Evolution and selection of river networks: Statics, dynamics, and complexity

PubMed Central

Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R.; Maritan, Amos; Rodriguez-Iturbe, Ignacio

2014-01-01

Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics—every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept. PMID:24550264

Dynamic programming and graph algorithms in computer vision.

PubMed

Felzenszwalb, Pedro F; Zabih, Ramin

2011-04-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting since, by carefully exploiting problem structure, they often provide nontrivial guarantees concerning solution quality. In this paper, we review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo, the mid-level problem of interactive object segmentation, and the high-level problem of model-based recognition.

A COMPARISON OF STATIC AND DYNAMIC OPTIMIZATION MUSCLE FORCE PREDICTIONS DURING WHEELCHAIR PROPULSION

PubMed Central

Morrow, Melissa M.; Rankin, Jeffery W.; Neptune, Richard R.; Kaufman, Kenton R.

2014-01-01

The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4 % Fmax error in the middle deltoid) to good (6.4 % Fmax error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation-supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction. PMID:25282075

Real-time high dynamic range laser scanning microscopy

NASA Astrophysics Data System (ADS)

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-04-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Optimizing Floating Guard Ring Designs for FASPAX N-in-P Silicon Sensors

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

Shin, Kyung-Wook; Bradford, Robert; Lipton, Ronald

2016-10-06

FASPAX (Fermi-Argonne Semiconducting Pixel Array X-ray detector) is being developed as a fast integrating area detector with wide dynamic range for time resolved applications at the upgraded Advanced Photon Source (APS.) A burst mode detector with intendedmore » $$\\mbox{13 $$MHz$}$ image rate, FASPAX will also incorporate a novel integration circuit to achieve wide dynamic range, from single photon sensitivity to $$10^{\\text{5}}$$ x-rays/pixel/pulse. To achieve these ambitious goals, a novel silicon sensor design is required. This paper will detail early design of the FASPAX sensor. Results from TCAD optimization studies, and characterization of prototype sensors will be presented.« less

Dynamic tuning of chemiresistor sensitivity using mechanical strain

DOEpatents

Martin, James E; Read, Douglas H

2014-09-30

The sensitivity of a chemiresistor sensor can be dynamically tuned using mechanical strain. The increase in sensitivity is a smooth, continuous function of the applied strain, and the effect can be reversible. Sensitivity tuning enables the response curve of the sensor to be dynamically optimized for sensing analytes, such as volatile organic compounds, over a wide concentration range.

Multi-objective design optimization and control of magnetorheological fluid brakes for automotive applications

NASA Astrophysics Data System (ADS)

Shamieh, Hadi; Sedaghati, Ramin

2017-12-01

The magnetorheological brake (MRB) is an electromechanical device that generates a retarding torque through employing magnetorheological (MR) fluids. The objective of this paper is to design, optimize and control an MRB for automotive applications considering. The dynamic range of a disk-type MRB expressing the ratio of generated toque at on and off states has been formulated as a function of the rotational speed, geometrical and material properties, and applied electrical current. Analytical magnetic circuit analysis has been conducted to derive the relation between magnetic field intensity and the applied electrical current as a function of the MRB geometrical and material properties. A multidisciplinary design optimization problem has then been formulated to identify the optimal brake geometrical parameters to maximize the dynamic range and minimize the response time and weight of the MRB under weight, size and magnetic flux density constraints. The optimization problem has been solved using combined genetic and sequential quadratic programming algorithms. Finally, the performance of the optimally designed MRB has been investigated in a quarter vehicle model. A PID controller has been designed to regulate the applied current required by the MRB in order to improve vehicle’s slipping on different road conditions.

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

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

Liu, Guodong; Li, Zhi; Starke, Michael R.

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintainingmore » the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.« less

The consequences of neural degeneration regarding optimal cochlear implant position in scala tympani: a model approach.

