Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network
NASA Astrophysics Data System (ADS)
Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng
2013-01-01
Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.
Dynamic inverse models in human-cyber-physical systems
NASA Astrophysics Data System (ADS)
Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar
2016-05-01
Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.
Using a pseudo-dynamic source inversion approach to improve earthquake source imaging
NASA Astrophysics Data System (ADS)
Zhang, Y.; Song, S. G.; Dalguer, L. A.; Clinton, J. F.
2014-12-01
Imaging a high-resolution spatio-temporal slip distribution of an earthquake rupture is a core research goal in seismology. In general we expect to obtain a higher quality source image by improving the observational input data (e.g. using more higher quality near-source stations). However, recent studies show that increasing the surface station density alone does not significantly improve source inversion results (Custodio et al. 2005; Zhang et al. 2014). We introduce correlation structures between the kinematic source parameters: slip, rupture velocity, and peak slip velocity (Song et al. 2009; Song and Dalguer 2013) in the non-linear source inversion. The correlation structures are physical constraints derived from rupture dynamics that effectively regularize the model space and may improve source imaging. We name this approach pseudo-dynamic source inversion. We investigate the effectiveness of this pseudo-dynamic source inversion method by inverting low frequency velocity waveforms from a synthetic dynamic rupture model of a buried vertical strike-slip event (Mw 6.5) in a homogeneous half space. In the inversion, we use a genetic algorithm in a Bayesian framework (Moneli et al. 2008), and a dynamically consistent regularized Yoffe function (Tinti, et al. 2005) was used for a single-window slip velocity function. We search for local rupture velocity directly in the inversion, and calculate the rupture time using a ray-tracing technique. We implement both auto- and cross-correlation of slip, rupture velocity, and peak slip velocity in the prior distribution. Our results suggest that kinematic source model estimates capture the major features of the target dynamic model. The estimated rupture velocity closely matches the target distribution from the dynamic rupture model, and the derived rupture time is smoother than the one we searched directly. By implementing both auto- and cross-correlation of kinematic source parameters, in comparison to traditional smoothing constraints, we are in effect regularizing the model space in a more physics-based manner without loosing resolution of the source image. Further investigation is needed to tune the related parameters of pseudo-dynamic source inversion and relative weighting between the prior and the likelihood function in the Bayesian inversion.
2016-01-01
Introduction Inverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)–multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints. Methods We performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power. Results The EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2–7%. Conclusions During Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs. PMID:27764110
Honert, Eric C; Zelik, Karl E
2016-01-01
Inverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)-multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints. We performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power. The EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2-7%. During Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs.
Feedback control laws for highly maneuverable aircraft
NASA Technical Reports Server (NTRS)
Garrard, William L.; Balas, Gary J.
1994-01-01
During the first half of the year, the investigators concentrated their efforts on completing the design of control laws for the longitudinal axis of the HARV. During the second half of the year they concentrated on the synthesis of control laws for the lateral-directional axes. The longitudinal control law design efforts can be briefly summarized as follows. Longitudinal control laws were developed for the HARV using mu synthesis design techniques coupled with dynamic inversion. An inner loop dynamic inversion controller was used to simplify the system dynamics by eliminating the aerodynamic nonlinearities and inertial cross coupling. Models of the errors resulting from uncertainties in the principal longitudinal aerodynamic terms were developed and included in the model of the HARV with the inner loop dynamic inversion controller. This resulted in an inner loop transfer function model which was an integrator with the modeling errors characterized as uncertainties in gain and phase. Outer loop controllers were then designed using mu synthesis to provide robustness to these modeling errors and give desired response to pilot inputs. Both pitch rate and angle of attack command following systems were designed. The following tasks have been accomplished for the lateral-directional controllers: inner and outer loop dynamic inversion controllers have been designed; an error model based on a linearized perturbation model of the inner loop system was derived; controllers for the inner loop system have been designed, using classical techniques, that control roll rate and Dutch roll response; the inner loop dynamic inversion and classical controllers have been implemented on the six degree of freedom simulation; and lateral-directional control allocation scheme has been developed based on minimizing required control effort.
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.
A 3D generic inverse dynamic method using wrench notation and quaternion algebra.
Dumas, R; Aissaoui, R; de Guise, J A
2004-06-01
In the literature, conventional 3D inverse dynamic models are limited in three aspects related to inverse dynamic notation, body segment parameters and kinematic formalism. First, conventional notation yields separate computations of the forces and moments with successive coordinate system transformations. Secondly, the way conventional body segment parameters are defined is based on the assumption that the inertia tensor is principal and the centre of mass is located between the proximal and distal ends. Thirdly, the conventional kinematic formalism uses Euler or Cardanic angles that are sequence-dependent and suffer from singularities. In order to overcome these limitations, this paper presents a new generic method for inverse dynamics. This generic method is based on wrench notation for inverse dynamics, a general definition of body segment parameters and quaternion algebra for the kinematic formalism.
High effective inverse dynamics modelling for dual-arm robot
NASA Astrophysics Data System (ADS)
Shen, Haoyu; Liu, Yanli; Wu, Hongtao
2018-05-01
To deal with the problem of inverse dynamics modelling for dual arm robot, a recursive inverse dynamics modelling method based on decoupled natural orthogonal complement is presented. In this model, the concepts and methods of Decoupled Natural Orthogonal Complement matrices are used to eliminate the constraint forces in the Newton-Euler kinematic equations, and the screws is used to express the kinematic and dynamics variables. On this basis, the paper has developed a special simulation program with symbol software of Mathematica and conducted a simulation research on the a dual-arm robot. Simulation results show that the proposed method based on decoupled natural orthogonal complement can save an enormous amount of CPU time that was spent in computing compared with the recursive Newton-Euler kinematic equations and the results is correct and reasonable, which can verify the reliability and efficiency of the method.
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
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.
NASA Astrophysics Data System (ADS)
Liu, Yi; Zhang, He; Liu, Siwei; Lin, Fuchang
2018-05-01
The J-A (Jiles-Atherton) model is widely used to describe the magnetization characteristics of magnetic cores in a low-frequency alternating field. However, this model is deficient in the quantitative analysis of the eddy current loss and residual loss in a high-frequency magnetic field. Based on the decomposition of magnetization intensity, an inverse J-A model is established which uses magnetic flux density B as an input variable. Static and dynamic core losses under high frequency excitation are separated based on the inverse J-A model. Optimized parameters of the inverse J-A model are obtained based on particle swarm optimization. The platform for the pulsed magnetization characteristic test is designed and constructed. The hysteresis curves of ferrite and Fe-based nanocrystalline cores at high magnetization rates are measured. The simulated and measured hysteresis curves are presented and compared. It is found that the inverse J-A model can be used to describe the magnetization characteristics at high magnetization rates and to separate the static loss and dynamic loss accurately.
Multiple estimation channel decoupling and optimization method based on inverse system
NASA Astrophysics Data System (ADS)
Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng
2018-03-01
This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.
Inverse problem of HIV cell dynamics using Genetic Algorithms
NASA Astrophysics Data System (ADS)
González, J. A.; Guzmán, F. S.
2017-01-01
In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.
Inverse problems in the modeling of vibrations of flexible beams
NASA Technical Reports Server (NTRS)
Banks, H. T.; Powers, R. K.; Rosen, I. G.
1987-01-01
The formulation and solution of inverse problems for the estimation of parameters which describe damping and other dynamic properties in distributed models for the vibration of flexible structures is considered. Motivated by a slewing beam experiment, the identification of a nonlinear velocity dependent term which models air drag damping in the Euler-Bernoulli equation is investigated. Galerkin techniques are used to generate finite dimensional approximations. Convergence estimates and numerical results are given. The modeling of, and related inverse problems for the dynamics of a high pressure hose line feeding a gas thruster actuator at the tip of a cantilevered beam are then considered. Approximation and convergence are discussed and numerical results involving experimental data are presented.
NASA Technical Reports Server (NTRS)
Kwon, Dong-Soo
1991-01-01
All research results about flexible manipulator control were integrated to show a control scenario of a bracing manipulator. First, dynamic analysis of a flexible manipulator was done for modeling. Second, from the dynamic model, the inverse dynamic equation was derived, and the time domain inverse dynamic method was proposed for the calculation of the feedforward torque and the desired flexible coordinate trajectories. Third, a tracking controller was designed by combining the inverse dynamic feedforward control with the joint feedback control. The control scheme was applied to the tip position control of a single link flexible manipulator for zero and non-zero initial condition cases. Finally, the contact control scheme was added to the position tracking control. A control scenario of a bracing manipulator is provided and evaluated through simulation and experiment on a single link flexible manipulator.
NASA Astrophysics Data System (ADS)
Mai, P. M.; Schorlemmer, D.; Page, M.
2012-04-01
Earthquake source inversions image the spatio-temporal rupture evolution on one or more fault planes using seismic and/or geodetic data. Such studies are critically important for earthquake seismology in general, and for advancing seismic hazard analysis in particular, as they reveal earthquake source complexity and help (i) to investigate earthquake mechanics; (ii) to develop spontaneous dynamic rupture models; (iii) to build models for generating rupture realizations for ground-motion simulations. In applications (i - iii), the underlying finite-fault source models are regarded as "data" (input information), but their uncertainties are essentially unknown. After all, source models are obtained from solving an inherently ill-posed inverse problem to which many a priori assumptions and uncertain observations are applied. The Source Inversion Validation (SIV) project is a collaborative effort to better understand the variability between rupture models for a single earthquake (as manifested in the finite-source rupture model database) and to develop robust uncertainty quantification for earthquake source inversions. The SIV project highlights the need to develop a long-standing and rigorous testing platform to examine the current state-of-the-art in earthquake source inversion, and to develop and test novel source inversion approaches. We will review the current status of the SIV project, and report the findings and conclusions of the recent workshops. We will briefly discuss several source-inversion methods, how they treat uncertainties in data, and assess the posterior model uncertainty. Case studies include initial forward-modeling tests on Green's function calculations, and inversion results for synthetic data from spontaneous dynamic crack-like strike-slip earthquake on steeply dipping fault, embedded in a layered crustal velocity-density structure.
GARCH modelling of covariance in dynamical estimation of inverse solutions
NASA Astrophysics Data System (ADS)
Galka, Andreas; Yamashita, Okito; Ozaki, Tohru
2004-12-01
The problem of estimating unobserved states of spatially extended dynamical systems poses an inverse problem, which can be solved approximately by a recently developed variant of Kalman filtering; in order to provide the model of the dynamics with more flexibility with respect to space and time, we suggest to combine the concept of GARCH modelling of covariance, well known in econometrics, with Kalman filtering. We formulate this algorithm for spatiotemporal systems governed by stochastic diffusion equations and demonstrate its feasibility by presenting a numerical simulation designed to imitate the situation of the generation of electroencephalographic recordings by the human cortex.
Feder, Jeffrey L.; Nosil, Patrik; Flaxman, Samuel M.
2014-01-01
Many hypotheses have been put forth to explain the origin and spread of inversions, and their significance for speciation. Several recent genic models have proposed that inversions promote speciation with gene flow due to the adaptive significance of the genes contained within them and because of the effects inversions have on suppressing recombination. However, the consequences of inversions for the dynamics of genome wide divergence across the speciation continuum remain unclear, an issue we examine here. We review a framework for the genomics of speciation involving the congealing of the genome into alternate adaptive states representing species (“genome wide congealing”). We then place inversions in this context as examples of how genetic hitchhiking can potentially hasten genome wide congealing. Specifically, we use simulation models to (i) examine the conditions under which inversions may speed genome congealing and (ii) quantify predicted magnitudes of these effects. Effects of inversions on promoting speciation were most common and pronounced when inversions were initially fixed between populations before secondary contact and adaptation involved many genes with small fitness effects. Further work is required on the role of underdominance and epistasis between a few loci of major effect within inversions. The results highlight five important aspects of the roles of inversions in speciation: (i) the geographic context of the origins and spread of inversions, (ii) the conditions under which inversions can facilitate divergence, (iii) the magnitude of that facilitation, (iv) the extent to which the buildup of divergence is likely to be biased within vs. outside of inversions, and (v) the dynamics of the appearance and disappearance of exceptional divergence within inversions. We conclude by discussing the empirical challenges in showing that inversions play a central role in facilitating speciation with gene flow. PMID:25206365
Comparison of dynamic treatment regimes via inverse probability weighting.
Hernán, Miguel A; Lanoy, Emilie; Costagliola, Dominique; Robins, James M
2006-03-01
Appropriate analysis of observational data is our best chance to obtain answers to many questions that involve dynamic treatment regimes. This paper describes a simple method to compare dynamic treatment regimes by artificially censoring subjects and then using inverse probability weighting (IPW) to adjust for any selection bias introduced by the artificial censoring. The basic strategy can be summarized in four steps: 1) define two regimes of interest, 2) artificially censor individuals when they stop following one of the regimes of interest, 3) estimate inverse probability weights to adjust for the potential selection bias introduced by censoring in the previous step, 4) compare the survival of the uncensored individuals under each regime of interest by fitting an inverse probability weighted Cox proportional hazards model with the dichotomous regime indicator and the baseline confounders as covariates. In the absence of model misspecification, the method is valid provided data are available on all time-varying and baseline joint predictors of survival and regime discontinuation. We present an application of the method to compare the AIDS-free survival under two dynamic treatment regimes in a large prospective study of HIV-infected patients. The paper concludes by discussing the relative advantages and disadvantages of censoring/IPW versus g-estimation of nested structural models to compare dynamic regimes.
NASA Technical Reports Server (NTRS)
Campbell, Stefan F.; Kaneshige, John T.
2010-01-01
Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).
Feedback control by online learning an inverse model.
Waegeman, Tim; Wyffels, Francis; Schrauwen, Francis
2012-10-01
A model, predictor, or error estimator is often used by a feedback controller to control a plant. Creating such a model is difficult when the plant exhibits nonlinear behavior. In this paper, a novel online learning control framework is proposed that does not require explicit knowledge about the plant. This framework uses two learning modules, one for creating an inverse model, and the other for actually controlling the plant. Except for their inputs, they are identical. The inverse model learns by the exploration performed by the not yet fully trained controller, while the actual controller is based on the currently learned model. The proposed framework allows fast online learning of an accurate controller. The controller can be applied on a broad range of tasks with different dynamic characteristics. We validate this claim by applying our control framework on several control tasks: 1) the heating tank problem (slow nonlinear dynamics); 2) flight pitch control (slow linear dynamics); and 3) the balancing problem of a double inverted pendulum (fast linear and nonlinear dynamics). The results of these experiments show that fast learning and accurate control can be achieved. Furthermore, a comparison is made with some classical control approaches, and observations concerning convergence and stability are made.
Full analogue electronic realisation of the Hodgkin-Huxley neuronal dynamics in weak-inversion CMOS.
Lazaridis, E; Drakakis, E M; Barahona, M
2007-01-01
This paper presents a non-linear analog synthesis path towards the modeling and full implementation of the Hodgkin-Huxley neuronal dynamics in silicon. The proposed circuits have been realized in weak-inversion CMOS technology and take advantage of both log-domain and translinear transistor-level techniques.
Pseudo-dynamic source characterization accounting for rough-fault effects
NASA Astrophysics Data System (ADS)
Galis, Martin; Thingbaijam, Kiran K. S.; Mai, P. Martin
2016-04-01
Broadband ground-motion simulations, ideally for frequencies up to ~10Hz or higher, are important for earthquake engineering; for example, seismic hazard analysis for critical facilities. An issue with such simulations is realistic generation of radiated wave-field in the desired frequency range. Numerical simulations of dynamic ruptures propagating on rough faults suggest that fault roughness is necessary for realistic high-frequency radiation. However, simulations of dynamic ruptures are too expensive for routine applications. Therefore, simplified synthetic kinematic models are often used. They are usually based on rigorous statistical analysis of rupture models inferred by inversions of seismic and/or geodetic data. However, due to limited resolution of the inversions, these models are valid only for low-frequency range. In addition to the slip, parameters such as rupture-onset time, rise time and source time functions are needed for complete spatiotemporal characterization of the earthquake rupture. But these parameters are poorly resolved in the source inversions. To obtain a physically consistent quantification of these parameters, we simulate and analyze spontaneous dynamic ruptures on rough faults. First, by analyzing the impact of fault roughness on the rupture and seismic radiation, we develop equivalent planar-fault kinematic analogues of the dynamic ruptures. Next, we investigate the spatial interdependencies between the source parameters to allow consistent modeling that emulates the observed behavior of dynamic ruptures capturing the rough-fault effects. Based on these analyses, we formulate a framework for pseudo-dynamic source model, physically consistent with the dynamic ruptures on rough faults.
Inverse dynamic substructuring using the direct hybrid assembly in the frequency domain
NASA Astrophysics Data System (ADS)
D'Ambrogio, Walter; Fregolent, Annalisa
2014-04-01
The paper deals with the identification of the dynamic behaviour of a structural subsystem, starting from the known dynamic behaviour of both the coupled system and the remaining part of the structural system (residual subsystem). This topic is also known as decoupling problem, subsystem subtraction or inverse dynamic substructuring. Whenever it is necessary to combine numerical models (e.g. FEM) and test models (e.g. FRFs), one speaks of experimental dynamic substructuring. Substructure decoupling techniques can be classified as inverse coupling or direct decoupling techniques. In inverse coupling, the equations describing the coupling problem are rearranged to isolate the unknown substructure instead of the coupled structure. On the contrary, direct decoupling consists in adding to the coupled system a fictitious subsystem that is the negative of the residual subsystem. Starting from a reduced version of the 3-field formulation (dynamic equilibrium using FRFs, compatibility and equilibrium of interface forces), a direct hybrid assembly is developed by requiring that both compatibility and equilibrium conditions are satisfied exactly, either at coupling DoFs only, or at additional internal DoFs of the residual subsystem. Equilibrium and compatibility DoFs might not be the same: this generates the so-called non-collocated approach. The technique is applied using experimental data from an assembled system made by a plate and a rigid mass.
The experimental identification of magnetorheological dampers and evaluation of their controllers
NASA Astrophysics Data System (ADS)
Metered, H.; Bonello, P.; Oyadiji, S. O.
2010-05-01
Magnetorheological (MR) fluid dampers are semi-active control devices that have been applied over a wide range of practical vibration control applications. This paper concerns the experimental identification of the dynamic behaviour of an MR damper and the use of the identified parameters in the control of such a damper. Feed-forward and recurrent neural networks are used to model both the direct and inverse dynamics of the damper. Training and validation of the proposed neural networks are achieved by using the data generated through dynamic tests with the damper mounted on a tensile testing machine. The validation test results clearly show that the proposed neural networks can reliably represent both the direct and inverse dynamic behaviours of an MR damper. The effect of the cylinder's surface temperature on both the direct and inverse dynamics of the damper is studied, and the neural network model is shown to be reasonably robust against significant temperature variation. The inverse recurrent neural network model is introduced as a damper controller and experimentally evaluated against alternative controllers proposed in the literature. The results reveal that the neural-based damper controller offers superior damper control. This observation and the added advantages of low-power requirement, extended service life of the damper and the minimal use of sensors, indicate that a neural-based damper controller potentially offers the most cost-effective vibration control solution among the controllers investigated.
Constraining inverse-curvature gravity with supernovae.
Mena, Olga; Santiago, José; Weller, Jochen
2006-02-03
We show that models of generalized modified gravity, with inverse powers of the curvature, can explain the current accelerated expansion of the Universe without resorting to dark energy and without conflicting with solar system experiments. We have solved the Friedmann equations for the full dynamical range of the evolution of the Universe and performed a detailed analysis of supernovae data in the context of such models that results in an excellent fit. If we further include constraints on the current expansion of the Universe and on its age, we obtain that the matter content of the Universe is 0.07
NASA Astrophysics Data System (ADS)
Müller, Silvia; Brockmann, Jan Martin; Schuh, Wolf-Dieter
2015-04-01
The ocean's dynamic topography as the difference between the sea surface and the geoid reflects many characteristics of the general ocean circulation. Consequently, it provides valuable information for evaluating or tuning ocean circulation models. The sea surface is directly observed by satellite radar altimetry while the geoid cannot be observed directly. The satellite-based gravity field determination requires different measurement principles (satellite-to-satellite tracking (e.g. GRACE), satellite-gravity-gradiometry (GOCE)). In addition, hydrographic measurements (salinity, temperature and pressure; near-surface velocities) provide information on the dynamic topography. The observation types have different representations and spatial as well as temporal resolutions. Therefore, the determination of the dynamic topography is not straightforward. Furthermore, the integration of the dynamic topography into ocean circulation models requires not only the dynamic topography itself but also its inverse covariance matrix on the ocean model grid. We developed a rigorous combination method in which the dynamic topography is parameterized in space as well as in time. The altimetric sea surface heights are expressed as a sum of geoid heights represented in terms of spherical harmonics and the dynamic topography parameterized by a finite element method which can be directly related to the particular ocean model grid. Besides the difficult task of combining altimetry data with a gravity field model, a major aspect is the consistent combination of satellite data and in-situ observations. The particular characteristics and the signal content of the different observations must be adequately considered requiring the introduction of auxiliary parameters. Within our model the individual observation groups are combined in terms of normal equations considering their full covariance information; i.e. a rigorous variance/covariance propagation from the original measurements to the final product is accomplished. In conclusion, the developed integrated approach allows for estimating the dynamic topography and its inverse covariance matrix on arbitrary grids in space and time. The inverse covariance matrix contains the appropriate weights for model-data misfits in least-squares ocean model inversions. The focus of this study is on the North Atlantic Ocean. We will present the conceptual design and dynamic topography estimates based on time variable data from seven satellite altimeter missions (Jason-1, Jason-2, Topex/Poseidon, Envisat, ERS-2, GFO, Cryosat2) in combination with the latest GOCE gravity field model and in-situ data from the Argo floats and near-surface drifting buoys.
van der Kruk, E; Schwab, A L; van der Helm, F C T; Veeger, H E J
2018-03-01
In gait studies body pose reconstruction (BPR) techniques have been widely explored, but no previous protocols have been developed for speed skating, while the peculiarities of the skating posture and technique do not automatically allow for the transfer of the results of those explorations to kinematic skating data. The aim of this paper is to determine the best procedure for body pose reconstruction and inverse dynamics of speed skating, and to what extend this choice influences the estimation of joint power. The results show that an eight body segment model together with a global optimization method with revolute joint in the knee and in the lumbosacral joint, while keeping the other joints spherical, would be the most realistic model to use for the inverse kinematics in speed skating. To determine joint power, this method should be combined with a least-square error method for the inverse dynamics. Reporting on the BPR technique and the inverse dynamic method is crucial to enable comparison between studies. Our data showed an underestimation of up to 74% in mean joint power when no optimization procedure was applied for BPR and an underestimation of up to 31% in mean joint power when a bottom-up inverse dynamics method was chosen instead of a least square error approach. Although these results are aimed at speed skating, reporting on the BPR procedure and the inverse dynamics method, together with setting a golden standard should be common practice in all human movement research to allow comparison between studies. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Rainone, Corrado; Ferrari, Ulisse; Paoluzzi, Matteo; Leuzzi, Luca
2015-12-01
The short- and long-time dynamics of model systems undergoing a glass transition with apparent inversion of Kauzmann and dynamical arrest glass transition lines is investigated. These models belong to the class of the spherical mean-field approximation of a spin-1 model with p -body quenched disordered interaction, with p >2 , termed spherical Blume-Emery-Griffiths models. Depending on temperature and chemical potential the system is found in a paramagnetic or in a glassy phase and the transition between these phases can be of a different nature. In specific regions of the phase diagram coexistence of low-density and high-density paramagnets can occur, as well as the coexistence of spin-glass and paramagnetic phases. The exact static solution for the glassy phase is known to be obtained by the one-step replica symmetry breaking ansatz. Different scenarios arise for both the dynamic and the thermodynamic transitions. These include: (i) the usual random first-order transition (Kauzmann-like) for mean-field glasses preceded by a dynamic transition, (ii) a thermodynamic first-order transition with phase coexistence and latent heat, and (iii) a regime of apparent inversion of static transition line and dynamic transition lines, the latter defined as a nonzero complexity line. The latter inversion, though, turns out to be preceded by a dynamical arrest line at higher temperature. Crossover between different regimes is analyzed by solving mode-coupling-theory equations near the boundaries of paramagnetic solutions and the relationship with the underlying statics is discussed.
Tuning Fractures With Dynamic Data
NASA Astrophysics Data System (ADS)
Yao, Mengbi; Chang, Haibin; Li, Xiang; Zhang, Dongxiao
2018-02-01
Flow in fractured porous media is crucial for production of oil/gas reservoirs and exploitation of geothermal energy. Flow behaviors in such media are mainly dictated by the distribution of fractures. Measuring and inferring the distribution of fractures is subject to large uncertainty, which, in turn, leads to great uncertainty in the prediction of flow behaviors. Inverse modeling with dynamic data may assist to constrain fracture distributions, thus reducing the uncertainty of flow prediction. However, inverse modeling for flow in fractured reservoirs is challenging, owing to the discrete and non-Gaussian distribution of fractures, as well as strong nonlinearity in the relationship between flow responses and model parameters. In this work, building upon a series of recent advances, an inverse modeling approach is proposed to efficiently update the flow model to match the dynamic data while retaining geological realism in the distribution of fractures. In the approach, the Hough-transform method is employed to parameterize non-Gaussian fracture fields with continuous parameter fields, thus rendering desirable properties required by many inverse modeling methods. In addition, a recently developed forward simulation method, the embedded discrete fracture method (EDFM), is utilized to model the fractures. The EDFM maintains computational efficiency while preserving the ability to capture the geometrical details of fractures because the matrix is discretized as structured grid, while the fractures being handled as planes are inserted into the matrix grids. The combination of Hough representation of fractures with the EDFM makes it possible to tune the fractures (through updating their existence, location, orientation, length, and other properties) without requiring either unstructured grids or regridding during updating. Such a treatment is amenable to numerous inverse modeling approaches, such as the iterative inverse modeling method employed in this study, which is capable of dealing with strongly nonlinear problems. A series of numerical case studies with increasing complexity are set up to examine the performance of the proposed approach.
Informativeness of Wind Data in Linear Madden-Julian Oscillation Prediction
2016-08-15
Linear inverse models (LIMs) are used to explore predictability and information content of the Madden–Julian Oscillation (MJO). Hindcast skill for...mostly at the largest scales, adds 1–2 days of skill. Keywords: linear inverse modeling; Madden–Julian Oscillation; sub-seasonal prediction 1...tion that may reflect on the MJO’s incompletely under- stood dynamics. Cavanaugh et al. (2014, hereafter C14) explored the skill of linear inverse
An inverse dynamics approach to face animation.
Pitermann, M; Munhall, K G
2001-09-01
Muscle-based models of the human face produce high quality animation but rely on recorded muscle activity signals or synthetic muscle signals that are often derived by trial and error. This paper presents a dynamic inversion of a muscle-based model (Lucero and Munhall, 1999) that permits the animation to be created from kinematic recordings of facial movements. Using a nonlinear optimizer (Powell's algorithm), the inversion produces a muscle activity set for seven muscles in the lower face that minimize the root mean square error between kinematic data recorded with OPTOTRAK and the corresponding nodes of the modeled facial mesh. This inverted muscle activity is then used to animate the facial model. In three tests of the inversion, strong correlations were observed for kinematics produced from synthetic muscle activity, for OPTOTRAK kinematics recorded from a talker for whom the facial model is morphologically adapted and finally for another talker with the model morphology adapted to a different individual. The correspondence between the animation kinematics and the three-dimensional OPTOTRAK data are very good and the animation is of high quality. Because the kinematic to electromyography (EMG) inversion is ill posed, there is no relation between the actual EMG and the inverted EMG. The overall redundancy of the motor system means that many different EMG patterns can produce the same kinematic output.
Hybrid Adaptive Flight Control with Model Inversion Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2011-01-01
This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.
Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim
Modenese, L.; Lloyd, D.G.
2017-01-01
Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time. PMID:27723992
Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim.
Pizzolato, C; Reggiani, M; Modenese, L; Lloyd, D G
2017-03-01
Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.
Inferior olive mirrors joint dynamics to implement an inverse controller.
Alvarez-Icaza, Rodrigo; Boahen, Kwabena
2012-10-01
To produce smooth and coordinated motion, our nervous systems need to generate precisely timed muscle activation patterns that, due to axonal conduction delay, must be generated in a predictive and feedforward manner. Kawato proposed that the cerebellum accomplishes this by acting as an inverse controller that modulates descending motor commands to predictively drive the spinal cord such that the musculoskeletal dynamics are canceled out. This and other cerebellar theories do not, however, account for the rich biophysical properties expressed by the olivocerebellar complex's various cell types, making these theories difficult to verify experimentally. Here we propose that a multizonal microcomplex's (MZMC) inferior olivary neurons use their subthreshold oscillations to mirror a musculoskeletal joint's underdamped dynamics, thereby achieving inverse control. We used control theory to map a joint's inverse model onto an MZMC's biophysics, and we used biophysical modeling to confirm that inferior olivary neurons can express the dynamics required to mirror biomechanical joints. We then combined both techniques to predict how experimentally injecting current into the inferior olive would affect overall motor output performance. We found that this experimental manipulation unmasked a joint's natural dynamics, as observed by motor output ringing at the joint's natural frequency, with amplitude proportional to the amount of current. These results support the proposal that the cerebellum-in particular an MZMC-is an inverse controller; the results also provide a biophysical implementation for this controller and allow one to make an experimentally testable prediction.
Li, YuHui; Jin, FeiTeng
2017-01-01
The inversion design approach is a very useful tool for the complex multiple-input-multiple-output nonlinear systems to implement the decoupling control goal, such as the airplane model and spacecraft model. In this work, the flight control law is proposed using the neural-based inversion design method associated with the nonlinear compensation for a general longitudinal model of the airplane. First, the nonlinear mathematic model is converted to the equivalent linear model based on the feedback linearization theory. Then, the flight control law integrated with this inversion model is developed to stabilize the nonlinear system and relieve the coupling effect. Afterwards, the inversion control combined with the neural network and nonlinear portion is presented to improve the transient performance and attenuate the uncertain effects on both external disturbances and model errors. Finally, the simulation results demonstrate the effectiveness of this controller. PMID:29410680
Movement Characteristics Analysis and Dynamic Simulation of Collaborative Measuring Robot
NASA Astrophysics Data System (ADS)
guoqing, MA; li, LIU; zhenglin, YU; guohua, CAO; yanbin, ZHENG
2017-03-01
Human-machine collaboration is becoming increasingly more necessary, and so collaborative robot applications are also in high demand. We selected a UR10 robot as our research subject for this study. First, we applied D-H coordinate transformation of the robot to establish a link system, and we then used inverse transformation to solve the robot’s inverse kinematics and find all the joints. Use Lagrange method to analysis UR robot dynamics; use ADAMS multibody dynamics simulation software to dynamic simulation; verifying the correctness of the derived kinetic models.
NASA Astrophysics Data System (ADS)
Monnier, J.; Couderc, F.; Dartus, D.; Larnier, K.; Madec, R.; Vila, J.-P.
2016-11-01
The 2D shallow water equations adequately model some geophysical flows with wet-dry fronts (e.g. flood plain or tidal flows); nevertheless deriving accurate, robust and conservative numerical schemes for dynamic wet-dry fronts over complex topographies remains a challenge. Furthermore for these flows, data are generally complex, multi-scale and uncertain. Robust variational inverse algorithms, providing sensitivity maps and data assimilation processes may contribute to breakthrough shallow wet-dry front dynamics modelling. The present study aims at deriving an accurate, positive and stable finite volume scheme in presence of dynamic wet-dry fronts, and some corresponding inverse computational algorithms (variational approach). The schemes and algorithms are assessed on classical and original benchmarks plus a real flood plain test case (Lèze river, France). Original sensitivity maps with respect to the (friction, topography) pair are performed and discussed. The identification of inflow discharges (time series) or friction coefficients (spatially distributed parameters) demonstrate the algorithms efficiency.
Is chemical heating a major cause of the mesosphere inversion layer?
NASA Technical Reports Server (NTRS)
Meriwether, John W.; Mlynczak, Martin G.
1995-01-01
A region of thermal enhancement of the mesosphere has been detected on numerous occasions by in situ measurements, remote sensing from space, and lidar techniques. The source of these 'temperature inversion layers' has been attributed in the literature to the dissipation relating to dynamical forcing by gravity wave or tidal activity. However, evidence that gravity wave breaking can produce the inversion layer with amplitude as large as that observed in lidar measurements has been limited to results of numerical modeling. An alternative source for the production of the thermal inversion layer in the mesosphere is the direct deposition of heat by exothermic chemical reactions. Two-dimensional modeling combining a comprehensive model of the mesosphere photochemistry with the dynamical transport of long-lived species shows that the region from 80 to 95 km may be heated as much as 3 to 10 K/d during the night and half this rate during the day. Given the uncertainties in our understanding of the dynamics and chemistry for the mesopause region, separating the two sources by passive observations of the mesosphere thermal structure looks to be difficult. Therefore we have considered an active means for producing a mesopause thermal layer, namely the release of ozone into the upper mesosphere from a rocket payload. The induced effects would include artificial enhancements of the OH and Na airglow intensities as well as the mesopause thermal structure. The advantages of the rocket release of ozone is that detection of these effects by ground-based imaging, radar, and lidar systems and comparison of these effects with model predictions would help quantify the partition of the artificial inversion layer production into sources of dynamical and chemical forcing.
A mesostate-space model for EEG and MEG.
Daunizeau, Jean; Friston, Karl J
2007-10-15
We present a multi-scale generative model for EEG, that entails a minimum number of assumptions about evoked brain responses, namely: (1) bioelectric activity is generated by a set of distributed sources, (2) the dynamics of these sources can be modelled as random fluctuations about a small number of mesostates, (3) mesostates evolve in a temporal structured way and are functionally connected (i.e. influence each other), and (4) the number of mesostates engaged by a cognitive task is small (e.g. between one and a few). A Variational Bayesian learning scheme is described that furnishes the posterior density on the models parameters and its evidence. Since the number of meso-sources specifies the model, the model evidence can be used to compare models and find the optimum number of meso-sources. In addition to estimating the dynamics at each cortical dipole, the mesostate-space model and its inversion provide a description of brain activity at the level of the mesostates (i.e. in terms of the dynamics of meso-sources that are distributed over dipoles). The inclusion of a mesostate level allows one to compute posterior probability maps of each dipole being active (i.e. belonging to an active mesostate). Critically, this model accommodates constraints on the number of meso-sources, while retaining the flexibility of distributed source models in explaining data. In short, it bridges the gap between standard distributed and equivalent current dipole models. Furthermore, because it is explicitly spatiotemporal, the model can embed any stochastic dynamical causal model (e.g. a neural mass model) as a Markov process prior on the mesostate dynamics. The approach is evaluated and compared to standard inverse EEG techniques, using synthetic data and real data. The results demonstrate the added-value of the mesostate-space model and its variational inversion.
NASA Astrophysics Data System (ADS)
Ryzhikov, I. S.; Semenkin, E. S.
2017-02-01
This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.
Inverse Modelling to Obtain Head Movement Controller Signal
NASA Technical Reports Server (NTRS)
Kim, W. S.; Lee, S. H.; Hannaford, B.; Stark, L.
1984-01-01
Experimentally obtained dynamics of time-optimal, horizontal head rotations have previously been simulated by a sixth order, nonlinear model driven by rectangular control signals. Electromyography (EMG) recordings have spects which differ in detail from the theoretical rectangular pulsed control signal. Control signals for time-optimal as well as sub-optimal horizontal head rotations were obtained by means of an inverse modelling procedures. With experimentally measured dynamical data serving as the input, this procedure inverts the model to produce the neurological control signals driving muscles and plant. The relationships between these controller signals, and EMG records should contribute to the understanding of the neurological control of movements.
Biomechanical Comparison of 3 Ankle Braces With and Without Free Rotation in the Sagittal Plane
Alfuth, Martin; Klein, Dieter; Koch, Raphael; Rosenbaum, Dieter
2014-01-01
Context: Various designs of braces including hinged and nonhinged models are used to provide external support of the ankle. Hinged ankle braces supposedly allow almost free dorsiflexion and plantar flexion of the foot in the sagittal plane. It is unclear, however, whether this additional degree of freedom affects the stabilizing effect of the brace in the other planes of motion. Objective: To investigate the dynamic and passive stabilizing effects of 3 ankle braces, 2 hinged models that provide free plantar flexion–dorsiflexion in the sagittal plane and 1 ankle brace without a hinge. Design: Crossover study. Setting: University Movement Analysis Laboratory. Patients or Other Participants: Seventeen healthy volunteers (5 women, 12 men; age = 25.4 ± 4.8 years; height = 180.3 ± 6.5 cm; body mass = 75.5 ± 10.4 kg). Intervention(s): We dynamically induced foot inversion on a tilting platform and passively induced foot movements in 6 directions via a custom-built apparatus in 3 brace conditions and a control condition (no brace). Main Outcome Measure(s): Maximum inversion was determined dynamically using an in-shoe electrogoniometer. Passively induced maximal joint angles were measured using a torque and angle sensor. We analyzed differences among the 4 ankle-brace conditions (3 braces, 1 control) for each of the dependent variables with Friedman and post hoc tests (P < .05). Results: Each ankle brace restricted dynamic foot-inversion movements on the tilting platform as compared with the control condition, whereas only the 2 hinged ankle braces differed from each other, with greater movement restriction caused by the Ankle X model. Passive foot inversion was reduced with all ankle braces. Passive plantar flexion was greater in the hinged models as compared with the nonhinged brace. Conclusions: All ankle braces showed stabilizing effects against dynamic and passive foot inversion. Differences between the hinged braces and the nonhinged brace did not appear to be clinically relevant. PMID:25098661
An Inverse Problem for a Class of Conditional Probability Measure-Dependent Evolution Equations
Mirzaev, Inom; Byrne, Erin C.; Bortz, David M.
2016-01-01
We investigate the inverse problem of identifying a conditional probability measure in measure-dependent evolution equations arising in size-structured population modeling. We formulate the inverse problem as a least squares problem for the probability measure estimation. Using the Prohorov metric framework, we prove existence and consistency of the least squares estimates and outline a discretization scheme for approximating a conditional probability measure. For this scheme, we prove general method stability. The work is motivated by Partial Differential Equation (PDE) models of flocculation for which the shape of the post-fragmentation conditional probability measure greatly impacts the solution dynamics. To illustrate our methodology, we apply the theory to a particular PDE model that arises in the study of population dynamics for flocculating bacterial aggregates in suspension, and provide numerical evidence for the utility of the approach. PMID:28316360
Application of neural models as controllers in mobile robot velocity control loop
NASA Astrophysics Data System (ADS)
Cerkala, Jakub; Jadlovska, Anna
2017-01-01
This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.
Sivaramakrishnan, Shyam; Rajamani, Rajesh; Johnson, Bruce D
2009-01-01
Respiratory CO(2) measurement (capnography) is an important diagnosis tool that lacks inexpensive and wearable sensors. This paper develops techniques to enable use of inexpensive but slow CO(2) sensors for breath-by-breath tracking of CO(2) concentration. This is achieved by mathematically modeling the dynamic response and using model-inversion techniques to predict input CO(2) concentration from the slow-varying output. Experiments are designed to identify model-dynamics and extract relevant model-parameters for a solidstate room monitoring CO(2) sensor. A second-order model that accounts for flow through the sensor's filter and casing is found to be accurate in describing the sensor's slow response. The resulting estimate is compared with a standard-of-care respiratory CO(2) analyzer and shown to effectively track variation in breath-by-breath CO(2) concentration. This methodology is potentially useful for measuring fast-varying inputs to any slow sensor.
System Identification for Nonlinear Control Using Neural Networks
NASA Technical Reports Server (NTRS)
Stengel, Robert F.; Linse, Dennis J.
1990-01-01
An approach to incorporating artificial neural networks in nonlinear, adaptive control systems is described. The controller contains three principal elements: a nonlinear inverse dynamic control law whose coefficients depend on a comprehensive model of the plant, a neural network that models system dynamics, and a state estimator whose outputs drive the control law and train the neural network. Attention is focused on the system identification task, which combines an extended Kalman filter with generalized spline function approximation. Continual learning is possible during normal operation, without taking the system off line for specialized training. Nonlinear inverse dynamic control requires smooth derivatives as well as function estimates, imposing stringent goals on the approximating technique.
Inverse Dynamics Model for the Ankle Joint with Applications in Tibia Malleolus Fracture
NASA Astrophysics Data System (ADS)
Budescu, E.; Merticaru, E.; Chirazi, M.
The paper presents a biomechanical model of the ankle joint, in order to determine the force and the torque of reaction into the articulation, through inverse dynamic analysis, in various stages of the gait. Thus, knowing the acceleration of the foot and the reaction force between foot and ground during the gait, determined by experimental measurement, there was calculated, for five different positions of the foot, the joint reaction forces, on the basis of dynamic balance equations. The values numerically determined were compared with the admissible forces appearing in the technical systems of osteosynthesis of tibia malleolus fracture, in order to emphasize the motion restrictions during bone healing.
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.
Upper limb joint forces and moments during underwater cyclical movements.
Lauer, Jessy; Rouard, Annie Hélène; Vilas-Boas, João Paulo
2016-10-03
Sound inverse dynamics modeling is lacking in aquatic locomotion research because of the difficulty in measuring hydrodynamic forces in dynamic conditions. Here we report the successful implementation and validation of an innovative methodology crossing new computational fluid dynamics and inverse dynamics techniques to quantify upper limb joint forces and moments while moving in water. Upper limb kinematics of seven male swimmers sculling while ballasted with 4kg was recorded through underwater motion capture. Together with body scans, segment inertial properties, and hydrodynamic resistances computed from a unique dynamic mesh algorithm capable to handle large body deformations, these data were fed into an inverse dynamics model to solve for joint kinetics. Simulation validity was assessed by comparing the impulse produced by the arms, calculated by integrating vertical forces over a stroke period, to the net theoretical impulse of buoyancy and ballast forces. A resulting gap of 1.2±3.5% provided confidence in the results. Upper limb joint load was within 5% of swimmer׳s body weight, which tends to supports the use of low-load aquatic exercises to reduce joint stress. We expect this significant methodological improvement to pave the way towards deeper insights into the mechanics of aquatic movement and the establishment of practice guidelines in rehabilitation, fitness or swimming performance. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Tran, A. P.; Dafflon, B.; Hubbard, S.
2017-12-01
Soil organic carbon (SOC) is crucial for predicting carbon climate feedbacks in the vulnerable organic-rich Arctic region. However, it is challenging to achieve this property due to the general limitations of conventional core sampling and analysis methods. In this study, we develop an inversion scheme that uses single or multiple datasets, including soil liquid water content, temperature and ERT data, to estimate the vertical profile of SOC content. Our approach relies on the fact that SOC content strongly influences soil hydrological-thermal parameters, and therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. The scheme includes several advantages. First, this is the first time SOC content is estimated by using a coupled hydrogeophysical inversion. Second, by using the Community Land Model, we can account for the land surface dynamics (evapotranspiration, snow accumulation and melting) and ice/liquid phase transition. Third, we combine a deterministic and an adaptive Markov chain Monte Carlo optimization algorithm to better estimate the posterior distributions of desired model parameters. Finally, the simulated subsurface variables are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using synthetic experiments. The results show that compared to inversion of single dataset, joint inversion of these datasets significantly reduces parameter uncertainty. The joint inversion approach is able to estimate SOC content within the shallow active layer with high reliability. Next, we apply the scheme to estimate OC content along an intensive ERT transect in Barrow, Alaska using multiple datasets acquired in the 2013-2015 period. The preliminary results show a good agreement between modeled and measured soil temperature, thaw layer thickness and electrical resistivity. The accuracy of estimated SOC content will be evaluated by comparison with measurements from soil samples along the transect. Our study presents a new surface-subsurface, deterministic-stochastic hydrogeophysical inversion approach, as well as the benefit of including multiple types of data to estimate SOC and associated hydrological-thermal dynamics.
Stability analysis of an implicitly defined labor market model
NASA Astrophysics Data System (ADS)
Mendes, Diana A.; Mendes, Vivaldo M.
2008-06-01
Until very recently, the pervasive existence of models exhibiting well-defined backward dynamics but ill-defined forward dynamics in economics and finance has apparently posed no serious obstacles to the analysis of their dynamics and stability, despite the problems that may arise from possible erroneous conclusions regarding theoretical considerations and policy prescriptions from such models. A large number of papers have dealt with this problem in the past by assuming the existence of symmetry between forward and backward dynamics, even in the case when the map cannot be invertible either forward or backwards. However, this procedure has been seriously questioned over the last few years in a series of papers dealing with implicit difference equations and inverse limit spaces. This paper explores the search and matching labor market model developed by Bhattacharya and Bunzel [J. Bhattacharya, H. Bunzel, Chaotic Planning Solution in the Textbook Model of Equilibrium Labor Market Search and Matching, Mimeo, Iowa State University, 2002; J. Bhattacharya, H. Bunzel, Economics Bulletin 5 (19) (2003) 1-10], with the following objectives in mind: (i) to show that chaotic dynamics may still be present in the model for acceptable parameter values, (ii) to clarify some open questions related with the admissible dynamics in the forward looking setting, by providing a rigorous proof of the existence of cyclic and chaotic dynamics through the application of tools from symbolic dynamics and inverse limit theory.
Earthquake Source Inversion Blindtest: Initial Results and Further Developments
NASA Astrophysics Data System (ADS)
Mai, P.; Burjanek, J.; Delouis, B.; Festa, G.; Francois-Holden, C.; Monelli, D.; Uchide, T.; Zahradnik, J.
2007-12-01
Images of earthquake ruptures, obtained from modelling/inverting seismic and/or geodetic data exhibit a high degree in spatial complexity. This earthquake source heterogeneity controls seismic radiation, and is determined by the details of the dynamic rupture process. In turn, such rupture models are used for studying source dynamics and for ground-motion prediction. But how reliable and trustworthy are these earthquake source inversions? Rupture models for a given earthquake, obtained by different research teams, often display striking disparities (see http://www.seismo.ethz.ch/srcmod) However, well resolved, robust, and hence reliable source-rupture models are an integral part to better understand earthquake source physics and to improve seismic hazard assessment. Therefore it is timely to conduct a large-scale validation exercise for comparing the methods, parameterization and data-handling in earthquake source inversions.We recently started a blind test in which several research groups derive a kinematic rupture model from synthetic seismograms calculated for an input model unknown to the source modelers. The first results, for an input rupture model with heterogeneous slip but constant rise time and rupture velocity, reveal large differences between the input and inverted model in some cases, while a few studies achieve high correlation between the input and inferred model. Here we report on the statistical assessment of the set of inverted rupture models to quantitatively investigate their degree of (dis-)similarity. We briefly discuss the different inversion approaches, their possible strength and weaknesses, and the use of appropriate misfit criteria. Finally we present new blind-test models, with increasing source complexity and ambient noise on the synthetics. The goal is to attract a large group of source modelers to join this source-inversion blindtest in order to conduct a large-scale validation exercise to rigorously asses the performance and reliability of current inversion methods and to discuss future developments.
NASA Astrophysics Data System (ADS)
Phuong Tran, Anh; Dafflon, Baptiste; Hubbard, Susan S.
2017-09-01
Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface-subsurface hydrological-thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon-climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological-thermal processes associated with annual freeze-thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets - including soil liquid water content, temperature and electrical resistivity tomography (ERT) data - to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological-thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface-subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice-liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological-thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological-thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface-subsurface, deterministic-stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological-thermal dynamics.
The Lanchester square-law model extended to a (2,2) conflict
NASA Astrophysics Data System (ADS)
Colegrave, R. K.; Hyde, J. M.
1993-01-01
A natural extension of the Lanchester (1,1) square-law model is the (M,N) linear model in which M forces oppose N forces with constant attrition rates. The (2,2) model is treated from both direct and inverse viewpoints. The inverse problem means that the model is to be fitted to a minimum number of observed force levels, i.e. the attrition rates are to be found from the initial force levels together with the levels observed at two subsequent times. An approach based on Hamiltonian dynamics has enabled the authors to derive a procedure for solving the inverse problem, which is readily computerized. Conflicts in which participants unexpectedly rally or weaken must be excluded.
Reduction of Dynamic Loads in Mine Lifting Installations
NASA Astrophysics Data System (ADS)
Kuznetsov, N. K.; Eliseev, S. V.; Perelygina, A. Yu
2018-01-01
Article is devoted to a problem of decrease in the dynamic loadings arising in transitional operating modes of the mine lifting installations leading to heavy oscillating motions of lifting vessels and decrease in efficiency and reliability of work. The known methods and means of decrease in dynamic loadings and oscillating motions of the similar equipment are analysed. It is shown that an approach based on the concept of the inverse problems of dynamics can be effective method of the solution of this problem. The article describes the design model of a one-ended lifting installation in the form of a two-mass oscillation system, in which the inertial elements are the mass of the lifting vessel and the reduced mass of the engine, reducer, drum and pulley. The simplified mathematical model of this system and results of an efficiency research of an active way of reduction of dynamic loadings of lifting installation on the basis of the concept of the inverse problems of dynamics are given.
Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals.
Liu, X; Zhai, Z
2007-12-01
Reduction in indoor environment quality calls for effective control and improvement measures. Accurate and prompt identification of contaminant sources ensures that they can be quickly removed and contaminated spaces isolated and cleaned. This paper discusses the use of inverse modeling to identify potential indoor pollutant sources with limited pollutant sensor data. The study reviews various inverse modeling methods for advection-dispersion problems and summarizes the methods into three major categories: forward, backward, and probability inverse modeling methods. The adjoint probability inverse modeling method is indicated as an appropriate model for indoor air pollutant tracking because it can quickly find source location, strength and release time without prior information. The paper introduces the principles of the adjoint probability method and establishes the corresponding adjoint equations for both multi-zone airflow models and computational fluid dynamics (CFD) models. The study proposes a two-stage inverse modeling approach integrating both multi-zone and CFD models, which can provide a rapid estimate of indoor pollution status and history for a whole building. Preliminary case study results indicate that the adjoint probability method is feasible for indoor pollutant inverse modeling. The proposed method can help identify contaminant source characteristics (location and release time) with limited sensor outputs. This will ensure an effective and prompt execution of building management strategies and thus achieve a healthy and safe indoor environment. The method can also help design optimal sensor networks.
Inverse dynamics of a 3 degree of freedom spatial flexible manipulator
NASA Technical Reports Server (NTRS)
Bayo, Eduardo; Serna, M.
1989-01-01
A technique is presented for solving the inverse dynamics and kinematics of 3 degree of freedom spatial flexible manipulator. The proposed method finds the joint torques necessary to produce a specified end effector motion. Since the inverse dynamic problem in elastic manipulators is closely coupled to the inverse kinematic problem, the solution of the first also renders the displacements and rotations at any point of the manipulator, including the joints. Furthermore the formulation is complete in the sense that it includes all the nonlinear terms due to the large rotation of the links. The Timoshenko beam theory is used to model the elastic characteristics, and the resulting equations of motion are discretized using the finite element method. An iterative solution scheme is proposed that relies on local linearization of the problem. The solution of each linearization is carried out in the frequency domain. The performance and capabilities of this technique are tested through simulation analysis. Results show the potential use of this method for the smooth motion control of space telerobots.
NASA Astrophysics Data System (ADS)
Liang, Yingjie; Chen, Wen
2018-04-01
The mean squared displacement (MSD) of the traditional ultraslow diffusion is a logarithmic function of time. Recently, the continuous time random walk model is employed to characterize this ultraslow diffusion dynamics by connecting the heavy-tailed logarithmic function and its variation as the asymptotical waiting time density. In this study we investigate the limiting waiting time density of a general ultraslow diffusion model via the inverse Mittag-Leffler function, whose special case includes the traditional logarithmic ultraslow diffusion model. The MSD of the general ultraslow diffusion model is analytically derived as an inverse Mittag-Leffler function, and is observed to increase even more slowly than that of the logarithmic function model. The occurrence of very long waiting time in the case of the inverse Mittag-Leffler function has the largest probability compared with the power law model and the logarithmic function model. The Monte Carlo simulations of one dimensional sample path of a single particle are also performed. The results show that the inverse Mittag-Leffler waiting time density is effective in depicting the general ultraslow random motion.
NASA Astrophysics Data System (ADS)
Rittgers, J. B.; Revil, A.; Mooney, M. A.; Karaoulis, M.; Wodajo, L.; Hickey, C. J.
2016-12-01
Joint inversion and time-lapse inversion techniques of geophysical data are often implemented in an attempt to improve imaging of complex subsurface structures and dynamic processes by minimizing negative effects of random and uncorrelated spatial and temporal noise in the data. We focus on the structural cross-gradient (SCG) approach (enforcing recovered models to exhibit similar spatial structures) in combination with time-lapse inversion constraints applied to surface-based electrical resistivity and seismic traveltime refraction data. The combination of both techniques is justified by the underlying petrophysical models. We investigate the benefits and trade-offs of SCG and time-lapse constraints. Using a synthetic case study, we show that a combined joint time-lapse inversion approach provides an overall improvement in final recovered models. Additionally, we introduce a new approach to reweighting SCG constraints based on an iteratively updated normalized ratio of model sensitivity distributions at each time-step. We refer to the new technique as the Automatic Joint Constraints (AJC) approach. The relevance of the new joint time-lapse inversion process is demonstrated on the synthetic example. Then, these approaches are applied to real time-lapse monitoring field data collected during a quarter-scale earthen embankment induced-piping failure test. The use of time-lapse joint inversion is justified by the fact that a change of porosity drives concomitant changes in seismic velocities (through its effect on the bulk and shear moduli) and resistivities (through its influence upon the formation factor). Combined with the definition of attributes (i.e. specific characteristics) of the evolving target associated with piping, our approach allows localizing the position of the preferential flow path associated with internal erosion. This is not the case using other approaches.
Inferring Fault Frictional and Reservoir Hydraulic Properties From Injection-Induced Seismicity
NASA Astrophysics Data System (ADS)
Jagalur-Mohan, Jayanth; Jha, Birendra; Wang, Zheng; Juanes, Ruben; Marzouk, Youssef
2018-02-01
Characterizing the rheological properties of faults and the evolution of fault friction during seismic slip are fundamental problems in geology and seismology. Recent increases in the frequency of induced earthquakes have intensified the need for robust methods to estimate fault properties. Here we present a novel approach for estimation of aquifer and fault properties, which combines coupled multiphysics simulation of injection-induced seismicity with adaptive surrogate-based Bayesian inversion. In a synthetic 2-D model, we use aquifer pressure, ground displacements, and fault slip measurements during fluid injection to estimate the dynamic fault friction, the critical slip distance, and the aquifer permeability. Our forward model allows us to observe nonmonotonic evolutions of shear traction and slip on the fault resulting from the interplay of several physical mechanisms, including injection-induced aquifer expansion, stress transfer along the fault, and slip-induced stress relaxation. This interplay provides the basis for a successful joint inversion of induced seismicity, yielding well-informed Bayesian posterior distributions of dynamic friction and critical slip. We uncover an inverse relationship between dynamic friction and critical slip distance, which is in agreement with the small dynamic friction and large critical slip reported during seismicity on mature faults.
NASA Astrophysics Data System (ADS)
Petersen, Ø. W.; Øiseth, O.; Nord, T. S.; Lourens, E.
2018-07-01
Numerical predictions of the dynamic response of complex structures are often uncertain due to uncertainties inherited from the assumed load effects. Inverse methods can estimate the true dynamic response of a structure through system inversion, combining measured acceleration data with a system model. This article presents a case study of full-field dynamic response estimation of a long-span floating bridge: the Bergøysund Bridge in Norway. This bridge is instrumented with a network of 14 triaxial accelerometers. The system model consists of 27 vibration modes with natural frequencies below 2 Hz, obtained from a tuned finite element model that takes the fluid-structure interaction with the surrounding water into account. Two methods, a joint input-state estimation algorithm and a dual Kalman filter, are applied to estimate the full-field response of the bridge. The results demonstrate that the displacements and the accelerations can be estimated at unmeasured locations with reasonable accuracy when the wave loads are the dominant source of excitation.
NASA Astrophysics Data System (ADS)
Yamada, M.; Mangeney, A.; Moretti, L.; Matsushi, Y.
2014-12-01
Understanding physical parameters, such as frictional coefficients, velocity change, and dynamic history, is important issue for assessing and managing the risks posed by deep-seated catastrophic landslides. Previously, landslide motion has been inferred qualitatively from topographic changes caused by the event, and occasionally from eyewitness reports. However, these conventional approaches are unable to evaluate source processes and dynamic parameters. In this study, we use broadband seismic recordings to trace the dynamic process of the deep-seated Akatani landslide that occurred on the Kii Peninsula, Japan, which is one of the best recorded large slope failures. Based on the previous results of waveform inversions and precise topographic surveys done before and after the event, we applied numerical simulations using the SHALTOP numerical model (Mangeney et al., 2007). This model describes homogeneous continuous granular flows on a 3D topography based on a depth averaged thin layer approximation. We assume a Coulomb's friction law with a constant friction coefficient, i. e. the friction is independent of the sliding velocity. We varied the friction coefficients in the simulation so that the resulting force acting on the surface agrees with the single force estimated from the seismic waveform inversion. Figure shows the force history of the east-west components after the band-pass filtering between 10-100 seconds. The force history of the simulation with frictional coefficient 0.27 (thin red line) the best agrees with the result of seismic waveform inversion (thick gray line). Although the amplitude is slightly different, phases are coherent for the main three pulses. This is an evidence that the point-source approximation works reasonably well for this particular event. The friction coefficient during the sliding was estimated to be 0.38 based on the seismic waveform inversion performed by the previous study and on the sliding block model (Yamada et al., 2013), whereas the frictional coefficient estimated from the numerical simulation was about 0.27. This discrepancy may be due to the digital elevation model, to the other forces such as pressure gradients and centrifugal acceleration included in the model. However, quantitative interpretation of this difference requires further investigation.
Spatial operator approach to flexible multibody system dynamics and control
NASA Technical Reports Server (NTRS)
Rodriguez, G.
1991-01-01
The inverse and forward dynamics problems for flexible multibody systems were solved using the techniques of spatially recursive Kalman filtering and smoothing. These algorithms are easily developed using a set of identities associated with mass matrix factorization and inversion. These identities are easily derived using the spatial operator algebra developed by the author. Current work is aimed at computational experiments with the described algorithms and at modelling for control design of limber manipulator systems. It is also aimed at handling and manipulation of flexible objects.
Inverse Force Determination on a Small Scale Launch Vehicle Model Using a Dynamic Balance
NASA Technical Reports Server (NTRS)
Ngo, Christina L.; Powell, Jessica M.; Ross, James C.
2017-01-01
A launch vehicle can experience large unsteady aerodynamic forces in the transonic regime that, while usually only lasting for tens of seconds during launch, could be devastating if structural components and electronic hardware are not designed to account for them. These aerodynamic loads are difficult to experimentally measure and even harder to computationally estimate. The current method for estimating buffet loads is through the use of a few hundred unsteady pressure transducers and wind tunnel test. Even with a large number of point measurements, the computed integrated load is not an accurate enough representation of the total load caused by buffeting. This paper discusses an attempt at using a dynamic balance to experimentally determine buffet loads on a generic scale hammer head launch vehicle model tested at NASA Ames Research Center's 11' x 11' transonic wind tunnel. To use a dynamic balance, the structural characteristics of the model needed to be identified so that the natural modal response could be and removed from the aerodynamic forces. A finite element model was created on a simplified version of the model to evaluate the natural modes of the balance flexures, assist in model design, and to compare to experimental data. Several modal tests were conducted on the model in two different configurations to check for non-linearity, and to estimate the dynamic characteristics of the model. The experimental results were used in an inverse force determination technique with a psuedo inverse frequency response function. Due to the non linearity, the model not being axisymmetric, and inconsistent data between the two shake tests from different mounting configuration, it was difficult to create a frequency response matrix that satisfied all input and output conditions for wind tunnel configuration to accurately predict unsteady aerodynamic loads.
