. We propose an active learning technique based on Gaussion Process Regression to automatically select experiments to map out the performance landscape with respect to scientific and machine parameters. The resulting performance model is then used to select optimal experiments for improving the accuracy of a reduced order model per unit of computational cost. We present the framework and evaluate its quality and capability using popular lithospheric dynamics models.

Nonlinear dynamics of team performance and adaptability in emergency response.

PubMed

Guastello, Stephen J

2010-04-01

The impact of team size and performance feedback on adaptation levels and performance of emergency response (ER) teams was examined to introduce a metric for quantifying adaptation levels based on nonlinear dynamical systems (NDS) theory. NDS principles appear in reports surrounding Hurricane Katrina, earthquakes, floods, a disease epidemic, and the Southeast Asian tsunami. They are also intrinsic to coordination within teams, adaptation levels, and performance in dynamic decision processes. Performance was measured in a dynamic decision task in which ER teams of different sizes worked against an attacker who was trying to destroy a city (total N = 225 undergraduates). The complexity of teams' and attackers' adaptation strategies and the role of the opponents' performance were assessed by nonlinear regression analysis. An optimal group size for team performance was identified. Teams were more readily influenced by the attackers' performance than vice versa. The adaptive capabilities of attackers and teams were impaired by their opponents in some conditions. ER teams should be large enough to contribute a critical mass of ideas but not so large that coordination would be compromised. ER teams used self-organized strategies that could have been more adaptive, whereas attackers used chaotic strategies. The model and results are applicable to ER processes or training maneuvers involving dynamic decisions but could be limited to nonhierarchical groups.

Flight Dynamics of Flexible Aircraft with Aeroelastic and Inertial Force Interactions

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Tuzcu, Ilhan

2009-01-01

This paper presents an integrated flight dynamic modeling method for flexible aircraft that captures coupled physics effects due to inertial forces, aeroelasticity, and propulsive forces that are normally present in flight. The present approach formulates the coupled flight dynamics using a structural dynamic modeling method that describes the elasticity of a flexible, twisted, swept wing using an equivalent beam-rod model. The structural dynamic model allows for three types of wing elastic motion: flapwise bending, chordwise bending, and torsion. Inertial force coupling with the wing elasticity is formulated to account for aircraft acceleration. The structural deflections create an effective aeroelastic angle of attack that affects the rigid-body motion of flexible aircraft. The aeroelastic effect contributes to aerodynamic damping forces that can influence aerodynamic stability. For wing-mounted engines, wing flexibility can cause the propulsive forces and moments to couple with the wing elastic motion. The integrated flight dynamics for a flexible aircraft are formulated by including generalized coordinate variables associated with the aeroelastic-propulsive forces and moments in the standard state-space form for six degree-of-freedom flight dynamics. A computational structural model for a generic transport aircraft has been created. The eigenvalue analysis is performed to compute aeroelastic frequencies and aerodynamic damping. The results will be used to construct an integrated flight dynamic model of a flexible generic transport aircraft.

Comparing models of Red Knot population dynamics

USGS Publications Warehouse

McGowan, Conor P.

2015-01-01

Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

Three-Dimensional Coupled Dynamics of The Two-Fluid Model in Superfluid 4He: Deformed Velocity Profile of Normal Fluid in Thermal Counterflow

NASA Astrophysics Data System (ADS)

Yui, Satoshi; Tsubota, Makoto; Kobayashi, Hiromichi

2018-04-01

The coupled dynamics of the two-fluid model of superfluid 4He is numerically studied for quantum turbulence of the thermal counterflow in a square channel. We combine the vortex filament model of the superfluid and the Navier-Stokes equations of normal fluid. Simulations of the coupled dynamics show that the velocity profile of the normal fluid is deformed significantly by superfluid turbulence as the vortices become dense. This result is consistent with recently performed visualization experiments. We introduce a dimensionless parameter that characterizes the deformation of the velocity profile.

A modeling technique for STOVL ejector and volume dynamics

NASA Technical Reports Server (NTRS)

Drummond, C. K.; Barankiewicz, W. S.

1990-01-01

New models for thrust augmenting ejector performance prediction and feeder duct dynamic analysis are presented and applied to a proposed Short Take Off and Vertical Landing (STOVL) aircraft configuration. Central to the analysis is the nontraditional treatment of the time-dependent volume integrals in the otherwise conventional control-volume approach. In the case of the thrust augmenting ejector, the analysis required a new relationship for transfer of kinetic energy from the primary flow to the secondary flow. Extraction of the required empirical corrections from current steady-state experimental data is discussed; a possible approach for modeling insight through Computational Fluid Dynamics (CFD) is presented.

Designing for Damage: Robust Flight Control Design using Sliding Mode Techniques

NASA Technical Reports Server (NTRS)

Vetter, T. K.; Wells, S. R.; Hess, Ronald A.; Bacon, Barton (Technical Monitor); Davidson, John (Technical Monitor)

2002-01-01

A brief review of sliding model control is undertaken, with particular emphasis upon the effects of neglected parasitic dynamics. Sliding model control design is interpreted in the frequency domain. The inclusion of asymptotic observers and control 'hedging' is shown to reduce the effects of neglected parasitic dynamics. An investigation into the application of observer-based sliding mode control to the robust longitudinal control of a highly unstable is described. The sliding mode controller is shown to exhibit stability and performance robustness superior to that of a classical loop-shaped design when significant changes in vehicle and actuator dynamics are employed to model airframe damage.

The internal processes and behavioral dynamics of hospital boards: an exploration of differences between high- and low-performing hospitals.

PubMed

Kane, Nancy M; Clark, Jonathan R; Rivenson, Howard L

2009-01-01

Nonprofit hospital boards are under increasing pressure to improve financial, clinical, and charitable and community benefit performance. Most research on board effectiveness focuses on variables measuring board structure and attributes associated with competing ideal models of board roles. However, the results do not provide clear evidence that one role is superior to another and suggest that in practice boards pursue hybrid roles. Board dynamics and processes have received less attention from researchers, but emerging theoretical frameworks highlight them as key to effective corporate governance. We explored differences in board processes and behavioral dynamics between financially high- and low-performing hospitals, with the goal of developing a better understanding of the best board practices in nonprofit hospitals. A comparative case study approach allowed for in-depth, qualitative assessments of how the internal workings of boards differ between low- and high-performing facilities. Boards of hospitals with strong financial performance exhibited behavioral dynamics and internal processes that differed in important ways from those of hospitals with poor financial performance. Boards need to actively attend to key processes and foster positive group dynamics in decision making to be more effective in governing hospitals.

Fluid Dynamics Lagrangian Simulation Model

NASA Astrophysics Data System (ADS)

Hyman, Ellis

1994-02-01

The work performed by Science Applications International Corporation (SAIC) on this contract, Fluid Dynamics Lagrangian Simulation Model, Contract Number N00014-89-C-2106, SAIC Project Number 01-0157-03-0768, focused on a number of research topics in fluid dynamics. The work was in support of the programs of NRL's Laboratory for Computational Physics and Fluid Dynamics and covered the period from 10 September 1989 to 9 December 1993. In the following sections, we describe each of the efforts and the results obtained. Much of the research work has resulted in journal publications. These are included in Appendices of this report for which the reader is referred for complete details.

Evaluation of Preduster in Cement Industry Based on Computational Fluid Dynamic

NASA Astrophysics Data System (ADS)

Septiani, E. L.; Widiyastuti, W.; Djafaar, A.; Ghozali, I.; Pribadi, H. M.