PubMed

Briaire, Jeroen J; Frijns, Johan H M

2006-04-01

Cochlear implant research endeavors to optimize the spatial selectivity, threshold and dynamic range with the objective of improving the speech perception performance of the implant user. One of the ways to achieve some of these goals is by electrode design. New cochlear implant electrode designs strive to bring the electrode contacts into close proximity to the nerve fibers in the modiolus: this is done by placing the contacts on the medial side of the array and positioning the implant against the medial wall of scala tympani. The question remains whether this is the optimal position for a cochlea with intact neural fibers and, if so, whether it is also true for a cochlea with degenerated neural fibers. In this study a computational model of the implanted human cochlea is used to investigate the optimal position of the array with respect to threshold, dynamic range and spatial selectivity for a cochlea with intact nerve fibers and for degenerated nerve fibers. In addition, the model is used to evaluate the predictive value of eCAP measurements for obtaining peri-operative information on the neural status. The model predicts improved threshold, dynamic range and spatial selectivity for the peri-modiolar position at the basal end of the cochlea, with minimal influence of neural degeneration. At the apical end of the array (1.5 cochlear turns), the dynamic range and the spatial selectivity are limited due to the occurrence of cross-turn stimulation, with the exception of the condition without neural degeneration and with the electrode array along the lateral wall of scala tympani. The eCAP simulations indicate that a large P(0) peak occurs before the N(1)P(1) complex when the fibers are not degenerated. The absence of this peak might be used as an indicator for neural degeneration.

Optimal control of multiphoton ionization dynamics of small alkali aggregates

NASA Astrophysics Data System (ADS)

Lindinger, A.; Bartelt, A.; Lupulescu, C.; Vajda, S.; Woste, Ludger

2003-11-01

We have performed transient multi-photon ionization experiments on small alkali clusters of different size in order to probe their wave packet dynamics, structural reorientations, charge transfers and dissociative events in different vibrationally excited electronic states including their ground state. The observed processes were highly dependent on the irradiated pulse parameters like wavelength range or its phase and amplitude; an emphasis to employ a feedback control system for generating the optimum pulse shapes. Their spectral and temporal behavior reflects interesting properties about the investigated system and the irradiated photo-chemical process. First, we present the vibrational dynamics of bound electronically excited states of alkali dimers and trimers. The scheme for observing the wave packet dynamics in the electronic ground state using stimulated Raman-pumping is shown. Since the employed pulse parameters significantly influence the efficiency of the irradiated dynamic pathways photo-induced ioniziation experiments were carried out. The controllability of 3-photon ionization pathways is investigated on the model-like systems NaK and K2. A closed learning loop for adaptive feedback control is used to find the optimal fs pulse shape. Sinusoidal parameterizations of the spectral phase modulation are investigated in regard to the obtained optimal field. By reducing the number of parameters and thereby the complexity of the phase moduation, optimal pulse shapes can be generated that carry fingerprints of the molecule's dynamical properties. This enables to find "understandable" optimal pulse forms and offers the possiblity to gain insight into the photo-induced control process. Characteristic motions of the involved wave packets are proposed to explain the optimized dynamic dissociation pathways.

Backward bifurcation and optimal control of Plasmodium Knowlesi malaria

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini

2014-07-01

A deterministic model for the transmission dynamics of Plasmodium Knowlesi malaria with direct transmission is developed. The model is analyzed using dynamical system techniques and it shows that the backward bifurcation occurs for some range of parameters. The model is extended to assess the impact of time dependent preventive (biological and chemical control) against the mosquitoes and vaccination for susceptible humans, while treatment for infected humans. The existence of optimal control is established analytically by the use of optimal control theory. Numerical simulations of the problem, suggest that applying the four control measure can effectively reduce if not eliminate the spread of Plasmodium Knowlesi in a community.

Dynamic Programming and Graph Algorithms in Computer Vision*

PubMed Central

Felzenszwalb, Pedro F.; Zabih, Ramin

2013-01-01

Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950

Real-time high dynamic range laser scanning microscopy

PubMed Central

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-01-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging. PMID:27032979

Modeling and Error Analysis of a Superconducting Gravity Gradiometer.