NASA Technical Reports Server (NTRS)
Smith, G. A.; Meyer, G.
1981-01-01
A full envelope automatic flight control system based on nonlinear inverse systems concepts has been applied to a vertical attitude takeoff and landing (VATOL) fighter aircraft. A new method for using an airborne digital aircraft model to perform the inversion of a nonlinear aircraft model is presented together with the results of a simulation study of the nonlinear inverse system concept for the vertical-attitude hover mode. The system response to maneuver commands in the vertical attitude was found to be excellent; and recovery from large initial offsets and large disturbances was found to be very satisfactory.
Regularity Aspects in Inverse Musculoskeletal Biomechanics
NASA Astrophysics Data System (ADS)
Lund, Marie; Stâhl, Fredrik; Gulliksson, Mârten
2008-09-01
Inverse simulations of musculoskeletal models computes the internal forces such as muscle and joint reaction forces, which are hard to measure, using the more easily measured motion and external forces as input data. Because of the difficulties of measuring muscle forces and joint reactions, simulations are hard to validate. One way of reducing errors for the simulations is to ensure that the mathematical problem is well-posed. This paper presents a study of regularity aspects for an inverse simulation method, often called forward dynamics or dynamical optimization, that takes into account both measurement errors and muscle dynamics. Regularity is examined for a test problem around the optimum using the approximated quadratic problem. The results shows improved rank by including a regularization term in the objective that handles the mechanical over-determinancy. Using the 3-element Hill muscle model the chosen regularization term is the norm of the activation. To make the problem full-rank only the excitation bounds should be included in the constraints. However, this results in small negative values of the activation which indicates that muscles are pushing and not pulling, which is unrealistic but the error maybe small enough to be accepted for specific applications. These results are a start to ensure better results of inverse musculoskeletal simulations from a numerical point of view.
Inference of effective river properties from remotely sensed observations of water surface
NASA Astrophysics Data System (ADS)
Garambois, Pierre-André; Monnier, Jérôme
2015-05-01
The future SWOT mission (Surface Water and Ocean Topography) will provide cartographic measurements of inland water surfaces (elevation, widths and slope) at an unprecedented spatial and temporal resolution. Given synthetic SWOT like data, forward flow models of hierarchical-complexity are revisited and few inverse formulations are derived and assessed for retrieving the river low flow bathymetry, roughness and discharge (A0, K, Q) . The concept of an effective low flow bathymetry A0 (the real one being never observed) and roughness K , hence an effective river dynamics description, is introduced. The few inverse models elaborated for inferring (A0, K, Q) are analyzed in two contexts: (1) only remotely sensed observations of the water surface (surface elevation, width and slope) are available; (2) one additional water depth measurement (or estimate) is available. The inverse models elaborated are independent of data acquisition dynamics; they are assessed on 91 synthetic test cases sampling a wide range of steady-state river flows (the Froude number varying between 0.05 and 0.5 for 1 km reaches) and in the case of a flood on the Garonne River (France) characterized by large spatio-temporal variabilities. It is demonstrated that the most complete shallow-water like model allowing to separate the roughness and bathymetry terms is the so-called low Froude model. In Case (1), the resulting RMSE on infered discharges are on the order of 15% for first guess errors larger than 50%. An important feature of the present inverse methods is the fairly good accuracy of the discharge Q obtained, while the identified roughness coefficient K includes the measurement errors and the misfit of physics between the real flow and the hypothesis on which the inverse models rely; the later neglecting the unobserved temporal variations of the flow and the inertia effects. A compensation phenomena between the indentifiedvalues of K and the unobserved bathymetry A0 is highlighted, while the present inverse models lead to an effective river dynamics model that is accurate in the range of the discharge variability observed. In Case (2), the effective bathymetry profile for 80 km of the Garonne River is retrieved with 1% relative error only. Next, accurate effective topography-friction pairs and also discharge can be inferred. Finally, defining river reaches from the observation grid tends to average the river properties in each reach, hence tends to smooth the hydraulic variability.
NASA Astrophysics Data System (ADS)
De Matteo, Ada; Massa, Bruno; D'Auria, Luca; Castaldo, Raffaele
2017-04-01
Geological processes are generally very complex and too slow to be directly observed in their completeness; modelling procedures overcome this limit. The state of stress in the upper lithosphere is the main responsible for driving geodynamical processes; in order to retrieve the active stress field in a rock volume, stress inversion techniques can be applied on both seismological and structural datasets. This approach has been successfully applied to active tectonics as well as volcanic areas. In this context the best approach in managing heterogeneous datasets in volcanic environments consists in the analysis of spatial variations of the stress field by applying robust techniques of inversion. The study of volcanic seismicity is an efficient tool to retrieve spatial and temporal pattern of the pre-, syn- and inter-eruptive stress field: magma migration as well as dynamics of magma chamber and hydrothermal system are directly connected to the volcanic seismicity. Additionally, analysis of the temporal variations of stress field pattern in volcanoes could be a useful monitoring tool. Recently the stress field acting on several active volcanoes has been investigated by using stress inversion techniques on seismological datasets (Massa et al., 2016). The Bayesian Right Trihedra Method (BRTM; D'Auria and Massa, 2015) is able to successfully manage heterogeneous datasets allowing the identification of regional fields locally overcame by the stress field due to volcano specific dynamics. In particular, the analysis of seismicity and stress field inversion at the Somma-Vesuvius highlighted the presence of two superposed volumes characterized by different behaviour and stress field pattern: a top volume dominated by an extensional stress field, in accordance with a gravitational spreading-style of deformation, and a bottom volume related to a regional extensional stress field. In addition, in order to evaluate the dynamics of deformation, both analogue and numerical modelling are being performed. Scaled analogue models of the Somma-Vesuvius are being built accordingly with the actual geometrical asymmetry of the volcano, varying just few parameters connected to the uncertainty of the depth and thickness of a buried decoupling layer. Experiments are being monitored by an optical stereo image system, useful to build a 3D time-lapsed models used to retrieve the model deformations. Simultaneously, a time-dependent 3D Finite Element model is being carried out in a fluid-dynamic context by fixing the same parameters of the proposed analogue model. Finally, a comparative analysis is being made between the model deformations and the DInSAR measurements derived from satellite data in order to estimate the uncertain parameters (i.e., thickness and viscosity of ductile layer). Preliminary results of the analogue models fit with the hypothesis of a spreading deformation active at the Somma-Vesuvius.
Feasible Muscle Activation Ranges Based on Inverse Dynamics Analyses of Human Walking
Simpson, Cole S.; Sohn, M. Hongchul; Allen, Jessica L.; Ting, Lena H.
2015-01-01
Although it is possible to produce the same movement using an infinite number of different muscle activation patterns owing to musculoskeletal redundancy, the degree to which observed variations in muscle activity can deviate from optimal solutions computed from biomechanical models is not known. Here, we examined the range of biomechanically permitted activation levels in individual muscles during human walking using a detailed musculoskeletal model and experimentally-measured kinetics and kinematics. Feasible muscle activation ranges define the minimum and maximum possible level of each muscle’s activation that satisfy inverse dynamics joint torques assuming that all other muscles can vary their activation as needed. During walking, 73% of the muscles had feasible muscle activation ranges that were greater than 95% of the total muscle activation range over more than 95% of the gait cycle, indicating that, individually, most muscles could be fully active or fully inactive while still satisfying inverse dynamics joint torques. Moreover, the shapes of the feasible muscle activation ranges did not resemble previously-reported muscle activation patterns nor optimal solutions, i.e. static optimization and computed muscle control, that are based on the same biomechanical constraints. Our results demonstrate that joint torque requirements from standard inverse dynamics calculations are insufficient to define the activation of individual muscles during walking in healthy individuals. Identifying feasible muscle activation ranges may be an effective way to evaluate the impact of additional biomechanical and/or neural constraints on possible versus actual muscle activity in both normal and impaired movements. PMID:26300401
Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.
2017-09-06
Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological–thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon–climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological–thermal processes associated with annual freeze–thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets – including soil liquid watermore » content, temperature and electrical resistivity tomography (ERT) data – to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological–thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface–subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice–liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological–thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological–thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface–subsurface, deterministic–stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological–thermal dynamics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.
Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological–thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon–climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological–thermal processes associated with annual freeze–thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets – including soil liquid watermore » content, temperature and electrical resistivity tomography (ERT) data – to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological–thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface–subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice–liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological–thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological–thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface–subsurface, deterministic–stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological–thermal dynamics.« less
X-38 Experimental Controls Laws
NASA Technical Reports Server (NTRS)
Munday, Steve; Estes, Jay; Bordano, Aldo J.
2000-01-01
X-38 Experimental Control Laws X-38 is a NASA JSC/DFRC experimental flight test program developing a series of prototypes for an International Space Station (ISS) Crew Return Vehicle, often called an ISS "lifeboat." X- 38 Vehicle 132 Free Flight 3, currently scheduled for the end of this month, will be the first flight test of a modem FCS architecture called Multi-Application Control-Honeywell (MACH), originally developed by the Honeywell Technology Center. MACH wraps classical P&I outer attitude loops around a modem dynamic inversion attitude rate loop. The dynamic inversion process requires that the flight computer have an onboard aircraft model of expected vehicle dynamics based upon the aerodynamic database. Dynamic inversion is computationally intensive, so some timing modifications were made to implement MACH on the slower flight computers of the subsonic test vehicles. In addition to linear stability margin analyses and high fidelity 6-DOF simulation, hardware-in-the-loop testing is used to verify the implementation of MACH and its robustness to aerodynamic and environmental uncertainties and disturbances.
2014-09-23
conduct simulations with a high-latitude data assimilation model. The specific objectives are to study magnetosphere-ionosphere ( M -I) coupling processes...based on three physics-based models, including a magnetosphere-ionosphere ( M -I) electrodynamics model, an ionosphere model, and a magnetic...inversion code. The ionosphere model is a high-resolution version of the Ionosphere Forecast Model ( IFM ), which is a 3-D, multi-ion model of the ionosphere
NASA Astrophysics Data System (ADS)
Bunge, H.; Hagelberg, C.; Travis, B.
2002-12-01
EarthScope will deliver data on structure and dynamics of continental North America and the underlying mantle on an unprecedented scale. Indeed, the scope of EarthScope makes its mission comparable to the large remote sensing efforts that are transforming the oceanographic and atmospheric sciences today. Arguably the main impact of new solid Earth observing systems is to transform our use of geodynamic models increasingly from conditions that are data poor to an environment that is data rich. Oceanographers and meteorologists already have made substantial progress in adapting to this environment, by developing new approaches of interpreting oceanographic and atmospheric data objectively through data assimilation methods in their models. However, a similarly rigorous theoretical framework for merging EarthScope derived solid Earth data with geodynamic models has yet to be devised. Here we explore the feasibility of data assimilation in mantle convection studies in an attempt to fit global geodynamic model calculations explicitly to tomographic and tectonic constraints. This is an inverse problem not quite unlike the inverse problem of finding optimal seismic velocity structures faced by seismologists. We derive the generalized inverse of mantle convection from a variational approach and present the adjoint equations of mantle flow. The substantial computational burden associated with solutions to the generalized inverse problem of mantle convection is made feasible using a highly efficient finite element approach based on the 3-D spherical fully parallelized mantle dynamics code TERRA, implemented on a cost-effective topical PC-cluster (geowulf) dedicated specifically to large-scale geophysical simulations. This dedicated geophysical modeling computer allows us to investigate global inverse convection problems having a spatial discretization of less than 50 km throughout the mantle. We present a synthetic high-resolution modeling experiment to demonstrate that mid-Cretaceous mantle structure can be inferred accurately from our inverse approach assuming present-day mantle structure is well-known, even if an initial first guess assumption about the mid-Cretaceous mantle involved only a simple 1-D radial temperature profile. We suggest that geodynamic inverse modeling should make it possible to infer a number of flow parameters from observational constraints of the mantle.
Force and Moment Approach for Achievable Dynamics Using Nonlinear Dynamic Inversion
NASA Technical Reports Server (NTRS)
Ostroff, Aaron J.; Bacon, Barton J.
1999-01-01
This paper describes a general form of nonlinear dynamic inversion control for use in a generic nonlinear simulation to evaluate candidate augmented aircraft dynamics. The implementation is specifically tailored to the task of quickly assessing an aircraft's control power requirements and defining the achievable dynamic set. The achievable set is evaluated while undergoing complex mission maneuvers, and perfect tracking will be accomplished when the desired dynamics are achievable. Variables are extracted directly from the simulation model each iteration, so robustness is not an issue. Included in this paper is a description of the implementation of the forces and moments from simulation variables, the calculation of control effectiveness coefficients, methods for implementing different types of aerodynamic and thrust vectoring controls, adjustments for control effector failures, and the allocation approach used. A few examples illustrate the perfect tracking results obtained.
Estimating Soil and Root Parameters of Biofuel Crops using a Hydrogeophysical Inversion
NASA Astrophysics Data System (ADS)
Kuhl, A.; Kendall, A. D.; Van Dam, R. L.; Hyndman, D. W.
2017-12-01
Transpiration is the dominant pathway for continental water exchange to the atmosphere, and therefore a crucial aspect of modeling water balances at many scales. The root water uptake dynamics that control transpiration are dependent on soil water availability, as well as the root distribution. However, the root distribution is determined by many factors beyond the plant species alone, including climate conditions and soil texture. Despite the significant contribution of transpiration to global water fluxes, modelling the complex critical zone processes that drive root water uptake remains a challenge. Geophysical tools such as electrical resistivity (ER), have been shown to be highly sensitive to water dynamics in the unsaturated zone. ER data can be temporally and spatially robust, covering large areas or long time periods non-invasively, which is an advantage over in-situ methods. Previous studies have shown the value of using hydrogeophysical inversions to estimate soil properties. Others have used hydrological inversions to estimate both soil properties and root distribution parameters. In this study, we combine these two approaches to create a coupled hydrogeophysical inversion that estimates root and retention curve parameters for a HYDRUS model. To test the feasibility of this new approach, we estimated daily water fluxes and root growth for several biofuel crops at a long-term ecological research site in Southwest Michigan, using monthly ER data from 2009 through 2011. Time domain reflectometry data at seven depths was used to validate modeled soil moisture estimates throughout the model period. This hydrogeophysical inversion method shows promise for improving root distribution and transpiration estimates across a wide variety of settings.
Takamuku, Shinya; Forbes, Paul A G; Hamilton, Antonia F de C; Gomi, Hiroaki
2018-05-07
There is increasing evidence for motor difficulties in many people with autism spectrum condition (ASC). These difficulties could be linked to differences in the use of internal models which represent relations between motions and forces/efforts. The use of these internal models may be dependent on the cerebellum which has been shown to be abnormal in autism. Several studies have examined internal computations of forward dynamics (motion from force information) in autism, but few have tested the inverse dynamics computation, that is, the determination of force-related information from motion information. Here, we examined this ability in autistic adults by measuring two perceptual biases which depend on the inverse computation. First, we asked participants whether they experienced a feeling of resistance when moving a delayed cursor, which corresponds to the inertial force of the cursor implied by its motion-both typical and ASC participants reported similar feelings of resistance. Second, participants completed a psychophysical task in which they judged the velocity of a moving hand with or without a visual cue implying inertial force. Both typical and ASC participants perceived the hand moving with the inertial cue to be slower than the hand without it. In both cases, the magnitude of the effects did not differ between the two groups. Our results suggest that the neural systems engaged in the inverse dynamics computation are preserved in ASC, at least in the observed conditions. Autism Res 2018. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. We tested the ability to estimate force information from motion information, which arises from a specific "inverse dynamics" computation. Autistic adults and a matched control group reported feeling a resistive sensation when moving a delayed cursor and also judged a moving hand to be slower when it was pulling a load. These findings both suggest that the ability to estimate force information from motion information is intact in autism. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.
Recursive flexible multibody system dynamics using spatial operators
NASA Technical Reports Server (NTRS)
Jain, A.; Rodriguez, G.
1992-01-01
This paper uses spatial operators to develop new spatially recursive dynamics algorithms for flexible multibody systems. The operator description of the dynamics is identical to that for rigid multibody systems. Assumed-mode models are used for the deformation of each individual body. The algorithms are based on two spatial operator factorizations of the system mass matrix. The first (Newton-Euler) factorization of the mass matrix leads to recursive algorithms for the inverse dynamics, mass matrix evaluation, and composite-body forward dynamics for the systems. The second (innovations) factorization of the mass matrix, leads to an operator expression for the mass matrix inverse and to a recursive articulated-body forward dynamics algorithm. The primary focus is on serial chains, but extensions to general topologies are also described. A comparison of computational costs shows that the articulated-body, forward dynamics algorithm is much more efficient than the composite-body algorithm for most flexible multibody systems.
Dynamic Paper Constructions for Easier Visualization of Molecular Symmetry
ERIC Educational Resources Information Center
Sein, Lawrence T., Jr.
2010-01-01
A system for construction of simple poster-board models is described. The models dynamically demonstrate the symmetry operations of proper rotation, improper rotation, reflection, and inversion for the chemically important point groups D[subscript 3h], D[subscript 4h], D[subscript 5h], D[subscript 6h], T[subscript d], and O[subscript h]. The…
Boreal soil carbon dynamics under a changing climate: a model inversion approach
Zhaosheng Fan; Jason C. Neff; Jennifer W. Harden; Kimberly P. Wickland
2008-01-01
Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and...
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.
NASA Technical Reports Server (NTRS)
Bacon, Barton J.; Ostroff, Aaron J.
2000-01-01
This paper presents an approach to on-line control design for aircraft that have suffered either actuator failure, missing effector surfaces, surface damage, or any combination. The approach is based on a modified version of nonlinear dynamic inversion. The approach does not require a model of the baseline vehicle (effectors at zero deflection), but does require feedback of accelerations and effector positions. Implementation issues are addressed and the method is demonstrated on an advanced tailless aircraft. An experimental simulation analysis tool is used to directly evaluate the nonlinear system's stability robustness.
Simulation gravity modeling to spacecraft-tracking data - Analysis and application
NASA Technical Reports Server (NTRS)
Phillips, R. J.; Sjogren, W. L.; Abbott, E. A.; Zisk, S. H.
1978-01-01
It is proposed that line-of-sight gravity measurements derived from spacecraft-tracking data can be used for quantitative subsurface density modeling by suitable orbit simulation procedures. Such an approach avoids complex dynamic reductions and is analogous to the modeling of conventional surface gravity data. This procedure utilizes the vector calculations of a given gravity model in a simplified trajectory integration program that simulates the line-of-sight gravity. Solutions from an orbit simulation inversion and a dynamic inversion on Doppler observables compare well (within 1% in mass and size), and the error sources in the simulation approximation are shown to be quite small. An application of this technique is made to lunar crater gravity anomalies by simulating the complete Bouguer correction to several large young lunar craters. It is shown that the craters all have negative Bouguer anomalies.
Dynamic rupture models of earthquakes on the Bartlett Springs Fault, Northern California
Lozos, Julian C.; Harris, Ruth A.; Murray, Jessica R.; Lienkaemper, James J.
2015-01-01
The Bartlett Springs Fault (BSF), the easternmost branch of the northern San Andreas Fault system, creeps along much of its length. Geodetic data for the BSF are sparse, and surface creep rates are generally poorly constrained. The two existing geodetic slip rate inversions resolve at least one locked patch within the creeping zones. We use the 3-D finite element code FaultMod to conduct dynamic rupture models based on both geodetic inversions, in order to determine the ability of rupture to propagate into the creeping regions, as well as to assess possible magnitudes for BSF ruptures. For both sets of models, we find that the distribution of aseismic creep limits the extent of coseismic rupture, due to the contrast in frictional properties between the locked and creeping regions.
Parameter Selection Methods in Inverse Problem Formulation
2010-11-03
clinical data and used for prediction and a model for the reaction of the cardiovascular system to an ergometric workload. Key Words: Parameter selection...model for HIV dynamics which has been successfully validated with clinical data and used for prediction and a model for the reaction of the...recently developed in-host model for HIV dynamics which has been successfully validated with clinical data and used for prediction [4, 8]; b) a global
Study of crash energy absorption characteristics of inversion tube on passenger vehicle
NASA Astrophysics Data System (ADS)
Liu, Jiandong; Liu, Tao; Yao, Shengjie; Zhao, Rutao
2017-09-01
This article studied the energy absorption characteristics of the inversion tube and acquired the inversion tube design key dimensions under theoretical conditions by performing formula derivation in the quasi-static and dynamic state based on the working principle of the inversion tube: free inversion. The article further adopted HyperMesh and LS-Dyna to perform simulation and compared the simulation result with the theoretical calculating value for comparison. The design was applied in the full-vehicle model to perform 50km/h front fullwidth crash simulation. The findings showed that the deformation mode of the inversion tube in the full-vehicle crash was consistent with the design mode, and the inversion tube absorbed 33.0% of total energy, thereby conforming to the vehicle safety design requirements.
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.
Jansen-Osmann, Petra; Richter, Stefanie; Konczak, Jürgen; Kalveram, Karl-Theodor
2002-03-01
When humans perform goal-directed arm movements under the influence of an external damping force, they learn to adapt to these external dynamics. After removal of the external force field, they reveal kinematic aftereffects that are indicative of a neural controller that still compensates the no longer existing force. Such behavior suggests that the adult human nervous system uses a neural representation of inverse arm dynamics to control upper-extremity motion. Central to the notion of an inverse dynamic model (IDM) is that learning generalizes. Consequently, aftereffects should be observable even in untrained workspace regions. Adults have shown such behavior, but the ontogenetic development of this process remains unclear. This study examines the adaptive behavior of children and investigates whether learning a force field in one hemifield of the right arm workspace has an effect on force adaptation in the other hemifield. Thirty children (aged 6-10 years) and ten adults performed 30 degrees elbow flexion movements under two conditions of external damping (negative and null). We found that learning to compensate an external damping force transferred to the opposite hemifield, which indicates that a model of the limb dynamics rather than an association of visited space and experienced force was acquired. Aftereffects were more pronounced in the younger children and readaptation to a null-force condition was prolonged. This finding is consistent with the view that IDMs in children are imprecise neural representations of the actual arm dynamics. It indicates that the acquisition of IDMs is a developmental achievement and that the human motor system is inherently flexible enough to adapt to any novel force within the limits of the organism's biomechanics.
Control of a high beta maneuvering reentry vehicle using dynamic inversion.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Watts, Alfred Chapman
2005-05-01
The design of flight control systems for high performance maneuvering reentry vehicles presents a significant challenge to the control systems designer. These vehicles typically have a much higher ballistic coefficient than crewed vehicles like as the Space Shuttle or proposed crew return vehicles such as the X-38. Moreover, the missions of high performance vehicles usually require a steeper reentry flight path angle, followed by a pull-out into level flight. These vehicles then must transit the entire atmosphere and robustly perform the maneuvers required for the mission. The vehicles must also be flown with small static margins in order to performmore » the required maneuvers, which can result in highly nonlinear aerodynamic characteristics that frequently transition from being aerodynamically stable to unstable as angle of attack increases. The control system design technique of dynamic inversion has been applied successfully to both high performance aircraft and low beta reentry vehicles. The objective of this study was to explore the application of this technique to high performance maneuvering reentry vehicles, including the basic derivation of the dynamic inversion technique, followed by the extension of that technique to the use of tabular trim aerodynamic models in the controller. The dynamic inversion equations are developed for high performance vehicles and augmented to allow the selection of a desired response for the control system. A six degree of freedom simulation is used to evaluate the performance of the dynamic inversion approach, and results for both nominal and off nominal aerodynamic characteristics are presented.« less
NASA Astrophysics Data System (ADS)
Cheung, Mark C. M.; Boerner, P.; Schrijver, C. J.; Testa, P.; Chen, F.; Peter, H.; Malanushenko, A.
2015-07-01
We present a new method for performing differential emission measure (DEM) inversions on narrow-band EUV images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. The method yields positive definite DEM solutions by solving a linear program. This method has been validated against a diverse set of thermal models of varying complexity and realism. These include (1) idealized Gaussian DEM distributions, (2) 3D models of NOAA Active Region 11158 comprising quasi-steady loop atmospheres in a nonlinear force-free field, and (3) thermodynamic models from a fully compressible, 3D MHD simulation of active region (AR) corona formation following magnetic flux emergence. We then present results from the application of the method to AIA observations of Active Region 11158, comparing the region's thermal structure on two successive solar rotations. Additionally, we show how the DEM inversion method can be adapted to simultaneously invert AIA and Hinode X-ray Telescope data, and how supplementing AIA data with the latter improves the inversion result. The speed of the method allows for routine production of DEM maps, thus facilitating science studies that require tracking of the thermal structure of the solar corona in time and space.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cheung, Mark C. M.; Boerner, P.; Schrijver, C. J.
We present a new method for performing differential emission measure (DEM) inversions on narrow-band EUV images from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. The method yields positive definite DEM solutions by solving a linear program. This method has been validated against a diverse set of thermal models of varying complexity and realism. These include (1) idealized Gaussian DEM distributions, (2) 3D models of NOAA Active Region 11158 comprising quasi-steady loop atmospheres in a nonlinear force-free field, and (3) thermodynamic models from a fully compressible, 3D MHD simulation of active region (AR) corona formation following magneticmore » flux emergence. We then present results from the application of the method to AIA observations of Active Region 11158, comparing the region's thermal structure on two successive solar rotations. Additionally, we show how the DEM inversion method can be adapted to simultaneously invert AIA and Hinode X-ray Telescope data, and how supplementing AIA data with the latter improves the inversion result. The speed of the method allows for routine production of DEM maps, thus facilitating science studies that require tracking of the thermal structure of the solar corona in time and space.« less
NASA Astrophysics Data System (ADS)
Vignon, Etienne; Hourdin, Frédéric; Genthon, Christophe; Van de Wiel, Bas J. H.; Gallée, Hubert; Madeleine, Jean-Baptiste; Beaumet, Julien
2018-01-01
Observations evidence extremely stable boundary layers (SBL) over the Antarctic Plateau and sharp regime transitions between weakly and very stable conditions. Representing such features is a challenge for climate models. This study assesses the modeling of the dynamics of the boundary layer over the Antarctic Plateau in the LMDZ general circulation model. It uses 1 year simulations with a stretched-grid over Dome C. The model is nudged with reanalyses outside of the Dome C region such as simulations can be directly compared to in situ observations. We underline the critical role of the downward longwave radiation for modeling the surface temperature. LMDZ reasonably represents the near-surface seasonal profiles of wind and temperature but strong temperature inversions are degraded by enhanced turbulent mixing formulations. Unlike ERA-Interim reanalyses, LMDZ reproduces two SBL regimes and the regime transition, with a sudden increase in the near-surface inversion with decreasing wind speed. The sharpness of the transition depends on the stability function used for calculating the surface drag coefficient. Moreover, using a refined vertical grid leads to a better reversed "S-shaped" relationship between the inversion and the wind. Sudden warming events associated to synoptic advections of warm and moist air are also well reproduced. Near-surface supersaturation with respect to ice is not allowed in LMDZ but the impact on the SBL structure is moderate. Finally, climate simulations with the free model show that the recommended configuration leads to stronger inversions and winds over the ice-sheet. However, the near-surface wind remains underestimated over the slopes of East-Antarctica.
2010-09-19
estimated directly form the surveillance data Infection control measures were implemented in the form of health care worker hand - hygiene before and after...hospital infections , is used to motivate possibilities of modeling nosocomial infec- tion dynamics. This is done in the context of hospital monitoring and...model development. Key Words: Delay equations, discrete events, nosocomial infection dynamics, surveil- lance data, inverse problems, parameter
Learn the Lagrangian: A Vector-Valued RKHS Approach to Identifying Lagrangian Systems.
Cheng, Ching-An; Huang, Han-Pang
2016-12-01
We study the modeling of Lagrangian systems with multiple degrees of freedom. Based on system dynamics, canonical parametric models require ad hoc derivations and sometimes simplification for a computable solution; on the other hand, due to the lack of prior knowledge in the system's structure, modern nonparametric models in machine learning face the curse of dimensionality, especially in learning large systems. In this paper, we bridge this gap by unifying the theories of Lagrangian systems and vector-valued reproducing kernel Hilbert space. We reformulate Lagrangian systems with kernels that embed the governing Euler-Lagrange equation-the Lagrangian kernels-and show that these kernels span a subspace capturing the Lagrangian's projection as inverse dynamics. By such property, our model uses only inputs and outputs as in machine learning and inherits the structured form as in system dynamics, thereby removing the need for the mundane derivations for new systems as well as the generalization problem in learning from scratches. In effect, it learns the system's Lagrangian, a simpler task than directly learning the dynamics. To demonstrate, we applied the proposed kernel to identify the robot inverse dynamics in simulations and experiments. Our results present a competitive novel approach to identifying Lagrangian systems, despite using only inputs and outputs.
The Effect of Overskilling Dynamics on Wages
ERIC Educational Resources Information Center
Mavromaras, Kostas; Mahuteau, Stephane; Sloane, Peter; Wei, Zhang
2013-01-01
We use a random-effects dynamic probit model to estimate the effect of overskilling dynamics on wages. We find that overskilling mismatch is common and more likely among those who have been overskilled in the past. It is also highly persistent, in a manner that is inversely related to educational level. Yet, the wages of university graduates are…
Inverse problems and computational cell metabolic models: a statistical approach
NASA Astrophysics Data System (ADS)
Calvetti, D.; Somersalo, E.
2008-07-01
In this article, we give an overview of the Bayesian modelling of metabolic systems at the cellular and subcellular level. The models are based on detailed description of key biochemical reactions occurring in tissue, which may in turn be compartmentalized into cytosol and mitochondria, and of transports between the compartments. The classical deterministic approach which models metabolic systems as dynamical systems with Michaelis-Menten kinetics, is replaced by a stochastic extension where the model parameters are interpreted as random variables with an appropriate probability density. The inverse problem of cell metabolism in this setting consists of estimating the density of the model parameters. After discussing some possible approaches to solving the problem, we address the issue of how to assess the reliability of the predictions of a stochastic model by proposing an output analysis in terms of model uncertainties. Visualization modalities for organizing the large amount of information provided by the Bayesian dynamic sensitivity analysis are also illustrated.
Inverse stochastic-dynamic models for high-resolution Greenland ice core records
NASA Astrophysics Data System (ADS)
Boers, Niklas; Chekroun, Mickael D.; Liu, Honghu; Kondrashov, Dmitri; Rousseau, Denis-Didier; Svensson, Anders; Bigler, Matthias; Ghil, Michael
2017-12-01
Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic-dynamic models from δ18O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59-22 ka b2k. Our model reproduces the dynamical characteristics of both the δ18O and dust proxy records, including the millennial-scale Dansgaard-Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the δ18O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects.
Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh
2018-06-25
New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.
NASA Technical Reports Server (NTRS)
Bayo, Eduardo; Ledesma, Ragnar
1993-01-01
A technique is presented for solving the inverse dynamics of flexible planar multibody systems. This technique yields the non-causal joint efforts (inverse dynamics) as well as the internal states (inverse kinematics) that produce a prescribed nominal trajectory of the end effector. A non-recursive global Lagrangian approach is used in formulating the equations for motion as well as in solving the inverse dynamics equations. Contrary to the recursive method previously presented, the proposed method solves the inverse problem in a systematic and direct manner for both open-chain as well as closed-chain configurations. Numerical simulation shows that the proposed procedure provides an excellent tracking of the desired end effector trajectory.
Real-Time Minimization of Tracking Error for Aircraft Systems
NASA Technical Reports Server (NTRS)
Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John
2013-01-01
This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.
Movement decoupling control for two-axis fast steering mirror
NASA Astrophysics Data System (ADS)
Wang, Rui; Qiao, Yongming; Lv, Tao
2017-02-01
Based on flexure hinge and piezoelectric actuator of two-axis fast steering mirror is a complex system with time varying, uncertain and strong coupling. It is extremely difficult to achieve high precision decoupling control with the traditional PID control method. The feedback error learning method was established an inverse hysteresis model which was based inner product dynamic neural network nonlinear and no-smooth for piezo-ceramic. In order to improve the actuator high precision, a method was proposed, which was based piezo-ceramic inverse model of two dynamic neural network adaptive control. The experiment result indicated that, compared with two neural network adaptive movement decoupling control algorithm, static relative error is reduced from 4.44% to 0.30% and coupling degree is reduced from 12.71% to 0.60%, while dynamic relative error is reduced from 13.92% to 2.85% and coupling degree is reduced from 2.63% to 1.17%.
Gear fatigue crack prognosis using embedded model, gear dynamic model and fracture mechanics
NASA Astrophysics Data System (ADS)
Li, C. James; Lee, Hyungdae
2005-07-01
This paper presents a model-based method that predicts remaining useful life of a gear with a fatigue crack. The method consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffness; a gear dynamic model to simulate gear meshing dynamics and determine the dynamic load on the cracked tooth; and a fast crack propagation model to forecast the remaining useful life based on the estimated crack size and dynamic load. The fast crack propagation model was established to avoid repeated calculations of FEM and facilitate field deployment of the proposed method. Experimental studies were conducted to validate and demonstrate the feasibility of the proposed method for prognosis of a cracked gear.
NASA Astrophysics Data System (ADS)
Vater, Stefan; Behrens, Jörn
2017-04-01
Simulations of historic tsunami events such as the 2004 Sumatra or the 2011 Tohoku event are usually initialized using earthquake sources resulting from inversion of seismic data. Also, other data from ocean buoys etc. is sometimes included in the derivation of the source model. The associated tsunami event can often be well simulated in this way, and the results show high correlation with measured data. However, it is unclear how the derived source model compares to the particular earthquake event. In this study we use the results from dynamic rupture simulations obtained with SeisSol, a software package based on an ADER-DG discretization solving the spontaneous dynamic earthquake rupture problem with high-order accuracy in space and time. The tsunami model is based on a second-order Runge-Kutta discontinuous Galerkin (RKDG) scheme on triangular grids and features a robust wetting and drying scheme for the simulation of inundation events at the coast. Adaptive mesh refinement enables the efficient computation of large domains, while at the same time it allows for high local resolution and geometric accuracy. The results are compared to measured data and results using earthquake sources based on inversion. With the approach of using the output of actual dynamic rupture simulations, we can estimate the influence of different earthquake parameters. Furthermore, the comparison to other source models enables a thorough comparison and validation of important tsunami parameters, such as the runup at the coast. This work is part of the ASCETE (Advanced Simulation of Coupled Earthquake and Tsunami Events) project, which aims at an improved understanding of the coupling between the earthquake and the generated tsunami event.
Nonlinear Inversion for Dynamic Rupture Parameters from the 2004 Mw6.0 Parkfield Earthquake
NASA Astrophysics Data System (ADS)
Jimenez, R. M.; Olsen, K. B.
2007-12-01
The Parkfield section of the San Andreas Fault has produced repeated moderate-size earthquakes at fairly regular intervals and is therefore an important target for investigations of rupture initiation, propagation and arrest, which could eventually lead to clues on earthquake prediction. The most recent member of the Parkfield series of earthquakes, the 2004 Mw6.0 event, produced a considerable amount of high-resolution strong motion data, and provides an ideal test bed for analysis of the dynamic rupture propagation. Here, we use a systematic nonlinear direct-search method to invert strong-ground motion data (less than 1 Hz) at 37 stations to obtain models of the slip weakening distance and spatially-varying stress drop (8 by 4 subfaults) on the (vertical) causative segment of the San Andreas fault (40 km long by 15 km wide), along with spatial-temporal coseismic slip distributions. The rupture and wave propagation modeling is performed by a three-dimensional finite-difference method with a slip- weakening friction law and the stress-glut dynamic-rupture formulation (Andrews, 1999), and the inversion is carried out by a neighborhood algorithm (Sambridge, 1999), minimizing the least-squares misfit between the calculated and observed seismograms. The dynamic rupture is nucleated artificially by lowering the yield stress in a 3 km by 3 km patch centered at the location of the hypocenter estimated from strong motion data. Outside the nucleation patch the yield stress is kept constant (5-10 MPa), and we constrain the slip-weakening distance to values less than 1 m. We compare the inversion results for two different velocity models: (1) a 3-D model based on the P-wave velocity structure by Thurber (2006), with S-wave and density relations based on Brocher (2005), and (2) a combination of two different 1-D layered velocity structures on either side of the fault, as proposed by Liu et al. (2006). Due to the non-uniqueness of the problem, the inversion provides an ensemble of equally valid rupture models that produce synthetics with comparable fit to the observed strong motion data. Our preliminary results with the smallest misfits, out of about 3000 tested rupture models, suggest an average slip-weakening distance of 19-81 cm and an average stress drop across the fault of 6.7 - 8.4 MPa. Compared to the kinematic inversion results by Liu et al. (2006) our models with the smallest misfits produce a larger maximum slip (up to about 81 cm) and smaller rupture area, but similar rupture duration (5-7s). The inversions carried out for the layered models tend to produce smaller misfit between data and synthetics as compared to the results using the 3D structure. This suggests that our 3D structure needs improvement, including the Vs-Vp and density-Vp relation. We expect further decrease in the misfit values by increasing the number of tested rupture models.
NASA Astrophysics Data System (ADS)
Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng
2017-10-01
Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.
NASA Astrophysics Data System (ADS)
Wan, S.; He, W.
2016-12-01
The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963) equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data." On the basis of the intelligent features of evolutionary modeling (EM), including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.
Prediction of muscle activation for an eye movement with finite element modeling.
Karami, Abbas; Eghtesad, Mohammad; Haghpanah, Seyyed Arash
2017-10-01
In this paper, a 3D finite element (FE) modeling is employed in order to predict extraocular muscles' activation and investigate force coordination in various motions of the eye orbit. A continuum constitutive hyperelastic model is employed for material description in dynamic modeling of the extraocular muscles (EOMs). Two significant features of this model are accurate mass modeling with FE method and stimulating EOMs for motion through muscle activation parameter. In order to validate the eye model, a forward dynamics simulation of the eye motion is carried out by variation of the muscle activation. Furthermore, to realize muscle activation prediction in various eye motions, two different tracking-based inverse controllers are proposed. The performance of these two inverse controllers is investigated according to their resulted muscle force magnitude and muscle force coordination. The simulation results are compared with the available experimental data and the well-known existing neurological laws. The comparison authenticates both the validation and the prediction results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Dark Matter and the elusive Z' in a dynamical Inverse Seesaw scenario
De Romeri, Valentina; Fernandez-Martinez, Enrique; Gehrlein, Julia; ...
2017-10-24
The Inverse Seesaw naturally explains the smallness of neutrino masses via an approximate $B-L$ symmetry broken only by a correspondingly small parameter. In this work the possible dynamical generation of the Inverse Seesaw neutrino mass mechanism from the spontaneous breaking of a gauged $U(1)$ $B-L$ symmetry is investigated. Interestingly, the Inverse Seesaw pattern requires a chiral content such that anomaly cancellation predicts the existence of extra fermions belonging to a dark sector with large, non-trivial, charges under the $U(1)$ $B-L$. We investigate the phenomenology associated to these new states and find that one of them is a viable dark mattermore » candidate with mass around the TeV scale, whose interaction with the Standard Model is mediated by the $Z'$ boson associated to the gauged $U(1)$ $B-L$ symmetry. Given the large charges required for anomaly cancellation in the dark sector, the $B-L$ $Z'$ interacts preferentially with this dark sector rather than with the Standard Model. This suppresses the rate at direct detection searches and thus alleviates the constraints on $Z'$-mediated dark matter relic abundance. Furthermore, the collider phenomenology of this elusive $Z'$ is also discussed.« less
NASA Technical Reports Server (NTRS)
Gherlone, Marco; Cerracchio, Priscilla; Mattone, Massimiliano; Di Sciuva, Marco; Tessler, Alexander
2011-01-01
A robust and efficient computational method for reconstructing the three-dimensional displacement field of truss, beam, and frame structures, using measured surface-strain data, is presented. Known as shape sensing , this inverse problem has important implications for real-time actuation and control of smart structures, and for monitoring of structural integrity. The present formulation, based on the inverse Finite Element Method (iFEM), uses a least-squares variational principle involving strain measures of Timoshenko theory for stretching, torsion, bending, and transverse shear. Two inverse-frame finite elements are derived using interdependent interpolations whose interior degrees-of-freedom are condensed out at the element level. In addition, relationships between the order of kinematic-element interpolations and the number of required strain gauges are established. As an example problem, a thin-walled, circular cross-section cantilevered beam subjected to harmonic excitations in the presence of structural damping is modeled using iFEM; where, to simulate strain-gauge values and to provide reference displacements, a high-fidelity MSC/NASTRAN shell finite element model is used. Examples of low and high-frequency dynamic motion are analyzed and the solution accuracy examined with respect to various levels of discretization and the number of strain gauges.
Dark Matter and the elusive Z' in a dynamical Inverse Seesaw scenario
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Romeri, Valentina; Fernandez-Martinez, Enrique; Gehrlein, Julia
The Inverse Seesaw naturally explains the smallness of neutrino masses via an approximate $B-L$ symmetry broken only by a correspondingly small parameter. In this work the possible dynamical generation of the Inverse Seesaw neutrino mass mechanism from the spontaneous breaking of a gauged $U(1)$ $B-L$ symmetry is investigated. Interestingly, the Inverse Seesaw pattern requires a chiral content such that anomaly cancellation predicts the existence of extra fermions belonging to a dark sector with large, non-trivial, charges under the $U(1)$ $B-L$. We investigate the phenomenology associated to these new states and find that one of them is a viable dark mattermore » candidate with mass around the TeV scale, whose interaction with the Standard Model is mediated by the $Z'$ boson associated to the gauged $U(1)$ $B-L$ symmetry. Given the large charges required for anomaly cancellation in the dark sector, the $B-L$ $Z'$ interacts preferentially with this dark sector rather than with the Standard Model. This suppresses the rate at direct detection searches and thus alleviates the constraints on $Z'$-mediated dark matter relic abundance. Furthermore, the collider phenomenology of this elusive $Z'$ is also discussed.« less
Analysis of a homemade Edison tinfoil phonograph.
Sagers, Jason D; McNeese, Andrew R; Lenhart, Richard D; Wilson, Preston S
2012-10-01
Thomas Edison's phonograph was a landmark acoustic invention. In this paper, the phonograph is presented as a tool for education in acoustics. A brief history of the phonograph is outlined and an analogous circuit model that describes its dynamic response is discussed. Microphone and scanning laser Doppler vibrometer (SLDV) measurements were made on a homemade phonograph for model validation and inversion for unknown model parameters. SLDV measurements also conclusively illustrate where model assumptions are violated. The model elements which dominate the dynamic response are discussed.
Analysis and numerical modelling of eddy current damper for vibration problems
NASA Astrophysics Data System (ADS)
Irazu, L.; Elejabarrieta, M. J.
2018-07-01
This work discusses a contactless eddy current damper, which is used to attenuate structural vibration. Eddy currents can remove energy from dynamic systems without any contact and, thus, without adding mass or modifying the rigidity of the structure. An experimental modal analysis of a cantilever beam in the absence of and under a partial magnetic field is conducted in the bandwidth of 01 kHz. The results show that the eddy current phenomenon can attenuate the vibration of the entire structure without modifying the natural frequencies or the mode shapes of the structure itself. In this study, a new inverse method to numerically determine the dynamic properties of the contactless eddy current damper is proposed. The proposed inverse method and the eddy current model based on a lineal viscous force are validated by a practical application. The numerically obtained transfer function correlates with the experimental one, thus showing good agreement in the entire bandwidth of 01 kHz. The proposed method provides an easy and quick tool to model and predict the dynamic behaviour of the contactless eddy current damper, thereby avoiding the use of complex analytical models.
Inverse Optimization: A New Perspective on the Black-Litterman Model.
Bertsimas, Dimitris; Gupta, Vishal; Paschalidis, Ioannis Ch
2012-12-11
The Black-Litterman (BL) model is a widely used asset allocation model in the financial industry. In this paper, we provide a new perspective. The key insight is to replace the statistical framework in the original approach with ideas from inverse optimization. This insight allows us to significantly expand the scope and applicability of the BL model. We provide a richer formulation that, unlike the original model, is flexible enough to incorporate investor information on volatility and market dynamics. Equally importantly, our approach allows us to move beyond the traditional mean-variance paradigm of the original model and construct "BL"-type estimators for more general notions of risk such as coherent risk measures. Computationally, we introduce and study two new "BL"-type estimators and their corresponding portfolios: a Mean Variance Inverse Optimization (MV-IO) portfolio and a Robust Mean Variance Inverse Optimization (RMV-IO) portfolio. These two approaches are motivated by ideas from arbitrage pricing theory and volatility uncertainty. Using numerical simulation and historical backtesting, we show that both methods often demonstrate a better risk-reward tradeoff than their BL counterparts and are more robust to incorrect investor views.
Oguz, Ozgur S; Zhou, Zhehua; Glasauer, Stefan; Wollherr, Dirk
2018-04-03
Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS.
Generalised filtering and stochastic DCM for fMRI.
Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E; Penny, Will; Hu, Dewen; Friston, Karl
2011-09-15
This paper is about the fitting or inversion of dynamic causal models (DCMs) of fMRI time series. It tries to establish the validity of stochastic DCMs that accommodate random fluctuations in hidden neuronal and physiological states. We compare and contrast deterministic and stochastic DCMs, which do and do not ignore random fluctuations or noise on hidden states. We then compare stochastic DCMs, which do and do not ignore conditional dependence between hidden states and model parameters (generalised filtering and dynamic expectation maximisation, respectively). We first characterise state-noise by comparing the log evidence of models with different a priori assumptions about its amplitude, form and smoothness. Face validity of the inversion scheme is then established using data simulated with and without state-noise to ensure that DCM can identify the parameters and model that generated the data. Finally, we address construct validity using real data from an fMRI study of internet addiction. Our analyses suggest the following. (i) The inversion of stochastic causal models is feasible, given typical fMRI data. (ii) State-noise has nontrivial amplitude and smoothness. (iii) Stochastic DCM has face validity, in the sense that Bayesian model comparison can distinguish between data that have been generated with high and low levels of physiological noise and model inversion provides veridical estimates of effective connectivity. (iv) Relaxing conditional independence assumptions can have greater construct validity, in terms of revealing group differences not disclosed by variational schemes. Finally, we note that the ability to model endogenous or random fluctuations on hidden neuronal (and physiological) states provides a new and possibly more plausible perspective on how regionally specific signals in fMRI are generated. Copyright © 2011. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Falcon, N.
2017-07-01
At cosmic scales the dynamics of the Universe are almost exclusively prescribed by the force of gravity; however the assumption of the law of gravitation, depending on the inverse of the distance, leads to the known problems of the rotation curves of galaxies and missing mass (dark matter). The problem of the coupling of gravity to changes in scale and deviations from the law of the inverse square is an old problem (Laplace, 1805; Seeliger 1898), which has motivated alternatives to Newtonian dynamics compatible with observations. The present paper postulates a modified Newtonian dynamics by adding an inverse Yukawa potential: U(r)≡U0(M)(r-r0)e-α/r is the the potential per unit mass (in N/kg) as a function of the barionic mass that causes the field, r0 is of the order of 50h-1 Mpc and alpha is a coupling constant of the order of 2.5 h-1 Mpc. This potential is zero within the solar system, slightly attractive at interstellar distances, very attractive in galactic range and repulsive at cosmic scales. Its origin is the barionic matter, it allows to include the Milgrow MoND theory to explain the rotation curves, it is compatible with the experiments Eovos type, and allows to deduce the law of Hubble to cosmic scales, in the form H0=100h km/s Mpc≍U0(M)/c, where U0(M)≍ 4pi×6.67 10-11m/s2, is obtained from the Laplace's equation, assuming that the gravitational force is the law of the inverse of the square plus a non-linear term type Yukawa inverse. It is concluded that the modification of the law of gravity with nonlinear terms, allows to model the dynamics of the Universe on a large scale and include non-locality without dark matter. (See Falcon et al. 2014, International Journal of Astronomy and Astrophysics, 4, 551-559).
NASA Astrophysics Data System (ADS)
Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.
2011-12-01
High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve the spatial structure in the inverse model, which leads to better parameter estimates and improved predictions when using the inverse-conditioned realizations of parameter fields.
Success Stories in Control: Nonlinear Dynamic Inversion Control
NASA Technical Reports Server (NTRS)
Bosworth, John T.
2010-01-01
NASA plays an important role in advancing the state of the art in flight control systems. In the case of Nonlinear Dynamic Inversion (NDI) NASA supported initial implementation of the theory in an aircraft and demonstration in a space vehicle. Dr. Dale Enns of Honeywell Aerospace Advanced Technology performed this work in cooperation with NASA and under NASA contract. Honeywell and Lockheed Martin were subsequently contracted by AFRL to create "Design Guidelines for Multivariable Control Theory". This foundational work directly contributed to the advancement of the technology and the credibility of the control law as a design option. As a result Honeywell collaborated with Lockheed Martin to produce a Nonlinear Dynamic Inversion controller for the X-35 and subsequently Lockheed Martin did the same for the production Lockheed Martin F-35 vehicle. The theory behind NDI is to use a systematic generalized approach to controlling a vehicle. Using general aircraft nonlinear equations of motion and onboard aerodynamic, mass properties, and engine models specific to the vehicle, a relationship between control effectors and desired aircraft motion can be formulated. Using this formulation a control combination is used that provides a predictable response to commanded motion. Control loops around this formulation shape the response as desired and provide robustness to modeling errors. Once the control law is designed it can be used on a similar class of vehicle with only an update to the vehicle specific onboard models.
Preliminary assessment of the robustness of dynamic inversion based flight control laws
NASA Technical Reports Server (NTRS)
Snell, S. A.
1992-01-01
Dynamic-inversion-based flight control laws present an attractive alternative to conventional gain-scheduled designs for high angle-of-attack maneuvering, where nonlinearities dominate the dynamics. Dynamic inversion is easily applied to the aircraft dynamics requiring a knowledge of the nonlinear equations of motion alone, rather than an extensive set of linearizations. However, the robustness properties of the dynamic inversion are questionable especially when considering the uncertainties involved with the aerodynamic database during post-stall flight. This paper presents a simple analysis and some preliminary results of simulations with a perturbed database. It is shown that incorporating integrators into the control loops helps to improve the performance in the presence of these perturbations.
An Inverse Neural Controller Based on the Applicability Domain of RBF Network Models
Alexandridis, Alex; Stogiannos, Marios; Papaioannou, Nikolaos; Zois, Elias; Sarimveis, Haralambos
2018-01-01
This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions. Finally, an error correction term, estimating the error produced by the unmodeled dynamics and/or unmeasured external disturbances, is included to the control scheme to increase robustness. The resulting controller guarantees bounded input-bounded state (BIBS) stability for the closed loop system when the open loop system is BIBS stable. The proposed methodology is evaluated on two different control problems, namely, the control of an experimental armature-controlled direct current (DC) motor and the stabilization of a highly nonlinear simulated inverted pendulum. For each one of these problems, appropriate case studies are tested, in which a conventional neural controller employing inverse models and a PID controller are also applied. The results reveal the ability of the proposed control scheme to handle and manipulate diverse data through a data fusion approach and illustrate the superiority of the method in terms of faster and less oscillatory responses. PMID:29361781
Monte Carlo Volcano Seismic Moment Tensors
NASA Astrophysics Data System (ADS)
Waite, G. P.; Brill, K. A.; Lanza, F.
2015-12-01
Inverse modeling of volcano seismic sources can provide insight into the geometry and dynamics of volcanic conduits. But given the logistical challenges of working on an active volcano, seismic networks are typically deficient in spatial and temporal coverage; this potentially leads to large errors in source models. In addition, uncertainties in the centroid location and moment-tensor components, including volumetric components, are difficult to constrain from the linear inversion results, which leads to a poor understanding of the model space. In this study, we employ a nonlinear inversion using a Monte Carlo scheme with the objective of defining robustly resolved elements of model space. The model space is randomized by centroid location and moment tensor eigenvectors. Point sources densely sample the summit area and moment tensors are constrained to a randomly chosen geometry within the inversion; Green's functions for the random moment tensors are all calculated from modeled single forces, making the nonlinear inversion computationally reasonable. We apply this method to very-long-period (VLP) seismic events that accompany minor eruptions at Fuego volcano, Guatemala. The library of single force Green's functions is computed with a 3D finite-difference modeling algorithm through a homogeneous velocity-density model that includes topography, for a 3D grid of nodes, spaced 40 m apart, within the summit region. The homogenous velocity and density model is justified by long wavelength of VLP data. The nonlinear inversion reveals well resolved model features and informs the interpretation through a better understanding of the possible models. This approach can also be used to evaluate possible station geometries in order to optimize networks prior to deployment.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hou, Z; Terry, N; Hubbard, S S
2013-02-12
In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniquenessmore » and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability distribution functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSim) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes advantage of the spatial-temporal correlation of the state variables. We first apply the inversion framework to a static synthetic example and then to a time-lapse GPR tomographic dataset collected during a dynamic experiment conducted at the Hanford Site in Richland, WA. We demonstrate that the MRE-Bayesian inversion enables us to merge various data types, quantify uncertainty, evaluate nonlinear models, and produce more detailed and better resolved estimates than straight-ray based inversion; therefore, it has the potential to improve estimates of inter-wellbore dielectric permittivity and soil moisture content and to monitor their temporal dynamics more accurately.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hou, Zhangshuan; Terry, Neil C.; Hubbard, Susan S.
2013-02-22
In this study, we evaluate the possibility of monitoring soil moisture variation using tomographic ground penetrating radar travel time data through Bayesian inversion, which is integrated with entropy memory function and pilot point concepts, as well as efficient sampling approaches. It is critical to accurately estimate soil moisture content and variations in vadose zone studies. Many studies have illustrated the promise and value of GPR tomographic data for estimating soil moisture and associated changes, however, challenges still exist in the inversion of GPR tomographic data in a manner that quantifies input and predictive uncertainty, incorporates multiple data types, handles non-uniquenessmore » and nonlinearity, and honors time-lapse tomograms collected in a series. To address these challenges, we develop a minimum relative entropy (MRE)-Bayesian based inverse modeling framework that non-subjectively defines prior probabilities, incorporates information from multiple sources, and quantifies uncertainty. The framework enables us to estimate dielectric permittivity at pilot point locations distributed within the tomogram, as well as the spatial correlation range. In the inversion framework, MRE is first used to derive prior probability density functions (pdfs) of dielectric permittivity based on prior information obtained from a straight-ray GPR inversion. The probability distributions are then sampled using a Quasi-Monte Carlo (QMC) approach, and the sample sets provide inputs to a sequential Gaussian simulation (SGSIM) algorithm that constructs a highly resolved permittivity/velocity field for evaluation with a curved-ray GPR forward model. The likelihood functions are computed as a function of misfits, and posterior pdfs are constructed using a Gaussian kernel. Inversion of subsequent time-lapse datasets combines the Bayesian estimates from the previous inversion (as a memory function) with new data. The memory function and pilot point design takes advantage of the spatial-temporal correlation of the state variables. We first apply the inversion framework to a static synthetic example and then to a time-lapse GPR tomographic dataset collected during a dynamic experiment conducted at the Hanford Site in Richland, WA. We demonstrate that the MRE-Bayesian inversion enables us to merge various data types, quantify uncertainty, evaluate nonlinear models, and produce more detailed and better resolved estimates than straight-ray based inversion; therefore, it has the potential to improve estimates of inter-wellbore dielectric permittivity and soil moisture content and to monitor their temporal dynamics more accurately.« less
Pursuit tracking and higher levels of skill development in the human pilot
NASA Technical Reports Server (NTRS)
Hess, R. A.
1981-01-01
A model of the human pilot is offered for pursuit tracking tasks; the model encompasses an existing model for compensatory tracking. The central hypothesis in the development of this model states that those primary structural elements in the compensatory model responsible for the pilot's equalization capabilities remain intact in the pursuit model. In this latter case, effective low-frequency inversion of the controlled-element dynamics occurs by feeding-forward derived input rate through the equalization dynamics, with low-frequency phase droop minimized. The sharp reduction in low-frequency phase lag beyond that associated with the disappearance of phase droop is seen to accompany relatively low-gain feedback of vehicle output. The results of some recent motion cue research are discussed and interpreted in terms of the compensatory-pursuit display dichotomy. Tracking with input preview is discussed in a qualitative way. In terms of the model, preview is shown to demand no fundamental changes in structure or equalization and to allow the pilot to eliminate the effective time delays that accrue in the inversion of the controlled-element dynamics. Precognitive behavior is discussed, and a model that encompasses all the levels of skill development outlined in the successive organizations of perception theory is finally proposed.
On the origin of bursts and heavy tails in animal dynamics
NASA Astrophysics Data System (ADS)
Reynolds, A. M.
2011-01-01
Over recent years there has been an accumulation of evidence that many animal behaviours are characterised by common scale-invariant patterns of switching between two contrasting activities over a period of time. This is evidenced in mammalian wake-sleep patterns, in the intermittent stop-start locomotion of Drosophila fruit flies, and in the Lévy walk movement patterns of a diverse range of animals in which straight-line movements are punctuated by occasional turns. Here it is shown that these dynamics can be modelled by a stochastic variant of Barabási’s model [A.-L. Barabási, The origin of bursts and heavy tails in human dynamics, Nature 435 (2005) 207-211] for bursts and heavy tails in human dynamics. The new model captures a tension between two competing and conflicting activities. The durations of one type of activity are distributed according to an inverse-square power-law, mirroring the ubiquity of inverse-square power-law scaling seen in empirical data. The durations of the second type of activity follow exponential distributions with characteristic timescales that depend on species and metabolic rates. This again is a common feature of animal behaviour. Bursty human dynamics, on the other hand, are characterised by power-law distributions with scaling exponents close to -1 and -3/2.
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
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.
Laughman, Brian; Wang, Ling; Lund, Thomas S.; Collins, Richard L.
2018-01-01
Abstract An anelastic numerical model is employed to explore the dynamics of gravity waves (GWs) encountering a mesosphere inversion layer (MIL) having a moderate static stability enhancement and a layer of weaker static stability above. Instabilities occur within the MIL when the GW amplitude approaches that required for GW breaking due to compression of the vertical wavelength accompanying the increasing static stability. Thus, MILs can cause large‐amplitude GWs to yield instabilities and turbulence below the altitude where they would otherwise arise. Smaller‐amplitude GWs encountering a MIL do not lead to instability and turbulence but do exhibit partial reflection and transmission, and the transmission is a smaller fraction of the incident GW when instabilities and turbulence arise within the MIL. Additionally, greater GW transmission occurs for weaker MILs and for GWs having larger vertical wavelengths relative to the MIL depth and for lower GW intrinsic frequencies. These results imply similar dynamics for inversions due to other sources, including the tropopause inversion layer, the high stability capping the polar summer mesopause, and lower frequency GWs or tides having sufficient amplitudes to yield significant variations in stability at large and small vertical scales. MILs also imply much stronger reflections and less coherent GW propagation in environments having significant fine structure in the stability and velocity fields than in environments that are smoothly varying. PMID:29576994
NASA Astrophysics Data System (ADS)
Fritts, David C.; Laughman, Brian; Wang, Ling; Lund, Thomas S.; Collins, Richard L.
2018-01-01
An anelastic numerical model is employed to explore the dynamics of gravity waves (GWs) encountering a mesosphere inversion layer (MIL) having a moderate static stability enhancement and a layer of weaker static stability above. Instabilities occur within the MIL when the GW amplitude approaches that required for GW breaking due to compression of the vertical wavelength accompanying the increasing static stability. Thus, MILs can cause large-amplitude GWs to yield instabilities and turbulence below the altitude where they would otherwise arise. Smaller-amplitude GWs encountering a MIL do not lead to instability and turbulence but do exhibit partial reflection and transmission, and the transmission is a smaller fraction of the incident GW when instabilities and turbulence arise within the MIL. Additionally, greater GW transmission occurs for weaker MILs and for GWs having larger vertical wavelengths relative to the MIL depth and for lower GW intrinsic frequencies. These results imply similar dynamics for inversions due to other sources, including the tropopause inversion layer, the high stability capping the polar summer mesopause, and lower frequency GWs or tides having sufficient amplitudes to yield significant variations in stability at large and small vertical scales. MILs also imply much stronger reflections and less coherent GW propagation in environments having significant fine structure in the stability and velocity fields than in environments that are smoothly varying.
Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions
NASA Technical Reports Server (NTRS)
Miller, Christopher J.
2011-01-01
A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.
Kinematics and dynamics of robotic systems with multiple closed loops
NASA Astrophysics Data System (ADS)
Zhang, Chang-De
The kinematics and dynamics of robotic systems with multiple closed loops, such as Stewart platforms, walking machines, and hybrid manipulators, are studied. In the study of kinematics, focus is on the closed-form solutions of the forward position analysis of different parallel systems. A closed-form solution means that the solution is expressed as a polynomial in one variable. If the order of the polynomial is less than or equal to four, the solution has analytical closed-form. First, the conditions of obtaining analytical closed-form solutions are studied. For a Stewart platform, the condition is found to be that one rotational degree of freedom of the output link is decoupled from the other five. Based on this condition, a class of Stewart platforms which has analytical closed-form solution is formulated. Conditions of analytical closed-form solution for other parallel systems are also studied. Closed-form solutions of forward kinematics for walking machines and multi-fingered grippers are then studied. For a parallel system with three three-degree-of-freedom subchains, there are 84 possible ways to select six independent joints among nine joints. These 84 ways can be classified into three categories: Category 3:3:0, Category 3:2:1, and Category 2:2:2. It is shown that the first category has no solutions; the solutions of the second category have analytical closed-form; and the solutions of the last category are higher order polynomials. The study is then extended to a nearly general Stewart platform. The solution is a 20th order polynomial and the Stewart platform has a maximum of 40 possible configurations. Also, the study is extended to a new class of hybrid manipulators which consists of two serially connected parallel mechanisms. In the study of dynamics, a computationally efficient method for inverse dynamics of manipulators based on the virtual work principle is developed. Although this method is comparable with the recursive Newton-Euler method for serial manipulators, its advantage is more noteworthy when applied to parallel systems. An approach of inverse dynamics of a walking machine is also developed, which includes inverse dynamic modeling, foot force distribution, and joint force/torque allocation.
Sarode, Ketan Dinkar; Kumar, V Ravi; Kulkarni, B D
2016-05-01
An efficient inverse problem approach for parameter estimation, state and structure identification from dynamic data by embedding training functions in a genetic algorithm methodology (ETFGA) is proposed for nonlinear dynamical biosystems using S-system canonical models. Use of multiple shooting and decomposition approach as training functions has been shown for handling of noisy datasets and computational efficiency in studying the inverse problem. The advantages of the methodology are brought out systematically by studying it for three biochemical model systems of interest. By studying a small-scale gene regulatory system described by a S-system model, the first example demonstrates the use of ETFGA for the multifold aims of the inverse problem. The estimation of a large number of parameters with simultaneous state and network identification is shown by training a generalized S-system canonical model with noisy datasets. The results of this study bring out the superior performance of ETFGA on comparison with other metaheuristic approaches. The second example studies the regulation of cAMP oscillations in Dictyostelium cells now assuming limited availability of noisy data. Here, flexibility of the approach to incorporate partial system information in the identification process is shown and its effect on accuracy and predictive ability of the estimated model are studied. The third example studies the phenomenological toy model of the regulation of circadian oscillations in Drosophila that follows rate laws different from S-system power-law. For the limited noisy data, using a priori information about properties of the system, we could estimate an alternate S-system model that showed robust oscillatory behavior with predictive abilities. Copyright © 2016 Elsevier Inc. All rights reserved.
Mantle viscosity structure constrained by joint inversions of seismic velocities and density
NASA Astrophysics Data System (ADS)
Rudolph, M. L.; Moulik, P.; Lekic, V.
2017-12-01
The viscosity structure of Earth's deep mantle affects the thermal evolution of Earth, the ascent of mantle upwellings, sinking of subducted oceanic lithosphere, and the mixing of compositional heterogeneities in the mantle. Modeling the long-wavelength dynamic geoid allows us to constrain the radial viscosity profile of the mantle. Typically, in inversions for the mantle viscosity structure, wavespeed variations are mapped into density variations using a constant- or depth-dependent scaling factor. Here, we use a newly developed joint model of anisotropic Vs, Vp, density and transition zone topographies to generate a suite of solutions for the mantle viscosity structure directly from the seismologically constrained density structure. The density structure used to drive our forward models includes contributions from both thermal and compositional variations, including important contributions from compositionally dense material in the Large Low Velocity Provinces at the base of the mantle. These compositional variations have been neglected in the forward models used in most previous inversions and have the potential to significantly affect large-scale flow and thus the inferred viscosity structure. We use a transdimensional, hierarchical, Bayesian approach to solve the inverse problem, and our solutions for viscosity structure include an increase in viscosity below the base of the transition zone, in the shallow lower mantle. Using geoid dynamic response functions and an analysis of the correlation between the observed geoid and mantle structure, we demonstrate the underlying reason for this inference. Finally, we present a new family of solutions in which the data uncertainty is accounted for using covariance matrices associated with the mantle structure models.
Estimated landmark calibration of biomechanical models for inverse kinematics.
Trinler, Ursula; Baker, Richard
2018-01-01
Inverse kinematics is emerging as the optimal method in movement analysis to fit a multi-segment biomechanical model to experimental marker positions. A key part of this process is calibrating the model to the dimensions of the individual being analysed which requires scaling of the model, pose estimation and localisation of tracking markers within the relevant segment coordinate systems. The aim of this study is to propose a generic technique for this process and test a specific application to the OpenSim model Gait2392. Kinematic data from 10 healthy adult participants were captured in static position and normal walking. Results showed good average static and dynamic fitting errors between virtual and experimental markers of 0.8 cm and 0.9 cm, respectively. Highest fitting errors were found on the epicondyle (static), feet (static, dynamic) and on the thigh (dynamic). These result from inconsistencies between the model geometry and degrees of freedom and the anatomy and movement pattern of the individual participants. A particular limitation is in estimating anatomical landmarks from the bone meshes supplied with Gait2392 which do not conform with the bone morphology of the participants studied. Soft tissue artefact will also affect fitting the model to walking trials. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.
Wang, Ruoli; Gutierrez-Farewik, Elena M
2011-05-01
The purpose of this study was to determine how gait deviation in one plane (i.e. excessive subtalar inversion/eversion) can affect the dynamic function of the tibialis anterior, gastrocnemius, and soleus to accelerate the subtalar, ankle, knee and hip joints, as well as the body center of mass. Induced acceleration analysis was performed based on a subject-specific three-dimensional linkage model configured by stance phase gait data and driven by one unit of muscle force. Eight healthy adult subjects were examined in gait analysis. The subtalar inversion/eversion was modeled by offsetting up to 20° from the normal subtalar angle while other configurations remained unaltered. This study showed that the gastrocnemius, soleus and tibialis anterior generally functioned as their anatomical definition in normal gait, but counterintuitive function was occasionally found in the bi-articular gastrocnemius. The plantarflexors play important roles in the body support and forward progression. Excessive subtalar eversion was found to enlarge the plantarflexors and tibialis anterior's function. Induced acceleration analysis demonstrated its ability to isolate the contributions of individual muscle to a given factor, and as a means of studying effect of pathological gait on the dynamic muscle functions. Copyright © 2011 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luh, G.C.
1994-01-01
This thesis presents the application of advanced modeling techniques to construct nonlinear forward and inverse models of internal combustion engines for the detection and isolation of incipient faults. The NARMAX (Nonlinear Auto-Regressive Moving Average modeling with eXogenous inputs) technique of system identification proposed by Leontaritis and Billings was used to derive the nonlinear model of a internal combustion engine, over operating conditions corresponding to the I/M240 cycle. The I/M240 cycle is a standard proposed by the United States Environmental Protection Agency to measure tailpipe emissions in inspection and maintenance programs and consists of a driving schedule developed for the purposemore » of testing compliance with federal vehicle emission standards for carbon monoxide, unburned hydrocarbons, and nitrogen oxides. The experimental work for model identification and validation was performed on a 3.0 liter V6 engine installed in an engine test cell at the Center for Automotive Research at The Ohio State University. In this thesis, different types of model structures were proposed to obtain multi-input multi-output (MIMO) nonlinear NARX models. A modification of the algorithm proposed by He and Asada was used to estimate the robust orders of the derived MIMO nonlinear models. A methodology for the analysis of inverse NARX model was developed. Two methods were proposed to derive the inverse NARX model: (1) inversion from the forward NARX model; and (2) direct identification of inverse model from the output-input data set. In this thesis, invertibility, minimum-phase characteristic of zero dynamics, and stability analysis of NARX forward model are also discussed. Stability in the sense of Lyapunov is also investigated to check the stability of the identified forward and inverse models. This application of inverse problem leads to the estimation of unknown inputs and to actuator fault diagnosis.« less
A time domain inverse dynamic method for the end point tracking control of a flexible manipulator
NASA Technical Reports Server (NTRS)
Kwon, Dong-Soo; Book, Wayne J.
1991-01-01
The inverse dynamic equation of a flexible manipulator was solved in the time domain. By dividing the inverse system equation into the causal part and the anticausal part, we calculated the torque and the trajectories of all state variables for a given end point trajectory. The interpretation of this method in the frequency domain was explained in detail using the two-sided Laplace transform and the convolution integral. The open loop control of the inverse dynamic method shows an excellent result in simulation. For real applications, a practical control strategy is proposed by adding a feedback tracking control loop to the inverse dynamic feedforward control, and its good experimental performance is presented.
The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.
Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael
2018-02-01
We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.
Studies of Trace Gas Chemical Cycles Using Inverse Methods and Global Chemical Transport Models
NASA Technical Reports Server (NTRS)
Prinn, Ronald G.
2003-01-01
We report progress in the first year, and summarize proposed work for the second year of the three-year dynamical-chemical modeling project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (b) utilization of inverse methods to determine these source/sink strengths using either MATCH (Model for Atmospheric Transport and Chemistry) which is based on analyzed observed wind fields or back-trajectories computed from these wind fields, (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important goals include determination of regional source strengths of methane, nitrous oxide, methyl bromide, and other climatically and chemically important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal protocol and its follow-on agreements and hydrohalocarbons now used as alternatives to the restricted halocarbons.
Inverse Optimization: A New Perspective on the Black-Litterman Model
Bertsimas, Dimitris; Gupta, Vishal; Paschalidis, Ioannis Ch.
2014-01-01
The Black-Litterman (BL) model is a widely used asset allocation model in the financial industry. In this paper, we provide a new perspective. The key insight is to replace the statistical framework in the original approach with ideas from inverse optimization. This insight allows us to significantly expand the scope and applicability of the BL model. We provide a richer formulation that, unlike the original model, is flexible enough to incorporate investor information on volatility and market dynamics. Equally importantly, our approach allows us to move beyond the traditional mean-variance paradigm of the original model and construct “BL”-type estimators for more general notions of risk such as coherent risk measures. Computationally, we introduce and study two new “BL”-type estimators and their corresponding portfolios: a Mean Variance Inverse Optimization (MV-IO) portfolio and a Robust Mean Variance Inverse Optimization (RMV-IO) portfolio. These two approaches are motivated by ideas from arbitrage pricing theory and volatility uncertainty. Using numerical simulation and historical backtesting, we show that both methods often demonstrate a better risk-reward tradeoff than their BL counterparts and are more robust to incorrect investor views. PMID:25382873
Modified Dynamic Inversion to Control Large Flexible Aircraft: What's Going On?
NASA Technical Reports Server (NTRS)
Gregory, Irene M.
1999-01-01
High performance aircraft of the future will be designed lighter, more maneuverable, and operate over an ever expanding flight envelope. One of the largest differences from the flight control perspective between current and future advanced aircraft is elasticity. Over the last decade, dynamic inversion methodology has gained considerable popularity in application to highly maneuverable fighter aircraft, which were treated as rigid vehicles. This paper explores dynamic inversion application to an advanced highly flexible aircraft. An initial application has been made to a large flexible supersonic aircraft. In the course of controller design for this advanced vehicle, modifications were made to the standard dynamic inversion methodology. The results of this application were deemed rather promising. An analytical study has been undertaken to better understand the nature of the made modifications and to determine its general applicability. This paper presents the results of this initial analytical look at the modifications to dynamic inversion to control large flexible aircraft.
Dynamic electrical impedance imaging with the interacting multiple model scheme.
Kim, Kyung Youn; Kim, Bong Seok; Kim, Min Chan; Kim, Sin; Isaacson, David; Newell, Jonathan C
2005-04-01
In this paper, an effective dynamical EIT imaging scheme is presented for on-line monitoring of the abruptly changing resistivity distribution inside the object, based on the interacting multiple model (IMM) algorithm. The inverse problem is treated as a stochastic nonlinear state estimation problem with the time-varying resistivity (state) being estimated on-line with the aid of the IMM algorithm. In the design of the IMM algorithm multiple models with different process noise covariance are incorporated to reduce the modeling uncertainty. Simulations and phantom experiments are provided to illustrate the proposed algorithm.
The Earthquake Source Inversion Validation (SIV) - Project: Summary, Status, Outlook
NASA Astrophysics Data System (ADS)
Mai, P. M.
2017-12-01
Finite-fault earthquake source inversions infer the (time-dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, this kinematic source inversion is ill-posed and returns non-unique solutions, as seen for instance in multiple source models for the same earthquake, obtained by different research teams, that often exhibit remarkable dissimilarities. To address the uncertainties in earthquake-source inversions and to understand strengths and weaknesses of various methods, the Source Inversion Validation (SIV) project developed a set of forward-modeling exercises and inversion benchmarks. Several research teams then use these validation exercises to test their codes and methods, but also to develop and benchmark new approaches. In this presentation I will summarize the SIV strategy, the existing benchmark exercises and corresponding results. Using various waveform-misfit criteria and newly developed statistical comparison tools to quantify source-model (dis)similarities, the SIV platforms is able to rank solutions and identify particularly promising source inversion approaches. Existing SIV exercises (with related data and descriptions) and all computational tools remain available via the open online collaboration platform; additional exercises and benchmark tests will be uploaded once they are fully developed. I encourage source modelers to use the SIV benchmarks for developing and testing new methods. The SIV efforts have already led to several promising new techniques for tackling the earthquake-source imaging problem. I expect that future SIV benchmarks will provide further innovations and insights into earthquake source kinematics that will ultimately help to better understand the dynamics of the rupture process.
NASA Astrophysics Data System (ADS)
Virgili-Llop, Josep; Zagaris, Costantinos; Park, Hyeongjun; Zappulla, Richard; Romano, Marcello
2018-03-01
An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a ground-based air-bearing test bed, using spacecraft simulators that float over a granite table.
Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems
NASA Astrophysics Data System (ADS)
Williams, Rube B.
2004-02-01
Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.
NASA Astrophysics Data System (ADS)
Díaz-Mojica, J. J.; Cruz-Atienza, V. M.; Madariaga, R.; Singh, S. K.; Iglesias, A.
2013-05-01
We introduce a novel approach for imaging the earthquakes dynamics from ground motion records based on a parallel genetic algorithm (GA). The method follows the elliptical dynamic-rupture-patch approach introduced by Di Carli et al. (2010) and has been carefully verified through different numerical tests (Díaz-Mojica et al., 2012). Apart from the five model parameters defining the patch geometry, our dynamic source description has four more parameters: the stress drop inside the nucleation and the elliptical patches; and two friction parameters, the slip weakening distance and the change of the friction coefficient. These parameters are constant within the rupture surface. The forward dynamic source problem, involved in the GA inverse method, uses a highly accurate computational solver for the problem, namely the staggered-grid split-node. The synthetic inversion presented here shows that the source model parameterization is suitable for the GA, and that short-scale source dynamic features are well resolved in spite of low-pass filtering of the data for periods comparable to the source duration. Since there is always uncertainty in the propagation medium as well as in the source location and the focal mechanisms, we have introduced a statistical approach to generate a set of solution models so that the envelope of the corresponding synthetic waveforms explains as much as possible the observed data. We applied the method to the 2012 Mw6.5 intraslab Zumpango, Mexico earthquake and determined several fundamental source parameters that are in accordance with different and completely independent estimates for Mexican and worldwide earthquakes. Our weighted-average final model satisfactorily explains eastward rupture directivity observed in the recorded data. Some parameters found for the Zumpango earthquake are: Δτ = 30.2+/-6.2 MPa, Er = 0.68+/-0.36x10^15 J, G = 1.74+/-0.44x10^15 J, η = 0.27+/-0.11, Vr/Vs = 0.52+/-0.09 and Mw = 6.64+/-0.07; for the stress drop, radiated energy, fracture energy, radiation efficiency, rupture velocity and moment magnitude, respectively. Mw6.5 intraslab Zumpango earthquake location, stations location and tectonic setting in central Mexico
Three-dimensional audio-magnetotelluric sounding in monitoring coalbed methane reservoirs
NASA Astrophysics Data System (ADS)
Wang, Nan; Zhao, Shanshan; Hui, Jian; Qin, Qiming
2017-03-01
Audio-magnetotelluric (AMT) sounding is widely employed in rapid resistivity delineation of objective geometry in near surface exploration. According to reservoir patterns and electrical parameters obtained in Qinshui Basin, China, two-dimensional and three-dimensional synthetic "objective anomaly" models were designed and inverted with the availability of a modular system for electromagnetic inversion (ModEM). The results revealed that 3-D full impedance inversion yielded the subsurface models closest to synthetic models. One or more conductive targets were correctly recovered. Therefore, conductive aquifers in the study area, including hydrous coalbed methane (CBM) reservoirs, were suggested to be the interpretation signs for reservoir characterization. With the aim of dynamic monitoring of CBM reservoirs, the AMT surveys in continuous years (June 2013-May 2015) were carried out. 3-D inversion results demonstrated that conductive anomalies accumulated around the producing reservoirs at the corresponding depths if CBM reservoirs were in high water production rates. In contrast, smaller conductive anomalies were generally identical with rapid gas production or stopping production of reservoirs. These analyses were in accordance with actual production history of CBM wells. The dynamic traces of conductive anomalies revealed that reservoir water migrated deep or converged in axial parts and wings of folds, which contributed significantly to formations of CBM traps. Then the well spacing scenario was also evaluated based on the dynamic production analysis. Wells distributed near closed faults or flat folds, rather than open faults, had CBM production potential to ascertain stable gas production. Therefore, three-dimensional AMT sounding becomes an attractive option with the ability of dynamic monitoring of CBM reservoirs, and lays a solid foundation of quantitative evaluation of reservoir parameters.
Dynamic characterization of high damping viscoelastic materials from vibration test data
NASA Astrophysics Data System (ADS)
Martinez-Agirre, Manex; Elejabarrieta, María Jesús
2011-08-01
The numerical analysis and design of structural systems involving viscoelastic damping materials require knowledge of material properties and proper mathematical models. A new inverse method for the dynamic characterization of high damping and strong frequency-dependent viscoelastic materials from vibration test data measured by forced vibration tests with resonance is presented. Classical material parameter extraction methods are reviewed; their accuracy for characterizing high damping materials is discussed; and the bases of the new analysis method are detailed. The proposed inverse method minimizes the residue between the experimental and theoretical dynamic response at certain discrete frequencies selected by the user in order to identify the parameters of the material constitutive model. Thus, the material properties are identified in the whole bandwidth under study and not just at resonances. Moreover, the use of control frequencies makes the method insensitive to experimental noise and the efficiency is notably enhanced. Therefore, the number of tests required is drastically reduced and the overall process is carried out faster and more accurately. The effectiveness of the proposed method is demonstrated with the characterization of a CLD (constrained layer damping) cantilever beam. First, the elastic properties of the constraining layers are identified from the dynamic response of a metallic cantilever beam. Then, the viscoelastic properties of the core, represented by a four-parameter fractional derivative model, are identified from the dynamic response of a CLD cantilever beam.
NASA Astrophysics Data System (ADS)
Roth, Eatai; Howell, Darrin; Beckwith, Cydney; Burden, Samuel A.
2017-05-01
Humans, interacting with cyber-physical systems (CPS), formulate beliefs about the system's dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human-cyber-physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system's dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator's ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.
Dynamic data integration and stochastic inversion of a confined aquifer
NASA Astrophysics Data System (ADS)
Wang, D.; Zhang, Y.; Irsa, J.; Huang, H.; Wang, L.
2013-12-01
Much work has been done in developing and applying inverse methods to aquifer modeling. The scope of this paper is to investigate the applicability of a new direct method for large inversion problems and to incorporate uncertainty measures in the inversion outcomes (Wang et al., 2013). The problem considered is a two-dimensional inverse model (50×50 grid) of steady-state flow for a heterogeneous ground truth model (500×500 grid) with two hydrofacies. From the ground truth model, decreasing number of wells (12, 6, 3) were sampled for facies types, based on which experimental indicator histograms and directional variograms were computed. These parameters and models were used by Sequential Indicator Simulation to generate 100 realizations of hydrofacies patterns in a 100×100 (geostatistical) grid, which were conditioned to the facies measurements at wells. These realizations were smoothed with Simulated Annealing, coarsened to the 50×50 inverse grid, before they were conditioned with the direct method to the dynamic data, i.e., observed heads and groundwater fluxes at the same sampled wells. A set of realizations of estimated hydraulic conductivities (Ks), flow fields, and boundary conditions were created, which centered on the 'true' solutions from solving the ground truth model. Both hydrofacies conductivities were computed with an estimation accuracy of ×10% (12 wells), ×20% (6 wells), ×35% (3 wells) of the true values. For boundary condition estimation, the accuracy was within × 15% (12 wells), 30% (6 wells), and 50% (3 wells) of the true values. The inversion system of equations was solved with LSQR (Paige et al, 1982), for which coordinate transform and matrix scaling preprocessor were used to improve the condition number (CN) of the coefficient matrix. However, when the inverse grid was refined to 100×100, Gaussian Noise Perturbation was used to limit the growth of the CN before the matrix solve. To scale the inverse problem up (i.e., without smoothing and coarsening and therefore reducing the associated estimation uncertainty), a parallel LSQR solver was written and verified. For the 50×50 grid, the parallel solver sped up the serial solution time by 14X using 4 CPUs (research on parallel performance and scaling is ongoing). A sensitivity analysis was conducted to examine the relation between the observed data and the inversion outcomes, where measurement errors of increasing magnitudes (i.e., ×1, 2, 5, 10% of the total head variation and up to ×2% of the total flux variation) were imposed on the observed data. Inversion results were stable but the accuracy of Ks and boundary estimation degraded with increasing errors, as expected. In particular, quality of the observed heads is critical to hydraulic head recovery, while quality of the observed fluxes plays a dominant role in K estimation. References: Wang, D., Y. Zhang, J. Irsa, H. Huang, and L. Wang (2013), Data integration and stochastic inversion of a confined aquifer with high performance computing, Advances in Water Resources, in preparation. Paige, C. C., and M. A. Saunders (1982), LSQR: an algorithm for sparse linear equations and sparse least squares, ACM Transactions on Mathematical Software, 8(1), 43-71.
Next Generation Robots for STEM Education andResearch at Huston Tillotson University
2017-11-10
dynamics through the following command: roslaunch mtb_lab6_feedback_linearization gravity_compensation.launch Part B: Gravity Inversion : After...understood the system’s natural dynamics. roslaunch mtb_lab6_feedback_linearization gravity_compensation.launch Part B: Gravity Inversion ...is created using the following command: roslaunch mtb_lab6_feedback_linearization gravity_inversion.launch Gravity inversion is just one
Motion control of musculoskeletal systems with redundancy.
Park, Hyunjoo; Durand, Dominique M
2008-12-01
Motion control of musculoskeletal systems for functional electrical stimulation (FES) is a challenging problem due to the inherent complexity of the systems. These include being highly nonlinear, strongly coupled, time-varying, time-delayed, and redundant. The redundancy in particular makes it difficult to find an inverse model of the system for control purposes. We have developed a control system for multiple input multiple output (MIMO) redundant musculoskeletal systems with little prior information. The proposed method separates the steady-state properties from the dynamic properties. The dynamic control uses a steady-state inverse model and is implemented with both a PID controller for disturbance rejection and an artificial neural network (ANN) feedforward controller for fast trajectory tracking. A mechanism to control the sum of the muscle excitation levels is also included. To test the performance of the proposed control system, a two degree of freedom ankle-subtalar joint model with eight muscles was used. The simulation results show that separation of steady-state and dynamic control allow small output tracking errors for different reference trajectories such as pseudo-step, sinusoidal and filtered random signals. The proposed control method also demonstrated robustness against system parameter and controller parameter variations. A possible application of this control algorithm is FES control using multiple contact cuff electrodes where mathematical modeling is not feasible and the redundancy makes the control of dynamic movement difficult.
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.
Heteroclinic dynamics of coupled semiconductor lasers with optoelectronic feedback.
Shahin, S; Vallini, F; Monifi, F; Rabinovich, M; Fainman, Y
2016-11-15
Generalized Lotka-Volterra (GLV) equations are important equations used in various areas of science to describe competitive dynamics among a population of N interacting nodes in a network topology. In this Letter, we introduce a photonic network consisting of three optoelectronically cross-coupled semiconductor lasers to realize a GLV model. In such a network, the interaction of intensity and carrier inversion rates, as well as phases of laser oscillator nodes, result in various dynamics. We study the influence of asymmetric coupling strength and frequency detuning between semiconductor lasers and show that inhibitory asymmetric coupling is required to achieve consecutive amplitude oscillations of the laser nodes. These studies were motivated primarily by the dynamical models used to model brain cognitive activities and their correspondence with dynamics obtained among coupled laser oscillators.
Approximated Stable Inversion for Nonlinear Systems with Nonhyperbolic Internal Dynamics. Revised
NASA Technical Reports Server (NTRS)
Devasia, Santosh
1999-01-01
A technique to achieve output tracking for nonminimum phase nonlinear systems with non- hyperbolic internal dynamics is presented. The present paper integrates stable inversion techniques (that achieve exact-tracking) with approximation techniques (that modify the internal dynamics) to circumvent the nonhyperbolicity of the internal dynamics - this nonhyperbolicity is an obstruction to applying presently available stable inversion techniques. The theory is developed for nonlinear systems and the method is applied to a two-cart with inverted-pendulum example.
An inverse dynamics approach to trajectory optimization and guidance for an aerospace plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1992-01-01
The optimal ascent problem for an aerospace planes is formulated as an optimal inverse dynamic problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the optimal trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suited for onboard implementation. Robust ascent guidance is obtained by using combination of feedback compensation and onboard generation of control through the inverse dynamics approach. Accurate orbital insertion can be achieved with near-optimal control of the rocket through inverse dynamics even in the presence of disturbances.
NASA Astrophysics Data System (ADS)
Liang, Yingjie; Chen, Wen
2018-03-01
Ultraslow diffusion has been observed in numerous complicated systems. Its mean squared displacement (MSD) is not a power law function of time, but instead a logarithmic function, and in some cases grows even more slowly than the logarithmic rate. The distributed-order fractional diffusion equation model simply does not work for the general ultraslow diffusion. Recent study has used the local structural derivative to describe ultraslow diffusion dynamics by using the inverse Mittag-Leffler function as the structural function, in which the MSD is a function of inverse Mittag-Leffler function. In this study, a new stretched logarithmic diffusion law and its underlying non-local structural derivative diffusion model are proposed to characterize the ultraslow diffusion in aging dense colloidal glass at both the short and long waiting times. It is observed that the aging dynamics of dense colloids is a class of the stretched logarithmic ultraslow diffusion processes. Compared with the power, the logarithmic, and the inverse Mittag-Leffler diffusion laws, the stretched logarithmic diffusion law has better precision in fitting the MSD of the colloidal particles at high densities. The corresponding non-local structural derivative diffusion equation manifests clear physical mechanism, and its structural function is equivalent to the first-order derivative of the MSD.
Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.; ...
2016-04-25
Improving our ability to estimate the parameters that control water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. The objectives of this study are to develop and test a new inversion scheme to simultaneously estimate subsurface hydrological, thermal and petrophysical parameters using hydrological, thermal and electrical resistivity tomography (ERT) data. The inversion scheme-which is based on a nonisothermal, multiphase hydrological model-provides the desired subsurface property estimates in high spatiotemporal resolution. A particularly novel aspect of the inversion scheme is the explicit incorporation of the dependence of themore » subsurface electrical resistivity on both moisture and temperature. The scheme was applied to synthetic case studies, as well as to real datasets that were autonomously collected at a biogeochemical field study site in Rifle, Colorado. At the Rifle site, the coupled hydrological-thermal-geophysical inversion approach well predicted the matric potential, temperature and apparent resistivity with the Nash-Sutcliffe efficiency criterion greater than 0.92. Synthetic studies found that neglecting the subsurface temperature variability, and its effect on the electrical resistivity in the hydrogeophysical inversion, may lead to an incorrect estimation of the hydrological parameters. The approach is expected to be especially useful for the increasing number of studies that are taking advantage of autonomously collected ERT and soil measurements to explore complex terrestrial system dynamics.« less
Feedback control laws for highly maneuverable aircraft
NASA Technical Reports Server (NTRS)
Garrard, William L.; Balas, Gary J.
1995-01-01
During this year, we concentrated our efforts on the design of controllers for lateral/directional control using mu synthesis. This proved to be a more difficult task than we anticipated and we are still working on the designs. In the lateral-directional control problem, the inputs are pilot lateral stick and pedal commands and the outputs are roll rate about the velocity vector and side slip angle. The control effectors are ailerons, rudder deflection, and directional thrust vectoring vane deflection which produces a yawing moment about the body axis. Our math model does not contain any provision for thrust vectoring of rolling moment. This has resulted in limitations of performance at high angles of attack. During 1994-95, the following tasks for the lateral-directional controllers were accomplished: (1) Designed both inner and outer loop dynamic inversion controllers. These controllers are implemented using accelerometer outputs rather than an a priori model of the vehicle aerodynamics; (2) Used classical techniques to design controllers for the system linearized by dynamics inversion. These controllers acted to control roll rate and Dutch roll response; (3) Implemented the inner loop dynamic inversion and classical controllers on the six DOF simulation; (4) Developed a lateral-directional control allocation scheme based on minimizing required control effort among the ailerons, rudder, and directional thrust vectoring; and (5) Developed mu outer loop controllers combined with classical inner loop controllers.
A systematic linear space approach to solving partially described inverse eigenvalue problems
NASA Astrophysics Data System (ADS)
Hu, Sau-Lon James; Li, Haujun
2008-06-01
Most applications of the inverse eigenvalue problem (IEP), which concerns the reconstruction of a matrix from prescribed spectral data, are associated with special classes of structured matrices. Solving the IEP requires one to satisfy both the spectral constraint and the structural constraint. If the spectral constraint consists of only one or few prescribed eigenpairs, this kind of inverse problem has been referred to as the partially described inverse eigenvalue problem (PDIEP). This paper develops an efficient, general and systematic approach to solve the PDIEP. Basically, the approach, applicable to various structured matrices, converts the PDIEP into an ordinary inverse problem that is formulated as a set of simultaneous linear equations. While solving simultaneous linear equations for model parameters, the singular value decomposition method is applied. Because of the conversion to an ordinary inverse problem, other constraints associated with the model parameters can be easily incorporated into the solution procedure. The detailed derivation and numerical examples to implement the newly developed approach to symmetric Toeplitz and quadratic pencil (including mass, damping and stiffness matrices of a linear dynamic system) PDIEPs are presented. Excellent numerical results for both kinds of problem are achieved under the situations that have either unique or infinitely many solutions.
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.
H∞ control of combustion in diesel engines using a discrete dynamics model
NASA Astrophysics Data System (ADS)
Hirata, Mitsuo; Ishizuki, Sota; Suzuki, Masayasu
2016-09-01
This paper proposes a control method for combustion in diesel engines using a discrete dynamics model. The proposed two-degree-of-freedom control scheme achieves not only good feedback properties such as disturbance suppression and robust stability but also a good transient response. The method includes a feedforward controller constructed from the inverse model of the plant, and a feedback controller designed by an Hcontrol method, which reduces the effect of the turbocharger lag. The effectiveness of the proposed method is evaluated via numerical simulations.
NASA Technical Reports Server (NTRS)
Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.
2011-01-01
Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.
Langevin Dynamics Simulations of Genome Packing in Bacteriophage
Forrey, Christopher; Muthukumar, M.
2006-01-01
We use Langevin dynamics simulations to study the process by which a coarse-grained DNA chain is packaged within an icosahedral container. We focus our inquiry on three areas of interest in viral packing: the evolving structure of the packaged DNA condensate; the packing velocity; and the internal buildup of energy and resultant forces. Each of these areas has been studied experimentally, and we find that we can qualitatively reproduce experimental results. However, our findings also suggest that the phage genome packing process is fundamentally different than that suggested by the inverse spool model. We suggest that packing in general does not proceed in the deterministic fashion of the inverse-spool model, but rather is stochastic in character. As the chain configuration becomes compressed within the capsid, the structure, energy, and packing velocity all become dependent upon polymer dynamics. That many observed features of the packing process are rooted in condensed-phase polymer dynamics suggests that statistical mechanics, rather than mechanics, should serve as the proper theoretical basis for genome packing. Finally we suggest that, as a result of an internal protein unique to bacteriophage T7, the T7 genome may be significantly more ordered than is true for bacteriophage in general. PMID:16617089
Langevin dynamics simulations of genome packing in bacteriophage.
Forrey, Christopher; Muthukumar, M
2006-07-01
We use Langevin dynamics simulations to study the process by which a coarse-grained DNA chain is packaged within an icosahedral container. We focus our inquiry on three areas of interest in viral packing: the evolving structure of the packaged DNA condensate; the packing velocity; and the internal buildup of energy and resultant forces. Each of these areas has been studied experimentally, and we find that we can qualitatively reproduce experimental results. However, our findings also suggest that the phage genome packing process is fundamentally different than that suggested by the inverse spool model. We suggest that packing in general does not proceed in the deterministic fashion of the inverse-spool model, but rather is stochastic in character. As the chain configuration becomes compressed within the capsid, the structure, energy, and packing velocity all become dependent upon polymer dynamics. That many observed features of the packing process are rooted in condensed-phase polymer dynamics suggests that statistical mechanics, rather than mechanics, should serve as the proper theoretical basis for genome packing. Finally we suggest that, as a result of an internal protein unique to bacteriophage T7, the T7 genome may be significantly more ordered than is true for bacteriophage in general.
Goal Directed Model Inversion: A Study of Dynamic Behavior
NASA Technical Reports Server (NTRS)
Colombano, Silvano P.; Compton, Michael; Raghavan, Bharathi; Lum, Henry, Jr. (Technical Monitor)
1994-01-01
Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome 0 "would have been right if the outcome had been the desired one." The algorithm then proceeds as follows: (1) store the action that produced the wrong outcome as a "target" (2) redefine the wrong outcome as a desired goal (3) submit the new desired goal to the system (4) compare the new action with the target action and modify the system by using a suitable algorithm for credit assignment (Back propagation in our example) (5) resubmit the original goal. Prior publications by our group in this area focused on demonstrating empirical results based on the inverse kinematic problem for a simulated robotic arm. In this paper we apply the inversion process to much simpler analytic functions in order to elucidate the dynamic behavior of the system and to determine the sensitivity of the learning process to various parameters. This understanding will be necessary for the acceptance of GDMI as a practical tool.
Bayesian inversions of a dynamic vegetation model in four European grassland sites
NASA Astrophysics Data System (ADS)
Minet, J.; Laloy, E.; Tychon, B.; François, L.
2015-01-01
Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB dynamic vegetation model (DVM) with ten unknown parameters, using the DREAM(ZS) Markov chain Monte Carlo (MCMC) sampler. We compare model inversions considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a~priori or jointly inferred with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root-mean-square error (RMSE) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19 g C m-2 day-1, 1.04 to 1.56 g C m-2 day-1, and 0.50 to 1.28 mm day-1, respectively. In validation, mismatches between measured and simulated data are larger, but still with Nash-Sutcliffe efficiency scores above 0.5 for three out of the four sites. Although measurement errors associated with eddy covariance data are known to be heteroscedastic, we showed that assuming a classical linear heteroscedastic model of the residual errors in the inversion do not fully remove heteroscedasticity. Since the employed heteroscedastic error model allows for larger deviations between simulated and measured data as the magnitude of the measured data increases, this error model expectedly lead to poorer data fitting compared to inversions considering a constant variance of the residual errors. Furthermore, sampling the residual error variances along with model parameters results in overall similar model parameter posterior distributions as those obtained by fixing these variances beforehand, while slightly improving model performance. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides model behaviour, difference between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics. Lastly, the possibility of finding a common set of parameters among the four experimental sites is discussed.
2014-01-01
An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method. PMID:24782676
Zhu, Bing; Chen, Yizhou; Zhao, Jian
2014-01-01
An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method.
Gender recognition from vocal source
NASA Astrophysics Data System (ADS)
Sorokin, V. N.; Makarov, I. S.
2008-07-01
Efficiency of automatic recognition of male and female voices based on solving the inverse problem for glottis area dynamics and for waveform of the glottal airflow volume velocity pulse is studied. The inverse problem is regularized through the use of analytical models of the voice excitation pulse and of the dynamics of the glottis area, as well as the model of one-dimensional glottal airflow. Parameters of these models and spectral parameters of the volume velocity pulse are considered. The following parameters are found to be most promising: the instant of maximum glottis area, the maximum derivative of the area, the slope of the spectrum of the glottal airflow volume velocity pulse, the amplitude ratios of harmonics of this spectrum, and the pitch. On the plane of the first two main components in the space of these parameters, an almost twofold decrease in the classification error relative to that for the pitch alone is attained. The male voice recognition probability is found to be 94.7%, and the female voice recognition probability is 95.9%.
System parameter identification from projection of inverse analysis
NASA Astrophysics Data System (ADS)
Liu, K.; Law, S. S.; Zhu, X. Q.
2017-05-01
The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.
jInv: A Modular and Scalable Framework for Electromagnetic Inverse Problems
NASA Astrophysics Data System (ADS)
Belliveau, P. T.; Haber, E.
2016-12-01
Inversion is a key tool in the interpretation of geophysical electromagnetic (EM) data. Three-dimensional (3D) EM inversion is very computationally expensive and practical software for inverting large 3D EM surveys must be able to take advantage of high performance computing (HPC) resources. It has traditionally been difficult to achieve those goals in a high level dynamic programming environment that allows rapid development and testing of new algorithms, which is important in a research setting. With those goals in mind, we have developed jInv, a framework for PDE constrained parameter estimation problems. jInv provides optimization and regularization routines, a framework for user defined forward problems, and interfaces to several direct and iterative solvers for sparse linear systems. The forward modeling framework provides finite volume discretizations of differential operators on rectangular tensor product meshes and tetrahedral unstructured meshes that can be used to easily construct forward modeling and sensitivity routines for forward problems described by partial differential equations. jInv is written in the emerging programming language Julia. Julia is a dynamic language targeted at the computational science community with a focus on high performance and native support for parallel programming. We have developed frequency and time-domain EM forward modeling and sensitivity routines for jInv. We will illustrate its capabilities and performance with two synthetic time-domain EM inversion examples. First, in airborne surveys, which use many sources, we achieve distributed memory parallelism by decoupling the forward and inverse meshes and performing forward modeling for each source on small, locally refined meshes. Secondly, we invert grounded source time-domain data from a gradient array style induced polarization survey using a novel time-stepping technique that allows us to compute data from different time-steps in parallel. These examples both show that it is possible to invert large scale 3D time-domain EM datasets within a modular, extensible framework written in a high-level, easy to use programming language.
Technical Note: Approximate Bayesian parameterization of a complex tropical forest model
NASA Astrophysics Data System (ADS)
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2013-08-01
Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.
NASA Technical Reports Server (NTRS)
Cho, Jeongho; Principe, Jose C.; Erdogmus, Deniz; Motter, Mark A.
2005-01-01
The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a SOM-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.
A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Osei-Kuffuor, Daniel; Fattebert, Jean-Luc
2014-01-01
Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N 3) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix,more » based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.« less
A new full-Stokes model as a tool for basal inversions.
NASA Astrophysics Data System (ADS)
Kyrke-Smith, Teresa M.; Hilmar Gudmundsson, G.; Farrell, Patrick E.
2016-04-01
High resolution models of ice sheet dynamics are required to make accurate predictions of the future mass balance of ice sheets. These require knowledge of flow conditions at the bed of the ice, however, the inaccessibility of the bed means there exist few observational constraints. Inverse methods are therefore commonly used to obtain information about the nature of basal control using given surface observations. We present a new 3D Stokes solver written using FEniCS with the potential to carry out second-order inversions for basal slipperiness. We will be applying the model to Pine Island Glacier, Antarctica. Pine Island Glacier is one of the fastest flowing and most rapidly changing ice streams in Antarctica, and is currently contributing to sea-level rise at an increasing rate. Recent field seasons as part of the iSTAR project have acquired high-resolution in-situ geophysical measurements; results from our model will be compared with these to try and increase understanding about the conditions at the bed of Pine Island Glacier.
Dynamics of a multimode semiconductor laser with optical feedback
DOE Office of Scientific and Technical Information (OSTI.GOV)
Koryukin, I. V.
A new model of a multi-longitudinal-mode semiconductor laser with weak optical feedback is proposed. This model generalizes the well-known Tang-Statz-deMars equations, which are derived from the first principles and adequately describe solid-state lasers to a semiconductor active medium. Steady states of the model and the spectrum of relaxation oscillations are found, and the laser dynamics in the chaotic regime of low-frequency fluctuations of intensity is investigated. It is established that the dynamic properties of the proposed model depend mainly on the carrier diffusion, which controls mode-mode coupling in the active medium via spread of gratings of spatial inversion. The resultsmore » obtained are compared with the predictions of previous semiphenomenological models and the scope of applicability of these models is determined.« less
NASA Technical Reports Server (NTRS)
Ostroff, Aaron J.
1998-01-01
This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.
Identification of dynamic characteristics of flexible rotors as dynamic inverse problem
NASA Technical Reports Server (NTRS)
Roisman, W. P.; Vajingortin, L. D.
1991-01-01
The problem of dynamic and balancing of flexible rotors were considered, which were set and solved as the problem of the identification of flexible rotor systems, which is the same as the inverse problem of the oscillation theory dealing with the task of the identifying the outside influences and system parameters on the basis of the known laws of motion. This approach to the problem allows the disclosure the picture of disbalances throughout the rotor-under-test (which traditional methods of flexible rotor balancing, based on natural oscillations, could not provide), and identify dynamic characteristics of the system, which correspond to a selected mathematical model. Eventually, various methods of balancing were developed depending on the special features of the machines as to their design, technology, and operation specifications. Also, theoretical and practical methods are given for the flexible rotor balancing at far from critical rotation frequencies, which does not necessarily require the knowledge forms of oscillation, dissipation, and elasticity and inertia characteristics, and to use testing masses.
NASA Astrophysics Data System (ADS)
di Volo, Matteo; Burioni, Raffaella; Casartelli, Mario; Livi, Roberto; Vezzani, Alessandro
2016-01-01
We study the dynamics of networks with inhibitory and excitatory leak-integrate-and-fire neurons with short-term synaptic plasticity in the presence of depressive and facilitating mechanisms. The dynamics is analyzed by a heterogeneous mean-field approximation, which allows us to keep track of the effects of structural disorder in the network. We describe the complex behavior of different classes of excitatory and inhibitory components, which give rise to a rich dynamical phase diagram as a function of the fraction of inhibitory neurons. Using the same mean-field approach, we study and solve a global inverse problem: reconstructing the degree probability distributions of the inhibitory and excitatory components and the fraction of inhibitory neurons from the knowledge of the average synaptic activity field. This approach unveils new perspectives on the numerical study of neural network dynamics and the possibility of using these models as a test bed for the analysis of experimental data.
NASA Astrophysics Data System (ADS)
Cui, Yi-an; Liu, Lanbo; Zhu, Xiaoxiong
2017-08-01
Monitoring the extent and evolution of contaminant plumes in local and regional groundwater systems from existing landfills is critical in contamination control and remediation. The self-potential survey is an efficient and economical nondestructive geophysical technique that can be used to investigate underground contaminant plumes. Based on the unscented transform, we have built a Kalman filtering cycle to conduct time-lapse data assimilation for monitoring the transport of solute based on the solute transport experiment using a bench-scale physical model. The data assimilation was formed by modeling the evolution based on the random walk model and observation correcting based on the self-potential forward. Thus, monitoring self-potential data can be inverted by the data assimilation technique. As a result, we can reconstruct the dynamic process of the contaminant plume instead of using traditional frame-to-frame static inversion, which may cause inversion artifacts. The data assimilation inversion algorithm was evaluated through noise-added synthetic time-lapse self-potential data. The result of the numerical experiment shows validity, accuracy and tolerance to the noise of the dynamic inversion. To validate the proposed algorithm, we conducted a scaled-down sandbox self-potential observation experiment to generate time-lapse data that closely mimics the real-world contaminant monitoring setup. The results of physical experiments support the idea that the data assimilation method is a potentially useful approach for characterizing the transport of contamination plumes using the unscented Kalman filter (UKF) data assimilation technique applied to field time-lapse self-potential data.
1992-09-01
finding an inverse plant such as was done by Bertrand [BD91] and by Levin, Gewirtzman and Inbar in a binary type inverse controller [LGI91], to self tuning...gain robust control. 2) Self oscillating adaptive controller. 3) Gain scheduling. 4) Self tuning. 5) Model-reference adaptive systems. Although the...of multidimensional systems (CS881 as well as aircraft [HG90]. The self oscillating method is also a feedback based mechanism, utilizing a relay in the
Trajectory optimization for the National Aerospace Plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1992-01-01
The primary objective of this research is to develop an efficient and robust trajectory optimization tool for the optimal ascent problem of the National Aerospace Plane (NASP). This report is organized in the following order to summarize the complete work: Section two states the formulation and models of the trajectory optimization problem. An inverse dynamics approach to the problem is introduced in Section three. Optimal trajectories corresponding to various conditions and performance parameters are presented in Section four. A midcourse nonlinear feedback controller is developed in Section five. Section six demonstrates the performance of the inverse dynamics approach and midcourse controller during disturbances. Section seven discusses rocket assisted ascent which may be beneficial when orbital altitude is high. Finally, Section eight recommends areas of future research.
Transdimensional, hierarchical, Bayesian inversion of ambient seismic noise: Australia
NASA Astrophysics Data System (ADS)
Crowder, E.; Rawlinson, N.; Cornwell, D. G.
2017-12-01
We present models of crustal velocity structure in southeastern Australia using a novel, transdimensional and hierarchical, Bayesian inversion approach. The inversion is applied to long-time ambient noise cross-correlations. The study area of SE Australia is thought to represent the eastern margin of Gondwana. Conflicting tectonic models have been proposed to explain the formation of eastern Gondwana and the enigmatic geological relationships in Bass Strait, which separates Tasmania and the mainland. A geologically complex area of crustal accretion, Bass Strait may contain part of an exotic continental block entrained in colliding crusts. Ambient noise data recorded by an array of 24 seismometers is used to produce a high resolution, 3D shear wave velocity model of Bass Strait. Phase velocity maps in the period range 2-30 s are produced and subsequently inverted for 3D shear wave velocity structure. The transdimensional, hierarchical Bayesian, inversion technique is used. This technique proves far superior to linearised inversion. The inversion model is dynamically parameterised during the process, implicitly controlled by the data, and noise is treated as an inversion unknown. The resulting shear wave velocity model shows three sedimentary basins in Bass Strait constrained by slow shear velocities (2.4-2.9 km/s) at 2-10 km depth. These failed rift basins from the breakup of Australia-Antartica appear to be overlying thinned crust, where typical mantle velocities of 3.8-4.0 km/s occur at depths greater than 20 km. High shear wave velocities ( 3.7-3.8 km/s) in our new model also match well with regions of high magnetic and gravity anomalies. Furthermore, we use both Rayleigh and Love wave phase data to to construct Vsv and Vsh maps. These are used to estimate crustal radial anisotropy in the Bass Strait. We interpret that structures delineated by our velocity models support the presence and extent of the exotic Precambrian micro-continent (the Selwyn Block) that was most likely entrained during crustal accretion.
Discrete Inverse and State Estimation Problems
NASA Astrophysics Data System (ADS)
Wunsch, Carl
2006-06-01
The problems of making inferences about the natural world from noisy observations and imperfect theories occur in almost all scientific disciplines. This book addresses these problems using examples taken from geophysical fluid dynamics. It focuses on discrete formulations, both static and time-varying, known variously as inverse, state estimation or data assimilation problems. Starting with fundamental algebraic and statistical ideas, the book guides the reader through a range of inference tools including the singular value decomposition, Gauss-Markov and minimum variance estimates, Kalman filters and related smoothers, and adjoint (Lagrange multiplier) methods. The final chapters discuss a variety of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for graduate students and researchers in oceanography, meteorology, climate dynamics, and geophysical fluid dynamics. It is also accessible to a wider scientific audience; the only prerequisite is an understanding of linear algebra. Provides a comprehensive introduction to discrete methods of inference from incomplete information Based upon 25 years of practical experience using real data and models Develops sequential and whole-domain analysis methods from simple least-squares Contains many examples and problems, and web-based support through MIT opencourseware
Enhancing Autonomy of Aerial Systems Via Integration of Visual Sensors into Their Avionics Suite
2016-09-01
aerial platform for subsequent visual sensor integration. 14. SUBJECT TERMS autonomous system, quadrotors, direct method, inverse ...CONTROLLER ARCHITECTURE .....................................................43 B. INVERSE DYNAMICS IN THE VIRTUAL DOMAIN ......................45 1...control station GPS Global-Positioning System IDVD inverse dynamics in the virtual domain ILP integer linear program INS inertial-navigation system
The Shock and Vibration Bulletin. Part 2. Structural Analysis, Design Techniques
1973-06-01
FLOATING SHOCK PLATFORM SUBJECTED TO UNDERWATER EXPLOSIONS R. P. Brooks, and B. C, McNalght Naval Air Engineering Center Philadelphia, Pa, A lumped...Lohwasser, Air Force Flight Dynamics Laboratory, Wright -Patterson APB, Ohio AN ALGORITHM FOR SEMI-INVERSE ANALYSIS OF NONLINEAR DYNAMIC SYSTEMS ... 65 R...MATHEMATICAL MODEL OF A TYPICAL.FOATING SHOCK PLATFORM SSUBJECTED TO-UNDERWATE- EXPLOSIONS .......... ...................... 143 R. P. Brooks and B. C
NASA Astrophysics Data System (ADS)
Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han
2016-09-01
Motion control of the piezoactuator system over broadband frequencies is limited due to its inherent hysteresis and system dynamics. One of the suggested ways is to use feedforward controller to linearize the input-output relationship of the piezoactuator system. Although there have been many feedforward approaches, it is still a challenge to develop feedforward controller for the piezoactuator system at high frequency. Hence, this paper presents a comprehensive inversion approach in consideration of the coupling of hysteresis and dynamics. In this work, the influence of dynamics compensation on the input-output relationship of the piezoactuator system is investigated first. With system dynamics compensation, the input-output relationship of the piezoactuator system will be further represented as rate-dependent nonlinearity due to the inevitable dynamics compensation error, especially at high frequency. Base on this result, the feedforward controller composed by a cascade of linear dynamics inversion and rate-dependent nonlinearity inversion is developed. Then, the system identification of the comprehensive inversion approach is proposed. Finally, experimental results show that the proposed approach can improve the performance on tracking of both periodic and non-periodic trajectories at medium and high frequency compared with the conventional feedforward approaches.
Huang, Weidong; Li, Kun; Wang, Gan; Wang, Yingzhe
2013-11-01
In this article, we present a newly designed inverse umbrella surface aerator, and tested its performance in driving flow of an oxidation ditch. Results show that it has a better performance in driving the oxidation ditch than the original one with higher average velocity and more uniform flow field. We also present a computational fluid dynamics model for predicting the flow field in an oxidation ditch driven by a surface aerator. The improved momentum source term approach to simulate the flow field of the oxidation ditch driven by an inverse umbrella surface aerator was developed and validated through experiments. Four kinds of turbulent models were investigated with the approach, including the standard k - ɛ model, RNG k - ɛ model, realizable k - ɛ model, and Reynolds stress model, and the predicted data were compared with those calculated with the multiple rotating reference frame approach (MRF) and sliding mesh approach (SM). Results of the momentum source term approach are in good agreement with the experimental data, and its prediction accuracy is better than MRF, close to SM. It is also found that the momentum source term approach has lower computational expenses, is simpler to preprocess, and is easier to use.
2017-04-01
crosstalk); analysis of tested subjects underway. 4) Developed analytical methods to obtain knee joint loads using EMG-driven inverse dynamics; analysis of...13/2018. Completion %: 40. Task 1.3: EMG-driven inverse dynamic (ID) analyses with OpenSim for amputee and control group subjects. Target date: 1...predicted by EMG-driven inverse dynamics. Two-three conference papers are being prepared for submission in February 2017. Other achievements. None
Mirus, B.B.; Perkins, K.S.; Nimmo, J.R.; Singha, K.
2009-01-01
To understand their relation to pedogenic development, soil hydraulic properties in the Mojave Desert were investi- gated for three deposit types: (i) recently deposited sediments in an active wash, (ii) a soil of early Holocene age, and (iii) a highly developed soil of late Pleistocene age. Eff ective parameter values were estimated for a simplifi ed model based on Richards' equation using a fl ow simulator (VS2D), an inverse algorithm (UCODE-2005), and matric pressure and water content data from three ponded infi ltration experiments. The inverse problem framework was designed to account for the eff ects of subsurface lateral spreading of infi ltrated water. Although none of the inverse problems converged on a unique, best-fi t parameter set, a minimum standard error of regression was reached for each deposit type. Parameter sets from the numerous inversions that reached the minimum error were used to develop probability distribu tions for each parameter and deposit type. Electrical resistance imaging obtained for two of the three infi ltration experiments was used to independently test fl ow model performance. Simulations for the active wash and Holocene soil successfully depicted the lateral and vertical fl uxes. Simulations of the more pedogenically developed Pleistocene soil did not adequately replicate the observed fl ow processes, which would require a more complex conceptual model to include smaller scale heterogeneities. The inverse-modeling results, however, indicate that with increasing age, the steep slope of the soil water retention curve shitis toward more negative matric pressures. Assigning eff ective soil hydraulic properties based on soil age provides a promising framework for future development of regional-scale models of soil moisture dynamics in arid environments for land-management applications. ?? Soil Science Society of America.
The Tropopause Inversion Layer: New Observations, New Theories
NASA Astrophysics Data System (ADS)
Tandon, N.; Randel, W. J.; Pan, L.; Son, S.; Polvani, L. M.
2009-12-01
There is now great interest in the tropopause inversion inversion layer (TIL), a 1-2 km region just above the tropopause where there is a spike in static stability. Radio occultation data from the COSMIC GPS mission are providing an unprecedented level of spatial and temporal resolution with which to analyze the TIL. We start by showing the agreement between GPS data and radiosondes. We then examine the causes and consequences of the TIL. Observations from the ACE satellite and fixed dynamical heating calculations suggest strong roles for water vapor and ozone in the formation and modulation of the TIL. This agrees with observations showing a large TIL in the polar winter, where water vapor levels are persistently high. It is also clear that TIL strength is related to vorticity, but observations and models have important differences that need to be reconciled. These dynamical considerations dovetail with observations showing high TIL variability in the storm-track regions. Finally there is evidence from ozonesonde data that the TIL may be coupled to transport across the tropopause.
NASA Astrophysics Data System (ADS)
Siegenthaler-Le Drian, C.; Spichtinger, P.; Lohmann, U.
2010-09-01
Marine stratocumulus-capped boundary layers exhibit a strong net cooling impact on the Earth-Atmosphere system. Moreover, they are highly persistent over subtropical oceans. Therefore climate models need to represent them well in order to make reliable projections of future climate. One of the reasons for the absence of stratocumuli in the general circulation model ECHAM5-HAM (Roeckner et al., 2003; Stier et al., 2005) is due to the limited vertical resolution. In the current model version, no vertical sub-grid scale variability of clouds is taken into account, such that clouds occupy the full vertical layer. Around the inversion on top of the planetary boundary layer (PBL), conserved variables often have a steep gradient, which in a GCM may produce large discretization errors (Bretherton and Park, 2009). This inversion has a large diurnal cycle and varies with location around the globe, which is difficult to represent in a classical, coarse Eulerian approach. Furthermore, Lenderink and Holtslag (2000) and Lock (2001) showed that an inconsistent numerical representation between the entrainment parametrization and the other schemes, particularly with the vertical advection can lead to the occurrence of 'numerical entrainment'. The problem can be resolved by introducing a dynamical inversion as introduced by Grenier and Bretherton (2001) and Lock (2001). As these features can be seen in our version of ECHAM5-HAM, our implementation is aimed to reduce the numerical entrainment and to better represent stratocumuli in ECHAM5-HAM. To better resolve stratocumulus clouds, their inversion and the interaction between the turbulent diffusion and the vertical advection, the vertical grid is dynamically refined. The new grid is based on the reconstruction of the profiles of variables experiencing a sharp gradient (temperature, mixing ratio) applying the method presented in Grenier and Bretherton (2001). In typical stratocumulus regions, an additional grid level is thus associated with the PBL top. In case a cloud can be formed, a new level is associated with the lifting condensation level as well. The regular grid plus the two additional levels define the new dynamical grid, which varies geographically and temporally. The physical processes are computed on this new dynamical grid, Consequently, the sharp gradients and the interaction between the different processes can be better resolved. Some results of this new parametrization will be presented. On a single column model set-up, the reconstruction method accurately finds the inversion at the PBL top for the EPIC stratocumulus case. Also, on a global scale, the occurrence of a successful reconstruction, which is restricted in typical stratocumulus regions, occurs with a high frequency. The impact of the new dynamical grid on clouds and the radiation balance will be presented in the talk. References [Bretherton and Park, 2009] Bretherton, C. S. and Park, S. (2009). A new moist turbulence parametrization in the community atmosphere model. J. Climate, 22:3422-3448. [Grenier and Bretherton, 2001] Grenier, H. and Bretherton, C. S. (2001). A moist parametrization for large-scale models and its application to subtropical cloud-topped marine boundary layers. Mon. Wea. Rev., 129:357-377. [Lenderink and Holtslag, 2000] Lenderink, G. and Holtslag, A. M. (2000). Evaluation of the kinetic energy approach for modeling turbulent fluxes in stratocumulus. Mon. Wea. Rev., 128:244-258. [Lock, 2001] Lock, A. P. (2001). The numerical representation of entrainment in parametrizations of boundary layer turbulent mixing. Mon. Wea. Rev., 129:1148-1163. [Roeckner et al., 2003] Roeckner, E., Bäuml, G., Bonaventura, L. et al. (2003). The atmospheric general circulation model echam5, part I: Model description. Technical Report 349, Max-Planck-Institute for Meteorology, Hamburg,Germany. [Stier et al., 2005] Stier, P., Feichter, J., Kinne, S. et al. (2005). The aerosol-climate model ECHAM5-HAM. Atmos. Chem. Phys., 5:1125-1156.
Antisynchronization of Two Complex Dynamical Networks
NASA Astrophysics Data System (ADS)
Banerjee, Ranjib; Grosu, Ioan; Dana, Syamal K.
A nonlinear type open-plus-closed-loop (OPCL) coupling is investi-gated for antisynchronization of two complex networks under unidirectional and bidirectional interactions where each node of the networks is considered as a continuous dynamical system. We present analytical results for antisynchroni-zation in identical networks. A numerical example is given for unidirectional coupling with each node represented by a spiking-bursting type Hindmarsh-Rose neuron model. Antisynchronization for mutual interaction is allowed only to inversion symmetric dynamical systems as chosen nodes.