2017-10-01

Ash-laden hot air from clinker in cement industry is being used to reduce water contain in coal, however it may contain large amount of ash even though it was treated by a preduster. This study investigated preduster performance as a cyclone separator in the cement industry by Computational Fluid Dynamic method. In general, the best performance of cyclone is it have relatively high efficiency with the low pressure drop. The most accurate and simple turbulence model, Reynold Average Navier Stokes (RANS), standard k-ε, and combination with Lagrangian model as particles tracking model were used to solve the problem. The measurement in simulation result are flow pattern in the cyclone, pressure outlet and collection efficiency of preduster. The applied model well predicted by comparing with the most accurate empirical model and pressure outlet in experimental measurement.

Performance Monitoring of Diabetic Patient Systems

DTIC Science & Technology

2001-10-25

a process delay that is due to the dynamics of the glucose sensor. A. Bergman Model The Bergman and AIDA models both utilize a \\minimal model...approxima- tion of the process must be made to achieve reasonable performance. A rst order approximation, ~g(s), of both the Bergman and AIDA models is...Within the IMC framework, both the Bergman and AIDA models can be controlled within acceptable toler- ances. The simulated faults are stochastic

Estimating Power System Dynamic States Using Extended Kalman Filter

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

Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw

2014-10-31

Abstract—The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated “dynamic state estimation” includes true system dynamics reflected in differential equations, not like previously proposed “dynamic state estimation” which only considers the time-variant snapshots based on steady state modeling. This newmore » dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.« less

Multi-Body Analysis of the 1/5 Scale Wind Tunnel Model of the V-22 Tiltrotor

NASA Technical Reports Server (NTRS)

Ghiringhelli, G. L.; Masarati, P.; Mantegazza, P.; Nixon, M. W.

1999-01-01

The paper presents a multi-body analysis of the 1/5 scale wind tunnel model of the V-22 tiltrotor, the Wing and Rotor Aeroelastic Testing System (WRATS), currently tested at NASA Langley Research Center. An original multi-body formulation has been developed at the Dipartimento di Ingegneria Aerospaziale of the Politecnico di Milano, Italy. It is based on the direct writing of the equilibrium equations of independent rigid bodies, connected by kinematic constraints that result in the addition of algebraic constraint equations, and by dynamic constraints, that directly contribute to the equilibrium equations. The formulation has been extended to the simultaneous solution of interdisciplinary problems by modeling electric and hydraulic networks, for aeroservoelastic problems. The code has been tailored to the modeling of rotorcrafts while preserving a complete generality. A family of aerodynamic elements has been introduced to model high aspect aerodynamic surfaces, based on the strip theory, with quasi-steady aerodynamic coefficients, compressibility, post-stall interpolation of experimental data, dynamic stall modeling, and radial flow drag. Different models for the induced velocity of the rotor can be used, from uniform velocity to dynamic in flow. A complete dynamic and aeroelastic analysis of the model of the V-22 tiltrotor has been performed, to assess the validity of the formulation and to exploit the unique features of multi-body analysis with respect to conventional comprehensive rotorcraft codes; These are the ability to model the exact kinematics of mechanical systems, and the possibility to simulate unusual maneuvers and unusual flight conditions, that are particular to the tiltrotor, e.g. the conversion maneuver. A complete modal validation of the analytical model has been performed, to assess the ability to reproduce the correct dynamics of the system with a relatively coarse beam model of the semispan wing, pylon and rotor. Particular care has been used to model the kinematics of the gimbal joint, that characterizes the rotor hub, and of the control system, consisting in the entire swashplate mechanism. The kinematics of the fixed and the rotating plates have been modeled, with variable length control links used to input the controls, the rotating flexible links, the pitch horns and the pitch bearings. The investigations took advantage of concurring wind tunnel test runs, that were performed in August 1998, and allowed the acquisition of data specific to the multi-body analysis.

On the Performance of Alternate Conceptual Ecohydrological Models for Streamflow Prediction

NASA Astrophysics Data System (ADS)

Naseem, Bushra; Ajami, Hoori; Cordery, Ian; Sharma, Ashish

2016-04-01

A merging of a lumped conceptual hydrological model with two conceptual dynamic vegetation models is presented to assess the performance of these models for simultaneous simulations of streamflow and leaf area index (LAI). Two conceptual dynamic vegetation models with differing representation of ecological processes are merged with a lumped conceptual hydrological model (HYMOD) to predict catchment scale streamflow and LAI. The merged RR-LAI-I model computes relative leaf biomass based on transpiration rates while the RR-LAI-II model computes above ground green and dead biomass based on net primary productivity and water use efficiency in response to soil moisture dynamics. To assess the performance of these models, daily discharge and 8-day MODIS LAI product for 27 catchments of 90 - 1600km2 in size located in the Murray - Darling Basin in Australia are used. Our results illustrate that when single-objective optimisation was focussed on maximizing the objective function for streamflow or LAI, the other un-calibrated predicted outcome (LAI if streamflow is the focus) was consistently compromised. Thus, single-objective optimization cannot take into account the essence of all processes in the conceptual ecohydrological models. However, multi-objective optimisation showed great strength for streamflow and LAI predictions. Both response outputs were better simulated by RR-LAI-II than RR-LAI-I due to better representation of physical processes such as net primary productivity (NPP) in RR-LAI-II. Our results highlight that simultaneous calibration of streamflow and LAI using a multi-objective algorithm proves to be an attractive tool for improved streamflow predictions.

Attitude control with realization of linear error dynamics

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

1993-01-01

An attitude control law is derived to realize linear unforced error dynamics with the attitude error defined in terms of rotation group algebra (rather than vector algebra). Euler parameters are used in the rotational dynamics model because they are globally nonsingular, but only the minimal three Euler parameters are used in the error dynamics model because they have no nonlinear mathematical constraints to prevent the realization of linear error dynamics. The control law is singular only when the attitude error angle is exactly pi rad about any eigenaxis, and a simple intuitive modification at the singularity allows the control law to be used globally. The forced error dynamics are nonlinear but stable. Numerical simulation tests show that the control law performs robustly for both initial attitude acquisition and attitude control.

Finite element modeling of ROPS in static testing and rear overturns.

PubMed

Harris, J R; Mucino, V H; Etherton, J R; Snyder, K A; Means, K H

2000-08-01

Even with the technological advances of the last several decades, agricultural production remains one of the most hazardous occupations in the United States. Death due to tractor rollover is a prime contributor to this hazard. Standards for rollover protective structures (ROPS) performance and certification have been developed by groups such as the Society of Automotive Engineers (SAE) and the American Society of Agricultural Engineers (ASAE) to combat these problems. The current ROPS certification standard, SAE J2194, requires either a dynamic or static testing sequence or both. Although some ROPS manufacturers perform both the dynamic and static phases of SAE J2194 testing, it is possible for a ROPS to be certified for field operation using static testing alone. This research compared ROPS deformation response from a simulated SAE J2194 static loading sequence to ROPS deformation response as a result of a simulated rearward tractor rollover. Finite element analysis techniques for plastic deformation were used to simulate both the static and dynamic rear rollover scenarios. Stress results from the rear rollover model were compared to results from simulated static testing per SAE J2194. Maximum stress values from simulated rear rollovers exceeded maximum stress values recorded during simulated static testing for half of the elements comprising the uprights. In the worst case, the static model underpredicts dynamic model results by approximately 7%. In the best case, the static model overpredicts dynamic model results by approximately 32%. These results suggest the need for additional experimental work to characterize ROPS stress levels during staged overturns and during testing according to the SAE standard.