DTIC Science & Technology

1979-08-01

fundamental limit to instrument - -1- sensitivity is the thermal noise of the sensor . For the gradiometer design outlined above, the best sensitivity...Mapoles at Stanford. Chapter IV determines the relation between dynamic range, the sensor Q, and the thermal noise of the cryogenic accelerometer. An...C.1 Accelerometer Optimization (1) Development and optimization of the loaded diaphragm sensor . (2) Determination of the optimal values of the

Trajectory optimization study of a lifting body re-entry vehicle for medium to intermediate range applications

NASA Astrophysics Data System (ADS)

Rizvi, S. Tauqeer ul Islam; Linshu, He; ur Rehman, Tawfiq; Rafique, Amer Farhan

2012-11-01

A numerical optimization study of lifting body re-entry vehicles is presented for nominal as well as shallow entry conditions for Medium and Intermediate Range applications. Due to the stringent requirement of a high degree of accuracy for conventional vehicles, lifting re-entry can be used to attain the impact at the desired terminal flight path angle and speed and thus can potentially improve accuracy of the re-entry vehicle. The re-entry of a medium range and intermediate range vehicles is characterized by very high negative flight path angle and low re-entry speed as compared to a maneuverable re-entry vehicle or a common aero vehicle intended for an intercontinental range. Highly negative flight path angles at the re-entry impose high dynamic pressure as well as heat loads on the vehicle. The trajectory studies are carried out to maximize the cross range of the re-entry vehicle while imposing a maximum dynamic pressure constraint of 350 KPa with a 3 MW/m2 heat rate limit. The maximum normal acceleration and the total heat load experienced by the vehicle at the stagnation point during the maneuver have been computed for the vehicle for possible future conceptual design studies. It has been found that cross range capability of up to 35 km can be achieved with a lifting-body design within the heat rate and the dynamic pressure boundary at normal entry conditions. For shallow entry angle of -20 degree and intermediate ranges a cross range capability of up to 250 km can be attained for a lifting body design with less than 10 percent loss in overall range. The normal acceleration also remains within limits. The lifting-body results have also been compared with wing-body results at shallow entry condition. An hp-adaptive pseudo-spectral method has been used for constrained trajectory optimization.

FIR Detector Sensitivity, Dynamic Range, and Multiplexing Requirements for the Origins Space Telescope (OST)

NASA Astrophysics Data System (ADS)

Staguhn, Johannes G.

2018-05-01

Spectroscopic, cold, space-based mid-to-far-infrared (FIR) missions, such as the Origins Space Telescope, will require large (tens of kilopixels), ultra-sensitive FIR detector arrays with sufficient dynamic range and high-density multiplexing schemes for the readout, in order to optimize the scientific return while staying within a realistic cost range. Issues like power consumption of multiplexers and their readout are significantly more important for space missions than they are for ground-based or suborbital applications. In terms of the detectors and their configuration into large arrays, significant development efforts are needed even for both of the most mature candidate superconducting detector technologies, namely transition edge sensors and (microwave) kinetic inductance detectors. Here we explore both practical and fundamental limits for those technologies in order to lay out a realistic path forward for both technologies. We conclude that beyond the need to enhance the detector sensitivities and pixel numbers by about an order of magnitude over currently existing devices, improved concepts for larger dynamic range and multiplexing density will be needed in order to optimize the scientific return of future cold FIR space missions. Background-limited, very high spectral resolution instruments will require photon-counting detectors.

Lewis Structures Technology, 1988. Volume 1: Structural Dynamics

NASA Technical Reports Server (NTRS)

1988-01-01

The specific purpose of the symposium was to familiarize the engineering structures community with the depth and range of research performed by the Structures Division of the Lewis Research Center and its academic and industrial partners. Sessions covered vibration control, fracture mechanics, ceramic component reliability, parallel computing, nondestructive testing, dynamical systems, fatigue and damage, wind turbines, hot section technology, structural mechanics codes, computational methods for dynamics, structural optimization, and applications of structural dynamics.