4D Subject-Specific Inverse Modeling of the Chick Embryonic Heart Outflow Tract Hemodynamics
Goenezen, Sevan; Chivukula, Venkat Keshav; Midgett, Madeline; Phan, Ly; Rugonyi, Sandra
2015-01-01
Blood flow plays a critical role in regulating embryonic cardiac growth and development, with altered flow leading to congenital heart disease. Progress in the field, however, is hindered by a lack of quantification of hemodynamic conditions in the developing heart. In this study, we present a methodology to quantify blood flow dynamics in the embryonic heart using subject-specific computational fluid dynamics (CFD) models. While the methodology is general, we focused on a model of the chick embryonic heart outflow tract (OFT), which distally connects the heart to the arterial system, and is the region of origin of many congenital cardiac defects. Using structural and Doppler velocity data collected from optical coherence tomography (OCT), we generated 4D (3D + time) embryo-specific CFD models of the heart OFT. To replicate the blood flow dynamics over time during the cardiac cycle, we developed an iterative inverse-method optimization algorithm, which determines the CFD model boundary conditions such that differences between computed velocities and measured velocities at one point within the OFT lumen are minimized. Results from our developed CFD model agree with previously measured hemodynamics in the OFT. Further, computed velocities and measured velocities differ by less than 15% at locations that were not used in the optimization, validating the model. The presented methodology can be used in quantifications of embryonic cardiac hemodynamics under normal and altered blood flow conditions, enabling an in depth quantitative study of how blood flow influences cardiac development. PMID:26361767
Query-based learning for aerospace applications.
Saad, E W; Choi, J J; Vian, J L; Wunsch, D C Ii
2003-01-01
Models of real-world applications often include a large number of parameters with a wide dynamic range, which contributes to the difficulties of neural network training. Creating the training data set for such applications becomes costly, if not impossible. In order to overcome the challenge, one can employ an active learning technique known as query-based learning (QBL) to add performance-critical data to the training set during the learning phase, thereby efficiently improving the overall learning/generalization. The performance-critical data can be obtained using an inverse mapping called network inversion (discrete network inversion and continuous network inversion) followed by oracle query. This paper investigates the use of both inversion techniques for QBL learning, and introduces an original heuristic to select the inversion target values for continuous network inversion method. Efficiency and generalization was further enhanced by employing node decoupled extended Kalman filter (NDEKF) training and a causality index (CI) as a means to reduce the input search dimensionality. The benefits of the overall QBL approach are experimentally demonstrated in two aerospace applications: a classification problem with large input space and a control distribution problem.
Dynamic Inversion based Control of a Docking Mechanism
NASA Technical Reports Server (NTRS)
Kulkarni, Nilesh V.; Ippolito, Corey; Krishnakumar, Kalmanje
2006-01-01
The problem of position and attitude control of the Stewart platform based docking mechanism is considered motivated by its future application in space missions requiring the autonomous docking capability. The control design is initiated based on the framework of the intelligent flight control architecture being developed at NASA Ames Research Center. In this paper, the baseline position and attitude control system is designed using dynamic inversion with proportional-integral augmentation. The inverse dynamics uses a Newton-Euler formulation that includes the platform dynamics, the dynamics of the individual legs along with viscous friction in the joints. Simulation results are presented using forward dynamics simulated by a commercial physics engine that builds the system as individual elements with appropriate joints and uses constrained numerical integration,
Robust state preparation in quantum simulations of Dirac dynamics
NASA Astrophysics Data System (ADS)
Song, Xue-Ke; Deng, Fu-Guo; Lamata, Lucas; Muga, J. G.
2017-02-01
A nonrelativistic system such as an ultracold trapped ion may perform a quantum simulation of a Dirac equation dynamics under specific conditions. The resulting Hamiltonian and dynamics are highly controllable, but the coupling between momentum and internal levels poses some difficulties to manipulate the internal states accurately in wave packets. We use invariants of motion to inverse engineer robust population inversion processes with a homogeneous, time-dependent simulated electric field. This exemplifies the usefulness of inverse-engineering techniques to improve the performance of quantum simulation protocols.
Finite element dynamic analysis of soft tissues using state-space model.
Iorga, Lucian N; Shan, Baoxiang; Pelegri, Assimina A
2009-04-01
A finite element (FE) model is employed to investigate the dynamic response of soft tissues under external excitations, particularly corresponding to the case of harmonic motion imaging. A solid 3D mixed 'u-p' element S8P0 is implemented to capture the near-incompressibility inherent in soft tissues. Two important aspects in structural modelling of these tissues are studied; these are the influence of viscous damping on the dynamic response and, following FE-modelling, a developed state-space formulation that valuates the efficiency of several order reduction methods. It is illustrated that the order of the mathematical model can be significantly reduced, while preserving the accuracy of the observed system dynamics. Thus, the reduced-order state-space representation of soft tissues for general dynamic analysis significantly reduces the computational cost and provides a unitary framework for the 'forward' simulation and 'inverse' estimation of soft tissues. Moreover, the results suggest that damping in soft-tissue is significant, effectively cancelling the contribution of all but the first few vibration modes.
The changing phenology of the land carbon fluxes as derived from atmospheric CO2 data
NASA Astrophysics Data System (ADS)
Cescatti, A.; Alkama, R.; Forzieri, G.; Rödenbeck, C.; Zaehle, S.; Sitch, S.; Friedlingstein, P.; Nabel, J.; Viovy, N.; Kato, E.; Koven, C.; Zeng, N.; Ciais, P.
2017-12-01
Dynamic vegetation models and atmospheric observations of CO2 concentration point to a large increase of the global terrestrial carbon uptake over the recent decades. However, they disagree on the key regions, on the seasonality and on the processes underlying such a persistent increase. In particular, the role of the changing plant phenology on the global carbon budget is still unknown. To investigate these issues we explored the temporal dynamic of the land carbon fluxes over 1981-2014 using the Jena CarboScope atmospheric CO2 inversion and an ensemble of land surface models (TRENDY). Using these datasets the temporal extent and timing of the land carbon uptake and carbon release period have been investigated in four different latitudinal bands (75N-45N; 45N-15N; 15N-15S; 15S-45S) to explore the recent changes in the phenology of the vegetation CO2 exchange across different climates and biomes. The impact of phenological changes on the land carbon flux has been investigated by factoring out the signal due to the length of the growing season from the other signals. Estimates retrieved from the atmospheric inversion have been compared with the prediction of the ensemble of vegetation models. Results shows that the changes in the global carbon fluxes occurred in the last three decades are dominated by the duration and intensification of the uptake during the growing season. Interestingly, the seasonality of the trends shows a consistent pattern at all latitudinal bands, with a systematic advancement of the onset and minor changes of the end dates of the growing season. According to the atmospheric inversion the increasing trend in the land sink is driven about equally by the changes in phenology (due to the earlier onset and later offset) and by the intensification of the daily uptake. The increased annual carbon uptake revealed by the atmospheric inversion is about 60% larger than the model predictions, possibly due to the model underestimation of land use flues and poor representation of climate-driven changes in phenology. The observed large and persistent variations in the phenology of the terrestrial carbon fluxes emphasize the ongoing rapid changes in boreal and tropical biomes, whose dynamic response to climate change and rising CO2 concentration is still poorly represented in vegetation models.
The Sensitivity of Joint Inversions of Seismic and Geodynamic Data to Mantle Viscosity
NASA Astrophysics Data System (ADS)
Lu, C.; Grand, S. P.; Forte, A. M.; Simmons, N. A.
2017-12-01
Seismic tomography has mapped the existence of large scale mantle heterogeneities in recent years. However, the origin of these velocity anomalies in terms of chemical and thermal variations is still under debate due to the limitations of tomography. Joint inversion of seismic, geodynamic, and mineral physics observations has proven to be a powerful tool to decouple thermal and chemical effects in the deep mantle (Simmons et al. 2010). The approach initially attempts to find a model that can be explained assuming temperature controls lateral variations in mantle properties and then to consider more complicated lateral variations that account for the presence of chemical heterogeneity to further fit data. The geodynamic observations include Earth's free air gravity field, tectonic plate motions, dynamic topography and the excess ellipticity of the core. The sensitivity of the geodynamic observables to density anomalies, however, depends on an assumed radial mantle viscosity profile. Here we perform joint inversions of seismic and geodynamic data using a number of published viscosity profiles. The goal is to test the sensitivity of joint inversion results to mantle viscosity. For each viscosity model, geodynamic sensitivity kernels are calculated and used to jointly invert the geodynamic observations as well as a new shear wave data set for a model of density and seismic velocity. Also, compared with previous joint inversion studies, two major improvements have been made in our inversion. First, we use a nonlinear inversion to account for anelastic effects. Applying the very fast simulate annealing (VFSA) method, we let the elastic scaling factor and anelastic parameters from mineral physics measurements vary within their possible ranges and find the best fitting model assuming thermal variations are the cause of the heterogeneity. We also include an a priori subducting slab model into the starting model. Thus the geodynamic and seismic signatures of short wavelength subducting slabs are better accounted for in the inversions. Reference: Simmons, N. A., A. M. Forte, L. Boschi, and S. P. Grand (2010), GyPSuM: A joint tomographic model of mantle density and seismic wave speeds, Journal of Geophysical Research: Solid Earth, 115(B12), B12310
Neural network based adaptive control for nonlinear dynamic regimes
NASA Astrophysics Data System (ADS)
Shin, Yoonghyun
Adaptive control designs using neural networks (NNs) based on dynamic inversion are investigated for aerospace vehicles which are operated at highly nonlinear dynamic regimes. NNs play a key role as the principal element of adaptation to approximately cancel the effect of inversion error, which subsequently improves robustness to parametric uncertainty and unmodeled dynamics in nonlinear regimes. An adaptive control scheme previously named 'composite model reference adaptive control' is further developed so that it can be applied to multi-input multi-output output feedback dynamic inversion. It can have adaptive elements in both the dynamic compensator (linear controller) part and/or in the conventional adaptive controller part, also utilizing state estimation information for NN adaptation. This methodology has more flexibility and thus hopefully greater potential than conventional adaptive designs for adaptive flight control in highly nonlinear flight regimes. The stability of the control system is proved through Lyapunov theorems, and validated with simulations. The control designs in this thesis also include the use of 'pseudo-control hedging' techniques which are introduced to prevent the NNs from attempting to adapt to various actuation nonlinearities such as actuator position and rate saturations. Control allocation is introduced for the case of redundant control effectors including thrust vectoring nozzles. A thorough comparison study of conventional and NN-based adaptive designs for a system under a limit cycle, wing-rock, is included in this research, and the NN-based adaptive control designs demonstrate their performances for two highly maneuverable aerial vehicles, NASA F-15 ACTIVE and FQM-117B unmanned aerial vehicle (UAV), operated under various nonlinearities and uncertainties.
Liu, X; Zhai, Z
2008-02-01
Indoor pollutions jeopardize human health and welfare and may even cause serious morbidity and mortality under extreme conditions. To effectively control and improve indoor environment quality requires immediate interpretation of pollutant sensor readings and accurate identification of indoor pollution history and source characteristics (e.g. source location and release time). This procedure is complicated by non-uniform and dynamic contaminant indoor dispersion behaviors as well as diverse sensor network distributions. This paper introduces a probability concept based inverse modeling method that is able to identify the source location for an instantaneous point source placed in an enclosed environment with known source release time. The study presents the mathematical models that address three different sensing scenarios: sensors without concentration readings, sensors with spatial concentration readings, and sensors with temporal concentration readings. The paper demonstrates the inverse modeling method and algorithm with two case studies: air pollution in an office space and in an aircraft cabin. The predictions were successfully verified against the forward simulation settings, indicating good capability of the method in finding indoor pollutant sources. The research lays a solid ground for further study of the method for more complicated indoor contamination problems. The method developed can help track indoor contaminant source location with limited sensor outputs. This will ensure an effective and prompt execution of building control strategies and thus achieve a healthy and safe indoor environment. The method can also assist the design of optimal sensor networks.
NASA Astrophysics Data System (ADS)
Paul, Subhajit; Das, Subir K.
2018-03-01
Via event-driven molecular dynamics simulations we study kinetics of clustering in assemblies of inelastic particles in various space dimensions. We consider two models, viz., the ballistic aggregation model (BAM) and the freely cooling granular gas model (GGM), for each of which we quantify the time dependence of kinetic energy and average mass of clusters (that form due to inelastic collisions). These quantities, for both the models, exhibit power-law behavior, at least in the long time limit. For the BAM, corresponding exponents exhibit strong dimension dependence and follow a hyperscaling relation. In addition, in the high packing fraction limit the behavior of these quantities become consistent with a scaling theory that predicts an inverse relation between energy and mass. On the other hand, in the case of the GGM we do not find any evidence for such a picture. In this case, even though the energy decay, irrespective of packing fraction, matches quantitatively with that for the high packing fraction picture of the BAM, it is inversely proportional to the growth of mass only in one dimension, and the growth appears to be rather insensitive to the choice of the dimension, unlike the BAM.
Robust Adaptive Flight Control Design of Air-breathing Hypersonic Vehicles
2016-12-07
dynamic inversion controller design for a non -minimum phase hypersonic vehicle is derived by Kuipers et al. [2008]. Moreover, integrated guidance and...stabilization time for inner loop variables is lesser than the intermediate loop variables because of the three-loop-control design methodology . The control...adaptive design . Control Engineering Practice, 2016. Michael A Bolender and David B Doman. A non -linear model for the longitudinal dynamics of a
NASA Astrophysics Data System (ADS)
Yoshimoto, Yuta; Li, Zhen; Kinefuchi, Ikuya; Karniadakis, George Em
2017-12-01
We propose a new coarse-grained (CG) molecular simulation technique based on the Mori-Zwanzig (MZ) formalism along with the iterative Boltzmann inversion (IBI). Non-Markovian dissipative particle dynamics (NMDPD) taking into account memory effects is derived in a pairwise interaction form from the MZ-guided generalized Langevin equation. It is based on the introduction of auxiliary variables that allow for the replacement of a non-Markovian equation with a Markovian one in a higher dimensional space. We demonstrate that the NMDPD model exploiting MZ-guided memory kernels can successfully reproduce the dynamic properties such as the mean square displacement and velocity autocorrelation function of a Lennard-Jones system, as long as the memory kernels are appropriately evaluated based on the Volterra integral equation using the force-velocity and velocity-velocity correlations. Furthermore, we find that the IBI correction of a pair CG potential significantly improves the representation of static properties characterized by a radial distribution function and pressure, while it has little influence on the dynamic processes. Our findings suggest that combining the advantages of both the MZ formalism and IBI leads to an accurate representation of both the static and dynamic properties of microscopic systems that exhibit non-Markovian behavior.
Computational structures for robotic computations
NASA Technical Reports Server (NTRS)
Lee, C. S. G.; Chang, P. R.
1987-01-01
The computational problem of inverse kinematics and inverse dynamics of robot manipulators by taking advantage of parallelism and pipelining architectures is discussed. For the computation of inverse kinematic position solution, a maximum pipelined CORDIC architecture has been designed based on a functional decomposition of the closed-form joint equations. For the inverse dynamics computation, an efficient p-fold parallel algorithm to overcome the recurrence problem of the Newton-Euler equations of motion to achieve the time lower bound of O(log sub 2 n) has also been developed.
Development of a database for the verification of trans-ionospheric remote sensing systems
NASA Astrophysics Data System (ADS)
Leitinger, R.
2005-08-01
Remote sensing systems need verification by means of in-situ data or by means of model data. In the case of ionospheric occultation inversion, ionosphere tomography and other imaging methods on the basis of satellite-to-ground or satellite-to-satellite electron content, the availability of in-situ data with adequate spatial and temporal co-location is a very rare case, indeed. Therefore the method of choice for verification is to produce artificial electron content data with realistic properties, subject these data to the inversion/retrieval method, compare the results with model data and apply a suitable type of “goodness of fit” classification. Inter-comparison of inversion/retrieval methods should be done with sets of artificial electron contents in a “blind” (or even “double blind”) way. The set up of a relevant database for the COST 271 Action is described. One part of the database will be made available to everyone interested in testing of inversion/retrieval methods. The artificial electron content data are calculated by means of large-scale models that are “modulated” in a realistic way to include smaller scale and dynamic structures, like troughs and traveling ionospheric disturbances.
Automated dynamic analytical model improvement for damped structures
NASA Technical Reports Server (NTRS)
Fuh, J. S.; Berman, A.
1985-01-01
A method is described to improve a linear nonproportionally damped analytical model of a structure. The procedure finds the smallest changes in the analytical model such that the improved model matches the measured modal parameters. Features of the method are: (1) ability to properly treat complex valued modal parameters of a damped system; (2) applicability to realistically large structural models; and (3) computationally efficiency without involving eigensolutions and inversion of a large matrix.
Adaptive control of robotic manipulators
NASA Technical Reports Server (NTRS)
Seraji, H.
1987-01-01
The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.
Inverse magnetic catalysis from improved holographic QCD in the Veneziano limit
NASA Astrophysics Data System (ADS)
Gürsoy, Umut; Iatrakis, Ioannis; Järvinen, Matti; Nijs, Govert
2017-03-01
We study the dependence of the chiral condensate on external magnetic field in the context of holographic QCD at large number of flavors. We consider a holographic QCD model where the flavor degrees of freedom fully backreact on the color dynamics. Perturbative QCD calculations have shown that B acts constructively on the chiral condensate, a phenomenon called "magnetic catalysis". In contrast, recent lattice calculations show that, depending on the number of flavors and temperature, the magnetic field may also act destructively, which is called "inverse magnetic catalysis". Here we show that the holographic theory is capable of both behaviors depending on the choice of parameters. For reasonable choice of the potentials entering the model we find qualitative agreement with the lattice expectations. Our results provide insight for the physical reasons behind the inverse magnetic catalysis. In particular, we argue that the backreaction of the flavors to the background geometry decatalyzes the condensate.
A regional high-resolution carbon flux inversion of North America for 2004
NASA Astrophysics Data System (ADS)
Schuh, A. E.; Denning, A. S.; Corbin, K. D.; Baker, I. T.; Uliasz, M.; Parazoo, N.; Andrews, A. E.; Worthy, D. E. J.
2010-05-01
Resolving the discrepancies between NEE estimates based upon (1) ground studies and (2) atmospheric inversion results, demands increasingly sophisticated techniques. In this paper we present a high-resolution inversion based upon a regional meteorology model (RAMS) and an underlying biosphere (SiB3) model, both running on an identical 40 km grid over most of North America. Current operational systems like CarbonTracker as well as many previous global inversions including the Transcom suite of inversions have utilized inversion regions formed by collapsing biome-similar grid cells into larger aggregated regions. An extreme example of this might be where corrections to NEE imposed on forested regions on the east coast of the United States might be the same as that imposed on forests on the west coast of the United States while, in reality, there likely exist subtle differences in the two areas, both natural and anthropogenic. Our current inversion framework utilizes a combination of previously employed inversion techniques while allowing carbon flux corrections to be biome independent. Temporally and spatially high-resolution results utilizing biome-independent corrections provide insight into carbon dynamics in North America. In particular, we analyze hourly CO2 mixing ratio data from a sparse network of eight towers in North America for 2004. A prior estimate of carbon fluxes due to Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) is constructed from the SiB3 biosphere model on a 40 km grid. A combination of transport from the RAMS and the Parameterized Chemical Transport Model (PCTM) models is used to forge a connection between upwind biosphere fluxes and downwind observed CO2 mixing ratio data. A Kalman filter procedure is used to estimate weekly corrections to biosphere fluxes based upon observed CO2. RMSE-weighted annual NEE estimates, over an ensemble of potential inversion parameter sets, show a mean estimate 0.57 Pg/yr sink in North America. We perform the inversion with two independently derived boundary inflow conditions and calculate jackknife-based statistics to test the robustness of the model results. We then compare final results to estimates obtained from the CarbonTracker inversion system and at the Southern Great Plains flux site. Results are promising, showing the ability to correct carbon fluxes from the biosphere models over annual and seasonal time scales, as well as over the different GPP and ER components. Additionally, the correlation of an estimated sink of carbon in the South Central United States with regional anomalously high precipitation in an area of managed agricultural and forest lands provides interesting hypotheses for future work.
He, W.; Anderson, R.N.
1998-08-25
A method is disclosed for inverting 3-D seismic reflection data obtained from seismic surveys to derive impedance models for a subsurface region, and for inversion of multiple 3-D seismic surveys (i.e., 4-D seismic surveys) of the same subsurface volume, separated in time to allow for dynamic fluid migration, such that small scale structure and regions of fluid and dynamic fluid flow within the subsurface volume being studied can be identified. The method allows for the mapping and quantification of available hydrocarbons within a reservoir and is thus useful for hydrocarbon prospecting and reservoir management. An iterative seismic inversion scheme constrained by actual well log data which uses a time/depth dependent seismic source function is employed to derive impedance models from 3-D and 4-D seismic datasets. The impedance values can be region grown to better isolate the low impedance hydrocarbon bearing regions. Impedance data derived from multiple 3-D seismic surveys of the same volume can be compared to identify regions of dynamic evolution and bypassed pay. Effective Oil Saturation or net oil thickness can also be derived from the impedance data and used for quantitative assessment of prospective drilling targets and reservoir management. 20 figs.
He, Wei; Anderson, Roger N.
1998-01-01
A method is disclosed for inverting 3-D seismic reflection data obtained from seismic surveys to derive impedance models for a subsurface region, and for inversion of multiple 3-D seismic surveys (i.e., 4-D seismic surveys) of the same subsurface volume, separated in time to allow for dynamic fluid migration, such that small scale structure and regions of fluid and dynamic fluid flow within the subsurface volume being studied can be identified. The method allows for the mapping and quantification of available hydrocarbons within a reservoir and is thus useful for hydrocarbon prospecting and reservoir management. An iterative seismic inversion scheme constrained by actual well log data which uses a time/depth dependent seismic source function is employed to derive impedance models from 3-D and 4-D seismic datasets. The impedance values can be region grown to better isolate the low impedance hydrocarbon bearing regions. Impedance data derived from multiple 3-D seismic surveys of the same volume can be compared to identify regions of dynamic evolution and bypassed pay. Effective Oil Saturation or net oil thickness can also be derived from the impedance data and used for quantitative assessment of prospective drilling targets and reservoir management.
Simple scaling of catastrophic landslide dynamics.
Ekström, Göran; Stark, Colin P
2013-03-22
Catastrophic landslides involve the acceleration and deceleration of millions of tons of rock and debris in response to the forces of gravity and dissipation. Their unpredictability and frequent location in remote areas have made observations of their dynamics rare. Through real-time detection and inverse modeling of teleseismic data, we show that landslide dynamics are primarily determined by the length scale of the source mass. When combined with geometric constraints from satellite imagery, the seismically determined landslide force histories yield estimates of landslide duration, momenta, potential energy loss, mass, and runout trajectory. Measurements of these dynamical properties for 29 teleseismogenic landslides are consistent with a simple acceleration model in which height drop and rupture depth scale with the length of the failing slope.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Manoli, Gabriele, E-mail: manoli@dmsa.unipd.it; Nicholas School of the Environment, Duke University, Durham, NC 27708; Rossi, Matteo
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequentialmore » inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.« less
Bai, Qifeng; Pérez-Sánchez, Horacio; Zhang, Yang; Shao, Yonghua; Shi, Danfeng; Liu, Huanxiang; Yao, Xiaojun
2014-08-14
The reported crystal structures of β2 adrenergic receptor (β2AR) reveal that the open and closed states of the water channel are correlated with the inactive and active conformations of β2AR. However, more details about the process by which the water channel states are affected by the active to inactive conformational change of β2AR remain illusive. In this work, molecular dynamics simulations are performed to study the dynamical inactive and active conformational change of β2AR induced by inverse agonist ICI 118,551. Markov state model analysis and free energy calculation are employed to explore the open and close states of the water channel. The simulation results show that inverse agonist ICI 118,551 can induce water channel opening during the conformational transition of β2AR. Markov state model (MSM) analysis proves that the energy contour can be divided into seven states. States S1, S2 and S5, which represent the active conformation of β2AR, show that the water channel is in the closed state, while states S4 and S6, which correspond to the intermediate state conformation of β2AR, indicate the water channel opens gradually. State S7, which represents the inactive structure of β2AR, corresponds to the full open state of the water channel. The opening mechanism of the water channel is involved in the ligand-induced conformational change of β2AR. These results can provide useful information for understanding the opening mechanism of the water channel and will be useful for the rational design of potent inverse agonists of β2AR.
Rendering potential wearable robot designs with the LOPES gait trainer.
Koopman, B; van Asseldonk, E H F; van der Kooij, H; van Dijk, W; Ronsse, R
2011-01-01
In recent years, wearable robots (WRs) for rehabilitation, personal assistance, or human augmentation are gaining increasing interest. To make these devices more energy efficient, radical changes to the mechanical structure of the device are being considered. However, it remains very difficult to predict how people will respond to, and interact with, WRs that differ in terms of mechanical design. Users may adjust their gait pattern in response to the mechanical restrictions or properties of the device. The goal of this pilot study is to show the feasibility of rendering the mechanical properties of different potential WR designs using the robotic gait training device LOPES. This paper describes a new method that selectively cancels the dynamics of LOPES itself and adds the dynamics of the rendered WR using two parallel inverse models. Adaptive frequency oscillators were used to get estimates of the joint position, velocity, and acceleration. Using the inverse models, different WR designs can be evaluated, eliminating the need to build several prototypes. As a proof of principle, we simulated the effect of a very simple WR that consisted of a mass attached to the ankles. Preliminary results show that we are partially able to cancel the dynamics of LOPES. Additionally, the simulation of the mass showed an increase in muscle activity but not in the same level as during the control, where subjects actually carried the mass. In conclusion, the results in this paper suggest that LOPES can be used to render different WRs. In addition, it is very likely that the results can be further optimized when more effort is put in retrieving proper estimations for the velocity and acceleration, which are required for the inverse models. © 2011 IEEE
Hu, Xingdi; Chen, Xinguang; Cook, Robert L.; Chen, Ding-Geng; Okafor, Chukwuemeka
2016-01-01
Background The probabilistic discrete event systems (PDES) method provides a promising approach to study dynamics of underage drinking using cross-sectional data. However, the utility of this approach is often limited because the constructed PDES model is often non-identifiable. The purpose of the current study is to attempt a new method to solve the model. Methods A PDES-based model of alcohol use behavior was developed with four progression stages (never-drinkers [ND], light/moderate-drinker [LMD], heavy-drinker [HD], and ex-drinker [XD]) linked with 13 possible transition paths. We tested the proposed model with data for participants aged 12–21 from the 2012 National Survey on Drug Use and Health (NSDUH). The Moore-Penrose (M-P) generalized inverse matrix method was applied to solve the proposed model. Results Annual transitional probabilities by age groups for the 13 drinking progression pathways were successfully estimated with the M-P generalized inverse matrix approach. Result from our analysis indicates an inverse “J” shape curve characterizing pattern of experimental use of alcohol from adolescence to young adulthood. We also observed a dramatic increase for the initiation of LMD and HD after age 18 and a sharp decline in quitting light and heavy drinking. Conclusion Our findings are consistent with the developmental perspective regarding the dynamics of underage drinking, demonstrating the utility of the M-P method in obtaining a unique solution for the partially-observed PDES drinking behavior model. The M-P approach we tested in this study will facilitate the use of the PDES approach to examine many health behaviors with the widely available cross-sectional data. PMID:26511344
Changing basal conditions during the speed-up of Jakobshavn Isbræ, Greenland
NASA Astrophysics Data System (ADS)
Habermann, M.; Truffer, M.; Maxwell, D.
2013-06-01
Ice-sheet outlet glaciers can undergo dynamic changes such as the rapid speed-up of Jakobshavn Isbræ following the disintegration of its floating ice tongue. These changes are associated with stress changes on the boundary of the ice mass. We investigate the basal conditions throughout a well-observed period of rapid change and evaluate parameterizations currently used in ice-sheet models. A Tikhonov inverse method with a Shallow Shelf Approximation forward model is used for diagnostic inversions for the years 1985, 2000, 2005, 2006 and 2008. Our ice softness, model norm, and regularization parameter choices are justified using the data-model misfit metric and the L-curve method. The sensitivity of the inversion results to these parameter choices is explored. We find a lowering of basal yield stress in the first 7 km of the 2008 grounding line and no significant changes higher upstream. The temporal evolution in the fast flow area is in broad agreement with a Mohr-Coulomb parameterization of basal shear stress, but with a till friction angle much lower than has been measured for till samples. The lowering of basal yield stress is significant within the uncertainties of the inversion, but it cannot be ruled out that there are other significant contributors to the acceleration of the glacier.
Quantum dynamics of a two-state system induced by a chirped zero-area pulse
NASA Astrophysics Data System (ADS)
Lee, Han-gyeol; Song, Yunheung; Kim, Hyosub; Jo, Hanlae; Ahn, Jaewook
2016-02-01
It is well known that area pulses make Rabi oscillation and chirped pulses in the adiabatic interaction regime induce complete population inversion of a two-state system. Here we show that chirped zero-area pulses could engineer an interplay between the adiabatic evolution and Rabi-like rotations. In a proof-of-principle experiment utilizing spectral chirping of femtosecond laser pulses with a resonant spectral hole, we demonstrate that the chirped zero-area pulses could induce, for example, complete population inversion and return of the cold rubidium atom two-state system. Experimental result agrees well with the theoretically considered overall dynamics, which could be approximately modeled to a Ramsey-like three-pulse interaction, where the x and z rotations are driven by the hole and the main pulse, respectively.
NASA Astrophysics Data System (ADS)
Zhang, Ye; Gong, Rongfang; Cheng, Xiaoliang; Gulliksson, Mårten
2018-06-01
This study considers the inverse source problem for elliptic partial differential equations with both Dirichlet and Neumann boundary data. The unknown source term is to be determined by additional boundary conditions. Unlike the existing methods found in the literature, which usually employ the first-order in time gradient-like system (such as the steepest descent methods) for numerically solving the regularized optimization problem with a fixed regularization parameter, we propose a novel method with a second-order in time dissipative gradient-like system and a dynamical selected regularization parameter. A damped symplectic scheme is proposed for the numerical solution. Theoretical analysis is given for both the continuous model and the numerical algorithm. Several numerical examples are provided to show the robustness of the proposed algorithm.
NASA Astrophysics Data System (ADS)
Liu, X.; Gurnis, M.; Stadler, G.; Rudi, J.; Ratnaswamy, V.; Ghattas, O.
2017-12-01
Dynamic topography, or uncompensated topography, is controlled by internal dynamics, and provide constraints on the buoyancy structure and rheological parameters in the mantle. Compared with other surface manifestations such as the geoid, dynamic topography is very sensitive to shallower and more regional mantle structure. For example, the significant dynamic topography above the subduction zone potentially provides a rich mine for inferring the rheological and mechanical properties such as plate coupling, flow, and lateral viscosity variations, all critical in plate tectonics. However, employing subduction zone topography in the inversion study requires that we have a better understanding of the topography from forward models, especially the influence of the viscosity formulation, numerical resolution, and other factors. One common approach to formulating a fault between the subducted slab and the overriding plates in viscous flow models assumes a thin weak zone. However, due to the large lateral variation in viscosity, topography from free-slip numerical models typically has artificially large magnitude as well as high-frequency undulations over subduction zone, which adds to the difficulty in making comparisons between model results and observations. In this study, we formulate a weak zone with the transversely isotropic viscosity (TI) where the tangential viscosity is much smaller than the viscosity in the normal direction. Similar with isotropic weak zone models, TI models effectively decouple subducted slabs from the overriding plates. However, we find that the topography in TI models is largely reduced compared with that in weak zone models assuming an isotropic viscosity. Moreover, the artificial `tooth paste' squeezing effect observed in isotropic weak zone models vanishes in TI models, although the difference becomes less significant when the dip angle is small. We also implement a free-surface condition in our numerical models, which has a smoothing effect on the topography. With the improved model configuration, we can use the adjoint inversion method in a high-resolution model and employ topography in addition to other observables such as the plate motion to infer critical mechanical and rheological parameters in the subduction zone.
Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer.
Roberts, James A; Friston, Karl J; Breakspear, Michael
2017-04-01
Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Pilots Rate Augmented Generalized Predictive Control for Reconfiguration
NASA Technical Reports Server (NTRS)
Soloway, Don; Haley, Pam
2004-01-01
The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.
Towards inverse modeling of turbidity currents: The inverse lock-exchange problem
NASA Astrophysics Data System (ADS)
Lesshafft, Lutz; Meiburg, Eckart; Kneller, Ben; Marsden, Alison
2011-04-01
A new approach is introduced for turbidite modeling, leveraging the potential of computational fluid dynamics methods to simulate the flow processes that led to turbidite formation. The practical use of numerical flow simulation for the purpose of turbidite modeling so far is hindered by the need to specify parameters and initial flow conditions that are a priori unknown. The present study proposes a method to determine optimal simulation parameters via an automated optimization process. An iterative procedure matches deposit predictions from successive flow simulations against available localized reference data, as in practice may be obtained from well logs, and aims at convergence towards the best-fit scenario. The final result is a prediction of the entire deposit thickness and local grain size distribution. The optimization strategy is based on a derivative-free, surrogate-based technique. Direct numerical simulations are performed to compute the flow dynamics. A proof of concept is successfully conducted for the simple test case of a two-dimensional lock-exchange turbidity current. The optimization approach is demonstrated to accurately retrieve the initial conditions used in a reference calculation.
Miller, Scot M.; Commane, Roisin; Melton, Joe R.; ...
2016-03-02
Existing estimates of methane (CH 4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH 4 observations from the US and Canada to analyze seven different bottom-up, wetland CH 4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH 4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use realmore » data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. Lastly, these models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.« less
NASA Astrophysics Data System (ADS)
Miller, Scot M.; Commane, Roisin; Melton, Joe R.; Andrews, Arlyn E.; Benmergui, Joshua; Dlugokencky, Edward J.; Janssens-Maenhout, Greet; Michalak, Anna M.; Sweeney, Colm; Worthy, Doug E. J.
2016-03-01
Existing estimates of methane (CH4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH4 observations from the US and Canada to analyze seven different bottom-up, wetland CH4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. These models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.
NASA Astrophysics Data System (ADS)
Cowie, L.; Kusznir, N. J.
2012-12-01
It has been proposed that some continental rifted margins have anomalous subsidence histories and that at breakup they were elevated at shallower bathymetries than the isostatic response of classical rift models (McKenzie 1978) would predict. The existence of anomalous syn or post breakup subsidence of this form would have important implications for our understanding of the geodynamics of continental breakup and rifted continental margin formation, margin subsidence history and the evolution of syn and post breakup depositional systems. We have investigated three rifted continental margins; the Gulf of Aden, Galicia Bank and the Gulf of Lions, to determine whether the oceanic crust in the ocean-continent transition of these margins has present day anomalous subsidence and if so, whether it is caused by mantle dynamic topography or anomalous oceanic crustal thickness. Residual depth anomalies (RDA) corrected for sediment loading, using flexural backstripping and decompaction, have been calculated by comparing observed and age predicted oceanic bathymetries in order to identify anomalous oceanic bathymetry and subsidence at these margins. Age predicted bathymetric anomalies have been calculated using the thermal plate model predictions from Crosby & McKenzie (2009). Non-zero sediment corrected RDAs may result from anomalous oceanic crustal thickness with respect to the global average, or from mantle dynamic uplift. Positive RDAs may result from thicker than average oceanic crust or mantle dynamic uplift; negative RDAs may result from thinner than average oceanic crust or mantle dynamic subsidence. Gravity inversion incorporating a lithosphere thermal gravity anomaly correction and sediment thickness from 2D seismic data has been used to determine Moho depth and oceanic crustal basement thickness. The reference Moho depths used in the gravity inversion have been calibrated against seismic refraction Moho depths. The gravity inversion crustal basement thicknesses together with Airy isostasy have been used to predict a "synthetic" gravity derived RDA. Sediment corrected RDA for oceanic crust in the Gulf of Aden are positive (+750m) indicating anomalous uplift with respect to normal subsidence. Gravity inversion predicts normal thickness oceanic crust and a zero "synthetic" gravity derived RDA in the oceanic domain. The difference between the positive sediment corrected RDA and the zero "synthetic" gravity derived RDA, implies that the anomalous subsidence reported in the Gulf of Aden is the result of mantle dynamic uplift. For the oceanic crust outboard of Galicia Bank both the sediment corrected RDA and the "synthetic" gravity derived RDA are negative (-800m) and of similar magnitude, indicating anomalous subsidence, which is the result of anomalously thin oceanic crust, not mantle dynamic topography. We conclude that there is negligible mantle dynamic topography influencing the Galicia Bank region. In the Gulf of Lions, gravity inversion predicts thinner than average oceanic crust. Both sediment corrected RDA (-1km) and "synthetic" gravity derived RDA (-500m) are negative. The more negative sediment corrected RDA compared with the "synthetic" gravity derived RDA implies that the anomalous subsidence in the Gulf of Lions is the result of mantle dynamic subsidence as well as thinner than average oceanic crust.
NASA Technical Reports Server (NTRS)
Devasia, Santosh
1996-01-01
A technique to achieve output tracking for nonminimum phase linear systems with non-hyperbolic and near non-hyperbolic internal dynamics is presented. This approach integrates stable inversion techniques, that achieve exact-tracking, with approximation techniques, that modify the internal dynamics to achieve desirable performance. Such modification of the internal dynamics is used (1) to remove non-hyperbolicity which an obstruction to applying stable inversion techniques and (2) to reduce large pre-actuation time needed to apply stable inversion for near non-hyperbolic cases. The method is applied to an example helicopter hover control problem with near non-hyperbolic internal dynamic for illustrating the trade-off between exact tracking and reduction of pre-actuation time.
TOPEX/POSEIDON tides estimated using a global inverse model
NASA Technical Reports Server (NTRS)
Egbert, Gary D.; Bennett, Andrew F.; Foreman, Michael G. G.
1994-01-01
Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.
Dynamics of Genome Rearrangement in Bacterial Populations
Darling, Aaron E.; Miklós, István; Ragan, Mark A.
2008-01-01
Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of “symmetric inversions”—inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings represent the first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes. PMID:18650965
Schryer, David W.; Peterson, Pearu; Illaste, Ardo; Vendelin, Marko
2012-01-01
To characterize intracellular energy transfer in the heart, two organ-level methods have frequently been employed: inversion and saturation transfer, and dynamic labeling. Creatine kinase (CK) fluxes obtained by following oxygen labeling have been considerably smaller than the fluxes determined by saturation transfer. It has been proposed that dynamic labeling determines net flux through CK shuttle, whereas saturation transfer measures total unidirectional flux. However, to our knowledge, no sensitivity analysis of flux determination by oxygen labeling has been performed, limiting our ability to compare flux distributions predicted by different methods. Here we analyze oxygen labeling in a physiological heart phosphotransfer network with active CK and adenylate kinase (AdK) shuttles and establish which fluxes determine the labeling state. A mathematical model consisting of a system of ordinary differential equations was composed describing enrichment in each phosphoryl group and inorganic phosphate. By varying flux distributions in the model and calculating the labeling, we analyzed labeling sensitivity to different fluxes in the heart. We observed that the labeling state is predominantly sensitive to total unidirectional CK and AdK fluxes and not to net fluxes. We conclude that measuring dynamic incorporation of into the high-energy phosphotransfer network in heart does not permit unambiguous determination of energetic fluxes with a higher magnitude than the ATP synthase rate when the bidirectionality of fluxes is taken into account. Our analysis suggests that the flux distributions obtained using dynamic labeling, after removing the net flux assumption, are comparable with those from inversion and saturation transfer. PMID:23236266
Inverse energy cascades in three-dimensional turbulence
NASA Technical Reports Server (NTRS)
Hossain, Murshed
1991-01-01
Fully three-dimensional magnetohydrodynamic (MHD) turbulence at large kinetic and low magnetic Reynolds numbers is considered in the presence of a strong uniform magnetic field. It is shown by numerical simulation of a model of MHD that the energy inverse cascades to longer length scales when the interaction parameter is large. While the steady-state dynamics of the driven problem is three-dimensional in character, the behavior has resemblance to two-dimensional hydrodynamics. These results have implications in turbulence theory, MHD power generator, planetary dynamos, and fusion reactor blanket design.
Large-scale inverse and forward modeling of adaptive resonance in the tinnitus decompensation.
Low, Yin Fen; Trenado, Carlos; Delb, Wolfgang; D'Amelio, Roberto; Falkai, Peter; Strauss, Daniel J
2006-01-01
Neural correlates of psychophysiological tinnitus models in humans may be used for their neurophysiological validation as well as for their refinement and improvement to better understand the pathogenesis of the tinnitus decompensation and to develop new therapeutic approaches. In this paper we make use of neural correlates of top-down projections, particularly, a recently introduced synchronization stability measure, together with a multiscale evoked response potential (ERP) model in order to study and evaluate the tinnitus decompensation by using a hybrid inverse-forward mathematical methodology. The neural synchronization stability, which according to the underlying model is linked to the focus of attention on the tinnitus signal, follows the experimental and inverse way and allows to discriminate between a group of compensated and decompensated tinnitus patients. The multiscale ERP model, which works in the forward direction, is used to consolidate hypotheses which are derived from the experiments for a known neural source dynamics related to attention. It is concluded that both methodologies agree and support each other in the description of the discriminatory character of the neural correlate proposed, but also help to fill the gap between the top-down adaptive resonance theory and the Jastreboff model of tinnitus.
Kanayama, Mieko; Suzuki, Machiko; Yuma, Yoshikazu
2016-01-01
The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. PMID:27366107
The origin, global distribution, and functional impact of the human 8p23 inversion polymorphism.
Salm, Maximilian P A; Horswell, Stuart D; Hutchison, Claire E; Speedy, Helen E; Yang, Xia; Liang, Liming; Schadt, Eric E; Cookson, William O; Wierzbicki, Anthony S; Naoumova, Rossi P; Shoulders, Carol C
2012-06-01
Genomic inversions are an increasingly recognized source of genetic variation. However, a lack of reliable high-throughput genotyping assays for these structures has precluded a full understanding of an inversion's phylogenetic, phenotypic, and population genetic properties. We characterize these properties for one of the largest polymorphic inversions in man (the ∼4.5-Mb 8p23.1 inversion), a structure that encompasses numerous signals of natural selection and disease association. We developed and validated a flexible bioinformatics tool that utilizes SNP data to enable accurate, high-throughput genotyping of the 8p23.1 inversion. This tool was applied retrospectively to diverse genome-wide data sets, revealing significant population stratification that largely follows a clinal "serial founder effect" distribution model. Phylogenetic analyses establish the inversion's ancestral origin within the Homo lineage, indicating that 8p23.1 inversion has occurred independently in the Pan lineage. The human inversion breakpoint was localized to an inverted pair of human endogenous retrovirus elements within the large, flanking low-copy repeats; experimental validation of this breakpoint confirmed these elements as the likely intermediary substrates that sponsored inversion formation. In five data sets, mRNA levels of disease-associated genes were robustly associated with inversion genotype. Moreover, a haplotype associated with systemic lupus erythematosus was restricted to the derived inversion state. We conclude that the 8p23.1 inversion is an evolutionarily dynamic structure that can now be accommodated into the understanding of human genetic and phenotypic diversity.
The origin, global distribution, and functional impact of the human 8p23 inversion polymorphism
Salm, Maximilian P.A.; Horswell, Stuart D.; Hutchison, Claire E.; Speedy, Helen E.; Yang, Xia; Liang, Liming; Schadt, Eric E.; Cookson, William O.; Wierzbicki, Anthony S.; Naoumova, Rossi P.; Shoulders, Carol C.
2012-01-01
Genomic inversions are an increasingly recognized source of genetic variation. However, a lack of reliable high-throughput genotyping assays for these structures has precluded a full understanding of an inversion's phylogenetic, phenotypic, and population genetic properties. We characterize these properties for one of the largest polymorphic inversions in man (the ∼4.5-Mb 8p23.1 inversion), a structure that encompasses numerous signals of natural selection and disease association. We developed and validated a flexible bioinformatics tool that utilizes SNP data to enable accurate, high-throughput genotyping of the 8p23.1 inversion. This tool was applied retrospectively to diverse genome-wide data sets, revealing significant population stratification that largely follows a clinal “serial founder effect” distribution model. Phylogenetic analyses establish the inversion's ancestral origin within the Homo lineage, indicating that 8p23.1 inversion has occurred independently in the Pan lineage. The human inversion breakpoint was localized to an inverted pair of human endogenous retrovirus elements within the large, flanking low-copy repeats; experimental validation of this breakpoint confirmed these elements as the likely intermediary substrates that sponsored inversion formation. In five data sets, mRNA levels of disease-associated genes were robustly associated with inversion genotype. Moreover, a haplotype associated with systemic lupus erythematosus was restricted to the derived inversion state. We conclude that the 8p23.1 inversion is an evolutionarily dynamic structure that can now be accommodated into the understanding of human genetic and phenotypic diversity. PMID:22399572
Development of esMOCA Biomechanic, Motion Capture Instrumentation for Biomechanics Analysis
NASA Astrophysics Data System (ADS)
Arendra, A.; Akhmad, S.
2018-01-01
This study aims to build motion capture instruments using inertial measurement unit sensors to assist in the analysis of biomechanics. Sensors used are accelerometer and gyroscope. Estimation of orientation sensors is done by digital motion processing in each sensor nodes. There are nine sensor nodes attached to the upper limbs. This sensor is connected to the pc via a wireless sensor network. The development of kinematics and inverse dynamamic models of the upper limb is done in simulink simmechanic. The kinematic model receives streaming data of sensor nodes mounted on the limbs. The output of the kinematic model is the pose of each limbs and visualized on display. The dynamic inverse model outputs the reaction force and reaction moment of each joint based on the limb motion input. Model validation in simulink with mathematical model of mechanical analysis showed results that did not differ significantly
NASA Astrophysics Data System (ADS)
Du, Xiaoping; Wang, Yang; Liu, Hao
2018-04-01
The space object in highly elliptical orbit is always presented as an image point on the ground-based imaging equipment so that it is difficult to resolve and identify the shape and attitude directly. In this paper a novel algorithm is presented for the estimation of spacecraft shape. The apparent magnitude model suitable for the inversion of object information such as shape and attitude is established based on the analysis of photometric characteristics. A parallel adaptive shape inversion algorithm based on UKF was designed after the achievement of dynamic equation of the nonlinear, Gaussian system involved with the influence of various dragging forces. The result of a simulation study demonstrate the viability and robustness of the new filter and its fast convergence rate. It realizes the inversion of combination shape with high accuracy, especially for the bus of cube and cylinder. Even though with sparse photometric data, it still can maintain a higher success rate of inversion.
Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen; ...
2018-01-02
When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pestana, Luis Ruiz; Minnetian, Natalie; Lammers, Laura Nielsen
When driven out of equilibrium, many diverse systems can form complex spatial and dynamical patterns, even in the absence of attractive interactions. Using kinetic Monte Carlo simulations, we investigate the phase behavior of a binary system of particles of dissimilar size confined between semiflexible planar surfaces, in which the nanoconfinement introduces a non-local coupling between particles, which we model as an activation energy barrier to diffusion that decreases with the local fraction of the larger particle. The system autonomously reaches a cyclical non-equilibrium state characterized by the formation and dissolution of metastable micelle-like clusters with the small particles in themore » core and the large ones in the surrounding corona. The power spectrum of the fluctuations in the aggregation number exhibits 1/f noise reminiscent of self-organized critical systems. Finally, we suggest that the dynamical metastability of the micellar structures arises from an inversion of the energy landscape, in which the relaxation dynamics of one of the species induces a metastable phase for the other species.« less
Modal resonant dynamics of cables with a flexible support: A modulated diffraction problem
NASA Astrophysics Data System (ADS)
Guo, Tieding; Kang, Houjun; Wang, Lianhua; Liu, Qijian; Zhao, Yueyu
2018-06-01
Modal resonant dynamics of cables with a flexible support is defined as a modulated (wave) diffraction problem, and investigated by asymptotic expansions of the cable-support coupled system. The support-cable mass ratio, which is usually very large, turns out to be the key parameter for characterizing cable-support dynamic interactions. By treating the mass ratio's inverse as a small perturbation parameter and scaling the cable tension properly, both cable's modal resonant dynamics and the flexible support dynamics are asymptotically reduced by using multiple scale expansions, leading finally to a reduced cable-support coupled model (i.e., on a slow time scale). After numerical validations of the reduced coupled model, cable-support coupled responses and the flexible support induced coupling effects on the cable, are both fully investigated, based upon the reduced model. More explicitly, the dynamic effects on the cable's nonlinear frequency and force responses, caused by the support-cable mass ratio, the resonant detuning parameter and the support damping, are carefully evaluated.
Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salerno, K. Michael; Agrawal, Anupriya; Perahia, Dvora
2016-02-05
Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion ismore » used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.« less
Iino, Yoichi; Kojima, Takeji
2012-08-01
This study investigated the validity of the top-down approach of inverse dynamics analysis in fast and large rotational movements of the trunk about three orthogonal axes of the pelvis for nine male collegiate students. The maximum angles of the upper trunk relative to the pelvis were approximately 47°, 49°, 32°, and 55° for lateral bending, flexion, extension, and axial rotation, respectively, with maximum angular velocities of 209°/s, 201°/s, 145°/s, and 288°/s, respectively. The pelvic moments about the axes during the movements were determined using the top-down and bottom-up approaches of inverse dynamics and compared between the two approaches. Three body segment inertial parameter sets were estimated using anthropometric data sets (Ae et al., Biomechanism 11, 1992; De Leva, J Biomech, 1996; Dumas et al., J Biomech, 2007). The root-mean-square errors of the moments and the absolute errors of the peaks of the moments were generally smaller than 10 N·m. The results suggest that the pelvic moment in motions involving fast and large trunk movements can be determined with a certain level of validity using the top-down approach in which the trunk is modeled as two or three rigid-link segments.
Huang, Weidong; Li, Kun; Wang, Gan; Wang, Yingzhe
2013-01-01
Abstract In this article, we present a newly designed inverse umbrella surface aerator, and tested its performance in driving flow of an oxidation ditch. Results show that it has a better performance in driving the oxidation ditch than the original one with higher average velocity and more uniform flow field. We also present a computational fluid dynamics model for predicting the flow field in an oxidation ditch driven by a surface aerator. The improved momentum source term approach to simulate the flow field of the oxidation ditch driven by an inverse umbrella surface aerator was developed and validated through experiments. Four kinds of turbulent models were investigated with the approach, including the standard k−ɛ model, RNG k−ɛ model, realizable k−ɛ model, and Reynolds stress model, and the predicted data were compared with those calculated with the multiple rotating reference frame approach (MRF) and sliding mesh approach (SM). Results of the momentum source term approach are in good agreement with the experimental data, and its prediction accuracy is better than MRF, close to SM. It is also found that the momentum source term approach has lower computational expenses, is simpler to preprocess, and is easier to use. PMID:24302850
Experimental verification of dynamic simulation
NASA Technical Reports Server (NTRS)
Yae, K. Harold; Hwang, Howyoung; Chern, Su-Tai
1989-01-01
The dynamics model here is a backhoe, which is a four degree of freedom manipulator from the dynamics standpoint. Two types of experiment are chosen that can also be simulated by a multibody dynamics simulation program. In the experiment, recorded were the configuration and force histories; that is, velocity and position, and force output and differential pressure change from the hydraulic cylinder, in the time domain. When the experimental force history is used as driving force in the simulation model, the forward dynamics simulation produces a corresponding configuration history. Then, the experimental configuration history is used in the inverse dynamics analysis to generate a corresponding force history. Therefore, two sets of configuration and force histories--one set from experiment, and the other from the simulation that is driven forward and backward with the experimental data--are compared in the time domain. More comparisons are made in regard to the effects of initial conditions, friction, and viscous damping.
Improved real-time dynamics from imaginary frequency lattice simulations
NASA Astrophysics Data System (ADS)
Pawlowski, Jan M.; Rothkopf, Alexander
2018-03-01
The computation of real-time properties, such as transport coefficients or bound state spectra of strongly interacting quantum fields in thermal equilibrium is a pressing matter. Since the sign problem prevents a direct evaluation of these quantities, lattice data needs to be analytically continued from the Euclidean domain of the simulation to Minkowski time, in general an ill-posed inverse problem. Here we report on a novel approach to improve the determination of real-time information in the form of spectral functions by setting up a simulation prescription in imaginary frequencies. By carefully distinguishing between initial conditions and quantum dynamics one obtains access to correlation functions also outside the conventional Matsubara frequencies. In particular the range between ω0 and ω1 = 2πT, which is most relevant for the inverse problem may be more highly resolved. In combination with the fact that in imaginary frequencies the kernel of the inverse problem is not an exponential but only a rational function we observe significant improvements in the reconstruction of spectral functions, demonstrated in a simple 0+1 dimensional scalar field theory toy model.
Atomic-scale origin of dynamic viscoelastic response and creep in disordered solids
NASA Astrophysics Data System (ADS)
Milkus, Rico; Zaccone, Alessio
2017-02-01
Viscoelasticity has been described since the time of Maxwell as an interpolation of purely viscous and purely elastic response, but its microscopic atomic-level mechanism in solids has remained elusive. We studied three model disordered solids: a random lattice, the bond-depleted fcc lattice, and the fcc lattice with vacancies. Within the harmonic approximation for central-force lattices, we applied sum rules for viscoelastic response derived on the basis of nonaffine atomic motions. The latter motions are a direct result of local structural disorder, and in particular, of the lack of inversion symmetry in disordered lattices. By defining a suitable quantitative and general atomic-level measure of nonaffinity and inversion symmetry, we show that the viscoelastic responses of all three systems collapse onto a master curve upon normalizing by the overall strength of inversion-symmetry breaking in each system. Close to the isostatic point for central-force lattices, power-law creep G (t ) ˜t-1 /2 emerges as a consequence of the interplay between soft vibrational modes and nonaffine dynamics, and various analytical scalings, supported by numerical calculations, are predicted by the theory.
Velocity Structure of the Iran Region Using Seismic and Gravity Observations
NASA Astrophysics Data System (ADS)
Syracuse, E. M.; Maceira, M.; Phillips, W. S.; Begnaud, M. L.; Nippress, S. E. J.; Bergman, E.; Zhang, H.
2015-12-01
We present a 3D Vp and Vs model of Iran generated using a joint inversion of body wave travel times, Rayleigh wave dispersion curves, and high-wavenumber filtered Bouguer gravity observations. Our work has two main goals: 1) To better understand the tectonics of a prominent example of continental collision, and 2) To assess the improvements in earthquake location possible as a result of joint inversion. The body wave dataset is mainly derived from previous work on location calibration and includes the first-arrival P and S phases of 2500 earthquakes whose initial locations qualify as GT25 or better. The surface wave dataset consists of Rayleigh wave group velocity measurements for regional earthquakes, which are inverted for a suite of period-dependent Rayleigh wave velocity maps prior to inclusion in the joint inversion for body wave velocities. We use gravity anomalies derived from the global gravity model EGM2008. To avoid mapping broad, possibly dynamic features in the gravity field intovariations in density and body wave velocity, we apply a high-pass wavenumber filter to the gravity measurements. We use a simple, approximate relationship between density and velocity so that the three datasets may be combined in a single inversion. The final optimized 3D Vp and Vs model allows us to explore how multi-parameter tomography addresses crustal heterogeneities in areas of limited coverage and improves travel time predictions. We compare earthquake locations from our models to independent locations obtained from InSAR analysis to assess the improvement in locations derived in a joint-inversion model in comparison to those derived in a more traditional body-wave-only velocity model.
NASA Astrophysics Data System (ADS)
Hendzel, Z.; Rykała, Ł.
2017-02-01
The work presents the dynamic equations of motion of a wheeled mobile robot with mecanum wheels derived with the use of Lagrange equations of the second kind. Mecanum wheels are a new type of wheels used in wheeled mobile robots and they consist of freely rotating rollers attached to the circumference of the wheels. In order to derive dynamic equations of motion of a wheeled mobile robot, the kinetic energy of the system is determined, as well as the generalised forces affecting the system. The resulting mathematical model of a wheeled mobile robot was generated with the use of Maple V software. The results of a solution of inverse and forward problems of dynamics of the discussed object are also published.
Simultaneous prediction of muscle and contact forces in the knee during gait.
Lin, Yi-Chung; Walter, Jonathan P; Banks, Scott A; Pandy, Marcus G; Fregly, Benjamin J
2010-03-22
Musculoskeletal models are currently the primary means for estimating in vivo muscle and contact forces in the knee during gait. These models typically couple a dynamic skeletal model with individual muscle models but rarely include articular contact models due to their high computational cost. This study evaluates a novel method for predicting muscle and contact forces simultaneously in the knee during gait. The method utilizes a 12 degree-of-freedom knee model (femur, tibia, and patella) combining muscle, articular contact, and dynamic skeletal models. Eight static optimization problems were formulated using two cost functions (one based on muscle activations and one based on contact forces) and four constraints sets (each composed of different combinations of inverse dynamic loads). The estimated muscle and contact forces were evaluated using in vivo tibial contact force data collected from a patient with a force-measuring knee implant. When the eight optimization problems were solved with added constraints to match the in vivo contact force measurements, root-mean-square errors in predicted contact forces were less than 10 N. Furthermore, muscle and patellar contact forces predicted by the two cost functions became more similar as more inverse dynamic loads were used as constraints. When the contact force constraints were removed, estimated medial contact forces were similar and lateral contact forces lower in magnitude compared to measured contact forces, with estimated muscle forces being sensitive and estimated patellar contact forces relatively insensitive to the choice of cost function and constraint set. These results suggest that optimization problem formulation coupled with knee model complexity can significantly affect predicted muscle and contact forces in the knee during gait. Further research using a complete lower limb model is needed to assess the importance of this finding to the muscle and contact force estimation process. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-02-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-01-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS. PMID:29875506
Highway traffic estimation of improved precision using the derivative-free nonlinear Kalman Filter
NASA Astrophysics Data System (ADS)
Rigatos, Gerasimos; Siano, Pierluigi; Zervos, Nikolaos; Melkikh, Alexey
2015-12-01
The paper proves that the PDE dynamic model of the highway traffic is a differentially flat one and by applying spatial discretization its shows that the model's transformation into an equivalent linear canonical state-space form is possible. For the latter representation of the traffic's dynamics, state estimation is performed with the use of the Derivative-free nonlinear Kalman Filter. The proposed filter consists of the Kalman Filter recursion applied on the transformed state-space model of the highway traffic. Moreover, it makes use of an inverse transformation, based again on differential flatness theory which enables to obtain estimates of the state variables of the initial nonlinear PDE model. By avoiding approximate linearizations and the truncation of nonlinear terms from the PDE model of the traffic's dynamics the proposed filtering methods outperforms, in terms of accuracy, other nonlinear estimators such as the Extended Kalman Filter. The article's theoretical findings are confirmed through simulation experiments.
Decomposed direct matrix inversion for fast non-cartesian SENSE reconstructions.
Qian, Yongxian; Zhang, Zhenghui; Wang, Yi; Boada, Fernando E
2006-08-01
A new k-space direct matrix inversion (DMI) method is proposed here to accelerate non-Cartesian SENSE reconstructions. In this method a global k-space matrix equation is established on basic MRI principles, and the inverse of the global encoding matrix is found from a set of local matrix equations by taking advantage of the small extension of k-space coil maps. The DMI algorithm's efficiency is achieved by reloading the precalculated global inverse when the coil maps and trajectories remain unchanged, such as in dynamic studies. Phantom and human subject experiments were performed on a 1.5T scanner with a standard four-channel phased-array cardiac coil. Interleaved spiral trajectories were used to collect fully sampled and undersampled 3D raw data. The equivalence of the global k-space matrix equation to its image-space version, was verified via conjugate gradient (CG) iterative algorithms on a 2x undersampled phantom and numerical-model data sets. When applied to the 2x undersampled phantom and human-subject raw data, the decomposed DMI method produced images with small errors (< or = 3.9%) relative to the reference images obtained from the fully-sampled data, at a rate of 2 s per slice (excluding 4 min for precalculating the global inverse at an image size of 256 x 256). The DMI method may be useful for noise evaluations in parallel coil designs, dynamic MRI, and 3D sodium MRI with fixed coils and trajectories. Copyright 2006 Wiley-Liss, Inc.