Superelement model based parallel algorithm for vehicle dynamics

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

Agrawal, O.P.; Danhof, K.J.; Kumar, R.

1994-05-01

This paper presents a superelement model based parallel algorithm for a planar vehicle dynamics. The vehicle model is made up of a chassis and two suspension systems each of which consists of an axle-wheel assembly and two trailing arms. In this model, the chassis is treated as a Cartesian element and each suspension system is treated as a superelement. The parameters associated with the superelements are computed using an inverse dynamics technique. Suspension shock absorbers and the tires are modeled by nonlinear springs and dampers. The Euler-Lagrange approach is used to develop the system equations of motion. This leads tomore » a system of differential and algebraic equations in which the constraints internal to superelements appear only explicitly. The above formulation is implemented on a multiprocessor machine. The numerical flow chart is divided into modules and the computation of several modules is performed in parallel to gain computational efficiency. In this implementation, the master (parent processor) creates a pool of slaves (child processors) at the beginning of the program. The slaves remain in the pool until they are needed to perform certain tasks. Upon completion of a particular task, a slave returns to the pool. This improves the overall response time of the algorithm. The formulation presented is general which makes it attractive for a general purpose code development. Speedups obtained in the different modules of the dynamic analysis computation are also presented. Results show that the superelement model based parallel algorithm can significantly reduce the vehicle dynamics simulation time. 52 refs.« less

Modeling radiation belt electron dynamics during GEM challenge intervals with the DREAM3D diffusion model

NASA Astrophysics Data System (ADS)

Tu, Weichao; Cunningham, G. S.; Chen, Y.; Henderson, M. G.; Camporeale, E.; Reeves, G. D.

2013-10-01

a response to the Geospace Environment Modeling (GEM) "Global Radiation Belt Modeling Challenge," a 3D diffusion model is used to simulate the radiation belt electron dynamics during two intervals of the Combined Release and Radiation Effects Satellite (CRRES) mission, 15 August to 15 October 1990 and 1 February to 31 July 1991. The 3D diffusion model, developed as part of the Dynamic Radiation Environment Assimilation Model (DREAM) project, includes radial, pitch angle, and momentum diffusion and mixed pitch angle-momentum diffusion, which are driven by dynamic wave databases from the statistical CRRES wave data, including plasmaspheric hiss, lower-band, and upper-band chorus. By comparing the DREAM3D model outputs to the CRRES electron phase space density (PSD) data, we find that, with a data-driven boundary condition at Lmax = 5.5, the electron enhancements can generally be explained by radial diffusion, though additional local heating from chorus waves is required. Because the PSD reductions are included in the boundary condition at Lmax = 5.5, our model captures the fast electron dropouts over a large L range, producing better model performance compared to previous published results. Plasmaspheric hiss produces electron losses inside the plasmasphere, but the model still sometimes overestimates the PSD there. Test simulations using reduced radial diffusion coefficients or increased pitch angle diffusion coefficients inside the plasmasphere suggest that better wave models and more realistic radial diffusion coefficients, both inside and outside the plasmasphere, are needed to improve the model performance. Statistically, the results show that, with the data-driven outer boundary condition, including radial diffusion and plasmaspheric hiss is sufficient to model the electrons during geomagnetically quiet times, but to best capture the radiation belt variations during active times, pitch angle and momentum diffusion from chorus waves are required.

An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows.

PubMed

Brun-Lafleur, L; Cutullic, E; Faverdin, P; Delaby, L; Disenhaus, C

2013-08-01

To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rates.

Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

PubMed

Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

2016-08-01

Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

Component model reduction via the projection and assembly method

NASA Technical Reports Server (NTRS)

Bernard, Douglas E.

1989-01-01

The problem of acquiring a simple but sufficiently accurate model of a dynamic system is made more difficult when the dynamic system of interest is a multibody system comprised of several components. A low order system model may be created by reducing the order of the component models and making use of various available multibody dynamics programs to assemble them into a system model. The difficulty is in choosing the reduced order component models to meet system level requirements. The projection and assembly method, proposed originally by Eke, solves this difficulty by forming the full order system model, performing model reduction at the the system level using system level requirements, and then projecting the desired modes onto the components for component level model reduction. The projection and assembly method is analyzed to show the conditions under which the desired modes are captured exactly; to the numerical precision of the algorithm.

Immediate effects of different types of stretching exercises on badminton jump smash.

PubMed

Jang, Hwi S; Kim, Daeho; Park, Jihong

2018-01-01

Since different types of stretching exercises may alter athletic performance, we compared the effects of three types of stretching exercises on badminton jump smash. Sixteen male collegiate badminton players performed one of three different stretching exercises in a counterbalanced order on different days. Static stretching had seven typical stretches, while dynamic stretching involved nine dynamic movements, and resistance dynamic stretching was performed with weighted vests and dumbbells. Before and after each stretching exercise, subjects performed 20 trials of jump smashes. Dependent measurements were the jump heights during jump smashes, velocities of jump-smashed shuttlecocks, and drop point of jump-smashed shuttlecocks. To test the effects of each stretching exercise, we performed mixed model ANOVAs and calculated between-time effect sizes (ES). Each stretching exercise improved the jump heights during jump smashes (type main effect: F(2,75)=1.19, P=0.31; static stretching: 22.1%, P<0.01, ES=0.98; dynamic stretching: 30.1%, P<0.01, ES=1.49; resistance dynamic stretching: 17.7%, P=0.03, ES=0.98) and velocities of jump-smashed shuttlecocks (type main effect: F(2,75)=2.18, P=0.12; static stretching: 5.7%, P=0.61, ES=0.39; dynamic stretching: 3.4%, P=0.94, ES=0.28; resistance dynamic stretching: 6%, P=0.50, ES=0.66). However, there were no differences among the stretching exercises for any measurement. The drop point of jump-smashed shuttlecocks did not change (interaction: F(2,75)=0.88, P=0.42). All stretching exercises improved badminton jump smash performance, but we could not determine the best protocol. Since badminton requires high-speed movement and explosive force, we suggest performing dynamic stretching or resistance dynamic stretching.

Exploring the dynamics of balance data — movement variability in terms of drift and diffusion

NASA Astrophysics Data System (ADS)

Gottschall, Julia; Peinke, Joachim; Lippens, Volker; Nagel, Volker

2009-02-01

We introduce a method to analyze postural control on a balance board by reconstructing the underlying dynamics in terms of a Langevin model. Drift and diffusion coefficients are directly estimated from the data and fitted by a suitable parametrization. The governing parameters are utilized to evaluate balance performance and the impact of supra-postural tasks on it. We show that the proposed method of analysis gives not only self-consistent results but also provides a plausible model for the reconstruction of balance dynamics.

Event-chain algorithm for the Heisenberg model: Evidence for z≃1 dynamic scaling.

PubMed

Nishikawa, Yoshihiko; Michel, Manon; Krauth, Werner; Hukushima, Koji

2015-12-01

We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.