NASA Technical Reports Server (NTRS)
Stammer, Detlef; Wunsch, Carl
1996-01-01
A Green's function method for obtaining an estimate of the ocean circulation using both a general circulation model and altimetric data is demonstrated. The fundamental assumption is that the model is so accurate that the differences between the observations and the model-estimated fields obey a linear dynamics. In the present case, the calculations are demonstrated for model/data differences occurring on very a large scale, where the linearization hypothesis appears to be a good one. A semi-automatic linearization of the Bryan/Cox general circulation model is effected by calculating the model response to a series of isolated (in both space and time) geostrophically balanced vortices. These resulting impulse responses or 'Green's functions' then provide the kernels for a linear inverse problem. The method is first demonstrated with a set of 'twin experiments' and then with real data spanning the entire model domain and a year of TOPEX/POSEIDON observations. Our present focus is on the estimate of the time-mean and annual cycle of the model. Residuals of the inversion/assimilation are largest in the western tropical Pacific, and are believed to reflect primarily geoid error. Vertical resolution diminishes with depth with 1 year of data. The model mean is modified such that the subtropical gyre is weakened by about 1 cm/s and the center of the gyre shifted southward by about 10 deg. Corrections to the flow field at the annual cycle suggest that the dynamical response is weak except in the tropics, where the estimated seasonal cycle of the low-latitude current system is of the order of 2 cm/s. The underestimation of observed fluctuations can be related to the inversion on the coarse spatial grid, which does not permit full resolution of the tropical physics. The methodology is easily extended to higher resolution, to use of spatially correlated errors, and to other data types.
NASA Astrophysics Data System (ADS)
Bai, Yongliang; Dong, Dongdong; Kirby, Jon F.; Williams, Simon E.; Wang, Zhenjie
2018-04-01
Lithospheric effective elastic thickness (Te), a proxy for plate strength, is helpful for the understanding of subduction characteristics. Affected by curvature, faulting and magma activity, lithospheric strength near trenches should be weakened but some regional inversion studies have shown much higher Te values along some trenches than in their surroundings. In order to improve Te estimation accuracy, here we discuss the long-wavelength effect of dynamic topography and gravity on Te estimation by taking the Izu-Bonin-Mariana (IBM) Trench as a case study area. We estimate the long-wavelength influence of the density and negative buoyancy of the subducting slab on observed gravity anomalies and seafloor topography. The residual topography and gravity are used to map Te using the fan-wavelet coherence method. Maps of Te, both with and without the effects of dynamic topography and slab gravity anomaly, contain a band of high-Te values along the IBM Trench, though these values and their errors are lower when slab effects are accounted for. Nevertheless, tests show that the Te map is relatively insensitive to the choice of slab-density modelling method, even though the dynamic topography and slab-induced gravity anomaly vary considerably when the slab density is modelled by different methods. The continued presence of a high-Te band along the trench after application of dynamic corrections shows that, before using 2D inversion methods to estimate Te variations in subduction zones, there are other factors that should be considered besides the slab dynamic effects on the overriding plate.
NASA Astrophysics Data System (ADS)
Bai, Yongliang; Dong, Dongdong; Kirby, Jon F.; Williams, Simon E.; Wang, Zhenjie
2018-07-01
Lithospheric effective elastic thickness (Te), a proxy for plIate strength, is helpful for the understanding of subduction characteristics. Affected by curvature, faulting and magma activity, lithospheric strength near trenches should be weakened but some regional inversion studies have shown much higher Te values along some trenches than in their surroundings. In order to improve Te-estimation accuracy, here we discuss the long-wavelength effect of dynamic topography and gravity on Te estimation by taking the Izu-Bonin-Mariana (IBM) Trench as a case study area. We estimate the long-wavelength influence of the density and negative buoyancy of the subducting slab on observed gravity anomalies and seafloor topography. The residual topography and gravity are used to map Te using the fan-wavelet coherence method. Maps of Te, both with and without the effects of dynamic topography and slab gravity anomaly, contain a band of high-Te values along the IBM Trench, though these values and their errors are lower when slab effects are accounted for. Nevertheless, tests show that the Te map is relatively insensitive to the choice of slab-density modelling method, even though the dynamic topography and slab-induced gravity anomaly vary considerably when the slab density is modelled by different methods. The continued presence of a high-Te band along the trench after application of dynamic corrections shows that, before using 2-D inversion methods to estimate Te variations in subduction zones, there are other factors that should be considered besides the slab dynamic effects on the overriding plate.
Dynamic stress changes during earthquake rupture
Day, S.M.; Yu, G.; Wald, D.J.
1998-01-01
We assess two competing dynamic interpretations that have been proposed for the short slip durations characteristic of kinematic earthquake models derived by inversion of earthquake waveform and geodetic data. The first interpretation would require a fault constitutive relationship in which rapid dynamic restrengthening of the fault surface occurs after passage of the rupture front, a hypothesized mechanical behavior that has been referred to as "self-healing." The second interpretation would require sufficient spatial heterogeneity of stress drop to permit rapid equilibration of elastic stresses with the residual dynamic friction level, a condition we refer to as "geometrical constraint." These interpretations imply contrasting predictions for the time dependence of the fault-plane shear stresses. We compare these predictions with dynamic shear stress changes for the 1992 Landers (M 7.3), 1994 Northridge (M 6.7), and 1995 Kobe (M 6.9) earthquakes. Stress changes are computed from kinematic slip models of these earthquakes, using a finite-difference method. For each event, static stress drop is highly variable spatially, with high stress-drop patches embedded in a background of low, and largely negative, stress drop. The time histories of stress change show predominantly monotonic stress change after passage of the rupture front, settling to a residual level, without significant evidence for dynamic restrengthening. The stress change at the rupture front is usually gradual rather than abrupt, probably reflecting the limited resolution inherent in the underlying kinematic inversions. On the basis of this analysis, as well as recent similar results obtained independently for the Kobe and Morgan Hill earthquakes, we conclude that, at the present time, the self-healing hypothesis is unnecessary to explain earthquake kinematics.
Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-01-01
X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) both reveal dynamics using coherent scattering, but X-rays permit investigating of dynamics in a much more diverse array of materials. Heterogeneous dynamics occur in many such materials, and we showed how classic tools employed in analysis of heterogeneous DLS dynamics extend to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. This work presents the software implementation of inverse transform analysis of XPCS data called CONTIN XPCS, an extension of traditional CONTIN that accommodates dynamics encountered in equilibrium XPCS measurements. PMID:29875507
Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan
2018-02-01
X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) both reveal dynamics using coherent scattering, but X-rays permit investigating of dynamics in a much more diverse array of materials. Heterogeneous dynamics occur in many such materials, and we showed how classic tools employed in analysis of heterogeneous DLS dynamics extend to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. This work presents the software implementation of inverse transform analysis of XPCS data called CONTIN XPCS, an extension of traditional CONTIN that accommodates dynamics encountered in equilibrium XPCS measurements.
Johnson, Cordell; Swarzenski, Peter W.; Richardson, Christina M.; Smith, Christopher G.; Kroeger, Kevin D.; Ganguli, Priya M.
2015-01-01
Rigorous ground-truthing at each field site showed that multi-channel electrcial resistivity techniques can reproduce the scales and dynamics of a seepage field when such data are correctly collected, and when the model inversions are tuned to field site characteristics. Such information can provide a unique perspective on the scales and dynamics of exchange processes within a coastal aquifer—information essential to scientists and resource managers alike.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Galanti, Eli; Kaspi, Yohai, E-mail: eli.galanti@weizmann.ac.il
2016-04-01
During 2016–17, the Juno and Cassini spacecraft will both perform close eccentric orbits of Jupiter and Saturn, respectively, obtaining high-precision gravity measurements for these planets. These data will be used to estimate the depth of the observed surface flows on these planets. All models to date, relating the winds to the gravity field, have been in the forward direction, thus only allowing the calculation of the gravity field from given wind models. However, there is a need to do the inverse problem since the new observations will be of the gravity field. Here, an inverse dynamical model is developed tomore » relate the expected measurable gravity field, to perturbations of the density and wind fields, and therefore to the observed cloud-level winds. In order to invert the gravity field into the 3D circulation, an adjoint model is constructed for the dynamical model, thus allowing backward integration. This tool is used for the examination of various scenarios, simulating cases in which the depth of the wind depends on latitude. We show that it is possible to use the gravity measurements to derive the depth of the winds, both on Jupiter and Saturn, also taking into account measurement errors. Calculating the solution uncertainties, we show that the wind depth can be determined more precisely in the low-to-mid-latitudes. In addition, the gravitational moments are found to be particularly sensitive to flows at the equatorial intermediate depths. Therefore, we expect that if deep winds exist on these planets they will have a measurable signature by Juno and Cassini.« less
Seismic waveform inversion for core-mantle boundary topography
NASA Astrophysics Data System (ADS)
Colombi, Andrea; Nissen-Meyer, Tarje; Boschi, Lapo; Giardini, Domenico
2014-07-01
The topography of the core-mantle boundary (CMB) is directly linked to the dynamics of both the mantle and the outer core, although it is poorly constrained and understood. Recent studies have produced topography models with mutual agreement up to degree 2. A broad-band waveform inversion strategy is introduced and applied here, with relatively low computational cost and based on a first-order Born approximation. Its performance is validated using synthetic waveforms calculated in theoretical earth models that include different topography patterns with varying lateral wavelengths, from 600 to 2500 km, and magnitudes (˜10 km peak-to-peak). The source-receiver geometry focuses mainly on the Pdiff, PKP, PcP and ScS phases. The results show that PKP branches, PcP and ScS generally perform well and in a similar fashion, while Pdiff yields unsatisfactory results. We investigate also how 3-D mantle correction influences the output models, and find that despite the disturbance introduced, the models recovered do not appear to be biased, provided that the 3-D model is correct. Using cross-correlated traveltimes, we derive new topography models from both P and S waves. The static corrections used to remove the mantle effect are likely to affect the inversion, compromising the agreement between models derived from P and S data. By modelling traveltime residuals starting from sensitivity kernels, we show how the simultaneous use of volumetric and boundary kernels can reduce the bias coming from mantle structures. The joint inversion approach should be the only reliable method to invert for CMB topography using absolute cross-correlation traveltimes.
NASA Astrophysics Data System (ADS)
Córdova-Sintjago, Tania C.; Liu, Yue; Booth, Raymond G.
2015-02-01
To understand molecular determinants for ligand activation of the serotonin 5-HT2C G protein-coupled receptor (GPCR), a drug target for obesity and neuropsychiatric disorders, a 5-HT2C homology model was built according to an adrenergic β2 GPCR (β2AR) structure and validated using a 5-HT2B GPCR crystal structure. The models were equilibrated in a simulated phosphatidyl choline membrane for ligand docking and molecular dynamics studies. Ligands included (2S, 4R)-(-)-trans-4-(3'-bromo- and trifluoro-phenyl)-N,N-dimethyl-1,2,3,4-tetrahydronaphthalene-2-amine (3'-Br-PAT and 3'-CF3-PAT), a 5-HT2C agonist and inverse agonist, respectively. Distinct interactions of 3'-Br-PAT and 3'-CF3-PAT at the wild-type (WT) 5-HT2C receptor model were observed and experimental 5-HT2C receptor mutagenesis studies were undertaken to validate the modelling results. For example, the inverse agonist 3'-CF3-PAT docked deeper in the WT 5-HT2C binding pocket and altered the orientation of transmembrane helices (TM) 6 in comparison to the agonist 3'-Br-PAT, suggesting that changes in TM orientation that result from ligand binding impact function. For both PATs, mutation of 5-HT2C residues S3.36, T3.37, and F5.47 to alanine resulted in significantly decreased affinity, as predicted from modelling results. It was concluded that upon PAT binding, 5-HT2C residues T3.37 and F5.47 in TMs 3 and 5, respectively, engage in inter-helical interactions with TMs 4 and 6, respectively. The movement of TMs 5 and 6 upon agonist and inverse agonist ligand binding observed in the 5-HT2C receptor modelling studies was similar to movements reported for the activation and deactivation of the β2AR, suggesting common mechanisms among aminergic neurotransmitter GPCRs.
NASA Technical Reports Server (NTRS)
Beech, G. S.; Hampton, R. D.; Rupert, J. K.
2004-01-01
Many microgravity space-science experiments require vibratory acceleration levels that are unachievable without active isolation. The Boeing Corporation's active rack isolation system (ARIS) employs a novel combination of magnetic actuation and mechanical linkages to address these isolation requirements on the International Space Station. Effective model-based vibration isolation requires: (1) An isolation device, (2) an adequate dynamic; i.e., mathematical, model of that isolator, and (3) a suitable, corresponding controller. This Technical Memorandum documents the validation of that high-fidelity dynamic model of ARIS. The verification of this dynamics model was achieved by utilizing two commercial off-the-shelf (COTS) software tools: Deneb's ENVISION(registered trademark), and Online Dynamics Autolev(trademark). ENVISION is a robotics software package developed for the automotive industry that employs three-dimensional computer-aided design models to facilitate both forward and inverse kinematics analyses. Autolev is a DOS-based interpreter designed, in general, to solve vector-based mathematical problems and specifically to solve dynamics problems using Kane's method. The simplification of this model was achieved using the small-angle theorem for the joint angle of the ARIS actuators. This simplification has a profound effect on the overall complexity of the closed-form solution while yielding a closed-form solution easily employed using COTS control hardware.
Electron-phonon thermalization in a scalable method for real-time quantum dynamics
NASA Astrophysics Data System (ADS)
Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.
2016-01-01
We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.
Nonlinear system guidance in the presence of transmission zero dynamics
NASA Technical Reports Server (NTRS)
Meyer, G.; Hunt, L. R.; Su, R.
1995-01-01
An iterative procedure is proposed for computing the commanded state trajectories and controls that guide a possibly multiaxis, time-varying, nonlinear system with transmission zero dynamics through a given arbitrary sequence of control points. The procedure is initialized by the system inverse with the transmission zero effects nulled out. Then the 'steady state' solution of the perturbation model with the transmission zero dynamics intact is computed and used to correct the initial zero-free solution. Both time domain and frequency domain methods are presented for computing the steady state solutions of the possibly nonminimum phase transmission zero dynamics. The procedure is illustrated by means of linear and nonlinear examples.
Changing basal conditions during the speed-up of Jakobshavn Isbræ, Greenland
NASA Astrophysics Data System (ADS)
Habermann, M.; Truffer, M.; Maxwell, D.
2013-11-01
Ice-sheet outlet glaciers can undergo dynamic changes such as the rapid speed-up of Jakobshavn Isbræ following the disintegration of its floating ice tongue. These changes are associated with stress changes on the boundary of the ice mass. We invert for basal conditions from surface velocity data throughout a well-observed period of rapid change and evaluate parameterizations currently used in ice-sheet models. A Tikhonov inverse method with a shallow-shelf approximation forward model is used for diagnostic inversions for the years 1985, 2000, 2005, 2006 and 2008. Our ice-softness, model norm, and regularization parameter choices are justified using the data-model misfit metric and the L curve method. The sensitivity of the inversion results to these parameter choices is explored. We find a lowering of effective basal yield stress in the first 7 km upstream from the 2008 grounding line and no significant changes higher upstream. The temporal evolution in the fast flow area is in broad agreement with a Mohr-Coulomb parameterization of basal shear stress, but with a till friction angle much lower than has been measured for till samples. The lowering of effective basal yield stress is significant within the uncertainties of the inversion, but it cannot be ruled out that there are other significant contributors to the acceleration of the glacier.
Generation of Look-Up Tables for Dynamic Job Shop Scheduling Decision Support Tool
NASA Astrophysics Data System (ADS)
Oktaviandri, Muchamad; Hassan, Adnan; Mohd Shaharoun, Awaluddin
2016-02-01
Majority of existing scheduling techniques are based on static demand and deterministic processing time, while most job shop scheduling problem are concerned with dynamic demand and stochastic processing time. As a consequence, the solutions obtained from the traditional scheduling technique are ineffective wherever changes occur to the system. Therefore, this research intends to develop a decision support tool (DST) based on promising artificial intelligent that is able to accommodate the dynamics that regularly occur in job shop scheduling problem. The DST was designed through three phases, i.e. (i) the look-up table generation, (ii) inverse model development and (iii) integration of DST components. This paper reports the generation of look-up tables for various scenarios as a part in development of the DST. A discrete event simulation model was used to compare the performance among SPT, EDD, FCFS, S/OPN and Slack rules; the best performances measures (mean flow time, mean tardiness and mean lateness) and the job order requirement (inter-arrival time, due dates tightness and setup time ratio) which were compiled into look-up tables. The well-known 6/6/J/Cmax Problem from Muth and Thompson (1963) was used as a case study. In the future, the performance measure of various scheduling scenarios and the job order requirement will be mapped using ANN inverse model.
Canonical formalism for modelling and control of rigid body dynamics.
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.
On parameterization of the inverse problem for estimating aquifer properties using tracer data
NASA Astrophysics Data System (ADS)
Kowalsky, M. B.; Finsterle, S.; Williams, K. H.; Murray, C.; Commer, M.; Newcomer, D.; Englert, A.; Steefel, C. I.; Hubbard, S. S.
2012-06-01
In developing a reliable approach for inferring hydrological properties through inverse modeling of tracer data, decisions made on how to parameterize heterogeneity (i.e., how to represent a heterogeneous distribution using a limited number of parameters that are amenable to estimation) are of paramount importance, as errors in the model structure are partly compensated for by estimating biased property values during the inversion. These biased estimates, while potentially providing an improved fit to the calibration data, may lead to wrong interpretations and conclusions and reduce the ability of the model to make reliable predictions. We consider the estimation of spatial variations in permeability and several other parameters through inverse modeling of tracer data, specifically synthetic and actual field data associated with the 2007 Winchester experiment from the Department of Energy Rifle site. Characterization is challenging due to the real-world complexities associated with field experiments in such a dynamic groundwater system. Our aim is to highlight and quantify the impact on inversion results of various decisions related to parameterization, such as the positioning of pilot points in a geostatistical parameterization; the handling of up-gradient regions; the inclusion of zonal information derived from geophysical data or core logs; extension from 2-D to 3-D; assumptions regarding the gradient direction, porosity, and the semivariogram function; and deteriorating experimental conditions. This work adds to the relatively limited number of studies that offer guidance on the use of pilot points in complex real-world experiments involving tracer data (as opposed to hydraulic head data).
Tachyon with an inverse power-law potential in a braneworld cosmology
NASA Astrophysics Data System (ADS)
Bilić, Neven; Domazet, Silvije; Djordjevic, Goran S.
2017-08-01
We study a tachyon cosmological model based on the dynamics of a 3-brane in the bulk of the second Randall-Sundrum model extended to more general warp functions. A well known prototype of such a generalization is the bulk with a selfinteracting scalar field. As a consequence of a generalized bulk geometry the cosmology on the observer brane is modified by the scale dependent four-dimensional gravitational constant. In particular, we study a power law warp factor which generates an inverse power-law potential V\\propto \\varphi-n of the tachyon field φ. We find a critical power n cr that divides two subclasses with distinct asymptotic behaviors: a dust universe for n>n_cr and a quasi de Sitter universe for 0.
Neural learning of constrained nonlinear transformations
NASA Technical Reports Server (NTRS)
Barhen, Jacob; Gulati, Sandeep; Zak, Michail
1989-01-01
Two issues that are fundamental to developing autonomous intelligent robots, namely, rudimentary learning capability and dexterous manipulation, are examined. A powerful neural learning formalism is introduced for addressing a large class of nonlinear mapping problems, including redundant manipulator inverse kinematics, commonly encountered during the design of real-time adaptive control mechanisms. Artificial neural networks with terminal attractor dynamics are used. The rapid network convergence resulting from the infinite local stability of these attractors allows the development of fast neural learning algorithms. Approaches to manipulator inverse kinematics are reviewed, the neurodynamics model is discussed, and the neural learning algorithm is presented.
Hooked Flare Ribbons and Flux-rope-related QSL Footprints
NASA Astrophysics Data System (ADS)
Zhao, Jie; Gilchrist, Stuart A.; Aulanier, Guillaume; Schmieder, Brigitte; Pariat, Etienne; Li, Hui
2016-05-01
We studied the magnetic topology of active region 12158 on 2014 September 10 and compared it with the observations before and early in the flare that begins at 17:21 UT (SOL2014-09-10T17:45:00). Our results show that the sigmoidal structure and flare ribbons of this active region observed by the Solar Dynamics Observatory/Atmospheric Imaging Assembly can be well reproduced from a Grad-Rubin nonlinear force-free field extrapolation method. Various inverse-S- and inverse-J-shaped magnetic field lines, which surround a coronal flux rope, coincide with the sigmoid as observed in different extreme-ultraviolet wavelengths, including its multithreaded curved ends. Also, the observed distribution of surface currents in the magnetic polarity where it was not prescribed is well reproduced. This validates our numerical implementation and setup of the Grad-Rubin method. The modeled double inverse-J-shaped quasi-separatrix layer (QSL) footprints match the observed flare ribbons during the rising phase of the flare, including their hooked parts. The spiral-like shape of the latter may be related to a complex pre-eruptive flux rope with more than one turn of twist, as obtained in the model. These ribbon-associated flux-rope QSL footprints are consistent with the new standard flare model in 3D, with the presence of a hyperbolic flux tube located below an inverse-teardrop-shaped coronal QSL. This is a new step forward forecasting the locations of reconnection and ribbons in solar flares and the geometrical properties of eruptive flux ropes.
A test of the chromosomal theory of ecotypic speciation in Anopheles gambiae
Manoukis, Nicholas C.; Powell, Jeffrey R.; Touré, Mahamoudou B.; Sacko, Adama; Edillo, Frances E.; Coulibaly, Mamadou B.; Traoré, Sekou F.; Taylor, Charles E.; Besansky, Nora J.
2008-01-01
The role of chromosomal inversions in speciation has long been of interest to evolutionists. Recent quantitative modeling has stimulated reconsideration of previous conceptual models for chromosomal speciation. Anopheles gambiae, the most important vector of human malaria, carries abundant chromosomal inversion polymorphism nonrandomly associated with ecotypes that mate assortatively. Here, we consider the potential role of paracentric inversions in promoting speciation in A. gambiae via “ecotypification,” a term that refers to differentiation arising from local adaptation. In particular, we focus on the Bamako form, an ecotype characterized by low inversion polymorphism and fixation of an inversion, 2Rj, that is very rare or absent in all other forms of A. gambiae. The Bamako form has a restricted distribution by the upper Niger River and its tributaries that is associated with a distinctive type of larval habitat, laterite rock pools, hypothesized to be its optimal breeding site. We first present computer simulations to investigate whether the population dynamics of A. gambiae are consistent with chromosomal speciation by ecotypification. The models are parameterized using field observations on the various forms of A. gambiae that exist in Mali, West Africa. We then report on the distribution of larvae of this species collected from rock pools and more characteristic breeding sites nearby. Both the simulations and field observations support the thesis that speciation by ecotypification is occurring, or has occurred, prompting consideration of Bamako as an independent species. PMID:18287019
An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
Willis, Matthew P.; Stevenson, Shawn M.; Pearl, Thomas P.; Mantooth, Brent A.
2014-01-01
The ability to directly characterize chemical transport and interactions that occur within a material (i.e., subsurface dynamics) is a vital component in understanding contaminant mass transport and the ability to decontaminate materials. If a material is contaminated, over time, the transport of highly toxic chemicals (such as chemical warfare agent species) out of the material can result in vapor exposure or transfer to the skin, which can result in percutaneous exposure to personnel who interact with the material. Due to the high toxicity of chemical warfare agents, the release of trace chemical quantities is of significant concern. Mapping subsurface concentration distribution and transport characteristics of absorbed agents enables exposure hazards to be assessed in untested conditions. Furthermore, these tools can be used to characterize subsurface reaction dynamics to ultimately design improved decontaminants or decontamination procedures. To achieve this goal, an inverse analysis mass transport modeling approach was developed that utilizes time-resolved mass spectroscopy measurements of vapor emission from contaminated paint coatings as the input parameter for calculation of subsurface concentration profiles. Details are provided on sample preparation, including contaminant and material handling, the application of mass spectrometry for the measurement of emitted contaminant vapor, and the implementation of inverse analysis using a physics-based diffusion model to determine transport properties of live chemical warfare agents including distilled mustard (HD) and the nerve agent VX. PMID:25226346
1993-10-01
Structures: Simultaneous Trajectory Tracking and Vibration Reduction ... 10 3 . Buckling Control of a Flexible Beam Using Piezoelectric Actuators...bounded solution for the inverse dynamic torque has to be non-causal. Bayo, et. al. [ 3 ], extended the inverse dynamics to planar, multiple-link systems...presented by &ayo and Moulin [4] for the single link system, with provisions for 3 extension to multiple link systems. An equivalent time domain approach for
Suspension parameter estimation in the frequency domain using a matrix inversion approach
NASA Astrophysics Data System (ADS)
Thite, A. N.; Banvidi, S.; Ibicek, T.; Bennett, L.
2011-12-01
The dynamic lumped parameter models used to optimise the ride and handling of a vehicle require base values of the suspension parameters. These parameters are generally experimentally identified. The accuracy of identified parameters can depend on the measurement noise and the validity of the model used. The existing publications on suspension parameter identification are generally based on the time domain and use a limited degree of freedom. Further, the data used are either from a simulated 'experiment' or from a laboratory test on an idealised quarter or a half-car model. In this paper, a method is developed in the frequency domain which effectively accounts for the measurement noise. Additional dynamic constraining equations are incorporated and the proposed formulation results in a matrix inversion approach. The nonlinearities in damping are estimated, however, using a time-domain approach. Full-scale 4-post rig test data of a vehicle are used. The variations in the results are discussed using the modal resonant behaviour. Further, a method is implemented to show how the results can be improved when the matrix inverted is ill-conditioned. The case study shows a good agreement between the estimates based on the proposed frequency-domain approach and measurable physical parameters.
Wavelet-based spectral finite element dynamic analysis for an axially moving Timoshenko beam
NASA Astrophysics Data System (ADS)
Mokhtari, Ali; Mirdamadi, Hamid Reza; Ghayour, Mostafa
2017-08-01
In this article, wavelet-based spectral finite element (WSFE) model is formulated for time domain and wave domain dynamic analysis of an axially moving Timoshenko beam subjected to axial pretension. The formulation is similar to conventional FFT-based spectral finite element (SFE) model except that Daubechies wavelet basis functions are used for temporal discretization of the governing partial differential equations into a set of ordinary differential equations. The localized nature of Daubechies wavelet basis functions helps to rule out problems of SFE model due to periodicity assumption, especially during inverse Fourier transformation and back to time domain. The high accuracy of WSFE model is then evaluated by comparing its results with those of conventional finite element and SFE results. The effects of moving beam speed and axial tensile force on vibration and wave characteristics, and static and dynamic stabilities of moving beam are investigated.
Propeller sheet cavitation noise source modeling and inversion
NASA Astrophysics Data System (ADS)
Lee, Keunhwa; Lee, Jaehyuk; Kim, Dongho; Kim, Kyungseop; Seong, Woojae
2014-02-01
Propeller sheet cavitation is the main contributor to high level of noise and vibration in the after body of a ship. Full measurement of the cavitation-induced hull pressure over the entire surface of the affected area is desired but not practical. Therefore, using a few measurements on the outer hull above the propeller in a cavitation tunnel, empirical or semi-empirical techniques based on physical model have been used to predict the hull-induced pressure (or hull-induced force). In this paper, with the analytic source model for sheet cavitation, a multi-parameter inversion scheme to find the positions of noise sources and their strengths is suggested. The inversion is posed as a nonlinear optimization problem, which is solved by the optimization algorithm based on the adaptive simplex simulated annealing algorithm. Then, the resulting hull pressure can be modeled with boundary element method from the inverted cavitation noise sources. The suggested approach is applied to the hull pressure data measured in a cavitation tunnel of the Samsung Heavy Industry. Two monopole sources are adequate to model the propeller sheet cavitation noise. The inverted source information is reasonable with the cavitation dynamics of the propeller and the modeled hull pressure shows good agreement with cavitation tunnel experimental data.
NASA Astrophysics Data System (ADS)
Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.
2018-06-01
Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.
Alonso, Rodrigo; Fernandez Martinez, Enrique; Gavela, M. B.; ...
2016-12-22
The gauging of the lepton flavour group is considered in the Standard Model context and in its extension with three right-handed neutrinos. The anomaly cancellation conditions lead to a Seesaw mechanism as underlying dynamics for all leptons; in addition, it requires a phenomenologically viable setup which leads to Majorana masses for the neutral sector: the type I Seesaw Lagrangian in the Standard Model case and the inverse Seesaw in the extended model. Within the minimal extension of the scalar sector, the Yukawa couplings are promoted to scalar fields in the bifundamental of the flavour group. The resulting low-energy Yukawa couplingsmore » are proportional to inverse powers of the vacuum expectation values of those scalars; the protection against flavour changing neutral currents differs from that of Minimal Flavour Violation. In every case, the μ - τ flavour sector exhibits rich and promising phenomenological signals.« less
An inverse problem for a mathematical model of aquaponic agriculture
NASA Astrophysics Data System (ADS)
Bobak, Carly; Kunze, Herb
2017-01-01
Aquaponic agriculture is a sustainable ecosystem that relies on a symbiotic relationship between fish and macrophytes. While the practice has been growing in popularity, relatively little mathematical models exist which aim to study the system processes. In this paper, we present a system of ODEs which aims to mathematically model the population and concetrations dynamics present in an aquaponic environment. Values of the parameters in the system are estimated from the literature so that simulated results can be presented to illustrate the nature of the solutions to the system. As well, a brief sensitivity analysis is performed in order to identify redundant parameters and highlight those which may need more reliable estimates. Specifically, an inverse problem with manufactured data for fish and plants is presented to demonstrate the ability of the collage theorem to recover parameter estimates.
Quantum dynamics of hydrogen atoms on graphene. I. System-bath modeling.
Bonfanti, Matteo; Jackson, Bret; Hughes, Keith H; Burghardt, Irene; Martinazzo, Rocco
2015-09-28
An accurate system-bath model to investigate the quantum dynamics of hydrogen atoms chemisorbed on graphene is presented. The system comprises a hydrogen atom and the carbon atom from graphene that forms the covalent bond, and it is described by a previously developed 4D potential energy surface based on density functional theory ab initio data. The bath describes the rest of the carbon lattice and is obtained from an empirical force field through inversion of a classical equilibrium correlation function describing the hydrogen motion. By construction, model building easily accommodates improvements coming from the use of higher level electronic structure theory for the system. Further, it is well suited to a determination of the system-environment coupling by means of ab initio molecular dynamics. This paper details the system-bath modeling and shows its application to the quantum dynamics of vibrational relaxation of a chemisorbed hydrogen atom, which is here investigated at T = 0 K with the help of the multi-configuration time-dependent Hartree method. Paper II deals with the sticking dynamics.
Quantum dynamics of hydrogen atoms on graphene. I. System-bath modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bonfanti, Matteo, E-mail: matteo.bonfanti@unimi.it; Jackson, Bret; Hughes, Keith H.
2015-09-28
An accurate system-bath model to investigate the quantum dynamics of hydrogen atoms chemisorbed on graphene is presented. The system comprises a hydrogen atom and the carbon atom from graphene that forms the covalent bond, and it is described by a previously developed 4D potential energy surface based on density functional theory ab initio data. The bath describes the rest of the carbon lattice and is obtained from an empirical force field through inversion of a classical equilibrium correlation function describing the hydrogen motion. By construction, model building easily accommodates improvements coming from the use of higher level electronic structure theorymore » for the system. Further, it is well suited to a determination of the system-environment coupling by means of ab initio molecular dynamics. This paper details the system-bath modeling and shows its application to the quantum dynamics of vibrational relaxation of a chemisorbed hydrogen atom, which is here investigated at T = 0 K with the help of the multi-configuration time-dependent Hartree method. Paper II deals with the sticking dynamics.« less
Performance of an inverted pendulum model directly applied to normal human gait.
Buczek, Frank L; Cooney, Kevin M; Walker, Matthew R; Rainbow, Michael J; Concha, M Cecilia; Sanders, James O
2006-03-01
In clinical gait analysis, we strive to understand contributions to body support and propulsion as this forms a basis for treatment selection, yet the relative importance of gravitational forces and joint powers can be controversial even for normal gait. We hypothesized that an inverted pendulum model, propelled only by gravity, would be inadequate to predict velocities and ground reaction forces during gait. Unlike previous ballistic and passive dynamic walking studies, we directly compared model predictions to gait data for 24 normal children. We defined an inverted pendulum from the average center-of-pressure to the instantaneous center-of-mass, and derived equations of motion during single support that allowed a telescoping action. Forward and inverse dynamics predicted pendulum velocities and ground reaction forces, and these were statistically and graphically compared to actual gait data for identical strides. Results of forward dynamics replicated those in the literature, with reasonable predictions for velocities and anterior ground reaction forces, but poor predictions for vertical ground reaction forces. Deviations from actual values were explained by joint powers calculated for these subjects. With a telescoping action during inverse dynamics, predicted vertical forces improved dramatically and gained a dual-peak pattern previously missing in the literature, yet expected for normal gait. These improvements vanished when telescoping terms were set to zero. Because this telescoping action is difficult to explain without muscle activity, we believe these results support the need for both gravitational forces and joint powers in normal gait. Our approach also begins to quantify the relative contributions of each.
Takamuku, Shinya; Gomi, Hiroaki
2015-07-22
How our central nervous system (CNS) learns and exploits relationships between force and motion is a fundamental issue in computational neuroscience. While several lines of evidence have suggested that the CNS predicts motion states and signals from motor commands for control and perception (forward dynamics), it remains controversial whether it also performs the 'inverse' computation, i.e. the estimation of force from motion (inverse dynamics). Here, we show that the resistive sensation we experience while moving a delayed cursor, perceived purely from the change in visual motion, provides evidence of the inverse computation. To clearly specify the computational process underlying the sensation, we systematically varied the visual feedback and examined its effect on the strength of the sensation. In contrast to the prevailing theory that sensory prediction errors modulate our perception, the sensation did not correlate with errors in cursor motion due to the delay. Instead, it correlated with the amount of exposure to the forward acceleration of the cursor. This indicates that the delayed cursor is interpreted as a mechanical load, and the sensation represents its visually implied reaction force. Namely, the CNS automatically computes inverse dynamics, using visually detected motions, to monitor the dynamic forces involved in our actions. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Zhu, Zhiwei; Zhou, Xiaoqin
2012-01-01
The main contribution of this paper is the development of a linearized model for describing the dynamic hysteresis behaviors of piezoelectrically actuated fast tool servo (FTS). A linearized hysteresis force model is proposed and mathematically described by a fractional order differential equation. Combining the dynamic modeling of the FTS mechanism, a linearized fractional order dynamic hysteresis (LFDH) model for the piezoelectrically actuated FTS is established. The unique features of the LFDH model could be summarized as follows: (a) It could well describe the rate-dependent hysteresis due to its intrinsic characteristics of frequency-dependent nonlinear phase shifts and amplitude modulations; (b) The linearization scheme of the LFDH model would make it easier to implement the inverse dynamic control on piezoelectrically actuated micro-systems. To verify the effectiveness of the proposed model, a series of experiments are conducted. The toolpaths of the FTS for creating two typical micro-functional surfaces involving various harmonic components with different frequencies and amplitudes are scaled and employed as command signals for the piezoelectric actuator. The modeling errors in the steady state are less than ±2.5% within the full span range which is much smaller than certain state-of-the-art modeling methods, demonstrating the efficiency and superiority of the proposed model for modeling dynamic hysteresis effects. Moreover, it indicates that the piezoelectrically actuated micro systems would be more suitably described as a fractional order dynamic system.
Validation of a "Kane's Dynamics" Model for the Active Rack Isolation System
NASA Technical Reports Server (NTRS)
Beech, Geoffrey S.; Hampton, R. David
2000-01-01
Many microgravity space-science experiments require vibratory acceleration levels unachievable without active isolation. The Boeing Corporation's Active Rack Isolation System (ARIS) employs a novel combination of magnetic actuation and mechanical linkages, to address these isolation requirements on the International Space Station (ISS). ARIS provides isolation at the rack (international Standard Payload Rack, or ISPR) level. Effective model-based vibration isolation requires (1) an isolation device, (2) an adequate dynamic (i.e., mathematical) model of that isolator, and (3) a suitable, corresponding controller, ARIS provides the ISS response to the first requirement. In November 1999, the authors presented a response to the second ("A 'Kane's Dynamics' model for the Active Rack Isolation System", Hampton and Beech) intended to facilitate an optimal-controls approach to the third. This paper documents the validation of that high-fidelity dynamic model of ARIS. As before, this model contains the full actuator dynamics, however, the umbilical models are not included in this presentation. The validation of this dynamics model was achieved by utilizing two Commercial Off the Shelf (COTS) software tools: Deneb's ENVISION, and Online Dynamics' AUTOLEV. ENVISION is a robotics software package developed for the automotive industry that employs 3-dimensional (3-D) Computer Aided Design (CAD) models to facilitate both forward and inverse kinematics analyses. AUTOLEV is a DOS based interpreter that is designed in general to solve vector based mathematical problems and specifically to solve Dynamics problems using Kane's method.
A spatial operator algebra for manipulator modeling and control
NASA Technical Reports Server (NTRS)
Rodriguez, G.; Kreutz, K.; Milman, M.
1988-01-01
A powerful new spatial operator algebra for modeling, control, and trajectory design of manipulators is discussed along with its implementation in the Ada programming language. Applications of this algebra to robotics include an operator representation of the manipulator Jacobian matrix; the robot dynamical equations formulated in terms of the spatial algebra, showing the complete equivalence between the recursive Newton-Euler formulations to robot dynamics; the operator factorization and inversion of the manipulator mass matrix which immediately results in O(N) recursive forward dynamics algorithms; the joint accelerations of a manipulator due to a tip contact force; the recursive computation of the equivalent mass matrix as seen at the tip of a manipulator; and recursive forward dynamics of a closed chain system. Finally, additional applications and current research involving the use of the spatial operator algebra are discussed in general terms.
Dissipative particle dynamics: Effects of thermostating schemes on nano-colloid electrophoresis
NASA Astrophysics Data System (ADS)
Hassanzadeh Afrouzi, Hamid; Moshfegh, Abouzar; Farhadi, Mousa; Sedighi, Kurosh
2018-05-01
A novel fully explicit approach using dissipative particle dynamics (DPD) method is introduced in the present study to model the electrophoretic transport of nano-colloids in an electrolyte solution. Slater type charge smearing function included in 3D Ewald summation method is employed to treat electrostatic interaction. Performance of various thermostats are challenged to control the system temperature and study the dynamic response of colloidal electrophoretic mobility under practical ranges of external electric field (0 . 072 < E < 0 . 361 v/nm) covering linear to non-linear response regime, and ionic salt concentration (0.049 < SC < 0 . 69 [M]) covering weak to strong Debye screening of the colloid. System temperature and electrophoretic mobility both show a direct and inverse relationships respectively with electric field and colloidal repulsion; although they each respectively behave direct and inverse trends with salt concentration under various thermostats. Nosé-Hoover-Lowe-Andersen and Lowe-Andersen thermostats are found to function more effectively under high electric fields (E > 0 . 145[v/nm ]) while thermal equilibrium is maintained. Reasonable agreements are achieved by benchmarking the system radial distribution function with available EW3D modellings, as well as comparing reduced mobility against conventional Smoluchowski and Hückel theories, and numerical solution of Poisson-Boltzmann equation.
Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.
Daunizeau, J; Friston, K J; Kiebel, S J
2009-11-01
In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; ...
2018-02-01
X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less
Development of automation and robotics for space via computer graphic simulation methods
NASA Technical Reports Server (NTRS)
Fernandez, Ken
1988-01-01
A robot simulation system, has been developed to perform automation and robotics system design studies. The system uses a procedure-oriented solid modeling language to produce a model of the robotic mechanism. The simulator generates the kinematics, inverse kinematics, dynamics, control, and real-time graphic simulations needed to evaluate the performance of the model. Simulation examples are presented, including simulation of the Space Station and the design of telerobotics for the Orbital Maneuvering Vehicle.
NASA Technical Reports Server (NTRS)
Burken, John J.
2005-01-01
This viewgraph presentation covers the following topics: 1) Brief explanation of Generation II Flight Program; 2) Motivation for Neural Network Adaptive Systems; 3) Past/ Current/ Future IFCS programs; 4) Dynamic Inverse Controller with Explicit Model; 5) Types of Neural Networks Investigated; and 6) Brief example
NASA Astrophysics Data System (ADS)
Chuvashov, I. N.
2011-07-01
In this paper complex of algorithms and programs for solving inverse problems of artificial earth satellite dynamics is described. Complex has been intended for satellite orbit improvement, calculation of motion model parameters and etc. Programs complex has been worked up for cluster "Skiff Cyberia". Results of numerical experiments obtained by using new complex in common the program "Numerical model of the system artificial satellites motion" is presented in this paper.
Flatness-based model inverse for feed-forward braking control
NASA Astrophysics Data System (ADS)
de Vries, Edwin; Fehn, Achim; Rixen, Daniel
2010-12-01
For modern cars an increasing number of driver assistance systems have been developed. Some of these systems interfere/assist with the braking of a car. Here, a brake actuation algorithm for each individual wheel that can respond to both driver inputs and artificial vehicle deceleration set points is developed. The algorithm consists of a feed-forward control that ensures, within the modelled system plant, the optimal behaviour of the vehicle. For the quarter-car model with LuGre-tyre behavioural model, an inverse model can be derived using v x as the 'flat output', that is, the input for the inverse model. A number of time derivatives of the flat output are required to calculate the model input, brake torque. Polynomial trajectory planning provides the needed time derivatives of the deceleration request. The transition time of the planning can be adjusted to meet actuator constraints. It is shown that the output of the trajectory planning would ripple and introduce a time delay when a gradual continuous increase of deceleration is requested by the driver. Derivative filters are then considered: the Bessel filter provides the best symmetry in its step response. A filter of same order and with negative real-poles is also used, exhibiting no overshoot nor ringing. For these reasons, the 'real-poles' filter would be preferred over the Bessel filter. The half-car model can be used to predict the change in normal load on the front and rear axle due to the pitching of the vehicle. The anticipated dynamic variation of the wheel load can be included in the inverse model, even though it is based on a quarter-car. Brake force distribution proportional to normal load is established. It provides more natural and simpler equations than a fixed force ratio strategy.
Open-ocean boundary conditions from interior data: Local and remote forcing of Massachusetts Bay
Bogden, P.S.; Malanotte-Rizzoli, P.; Signell, R.
1996-01-01
Massachusetts and Cape Cod Bays form a semienclosed coastal basin that opens onto the much larger Gulf of Maine. Subtidal circulation in the bay is driven by local winds and remotely driven flows from the gulf. The local-wind forced flow is estimated with a regional shallow water model driven by wind measurements. The model uses a gravity wave radiation condition along the open-ocean boundary. Results compare reasonably well with observed currents near the coast. In some offshore regions however, modeled flows are an order of magnitude less energetic than the data. Strong flows are observed even during periods of weak local wind forcing. Poor model-data comparisons are attributable, at least in part, to open-ocean boundary conditions that neglect the effects of remote forcing. Velocity measurements from within Massachusetts Bay are used to estimate the remotely forced component of the flow. The data are combined with shallow water dynamics in an inverse-model formulation that follows the theory of Bennett and McIntosh [1982], who considered tides. We extend their analysis to consider the subtidal response to transient forcing. The inverse model adjusts the a priori open-ocean boundary condition, thereby minimizing a combined measure of model-data misfit and boundary condition adjustment. A "consistency criterion" determines the optimal trade-off between the two. The criterion is based on a measure of plausibility for the inverse solution. The "consistent" inverse solution reproduces 56% of the average squared variation in the data. The local-wind-driven flow alone accounts for half of the model skill. The other half is attributable to remotely forced flows from the Gulf of Maine. The unexplained 44% comes from measurement errors and model errors that are not accounted for in the analysis.
X-38 Application of Dynamic Inversion Flight Control
NASA Technical Reports Server (NTRS)
Wacker, Roger; Munday, Steve; Merkle, Scott
2001-01-01
This paper summarizes the application of a nonlinear dynamic inversion (DI) flight control system (FCS) to an autonomous flight test vehicle in NASA's X-38 Project, a predecessor to the International Space Station (ISS) Crew Return Vehicle (CRV). Honeywell's Multi-Application Control-H (MACH) is a parameterized FCS design architecture including both model-based DI rate-compensation and classical P+I command-tracking. MACH was adopted by X-38 in order to shorten the design cycle time for different vehicle shapes and flight envelopes and evolving aerodynamic databases. Specific design issues and analysis results are presented for the application of MACH to the 3rd free flight (FF3) of X-38 Vehicle 132 (V132). This B-52 drop test, occurring on March 30, 2000, represents the first flight test of MACH and one of the first few known applications of DI in the primary FCS of an autonomous flight test vehicle.
Volcano Deformation and Eruption Forecasting using Data Assimilation: Building the Strategy
NASA Astrophysics Data System (ADS)
Bato, M. G.; Pinel, V.; Yan, Y.
2016-12-01
In monitoring active volcanoes, the magma overpressure is one of the key parameters used in forecasting volcanic eruptions. This can be inferred from the ground displacements measured on the Earth's surface by applying inversion techniques. However, during the inversion, we lose the temporal characteristic along with huge amount of information about the behaviour of the volcano. Our work focuses on developing a strategy in order to better forecast the magma overpressure using data assimilation. Data assimilation is a sequential time-forward process that best combines models and observations, sometimes a priori information based on error statistics, to predict the state of a dynamical system. It has gained popularity in various fields of geoscience (e.g. ocean-weather forecasting, geomagnetism and natural resources exploration), but remains a new and emerging technique in the field of volcanology. With the increasing amount of geodetic data (i.e. InSAR and GPS) recorded on volcanoes nowadays, and the wide-range availability of dynamical models that can provide better understanding about the volcano plumbing system; developing a forecasting framework that can efficiently combine them is crucial. Here, we particularly built our strategy on the basis of the Ensemble Kalman Filter (EnKF) [1]. We predict the temporal behaviours of the magma overpressures and surface deformations by adopting the two-magma chamber model proposed by Reverso et. al., 2014 [2] and by using synthetic GPS and/or InSAR data. Several tests are performed in order to answer the following: 1) know the efficiency of EnKF in forecasting volcanic unrests, 2) constrain unknown parameters of the model, 3) properly use GPS and/or InSAR during assimilation and 4) compare EnKF with classic inversion while using the same dynamical model. Results show that EnKF works well with the synthetic cases and there is a great potential in utilising the method for real-time monitoring of volcanic unrests. [1] Evensen, G., The Ensemble Kalman Filter: theoretical formulation and practical implementation. Ocean Dyn.,53, 343-367, 2003 [2] T. Reverso, J. Vandemeulebrouck, F. Jouanne, V. Pinel, T. Villemin, E. Sturkell, A two-magma chamber as a source of deformation at Grimsvötn volcano, Iceland, JGR, 2014
Spatial operator factorization and inversion of the manipulator mass matrix
NASA Technical Reports Server (NTRS)
Rodriguez, Guillermo; Kreutz-Delgado, Kenneth
1992-01-01
This paper advances two linear operator factorizations of the manipulator mass matrix. Embedded in the factorizations are many of the techniques that are regarded as very efficient computational solutions to inverse and forward dynamics problems. The operator factorizations provide a high-level architectural understanding of the mass matrix and its inverse, which is not visible in the detailed algorithms. They also lead to a new approach to the development of computer programs or organize complexity in robot dynamics.
An inverse dynamics approach to trajectory optimization for an aerospace plane
NASA Technical Reports Server (NTRS)
Lu, Ping
1992-01-01
An inverse dynamics approach for trajectory optimization is proposed. This technique can be useful in many difficult trajectory optimization and control problems. The application of the approach is exemplified by ascent trajectory optimization for an aerospace plane. Both minimum-fuel and minimax types of performance indices are considered. When rocket augmentation is available for ascent, it is shown that accurate orbital insertion can be achieved through the inverse control of the rocket in the presence of disturbances.
Estimates of CO2 fluxes over the city of Cape Town, South Africa, through Bayesian inverse modelling
NASA Astrophysics Data System (ADS)
Nickless, Alecia; Rayner, Peter J.; Engelbrecht, Francois; Brunke, Ernst-Günther; Erni, Birgit; Scholes, Robert J.
2018-04-01
We present a city-scale inversion over Cape Town, South Africa. Measurement sites for atmospheric CO2 concentrations were installed at Robben Island and Hangklip lighthouses, located downwind and upwind of the metropolis. Prior estimates of the fossil fuel fluxes were obtained from a bespoke inventory analysis where emissions were spatially and temporally disaggregated and uncertainty estimates determined by means of error propagation techniques. Net ecosystem exchange (NEE) fluxes from biogenic processes were obtained from the land atmosphere exchange model CABLE (Community Atmosphere Biosphere Land Exchange). Uncertainty estimates were based on the estimates of net primary productivity. CABLE was dynamically coupled to the regional climate model CCAM (Conformal Cubic Atmospheric Model), which provided the climate inputs required to drive the Lagrangian particle dispersion model. The Bayesian inversion framework included a control vector where fossil fuel and NEE fluxes were solved for separately.Due to the large prior uncertainty prescribed to the NEE fluxes, the current inversion framework was unable to adequately distinguish between the fossil fuel and NEE fluxes, but the inversion was able to obtain improved estimates of the total fluxes within pixels and across the domain. The median of the uncertainty reductions of the total weekly flux estimates for the inversion domain of Cape Town was 28 %, but reach as high as 50 %. At the pixel level, uncertainty reductions of the total weekly flux reached up to 98 %, but these large uncertainty reductions were for NEE-dominated pixels. Improved corrections to the fossil fuel fluxes would be possible if the uncertainty around the prior NEE fluxes could be reduced. In order for this inversion framework to be operationalised for monitoring, reporting, and verification (MRV) of emissions from Cape Town, the NEE component of the CO2 budget needs to be better understood. Additional measurements of Δ14C and δ13C isotope measurements would be a beneficial component of an atmospheric monitoring programme aimed at MRV of CO2 for any city which has significant biogenic influence, allowing improved separation of contributions from NEE and fossil fuel fluxes to the observed CO2 concentration.
Geomagnetic inverse problem and data assimilation: a progress report
NASA Astrophysics Data System (ADS)
Aubert, Julien; Fournier, Alexandre
2013-04-01
In this presentation I will present two studies recently undertaken by our group in an effort to bring the benefits of data assimilation to the study of Earth's magnetic field and the dynamics of its liquid iron core, where the geodynamo operates. In a first part I will focus on the geomagnetic inverse problem, which attempts to recover the fluid flow in the core from the temporal variation of the magnetic field (known as the secular variation). Geomagnetic data can be downward continued from the surface of the Earth down to the core-mantle boundary, but not further below, since the core is an electrical conductor. Historically, solutions to the geomagnetic inverse problem in such a sparsely observed system were thus found only for flow immediately below the core mantle boundary. We have recently shown that combining a numerical model of the geodynamo together with magnetic observations, through the use of Kalman filtering, now allows to present solutions for flow throughout the core. In a second part, I will present synthetic tests of sequential geomagnetic data assimilation aiming at evaluating the range at which the future of the geodynamo can be predicted, and our corresponding prospects to refine the current geomagnetic predictions. Fournier, Aubert, Thébault: Inference on core surface flow from observations and 3-D dynamo modelling, Geophys. J. Int. 186, 118-136, 2011, doi: 10.1111/j.1365-246X.2011.05037.x Aubert, Fournier: Inferring internal properties of Earth's core dynamics and their evolution from surface observations and a numerical geodynamo model, Nonlinear Proc. Geoph. 18, 657-674, 2011, doi:10.5194/npg-18-657-2011 Aubert: Flow throughout the Earth's core inverted from geomagnetic observations and numerical dynamo models, Geophys. J. Int., 2012, doi: 10.1093/gji/ggs051
NASA Astrophysics Data System (ADS)
Brossier, Romain; Zhou, Wei; Operto, Stéphane; Virieux, Jean
2015-04-01
Full Waveform Inversion (FWI) is an appealing method for quantitative high-resolution subsurface imaging (Virieux et al., 2009). For crustal-scales exploration from surface seismic, FWI generally succeeds in recovering a broadband of wavenumbers in the shallow part of the targeted medium taking advantage of the broad scattering-angle provided by both reflected and diving waves. In contrast, deeper targets are often only illuminated by short-spread reflections, which favor the reconstruction of the short wavelengths at the expense of the longer ones, leading to a possible notch in the intermediate part of the wavenumber spectrum. To update the velocity macromodel from reflection data, image-domain strategies (e.g., Symes & Carazzone, 1991) aim to maximize a semblance criterion in the migrated domain. Alternatively, recent data-domain strategies (e.g., Xu et al., 2012, Ma & Hale, 2013, Brossier et al., 2014), called Reflection FWI (RFWI), inspired by Chavent et al. (1994), rely on a scale separation between the velocity macromodel and prior knowledge of the reflectivity to emphasize the transmission regime in the sensitivity kernel of the inversion. However, all these strategies focus on reflected waves only, discarding the low-wavenumber information carried out by diving waves. With the current development of very long-offset and wide-azimuth acquisitions, a significant part of the recorded energy is provided by diving waves and subcritical reflections, and high-resolution tomographic methods should take advantage of all types of waves. In this presentation, we will first review the issues of classical FWI when applied to reflected waves and how RFWI is able to retrieve the long wavelength of the model. We then propose a unified formulation of FWI (Zhou et al., 2014) to update the low wavenumbers of the velocity model by the joint inversion of diving and reflected arrivals, while the impedance model is updated thanks to reflected wave only. An alternate inversion of high wavenumber impedance model and low wavenumber velocity model is performed to iteratively improve subsurface models. References : Brossier, R., Operto, S. & Virieux, J., 2014. Velocity model building from seismic reflection data by full waveform inversion, Geophysical Prospecting, doi:10.1111/1365-2478.12190 Chavent, G., Clément, F. & Gomez, S., 1994.Automatic determination of velocities via migration-based traveltime waveform inversion: A synthetic data example, SEG Technical Program Expanded Abstracts 1994, pp. 1179--1182. Ma, Y. & Hale, D., 2013. Wave-equation reflection traveltime inversion with dynamic warping and full waveform inversion, Geophysics, 78(6), R223--R233. Symes, W.W. & Carazzone, J.J., 1991. Velocity inversion by differential semblance optimization, Geophysics, 56, 654--663. Virieux, J. & Operto, S., 2009. An overview of full waveform inversion in exploration geophysics, Geophysics, 74(6), WCC1--WCC26. Xu, S., Wang, D., Chen, F., Lambaré, G. & Zhang, Y., 2012. Inversion on reflected seismic wave, SEG Technical Program Expanded Abstracts 2012, pp. 1--7. Zhou, W., Brossier, R., Operto, S., & Virieux, J., 2014. Acoustic multiparameter full-waveform inversion through a hierachical scheme, in SEG Technical Program Expanded Abstracts 2014, pp. 1249--1253
A Hybrid Approach to Data Assimilation for Reconstructing the Evolution of Mantle Dynamics
NASA Astrophysics Data System (ADS)
Zhou, Quan; Liu, Lijun
2017-11-01
Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation approach that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics the best.
NASA Astrophysics Data System (ADS)
Zhou, Q.; Liu, L.
2017-12-01
Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation method that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics to the best.
Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft
NASA Technical Reports Server (NTRS)
Burken, John J.
2007-01-01
This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.
Mean field dynamics of some open quantum systems
NASA Astrophysics Data System (ADS)
Merkli, Marco; Rafiyi, Alireza
2018-04-01
We consider a large number N of quantum particles coupled via a mean field interaction to another quantum system (reservoir). Our main result is an expansion for the averages of observables, both of the particles and of the reservoir, in inverse powers of √{N }. The analysis is based directly on the Dyson series expansion of the propagator. We analyse the dynamics, in the limit N →∞ , of observables of a fixed number n of particles, of extensive particle observables and their fluctuations, as well as of reservoir observables. We illustrate our results on the infinite mode Dicke model and on various energy-conserving models.
Mean field dynamics of some open quantum systems.
Merkli, Marco; Rafiyi, Alireza
2018-04-01
We consider a large number N of quantum particles coupled via a mean field interaction to another quantum system (reservoir). Our main result is an expansion for the averages of observables, both of the particles and of the reservoir, in inverse powers of [Formula: see text]. The analysis is based directly on the Dyson series expansion of the propagator. We analyse the dynamics, in the limit [Formula: see text], of observables of a fixed number n of particles, of extensive particle observables and their fluctuations, as well as of reservoir observables. We illustrate our results on the infinite mode Dicke model and on various energy-conserving models.
Interplay between dewetting and layer inversion in poly(4-vinylpyridine)/polystyrene bilayers.
Thickett, Stuart C; Harris, Andrew; Neto, Chiara
2010-10-19
We investigated the morphology and dynamics of the dewetting of metastable poly(4-vinylpyridine) (P4VP) thin films situated on top of polystyrene (PS) thin films as a function of the molecular weight and thickness of both films. We focused on the competition between the dewetting process, occurring as a result of unfavorable intermolecular interactions at the P4VP/PS interface, and layer inversion due to the lower surface energy of PS. By means of optical and atomic force microscopy (AFM), we observed how both the dynamics of the instability and the morphology of the emerging patterns depend on the ratio of the molecular weights of the polymer films. When the bottom PS layer was less viscous than the top P4VP layer (liquid-liquid dewetting), nucleated holes in the P4VP film typically stopped growing at long annealing times because of a combination of viscous dissipation in the bottom layer and partial layer inversion. Full layer inversion was achieved when the viscosity of the top P4VP layer was significantly greater (>10⁴) than the viscosity of the PS layer underneath, which is attributed to strongly different mobilities of the two layers. The density of holes produced by nucleation dewetting was observed for the first time to depend on the thickness of the top film as well as the polymer molecular weight. The final (completely dewetted) morphology of isolated droplets could be achieved only if the time frame of layer inversion was significantly slower than that of dewetting, which was characteristic of high-viscosity PS underlayers that allowed dewetting to fall into a liquid-solid regime. Assuming a simple reptation model for layer inversion occurring at the dewetting front, the observed surface morphologies could be predicted on the basis of the relative rates of dewetting and layer inversion.
Efficacy of an ankle brace with a subtalar locking system in inversion control in dynamic movements.
Zhang, Songning; Wortley, Michael; Chen, Qingjian; Freedman, Julia
2009-12-01
Controlled laboratory study. To examine effectiveness of an ankle brace with a subtalar locking system in restricting ankle inversion during passive and dynamic movements. Semirigid ankle braces are considered more effective in restricting ankle inversion than other types of brace, but a semirigid brace with a subtalar locking system may be even more effective. Nineteen healthy subjects with no history of major lower extremity injuries were included in the study. Participants performed 5 trials of an ankle inversion drop test and a lateral-cutting movement without wearing a brace and while wearing either the Element (with the subtalar locking system), a Functional ankle brace, or an ASO ankle brace. A 2-way repeated-measures analysis of variance (ANOVA) was used to assess brace differences (P?.05). All 3 braces significantly reduced total passive ankle frontal plane range of motion (ROM), with the Element ankle brace being the most effective. For the inversion drop the results showed significant reductions in peak ankle inversion angle and inversion ROM for all 3 braces compared to the no brace condition; and the peak inversion velocity was also reduced for the Element brace and the Functional brace. In the lateral-cutting movement, a small but significant reduction of the peak inversion angle in early foot contact and the peak eversion velocity at push-off were seen when wearing the Element and the Functional ankle braces compared to the no brace condition. Peak vertical ground reaction force was reduced for the Element brace compared to the ASO brace and the no brace conditions. These results suggest that the tested ankle braces, especially the Element brace, provided effective restriction of ankle inversion during both passive and dynamic movements.
Nelson, Emily S; Mulugeta, Lealem; Feola, Andrew; Raykin, Julia; Myers, Jerry G; Samuels, Brian C; Ethier, C Ross
2017-08-01
Exposure to microgravity causes a bulk fluid shift toward the head, with concomitant changes in blood volume/pressure, and intraocular pressure (IOP). These and other factors, such as intracranial pressure (ICP) changes, are suspected to be involved in the degradation of visual function and ocular anatomical changes exhibited by some astronauts. This is a significant health concern. Here, we describe a lumped-parameter numerical model to simulate volume/pressure alterations in the eye during gravitational changes. The model includes the effects of blood and aqueous humor dynamics, ICP, and IOP-dependent ocular compliance. It is formulated as a series of coupled differential equations and was validated against four existing data sets on parabolic flight, body inversion, and head-down tilt (HDT). The model accurately predicted acute IOP changes in parabolic flight and HDT, and was satisfactory for the more extreme case of inversion. The short-term response to the changing gravitational field was dominated by ocular blood pressures and compliance, while longer-term responses were more dependent on aqueous humor dynamics. ICP had a negligible effect on acute IOP changes. This relatively simple numerical model shows promising predictive capability. To extend the model to more chronic conditions, additional data on longer-term autoregulation of blood and aqueous humor dynamics are needed. NEW & NOTEWORTHY A significant percentage of astronauts present anatomical changes in the posterior eye tissues after spaceflight. Hypothesized increases in ocular blood volume and intracranial pressure (ICP) in space have been considered to be likely factors. In this work, we provide a novel numerical model of the eye that incorporates ocular hemodynamics, gravitational forces, and ICP changes. We find that changes in ocular hemodynamics govern the response of intraocular pressure during acute gravitational change. Copyright © 2017 the American Physiological Society.
Universal inverse power-law distribution for temperature and rainfall in the UK region
NASA Astrophysics Data System (ADS)
Selvam, A. M.
2014-06-01
Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.
Modeling of laser induced air plasma and shock wave dynamics using 2D-hydrodynamic simulations
NASA Astrophysics Data System (ADS)
Paturi, Prem Kiran; S, Sai Shiva; Chelikani, Leela; Ikkurthi, Venkata Ramana; C. D., Sijoy; Chaturvedi, Shashank; Acrhem, University Of Hyderabad Team; Computational Analysis Division, Bhabha Atomic Research Centre, Visakhapatnam Team
2017-06-01
The laser induced air plasma dynamics and the SW evolution modeled using the two dimensional hydrodynamic code by considering two different EOS: ideal gas EOS with charge state effects taken into consideration and Chemical Equilibrium applications (CEA) EOS considering the chemical kinetics of different species will be presented. The inverse bremsstrahlung absorption process due to electron-ion and electron-neutrals is considered for the laser-air interaction process for both the models. The numerical results obtained with the two models were compared with that of the experimental observations over the time scales of 200 - 4000 ns at an input laser intensity of 2.3 ×1010 W/cm2. The comparison shows that the plasma and shock dynamics differ significantly for two EOS considered. With the ideas gas EOS the asymmetric expansion and the subsequent plasma dynamics have been well reproduced as observed in the experiments, whereas with the CEA model these processes were not reproduced due to the laser energy absorption occurring mostly at the focal volume. ACRHEM team thank DRDO, India for funding.
A spring-block analogy for the dynamics of stock indexes
NASA Astrophysics Data System (ADS)
Sándor, Bulcsú; Néda, Zoltán
2015-06-01
A spring-block chain placed on a running conveyor belt is considered for modeling stylized facts observed in the dynamics of stock indexes. Individual stocks are modeled by the blocks, while the stock-stock correlations are introduced via simple elastic forces acting in the springs. The dragging effect of the moving belt corresponds to the expected economic growth. The spring-block system produces collective behavior and avalanche like phenomena, similar to the ones observed in stock markets. An artificial index is defined for the spring-block chain, and its dynamics is compared with the one measured for the Dow Jones Industrial Average. For certain parameter regions the model reproduces qualitatively well the dynamics of the logarithmic index, the logarithmic returns, the distribution of the logarithmic returns, the avalanche-size distribution and the distribution of the investment horizons. A noticeable success of the model is that it is able to account for the gain-loss asymmetry observed in the inverse statistics. Our approach has mainly a pedagogical value, bridging between a complex socio-economic phenomena and a basic (mechanical) model in physics.
Estimating net joint torques from kinesiological data using optimal linear system theory.
Runge, C F; Zajac, F E; Allum, J H; Risher, D W; Bryson, A E; Honegger, F
1995-12-01
Net joint torques (NJT) are frequently computed to provide insights into the motor control of dynamic biomechanical systems. An inverse dynamics approach is almost always used, whereby the NJT are computed from 1) kinematic measurements (e.g., position of the segments), 2) kinetic measurements (e.g., ground reaction forces) that are, in effect, constraints defining unmeasured kinematic quantities based on a dynamic segmental model, and 3) numerical differentiation of the measured kinematics to estimate velocities and accelerations that are, in effect, additional constraints. Due to errors in the measurements, the segmental model, and the differentiation process, estimated NJT rarely produce the observed movement in a forward simulation when the dynamics of the segmental system are inherently unstable (e.g., human walking). Forward dynamic simulations are, however, essential to studies of muscle coordination. We have developed an alternative approach, using the linear quadratic follower (LQF) algorithm, which computes the NJT such that a stable simulation of the observed movement is produced and the measurements are replicated as well as possible. The LQF algorithm does not employ constraints depending on explicit differentiation of the kinematic data, but rather employs those depending on specification of a cost function, based on quantitative assumptions about data confidence. We illustrate the usefulness of the LQF approach by using it to estimate NJT exerted by standing humans perturbed by support-surface movements. We show that unless the number of kinematic and force variables recorded is sufficiently high, the confidence that can be placed in the estimates of the NJT, obtained by any method (e.g., LQF, or the inverse dynamics approach), may be unsatisfactorily low.
A fast new algorithm for a robot neurocontroller using inverse QR decomposition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morris, A.S.; Khemaissia, S.
2000-01-01
A new adaptive neural network controller for robots is presented. The controller is based on direct adaptive techniques. Unlike many neural network controllers in the literature, inverse dynamical model evaluation is not required. A numerically robust, computationally efficient processing scheme for neutral network weight estimation is described, namely, the inverse QR decomposition (INVQR). The inverse QR decomposition and a weighted recursive least-squares (WRLS) method for neural network weight estimation is derived using Cholesky factorization of the data matrix. The algorithm that performs the efficient INVQR of the underlying space-time data matrix may be implemented in parallel on a triangular array.more » Furthermore, its systolic architecture is well suited for VLSI implementation. Another important benefit is well suited for VLSI implementation. Another important benefit of the INVQR decomposition is that it solves directly for the time-recursive least-squares filter vector, while avoiding the sequential back-substitution step required by the QR decomposition approaches.« less
Electron-phonon thermalization in a scalable method for real-time quantum dynamics
Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; ...
2016-01-27
Here, we present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicitmore » quantum dynamics.« less
Uncertainty quantification for PZT bimorph actuators
NASA Astrophysics Data System (ADS)
Bravo, Nikolas; Smith, Ralph C.; Crews, John
2018-03-01
In this paper, we discuss the development of a high fidelity model for a PZT bimorph actuator used for micro-air vehicles, which includes the Robobee. We developed a high-fidelity model for the actuator using the homogenized energy model (HEM) framework, which quantifies the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in dynamic operating regimes. We then discussed an inverse problem on the model. We included local and global sensitivity analysis of the parameters in the high-fidelity model. Finally, we will discuss the results of Bayesian inference and uncertainty quantification on the HEM.
Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.
Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less
Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts
Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.; ...
2016-10-10
Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan
X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) reveal materials dynamics using coherent scattering, with XPCS permitting the investigation of dynamics in a more diverse array of materials than DLS. Heterogeneous dynamics occur in many material systems. The authors' recent work has shown how classic tools employed in the DLS analysis of heterogeneous dynamics can be extended to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. The present work describes the software implementation of inverse transform analysis of XPCS data. This software, calledCONTIN XPCS, is an extension of traditionalCONTINanalysis and accommodates the various dynamics encountered inmore » equilibrium XPCS measurements.« less
Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; ...
2018-02-01
X-ray photon correlation spectroscopy (XPCS) and dynamic light scattering (DLS) reveal materials dynamics using coherent scattering, with XPCS permitting the investigation of dynamics in a more diverse array of materials than DLS. Heterogeneous dynamics occur in many material systems. The authors' recent work has shown how classic tools employed in the DLS analysis of heterogeneous dynamics can be extended to XPCS, revealing additional information that conventional Kohlrausch exponential fitting obscures. The present work describes the software implementation of inverse transform analysis of XPCS data. This software, calledCONTIN XPCS, is an extension of traditionalCONTINanalysis and accommodates the various dynamics encountered inmore » equilibrium XPCS measurements.« less
Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène
2015-03-01
Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.
Relationship between synoptic scale weather systems and column averaged atmospheric CO2
NASA Astrophysics Data System (ADS)
Naja, M.; Yaremchuk, A.; Onishi, R.; Maksyutov, S.; Inoue, G.
2005-12-01
Analysis of the atmospheric CO2 observations with transport models contributes to the understanding of the geographical distributions of CO2 sources and sinks. Space-borne sensors could be advantageous for CO2 measurements as they can provide wider spatial and temporal coverage. Inversion studies have suggested requirement of better than 1% precision for the space-borne observations. Since sources and sinks are inferred from spatial and temporal gradients in CO2, the space-borne observations must have no significant geographically varying biases. To study the dynamical biases in column CO2 due to possible correlation between clouds and atmospheric CO2 at synoptic scale, we have made simulations of CO2 (1988-2003) using NIES tracer transport model. Model resolution is 2.5o x 2.5o in horizontal and it has 15 vertical sigma-layers. Fluxes for (1) fossil fuels, (2) terrestrial biosphere (CASA NEP), (3) the oceans, and (4) inverse model derived monthly regional fluxes from 11 land and 11 ocean regions are used. SVD truncation is used to filter out noise in the inverse model flux time series. Model reproduces fairly well CO2 global trend and observed time series at monitoring sites around the globe. Lower column CO2 concentration is simulated inside cyclonic systems in summer over North hemispheric continental areas. Surface pressure is used as a proxy for dynamics and it is demonstrated that anomalies in column averaged CO2 has fairly good correlation with the anomalies in surface pressure. Positive correlation, as high as 0.7, has been estimated over parts of Siberia and N. America in summer time. Our explanation is based on that the low-pressure system is associated the upward motion, which leads to lower column CO2 values over these regions due to lifting of CO2-depleted summertime PBL air, and higher column CO2 over source areas. A sensitivity study without inverse model fluxes shows same correlation. The low-pressure systems' induced negative biases are 0.4-0.6 ppmv in summer over Siberia. Therefore it is essential to consider this bias due to covariance with vertical motion, while analyzing the column CO2 from space-borne observations together with in-situ observations, because most optical observations are not available under cloudy conditions typical for the low-pressure system.
Abbasi, Mostafa; Barakat, Mohammed S; Vahidkhah, Koohyar; Azadani, Ali N
2016-09-01
Computational modeling has an important role in design and assessment of medical devices. In computational simulations, considering accurate constitutive models is of the utmost importance to capture mechanical response of soft tissue and biomedical materials under physiological loading conditions. Lack of comprehensive three-dimensional constitutive models for soft tissue limits the effectiveness of computational modeling in research and development of medical devices. The aim of this study was to use inverse finite element (FE) analysis to determine three-dimensional mechanical properties of bovine pericardial leaflets of a surgical bioprosthesis under dynamic loading condition. Using inverse parameter estimation, 3D anisotropic Fung model parameters were estimated for the leaflets. The FE simulations were validated using experimental in-vitro measurements, and the impact of different constitutive material models was investigated on leaflet stress distribution. The results of this study showed that the anisotropic Fung model accurately simulated the leaflet deformation and coaptation during valve opening and closing. During systole, the peak stress reached to 3.17MPa at the leaflet boundary while during diastole high stress regions were primarily observed in the commissures with the peak stress of 1.17MPa. In addition, the Rayleigh damping coefficient that was introduced to FE simulations to simulate viscous damping effects of surrounding fluid was determined. Copyright © 2016 Elsevier Ltd. All rights reserved.
Phase Inversion of EPDM/PP Blends: Effect of Viscosity Ratio
NASA Astrophysics Data System (ADS)
Machado, Ana Vera; Antunes, Carla Filipa; van Duin, Martin
2011-07-01
EPDM/PP blends and TPVs with and without crosslinking, respectively, were prepared, in a batch mixer, using three different EPDM rubbers. EPDM/PP based TPVs were dynamic vulcanised using the resol/SnCl2 system. Samples were collected along the time in order to get information on the morphology evolution and crosslinking density during dynamic vulcanisation. The morphology was studied by SEM and the crosslink density by gel content. In the case of low viscosity EPDMs, crosslinking of the EPDM phase was retarded due to its low crosslinking efficiency. This delay on crosslinking reaction enables the observation of the various stages of the morphological mechanism that takes place during dynamic vulcanisation. It could be observed that phase inversion takes place via lamellar mechanism. More detailed insight on phase inversion mechanism during dynamic vulcanisation was accomplished.
Stability Result For Dynamic Inversion Devised to Control Large Flexible Aircraft
NASA Technical Reports Server (NTRS)
Gregory, Irene M.
2001-01-01
High performance aircraft of the future will be designed lighter, more maneuverable, and operate over an ever expanding flight envelope. One of the largest differences from the flight control perspective between current and future advanced aircraft is elasticity. Over the last decade, dynamic inversion methodology has gained considerable popularity in application to highly maneuverable fighter aircraft, which were treated as rigid vehicles. This paper is an initial attempt to establish global stability results for dynamic inversion methodology as applied to a large, flexible aircraft. This work builds on a previous result for rigid fighter aircraft and adds a new level of complexity that is the flexible aircraft dynamics, which cannot be ignored even in the most basic flight control. The results arise from observations of the control laws designed for a new generation of the High-Speed Civil Transport aircraft.
Evaluation of the power consumption of a high-speed parallel robot
NASA Astrophysics Data System (ADS)
Han, Gang; Xie, Fugui; Liu, Xin-Jun
2018-06-01
An inverse dynamic model of a high-speed parallel robot is established based on the virtual work principle. With this dynamic model, a new evaluation method is proposed to measure the power consumption of the robot during pick-and-place tasks. The power vector is extended in this method and used to represent the collinear velocity and acceleration of the moving platform. Afterward, several dynamic performance indices, which are homogenous and possess obvious physical meanings, are proposed. These indices can evaluate the power input and output transmissibility of the robot in a workspace. The distributions of the power input and output transmissibility of the high-speed parallel robot are derived with these indices and clearly illustrated in atlases. Furtherly, a low-power-consumption workspace is selected for the robot.
A fragmentation model of earthquake-like behavior in internet access activity
NASA Astrophysics Data System (ADS)
Paguirigan, Antonino A.; Angco, Marc Jordan G.; Bantang, Johnrob Y.
We present a fragmentation model that generates almost any inverse power-law size distribution, including dual-scaled versions, consistent with the underlying dynamics of systems with earthquake-like behavior. We apply the model to explain the dual-scaled power-law statistics observed in an Internet access dataset that covers more than 32 million requests. The non-Poissonian statistics of the requested data sizes m and the amount of time τ needed for complete processing are consistent with the Gutenberg-Richter-law. Inter-event times δt between subsequent requests are also shown to exhibit power-law distributions consistent with the generalized Omori law. Thus, the dataset is similar to the earthquake data except that two power-law regimes are observed. Using the proposed model, we are able to identify underlying dynamics responsible in generating the observed dual power-law distributions. The model is universal enough for its applicability to any physical and human dynamics that is limited by finite resources such as space, energy, time or opportunity.
NASA Astrophysics Data System (ADS)
Zhou, Renjie; So, Peter T. C.; Yaqoob, Zahid; Jin, Di; Hosseini, Poorya; Kuang, Cuifang; Singh, Vijay Raj; Kim, Yang-Hyo; Dasari, Ramachandra R.
2017-02-01
Most of the quantitative phase microscopy systems are unable to provide depth-resolved information for measuring complex biological structures. Optical diffraction tomography provides a non-trivial solution to it by 3D reconstructing the object with multiple measurements through different ways of realization. Previously, our lab developed a reflection-mode dynamic speckle-field phase microscopy (DSPM) technique, which can be used to perform depth resolved measurements in a single shot. Thus, this system is suitable for measuring dynamics in a layer of interest in the sample. DSPM can be also used for tomographic imaging, which promises to solve the long-existing "missing cone" problem in 3D imaging. However, the 3D imaging theory for this type of system has not been developed in the literature. Recently, we have developed an inverse scattering model to rigorously describe the imaging physics in DSPM. Our model is based on the diffraction tomography theory and the speckle statistics. Using our model, we first precisely calculated the defocus response and the depth resolution in our system. Then, we further calculated the 3D coherence transfer function to link the 3D object structural information with the axially scanned imaging data. From this transfer function, we found that in the reflection mode excellent sectioning effect exists in the low lateral spatial frequency region, thus allowing us to solve the "missing cone" problem. Currently, we are working on using this coherence transfer function to reconstruct layered structures and complex cells.
HOOKED FLARE RIBBONS AND FLUX-ROPE-RELATED QSL FOOTPRINTS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Jie; Li, Hui; Gilchrist, Stuart A.
2016-05-20
We studied the magnetic topology of active region 12158 on 2014 September 10 and compared it with the observations before and early in the flare that begins at 17:21 UT (SOL2014-09-10T17:45:00). Our results show that the sigmoidal structure and flare ribbons of this active region observed by the Solar Dynamics Observatory /Atmospheric Imaging Assembly can be well reproduced from a Grad–Rubin nonlinear force-free field extrapolation method. Various inverse-S- and inverse-J-shaped magnetic field lines, which surround a coronal flux rope, coincide with the sigmoid as observed in different extreme-ultraviolet wavelengths, including its multithreaded curved ends. Also, the observed distribution of surfacemore » currents in the magnetic polarity where it was not prescribed is well reproduced. This validates our numerical implementation and setup of the Grad–Rubin method. The modeled double inverse-J-shaped quasi-separatrix layer (QSL) footprints match the observed flare ribbons during the rising phase of the flare, including their hooked parts. The spiral-like shape of the latter may be related to a complex pre-eruptive flux rope with more than one turn of twist, as obtained in the model. These ribbon-associated flux-rope QSL footprints are consistent with the new standard flare model in 3D, with the presence of a hyperbolic flux tube located below an inverse-teardrop-shaped coronal QSL. This is a new step forward forecasting the locations of reconnection and ribbons in solar flares and the geometrical properties of eruptive flux ropes.« less
Development of the WRF-CO2 4D-Var assimilation system v1.0
NASA Astrophysics Data System (ADS)
Zheng, Tao; French, Nancy H. F.; Baxter, Martin
2018-05-01
Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var) assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF) modeling system, including the system coupled to chemistry (WRF-Chem), with tangent linear and adjoint codes (WRFPLUS), and with data assimilation (WRFDA), all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimization algorithm (L-BFGS-B) and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.
Stress drop with constant, scale independent seismic efficiency and overshoot
Beeler, N.M.
2001-01-01
To model dissipated and radiated energy during earthquake stress drop, I calculate dynamic fault slip using a single degree of freedom spring-slider block and a laboratory-based static/kinetic fault strength relation with a dynamic stress drop proportional to effective normal stress. The model is scaled to earthquake size assuming a circular rupture; stiffness varies inversely with rupture radius, and rupture duration is proportional to radius. Calculated seismic efficiency, the ratio of radiated to total energy expended during stress drop, is in good agreement with laboratory and field observations. Predicted overshoot, a measure of how much the static stress drop exceeds the dynamic stress drop, is higher than previously published laboratory and seismic observations and fully elasto-dynamic calculations. Seismic efficiency and overshoot are constant, independent of normal stress and scale. Calculated variation of apparent stress with seismic moment resembles the observational constraints of McGarr [1999].
Analysis of the August and November dynamical structures in the MLT region
NASA Astrophysics Data System (ADS)
Gusev, O.; Grossmann, K.-U.; Schmidt, H.
The inversion of the infrared limb radiance measurements made by {CR}yogenic {I}nfrared {S}pectrometers and {T}elescopes for the {A}tmosphere (CRISTA) satellite experiment provided a global dataset of pressures, temperatures and atmospheric gas number densities for November 1994 and August 1997 in the altitude range 7-180 km. The {HAM}burg {MO}del of the {N}eutral and {I}onized {A}tmosphere (HAMMONIA) is a general circulation and chemistry model covering the atmosphere from the Earth's surface up to about 250 km. To simulate the conditions found during both CRISTA time periods a special HAMMONIA run was performed. We discuss the MLT dynamical parameters found by analysing the measured and modelled data, their similarities and differences.
A simulation-based analytic model of radio galaxies
NASA Astrophysics Data System (ADS)
Hardcastle, M. J.
2018-04-01
I derive and discuss a simple semi-analytical model of the evolution of powerful radio galaxies which is not based on assumptions of self-similar growth, but rather implements some insights about the dynamics and energetics of these systems derived from numerical simulations, and can be applied to arbitrary pressure/density profiles of the host environment. The model can qualitatively and quantitatively reproduce the source dynamics and synchrotron light curves derived from numerical modelling. Approximate corrections for radiative and adiabatic losses allow it to predict the evolution of radio spectral index and of inverse-Compton emission both for active and `remnant' sources after the jet has turned off. Code to implement the model is publicly available. Using a standard model with a light relativistic (electron-positron) jet, subequipartition magnetic fields, and a range of realistic group/cluster environments, I simulate populations of sources and show that the model can reproduce the range of properties of powerful radio sources as well as observed trends in the relationship between jet power and radio luminosity, and predicts their dependence on redshift and environment. I show that the distribution of source lifetimes has a significant effect on both the source length distribution and the fraction of remnant sources expected in observations, and so can in principle be constrained by observations. The remnant fraction is expected to be low even at low redshift and low observing frequency due to the rapid luminosity evolution of remnants, and to tend rapidly to zero at high redshift due to inverse-Compton losses.
Universal characteristics of fractal fluctuations in prime number distribution
NASA Astrophysics Data System (ADS)
Selvam, A. M.
2014-11-01
The frequency of occurrence of prime numbers at unit number spacing intervals exhibits self-similar fractal fluctuations concomitant with inverse power law form for power spectrum generic to dynamical systems in nature such as fluid flows, stock market fluctuations and population dynamics. The physics of long-range correlations exhibited by fractals is not yet identified. A recently developed general systems theory visualizes the eddy continuum underlying fractals to result from the growth of large eddies as the integrated mean of enclosed small scale eddies, thereby generating a hierarchy of eddy circulations or an inter-connected network with associated long-range correlations. The model predictions are as follows: (1) The probability distribution and power spectrum of fractals follow the same inverse power law which is a function of the golden mean. The predicted inverse power law distribution is very close to the statistical normal distribution for fluctuations within two standard deviations from the mean of the distribution. (2) Fractals signify quantum-like chaos since variance spectrum represents probability density distribution, a characteristic of quantum systems such as electron or photon. (3) Fractal fluctuations of frequency distribution of prime numbers signify spontaneous organization of underlying continuum number field into the ordered pattern of the quasiperiodic Penrose tiling pattern. The model predictions are in agreement with the probability distributions and power spectra for different sets of frequency of occurrence of prime numbers at unit number interval for successive 1000 numbers. Prime numbers in the first 10 million numbers were used for the study.
Performance evaluation of the inverse dynamics method for optimal spacecraft reorientation
NASA Astrophysics Data System (ADS)
Ventura, Jacopo; Romano, Marcello; Walter, Ulrich
2015-05-01
This paper investigates the application of the inverse dynamics in the virtual domain method to Euler angles, quaternions, and modified Rodrigues parameters for rapid optimal attitude trajectory generation for spacecraft reorientation maneuvers. The impact of the virtual domain and attitude representation is numerically investigated for both minimum time and minimum energy problems. Owing to the nature of the inverse dynamics method, it yields sub-optimal solutions for minimum time problems. Furthermore, the virtual domain improves the optimality of the solution, but at the cost of more computational time. The attitude representation also affects solution quality and computational speed. For minimum energy problems, the optimal solution can be obtained without the virtual domain with any considered attitude representation.
Stochastic ontogenetic growth model
NASA Astrophysics Data System (ADS)
West, B. J.; West, D.
2012-02-01
An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tupek, Michael R.
2016-06-30
In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- putmore » parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.« less
Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew
2016-07-01
Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Takamuku, Shinya; Gomi, Hiroaki
2015-01-01
How our central nervous system (CNS) learns and exploits relationships between force and motion is a fundamental issue in computational neuroscience. While several lines of evidence have suggested that the CNS predicts motion states and signals from motor commands for control and perception (forward dynamics), it remains controversial whether it also performs the ‘inverse’ computation, i.e. the estimation of force from motion (inverse dynamics). Here, we show that the resistive sensation we experience while moving a delayed cursor, perceived purely from the change in visual motion, provides evidence of the inverse computation. To clearly specify the computational process underlying the sensation, we systematically varied the visual feedback and examined its effect on the strength of the sensation. In contrast to the prevailing theory that sensory prediction errors modulate our perception, the sensation did not correlate with errors in cursor motion due to the delay. Instead, it correlated with the amount of exposure to the forward acceleration of the cursor. This indicates that the delayed cursor is interpreted as a mechanical load, and the sensation represents its visually implied reaction force. Namely, the CNS automatically computes inverse dynamics, using visually detected motions, to monitor the dynamic forces involved in our actions. PMID:26156766
Rigatos, Gerasimos G; Rigatou, Efthymia G; Djida, Jean Daniel
2015-10-01
A method for early diagnosis of parametric changes in intracellular protein synthesis models (e.g. the p53 protein - mdm2 inhibitor model) is developed with the use of a nonlinear Kalman Filtering approach (Derivative-free nonlinear Kalman Filter) and of statistical change detection methods. The intracellular protein synthesis dynamic model is described by a set of coupled nonlinear differential equations. It is shown that such a dynamical system satisfies differential flatness properties and this allows to transform it, through a change of variables (diffeomorphism), to the so-called linear canonical form. For the linearized equivalent of the dynamical system, state estimation can be performed using the Kalman Filter recursion. Moreover, by applying an inverse transformation based on the previous diffeomorphism it becomes also possible to obtain estimates of the state variables of the initial nonlinear model. By comparing the output of the Kalman Filter (which is assumed to correspond to the undistorted dynamical model) with measurements obtained from the monitored protein synthesis system, a sequence of differences (residuals) is obtained. The statistical processing of the residuals with the use of x2 change detection tests, can provide indication within specific confidence intervals about parametric changes in the considered biological system and consequently indications about the appearance of specific diseases (e.g. malignancies).
Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle
NASA Technical Reports Server (NTRS)
Adams, Richard J.
1993-01-01
High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.
NASA Astrophysics Data System (ADS)
Selvam, A. M.
2017-01-01
Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).
Khodabandeloo, Babak; Melvin, Dyan; Jo, Hongki
2017-01-01
Direct measurements of external forces acting on a structure are infeasible in many cases. The Augmented Kalman Filter (AKF) has several attractive features that can be utilized to solve the inverse problem of identifying applied forces, as it requires the dynamic model and the measured responses of structure at only a few locations. But, the AKF intrinsically suffers from numerical instabilities when accelerations, which are the most common response measurements in structural dynamics, are the only measured responses. Although displacement measurements can be used to overcome the instability issue, the absolute displacement measurements are challenging and expensive for full-scale dynamic structures. In this paper, a reliable model-based data fusion approach to reconstruct dynamic forces applied to structures using heterogeneous structural measurements (i.e., strains and accelerations) in combination with AKF is investigated. The way of incorporating multi-sensor measurements in the AKF is formulated. Then the formulation is implemented and validated through numerical examples considering possible uncertainties in numerical modeling and sensor measurement. A planar truss example was chosen to clearly explain the formulation, while the method and formulation are applicable to other structures as well. PMID:29149088
Dynamics of a distributed drill string system: Characteristic parameters and stability maps
NASA Astrophysics Data System (ADS)
Aarsnes, Ulf Jakob F.; van de Wouw, Nathan
2018-03-01
This paper involves the dynamic (stability) analysis of distributed drill-string systems. A minimal set of parameters characterizing the linearized, axial-torsional dynamics of a distributed drill string coupled through the bit-rock interaction is derived. This is found to correspond to five parameters for a simple drill string and eight parameters for a two-sectioned drill-string (e.g., corresponding to the pipe and collar sections of a drilling system). These dynamic characterizations are used to plot the inverse gain margin of the system, parametrized in the non-dimensional parameters, effectively creating a stability map covering the full range of realistic physical parameters. This analysis reveals a complex spectrum of dynamics not evident in stability analysis with lumped models, thus indicating the importance of analysis using distributed models. Moreover, it reveals trends concerning stability properties depending on key system parameters useful in the context of system and control design aiming at the mitigation of vibrations.
NASA Astrophysics Data System (ADS)
Jia, Bing
One-parameter and two-parameter bifurcations of the Morris-Lecar (ML) neuron model with and without the fast inhibitory autapse, which is a synapse from a neuron onto itself, are investigated. The ML neuron model without autapse manifests an inverse Hopf bifurcation point from firing to a depolarized resting state with high level of membrane potential, with increasing depolarization current. When a fast inhibitory autapse is introduced, a negative feedback or inhibitory current is applied to the ML model. With increasing conductance of the autapse to middle level, the depolarized resting state near the inverse Hopf bifurcation point can change to oscillation and the parameter region of the oscillation becomes wide, which can be well interpreted by the dynamic responses of the depolarized resting state to the inhibitory current stimulus mediated by the autapse. The enlargement of the parameter region of the oscillation induced by the negative feedback presents a novel viewpoint different from the traditional one that inhibitory synapse often suppresses the neuronal oscillation activities. Furthermore, complex nonlinear dynamics such as the coexisting behaviors and codimension-2 bifurcations including the Bautin and cusp bifurcations are acquired. The relationship between the bifurcations and the depolarization block, a physiological concept that indicates a neuron can enter resting state when receiving the depolarization current, is discussed.
Contribution of tibiofemoral joint contact to net loads at the knee in gait.
Walter, Jonathan P; Korkmaz, Nuray; Fregly, Benjamin J; Pandy, Marcus G
2015-07-01
Inverse dynamics analysis is commonly used to estimate the net loads at a joint during human motion. Most lower-limb models of movement represent the knee as a simple hinge joint when calculating muscle forces. This approach is limited because it neglects the contributions from tibiofemoral joint contact forces and may therefore lead to errors in estimated muscle forces. The aim of this study was to quantify the contributions of tibiofemoral joint contact loads to the net knee loads calculated from inverse dynamics for multiple subjects and multiple gait patterns. Tibiofemoral joint contact loads were measured in four subjects with instrumented implants as each subject walked at their preferred speed (normal gait) and performed prescribed gait modifications designed to treat medial knee osteoarthritis. Tibiofemoral contact loads contributed substantially to the net knee extension and knee adduction moments in normal gait with mean values of 16% and 54%, respectively. These findings suggest that knee-contact kinematics and loads should be included in lower-limb models of movement for more accurate determination of muscle forces. The results of this study may be used to guide the development of more realistic lower-limb models that account for the effects of tibiofemoral joint contact at the knee. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
Comparing Amazon Basin CO2 fluxes from an atmospheric inversion with TRENDY biosphere models
NASA Astrophysics Data System (ADS)
Diffenbaugh, N. S.; Alden, C. B.; Harper, A. B.; Ahlström, A.; Touma, D. E.; Miller, J. B.; Gatti, L. V.; Gloor, M.
2015-12-01
Net exchange of carbon dioxide (CO2) between the atmosphere and the terrestrial biosphere is sensitive to environmental conditions, including extreme heat and drought. Of particular importance for local and global carbon balance and climate are the expansive tracts of tropical rainforest located in the Amazon Basin. Because of the Basin's size and ecological heterogeneity, net biosphere CO2 exchange with the atmosphere remains largely un-constrained. In particular, the response of net CO2 exchange to changes in environmental conditions such as temperature and precipitation are not yet well known. However, proper representation of these relationships in biosphere models is a necessary constraint for accurately modeling future climate and climate-carbon cycle feedbacks. In an effort to compare biosphere response to climate across different biosphere models, the TRENDY model intercomparison project coordinated the simulation of CO2 fluxes between the biosphere and atmosphere, in response to historical climate forcing, by 9 different Dynamic Global Vegetation Models. We examine the TRENDY model results in the Amazon Basin, and compare this "bottom-up" method with fluxes derived from a "top-down" approach to estimating net CO2 fluxes, obtained through atmospheric inverse modeling using CO2 measurements sampled by aircraft above the basin. We compare the "bottom-up" and "top-down" fluxes in 5 sub-regions of the Amazon basin on a monthly basis for 2010-2012. Our results show important periods of agreement between some models in the TRENDY suite and atmospheric inverse model results, notably the simulation of increased biosphere CO2 loss during wet season heat in the Central Amazon. During the dry season, however, model ability to simulate observed response of net CO2 exchange to drought was varied, with few models able to reproduce the "top-down" inversion flux signals. Our results highlight the value of atmospheric trace gas observations for helping to narrow the possibilities of future carbon-climate interactions, especially in historically under-observed regions like the Amazon.
NASA Astrophysics Data System (ADS)
Maeda, Yuta; Kato, Aitaro; Yamanaka, Yoshiko
2017-02-01
Although phreatic eruptions are common volcanic phenomena that sometimes result in significant disasters, their dynamics are poorly understood. In this study, we address the dynamics of the phreatic eruption of Mount Ontake, Japan, in 2014 based on analyses of a tilt change observed immediately (450 s) before the eruption onset. We conducted two sets of analysis: a waveform inversion and a modified phase-space analysis. Our waveform inversion of the tilt signal points to a vertical tensile crack at a depth of 1100 m. Our modified phase-space analysis suggests that the tilt change was at first a linear function in time that then switched to exponential growth. We constructed simple analytical models to explain these temporal functions. The linear function was explained by the boiling of underground water controlled by a constant heat supply from a greater depth. The exponential function was explained by the decompression-induced boiling of water and the upward Darcy flow of the water vapor through a permeable region of small cracks that were newly created in response to ongoing boiling. We interpret that this region was intact prior to the start of the tilt change, and thus, it has acted as a permeability barrier for the upward migration of fluids; it was a breakage of this barrier that led to the eruption.
NASA Astrophysics Data System (ADS)
Zheng, Jiajia; Li, Yancheng; Li, Zhaochun; Wang, Jiong
2015-10-01
This paper presents multi-physics modeling of an MR absorber considering the magnetic hysteresis to capture the nonlinear relationship between the applied current and the generated force under impact loading. The magnetic field, temperature field, and fluid dynamics are represented by the Maxwell equations, conjugate heat transfer equations, and Navier-Stokes equations. These fields are coupled through the apparent viscosity and the magnetic force, both of which in turn depend on the magnetic flux density and the temperature. Based on a parametric study, an inverse Jiles-Atherton hysteresis model is used and implemented for the magnetic field simulation. The temperature rise of the MR fluid in the annular gap caused by core loss (i.e. eddy current loss and hysteresis loss) and fluid motion is computed to investigate the current-force behavior. A group of impulsive tests was performed for the manufactured MR absorber with step exciting currents. The numerical and experimental results showed good agreement, which validates the effectiveness of the proposed multi-physics FEA model.
A spatial operator algebra for manipulator modeling and control
NASA Technical Reports Server (NTRS)
Rodriguez, G.; Jain, A.; Kreutz-Delgado, K.
1991-01-01
A recently developed spatial operator algebra for manipulator modeling, control, and trajectory design is discussed. The elements of this algebra are linear operators whose domain and range spaces consist of forces, moments, velocities, and accelerations. The effect of these operators is equivalent to a spatial recursion along the span of a manipulator. Inversion of operators can be efficiently obtained via techniques of recursive filtering and smoothing. The operator algebra provides a high-level framework for describing the dynamic and kinematic behavior of a manipulator and for control and trajectory design algorithms. The interpretation of expressions within the algebraic framework leads to enhanced conceptual and physical understanding of manipulator dynamics and kinematics.
Coseismic temporal changes of slip direction: the effect of absolute stress on dynamic rupture
Guatteri, Mariagiovanna; Spudich, P.
1998-01-01
We investigate the dynamics of rupture at low-stress level. We show that one main difference between the dynamics of high- and low-stress events is the amount of coseismic temporal rake rotation occurring at given points on the fault. Curved striations on exposed fault surfaces and earthquake dislocation models derived from ground-motion inversion indicate that the slip direction may change with time at a point on the fault during dynamic rupture. We use a 3D boundary integral method to model temporal rake variations during dynamic rupture propagation assuming a slip-weakening friction law and isotropic friction. The points at which the slip rotates most are characterized by an initial shear stress direction substantially different from the average stress direction over the fault plane. We show that for a given value of stress drop, the level of initial shear stress (i.e., the fractional stress drop) determines the amount of rotation in slip direction. We infer that seismic events that show evidence of temporal rake rotations are characterized by a low initial shear-stress level with spatially variable direction on the fault (possibly due to changes in fault surface geometry) and an almost complete stress drop.Our models motivate a new interpretation of curved and cross-cutting striations and put new constraints on their analysis. The initial rake is in general collinear with the initial stress at the hypocentral zone, supporting the assumptions made in stress-tensor inversion from first-motion analysis. At other points on the fault, especially away from the hypocenter, the initial slip rake may not be collinear with the initial shear stress, contradicting a common assumption of structural geology. On the other hand, the later part of slip in our models is systematically more aligned with the average stress direction than the early slip. Our modeling suggests that the length of the straight part of curved striations is usually an upper bound of the slip-weakening distance if this parameter is uniform over the fault plane, and the direction of the late part of slip of curved striations should have more weight in the estimate of initial stress direction.
Onset of normal and inverse homoclinic bifurcation in a double plasma system near a plasma fireball
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mitra, Vramori; Sarma, Bornali; Sarma, Arun
Plasma fireballs are generated due to a localized discharge and appear as a luminous glow with a sharp boundary, which suggests the presence of a localized electric field such as electrical sheath or double layer structure. The present work reports the observation of normal and inverse homoclinic bifurcation phenomena in plasma oscillations that are excited in the presence of fireball in a double plasma device. The controlling parameters for these observations are the ratio of target to source chamber (n{sub T}/n{sub S}) densities and applied electrode voltage. Homoclinic bifurcation is noticed in the plasma potential fluctuations as the system evolvesmore » from narrow to long time period oscillations and vice versa with the change of control parameter. The dynamical transition in plasma fireball is demonstrated by spectral analysis, recurrence quantification analysis (RQA), and statistical measures, viz., skewness and kurtosis. The increasing trend of normalized variance reflects that enhancing n{sub T}/n{sub S} induces irregularity in plasma dynamics. The exponential growth of the time period is strongly indicative of homoclinic bifurcation in the system. The gradual decrease of skewness and increase of kurtosis with the increase of n{sub T}/n{sub S} also reflect growing complexity in the system. The visual change of recurrence plot and gradual enhancement of RQA variables DET, L{sub max}, and ENT reflects the bifurcation behavior in the dynamics. The combination of RQA and spectral analysis is a clear evidence that homoclinic bifurcation occurs due to the presence of plasma fireball with different density ratios. However, inverse bifurcation takes place due to the change of fireball voltage. Some of the features observed in the experiment are consistent with a model that describes the dynamics of ionization instabilities.« less
NASA Astrophysics Data System (ADS)
Roy, Nilanjan; Sharma, Auditya
2018-03-01
We numerically investigate the link between the delocalization-localization transition and entanglement in a disordered long-range hopping model of spinless fermions by studying various static and dynamical quantities. This includes the inverse participation ratio, level statistics, entanglement entropy, and number fluctuations in the subsystem along with quench and wave-packet dynamics. Finite systems show delocalized, quasilocalized, and localized phases. The delocalized phase shows strong area-law violation, whereas the (quasi)localized phase adheres to (for large subsystems) the strict area law. The idea of "entanglement contour" nicely explains the violation of area law and its relationship with "fluctuation contour" reveals a signature at the transition point. The relationship between entanglement entropy and number fluctuations in the subsystem also carries signatures for the transition in the model. Results from the Aubry-Andre-Harper model are compared in this context. The propagation of charge and entanglement are contrasted by studying quench and wave-packet dynamics at the single-particle and many-particle levels.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kardaś, T. M., E-mail: kardas@chem.uw.edu.pl; Ratajska-Gadomska, B.; Gadomski, W.
2014-05-28
We have studied the effect of transient vibrational inversion of population in trans-β-apo-8{sup ′}-carotenal on the time-resolved femtosecond stimulated Raman scattering (TR-FSRS) signal. The experimental data are interpreted by applying a quantum mechanical approach, using the formalism of projection operators for constructing the theoretical model of TR-FSRS. Within this theoretical frame we explain the presence of transient Raman losses on the Stokes side of the TR-FSRS spectrum as the effect of vibrational inversion of population. In view of the obtained experimental and theoretical results, we conclude that the excited S{sub 2} electronic level of trans-β-apo-8{sup ′}-carotenal relaxes towards the S{submore » 0} ground state through a set of four vibrational sublevels of S{sub 1} state.« less
NASA Astrophysics Data System (ADS)
Adeline, K.; Ustin, S.; Roth, K. L.; Huesca Martinez, M.; Schaaf, C.; Baldocchi, D. D.; Gastellu-Etchegorry, J. P.
2015-12-01
The assessment of canopy biochemical diversity is critical for monitoring ecological and physiological functioning and for mapping vegetation change dynamics in relation to environmental resources. For example in oak woodland savannas, these dynamics are mainly driven by water constraints. Inversion using radiative transfer theory is one method for estimating canopy biochemistry. However, this approach generally only considers relatively simple scenarios to model the canopy due to the difficulty in encompassing stand heterogeneity with spatial and temporal consistency. In this research, we compared 3 modeling strategies for estimating canopy biochemistry variables (i.e. chlorophyll, carotenoids, water, dry matter) by coupling of the PROSPECT (leaf level) and DART (canopy level) models : i) a simple forest representation made of ellipsoid trees, and two representations taking into account the tree species and structural composition, and the landscape spatial pattern, using (ii) geometric tree crown shapes and iii) detailed tree crown and wood structure retrieved from terrestrial lidar acquisitions. AVIRIS 18m remote sensing data are up-scaled to simulate HyspIRI 30m images. Both spatial resolutions are validated by measurements acquired during 2013-2014 field campaigns (cover/tree inventory, LAI, leaf sampling, optical measures). The results outline the trade-off between accurate and abstract canopy modeling for inversion purposes and may provide perspectives to assess the impact of the California drought with multi-temporal monitoring of canopy biochemistry traits.
Marinkovic, Ksenija; Courtney, Maureen G.; Witzel, Thomas; Dale, Anders M.; Halgren, Eric
2014-01-01
Although a crucial role of the fusiform gyrus (FG) in face processing has been demonstrated with a variety of methods, converging evidence suggests that face processing involves an interactive and overlapping processing cascade in distributed brain areas. Here we examine the spatio-temporal stages and their functional tuning to face inversion, presence and configuration of inner features, and face contour in healthy subjects during passive viewing. Anatomically-constrained magnetoencephalography (aMEG) combines high-density whole-head MEG recordings and distributed source modeling with high-resolution structural MRI. Each person's reconstructed cortical surface served to constrain noise-normalized minimum norm inverse source estimates. The earliest activity was estimated to the occipital cortex at ~100 ms after stimulus onset and was sensitive to an initial coarse level visual analysis. Activity in the right-lateralized ventral temporal area (inclusive of the FG) peaked at ~160 ms and was largest to inverted faces. Images containing facial features in the veridical and rearranged configuration irrespective of the facial outline elicited intermediate level activity. The M160 stage may provide structural representations necessary for downstream distributed areas to process identity and emotional expression. However, inverted faces additionally engaged the left ventral temporal area at ~180 ms and were uniquely subserved by bilateral processing. This observation is consistent with the dual route model and spared processing of inverted faces in prosopagnosia. The subsequent deflection, peaking at ~240 ms in the anterior temporal areas bilaterally, was largest to normal, upright faces. It may reflect initial engagement of the distributed network subserving individuation and familiarity. These results support dynamic models suggesting that processing of unfamiliar faces in the absence of a cognitive task is subserved by a distributed and interactive neural circuit. PMID:25426044
Anthropic versus cosmological solutions to the coincidence problem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barreira, A.; Avelino, P. P.; Departamento de Fisica da Faculdade de Ciencias da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto
2011-05-15
In this paper, we investigate possible solutions to the coincidence problem in flat phantom dark-energy models with a constant dark-energy equation of state and quintessence models with a linear scalar field potential. These models are representative of a broader class of cosmological scenarios in which the universe has a finite lifetime. We show that, in the absence of anthropic constraints, including a prior probability for the models inversely proportional to the total lifetime of the universe excludes models very close to the {Lambda} cold dark matter model. This relates a cosmological solution to the coincidence problem with a dynamical dark-energymore » component having an equation-of-state parameter not too close to -1 at the present time. We further show that anthropic constraints, if they are sufficiently stringent, may solve the coincidence problem without the need for dynamical dark energy.« less
Rane, Rahul V; Rako, Lea; Kapun, Martin; Lee, Siu F; Hoffmann, Ary A
2015-05-01
Chromosomal inversion polymorphisms are common in animals and plants, and recent models suggest that alternative arrangements spread by capturing different combinations of alleles acting additively or epistatically to favour local adaptation. It is also thought that inversions typically maintain favoured combinations for a long time by suppressing recombination between alternative chromosomal arrangements. Here, we consider patterns of linkage disequilibrium and genetic divergence in an old inversion polymorphism in Drosophila melanogaster (In(3R)Payne) known to be associated with climate change adaptation and a recent invasion event into Australia. We extracted, karyotyped and sequenced whole chromosomes from two Australian populations, so that changes in the arrangement of the alleles between geographically separated tropical and temperate areas could be compared. Chromosome-wide linkage disequilibrium (LD) analysis revealed strong LD within the region spanned by In(3R)Payne. This genomic region also showed strong differentiation between the tropical and the temperate populations, but no differentiation between different karyotypes from the same population, after controlling for chromosomal arrangement. Patterns of differentiation across the chromosome arm and in gene ontologies were enhanced by the presence of the inversion. These data support the notion that inversions are strongly selected by bringing together combinations of genes, but it is still not clear if such combinations act additively or epistatically. Our data suggest that climatic adaptation through inversions can be dynamic, reflecting changes in the relative abundance of different forms of an inversion and ongoing evolution of allelic content within an inversion. © 2015 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Nevison, C. D.; Saikawa, E.; Dlugokencky, E. J.; Andrews, A. E.; Sweeney, C.
2014-12-01
Atmospheric N2O concentrations have increased from 275 ppb in the preindustrial to about 325 ppb in recent years, a ~20% increase with important implications for both anthropogenic greenhouse forcing and stratospheric ozone recovery. This increase has been driven largely by synthetic fertilizer production and other perturbations to the global nitrogen cycle associated with human agriculture. Several recent regional atmospheric inversion studies have quantified North American agricultural N2O emissions using top-down constraints based on atmospheric N2O data from the National Oceanic and Atmospheric Administration (NOAA) Global Greenhouse Gas Reference Network, including surface, aircraft and tall tower platforms. These studies have concluded that global N2O inventories such as EDGAR may be underestimating the true U.S. anthropogenic N2O source by a factor of 3 or more. However, simple back-of-the-envelope calculations show that emissions of this magnitude are difficult to reconcile with the basic constraints of the global N2O budget. Here, we explore some possible reasons why regional atmospheric inversions might overestimate the U.S. agricultural N2O source. First, the seasonality of N2O agricultural sources is not well known, but can have an important influence on inversion results, particularly when the inversions are based on data that are concentrated in the spring/summer growing season. Second, boundary conditions can strongly influence regional inversions but the boundary conditions used may not adequately account for remote influences on surface data such as the seasonal stratospheric influx of N2O-depleted air. We will present a set of forward model simulations, using the Community Land Model (CLM) and two atmospheric chemistry tracer transport models, MOZART and the Whole Atmosphere Community Climate Model (WACCM), that examine the influence of terrestrial emissions and atmospheric chemistry and dynamics on atmospheric variability in N2O at U.S. and global monitoring sites.
Compensation of significant parametric uncertainties using sliding mode online learning
NASA Astrophysics Data System (ADS)
Schnetter, Philipp; Kruger, Thomas
An augmented nonlinear inverse dynamics (NID) flight control strategy using sliding mode online learning for a small unmanned aircraft system (UAS) is presented. Because parameter identification for this class of aircraft often is not valid throughout the complete flight envelope, aerodynamic parameters used for model based control strategies may show significant deviations. For the concept of feedback linearization this leads to inversion errors that in combination with the distinctive susceptibility of small UAS towards atmospheric turbulence pose a demanding control task for these systems. In this work an adaptive flight control strategy using feedforward neural networks for counteracting such nonlinear effects is augmented with the concept of sliding mode control (SMC). SMC-learning is derived from variable structure theory. It considers a neural network and its training as a control problem. It is shown that by the dynamic calculation of the learning rates, stability can be guaranteed and thus increase the robustness against external disturbances and system failures. With the resulting higher speed of convergence a wide range of simultaneously occurring disturbances can be compensated. The SMC-based flight controller is tested and compared to the standard gradient descent (GD) backpropagation algorithm under the influence of significant model uncertainties and system failures.
Density and energy relaxation in an open one-dimensional system
NASA Astrophysics Data System (ADS)
Jose, Prasanth P.; Bagchi, Biman
2004-05-01
A new master equation to mimic the dynamics of a collection of interacting random walkers in an open system is proposed and solved numerically. In this model, the random walkers interact through excluded volume interaction (single-file system); and the total number of walkers in the lattice can fluctuate because of exchange with a bath. In addition, the movement of the random walkers is biased by an external perturbation. Two models for the latter are considered: (1) an inverse potential (V∝1/r), where r is the distance between the center of the perturbation and the random walker and (2) an inverse of sixth power potential (V∝1/r6). The calculated density of the walkers and the total energy show interesting dynamics. When the size of the system is comparable to the range of the perturbing field, the energy relaxation is found to be highly nonexponential. In this range, the system can show stretched exponential (e-(t/τs)β) and even logarithmic time dependence of energy relaxation over a limited range of time. Introduction of density exchange in the lattice markedly weakens this nonexponentiality of the relaxation function, irrespective of the nature of perturbation.
Forward and inverse functional variations in rotationally inelastic scattering
NASA Astrophysics Data System (ADS)
Guzman, Robert; Rabitz, Herschel
1986-09-01
This paper considers the response of various rotational energy transfer processes to functional variations about an assumed model intermolecular potential. Attention is focused on the scattering of an atom and a linear rigid rotor. The collision dynamics are approximated by employing both the infinite order sudden (IOS) and exponential distorted wave (EDW) methods to describe Ar-N2 and He-H2, respectively. The following cross sections are considered: state-to-state differential and integral, final state summed differential and integral, and effective diffusion and viscosity cross sections. Attention is first given to the forward sensitivity densities δ0/δV(R,r) where 0 denotes any of the aforementioned cross sections, R is the intermolecular distance, and r is the internal coordinates. These forward sensitivity densities (functional derivatives) offer a quantitative measure of the importance of different regions of the potential surface to a chosen cross section. Via knowledge of the forward sensitivities and a particular variation δV(R,r) the concomitant response δ0 is generated. It was found that locally a variation in the potential can give rise to a large response in the cross sections as measured by these forward densities. In contrast, a unit percent change in the overall potential produced a 1%-10% change in the cross sections studied indicating that the large + and - responses to local variations tend to cancel. In addition, inverse sensitivity densities δV(R,r)/δ0 are obtained. These inverse densities are of interest since they are the exact solution to the infinitesimal inverse scattering problem. Although the inverse sensitivity densities do not in themselves form an inversion algorithm, they do offer a quantitative measure of the importance of performing particular measurements for the ultimate purpose of inversion. Using a set of state-to-state integral cross sections we found that the resultant responses from the infinitesimal inversion were typically small such that ‖δV(R,r)‖≪‖V(R,r)‖. From the viewpoint of an actual inversion, these results indicate that only through an extensive effort will significant knowledge of the potential be gained from the cross sections. All of these calculations serve to illustrate the methodology, and other observables as well as dynamical schemes could be explored as desired.
Lane, John W.; Day-Lewis, Frederick D.; Versteeg, Roelof J.; Casey, Clifton C.
2004-01-01
Crosswell radar methods can be used to dynamically image ground-water flow and mass transport associated with tracer tests, hydraulic tests, and natural physical processes, for improved characterization of preferential flow paths and complex aquifer heterogeneity. Unfortunately, because the raypath coverage of the interwell region is limited by the borehole geometry, the tomographic inverse problem is typically underdetermined, and tomograms may contain artifacts such as spurious blurring or streaking that confuse interpretation.We implement object-based inversion (using a constrained, non-linear, least-squares algorithm) to improve results from pixel-based inversion approaches that utilize regularization criteria, such as damping or smoothness. Our approach requires pre- and post-injection travel-time data. Parameterization of the image plane comprises a small number of objects rather than a large number of pixels, resulting in an overdetermined problem that reduces the need for prior information. The nature and geometry of the objects are based on hydrologic insight into aquifer characteristics, the nature of the experiment, and the planned use of the geophysical results.The object-based inversion is demonstrated using synthetic and crosswell radar field data acquired during vegetable-oil injection experiments at a site in Fridley, Minnesota. The region where oil has displaced ground water is discretized as a stack of rectangles of variable horizontal extents. The inversion provides the geometry of the affected region and an estimate of the radar slowness change for each rectangle. Applying petrophysical models to these results and porosity from neutron logs, we estimate the vegetable-oil emulsion saturation in various layers.Using synthetic- and field-data examples, object-based inversion is shown to be an effective strategy for inverting crosswell radar tomography data acquired to monitor the emplacement of vegetable-oil emulsions. A principal advantage of object-based inversion is that it yields images that hydrologists and engineers can easily interpret and use for model calibration.
Robust inverse kinematics using damped least squares with dynamic weighting
NASA Technical Reports Server (NTRS)
Schinstock, D. E.; Faddis, T. N.; Greenway, R. B.
1994-01-01
This paper presents a general method for calculating the inverse kinematics with singularity and joint limit robustness for both redundant and non-redundant serial-link manipulators. Damped least squares inverse of the Jacobian is used with dynamic weighting matrices in approximating the solution. This reduces specific joint differential vectors. The algorithm gives an exact solution away from the singularities and joint limits, and an approximate solution at or near the singularities and/or joint limits. The procedure is here implemented for a six d.o.f. teleoperator and a well behaved slave manipulator resulted under teleoperational control.
Investigation into the Effects of Weapon Setback on Various Materials and Geometries.
1978-07-01
taking the Laplace Transform of the dynamic equation, rearrangement and taking the inverse transform to find the time-dependent strain. The "dynamic...taking the inverse transform of the above equation: ■»-«fa-to*« 1 E’ ♦ ¥®*> B’ (s+-fj- )(S2+f )T If we neglect the residual strain on the system...partial fractions yields: *t) --f (fr JC-> K, K2 —L_ + + K3 »+-^ s+i(f) s-i(f) performing the inverse transform yields: 4©[K,^> ♦ K2
A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.
Terrier, Alexandre; Aeberhard, Martin; Michellod, Yvan; Mullhaupt, Philippe; Gillet, Denis; Farron, Alain; Pioletti, Dominique P
2010-11-01
The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.
Real-time characterization of partially observed epidemics using surrogate models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia
We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiologicalmore » parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as observations from the 1918 influenza pandemic collected at Camp Custer, Michigan.« less
Decker, Jeremy D.; Swain, Eric D.; Stith, Bradley M.; Langtimm, Catherine A.
2013-01-01
Everglades restoration activities may cause changes to temperature and salinity stratification at the Port of the Islands (POI) marina, which could affect its suitability as a cold weather refuge for manatees. To better understand how the Picayune Strand Restoration Project (PSRP) may alter this important resource in Collier County in southwestern Florida, the USGS has developed a three-dimensional hydrodynamic model for the marina and canal system at POI. Empirical data suggest that manatees aggregate at the site during winter because of thermal inversions that provide warmer water near the bottom that appears to only occur in the presence of salinity stratification. To study these phenomena, the environmental fluid dynamics code simulator was used to represent temperature and salinity transport within POI. Boundary inputs were generated using a larger two-dimensional model constructed with the flow and transport in a linked overland-aquifer density-dependent system simulator. Model results for a representative winter period match observed trends in salinity and temperature fluctuations and produce temperature inversions similar to observed values. Modified boundary conditions, representing proposed PSRP alterations, were also tested to examine the possible effect on the salinity stratification and temperature inversion within POI. Results show that during some periods, salinity stratification is reduced resulting in a subsequent reduction in temperature inversion compared with the existing conditions simulation. This may have an effect on POI’s suitability as a passive thermal refuge for manatees and other temperature-sensitive species. Additional testing was completed to determine the important physical relationships affecting POI’s suitability as a refuge.
NASA Astrophysics Data System (ADS)
Chaves, Carlos Alberto Moreno; Ussami, Naomi
2013-12-01
developed a three-dimensional scheme to invert geoid anomalies aiming to map density variations in the mantle. Using an ellipsoidal-Earth approximation, the model space is represented by tesseroids. To assess the quality of the density models, the resolution and covariance matrices were computed. From a synthetic geoid anomaly caused by a plume tail with Gaussian noise added, the inversion code was able to recover a plausible solution about the density contrast and geometry when it is compared to the synthetic model. To test the inversion algorithm in a natural case study, geoid anomalies from the Yellowstone Province (YP) were inverted. From the Earth Gravitational Model 2008 expanded up to degree 2160, lower crust- and mantle-related negative geoid anomalies with amplitude of approximately 70 m were obtained after removing long-wavelength components (>5400 km) and crustal effects. We estimated three density models for the YP. The first model, the EDM-1 (estimated density model), uses a starting model with density contrast equal to 0. The other two models, the EDM-2 and EDM-3, use an initial density derived from two S-velocity models for the western United States, the Dynamic North America Models of S Waves by Obrebsky et al. (2011) and the Northwestern United States Teleseismic Tomography of S Waves (NWUS11-S) by James et al. (2011). In these three models, a lower and an upper bound for the density solution was also imposed as a priori information. Regardless of the initial constraints, the inversion of the residual geoid indicates that the lower crust and the upper mantle of the YP have a predominantly negative density contrast ( -50 kg/m3) relative to the surrounding mantle. This solution reveals that the density contrast extends at least to 660 km depth. Regional correlation analysis between the EDM-1 and NWUS11-S indicates an anticorrelation (coefficient of -0.7) at 400 km depth. Our study suggests that the mantle density derived from the inversion of geoid could be integrated with seismic velocity models to image mantle anomalous features beyond the depth limit of investigation achieved combining gravity and seismic tomography. ©2013. American Geophysical Union. All Rights Reserved.
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.
Simulation of Constrained Musculoskeletal Systems in Task Space.
Stanev, Dimitar; Moustakas, Konstantinos
2018-02-01
This paper proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics. The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the direct marker control and an adaptation of the computed muscle control algorithms for solving the inverse kinematics and muscle redundancy problems, respectively. Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection. The incorporation of constraints in the derivation unveils an important extension of this framework toward addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy, and most importantly, offers an abstract point of view and control, which can be advantageous toward further integration with high level models of the precommand level. Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.
Free energy profiles from single-molecule pulling experiments.
Hummer, Gerhard; Szabo, Attila
2010-12-14
Nonequilibrium pulling experiments provide detailed information about the thermodynamic and kinetic properties of molecules. We show that unperturbed free energy profiles as a function of molecular extension can be obtained rigorously from such experiments without using work-weighted position histograms. An inverse Weierstrass transform is used to relate the system free energy obtained from the Jarzynski equality directly to the underlying molecular free energy surface. An accurate approximation for the free energy surface is obtained by using the method of steepest descent to evaluate the inverse transform. The formalism is applied to simulated data obtained from a kinetic model of RNA folding, in which the dynamics consists of jumping between linker-dominated folded and unfolded free energy surfaces.