Inhibition of Metalloprotease Botulinum Serotype A from a Pseudo-Peptide Binding Mode to a Small Molecule that is Active in Primary Neurons

DTIC Science & Technology

2007-02-16

a modeled binding mode for inhibitor 2-mercapto-3-phenylpropionyl-RATKML (Ki 330 nM) was generated, and required the use of a molecular dynamic ...2-mercapto-3-phenylpropionyl-RATKML (K(i) = 330 nM) was generated, and required the use of a molecular dynamic conformer of the enzyme displaying the...SiliconGraphicsOctane 2. Insight II (Accelrys, San Diego, CA) was used to build and inspect models. Energy refinement and molecular dynamics were performed using the

Dynamics modelling and Hybrid Suppression Control of space robots performing cooperative object manipulation

NASA Astrophysics Data System (ADS)

Zarafshan, P.; Moosavian, S. Ali A.

2013-10-01

Dynamics modelling and control of multi-body space robotic systems composed of rigid and flexible elements is elaborated here. Control of such systems is highly complicated due to severe under-actuated condition caused by flexible elements, and an inherent uneven nonlinear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, also to develop simulation studies in support of design improvement, and finally for practical implementations. In this paper, the Rigid-Flexible Interactive dynamics Modelling (RFIM) approach is introduced as a combination of Lagrange and Newton-Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. To reveal such merits of this new approach, a Hybrid Suppression Control (HSC) for a cooperative object manipulation task will be proposed, and applied to usual space systems. A Wheeled Mobile Robotic (WMR) system with flexible appendages as a typical space rover is considered which contains a rigid main body equipped with two manipulating arms and two flexible solar panels, and next a Space Free Flying Robotic system (SFFR) with flexible members is studied. Modelling verification of these complicated systems is vigorously performed using ANSYS and ADAMS programs, while the limited computations of RFIM approach provides an efficient tool for the proposed controller design. Furthermore, it will be shown that the vibrations of the flexible solar panels results in disturbing forces on the base which may produce undesirable errors and perturb the object manipulation task. So, it is shown that these effects can be significantly eliminated by the proposed Hybrid Suppression Control algorithm.

Modeling and analysis of wet friction clutch engagement dynamics

NASA Astrophysics Data System (ADS)

Iqbal, Shoaib; Al-Bender, Farid; Ompusunggu, Agusmian P.; Pluymers, Bert; Desmet, Wim

2015-08-01

In recent years, there has been a significant increase in the usage of wet-friction clutches. Presently researchers across the globe are involved in improving the performance and lifetime of clutches through testing and simulation. To understand the clutch vibrational and dynamical behavior, an SAE#2 test setup mathematical model based on extended reset-integrator friction model is developed in this paper. In order to take into account the different phases of fluid lubrication during engagement cycle, the model includes the experimentally determined Stribeck function. In addition the model considers the viscous effect and the delay in the actuation pressure signal. The model is validated with the experiments performed on the SAE#2 test setup in both time and frequency domains. By analyzing the set of experimental results, we confirmed that the amplitude of shudder vibration is independent of the amplitude of applied contact pressure fluctuation.

Dynamic genome-scale metabolic modeling of the yeast Pichia pastoris.

PubMed

Saitua, Francisco; Torres, Paulina; Pérez-Correa, José Ricardo; Agosin, Eduardo

2017-02-21

Pichia pastoris shows physiological advantages in producing recombinant proteins, compared to other commonly used cell factories. This yeast is mostly grown in dynamic cultivation systems, where the cell's environment is continuously changing and many variables influence process productivity. In this context, a model capable of explaining and predicting cell behavior for the rational design of bioprocesses is highly desirable. Currently, there are five genome-scale metabolic reconstructions of P. pastoris which have been used to predict extracellular cell behavior in stationary conditions. In this work, we assembled a dynamic genome-scale metabolic model for glucose-limited, aerobic cultivations of Pichia pastoris. Starting from an initial model structure for batch and fed-batch cultures, we performed pre/post regression diagnostics to ensure that model parameters were identifiable, significant and sensitive. Once identified, the non-relevant ones were iteratively fixed until a priori robust modeling structures were found for each type of cultivation. Next, the robustness of these reduced structures was confirmed by calibrating the model with new datasets, where no sensitivity, identifiability or significance problems appeared in their parameters. Afterwards, the model was validated for the prediction of batch and fed-batch dynamics in the studied conditions. Lastly, the model was employed as a case study to analyze the metabolic flux distribution of a fed-batch culture and to unravel genetic and process engineering strategies to improve the production of recombinant Human Serum Albumin (HSA). Simulation of single knock-outs indicated that deviation of carbon towards cysteine and tryptophan formation improves HSA production. The deletion of methylene tetrahydrofolate dehydrogenase could increase the HSA volumetric productivity by 630%. Moreover, given specific bioprocess limitations and strain characteristics, the model suggests that implementation of a decreasing specific growth rate during the feed phase of a fed-batch culture results in a 25% increase of the volumetric productivity of the protein. In this work, we formulated a dynamic genome scale metabolic model of Pichia pastoris that yields realistic metabolic flux distributions throughout dynamic cultivations. The model can be calibrated with experimental data to rationally propose genetic and process engineering strategies to improve the performance of a P. pastoris strain of interest.

Modelling hydrologic responses in a small forested catchment (Panola Mountain, Georgia, USA): A comparison of the original and a new dynamic TOPMODEL

USGS Publications Warehouse

Peters, N.E.; Freer, J.; Beven, K.

2003-01-01

Preliminary modelling results for a new version of the rainfall-runoff model TOPMODEL, dynamic TOPMODEL, are compared with those of the original TOPMODEL formulation for predicting streamflow at the Panola Mountain Research Watershed, Georgia. Dynamic TOPMODEL uses a kinematic wave routing of subsurface flow, which allows for dynamically variable upslope contributing areas, while retaining the concept of hydrological similarity to increase computational efficiency. Model performance in predicting discharge was assessed for the original TOPMODEL and for one landscape unit (LU) and three LU versions of the dynamic TOPMODEL (a bare rock area, hillslope with regolith <1 m, and a riparian zone with regolith ???5 m). All simulations used a 30 min time step for each of three water years. Each 1-LU model underpredicted the peak streamflow, and generally overpredicted recession streamflow during wet periods and underpredicted during dry periods. The difference between predicted recession streamflow generally was less for the dynamic TOPMODEL and smallest for the 3-LU model. Bayesian combination of results for different water years within the GLUE methodology left no behavioural original or 1-LU dynamic models and only 168 (of 96 000 sample parameter sets) for the 3-LU model. The efficiency for the streamflow prediction of the best 3-LU model was 0.83 for an individual year, but the results suggest that further improvements could be made. ?? 2003 John Wiley & Sons, Ltd.

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

PubMed

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

A self-cognizant dynamic system approach for prognostics and health management

NASA Astrophysics Data System (ADS)

Bai, Guangxing; Wang, Pingfeng; Hu, Chao

2015-03-01

Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

Analysis and test evaluation of the dynamic response and stability of three advanced turboprop models

NASA Technical Reports Server (NTRS)

Bansal, P. N.; Arseneaux, P. J.; Smith, A. F.; Turnberg, J. E.; Brooks, B. M.

1985-01-01

Results of dynamic response and stability wind tunnel tests of three 62.2 cm (24.5 in) diameter models of the Prop-Fan, advanced turboprop, are presented. Measurements of dynamic response were made with the rotors mounted on an isolated nacelle, with varying tilt for nonuniform inflow. One model was also tested using a semi-span wing and fuselage configuration for response to realistic aircraft inflow. Stability tests were performed using tunnel turbulence or a nitrogen jet for excitation. Measurements are compared with predictions made using beam analysis methods for the model with straight blades, and finite element analysis methods for the models with swept blades. Correlations between measured and predicted rotating blade natural frequencies for all the models are very good. The IP dynamic response of the straight blade model is reasonably well predicted. The IP response of the swept blades is underpredicted and the wing induced response of the straight blade is overpredicted. Two models did not flutter, as predicted. One swept blade model encountered an instability at a higher RPM than predicted, showing predictions to be conservative.