An optimal resolved rate law for kindematically redundant manipulators
NASA Technical Reports Server (NTRS)
Bourgeois, B. J.
1987-01-01
The resolved rate law for a manipulator provides the instantaneous joint rates required to satisfy a given instantaneous hand motion. When the joint space has more degrees of freedom than the task space, the manipulator is kinematically redundant and the kinematic rate equations are underdetermined. These equations can be locally optimized, but the resulting pseudo-inverse solution was found to cause large joint rates in some case. A weighting matrix in the locally optimized (pseudo-inverse) solution is dynamically adjusted to control the joint motion as desired. Joint reach limit avoidance is demonstrated in a kinematically redundant planar arm model. The treatment is applicable to redundant manipulators with any number of revolute joints and to nonplanar manipulators.
NASA Technical Reports Server (NTRS)
Zalesak, J.
1975-01-01
A dynamic substructuring analysis, utilizing the component modes technique, of the 1/8 scale space shuttle orbiter finite element model is presented. The analysis was accomplished in 3 phases, using NASTRAN RIGID FORMAT 3, with appropriate Alters, on the IBM 360-370. The orbiter was divided into 5 substructures, each of which was reduced to interface degrees of freedom and generalized normal modes. The reduced substructures were coupled to yield the first 23 symmetric free-free orbiter modes, and the eigenvectors in the original grid point degree of freedom lineup were recovered. A comparison was made with an analysis which was performed with the same model using the direct coordinate elimination approach. Eigenvalues were extracted using the inverse power method.
NASA Astrophysics Data System (ADS)
Berges, J.; Boguslavski, K.; Chatrchyan, A.; Jaeckel, J.
2017-10-01
We study the impact of attractive self-interactions on the nonequilibrium dynamics of relativistic quantum fields with large occupancies at low momenta. Our primary focus is on Bose-Einstein condensation and nonthermal fixed points in such systems. For a model system, we consider O (N ) -symmetric scalar field theories. We use classical-statistical real-time simulations as well as a systematic 1 /N expansion of the quantum (two-particle-irreducible) effective action to next-to-leading order. When the mean self-interactions are repulsive, condensation occurs as a consequence of a universal inverse particle cascade to the zero-momentum mode with self-similar scaling behavior. For attractive mean self-interactions, the inverse cascade is absent, and the particle annihilation rate is enhanced compared to the repulsive case, which counteracts the formation of coherent field configurations. For N ≥2 , the presence of a nonvanishing conserved charge can suppress number-changing processes and lead to the formation of stable localized charge clumps, i.e., Q balls.
Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering
Havlicek, Martin; Friston, Karl J.; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.
2011-01-01
This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. PMID:21396454
McGuire, Jennifer A; Sherman, Paul M; Dean, Erica; Bernot, Jeremy M; Rowland, Laura M; McGuire, Stephen A; Kochunov, Peter V
2017-05-01
Repetitive hypobaric exposure in humans induces subcortical white matter change, observable on magnetic resonance imaging (MRI) and associated with cognitive impairment. Similar findings occur in traumatic brain injury (TBI). We are developing a swine MRI-driven model to understand the pathophysiology and to develop treatment interventions. Five miniature pigs (Sus scrofa domestica) were repetitively exposed to nonhypoxic hypobaria (30,000 feet/FIO 2 100%/transcutaneous PO 2 >90%) while under general anesthesia. Three pigs served as controls. Pre-exposure and postexposure MRIs were obtained that included structural sequences, dynamic contrast perfusion, and diffusion tensor quantification. Statistical comparison of individual subject and group change was performed utilizing a two-tailed t test. No structural imaging change was noted on T2-weighted or three-dimensional fluid-attenuated inversion recovery imaging between MRI 1 and MRI 2. No absolute difference in dynamic contrast perfusion was observed. A trend (p = 0.084) toward increase in interstitial extra-axonal fluid was noted. When individual subjects were examined, this trend toward increased extra-axonal fluid paralleled a decrease in contrast perfusion rate. This study demonstrates high reproducibility of quantitative noninvasive MRI, suggesting MRI is an appropriate assessment tool for TBI and hypobaric-induced injury research in swine. The lack of fluid-attenuated inversion recovery change may be multifactorial and requires further investigation. A trend toward increased extra-axonal water content that negatively correlates with dynamic contrast perfusion implies generalized axonal injury was induced. This study suggests this is a potential model for hypobaric-induced injury as well as potentially other axonal injuries such as TBI in which similar subcortical white matter change occurs. Further development of this model is necessary. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.
Towards a universal master curve in magnetorheology
NASA Astrophysics Data System (ADS)
Ruiz-López, José Antonio; Hidalgo-Alvarez, Roque; de Vicente, Juan
2017-05-01
We demonstrate that inverse ferrofluids behave as model magnetorheological fluids. A universal master curve is proposed, using a reduced Mason number, under the frame of a structural viscosity model where the magnetic field strength dependence is solely contained in the Mason number and the particle concentration is solely contained in the critical Mason number (i.e. the yield stress). A linear dependence of the critical Mason number with the particle concentration is observed that is in good agreement with a mean (average) magnetization approximation, particle level dynamic simulations and micromechanical models available in the literature.
Quantitative photoplethysmography: Lambert-Beer law or inverse function incorporating light scatter.
Cejnar, M; Kobler, H; Hunyor, S N
1993-03-01
Finger blood volume is commonly determined from measurement of infra-red (IR) light transmittance using the Lambert-Beer law of light absorption derived for use in non-scattering media, even when such transmission involves light scatter around the phalangeal bone. Simultaneous IR transmittance and finger volume were measured over the full dynamic range of vascular volumes in seven subjects and outcomes compared with data fitted according to the Lambert-Beer exponential function and an inverse function derived for light attenuation by scattering materials. Curves were fitted by the least-squares method and goodness of fit was compared using standard errors of estimate (SEE). The inverse function gave a better data fit in six of the subjects: mean SEE 1.9 (SD 0.7, range 0.7-2.8) and 4.6 (2.2, 2.0-8.0) respectively (p < 0.02, paired t-test). Thus, when relating IR transmittance to blood volume, as occurs in the finger during measurements of arterial compliance, an inverse function derived from a model of light attenuation by scattering media gives more accurate results than the traditional exponential fit.
NASA Technical Reports Server (NTRS)
Meyer, G.; Cicolani, L.
1981-01-01
A practical method for the design of automatic flight control systems for aircraft with complex characteristics and operational requirements, such as the powered lift STOL and V/STOL configurations, is presented. The method is effective for a large class of dynamic systems requiring multi-axis control which have highly coupled nonlinearities, redundant controls, and complex multidimensional operational envelopes. It exploits the concept of inverse dynamic systems, and an algorithm for the construction of inverse is given. A hierarchic structure for the total control logic with inverses is presented. The method is illustrated with an application to the Augmentor Wing Jet STOL Research Aircraft equipped with a digital flight control system. Results of flight evaluation of the control concept on this aircraft are presented.
Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait.
Rajagopal, Apoorva; Dembia, Christopher L; DeMers, Matthew S; Delp, Denny D; Hicks, Jennifer L; Delp, Scott L
2016-10-01
Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations.
NASA Astrophysics Data System (ADS)
Prasad, K.; Lopez-Coto, I.; Ghosh, S.; Mueller, K.; Whetstone, J. R.
2015-12-01
The North-East Corridor project aims to use a top-down inversion methodology to quantify sources of Greenhouse Gas (GHG) emissions over urban domains such as Washington DC / Baltimore with high spatial and temporal resolution. Atmospheric transport of tracer gases from an emission source to a tower mounted receptor are usually conducted using the Weather Research and Forecasting (WRF) model. For such simulations, WRF employs a parameterized turbulence model and does not resolve the fine scale dynamics generated by the flow around buildings and communities comprising a large city. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model that utilizes large eddy simulation methods to model flow around buildings at length scales much smaller than is practical with WRF. FDS has the potential to evaluate the impact of complex urban topography on near-field dispersion and mixing difficult to simulate with a mesoscale atmospheric model. Such capabilities may be important in determining urban GHG emissions using atmospheric measurements. A methodology has been developed to run FDS as a sub-grid scale model within a WRF simulation. The coupling is based on nudging the FDS flow field towards that computed by WRF, and is currently limited to one way coupling performed in an off-line mode. Using the coupled WRF / FDS model, NIST will investigate the effects of the urban canopy at horizontal resolutions of 10-20 m in a domain of 12 x 12 km. The coupled WRF-FDS simulations will be used to calculate the dispersion of tracer gases in the North-East Corridor and to evaluate the upwind areas that contribute to tower observations, referred to in the inversion community as influence functions. Results of this study will provide guidance regarding the importance of explicit simulations of urban atmospheric turbulence in obtaining accurate estimates of greenhouse gas emissions and transport.
Bayesian model reduction and empirical Bayes for group (DCM) studies
Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter
2016-01-01
This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570
Constraining Mass Anomalies Using Trans-dimensional Gravity Inversions
NASA Astrophysics Data System (ADS)
Izquierdo, K.; Montesi, L.; Lekic, V.
2016-12-01
The density structure of planetary interiors constitutes a key constraint on their composition, temperature, and dynamics. This has motivated the development of non-invasive methods to infer 3D distribution of density anomalies within a planet's interior using gravity observations made from the surface or orbit. On Earth, this information can be supplemented by seismic and electromagnetic observations, but such data are generally not available on other planets and inferences must be made from gravity observations alone. Unfortunately, inferences of density anomalies from gravity are non-unique and even the dimensionality of the problem - i.e., the number of density anomalies detectable in the planetary interior - is unknown. In this project, we use the Reversible Jump Markov chain Monte Carlo (RJMCMC) algorithm to approach gravity inversions in a trans-dimensional way, that is, considering the magnitude of the mass, the latitude, longitude, depth and number of anomalies itself as unknowns to be constrained by the observed gravity field at the surface of a planet. Our approach builds upon previous work using trans-dimensional gravity inversions in which the density contrast between the anomaly and the surrounding material is known. We validate the algorithm by analyzing a synthetic gravity field produced by a known density structure and comparing the retrieved and input density structures. We find excellent agreement between the input and retrieved structure when working in 1D and 2D domains. However, in 3D domains, comprehensive exploration of the much larger space of possible models makes search efficiency a key ingredient in successful gravity inversion. We find that upon a sufficiently long RJMCMC run, it is possible to use statistical information to recover a predicted model that matches the real model. We argue that even more complex problems, such as those involving real gravity acceleration data of a planet as the constraint, our trans-dimensional gravity inversion algorithm provides a good option to overcome the problem of non-uniqueness while achieving parsimony in gravity inversions.
Wake Vortex Inverse Model User's Guide
NASA Technical Reports Server (NTRS)
Lai, David; Delisi, Donald
2008-01-01
NorthWest Research Associates (NWRA) has developed an inverse model for inverting landing aircraft vortex data. The data used for the inversion are the time evolution of the lateral transport position and vertical position of both the port and starboard vortices. The inverse model performs iterative forward model runs using various estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Forward model predictions of lateral transport and altitude are then compared with the observed data. Differences between the data and model predictions guide the choice of vortex parameter values, crosswind profile and circulation evolution in the next iteration. Iterations are performed until a user-defined criterion is satisfied. Currently, the inverse model is set to stop when the improvement in the rms deviation between the data and model predictions is less than 1 percent for two consecutive iterations. The forward model used in this inverse model is a modified version of the Shear-APA model. A detailed description of this forward model, the inverse model, and its validation are presented in a different report (Lai, Mellman, Robins, and Delisi, 2007). This document is a User's Guide for the Wake Vortex Inverse Model. Section 2 presents an overview of the inverse model program. Execution of the inverse model is described in Section 3. When executing the inverse model, a user is requested to provide the name of an input file which contains the inverse model parameters, the various datasets, and directories needed for the inversion. A detailed description of the list of parameters in the inversion input file is presented in Section 4. A user has an option to save the inversion results of each lidar track in a mat-file (a condensed data file in Matlab format). These saved mat-files can be used for post-inversion analysis. A description of the contents of the saved files is given in Section 5. An example of an inversion input file, with preferred parameters values, is given in Appendix A. An example of the plot generated at a normal completion of the inversion is shown in Appendix B.
Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente
2016-05-01
Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.
Zavala, Miguel A; Angulo, Oscar; Bravo de la Parra, Rafael; López-Marcos, Juan C
2007-02-07
Light competition and interspecific differences in shade tolerance are considered key determinants of forest stand structure and dynamics. Specifically two main stand diameter distribution types as a function of shade tolerance have been proposed based on empirical observations. All-aged stands of shade tolerant species tend to have steeply descending, monotonic diameter distributions (inverse J-shaped curves). Shade intolerant species in contrast typically exhibit normal (unimodal) tree diameter distributions due to high mortality rates of smaller suppressed trees. In this study we explore the generality of this hypothesis which implies a causal relationship between light competition or shade tolerance and stand structure. For this purpose we formulate a partial differential equation system of stand dynamics as a function of individual tree growth, recruitment and mortality which allows us to explore possible individual-based mechanisms--e.g. light competition-underlying observed patterns of stand structure--e.g. unimodal or inverse J-shaped equilibrium diameter curves. We find that contrary to expectations interspecific differences in growth patterns can result alone in any of the two diameter distributions types observed in the field. In particular, slow growing species can present unimodal equilibrium curves even in the absence of light competition. Moreover, light competition and shade intolerance evaluated both at the tree growth and mortality stages did not have a significant impact on stand structure that tended to converge systematically towards an inverse J-shaped curves for most tree growth scenarios. Realistic transient stand dynamics for even aged stands of shade intolerant species (unimodal curves) were only obtained when recruitment was completely suppressed, providing further evidence on the critical role played by juvenile stages of tree development (e.g. the sampling stage) on final forest structure and composition. The results also point out the relevance of partial differential equations systems as a tool for exploring the individual-level mechanisms underpinning forest structure, particularly in relation to more complex forest simulation models that are more difficult to analyze and to interpret from a biological point of view.
Dynamics and Novel Mechanisms of SN2 Reactions on ab Initio Analytical Potential Energy Surfaces.
Szabó, István; Czakó, Gábor
2017-11-30
We describe a novel theoretical approach to the bimolecular nucleophilic substitution (S N 2) reactions that is based on analytical potential energy surfaces (PESs) obtained by fitting a few tens of thousands high-level ab initio energy points. These PESs allow computing millions of quasi-classical trajectories thereby providing unprecedented statistical accuracy for S N 2 reactions, as well as performing high-dimensional quantum dynamics computations. We developed full-dimensional ab initio PESs for the F - + CH 3 Y [Y = F, Cl, I] systems, which describe the direct and indirect, complex-forming Walden-inversion, the frontside attack, and the new double-inversion pathways as well as the proton-transfer channels. Reaction dynamics simulations on the new PESs revealed (a) a novel double-inversion S N 2 mechanism, (b) frontside complex formation, (c) the dynamics of proton transfer, (d) vibrational and rotational mode specificity, (e) mode-specific product vibrational distributions, (f) agreement between classical and quantum dynamics, (g) good agreement with measured scattering angle and product internal energy distributions, and (h) significant leaving group effect in accord with experiments.
Revealing physical interaction networks from statistics of collective dynamics
Nitzan, Mor; Casadiego, Jose; Timme, Marc
2017-01-01
Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630
The Self-Organization of a Spoken Word
Holden, John G.; Rajaraman, Srinivasan
2012-01-01
Pronunciation time probability density and hazard functions from large speeded word naming data sets were assessed for empirical patterns consistent with multiplicative and reciprocal feedback dynamics – interaction dominant dynamics. Lognormal and inverse power law distributions are associated with multiplicative and interdependent dynamics in many natural systems. Mixtures of lognormal and inverse power law distributions offered better descriptions of the participant’s distributions than the ex-Gaussian or ex-Wald – alternatives corresponding to additive, superposed, component processes. The evidence for interaction dominant dynamics suggests fundamental links between the observed coordinative synergies that support speech production and the shapes of pronunciation time distributions. PMID:22783213
Inverse Tone Mapping Based upon Retina Response
Huo, Yongqing; Yang, Fan; Brost, Vincent
2014-01-01
The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor. This paper proposed a novel physiological approach, which could avoid artifacts occurred in most existing algorithms. Inspired by the property of the human visual system (HVS), this dynamic range expansion scheme performs with a low computational complexity and a limited number of parameters and obtains high-quality HDR results. Comparisons with three recent algorithms in the literature also show that the proposed method reveals more important image details and produces less contrast loss and distortion. PMID:24744678
A fractal approach to dynamic inference and distribution analysis
van Rooij, Marieke M. J. W.; Nash, Bertha A.; Rajaraman, Srinivasan; Holden, John G.
2013-01-01
Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods. PMID:23372552
Full body musculoskeletal model for muscle-driven simulation of human gait
Rajagopal, Apoorva; Dembia, Christopher L.; DeMers, Matthew S.; Delp, Denny D.; Hicks, Jennifer L.; Delp, Scott L.
2017-01-01
Objective Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source, three-dimensional musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Methods Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model’s musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Results Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. Conclusion These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower-extremity. Significance The model is implemented in the open source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations. PMID:27392337
NASA Astrophysics Data System (ADS)
Ghasemian, E.; Tavassoly, M. K.
2017-09-01
In this paper we consider a system consisting of a number of two-level atoms in a Bose-Einstein condensate (BEC) and a single-mode quantized field, which interact with each other in the presence of two different damping sources, i.e. cavity and atomic reservoirs. The reservoirs which we consider here are thermal and squeezed vacuum ones corresponding to field and atom modes. Strictly speaking, by considering both types of reservoirs for each of the atom and field modes, we investigate the quantum dynamics of the interacting bosons in the system. Then, via solving the quantum Langevin equations for such a dissipative BEC system, we obtain analytical expressions for the time dependence of atomic population inversion, mean atom as well as photon number and quadrature squeezing in the field and atom modes. Our investigations demonstrate that for modeling the real physical systems, considering the dissipation effects is essential. Also, numerical calculations which are presented show that the atomic population inversion, the mean number of atoms in the BEC and the photons in the cavity possess damped oscillatory behavior due to the presence of reservoirs. In addition, non-classical squeezing effects in the field quadrature can be observed especially when squeezed vacuum reservoirs are taken into account. As an outstanding property of this model, we may refer to the fact that one can extract the atom-field coupling constant from the frequency of oscillations in the mentioned quantities such as atomic population inversion.
Laser Induced Aluminum Surface Breakdown Model
NASA Technical Reports Server (NTRS)
Chen, Yen-Sen; Liu, Jiwen; Zhang, Sijun; Wang, Ten-See (Technical Monitor)
2002-01-01
Laser powered propulsion systems involve complex fluid dynamics, thermodynamics and radiative transfer processes. Based on an unstructured grid, pressure-based computational aerothermodynamics; platform, several sub-models describing such underlying physics as laser ray tracing and focusing, thermal non-equilibrium, plasma radiation and air spark ignition have been developed. This proposed work shall extend the numerical platform and existing sub-models to include the aluminum wall surface Inverse Bremsstrahlung (IB) effect from which surface ablation and free-electron generation can be initiated without relying on the air spark ignition sub-model. The following tasks will be performed to accomplish the research objectives.
Takahashi, Daisuke A
2016-06-01
An integrable model possessing inhomogeneous ground states is proposed as an effective model of nonuniform quantum condensates such as supersolids and Fulde-Ferrell-Larkin-Ovchinnikov superfluids. The model is a higher-order analog of the nonlinear Schrödinger equation. We derive an n-soliton solution via the inverse scattering theory with elliptic-functional background and reveal various kinds of soliton dynamics such as dark soliton billiards, dislocations, gray solitons, and envelope solitons. We also provide the exact bosonic and fermionic quasiparticle eigenstates and show their tunneling phenomena. The solutions are expressed by a determinant of theta functions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Na; Zhang, Peng; Kang, Wei
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters aremore » systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.« less
Dynamic causal modelling: a critical review of the biophysical and statistical foundations.
Daunizeau, J; David, O; Stephan, K E
2011-09-15
The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.
Inverse modeling of geochemical and mechanical compaction in sedimentary basins
NASA Astrophysics Data System (ADS)
Colombo, Ivo; Porta, Giovanni Michele; Guadagnini, Alberto
2015-04-01
We study key phenomena driving the feedback between sediment compaction processes and fluid flow in stratified sedimentary basins formed through lithification of sand and clay sediments after deposition. Processes we consider are mechanic compaction of the host rock and the geochemical compaction due to quartz cementation in sandstones. Key objectives of our study include (i) the quantification of the influence of the uncertainty of the model input parameters on the model output and (ii) the application of an inverse modeling technique to field scale data. Proper accounting of the feedback between sediment compaction processes and fluid flow in the subsurface is key to quantify a wide set of environmentally and industrially relevant phenomena. These include, e.g., compaction-driven brine and/or saltwater flow at deep locations and its influence on (a) tracer concentrations observed in shallow sediments, (b) build up of fluid overpressure, (c) hydrocarbon generation and migration, (d) subsidence due to groundwater and/or hydrocarbons withdrawal, and (e) formation of ore deposits. Main processes driving the diagenesis of sediments after deposition are mechanical compaction due to overburden and precipitation/dissolution associated with reactive transport. The natural evolution of sedimentary basins is characterized by geological time scales, thus preventing direct and exhaustive measurement of the system dynamical changes. The outputs of compaction models are plagued by uncertainty because of the incomplete knowledge of the models and parameters governing diagenesis. Development of robust methodologies for inverse modeling and parameter estimation under uncertainty is therefore crucial to the quantification of natural compaction phenomena. We employ a numerical methodology based on three building blocks: (i) space-time discretization of the compaction process; (ii) representation of target output variables through a Polynomial Chaos Expansion (PCE); and (iii) model inversion (parameter estimation) within a maximum likelihood framework. In this context, the PCE-based surrogate model enables one to (i) minimize the computational cost associated with the (forward and inverse) modeling procedures leading to uncertainty quantification and parameter estimation, and (ii) compute the full set of Sobol indices quantifying the contribution of each uncertain parameter to the variability of target state variables. Results are illustrated through the simulation of one-dimensional test cases. The analyses focuses on the calibration of model parameters through literature field cases. The quality of parameter estimates is then analyzed as a function of number, type and location of data.
Travis DeLuca; Mary Ann Fajvan; Gary Miller
2009-01-01
Ten-years after diameter-limit harvesting in an Appalachian hardwood stand, the height, dbh, and basal area of sapling regeneration was inversely related to the degree of "overtopping" of residual trees. Black cherry and red maple were the most abundant saplings with 416.5 ± 25.7 and 152.9 ± 16.8 stems per acre, respectively. Models of black...
NASA Astrophysics Data System (ADS)
Li, Lei; Yu, Long; Yang, Kecheng; Li, Wei; Li, Kai; Xia, Min
2018-04-01
The multiangle dynamic light scattering (MDLS) technique can better estimate particle size distributions (PSDs) than single-angle dynamic light scattering. However, determining the inversion range, angular weighting coefficients, and scattering angle combination is difficult but fundamental to the reconstruction for both unimodal and multimodal distributions. In this paper, we propose a self-adapting regularization method called the wavelet iterative recursion nonnegative Tikhonov-Phillips-Twomey (WIRNNT-PT) algorithm. This algorithm combines a wavelet multiscale strategy with an appropriate inversion method and could self-adaptively optimize several noteworthy issues containing the choices of the weighting coefficients, the inversion range and the optimal inversion method from two regularization algorithms for estimating the PSD from MDLS measurements. In addition, the angular dependence of the MDLS for estimating the PSDs of polymeric latexes is thoroughly analyzed. The dependence of the results on the number and range of measurement angles was analyzed in depth to identify the optimal scattering angle combination. Numerical simulations and experimental results for unimodal and multimodal distributions are presented to demonstrate both the validity of the WIRNNT-PT algorithm and the angular dependence of MDLS and show that the proposed algorithm with a six-angle analysis in the 30-130° range can be satisfactorily applied to retrieve PSDs from MDLS measurements.
Molecular dynamics simulations of oxide memory resistors (memristors).
Savel'ev, S E; Alexandrov, A S; Bratkovsky, A M; Williams, R Stanley
2011-06-24
Reversible bipolar nanoswitches that can be set and read electronically in a solid-state two-terminal device are very promising for applications. We have performed molecular dynamics simulations that mimic systems with oxygen vacancies interacting via realistic potentials and driven by an external bias voltage. The competing short- and long-range interactions among charged mobile vacancies lead to density fluctuations and short-range ordering, while illustrating some aspects of observed experimental behavior, such as memristor polarity inversion. The simulations show that the 'localized conductive filaments' and 'uniform push/pull' models for memristive switching are actually two extremes of the one stochastic mechanism.
Inverse Symmetry in Complete Genomes and Whole-Genome Inverse Duplication
Kong, Sing-Guan; Fan, Wen-Lang; Chen, Hong-Da; Hsu, Zi-Ting; Zhou, Nengji; Zheng, Bo; Lee, Hoong-Chien
2009-01-01
The cause of symmetry is usually subtle, and its study often leads to a deeper understanding of the bearer of the symmetry. To gain insight into the dynamics driving the growth and evolution of genomes, we conducted a comprehensive study of textual symmetries in 786 complete chromosomes. We focused on symmetry based on our belief that, in spite of their extreme diversity, genomes must share common dynamical principles and mechanisms that drive their growth and evolution, and that the most robust footprints of such dynamics are symmetry related. We found that while complement and reverse symmetries are essentially absent in genomic sequences, inverse–complement plus reverse–symmetry is prevalent in complex patterns in most chromosomes, a vast majority of which have near maximum global inverse symmetry. We also discovered relations that can quantitatively account for the long observed but unexplained phenomenon of -mer skews in genomes. Our results suggest segmental and whole-genome inverse duplications are important mechanisms in genome growth and evolution, probably because they are efficient means by which the genome can exploit its double-stranded structure to enrich its code-inventory. PMID:19898631
NASA Astrophysics Data System (ADS)
Liang, Feng; Yang, Xiao-Dong; Zhang, Wei; Qian, Ying-Jing
2018-03-01
In this paper, a dynamical model of simply-supported spinning pipes conveying fluid with axial deployment is proposed and the transverse free vibration and stability for such a doubly gyroscopic system involving time-dependent parameters are investigated. The partial differential equations of motion are derived by the extended Hamilton principle and then truncated by the Galerkin technique. The time-variant frequencies, mode shapes and responses to initial conditions are comprehensively investigated to reveal the dynamical essence of the system. It is indicated that the qualitative stability evolution of the system mainly depends on the effect of fluid-structure interaction (FSI), while the spinning motion will enhance the pipe rigidity and eliminate the buckling instability. The dynamical evolution of a retracting pipe is almost inverse to that of the deploying one. The pipe possesses different mode configurations of spatial curves as the pipe length increases and some modal and response characteristics of the present system are found rather distinct from those of deploying cantilevered structures.
Solution landscapes in nematic microfluidics
NASA Astrophysics Data System (ADS)
Crespo, M.; Majumdar, A.; Ramos, A. M.; Griffiths, I. M.
2017-08-01
We study the static equilibria of a simplified Leslie-Ericksen model for a unidirectional uniaxial nematic flow in a prototype microfluidic channel, as a function of the pressure gradient G and inverse anchoring strength, B. We numerically find multiple static equilibria for admissible pairs (G , B) and classify them according to their winding numbers and stability. The case G = 0 is analytically tractable and we numerically study how the solution landscape is transformed as G increases. We study the one-dimensional dynamical model, the sensitivity of the dynamic solutions to initial conditions and the rate of change of G and B. We provide a physically interesting example of how the time delay between the applications of G and B can determine the selection of the final steady state.
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.
NASA Astrophysics Data System (ADS)
Jones, Alan G.; Afonso, Juan Carlos; Fullea, Javier
2015-04-01
The deep mantle African Superswell is thought to cause up to 500 m of the uplift of the Southern African Plateau. We investigate this phenomenon through stochastic thermo-chemical inversion modelling of the geoid, surface heat flow, Rayleigh and Love dispersion curves and MT data, in a manner that is fully petrologically-consistent. We invert for a three layer crustal velocity, density and thermal structure, but assume the resistivity layering (based on prior inversion of the MT data alone). Inversions are performed using an improved Delayed Rejection and Adaptive Metropolis (DRAM) type Markov chain Monte Carlo (MCMC) algorithm. We demonstrate that a single layer lithosphere can fit most of the data, but not the MT responses. We further demonstrate that modelling the seismic data alone, without the constraint of requiring reasonable oxide chemistry or of fitting the geoid, permits wildly acceptable elevations and with very poorly defined lithosphere-asthenosphere boundary (LAB). We parameterise the lithosphere into three layers, and bound the permitted oxide chemistry of each layer consistent with known chemical layering. We find acceptable models, from 5 million tested in each case, that fit all responses and yield a posteriori elevation distributions centred on 900-950 m, suggesting dynamic support from the lower mantle of some 400 m.
Caracterisation mecanique dynamique de materiaux poro-visco-elastiques
NASA Astrophysics Data System (ADS)
Renault, Amelie
Poro-viscoelastic materials are well modelled with Biot-Allard equations. This model needs a number of geometrical parameters in order to describe the macroscopic geometry of the material and elastic parameters in order to describe the elastic properties of the material skeleton. Several characterisation methods of viscoelastic parameters of porous materials are studied in this thesis. Firstly, quasistatic and resonant characterization methods are described and analyzed. Secondly, a new inverse dynamic characterization of the same modulus is developed. The latter involves a two layers metal-porous beam, which is excited at the center. The input mobility is measured. The set-up is simplified compared to previous methods. The parameters are obtained via an inversion procedure based on the minimisation of the cost function comparing the measured and calculated frequency response functions (FRF). The calculation is done with a general laminate model. A parametric study identifies the optimal beam dimensions for maximum sensitivity of the inversion model. The advantage of using a code which is not taking into account fluid-structure interactions is the low computation time. For most materials, the effect of this interaction on the elastic properties is negligible. Several materials are tested to demonstrate the performance of the method compared to the classical quasi-static approaches, and set its limitations and range of validity. Finally, conclusions about their utilisation are given. Keywords. Elastic parameters, porous materials, anisotropy, vibration.
Gómez, Pablo; Schützenberger, Anne; Kniesburges, Stefan; Bohr, Christopher; Döllinger, Michael
2018-06-01
This study presents a framework for a direct comparison of experimental vocal fold dynamics data to a numerical two-mass-model (2MM) by solving the corresponding inverse problem of which parameters lead to similar model behavior. The introduced 2MM features improvements such as a variable stiffness and a modified collision force. A set of physiologically sensible degrees of freedom is presented, and three optimization algorithms are compared on synthetic vocal fold trajectories. Finally, a total of 288 high-speed video recordings of six excised porcine larynges were optimized to validate the proposed framework. Particular focus lay on the subglottal pressure, as the experimental subglottal pressure is directly comparable to the model subglottal pressure. Fundamental frequency, amplitude and objective function values were also investigated. The employed 2MM is able to replicate the behavior of the porcine vocal folds very well. The model trajectories' fundamental frequency matches the one of the experimental trajectories in [Formula: see text] of the recordings. The relative error of the model trajectory amplitudes is on average [Formula: see text]. The experiments feature a mean subglottal pressure of 10.16 (SD [Formula: see text]) [Formula: see text]; in the model, it was on average 7.61 (SD [Formula: see text]) [Formula: see text]. A tendency of the model to underestimate the subglottal pressure is found, but the model is capable of inferring trends in the subglottal pressure. The average absolute error between the subglottal pressure in the model and the experiment is 2.90 (SD [Formula: see text]) [Formula: see text] or [Formula: see text]. A detailed analysis of the factors affecting the accuracy in matching the subglottal pressure is presented.
NASA Astrophysics Data System (ADS)
Cowie, Leanne; Kusznir, Nick
2014-05-01
Subsidence analysis of sedimentary basins and rifted continental margins requires a correction for the anomalous uplift or subsidence arising from mantle dynamic topography. Whilst different global model predictions of mantle dynamic topography may give a broadly similar pattern at long wavelengths, they differ substantially in the predicted amplitude and at shorter wavelengths. As a consequence the accuracy of predicted mantle dynamic topography is not sufficiently good to provide corrections for subsidence analysis. Measurements of present day anomalous subsidence, which we attribute to mantle dynamic topography, have been made for three rifted continental margins; offshore Iberia, the Gulf of Aden and southern Angola. We determine residual depth anomaly (RDA), corrected for sediment loading and crustal thickness variation for 2D profiles running from unequivocal oceanic crust across the continental ocean boundary onto thinned continental crust. Residual depth anomalies (RDA), corrected for sediment loading using flexural backstripping and decompaction, have been calculated by comparing observed and age predicted oceanic bathymetries at these margins. Age predicted bathymetric anomalies have been calculated using the thermal plate model predictions from Crosby & McKenzie (2009). Non-zero sediment corrected RDAs may result from anomalous oceanic crustal thickness with respect to the global average or from anomalous uplift or subsidence. Gravity anomaly inversion incorporating a lithosphere thermal gravity anomaly correction and sediment thickness from 2D seismic reflection data has been used to determine Moho depth, calibrated using seismic refraction, and oceanic crustal basement thickness. Crustal basement thicknesses derived from gravity inversion together with Airy isostasy have been used to correct for variations of crustal thickness from a standard oceanic thickness of 7km. The 2D profiles of RDA corrected for both sediment loading and non-standard crustal thickness provide a measurement of anomalous uplift or subsidence which we attribute to mantle dynamic topography. We compare our sediment and crustal thickness corrected RDA analysis results with published predictions of mantle dynamic topography from global models.
Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model
NASA Astrophysics Data System (ADS)
Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.
2014-02-01
Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.
Slip history and dynamic implications of the 1999 Chi-Chi, Taiwan, earthquake
Ji, C.; Helmberger, D.V.; Wald, D.J.; Ma, K.-F.
2003-01-01
We investigate the rupture process of the 1999 Chi-Chi, Taiwan, earthquake using extensive near-source observations, including three-component velocity waveforms at 36 strong motion stations and 119 GPS measurements. A three-plane fault geometry derived from our previous inversion using only static data [Ji et al., 2001] is applied. The slip amplitude, rake angle, rupture initiation time, and risetime function are inverted simultaneously with a recently developed finite fault inverse method that combines a wavelet transform approach with a simulated annealing algorithm [Ji et al., 2002b]. The inversion results are validated by the forward prediction of an independent data set, the teleseismic P and SH ground velocities, with notable agreement. The results show that the total seismic moment release of this earthquake is 2.7 ?? 1020 N m and that most of the slip occured in a triangular-shaped asperity involving two fault segments, which is consistent with our previous static inversion. The rupture front propagates with an average rupture velocity of ???2.0 km s-1, and the average slip duration (risetime) is 7.2 s. Several interesting observations related to the temporal evolution of the Chi-Chi earthquake are also investigated, including (1) the strong effect of the sinuous fault plane of the Chelungpu fault on spatial and temporal variations in slip history, (2) the intersection of fault 1 and fault 2 not being a strong impediment to the rupture propagation, and (3 the observation that the peak slip velocity near the surface is, in general, higher than on the deeper portion of the fault plane, as predicted by dynamic modeling.
NASA Astrophysics Data System (ADS)
Ortega Gelabert, Olga; Zlotnik, Sergio; Afonso, Juan Carlos; Díez, Pedro
2017-04-01
The determination of the present-day physical state of the thermal and compositional structure of the Earth's lithosphere and sub-lithospheric mantle is one of the main goals in modern lithospheric research. All this data is essential to build Earth's evolution models and to reproduce many geophysical observables (e.g. elevation, gravity anomalies, travel time data, heat flow, etc) together with understanding the relationship between them. Determining the lithospheric state involves the solution of high-resolution inverse problems and, consequently, the solution of many direct models is required. The main objective of this work is to contribute to the existing inversion techniques in terms of improving the estimation of the elevation (topography) by including a dynamic component arising from sub-lithospheric mantle flow. In order to do so, we implement an efficient Reduced Order Method (ROM) built upon classic Finite Elements. ROM allows to reduce significantly the computational cost of solving a family of problems, for example all the direct models that are required in the solution of the inverse problem. The strategy of the method consists in creating a (reduced) basis of solutions, so that when a new problem has to be solved, its solution is sought within the basis instead of attempting to solve the problem itself. In order to check the Reduced Basis approach, we implemented the method in a 3D domain reproducing a portion of Earth that covers up to 400 km depth. Within the domain the Stokes equation is solved with realistic viscosities and densities. The different realizations (the family of problems) is created by varying viscosities and densities in a similar way as it would happen in an inversion problem. The Reduced Basis method is shown to be an extremely efficiently solver for the Stokes equation in this context.
Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm
Chen, C.; Xia, J.; Liu, J.; Feng, G.
2006-01-01
Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant result is that final solution is determined by the average model derived from multiple trials instead of one computation due to the randomness in a genetic algorithm procedure. These advantages were demonstrated by synthetic and real-world examples of inversion of potential-field data. ?? 2005 Elsevier Ltd. All rights reserved.
Evaluation of a musculoskeletal model with prosthetic knee through six experimental gait trials.
Kia, Mohammad; Stylianou, Antonis P; Guess, Trent M
2014-03-01
Knowledge of the forces acting on musculoskeletal joint tissues during movement benefits tissue engineering, artificial joint replacement, and our understanding of ligament and cartilage injury. Computational models can be used to predict these internal forces, but musculoskeletal models that simultaneously calculate muscle force and the resulting loading on joint structures are rare. This study used publicly available gait, skeletal geometry, and instrumented prosthetic knee loading data [1] to evaluate muscle driven forward dynamics simulations of walking. Inputs to the simulation were measured kinematics and outputs included muscle, ground reaction, ligament, and joint contact forces. A full body musculoskeletal model with subject specific lower extremity geometries was developed in the multibody framework. A compliant contact was defined between the prosthetic femoral component and tibia insert geometries. Ligament structures were modeled with a nonlinear force-strain relationship. The model included 45 muscles on the right lower leg. During forward dynamics simulations a feedback control scheme calculated muscle forces using the error signal between the current muscle lengths and the lengths recorded during inverse kinematics simulations. Predicted tibio-femoral contact force, ground reaction forces, and muscle forces were compared to experimental measurements for six different gait trials using three different gait types (normal, trunk sway, and medial thrust). The mean average deviation (MAD) and root mean square deviation (RMSD) over one gait cycle are reported. The muscle driven forward dynamics simulations were computationally efficient and consistently reproduced the inverse kinematics motion. The forward simulations also predicted total knee contact forces (166N
NASA Astrophysics Data System (ADS)
Yang, Dikun; Oldenburg, Douglas W.; Haber, Eldad
2014-03-01
Airborne electromagnetic (AEM) methods are highly efficient tools for assessing the Earth's conductivity structures in a large area at low cost. However, the configuration of AEM measurements, which typically have widely distributed transmitter-receiver pairs, makes the rigorous modelling and interpretation extremely time-consuming in 3-D. Excessive overcomputing can occur when working on a large mesh covering the entire survey area and inverting all soundings in the data set. We propose two improvements. The first is to use a locally optimized mesh for each AEM sounding for the forward modelling and calculation of sensitivity. This dedicated local mesh is small with fine cells near the sounding location and coarse cells far away in accordance with EM diffusion and the geometric decay of the signals. Once the forward problem is solved on the local meshes, the sensitivity for the inversion on the global mesh is available through quick interpolation. Using local meshes for AEM forward modelling avoids unnecessary computing on fine cells on a global mesh that are far away from the sounding location. Since local meshes are highly independent, the forward modelling can be efficiently parallelized over an array of processors. The second improvement is random and dynamic down-sampling of the soundings. Each inversion iteration only uses a random subset of the soundings, and the subset is reselected for every iteration. The number of soundings in the random subset, determined by an adaptive algorithm, is tied to the degree of model regularization. This minimizes the overcomputing caused by working with redundant soundings. Our methods are compared against conventional methods and tested with a synthetic example. We also invert a field data set that was previously considered to be too large to be practically inverted in 3-D. These examples show that our methodology can dramatically reduce the processing time of 3-D inversion to a practical level without losing resolution. Any existing modelling technique can be included into our framework of mesh decoupling and adaptive sampling to accelerate large-scale 3-D EM inversions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wolf, Michael M.; Marzouk, Youssef M.; Adams, Brian M.
2008-10-01
Terrorist attacks using an aerosolized pathogen preparation have gained credibility as a national security concern since the anthrax attacks of 2001. The ability to characterize the parameters of such attacks, i.e., to estimate the number of people infected, the time of infection, the average dose received, and the rate of disease spread in contemporary American society (for contagious diseases), is important when planning a medical response. For non-contagious diseases, we address the characterization problem by formulating a Bayesian inverse problem predicated on a short time-series of diagnosed patients exhibiting symptoms. To keep the approach relevant for response planning, we limitmore » ourselves to 3.5 days of data. In computational tests performed for anthrax, we usually find these observation windows sufficient, especially if the outbreak model employed in the inverse problem is accurate. For contagious diseases, we formulated a Bayesian inversion technique to infer both pathogenic transmissibility and the social network from outbreak observations, ensuring that the two determinants of spreading are identified separately. We tested this technique on data collected from a 1967 smallpox epidemic in Abakaliki, Nigeria. We inferred, probabilistically, different transmissibilities in the structured Abakaliki population, the social network, and the chain of transmission. Finally, we developed an individual-based epidemic model to realistically simulate the spread of a rare (or eradicated) disease in a modern society. This model incorporates the mixing patterns observed in an (American) urban setting and accepts, as model input, pathogenic transmissibilities estimated from historical outbreaks that may have occurred in socio-economic environments with little resemblance to contemporary society. Techniques were also developed to simulate disease spread on static and sampled network reductions of the dynamic social networks originally in the individual-based model, yielding faster, though approximate, network-based epidemic models. These reduced-order models are useful in scenario analysis for medical response planning, as well as in computationally intensive inverse problems.« less
A lattice-based model of rotavirus epidemics
NASA Astrophysics Data System (ADS)
Lara-Sagahón, A.; Govezensky, T.; Méndez-Sánchez, R. A.; José, M. V.
2006-01-01
The cyclic recurrence of childhood rotavirus epidemics in unvaccinated populations provides one of the best documented phenomena in population dynamics and can become a paradigm for epidemic studies. Herein we analyse the monthly incidence of rotavirus infection from the city of Melbourne, Australia during 1976-2003. We show that there is an inverse nonlinear relationship of the cumulative distribution of the number of cases per month in a log-log plot. It is also shown that the rate of transmission of rotavirus infection follows a symmetric distribution centered on zero. A wavelet phase analysis of rotavirus epidemics is also carried out. We test the hypothesis that rotavirus dynamics could be a realization of a forest-fire model with sparks and with immune trees. Some statistical properties of this model turn out to be similar to the above results of actual rotavirus data.
Quench dynamics in SRF cavities: can we locate the quench origin with 2nd sound?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maximenko, Yulia; /Moscow, MIPT; Segatskov, Dmitri A.
2011-03-01
A newly developed method of locating quenches in SRF cavities by detecting second-sound waves has been gaining popularity in SRF laboratories. The technique is based on measurements of time delays between the quench as determined by the RF system and arrival of the second-sound wave to the multiple detectors placed around the cavity in superfluid helium. Unlike multi-channel temperature mapping, this approach requires only a few sensors and simple readout electronics; it can be used with SRF cavities of almost arbitrary shape. One of its drawbacks is that being an indirect method it requires one to solve an inverse problemmore » to find the location of a quench. We tried to solve this inverse problem by using a parametric forward model. By analyzing the data we found that the approximation where the second-sound emitter is a near-singular source does not describe the physical system well enough. A time-dependent analysis of the quench process can help us to put forward a more adequate model. We present here our current algorithm to solve the inverse problem and discuss the experimental results.« less
An interactive Bayesian geostatistical inverse protocol for hydraulic tomography
Fienen, Michael N.; Clemo, Tom; Kitanidis, Peter K.
2008-01-01
Hydraulic tomography is a powerful technique for characterizing heterogeneous hydrogeologic parameters. An explicit trade-off between characterization based on measurement misfit and subjective characterization using prior information is presented. We apply a Bayesian geostatistical inverse approach that is well suited to accommodate a flexible model with the level of complexity driven by the data and explicitly considering uncertainty. Prior information is incorporated through the selection of a parameter covariance model characterizing continuity and providing stability. Often, discontinuities in the parameter field, typically caused by geologic contacts between contrasting lithologic units, necessitate subdivision into zones across which there is no correlation among hydraulic parameters. We propose an interactive protocol in which zonation candidates are implied from the data and are evaluated using cross validation and expert knowledge. Uncertainty introduced by limited knowledge of dynamic regional conditions is mitigated by using drawdown rather than native head values. An adjoint state formulation of MODFLOW-2000 is used to calculate sensitivities which are used both for the solution to the inverse problem and to guide protocol decisions. The protocol is tested using synthetic two-dimensional steady state examples in which the wells are located at the edge of the region of interest.
NASA Astrophysics Data System (ADS)
Charco, M.; Rodriguez Molina, S.; Gonzalez, P. J.; Negredo, A. M.; Poland, M. P.; Schmidt, D. A.
2017-12-01
The Three Sisters volcanic region Oregon (USA) is one of the most active volcanic areas in the Cascade Range and is densely populated with eruptive vents. An extensive area just west of South Sister volcano has been actively uplifting since about 1998. InSAR data from 1992 through 2001 showed an uplift rate in the area of 3-4 cm/yr. Then the deformation rate considerably decreased between 2004 and 2006 as shown by both InSAR and continuous GPS measurements. Once magmatic system geometry and location are determined, a linear inversion of all GPS and InSAR data available is performed in order to estimate the volume changes of the source along the analyzed time interval. For doing so, we applied a technique based on the Truncated Singular Value Decomposition (TSVD) of the Green's function matrix representing the linear inversion. Here, we develop a strategy to provide a cut-off for truncation removing the smallest singular values without too much loose of data resolution against the stability of the method. Furthermore, the strategy will give us a quantification of the uncertainty of the volume change time series. The strength of the methodology resides in allowing the joint inversion of InSAR measurements from multiple tracks with different look angles and three component GPS measurements from multiple sites.Finally, we analyze the temporal behavior of the source volume changes using a new analytical model that describes the process of injecting magma into a reservoir surrounded by a viscoelastic shell. This dynamic model is based on Hagen-Poiseuille flow through a vertical conduit that leads to an increase in pressure within a spherical reservoir and time-dependent surface deformation. The volume time series are compared to predictions from the dynamic model to constrain model parameters, namely characteristic Poiseuille and Maxwell time scales, inlet and outlet injection pressure, and source and shell geometries. The modeling approach used here could be used to develop a mathematically rigorous strategy for including time-series deformation data in the interpretation of volcanic unrest.
Pedrocchi, Alessandra; Pedotti, Antonio; Baroni, Guido; Massion, Jean; Ferrigno, Giancarlo
2003-11-01
Present investigation faces the question of quantitative assessment of exchanged forces and torques at the restraints during whole body posture exercises in long-term microgravity. Inverse dynamic modelling and total angular momentum at the ankle joint were used in order to reconstruct movement dynamics at the restraining point, represented by the ankle joint. The hypothesis is that the minimisation of the torques at the interface point assumes a key role in movement planning in 0 g. This hypothesis would respond to an optimisation of muscles activity, a minimisation of energy expenditure and therefore an accurate control of body movement. Results show that the 0 g movement strategy adopted ensures that the integral of the net ankle moment between the beginning and the end of the movement is zero. This expected mechanical constraint is not satisfied when 0 g movement dynamics is simulated using terrestrial kinematics. This accounts for a significant imposed change of movement strategy. Particularly, the efficient compensation of the inertial effects of the segments in terms of total angular momentum at the ankle joint was evidenced. These results explain the exaggerated axial synergies, observed on kinematics and which moved centre of mass (CM) backward from its already backward initial positioning, as a tool for enhancing the compensation and achieving the desired minimisation of the torques exchanges at the restraints.
Forensic analysis of explosions: Inverse calculation of the charge mass.
van der Voort, M M; van Wees, R M M; Brouwer, S D; van der Jagt-Deutekom, M J; Verreault, J
2015-07-01
Forensic analysis of explosions consists of determining the point of origin, the explosive substance involved, and the charge mass. Within the EU FP7 project Hyperion, TNO developed the Inverse Explosion Analysis (TNO-IEA) tool to estimate the charge mass and point of origin based on observed damage around an explosion. In this paper, inverse models are presented based on two frequently occurring and reliable sources of information: window breakage and building damage. The models have been verified by applying them to the Enschede firework disaster and the Khobar tower attack. Furthermore, a statistical method has been developed to combine the various types of data, in order to determine an overall charge mass distribution. In relatively open environments, like for the Enschede firework disaster, the models generate realistic charge masses that are consistent with values found in forensic literature. The spread predicted by the IEA tool is however larger than presented in the literature for these specific cases. This is also realistic due to the large inherent uncertainties in a forensic analysis. The IEA-models give a reasonable first order estimate of the charge mass in a densely built urban environment, such as for the Khobar tower attack. Due to blast shielding effects which are not taken into account in the IEA tool, this is usually an under prediction. To obtain more accurate predictions, the application of Computational Fluid Dynamics (CFD) simulations is advised. The TNO IEA tool gives unique possibilities to inversely calculate the TNT equivalent charge mass based on a large variety of explosion effects and observations. The IEA tool enables forensic analysts, also those who are not experts on explosion effects, to perform an analysis with a largely reduced effort. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
An optimal resolved rate law for kinematically redundant manipulators
NASA Technical Reports Server (NTRS)
Bourgeois, B. J.
1987-01-01
The resolved rate law for a manipulator provides the instantaneous joint rates required to satisfy a given instantaneous hand motion. When the joint space has more degrees of freedom than the task space, the manipulator is kinematically redundant and the kinematic rate equations are underdetermined. These equations can be locally optimized, but the resulting pseudo-inverse solution has been found to cause large joint rates in some cases. A weighting matrix in the locally optimized (pseudo-inverse) solution is dynamically adjusted to control the joint motion as desired. Joint reach limit avoidance is demonstrated in a kinematically redundant planar arm model. The treatment is applicable to redundant manipulators with any number of revolute joints and to non-planar manipulators.
Hu, Jianping; Feng, Zhiwei; Ma, Shifan; Zhang, Yu; Tong, Qin; Alqarni, Mohammed Hamed; Gou, Xiaojun; Xie, Xiang-Qun
2016-06-27
Cannabinoid receptor 2 (CB2), a G protein-coupled receptor (GPCR), is a promising target for the treatment of neuropathic pain, osteoporosis, immune system, cancer, and drug abuse. The lack of an experimental three-dimensional CB2 structure has hindered not only the development of studies of conformational differences between the inactive and active CB2 but also the rational discovery of novel functional compounds targeting CB2. In this work, we constructed models of both inactive and active CB2 by homology modeling. Then we conducted two comparative 100 ns molecular dynamics (MD) simulations on the two systems-the active CB2 bound with both the agonist and G protein and the inactive CB2 bound with inverse agonist-to analyze the conformational difference of CB2 proteins and the key residues involved in molecular recognition. Our results showed that the inactive CB2 and the inverse agonist remained stable during the MD simulation. However, during the MD simulations, we observed dynamical details about the breakdown of the "ionic lock" between R131(3.50) and D240(6.30) as well as the outward/inward movements of transmembrane domains of the active CB2 that bind with G proteins and agonist (TM5, TM6, and TM7). All of these results are congruent with the experimental data and recent reports. Moreover, our results indicate that W258(6.48) in TM6 and residues in TM4 (V164(4.56)-L169(4.61)) contribute greatly to the binding of the agonist on the basis of the binding energy decomposition, while residues S180-F183 in extracellular loop 2 (ECL2) may be of importance in recognition of the inverse agonist. Furthermore, pharmacophore modeling and virtual screening were carried out for the inactive and active CB2 models in parallel. Among all 10 hits, two compounds exhibited novel scaffolds and can be used as novel chemical probes for future studies of CB2. Importantly, our studies show that the hits obtained from the inactive CB2 model mainly act as inverse agonist(s) or neutral antagonist(s) at low concentration. Moreover, the hit from the active CB2 model also behaves as a neutral antagonist at low concentration. Our studies provide new insight leading to a better understanding of the structural and conformational differences between two states of CB2 and illuminate the effects of structure on virtual screening and drug design.
Rapid finite-fault inversions in Southern California using Cybershake Green's functions
NASA Astrophysics Data System (ADS)
Thio, H. K.; Polet, J.
2017-12-01
We have developed a system for rapid finite fault inversion for intermediate and large Southern California earthquakes using local, regional and teleseismic seismic waveforms as well as geodetic data. For modeling the local seismic data, we use 3D Green's functions from the Cybershake project, which were made available to us courtesy of the Southern California Earthquake Center (SCEC). The use of 3D Green's functions allows us to extend the inversion to higher frequency waveform data and smaller magnitude earthquakes, in addition to achieving improved solutions in general. The ultimate aim of this work is to develop the ability to provide high quality finite fault models within a few hours after any damaging earthquake in Southern California, so that they may be used as input to various post-earthquake assessment tools such as ShakeMap, as well as by the scientific community and other interested parties. Additionally, a systematic determination of finite fault models has value as a resource for scientific studies on detailed earthquake processes, such as rupture dynamics and scaling relations. We are using an established least-squares finite fault inversion method that has been applied extensively both on large as well as smaller regional earthquakes, in conjunction with the 3D Green's functions, where available, as well as 1D Green's functions for areas for which the Cybershake library has not yet been developed. We are carrying out validation and calibration of this system using significant earthquakes that have occurred in the region over the last two decades, spanning a range of locations and magnitudes (5.4 and higher).
NASA Astrophysics Data System (ADS)
Karl, S.; Neuberg, J.
2011-12-01
Volcanoes exhibit a variety of seismic signals. One specific type, the so-called long-period (LP) or low-frequency event, has proven to be crucial for understanding the internal dynamics of the volcanic system. These long period (LP) seismic events have been observed at many volcanoes around the world, and are thought to be associated with resonating fluid-filled conduits or fluid movements (Chouet, 1996; Neuberg et al., 2006). While the seismic wavefield is well established, the actual trigger mechanism of these events is still poorly understood. Neuberg et al. (2006) proposed a conceptual model for the trigger of LP events at Montserrat involving the brittle failure of magma in the glass transition in response to the upwards movement of magma. In an attempt to gain a better quantitative understanding of the driving forces of LPs, inversions for the physical source mechanisms have become increasingly common. Previous studies have assumed a point source for waveform inversion. Knowing that applying a point source model to synthetic seismograms representing an extended source process does not yield the real source mechanism, it can, however, still lead to apparent moment tensor elements which then can be compared to previous results in the literature. Therefore, this study follows the proposed concepts of Neuberg et al. (2006), modelling the extended LP source as an octagonal arrangement of double couples approximating a circular ringfault bounding the circumference of the volcanic conduit. Synthetic seismograms were inverted for the physical source mechanisms of LPs using the moment tensor inversion code TDMTISO_INVC by Dreger (2003). Here, we will present the effects of changing the source parameters on the apparent moment tensor elements. First results show that, due to negative interference, the amplitude of the seismic signals of a ringfault structure is greatly reduced when compared to a single double couple source. Furthermore, best inversion results yield a solution comprised of positive isotropic and compensated linear vector dipole components. Thus, the physical source mechanisms of volcano seismic signals may be misinterpreted as opening shear or tensile cracks when wrongly assuming a point source. In order to approach the real physical sources with our models, inversions based on higher-order tensors might have to be considered in the future. An inversion technique where the point source is replaced by a so-called moment tensor density would allow inversions of volcano seismic signals for sources that can then be temporally and spatially extended.
A New Paradigm for Satellite Retrieval of Hydrologic Variables: The CDRD Methodology
NASA Astrophysics Data System (ADS)
Smith, E. A.; Mugnai, A.; Tripoli, G. J.
2009-09-01
Historically, retrieval of thermodynamically active geophysical variables in the atmosphere (e.g., temperature, moisture, precipitation) involved some time of inversion scheme - embedded within the retrieval algorithm - to transform radiometric observations (a vector) to the desired geophysical parameter(s) (either a scalar or a vector). Inversion is fundamentally a mathematical operation involving some type of integral-differential radiative transfer equation - often resisting a straightforward algebraic solution - in which the integral side of the equation (typically the right-hand side) contains the desired geophysical vector, while the left-hand side contains the radiative measurement vector often free of operators. Inversion was considered more desirable than forward modeling because the forward model solution had to be selected from a generally unmanageable set of parameter-observation relationships. However, in the classical inversion problem for retrieval of temperature using multiple radiative frequencies along the wing of an absorption band (or line) of a well-mixed radiatively active gas, in either the infrared or microwave spectrums, the inversion equation to be solved consists of a Fredholm integral equation of the 2nd kind - a specific type of transform problem in which there are an infinite number of solutions. This meant that special treatment of the transform process was required in order to obtain a single solution. Inversion had become the method of choice for retrieval in the 1950s because it appealed to the use of mathematical elegance, and because the numerical approaches used to solve the problems (typically some type of relaxation or perturbation scheme) were computationally fast in an age when computers speeds were slow. Like many solution schemes, inversion has lingered on regardless of the fact that computer speeds have increased many orders of magnitude and forward modeling itself has become far more elegant in combination with Bayesian averaging procedures given that the a priori probabilities of occurrence in the true environment of the parameter(s) in question can be approximated (or are actually known). In this presentation, the theory of the more modern retrieval approach using a combination of cloud, radiation and other specialized forward models in conjunction with Bayesian weighted averaging will be reviewed in light of a brief history of inversion. The application of the theory will be cast in the framework of what we call the Cloud-Dynamics-Radiation-Database (CDRD) methodology - which we now use for the retrieval of precipitation from spaceborne passive microwave radiometers. In a companion presentation, we will specifically describe the CDRD methodology and present results for its application within the Mediterranean basin.
Dynamics and Steady States in Excitable Mobile Agent Systems
NASA Astrophysics Data System (ADS)
Peruani, Fernando; Sibona, Gustavo J.
2008-04-01
We study the spreading of excitations in 2D systems of mobile agents where the excitation is transmitted when a quiescent agent keeps contact with an excited one during a nonvanishing time. We show that the steady states strongly depend on the spatial agent dynamics. Moreover, the coupling between exposition time (ω) and agent-agent contact rate (CR) becomes crucial to understand the excitation dynamics, which exhibits three regimes with CR: no excitation for low CR, an excited regime in which the number of quiescent agents (S) is inversely proportional to CR, and, for high CR, a novel third regime, model dependent, where S scales with an exponent ξ-1, with ξ being the scaling exponent of ω with CR.
Image contrast mechanisms in dynamic friction force microscopy: Antimony particles on graphite
NASA Astrophysics Data System (ADS)
Mertens, Felix; Göddenhenrich, Thomas; Dietzel, Dirk; Schirmeisen, Andre
2017-01-01
Dynamic Friction Force Microscopy (DFFM) is a technique based on Atomic Force Microscopy (AFM) where resonance oscillations of the cantilever are excited by lateral actuation of the sample. During this process, the AFM tip in contact with the sample undergoes a complex movement which consists of alternating periods of sticking and sliding. Therefore, DFFM can give access to dynamic transition effects in friction that are not accessible by alternative techniques. Using antimony nanoparticles on graphite as a model system, we analyzed how combined influences of friction and topography can effect different experimental configurations of DFFM. Based on the experimental results, for example, contrast inversion between fractional resonance and band excitation imaging strategies to extract reliable tribological information from DFFM images are devised.
Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.
Havlicek, Martin; Friston, Karl J; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D
2011-06-15
This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. Copyright © 2011 Elsevier Inc. All rights reserved.