A meta-model for computer executable dynamic clinical safety checklists.

PubMed

Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

2017-12-12

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

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.

Time scale of dynamic heterogeneity in model ionic liquids and its relation to static length scale and charge distribution.

PubMed

Park, Sang-Won; Kim, Soree; Jung, YounJoon

2015-11-21

We study how dynamic heterogeneity in ionic liquids is affected by the length scale of structural relaxation and the ionic charge distribution by the molecular dynamics simulations performed on two differently charged models of ionic liquid and their uncharged counterpart. In one model of ionic liquid, the charge distribution in the cation is asymmetric, and in the other it is symmetric, while their neutral counterpart has no charge with the ions. It is found that all the models display heterogeneous dynamics, exhibiting subdiffusive dynamics and a nonexponential decay of structural relaxation. We investigate the lifetime of dynamic heterogeneity, τ(dh), in these systems by calculating the three-time correlation functions to find that τ(dh) has in general a power-law behavior with respect to the structural relaxation time, τ(α), i.e., τ(dh) ∝ τ(α)(ζ(dh)). Although the dynamics of the asymmetric-charge model is seemingly more heterogeneous than that of the symmetric-charge model, the exponent is found to be similar, ζ(dh) ≈ 1.2, for all the models studied in this work. The same scaling relation is found regardless of interactions, i.e., with or without Coulomb interaction, and it holds even when the length scale of structural relaxation is long enough to become the Fickian diffusion. This fact indicates that τ(dh) is a distinctive time scale from τ(α), and the dynamic heterogeneity is mainly affected by the short-range interaction and the molecular structure.

Adaptive control based on an on-line parameter estimation of an upper limb exoskeleton.

PubMed

Riani, Akram; Madani, Tarek; Hadri, Abdelhafid El; Benallegue, Abdelaziz

2017-07-01

This paper presents an adaptive control strategy for an upper-limb exoskeleton based on an on-line dynamic parameter estimator. The objective is to improve the control performance of this system that plays a critical role in assisting patients for shoulder, elbow and wrist joint movements. In general, the dynamic parameters of the human limb are unknown and differ from a person to another, which degrade the performances of the exoskeleton-human control system. For this reason, the proposed control scheme contains a supplementary loop based on a new efficient on-line estimator of the dynamic parameters. Indeed, the latter is acting upon the parameter adaptation of the controller to ensure the performances of the system in the presence of parameter uncertainties and perturbations. The exoskeleton used in this work is presented and a physical model of the exoskeleton interacting with a 7 Degree of Freedom (DoF) upper limb model is generated using the SimMechanics library of MatLab/Simulink. To illustrate the effectiveness of the proposed approach, an example of passive rehabilitation movements is performed using multi-body dynamic simulation. The aims is to maneuver the exoskeleton that drive the upper limb to track desired trajectories in the case of the passive arm movements.

Design of an Adaptive Power Regulation Mechanism and a Nozzle for a Hydroelectric Power Plant Turbine Test Rig

NASA Astrophysics Data System (ADS)

Mert, Burak; Aytac, Zeynep; Tascioglu, Yigit; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

2014-11-01

This study deals with the design of a power regulation mechanism for a Hydroelectric Power Plant (HEPP) model turbine test system which is designed to test Francis type hydroturbines up to 2 MW power with varying head and flow(discharge) values. Unlike the tailor made regulation mechanisms of full-sized, functional HEPPs; the design for the test system must be easily adapted to various turbines that are to be tested. In order to achieve this adaptability, a dynamic simulation model is constructed in MATLAB/Simulink SimMechanics. This model acquires geometric data and hydraulic loading data of the regulation system from Autodesk Inventor CAD models and Computational Fluid Dynamics (CFD) analysis respectively. The dynamic model is explained and case studies of two different HEPPs are performed for validation. CFD aided design of the turbine guide vanes, which is used as input for the dynamic model, is also presented. This research is financially supported by Turkish Ministry of Development.

Data-driven Modeling of Metal-oxide Sensors with Dynamic Bayesian Networks

NASA Astrophysics Data System (ADS)

Gosangi, Rakesh; Gutierrez-Osuna, Ricardo

2011-09-01

We present a data-driven probabilistic framework to model the transient response of MOX sensors modulated with a sequence of voltage steps. Analytical models of MOX sensors are usually built based on the physico-chemical properties of the sensing materials. Although building these models provides an insight into the sensor behavior, they also require a thorough understanding of the underlying operating principles. Here we propose a data-driven approach to characterize the dynamical relationship between sensor inputs and outputs. Namely, we use dynamic Bayesian networks (DBNs), probabilistic models that represent temporal relations between a set of random variables. We identify a set of control variables that influence the sensor responses, create a graphical representation that captures the causal relations between these variables, and finally train the model with experimental data. We validated the approach on experimental data in terms of predictive accuracy and classification performance. Our results show that DBNs can accurately predict the dynamic response of MOX sensors, as well as capture the discriminatory information present in the sensor transients.

Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins.

PubMed

Karczyńska, Agnieszka S; Czaplewski, Cezary; Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Liwo, Adam

2017-12-05

Molecular simulations restrained to single or multiple templates are commonly used in protein-structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template-restrained canonical molecular dynamics (MD), multiplexed replica-exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse-grained UNRES force field on nine selected proteins, with pseudo-harmonic log-Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non-ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor-quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Method to Capture Macroslip at Bolted Interfaces

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

Hopkins, Ronald Neil; Heitman, Lili Anne Akin

2015-10-01

Relative motion at bolted connections can occur for large shock loads as the internal shear force in the bolted connection overcomes the frictional resistive force. This macroslip in a structure dissipates energy and reduces the response of the components above the bolted connection. There is a need to be able to capture macroslip behavior in a structural dynamics model. A linear model and many nonlinear models are not able to predict marcoslip effectively. The proposed method to capture macroslip is to use the multi-body dynamics code ADAMS to model joints with 3-D contact at the bolted interfaces. This model includesmore » both static and dynamic friction. The joints are preloaded and the pinning effect when a bolt shank impacts a through hole inside diameter is captured. Substructure representations of the components are included to account for component flexibility and dynamics. This method was applied to a simplified model of an aerospace structure and validation experiments were performed to test the adequacy of the method.« less

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

A Method to Capture Macroslip at Bolted Interfaces [PowerPoint

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

Hopkins, Ronald Neil; Heitman, Lili Anne Akin

2016-01-01

Relative motion at bolted connections can occur for large shock loads as the internal shear force in the bolted connection overcomes the frictional resistive force. This macroslip in a structure dissipates energy and reduces the response of the components above the bolted connection. There is a need to be able to capture macroslip behavior in a structural dynamics model. A linear model and many nonlinear models are not able to predict marcoslip effectively. The proposed method to capture macroslip is to use the multi-body dynamics code ADAMS to model joints with 3-D contact at the bolted interfaces. This model includesmore » both static and dynamic friction. The joints are preloaded and the pinning effect when a bolt shank impacts a through hole inside diameter is captured. Substructure representations of the components are included to account for component flexibility and dynamics. This method was applied to a simplified model of an aerospace structure and validation experiments were performed to test the adequacy of the method.« less

Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2017-09-01

In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Sharma, Pankaj; Jain, Ajai

2014-12-01

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.

Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

NASA Astrophysics Data System (ADS)

Junghans, Christoph; Mniszewski, Susan; Voter, Arthur; Perez, Danny; Eidenbenz, Stephan

2014-03-01

We present an example of a new class of tools that we call application simulators, parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation (PDES). We demonstrate our approach with a TADSim application simulator that models the Temperature Accelerated Dynamics (TAD) method, which is an algorithmically complex member of the Accelerated Molecular Dynamics (AMD) family. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We further extend TADSim to model algorithm extensions to standard TAD, such as speculative spawning of the compute-bound stages of the algorithm, and predict performance improvements without having to implement such a method. Focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights into the TAD algorithm behavior and suggested extensions to the TAD method.

Control system software, simulation, and robotic applications

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

1991-01-01

All essential existing capabilities needed to create a man-machine interaction dynamics and performance (MMIDAP) capability are reviewed. The multibody system dynamics software program Order N DISCOS will be used for machine and musculo-skeletal dynamics modeling. The program JACK will be used for estimating and animating whole body human response to given loading situations and motion constraints. The basic elements of performance (BEP) task decomposition methodologies associated with the Human Performance Institute database will be used for performance assessment. Techniques for resolving the statically indeterminant muscular load sharing problem will be used for a detailed understanding of potential musculotendon or ligamentous fatigue, pain, discomfort, and trauma. The envisioned capacity is to be used for mechanical system design, human performance assessment, extrapolation of man/machine interaction test data, biomedical engineering, and soft prototyping within a concurrent engineering (CE) system.

Approaching control for tethered space robot based on disturbance observer using super twisting law

NASA Astrophysics Data System (ADS)

Hu, Yongxin; Huang, Panfeng; Meng, Zhongjie; Wang, Dongke; Lu, Yingbo

2018-05-01

Approaching control is a key mission for the tethered space robot to perform the task of removing space debris. But the uncertainties of the TSR such as the change of model parameter have an important effect on the approaching mission. Considering the space tether and the attitude of the gripper, the dynamic model of the TSR is derived using Lagrange method. Then a disturbance observer is designed to estimate the uncertainty based on STW control method. Using the disturbance observer, a controller is designed, and the performance is compared with the dynamic inverse controller which turns out that the proposed controller performs better. Numerical simulation validates the feasibility of the proposed controller on the position and attitude tracking of the TSR.

Modelling and simulation of dynamic recrystallization (DRX) in OFHC copper at very high strain rates

NASA Astrophysics Data System (ADS)

Testa, G.; Bonora, N.; Ruggiero, A.; Iannitti, G.; Persechino, I.; Hörnqvist, M.; Mortazavi, N.

2017-01-01

At high strain rates, deformation processes are essentially adiabatic and if the plastic work is large enough dynamic recrystallization can occur. In this work, an examination on microstructure evolution of OFHC copper in Dynamic Tensile Extrusion (DTE) test, performed at 400 m/s, was carried out. EBSD investigations, along the center line of the fragment remaining in the extrusion die, showed a progressive elongation of the grains, and an accompanying development of a strong <001> + <111> dual fiber texture. Discontinuous dynamic recrystallization (DRX) occurred at larger strains, and it was showed that nucleation occurred during straining. A criterion for DRX to occur, based on the evolution of Zener-Hollomon parameter during the dynamic deformation process, is proposed. Finally, DTE test was simulated using the modified Rusinek-Klepaczko constitutive model incorporating a model for the prediction of DRX initiation.

Molecular Dynamics Simulations of Folding and Insertion of the Ebola Virus Fusion Peptide into a Membrane Bilayer

DTIC Science & Technology

2008-07-01

Molecular Dynamics Simulations of Folding and Insertion of the Ebola Virus Fusion Peptide into a Membrane Bilayer Mark A. Olson1, In...presents replica-exchange molecular dynamics simulations of the folding and insertion of a 16- residue Ebola virus fusion peptide into a membrane...separate calculated structures into conformational basins. 2.1 Simulation models Molecular dynamics simulations were performed using the all-atom

Dynamic modeling of moment wheel assemblies with nonlinear rolling bearing supports

NASA Astrophysics Data System (ADS)

Wang, Hong; Han, Qinkai; Luo, Ruizhi; Qing, Tao

2017-10-01

Moment wheel assemblies (MWA) have been widely used in spacecraft attitude control and large angle slewing maneuvers over the years. Understanding and controlling vibration of MWAs is a crucial factor to achieving the desired level of payload performance. Dynamic modeling of a MWA with nonlinear rolling bearing supports is conducted. An improved load distribution analysis is proposed to more accurately obtain the contact deformations and angles between the rolling balls and raceways. Then, the bearing restoring forces are then obtained through iteratively solving the load distribution equations at every time step. The effects of preload condition, surface waviness, Hertz contact and elastohydrodynamic lubrication could all be reflected in the nonlinear bearing forces. Considering the mass imbalances of the flywheel, flexibility of supporting structures and rolling bearing nonlinearity, the dynamic model of a typical MWA is established based upon the energy theorem. Dynamic tests are conducted to verify the nonlinear dynamic model. The influences of flywheel mass eccentricity and inner/outer waviness amplitudes on the dynamic responses are discussed in detail. The obtained results would be useful for the design and vibration control of the MWA system.

Further Investigations of Gravity Modeling on Surface-Interacting Vehicle Simulations

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2009-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of the gravitation and world model. A surface-interacting simulation cannot treat the gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a subsonic civil transport in level flight under various starting conditions.

Gravity Modeling Effects on Surface-Interacting Vehicles in Supersonic Flight

NASA Technical Reports Server (NTRS)

Madden, Michael M.

2010-01-01

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations per-form ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of these two models. A surface-interacting simulation cannot treat gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a supersonic aircraft in level flight under various start-ing conditions.

Dynamic and Thermal Turbulent Time Scale Modelling for Homogeneous Shear Flows

NASA Technical Reports Server (NTRS)

Schwab, John R.; Lakshminarayana, Budugur

1994-01-01

A new turbulence model, based upon dynamic and thermal turbulent time scale transport equations, is developed and applied to homogeneous shear flows with constant velocity and temperature gradients. The new model comprises transport equations for k, the turbulent kinetic energy; tau, the dynamic time scale; k(sub theta), the fluctuating temperature variance; and tau(sub theta), the thermal time scale. It offers conceptually parallel modeling of the dynamic and thermal turbulence at the two equation level, and eliminates the customary prescription of an empirical turbulent Prandtl number, Pr(sub t), thus permitting a more generalized prediction capability for turbulent heat transfer in complex flows and geometries. The new model also incorporates constitutive relations, based upon invariant theory, that allow the effects of nonequilibrium to modify the primary coefficients for the turbulent shear stress and heat flux. Predictions of the new model, along with those from two other similar models, are compared with experimental data for decaying homogeneous dynamic and thermal turbulence, homogeneous turbulence with constant temperature gradient, and homogeneous turbulence with constant temperature gradient and constant velocity gradient. The new model offers improvement in agreement with the data for most cases considered in this work, although it was no better than the other models for several cases where all the models performed poorly.

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

State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps

PubMed Central

Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.

2017-01-01

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

A dynamic response model for pressure sensors in continuum and high Knudsen number flows with large temperature gradients

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Petersen, Brian J.; Scott, David D.

1996-01-01

This paper develops a dynamic model for pressure sensors in continuum and rarefied flows with longitudinal temperature gradients. The model was developed from the unsteady Navier-Stokes momentum, energy, and continuity equations and was linearized using small perturbations. The energy equation was decoupled from momentum and continuity assuming a polytropic flow process. Rarefied flow conditions were accounted for using a slip flow boundary condition at the tubing wall. The equations were radially averaged and solved assuming gas properties remain constant along a small tubing element. This fundamental solution was used as a building block for arbitrary geometries where fluid properties may also vary longitudinally in the tube. The problem was solved recursively starting at the transducer and working upstream in the tube. Dynamic frequency response tests were performed for continuum flow conditions in the presence of temperature gradients. These tests validated the recursive formulation of the model. Model steady-state behavior was analyzed using the final value theorem. Tests were performed for rarefied flow conditions and compared to the model steady-state response to evaluate the regime of applicability. Model comparisons were excellent for Knudsen numbers up to 0.6. Beyond this point, molecular affects caused model analyses to become inaccurate.

An integrated physiology model to study regional lung damage effects and the physiologic response

PubMed Central

2014-01-01

Background This work expands upon a previously developed exercise dynamic physiology model (DPM) with the addition of an anatomic pulmonary system in order to quantify the impact of lung damage on oxygen transport and physical performance decrement. Methods A pulmonary model is derived with an anatomic structure based on morphometric measurements, accounting for heterogeneous ventilation and perfusion observed experimentally. The model is incorporated into an existing exercise physiology model; the combined system is validated using human exercise data. Pulmonary damage from blast, blunt trauma, and chemical injury is quantified in the model based on lung fluid infiltration (edema) which reduces oxygen delivery to the blood. The pulmonary damage component is derived and calibrated based on published animal experiments; scaling laws are used to predict the human response to lung injury in terms of physical performance decrement. Results The augmented dynamic physiology model (DPM) accurately predicted the human response to hypoxia, altitude, and exercise observed experimentally. The pulmonary damage parameters (shunt and diffusing capacity reduction) were fit to experimental animal data obtained in blast, blunt trauma, and chemical damage studies which link lung damage to lung weight change; the model is able to predict the reduced oxygen delivery in damage conditions. The model accurately estimates physical performance reduction with pulmonary damage. Conclusions We have developed a physiologically-based mathematical model to predict performance decrement endpoints in the presence of thoracic damage; simulations can be extended to estimate human performance and escape in extreme situations. PMID:25044032

Swarm Counter-Asymmetric-Threat (CAT) 6-DOF Dynamics Simulation

DTIC Science & Technology

2005-07-01

NAWCWD TP 8593 Swarm Counter-Asymmetric-Threat ( CAT ) 6-DOF Dynamics Simulation by James Bobinchak Weapons and Energetics...mathematical models used in the swarm counter- asymmetric-threat ( CAT ) simulation and the results of extensive Monte Carlo simulations. The swarm CAT ...Asymmetric-Threat ( CAT ) 6-DOF Dynamics Simulation (U) 6. AUTHOR(S) James Bobinchak and Gary Hewer 7. PERFORMING ORGANIZATION NAME(S) AND

Applying Aerodynamics Inspired Organizational Dynamic Fit Model Disaster Relief Endeavors

DTIC Science & Technology

2010-12-01

gusts, and a dynamically stable organization returns quickly to its intended profit level, for instance, after deviation by changed consumer preferences . Hence...dynamic stability limits the level, for instance, by changed consumer preferences . Hence static stability limits initial performance... consumer preferences Maneuverability Quickness of a controlled system’s planned change from one trajectory to another Quickness of planned

Experimental and analytical studies of advanced air cushion landing systems

NASA Technical Reports Server (NTRS)

Lee, E. G. S.; Boghani, A. B.; Captain, K. M.; Rutishauser, H. J.; Farley, H. L.; Fish, R. B.; Jeffcoat, R. L.

1981-01-01

Several concepts are developed for air cushion landing systems (ACLS) which have the potential for improving performance characteristics (roll stiffness, heave damping, and trunk flutter), and reducing fabrication cost and complexity. After an initial screening, the following five concepts were evaluated in detail: damped trunk, filled trunk, compartmented trunk, segmented trunk, and roll feedback control. The evaluation was based on tests performed on scale models. An ACLS dynamic simulation developed earlier is updated so that it can be used to predict the performance of full-scale ACLS incorporating these refinements. The simulation was validated through scale-model tests. A full-scale ACLS based on the segmented trunk concept was fabricated and installed on the NASA ACLS test vehicle, where it is used to support advanced system development. A geometrically-scaled model (one third full scale) of the NASA test vehicle was fabricated and tested. This model, evaluated by means of a series of static and dynamic tests, is used to investigate scaling relationships between reduced and full-scale models. The analytical model developed earlier is applied to simulate both the one third scale and the full scale response.

Longitudinal train dynamics model for a rail transit simulation system

DOE PAGES

Wang, Jinghui; Rakha, Hesham A.

2018-01-01

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of themore » model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.« less

Longitudinal train dynamics model for a rail transit simulation system

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

Wang, Jinghui; Rakha, Hesham A.

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of themore » model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.« less

Experimental and modelling of Arthrospira platensis cultivation in open raceway ponds.

PubMed

Ranganathan, Panneerselvam; Amal, J C; Savithri, S; Haridas, Ajith

2017-10-01

In this study, the growth of Arthrospira platensis was studied in an open raceway pond. Furthermore, dynamic model for algae growth and CFD modelling of hydrodynamics in open raceway pond were developed. The dynamic behaviour of the algal system was developed by solving mass balance equations of various components, considering light intensity and gas-liquid mass transfer. A CFD modelling of the hydrodynamics of open raceway pond was developed by solving mass and momentum balance equations of the liquid medium. The prediction of algae concentration from the dynamic model was compared with the experimental data. The hydrodynamic behaviour of the open raceway pond was compared with the literature data for model validation. The model predictions match the experimental findings. Furthermore, the hydrodynamic behaviour and residence time distribution in our small raceway pond were predicted. These models can serve as a tool to assess the pond performance criteria. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Predicting the evolution of complex networks via similarity dynamics

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-01-01

Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

Laser interferometer space antenna dynamics and controls model

NASA Astrophysics Data System (ADS)

Maghami, Peiman G.; Tupper Hyde, T.

2003-05-01

A 19 degree-of-freedom (DOF) dynamics and controls model of a laser interferometer space antenna (LISA) spacecraft has been developed. This model is used to evaluate the feasibility of the dynamic pointing and positioning requirements of a typical LISA spacecraft. These requirements must be met for LISA to be able to successfully detect gravitational waves in the frequency band of interest (0.1-100 mHz). The 19-DOF model includes all rigid-body degrees of freedom. A number of disturbance sources, both internal and external, are included. Preliminary designs for the four control systems that comprise the LISA disturbance reduction system (DRS) have been completed and are included in the model. Simulation studies are performed to demonstrate that the LISA pointing and positioning requirements are feasible and can be met.

A Nonlinear Dynamics-Based Estimator for Functional Electrical Stimulation: Preliminary Results From Lower-Leg Extension Experiments.