Kyriakopoulos, Christos; Oglesby, David D.; Funning, Gareth J.; Ryan, Kenneth
2017-01-01
The 2010 Mw 7.2 El Mayor-Cucapah earthquake is the largest event recorded in the broader Southern California-Baja California region in the last 18 years. Here we try to analyze primary features of this type of event by using dynamic rupture simulations based on a multifault interface and later compare our results with space geodetic models. Our results show that starting from homogeneous prestress conditions, slip heterogeneity can be achieved as a result of variable dip angle along strike and the modulation imposed by step over segments. We also considered effects from a topographic free surface and find that although this does not produce significant first-order effects for this earthquake, even a low topographic dome such as the Cucapah range can affect the rupture front pattern and fault slip rate. Finally, we inverted available interferometric synthetic aperture radar data, using the same geometry as the dynamic rupture model, and retrieved the space geodetic slip distribution that serves to constrain the dynamic rupture models. The one to one comparison of the final fault slip pattern generated with dynamic rupture models and the space geodetic inversion show good agreement. Our results lead us to the following conclusion: in a possible multifault rupture scenario, and if we have first-order geometry constraints, dynamic rupture models can be very efficient in predicting large-scale slip heterogeneities that are important for the correct assessment of seismic hazard and the magnitude of future events. Our work contributes to understanding the complex nature of multifault systems.
Studies of planetary upper atmospheres through occultations
NASA Technical Reports Server (NTRS)
Elliot, J. L.
1982-01-01
The structure, composition, dynamics and energy balance of planetary upper atmospheres through interpretation of steller occultation data from Uranus is discussed. The wave-optical problem of modelling strong scintillation for arbitrary turbulent atmospheres is studied, as well as influence of turbulence. It was concluded that quasi-global features of atmospheric structure are accurately determined by numerical inversion. Horizontally inhomogeneous structures are filtered out and have little effect on temperature profiles.
NASA Astrophysics Data System (ADS)
Kaluza, Thorsten; Hoor, Peter; Kunkel, Daniel
2017-04-01
Studies of baroclinic life cycles recently revelead that the tropopause inversion layer (TIL) in the extratropics is significantly strengthened by diabatic processes related to moist tropospheric dynamics as well as by breaking of the baroclinic wave itself. However, these findings summarize the results from idealized model simulations and the contribution from processes related to baroclinic life cycles relative to other processes enhancing the lower stratospheric static stability (stratospheric dynamics, seasonal variation of radiative feedbacks) to the observed TIL at midlatitudes has yet to be assessed. Further the role of the TIL for stratosphere-troposphere exchange (STE) is currently still under debate. In preparation of the up-coming field campaign WISE (Wave driven isentropic exchange) we explore the state and variability of the TIL over the North Atlantic between August and October in analysis model data. We use high resolution operational analysis from the European Center for Medium Range Weather Forecast to study the mesoscale structure of the TIL. The main focus is on case studies of the TIL in real baroclinic life cycles, in particular on small scale enhancements within the baroclinic disturbances and the relation to STE. Moreover, a summary is presented about the quasi climatological state of the tropopause location and sharpness over the North Atlantic over recent years.
Multiscale numerical simulations of magnetoconvection at low magnetic Prandtl and Rossby numbers.
NASA Astrophysics Data System (ADS)
Maffei, S.; Calkins, M. A.; Julien, K. A.; Marti, P.
2017-12-01
The dynamics of the Earth's outer core is characterized by low values of the Rossby (Ro), Ekman and magnetic Prandtl numbers. These values indicate the large spectra of temporal and spatial scales that need to be accounted for in realistic numerical simulations of the system. Current direct numerical simulation are not capable of reaching this extreme regime, suggesting that a new class of models is required to account for the rich dynamics expected in the natural system. Here we present results from a quasi-geostrophic, multiscale model based on the scale separation implied by the low Ro typical of rapidly rotating systems. We investigate a plane layer geometry where convection is driven by an imposed temperature gradient and the hydrodynamic equations are modified by a large scale magnetic field. Analytical investigation shows that at values of thermal and magnetic Prandtl numbers relevant for liquid metals, the energetic requirements for the onset of convection is not significantly altered even in the presence of strong magnetic fields. Results from strongly forced nonlinear numerical simulations show the presence of an inverse cascade, typical of 2-D turbulence, when no or weak magnetic field is applied. For higher values of the magnetic field the inverse cascade is quenched.
NASA Astrophysics Data System (ADS)
Burov, Evgueni; Gerya, Taras
2013-04-01
It has been long assumed that the dynamic topography associated with mantle-lithosphere interactions should be characterized by long-wavelength features (> 1000 km) correlating with morphology of mantle flow and expanding beyond the scale of tectonic processes. For example, debates on the existence of mantle plumes largely originate from interpretations of expected signatures of plume-induced topography that are compared to the predictions of analytical and numerical models of plume- or mantle-lithosphere interactions (MLI). Yet, most of the large-scale models treat the lithosphere as a homogeneous stagnant layer. We show that in continents, the dynamic topography is strongly affected by rheological properties and layered structure of the lithosphere. For that we reconcile mantle- and tectonic-scale models by introducing a tectonically realistic continental plate model in 3D large-scale plume-mantle-lithosphere interaction context. This model accounts for stratified structure of continental lithosphere, ductile and frictional (Mohr-Coulomb) plastic properties and thermodynamically consistent density variations. The experiments reveal a number of important differences from the predictions of the conventional models. In particular, plate bending, mechanical decoupling of crustal and mantle layers and intra-plate tension-compression instabilities result in transient topographic signatures such as alternating small-scale surface features that could be misinterpreted in terms of regional tectonics. Actually thick ductile lower crustal layer absorbs most of the "direct" dynamic topography and the features produced at surface are mostly controlled by the mechanical instabilities in the upper and intermediate crustal layers produced by MLI-induced shear and bending at Moho and LAB. Moreover, the 3D models predict anisotropic response of the lithosphere even in case of isotropic solicitations by axisymmetric mantle upwellings such as plumes. In particular, in presence of small (i.e. insufficient to produce solely any significant deformation) uniaxial extensional tectonic stress field, the plume-produced surface and LAB features have anisotropic linear shapes perpendicular to the far-field tectonic forces, typical for continental rifts. Compressional field results in singular sub-linear folds above the plume head, perpendicular to the direction of compression. Small bi-axial tectonic stress fields (compression in one direction and extension in the orthogonal direction) result in oblique, almost linear segmented normal or inverse faults with strike-slip components (or visa verse , strike-slip faults with normal or inverse components)
Vandervert, Larry
2017-01-01
Mathematicians and scientists have struggled to adequately describe the ultimate foundations of mathematics. Nobel laureates Albert Einstein and Eugene Wigner were perplexed by this issue, with Wigner concluding that the workability of mathematics in the real world is a mystery we cannot explain. In response to this classic enigma, the major purpose of this article is to provide a theoretical model of the ultimate origin of mathematics and "number sense" (as defined by S. Dehaene) that is proposed to involve the learning of inverse dynamics models through the collaboration of the cerebellum and the cerebral cortex (but prominently cerebellum-driven). This model is based upon (1) the modern definition of mathematics as the "science of patterns," (2) cerebellar sequence (pattern) detection, and (3) findings that the manipulation of numbers is automated in the cerebellum. This cerebro-cerebellar approach does not necessarily conflict with mathematics or number sense models that focus on brain functions associated with especially the intraparietal sulcus region of the cerebral cortex. A direct corollary purpose of this article is to offer a cerebellar inner speech explanation for difficulty in developing "number sense" in developmental dyscalculia. It is argued that during infancy the cerebellum learns (1) a first tier of internal models for a primitive physics that constitutes the foundations of visual-spatial working memory, and (2) a second (and more abstract) tier of internal models based on (1) that learns "number" and relationships among dimensions across the primitive physics of the first tier. Within this context it is further argued that difficulty in the early development of the second tier of abstraction (and "number sense") is based on the more demanding attentional requirements imposed on cerebellar inner speech executive control during the learning of cerebellar inverse dynamics models. Finally, it is argued that finger counting improves (does not originate) "number sense" by extending focus of attention in executive control of silent cerebellar inner speech. It is suggested that (1) the origin of mathematics has historically been an enigma only because it is learned below the level of conscious awareness in cerebellar internal models, (2) understandings of the development of "number sense" and developmental dyscalculia can be advanced by first understanding the ultimate foundations of number and mathematics do not simply originate in the cerebral cortex, but rather in cerebro-cerebellar collaboration (predominately driven by the cerebellum). It is concluded that difficulty with "number sense" results from the extended demands on executive control in learning inverse dynamics models associated with cerebellar inner speech related to the second tier of abstraction (numbers) of the infant's primitive physics.
Redundancy, Self-Motion, and Motor Control
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
Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma
Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan
2014-01-01
Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470
Simulating the Past, Present and Future of the Upper Troposphere and Lower Stratosphere
NASA Astrophysics Data System (ADS)
Gettelman, Andrew; Hegglin, Michaela
2010-05-01
A comprehensive assessment of coupled chemistry climate model (CCM) performance in the upper troposphere and lower stratosphere has been conducted with 18 models. Both qualitative and quantitative comparisons of model representation of UTLS dynamical, radiative and chemical structure have been conducted, using a collection of quantitative grading techniques. The models are able to reproduce the observed climatology of dynamical, radiative and chemical structure in the tropical and extratropical UTLS, despite relatively coarse vertical and horizontal resolution. Diagnostics of the Tropical Tropopause Layer (TTL), Tropopause Inversion Layer (TIL) and Extra-tropical Transition Layer (ExTL) are analyzed. The results provide new insight into the key processes that govern the dynamics and transport in the tropics and extra-tropicsa. The presentation will explain how models are able to reproduce key features of the UTLS, what features they do not reproduce, and why. Model trends over the historical period are also assessed and interannual variability is included in the metrics. Finally, key trends in the UTLS for the future with a given halogen and greenhouse gas scenario are presented, indicating significant changes in tropopause height and temperature, as well as UTLS ozone concentrations in the 21st century due to climate change and ozone recovery.
Nonlinear Stimulated Raman Exact Passage by Resonance-Locked Inverse Engineering
NASA Astrophysics Data System (ADS)
Dorier, V.; Gevorgyan, M.; Ishkhanyan, A.; Leroy, C.; Jauslin, H. R.; Guérin, S.
2017-12-01
We derive an exact and robust stimulated Raman process for nonlinear quantum systems driven by pulsed external fields. The external fields are designed with closed-form expressions from the inverse engineering of a given efficient and stable dynamics. This technique allows one to induce a controlled population inversion which surpasses the usual nonlinear stimulated Raman adiabatic passage efficiency.
The First Time Ever I Saw Your Feet: Inversion Effect in Newborns' Sensitivity to Biological Motion
ERIC Educational Resources Information Center
Bardi, Lara; Regolin, Lucia; Simion, Francesca
2014-01-01
Inversion effect in biological motion perception has been recently attributed to an innate sensitivity of the visual system to the gravity-dependent dynamic of the motion. However, the specific cues that determine the inversion effect in naïve subjects were never investigated. In the present study, we have assessed the contribution of the local…
Surprises from quenches in long-range-interacting systems: temperature inversion and cooling
NASA Astrophysics Data System (ADS)
Gupta, Shamik; Casetti, Lapo
2016-10-01
What happens when one of the parameters governing the dynamics of a long-range interacting system of particles in thermal equilibrium is abruptly changed (quenched) to a different value? While a short-range system, under the same conditions, will relax in time to a new thermal equilibrium with a uniform temperature across the system, a long-range system shows a fast relaxation to a non-equilibrium quasistationary state (QSS). The lifetime of such an off-equilibrium state diverges with the system size, and the temperature is non-uniform across the system. Quite surprisingly, the density profile in the QSS obtained after the quench is anticorrelated with the temperature profile in space, thus exhibiting the phenomenon of temperature inversion: denser regions are colder than sparser ones. We illustrate with extensive molecular dynamics simulations the ubiquity of this scenario in a prototypical long-range interacting system subject to a variety of quenching protocols, and in a model that mimics an experimental setup of atoms interacting with light in an optical cavity. We further demonstrate how a procedure of iterative quenching combined with filtering out the high-energy particles in the system may be employed to cool the system. Temperature inversion is observed in nature in some astrophysical settings; our results imply that such a phenomenon should be observable, and could even be exploitable to advantage, also in controlled laboratory experiments.
Takatsu, Yasuo; Ueyama, Tsuyoshi; Miyati, Tosiaki; Yamamura, Kenichirou
2016-12-01
The image characteristics in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) depend on the partial Fourier fraction and contrast medium concentration. These characteristics were assessed and the modulation transfer function (MTF) was calculated by computer simulation. A digital phantom was created from signal intensity data acquired at different contrast medium concentrations on a breast model. The frequency images [created by fast Fourier transform (FFT)] were divided into 512 parts and rearranged to form a new image. The inverse FFT of this image yielded the MTF. From the reference data, three linear models (low, medium, and high) and three exponential models (slow, medium, and rapid) of the signal intensity were created. Smaller partial Fourier fractions, and higher gradients in the linear models, corresponded to faster MTF decline. The MTF more gradually decreased in the exponential models than in the linear models. The MTF, which reflects the image characteristics in DCE-MRI, was more degraded as the partial Fourier fraction decreased.
Review: Optimization methods for groundwater modeling and management
NASA Astrophysics Data System (ADS)
Yeh, William W.-G.
2015-09-01
Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.
Coelho, Antonio Augusto Rodrigues
2016-01-01
This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723
Acceleration constraints in modeling and control of nonholonomic systems
NASA Astrophysics Data System (ADS)
Bajodah, Abdulrahman H.
2003-10-01
Acceleration constraints are used to enhance modeling techniques for dynamical systems. In particular, Kane's equations of motion subjected to bilateral constraints, unilateral constraints, and servo-constraints are modified by utilizing acceleration constraints for the purpose of simplifying the equations and increasing their applicability. The tangential properties of Kane's method provide relationships between the holonomic and the nonholonomic partial velocities, and hence allow one to describe nonholonomic generalized active and inertia forces in terms of their holonomic counterparts, i.e., those which correspond to the system without constraints. Therefore, based on the modeling process objectives, the holonomic and the nonholonomic vector entities in Kane's approach are used interchangeably to model holonomic and nonholonomic systems. When the holonomic partial velocities are used to model nonholonomic systems, the resulting models are full-order (also called nonminimal or unreduced) and separated in accelerations. As a consequence, they are readily integrable and can be used for generic system analysis. Other related topics are constraint forces, numerical stability of the nonminimal equations of motion, and numerical constraint stabilization. Two types of unilateral constraints considered are impulsive and friction constraints. Impulsive constraints are modeled by means of a continuous-in-velocities and impulse-momentum approaches. In controlled motion, the acceleration form of constraints is utilized with the Moore-Penrose generalized inverse of the corresponding constraint matrix to solve for the inverse dynamics of servo-constraints, and for the redundancy resolution of overactuated manipulators. If control variables are involved in the algebraic constraint equations, then these tools are used to modify the controlled equations of motion in order to facilitate control system design. An illustrative example of spacecraft stabilization is presented.
Bayesian inversions of a dynamic vegetation model at four European grassland sites
NASA Astrophysics Data System (ADS)
Minet, J.; Laloy, E.; Tychon, B.; Francois, L.
2015-05-01
Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters, using the DREAM(ZS) (DiffeRential Evolution Adaptive Metropolis) Markov chain Monte Carlo (MCMC) sampler. We focus on comparing model inversions, considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a priori or jointly inferred together with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root mean square errors (RMSEs) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19, 1.04 to 1.56 g C m-2 day-1 and 0.50 to 1.28 mm day-1, respectively. For the calibration period, using a homoscedastic eddy covariance residual error model resulted in a better agreement between measured and modelled data than using a heteroscedastic residual error model. However, a model validation experiment showed that CARAIB models calibrated considering heteroscedastic residual errors perform better. Posterior parameter distributions derived from using a heteroscedastic model of the residuals thus appear to be more robust. This is the case even though the classical linear heteroscedastic error model assumed herein did not fully remove heteroscedasticity of the GPP residuals. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides the residual error treatment, differences between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics.
Guidance of Nonlinear Nonminimum-Phase Dynamic Systems
NASA Technical Reports Server (NTRS)
Devasia, Santosh
1996-01-01
The research work has advanced the inversion-based guidance theory for: systems with non-hyperbolic internal dynamics; systems with parameter jumps; and systems where a redesign of the output trajectory is desired. A technique to achieve output tracking for nonminimum phase linear systems with non-hyperbolic and near non-hyperbolic internal dynamics was developed. This approach integrated stable inversion techniques, that achieve exact-tracking, with approximation techniques, that modify the internal dynamics to achieve desirable performance. Such modification of the internal dynamics was used (a) to remove non-hyperbolicity which is an obstruction to applying stable inversion techniques and (b) to reduce large preactuation times needed to apply stable inversion for near non-hyperbolic cases. The method was applied to an example helicopter hover control problem with near non-hyperbolic internal dynamics for illustrating the trade-off between exact tracking and reduction of preactuation time. Future work will extend these results to guidance of nonlinear non-hyperbolic systems. The exact output tracking problem for systems with parameter jumps was considered. Necessary and sufficient conditions were derived for the elimination of switching-introduced output transient. While previous works had studied this problem by developing a regulator that maintains exact tracking through parameter jumps (switches), such techniques are, however, only applicable to minimum-phase systems. In contrast, our approach is also applicable to nonminimum-phase systems and leads to bounded but possibly non-causal solutions. In addition, for the case when the reference trajectories are generated by an exosystem, we developed an exact-tracking controller which could be written in a feedback form. As in standard regulator theory, we also obtained a linear map from the states of the exosystem to the desired system state, which was defined via a matrix differential equation.
Laser Powered Launch Vehicle Performance Analyses
NASA Technical Reports Server (NTRS)
Chen, Yen-Sen; Liu, Jiwen; Wang, Ten-See (Technical Monitor)
2001-01-01
The purpose of this study is to establish the technical ground for modeling the physics of laser powered pulse detonation phenomenon. Laser powered propulsion systems involve complex fluid dynamics, thermodynamics and radiative transfer processes. Successful predictions of the performance of laser powered launch vehicle concepts depend on the sophisticate models that reflects the underlying flow physics including the laser ray tracing the focusing, inverse Bremsstrahlung (IB) effects, finite-rate air chemistry, thermal non-equilibrium, plasma radiation and detonation wave propagation, etc. The proposed work will extend the base-line numerical model to an efficient design analysis tool. The proposed model is suitable for 3-D analysis using parallel computing methods.
Spin-charge coupled dynamics driven by a time-dependent magnetization
NASA Astrophysics Data System (ADS)
Tölle, Sebastian; Eckern, Ulrich; Gorini, Cosimo
2017-03-01
The spin-charge coupled dynamics in a thin, magnetized metallic system are investigated. The effective driving force acting on the charge carriers is generated by a dynamical magnetic texture, which can be induced, e.g., by a magnetic material in contact with a normal-metal system. We consider a general inversion-asymmetric substrate/normal-metal/magnet structure, which, by specifying the precise nature of each layer, can mimic various experimentally employed setups. Inversion symmetry breaking gives rise to an effective Rashba spin-orbit interaction. We derive general spin-charge kinetic equations which show that such spin-orbit interaction, together with anisotropic Elliott-Yafet spin relaxation, yields significant corrections to the magnetization-induced dynamics. In particular, we present a consistent treatment of the spin density and spin current contributions to the equations of motion, inter alia, identifying a term in the effective force which appears due to a spin current polarized parallel to the magnetization. This "inverse-spin-filter" contribution depends markedly on the parameter which describes the anisotropy in spin relaxation. To further highlight the physical meaning of the different contributions, the spin-pumping configuration of typical experimental setups is analyzed in detail. In the two-dimensional limit the buildup of dc voltage is dominated by the spin-galvanic (inverse Edelstein) effect. A measuring scheme that could isolate this contribution is discussed.
Fluid moments of the nonlinear Landau collision operator
Hirvijoki, E.; Lingam, M.; Pfefferle, D.; ...
2016-08-09
An important problem in plasma physics is the lack of an accurate and complete description of Coulomb collisions in associated fluid models. To shed light on the problem, this Letter introduces an integral identity involving the multivariate Hermite tensor polynomials and presents a method for computing exact expressions for the fluid moments of the nonlinear Landau collision operator. In conclusion, the proposed methodology provides a systematic and rigorous means of extending the validity of fluid models that have an underlying inverse-square force particle dynamics to arbitrary collisionality and flow.
Pecha, Petr; Šmídl, Václav
2016-11-01
A stepwise sequential assimilation algorithm is proposed based on an optimisation approach for recursive parameter estimation and tracking of radioactive plume propagation in the early stage of a radiation accident. Predictions of the radiological situation in each time step of the plume propagation are driven by an existing short-term meteorological forecast and the assimilation procedure manipulates the model parameters to match the observations incoming concurrently from the terrain. Mathematically, the task is a typical ill-posed inverse problem of estimating the parameters of the release. The proposed method is designated as a stepwise re-estimation of the source term release dynamics and an improvement of several input model parameters. It results in a more precise determination of the adversely affected areas in the terrain. The nonlinear least-squares regression methodology is applied for estimation of the unknowns. The fast and adequately accurate segmented Gaussian plume model (SGPM) is used in the first stage of direct (forward) modelling. The subsequent inverse procedure infers (re-estimates) the values of important model parameters from the actual observations. Accuracy and sensitivity of the proposed method for real-time forecasting of the accident propagation is studied. First, a twin experiment generating noiseless simulated "artificial" observations is studied to verify the minimisation algorithm. Second, the impact of the measurement noise on the re-estimated source release rate is examined. In addition, the presented method can be used as a proposal for more advanced statistical techniques using, e.g., importance sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Kunkel, D.; Hoor, P. M.; Wirth, V.
2014-12-01
Observations and model simulations of temperature and tracer profiles in the extratropical upper troposphere/lower stratosphere (UTLS) show the presence of an inversion layer just above the thermal tropopause, i.e., the tropopause inversion layer (TIL), which is situated in a region affected by stratosphere-troposphere exchange (STE). Moreover, from a dynamical perspective the extratropical UTLS is highly affected by baroclinic life cycles. Since both the TIL and STE emerge, amongst many other features, during simulated baroclinic life cycles, we study whether there is a relationship between the TIL and STE. We use the non-hydrostatic model COSMO in an idealized mid-latitude channel configuration to simulate baroclinic life cycles. In a first step contributions of individual diabatic processes from turbulence, radiation, and cloud microphysics to the formation of the TIL are analyzed. These results are compared to those from adiabatic simulations in which the TIL forms during the life cycles with the limitation of being less sharp than in observations. Furthermore, passive tropospheric and stratospheric tracers are used to identify STE. Regions of STE are then analyzed with respect to the temporal evolution of the static stability above the tropopause. The results suggest that radiative effects, especially from water vapor, have the largest additional contribution to the TIL formation, while additional individual effects of cloud microphysics are almost negligible. STE occurs in all diabatic simulations but its strength depends highly on how the underlying diabatic process can affect the thermal and dynamical structure in the tropopause region. Weak STE is found when considering cloud microphysics, while STE is stronger in case of using turbulence and radiation. Tropopause-based vertical profiles of the tropospheric tracers show in some cases similarities with observed tracer profiles of CO.
Updated Results for the Wake Vortex Inverse Model
NASA Technical Reports Server (NTRS)
Robins, Robert E.; Lai, David Y.; Delisi, Donald P.; Mellman, George R.
2008-01-01
NorthWest Research Associates (NWRA) has developed an Inverse Model for inverting aircraft wake vortex data. The objective of the inverse modeling is to obtain estimates of the vortex circulation decay and crosswind vertical profiles, using time history measurements of the lateral and vertical position of aircraft vortices. The Inverse Model performs iterative forward model runs using estimates of vortex parameters, vertical crosswind profiles, and vortex circulation as a function of wake age. Iterations are performed until a user-defined criterion is satisfied. Outputs from an Inverse Model run are the best estimates of the time history of the vortex circulation derived from the observed data, the vertical crosswind profile, and several vortex parameters. The forward model, named SHRAPA, used in this inverse modeling is a modified version of the Shear-APA model, and it is described in Section 2 of this document. Details of the Inverse Model are presented in Section 3. The Inverse Model was applied to lidar-observed vortex data at three airports: FAA acquired data from San Francisco International Airport (SFO) and Denver International Airport (DEN), and NASA acquired data from Memphis International Airport (MEM). The results are compared with observed data. This Inverse Model validation is documented in Section 4. A summary is given in Section 5. A user's guide for the inverse wake vortex model is presented in a separate NorthWest Research Associates technical report (Lai and Delisi, 2007a).
Multisclae heterogeneity of the 2011 Tohoku-oki earthquake by inversion
NASA Astrophysics Data System (ADS)
Aochi, H.; Ulrich, T.; Cornier, G.
2012-12-01
Earthquake fault heterogeneity is often studied on a set of subfaults in kinematic inversion, while it is sometimes described with spatially localized geometry. Aochi and Ide (EPS, 2011) and Ide and Aochi (submitted to Pageoph and AGU, 2012) apply a concept of multi-scale heterogeneity to simulate the dynamic rupture process of the 2011 Tohoku-oki earthquake, introducing circular patches of different dimension in fault fracture energy distribution. Previously the patches are given by the past moderate earthquakes in this region, and this seems to be consistent with the evolution process of this mega earthquake, although a few patches, in particular, the largest patch, had not been known previously. In this study, we try to identify patches by inversion. As demonstrated in several earthquakes including the 2010 Maule (M8.8) earthquake, it is possible to indentify two asperities of ellipse kinematically or dynamically (e.g. Ruiz and Madariaga, 2011, and so on). In the successful examples, different asperities are rather visible, separated in space. However the Tohoku-oki earthquake has hierarchical structure of heterogeneity. We apply the Genetic Algorithm to inverse the model parameters from the ground motions (K-net and Kik-net from NIED) and the high sampling GPS (GSI). Starting from low frequency ranges (> 50 seconds), we obtain an ellipse corresponding to M9 event located around the hypocenter, coherent with the previous result by Madariaga et al. (pers. comm.). However it is difficult to identify the second smaller with few constraints. This is mainly because the largest covers the entire rupture area and any smaller patch improves the fitting only for the closer stations. Again, this needs to introduce the multi-scale concept in inversion procedure. Instead of finding the largest one at first, we have to start to extract rather smaller moderate patches from the beginning of the record, following the rupture process.
Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi
2015-10-08
In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.
A Geophysical Inversion Model Enhancement Technique Based on the Blind Deconvolution
NASA Astrophysics Data System (ADS)
Zuo, B.; Hu, X.; Li, H.
2011-12-01
A model-enhancement technique is proposed to enhance the geophysical inversion model edges and details without introducing any additional information. Firstly, the theoretic correctness of the proposed geophysical inversion model-enhancement technique is discussed. An inversion MRM (model resolution matrix) convolution approximating PSF (Point Spread Function) method is designed to demonstrate the correctness of the deconvolution model enhancement method. Then, a total-variation regularization blind deconvolution geophysical inversion model-enhancement algorithm is proposed. In previous research, Oldenburg et al. demonstrate the connection between the PSF and the geophysical inverse solution. Alumbaugh et al. propose that more information could be provided by the PSF if we return to the idea of it behaving as an averaging or low pass filter. We consider the PSF as a low pass filter to enhance the inversion model basis on the theory of the PSF convolution approximation. Both the 1D linear and the 2D magnetotelluric inversion examples are used to analyze the validity of the theory and the algorithm. To prove the proposed PSF convolution approximation theory, the 1D linear inversion problem is considered. It shows the ratio of convolution approximation error is only 0.15%. The 2D synthetic model enhancement experiment is presented. After the deconvolution enhancement, the edges of the conductive prism and the resistive host become sharper, and the enhancement result is closer to the actual model than the original inversion model according the numerical statistic analysis. Moreover, the artifacts in the inversion model are suppressed. The overall precision of model increases 75%. All of the experiments show that the structure details and the numerical precision of inversion model are significantly improved, especially in the anomalous region. The correlation coefficient between the enhanced inversion model and the actual model are shown in Fig. 1. The figure illustrates that more information and details structure of the actual model are enhanced through the proposed enhancement algorithm. Using the proposed enhancement method can help us gain a clearer insight into the results of the inversions and help make better informed decisions.
NASA Astrophysics Data System (ADS)
Ronchin, Erika; Masterlark, Timothy; Dawson, John; Saunders, Steve; Martì Molist, Joan
2017-06-01
We test an innovative inversion scheme using Green's functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green's function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green's functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.
Qian, Xinyi Lisa; Yarnal, Careen M; Almeida, David M
2013-01-01
Affective complexity, a manifestation of psychological well-being, refers to the relative independence between positive and negative affect (PA, NA). According to the Dynamic Model of Affect (DMA), stressful situations lead to highly inverse PA-NA relationship, reducing affective complexity. Meanwhile, positive events can sustain affective complexity by restoring PA-NA independence. Leisure, a type of positive events, has been identified as a coping resource. This study used the DMA to assess whether leisure time helps restore affective complexity on stressful days. We found that on days with more leisure time than usual, an individual experienced less negative PA-NA relationship after daily stressful events. The finding demonstrates the value of leisure time as a coping resource and the DMA's contribution to coping research.
NASA Astrophysics Data System (ADS)
Yu, Jiang-Bo; Zhao, Yan; Wu, Yu-Qiang
2014-04-01
This article considers the global robust output regulation problem via output feedback for a class of cascaded nonlinear systems with input-to-state stable inverse dynamics. The system uncertainties depend not only on the measured output but also all the unmeasurable states. By introducing an internal model, the output regulation problem is converted into a stabilisation problem for an appropriately augmented system. The designed dynamic controller could achieve the global asymptotic tracking control for a class of time-varying reference signals for the system output while keeping all other closed-loop signals bounded. It is of interest to note that the developed control approach can be applied to the speed tracking control of the fan speed control system. The simulation results demonstrate its effectiveness.
Sensitivity analyses of acoustic impedance inversion with full-waveform inversion
NASA Astrophysics Data System (ADS)
Yao, Gang; da Silva, Nuno V.; Wu, Di
2018-04-01
Acoustic impedance estimation has a significant importance to seismic exploration. In this paper, we use full-waveform inversion to recover the impedance from seismic data, and analyze the sensitivity of the acoustic impedance with respect to the source-receiver offset of seismic data and to the initial velocity model. We parameterize the acoustic wave equation with velocity and impedance, and demonstrate three key aspects of acoustic impedance inversion. First, short-offset data are most suitable for acoustic impedance inversion. Second, acoustic impedance inversion is more compatible with the data generated by density contrasts than velocity contrasts. Finally, acoustic impedance inversion requires the starting velocity model to be very accurate for achieving a high-quality inversion. Based upon these observations, we propose a workflow for acoustic impedance inversion as: (1) building a background velocity model with travel-time tomography or reflection waveform inversion; (2) recovering the intermediate wavelength components of the velocity model with full-waveform inversion constrained by Gardner’s relation; (3) inverting the high-resolution acoustic impedance model with short-offset data through full-waveform inversion. We verify this workflow by the synthetic tests based on the Marmousi model.
A Generic Inner-Loop Control Law Structure for Six-Degree-of-Freedom Conceptual Aircraft Design
NASA Technical Reports Server (NTRS)
Cox, Timothy H.; Cotting, M. Christopher
2005-01-01
A generic control system framework for both real-time and batch six-degree-of-freedom simulations is presented. This framework uses a simplified dynamic inversion technique to allow for stabilization and control of any type of aircraft at the pilot interface level. The simulation, designed primarily for the real-time simulation environment, also can be run in a batch mode through a simple guidance interface. Direct vehicle-state acceleration feedback is required with the simplified dynamic inversion technique. The estimation of surface effectiveness within real-time simulation timing constraints also is required. The generic framework provides easily modifiable control variables, allowing flexibility in the variables that the pilot commands. A direct control allocation scheme is used to command aircraft effectors. Primary uses for this system include conceptual and preliminary design of aircraft, when vehicle models are rapidly changing and knowledge of vehicle six-degree-of-freedom performance is required. A simulated airbreathing hypersonic vehicle and simulated high-performance fighter aircraft are used to demonstrate the flexibility and utility of the control system.
A Generic Inner-Loop Control Law Structure for Six-Degree-of-Freedom Conceptual Aircraft Design
NASA Technical Reports Server (NTRS)
Cox, Timothy H.; Cotting, Christopher
2005-01-01
A generic control system framework for both real-time and batch six-degree-of-freedom (6-DOF) simulations is presented. This framework uses a simplified dynamic inversion technique to allow for stabilization and control of any type of aircraft at the pilot interface level. The simulation, designed primarily for the real-time simulation environment, also can be run in a batch mode through a simple guidance interface. Direct vehicle-state acceleration feedback is required with the simplified dynamic inversion technique. The estimation of surface effectiveness within real-time simulation timing constraints also is required. The generic framework provides easily modifiable control variables, allowing flexibility in the variables that the pilot commands. A direct control allocation scheme is used to command aircraft effectors. Primary uses for this system include conceptual and preliminary design of aircraft, when vehicle models are rapidly changing and knowledge of vehicle 6-DOF performance is required. A simulated airbreathing hypersonic vehicle and simulated high-performance fighter aircraft are used to demonstrate the flexibility and utility of the control system.
NASA Technical Reports Server (NTRS)
Miller, Christopher J.
2011-01-01
A model reference nonlinear dynamic inversion control law has been developed to provide a baseline controller for research into simple adaptive elements for advanced flight control laws. This controller has been implemented and tested in a hardware-in-the-loop simulation and in flight. The flight results agree well with the simulation predictions and show good handling qualities throughout the tested flight envelope with some noteworthy deficiencies highlighted both by handling qualities metrics and pilot comments. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as simple as possible to easily allow the addition of the adaptive elements. The flight-test results and how they compare to the simulation predictions are discussed, along with a discussion about how each element affected pilot opinions. Additionally, aspects of the design that performed better than expected are presented, as well as some simple improvements that will be suggested for follow-on work.
Quantifying the value of information for uncertainty reduction in chemical EOR modeling
NASA Astrophysics Data System (ADS)
Leray, Sarah; Yeates, Christopher; Douarche, Frédéric; Roggero, Frédéric
2016-04-01
Reservoir modeling is a powerful tool to assess the technical and economic feasibility of chemical Enhanced Oil Recovery methods such as the joint injection of surfactant and polymer. Laboratory recovery experiments are usually undertaken on cores to understand recovery mechanisms and to estimate properties, that will be further used to build large scale models. To capture the different processes involved in chemical EOR, models are described by a large number of parameters which are basically only partially constrained by recovery experiments and additional characterizations, mainly because of cost and time restrictions or limited representativeness. Among the most uncertain properties, features the surfactant adsorption which cannot be straightforwardly derived from bulk or simplified dynamic measurements (e.g. single phase dynamic adsorption experiments). It is unfortunately critical for the economics of the process. Identifying the most informative observations (e.g. saturation scans, pressure differential, surfactant production, oil recovery) is of primary interest to compensate deficiency of some characterizations and improve models robustness and their predictive capability. Building a consistent set of recovery experiments that will allow to seize recovery mechanisms is critical as well. To address these inverse methodology issues, we create a synthetic numerical model with a well-defined set of parameter values, considered to be our reference case. This choice of model is based on a similar real data set and a broad literature review. It consists of a water-wet sandstone subject to typical surfactant-polymer injections. We first study the effect of a salinity gradient injected after a surfactant-polymer slug, as it is known to significantly improve oil recovery. We show that reaching optimal conditions of salinity gradient is a fragile balance between surfactant desorption and interfacial tension increase. This high dependence on surfactant adsorption properties indicates that two recovery tests with and without salinity gradient are of great interest for model inversion and characterization of surfactant adsorption. Second, we analyze our capacity to find again the reference model using an assisted history matching method to reproduce a set of synthetic core-scale experiments. To do so, we use the reference model over five configurations with respect to chemicals injection to provide baseline recovery data. Then, we consider some uncertainty on model parameters, regarding surfactant adsorption properties amongst others, leading to a total of twelve uncertain parameters. Finally, we extensively explore the parameter space to find several reasonable matches. We show that an additional sixth recovery experiment is necessary to fully constrain the model, and specifically characterize surfactant adsorption. We besides show that production data are not equally informative: pressure differential is for instance the less informative data while a saturation scan at the end of the polymer post-flush can greatly help in the inversion. The inverse methodology carried out here has also been successfully tested with a real set of coreflood experiments.
Bayesian model reduction and empirical Bayes for group (DCM) studies.
Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter
2016-03-01
This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Chaos Versus Noisy Periodicity: Alternative Hypotheses for Childhood Epidemics
NASA Astrophysics Data System (ADS)
Olsen, L. F.; Schaffer, W. M.
1990-08-01
Whereas case rates for some childhood diseases (chickenpox) often vary according to an almost regular annual cycle, the incidence of more efficiently transmitted infections such as measles is more variable. Three hypotheses have been proposed to account for such fluctuations. (i) Irregular dynamics result from random shocks to systems with stable equilibria. (ii) The intrinsic dynamics correspond to biennial cycles that are subject to stochastic forcing. (iii) Aperiodic fluctuations are intrinsic to the epidemiology. Comparison of real world data and epidemiological models suggests that measles epidemics are inherently chaotic. Conversely, the extent to which chickenpox outbreaks approximate a yearly cycle depends inversely on the population size.
NASA Astrophysics Data System (ADS)
Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.
2017-04-01
The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.
Fragata, I; Lopes-Cunha, M; Bárbaro, M; Kellen, B; Lima, M; Santos, M A; Faria, G S; Santos, M; Matos, M; Simões, P
2014-12-01
Chromosomal inversions are present in a wide range of animals and plants, having an important role in adaptation and speciation. Although empirical evidence of their adaptive value is abundant, the role of different processes underlying evolution of chromosomal polymorphisms is not fully understood. History and selection are likely to shape inversion polymorphism variation to an extent yet largely unknown. Here, we perform a real-time evolution study addressing the role of historical constraints and selection in the evolution of these polymorphisms. We founded laboratory populations of Drosophila subobscura derived from three locations along the European cline and followed the evolutionary dynamics of inversion polymorphisms throughout the first 40 generations. At the beginning, populations were highly differentiated and remained so throughout generations. We report evidence of positive selection for some inversions, variable between foundations. Signs of negative selection were more frequent, in particular for most cold-climate standard inversions across the three foundations. We found that previously observed convergence at the phenotypic level in these populations was not associated with convergence in inversion frequencies. In conclusion, our study shows that selection has shaped the evolutionary dynamics of inversion frequencies, but doing so within the constraints imposed by previous history. Both history and selection are therefore fundamental to predict the evolutionary potential of different populations to respond to global environmental changes. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
FINSTERLE, STEFAN; JUNG, YOOJIN; KOWALSKY, MICHAEL
2016-09-15
iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. iTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. iTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. iTOUGH2 solves the inverse problem bymore » minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. This upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. More details can be found at http://esd.lbl.gov/iTOUGH2.« less
A Part-Time Solar Chromosphere?
NASA Astrophysics Data System (ADS)
Kalkofen, W.
1999-05-01
The dynamical model of the nonmagnetic chromosphere of Carlsson & Stein (1994) has a time-dependent temperature structure from shock dissipation of upward-propagating acoustic waves. For the high-temperature phase of waves due to an observed photospheric velocity spectrum, the model reproduces to great fidelity the intricate velocity and intensity variations of the corresponding H line from an hour-long observing run. But for the low-temperature phase, in which the temperature drops monotonically in the outward direction up to a height of at least 1.8 Mm above tau =1, the model predicts UV spectra for lines and continua that should be observable in absorption everywhere and almost all the time. However, observations with SUMER show only emission lines, everywhere and all the time. The dynamical model fails as a temperature model because it uses less than 5% of the wave energy entering the chromosphere. The extra energy is hidden in the observed power spectrum at acoustic frequencies above 10 mHz; it accounts for a permanent temperature inversion and thus a full-time chromosphere.
Fieselmann, Andreas; Dennerlein, Frank; Deuerling-Zheng, Yu; Boese, Jan; Fahrig, Rebecca; Hornegger, Joachim
2011-06-21
Filtered backprojection is the basis for many CT reconstruction tasks. It assumes constant attenuation values of the object during the acquisition of the projection data. Reconstruction artifacts can arise if this assumption is violated. For example, contrast flow in perfusion imaging with C-arm CT systems, which have acquisition times of several seconds per C-arm rotation, can cause this violation. In this paper, we derived and validated a novel spatio-temporal model to describe these kinds of artifacts. The model separates the temporal dynamics due to contrast flow from the scan and reconstruction parameters. We introduced derivative-weighted point spread functions to describe the spatial spread of the artifacts. The model allows prediction of reconstruction artifacts for given temporal dynamics of the attenuation values. Furthermore, it can be used to systematically investigate the influence of different reconstruction parameters on the artifacts. We have shown that with optimized redundancy weighting function parameters the spatial spread of the artifacts around a typical arterial vessel can be reduced by about 70%. Finally, an inversion of our model could be used as the basis for novel dynamic reconstruction algorithms that further minimize these artifacts.
A nonlinear Kalman filtering approach to embedded control of turbocharged diesel engines
NASA Astrophysics Data System (ADS)
Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan
2014-10-01
The development of efficient embedded control for turbocharged Diesel engines, requires the programming of elaborated nonlinear control and filtering methods. To this end, in this paper nonlinear control for turbocharged Diesel engines is developed with the use of Differential flatness theory and the Derivative-free nonlinear Kalman Filter. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances the Derivative-free nonlinear Kalman Filter is used and redesigned as a disturbance observer. The filter consists of the Kalman Filter recursion on the linearized equivalent of the Diesel engine model and of an inverse transformation based on differential flatness theory which enables to obtain estimates for the state variables of the initial nonlinear model. Once the disturbances variables are identified it is possible to compensate them by including an additional control term in the feedback loop. The efficiency of the proposed control method is tested through simulation experiments.
Katiyar, Prateek; Divine, Mathew R; Kohlhofer, Ursula; Quintanilla-Martinez, Leticia; Schölkopf, Bernhard; Pichler, Bernd J; Disselhorst, Jonathan A
2017-04-01
In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18 F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18 F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18 F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18 F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor heterogeneity using dynamic PET studies. Because SC tumor segmentation is based on the intrinsic structure of the underlying data, it can be easily applied to other cancer types as well. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brown, Justin; Hund, Lauren
2017-02-01
Dynamic compression experiments are being performed on complicated materials using increasingly complex drivers. The data produced in these experiments are beginning to reach a regime where traditional analysis techniques break down; requiring the solution of an inverse problem. A common measurement in dynamic experiments is an interface velocity as a function of time, and often this functional output can be simulated using a hydrodynamics code. Bayesian model calibration is a statistical framework to estimate inputs into a computational model in the presence of multiple uncertainties, making it well suited to measurements of this type. In this article, we apply Bayesianmore » model calibration to high pressure (250 GPa) ramp compression measurements in tantalum. We address several issues speci c to this calibration including the functional nature of the output as well as parameter and model discrepancy identi ability. Speci cally, we propose scaling the likelihood function by an e ective sample size rather than modeling the autocorrelation function to accommodate the functional output and propose sensitivity analyses using the notion of `modularization' to assess the impact of experiment-speci c nuisance input parameters on estimates of material properties. We conclude that the proposed Bayesian model calibration procedure results in simple, fast, and valid inferences on the equation of state parameters for tantalum.« less
Orellana, Liliana; Rotnitzky, Andrea; Robins, James M
2010-01-01
Dynamic treatment regimes are set rules for sequential decision making based on patient covariate history. Observational studies are well suited for the investigation of the effects of dynamic treatment regimes because of the variability in treatment decisions found in them. This variability exists because different physicians make different decisions in the face of similar patient histories. In this article we describe an approach to estimate the optimal dynamic treatment regime among a set of enforceable regimes. This set is comprised by regimes defined by simple rules based on a subset of past information. The regimes in the set are indexed by a Euclidean vector. The optimal regime is the one that maximizes the expected counterfactual utility over all regimes in the set. We discuss assumptions under which it is possible to identify the optimal regime from observational longitudinal data. Murphy et al. (2001) developed efficient augmented inverse probability weighted estimators of the expected utility of one fixed regime. Our methods are based on an extension of the marginal structural mean model of Robins (1998, 1999) which incorporate the estimation ideas of Murphy et al. (2001). Our models, which we call dynamic regime marginal structural mean models, are specially suitable for estimating the optimal treatment regime in a moderately small class of enforceable regimes of interest. We consider both parametric and semiparametric dynamic regime marginal structural models. We discuss locally efficient, double-robust estimation of the model parameters and of the index of the optimal treatment regime in the set. In a companion paper in this issue of the journal we provide proofs of the main results.
Chng, Choon-Peng; Yang, Lee-Wei
2008-01-01
Molecular dynamics (MD) simulation has remained the most indispensable tool in studying equilibrium/non-equilibrium conformational dynamics since its advent 30 years ago. With advances in spectroscopy accompanying solved biocomplexes in growing sizes, sampling their dynamics that occur at biologically interesting spatial/temporal scales becomes computationally intractable; this motivated the use of coarse-grained (CG) approaches. CG-MD models are used to study folding and conformational transitions in reduced resolution and can employ enlarged time steps due to the absence of some of the fastest motions in the system. The Boltzmann-Inversion technique, heavily used in parameterizing these models, provides a smoothed-out effective potential on which molecular conformation evolves at a faster pace thus stretching simulations into tens of microseconds. As a result, a complete catalytic cycle of HIV-1 protease or the assembly of lipid-protein mixtures could be investigated by CG-MD to gain biological insights. In this review, we survey the theories developed in recent years, which are categorized into Folding-based and Molecular-Mechanics-based. In addition, physical bases in the selection of CG beads/time-step, the choice of effective potentials, representation of solvent, and restoration of molecular representations back to their atomic details are systematically discussed. PMID:19812774
NASA Astrophysics Data System (ADS)
Vemareddy, P.; Demóulin, P.
2018-04-01
We study the magnetic structure of a successively erupting sigmoid in active region 12371 by modeling the quasi-static coronal field evolution with nonlinear force-free field (NLFFF) equilibria. Helioseismic and Magnetic Imager/Solar Dynamic Observatory vector magnetograms are used as input to the NLFFF model. In all eruption events, the modeled structure resembles the observed pre-eruptive coronal sigmoid and the NLFFF core field is a combination of double inverse-J-shaped and inverse-S field lines with dips touching the photosphere. Such field lines are formed by the flux cancellation reconnection of opposite-J field lines at bald-patch locations, which in turn implies the formation of a weakly twisted flux-rope (FR) from large-scale sheared arcade field lines. Later on, this FR undergoes coronal tether-cutting reconnection until a coronal mass ejection is triggered. The modeled structure captured these major features of sigmoid-to-arcade-to-sigmoid transformation, which is reoccuring under continuous photospheric flux motions. Calculations of the field line twist reveal a fractional increase followed by a decrease of the number of pixels having a range of twist. This traces the buildup process of a twisted core field by slow photospheric motions and the relaxation after eruption, respectively. Our study infers that the large eruptivity of this AR is due to a steep decrease of the background coronal field meeting the torus instability criteria at a low height (≈40 Mm) in contrast to noneruptive ARs.
Tectonic plates, D (double prime) thermal structure, and the nature of mantle plumes
NASA Technical Reports Server (NTRS)
Lenardic, A.; Kaula, W. M.
1994-01-01
It is proposed that subducting tectonic plates can affect the nature of thermal mantle plumes by determining the temperature drop across a plume source layer. The temperature drop affects source layer stability and the morphology of plumes emitted from it. Numerical models are presented to demonstrate how introduction of platelike behavior in a convecting temperature dependent medium, driven by a combination of internal and basal heating, can increase the temperature drop across the lower boundary layer. The temperature drop increases dramatically following introduction of platelike behavior due to formation of a cold temperature inversion above the lower boundary layer. This thermal inversion, induced by deposition of upper boundary layer material to the system base, decays in time, but the temperature drop across the lower boundary layer always remains considerably higher than in models lacking platelike behavior. On the basis of model-inferred boundary layer temperature drops and previous studies of plume dynamics, we argue that generally accepted notions as to the nature of mantle plumes on Earth may hinge on the presence of plates. The implication for Mars and Venus, planets apparently lacking plate tectonics, is that mantle plumes of these planets may differ morphologically from those of Earth. A corollary model-based argument is that as a result of slab-induced thermal inversions above the core mantle boundary the lower most mantle may be subadiabatic, on average (in space and time), if major plate reorganization timescales are less than those acquired to diffuse newly deposited slab material.
Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle
NASA Technical Reports Server (NTRS)
Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.
2005-01-01
This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.
NASA Astrophysics Data System (ADS)
Gao, Ji; Zhang, Haijiang
2018-05-01
Cross-gradient joint inversion that enforces structural similarity between different models has been widely utilized in jointly inverting different geophysical data types. However, it is a challenge to combine different geophysical inversion systems with the cross-gradient structural constraint into one joint inversion system because they may differ greatly in the model representation, forward modelling and inversion algorithm. Here we propose a new joint inversion strategy that can avoid this issue. Different models are separately inverted using the existing inversion packages and model structure similarity is only enforced through cross-gradient minimization between two models after each iteration. Although the data fitting and structural similarity enforcing processes are decoupled, our proposed strategy is still able to choose appropriate models to balance the trade-off between geophysical data fitting and structural similarity. This is realized by using model perturbations from separate data inversions to constrain the cross-gradient minimization process. We have tested this new strategy on 2-D cross borehole synthetic seismic traveltime and DC resistivity data sets. Compared to separate geophysical inversions, our proposed joint inversion strategy fits the separate data sets at comparable levels while at the same time resulting in a higher structural similarity between the velocity and resistivity models.
Numerical Modeling in Geodynamics: Success, Failure and Perspective
NASA Astrophysics Data System (ADS)
Ismail-Zadeh, A.
2005-12-01
A real success in numerical modeling of dynamics of the Earth can be achieved only by multidisciplinary research teams of experts in geodynamics, applied and pure mathematics, and computer science. The success in numerical modeling is based on the following basic, but simple, rules. (i) People need simplicity most, but they understand intricacies best (B. Pasternak, writer). Start from a simple numerical model, which describes basic physical laws by a set of mathematical equations, and move then to a complex model. Never start from a complex model, because you cannot understand the contribution of each term of the equations to the modeled geophysical phenomenon. (ii) Study the numerical methods behind your computer code. Otherwise it becomes difficult to distinguish true and erroneous solutions to the geodynamic problem, especially when your problem is complex enough. (iii) Test your model versus analytical and asymptotic solutions, simple 2D and 3D model examples. Develop benchmark analysis of different numerical codes and compare numerical results with laboratory experiments. Remember that the numerical tool you employ is not perfect, and there are small bugs in every computer code. Therefore the testing is the most important part of your numerical modeling. (iv) Prove (if possible) or learn relevant statements concerning the existence, uniqueness and stability of the solution to the mathematical and discrete problems. Otherwise you can solve an improperly-posed problem, and the results of the modeling will be far from the true solution of your model problem. (v) Try to analyze numerical models of a geological phenomenon using as less as possible tuning model variables. Already two tuning variables give enough possibilities to constrain your model well enough with respect to observations. The data fitting sometimes is quite attractive and can take you far from a principal aim of your numerical modeling: to understand geophysical phenomena. (vi) If the number of tuning model variables are greater than two, test carefully the effect of each of the variables on the modeled phenomenon. Remember: With four exponents I can fit an elephant (E. Fermi, physicist). (vii) Make your numerical model as accurate as possible, but never put the aim to reach a great accuracy: Undue precision of computations is the first symptom of mathematical illiteracy (N. Krylov, mathematician). How complex should be a numerical model? A model which images any detail of the reality is as useful as a map of scale 1:1 (J. Robinson, economist). This message is quite important for geoscientists, who study numerical models of complex geodynamical processes. I believe that geoscientists will never create a model of the real Earth dynamics, but we should try to model the dynamics such a way to simulate basic geophysical processes and phenomena. Does a particular model have a predictive power? Each numerical model has a predictive power, otherwise the model is useless. The predictability of the model varies with its complexity. Remember that a solution to the numerical model is an approximate solution to the equations, which have been chosen in believe that they describe dynamic processes of the Earth. Hence a numerical model predicts dynamics of the Earth as well as the mathematical equations describe this dynamics. What methodological advances are still needed for testable geodynamic modeling? Inverse (time-reverse) numerical modeling and data assimilation are new methodologies in geodynamics. The inverse modeling can allow to test geodynamic models forward in time using restored (from present-day observations) initial conditions instead of unknown conditions.
Inverse Problems for Nonlinear Delay Systems
2011-03-15
population dynamics. We consider the delay between birth and adulthood for neonate pea aphids and present a mathematical model that treats this delay as...which there is currently no known cure. For HIV, the core of the virus is composed of single-stranded viral RNA and protein components. As depicted in...at a CD4 receptor site and the viral core is injected into the cell. Once inside, the protein components enable transcription and integration of the
Voxel inversion of airborne electromagnetic data for improved model integration
NASA Astrophysics Data System (ADS)
Fiandaca, Gianluca; Auken, Esben; Kirkegaard, Casper; Vest Christiansen, Anders
2014-05-01
Inversion of electromagnetic data has migrated from single site interpretations to inversions including entire surveys using spatial constraints to obtain geologically reasonable results. Though, the model space is usually linked to the actual observation points. For airborne electromagnetic (AEM) surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space, and the geophysical information has to be relocated for integration in (hydro)geological models. We have developed a new geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the soil properties is computed everywhere by means of an interpolation function (e.g. inverse distance or kriging). Given this definition of the voxel model space, the 1D forward responses of the AEM data are computed as follows: 1) a 1D model subdivision, in terms of model thicknesses, is defined for each 1D data set, creating "virtual" layers. 2) the "virtual" 1D models at the sounding positions are finalized by interpolating the soil properties (the resistivity) in the center of the "virtual" layers. 3) the forward response is computed in 1D for each "virtual" model. We tested the new inversion scheme on an AEM survey carried out with the SkyTEM system close to Odder, in Denmark. The survey comprises 106054 dual mode AEM soundings, and covers an area of approximately 13 km X 16 km. The voxel inversion was carried out on a structured grid of 260 X 325 X 29 xyz nodes (50 m xy spacing), for a total of 2450500 inversion parameters. A classical spatially constrained inversion (SCI) was carried out on the same data set, using 106054 spatially constrained 1D models with 29 layers. For comparison, the SCI inversion models have been gridded on the same grid of the voxel inversion. The new voxel inversion and the classic SCI give similar data fit and inversion models. The voxel inversion decouples the geophysical model from the position of acquired data, and at the same time fits the data as well as the classic SCI inversion. Compared to the classic approach, the voxel inversion is better suited for informing directly (hydro)geological models and for sequential/Joint/Coupled (hydro)geological inversion. We believe that this new approach will facilitate the integration of geophysics, geology and hydrology for improved groundwater and environmental management.
Direct NOE simulation from long MD trajectories.
Chalmers, G; Glushka, J N; Foley, B L; Woods, R J; Prestegard, J H
2016-04-01
A software package, MD2NOE, is presented which calculates Nuclear Overhauser Effect (NOE) build-up curves directly from molecular dynamics (MD) trajectories. It differs from traditional approaches in that it calculates correlation functions directly from the trajectory instead of extracting inverse sixth power distance terms as an intermediate step in calculating NOEs. This is particularly important for molecules that sample conformational states on a timescale similar to molecular reorientation. The package is tested on sucrose and results are shown to differ in small but significant ways from those calculated using an inverse sixth power assumption. Results are also compared to experiment and found to be in reasonable agreement despite an expected underestimation of water viscosity by the water model selected. Copyright © 2016 Elsevier Inc. All rights reserved.
Inverse axial mounting stiffness design for lithographic projection lenses.
Wen-quan, Yuan; Hong-bo, Shang; Wei, Zhang
2014-09-01
In order to balance axial mounting stiffness of lithographic projection lenses and the image quality under dynamic working conditions, an easy inverse axial mounting stiffness design method is developed in this article. Imaging quality deterioration at the wafer under different axial vibration levels is analyzed. The desired image quality can be determined according to practical requirements, and axial vibrational tolerance of each lens is solved with the damped least-squares method. Based on adaptive interval adjustment, a binary search algorithm, and the finite element method, the axial mounting stiffness of each lens can be traveled in a large interval, and converges to a moderate numerical solution which makes the axial vibrational amplitude of the lens converge to its axial vibrational tolerance. Model simulation is carried out to validate the effectiveness of the method.
Inverse analysis of water profile in starch by non-contact photopyroelectric method
NASA Astrophysics Data System (ADS)
Frandas, A.; Duvaut, T.; Paris, D.
2000-07-01
The photopyroelectric (PPE) method in a non-contact configuration was proposed to study water migration in starch sheets used for biodegradable packaging. A 1-D theoretical model was developed, allowing the study of samples having a water profile characterized by an arbitrary continuous function. An experimental setup was designed or this purpose which included the choice of excitation source, detection of signals, signal and data processing, and cells for conditioning the samples. We report here the development of an inversion procedure allowing for the determination of the parameters that influence the PPE signal. This procedure led to the optimization of experimental conditions in order to identify the parameters related to the water profile in the sample, and to monitor the dynamics of the process.
Development of force adaptation during childhood.
Konczak, Jürgen; Jansen-Osmann, Petra; Kalveram, Karl-Theodor
2003-03-01
Humans learn to make reaching movements in novel dynamic environments by acquiring an internal motor model of their limb dynamics. Here, the authors investigated how 4- to 11-year-old children (N = 39) and adults (N = 7) adapted to changes in arm dynamics, and they examined whether those data support the view that the human brain acquires inverse dynamics models (IDM) during development. While external damping forces were applied, the children learned to perform goal-directed forearm flexion movements. After changes in damping, all children showed kinematic aftereffects indicative of a neural controller that still attempted to compensate the no longer existing damping force. With increasing age, the number of trials toward complete adaptation decreased. When damping was present, forearm paths were most perturbed and most variable in the youngest children but were improved in the older children. The findings indicate that the neural representations of limb dynamics are less precise in children and less stable in time than those of adults. Such controller instability might be a primary cause of the high kinematic variability observed in many motor tasks during childhood. Finally, the young children were not able to update those models at the same rate as the older children, who, in turn, adapted more slowly than adults. In conclusion, the ability to adapt to unknown forces is a developmental achievement. The present results are consistent with the view that the acquisition and modification of internal models of the limb dynamics form the basis of that adaptive process.
Retrodicting the Cenozoic evolution of the mantle: Implications for dynamic surface topography
NASA Astrophysics Data System (ADS)
Glišović, Petar; Forte, Alessandro; Rowley, David; Simmons, Nathan; Grand, Stephen
2014-05-01
Seismic tomography is the essential starting ingredient for constructing realistic models of the mantle convective flow and for successfully predicting a wide range of convection-related surface observables. However, the lack of knowledge of the initial thermal state of the mantle in the geological past is still an outstanding problem in mantle convection. The resolution of this problem requires models of 3-D mantle evolution that yield maximum consistency with a wide suite of geophysical constraints. Quantifying the robustness of the reconstructed thermal evolution is another major concern. We have carried out mantle dynamic simulations (Glišović & Forte, EPSL 2014) using a pseudo-spectral solution for compressible-flow thermal convection in 3-D spectral geometry that directly incorporate: 1) joint seismic-geodynamic inversions of mantle density structure with constraints provided by mineral physics data (Simmons et al., GJI 2009); and 2) constraints on mantle viscosity inferred by inversion of a suite of convection-related and glacial isostatic adjustment data sets (Mitrovica & Forte, EPSL 2004) characterised by Earth-like Rayleigh numbers. These time-reversed convection simulations reveal how the buoyancy associated with hot, active upwellings is a major driver of the mantle-wide convective circulation and the changes in dynamic topography at the Earth's surface. These simulations reveal, for example, a stable and long-lived superplume under the East Pacific Rise (centred under the Easter and Pitcairn hotspots) that was previously identified by Rowley et al. (AGU 2011, Nature in review) on the basis of plate kinematic data. We also present 65 Myr reconstructions of the Reunion plume that gave rise to the Deccan Traps.