PubMed

Allen, Marcus; Zhong, Qiang; Kirsch, Nicholas; Dani, Ashwin; Clark, William W; Sharma, Nitin

2017-12-01

Miniature inertial measurement units (IMUs) are wearable sensors that measure limb segment or joint angles during dynamic movements. However, IMUs are generally prone to drift, external magnetic interference, and measurement noise. This paper presents a new class of nonlinear state estimation technique called state-dependent coefficient (SDC) estimation to accurately predict joint angles from IMU measurements. The SDC estimation method uses limb dynamics, instead of limb kinematics, to estimate the limb state. Importantly, the nonlinear limb dynamic model is formulated into state-dependent matrices that facilitate the estimator design without performing a Jacobian linearization. The estimation method is experimentally demonstrated to predict knee joint angle measurements during functional electrical stimulation of the quadriceps muscle. The nonlinear knee musculoskeletal model was identified through a series of experiments. The SDC estimator was then compared with an extended kalman filter (EKF), which uses a Jacobian linearization and a rotation matrix method, which uses a kinematic model instead of the dynamic model. Each estimator's performance was evaluated against the true value of the joint angle, which was measured through a rotary encoder. The experimental results showed that the SDC estimator, the rotation matrix method, and EKF had root mean square errors of 2.70°, 2.86°, and 4.42°, respectively. Our preliminary experimental results show the new estimator's advantage over the EKF method but a slight advantage over the rotation matrix method. However, the information from the dynamic model allows the SDC method to use only one IMU to measure the knee angle compared with the rotation matrix method that uses two IMUs to estimate the angle.

Structural model for fluctuations in financial markets

NASA Astrophysics Data System (ADS)

Anand, Kartik; Khedair, Jonathan; Kühn, Reimer

2018-05-01

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market which takes the form of an interacting generalization of the geometric Brownian motion model. It is formally equivalent to a model describing the stochastic dynamics of a system of analog neurons, which is expected to exhibit glassy properties and thus many metastable states in a large portion of its parameter space. We perform a generating functional analysis, introducing a slow driving of the dynamics to mimic the effect of slowly varying macroeconomic conditions. Distributions of asset returns over various time separations are evaluated analytically and are found to be fat-tailed in a manner broadly in line with empirical observations. Our model also allows us to identify collective, interaction-mediated properties of pricing distributions and it predicts pricing distributions which are significantly broader than their noninteracting counterparts, if interactions between prices in the model contain a ferromagnetic bias. Using simulations, we are able to substantiate one of the main hypotheses underlying the original modeling, viz., that the phenomenon of volatility clustering can be rationalized in terms of an interplay between the dynamics within metastable states and the dynamics of occasional transitions between them.

Dynamics Analysis of Anti-predator Model on Intermediate Predator With Ratio Dependent Functional Responses

NASA Astrophysics Data System (ADS)

Savitri, D.

2018-01-01

This articel discusses a predator prey model with anti-predator on intermediate predator using ratio dependent functional responses. Dynamical analysis performed on the model includes determination of equilibrium point, stability and simulation. Three kinds of equilibrium points have been discussed, namely the extinction of prey point, the extinction of intermediate predator point and the extinction of predator point are exists under certain conditions. It can be shown that the result of numerical simulations are in accordance with analitical results

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

On the robustness of complex heterogeneous gene expression networks.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir; Floría, Luis M

2005-04-01

We analyze a continuous gene expression model on the underlying topology of a complex heterogeneous network. Numerical simulations aimed at studying the chaotic and periodic dynamics of the model are performed. The results clearly indicate that there is a region in which the dynamical and structural complexity of the system avoid chaotic attractors. However, contrary to what has been reported for Random Boolean Networks, the chaotic phase cannot be completely suppressed, which has important bearings on network robustness and gene expression modeling.

Dynamic shear-lag model for understanding the role of matrix in energy dissipation in fiber-reinforced composites.

PubMed

Liu, Junjie; Zhu, Wenqing; Yu, Zhongliang; Wei, Xiaoding

2018-07-01

Lightweight and high impact performance composite design is a big challenge for scientists and engineers. Inspired from well-known biological materials, e.g., the bones, spider silk, and claws of mantis shrimp, artificial composites have been synthesized for engineering applications. Presently, the design of ballistic resistant composites mainly emphasizes the utilization of light and high-strength fibers, whereas the contribution from matrix materials receives less attention. However, recent ballistic experiments on fiber-reinforced composites challenge our common sense. The use of matrix with "low-grade" properties enhances effectively the impact performance. In this study, we establish a dynamic shear-lag model to explore the energy dissipation through viscous matrix materials in fiber-reinforced composites and the associations of energy dissipation characteristics with the properties and geometries of constituents. The model suggests that an enhancement in energy dissipation before the material integrity is lost can be achieved by tuning the shear modulus and viscosity of a matrix. Furthermore, our model implies that an appropriately designed staggered microstructure, adopted by many natural composites, can repeatedly activate the energy dissipation process and thus improve dramatically the impact performance. This model demonstrates the role of matrix in energy dissipation, and stimulates new advanced material design concepts for ballistic applications. Biological composites found in nature often possess exceptional mechanical properties that man-made materials haven't be able to achieve. For example, it is predicted that a pencil thick spider silk thread can stop a flying Boeing airplane. Here, by proposing a dynamic shear-lag model, we investigate the relationships between the impact performance of a composite with the dimensions and properties of its constituents. Our analysis suggests that the impact performance of fiber-reinforced composites could improve surprisingly with "low-grade" matrix materials, and discontinuities (often regarded as "defects") may play an important role in energy dissipation. Counter-intuitive as it may seem, our work helps understanding the secrets of the outstanding dynamic properties of some biological materials, and inspire novel ideas for man-made composites. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Mechanical model development of rolling bearing-rotor systems: A review

NASA Astrophysics Data System (ADS)

Cao, Hongrui; Niu, Linkai; Xi, Songtao; Chen, Xuefeng

2018-03-01

The rolling bearing rotor (RBR) system is the kernel of many rotating machines, which affects the performance of the whole machine. Over the past decades, extensive research work has been carried out to investigate the dynamic behavior of RBR systems. However, to the best of the authors' knowledge, no comprehensive review on RBR modelling has been reported yet. To address this gap in the literature, this paper reviews and critically discusses the current progress of mechanical model development of RBR systems, and identifies future trends for research. Firstly, five kinds of rolling bearing models, i.e., the lumped-parameter model, the quasi-static model, the quasi-dynamic model, the dynamic model, and the finite element (FE) model are summarized. Then, the coupled modelling between bearing models and various rotor models including De Laval/Jeffcott rotor, rigid rotor, transfer matrix method (TMM) models and FE models are presented. Finally, the paper discusses the key challenges of previous works and provides new insights into understanding of RBR systems for their advanced future engineering applications.

Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

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

Iacono, Michael J.

The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting eithermore » more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.« less

Dynamic and fluid–structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models

PubMed Central

Kamensky, David; Xu, Fei; Kiendl, Josef; Wang, Chenglong; Wu, Michael C. H.; Mineroff, Joshua; Reali, Alessandro; Bazilevs, Yuri; Sacks, Michael S.

2015-01-01

This paper builds on a recently developed immersogeometric fluid–structure interaction (FSI) methodology for bioprosthetic heart valve (BHV) modeling and simulation. It enhances the proposed framework in the areas of geometry design and constitutive modeling. With these enhancements, BHV FSI simulations may be performed with greater levels of automation, robustness and physical realism. In addition, the paper presents a comparison between FSI analysis and standalone structural dynamics simulation driven by prescribed transvalvular pressure, the latter being a more common modeling choice for this class of problems. The FSI computation achieved better physiological realism in predicting the valve leaflet deformation than its standalone structural dynamics counterpart. PMID:26392645