Insight into the Li2CO3-K2CO3 eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

NASA Astrophysics Data System (ADS)

Corradini, Dario; Coudert, François-Xavier; Vuilleumier, Rodolphe

2016-03-01

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li2CO3-K2CO3 (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900-1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture's self-diffusion coefficients, viscosity, and ionic conductivity.

Insight into the Li2CO3-K2CO3 eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics.

PubMed

Corradini, Dario; Coudert, François-Xavier; Vuilleumier, Rodolphe

2016-03-14

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li2CO3-K2CO3 (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900-1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, we present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture's self-diffusion coefficients, viscosity, and ionic conductivity.

Balancing on tightropes and slacklines

PubMed Central

Paoletti, P.; Mahadevan, L.

2012-01-01

Balancing on a tightrope or a slackline is an example of a neuromechanical task where the whole body both drives and responds to the dynamics of the external environment, often on multiple timescales. Motivated by a range of neurophysiological observations, here we formulate a minimal model for this system and use optimal control theory to design a strategy for maintaining an upright position. Our analysis of the open and closed-loop dynamics shows the existence of an optimal rope sag where balancing requires minimal effort, consistent with qualitative observations and suggestive of strategies for optimizing balancing performance while standing and walking. Our consideration of the effects of nonlinearities, potential parameter coupling and delays on the overall performance shows that although these factors change the results quantitatively, the existence of an optimal strategy persists. PMID:22513724

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

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

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE PAGES

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu; ...

2017-10-10

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Combined Optimal Control System for excavator electric drive

NASA Astrophysics Data System (ADS)

Kurochkin, N. S.; Kochetkov, V. P.; Platonova, E. V.; Glushkin, E. Y.; Dulesov, A. S.

2018-03-01

The article presents a synthesis of the combined optimal control algorithms of the AC drive rotation mechanism of the excavator. Synthesis of algorithms consists in the regulation of external coordinates - based on the theory of optimal systems and correction of the internal coordinates electric drive using the method "technical optimum". The research shows the advantage of optimal combined control systems for the electric rotary drive over classical systems of subordinate regulation. The paper presents a method for selecting the optimality criterion of coefficients to find the intersection of the range of permissible values of the coordinates of the control object. There is possibility of system settings by choosing the optimality criterion coefficients, which allows one to select the required characteristics of the drive: the dynamic moment (M) and the time of the transient process (tpp). Due to the use of combined optimal control systems, it was possible to significantly reduce the maximum value of the dynamic moment (M) and at the same time - reduce the transient time (tpp).

Energy management during the space shuttle transition

NASA Technical Reports Server (NTRS)

Stengel, R. F.

1972-01-01

An approach to calculating optimal, gliding flight paths of the type associated with the space shuttle's transition from entry to cruising flight is presented. Kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations, reducing the dimension and complexity of the problem. The capability for treating integral and terminal penalties (as well as Mach number effects) is retained in the numerical optimization; hence, stability and control boundaries can be observed as trajectories to the desired final energy, flight path angle, and range are determined. Numerical results show that the jump to the front-side of the L/D curve need not be made until the end of the transition and that the dynamic model provides a conservative range estimate. Alternatives for real time trajectory control are discussed.

Synthesis of Conformal Phased Antenna Arrays With A Novel Multiobjective Invasive Weed Optimization Algorithm

NASA Astrophysics Data System (ADS)

Li, Wen Tao; Hei, Yong Qiang; Shi, Xiao Wei

2018-04-01

By virtue of the excellent aerodynamic performances, conformal phased arrays have been attracting considerable attention. However, for the synthesis of patterns with low/ultra-low sidelobes of the conventional conformal arrays, the obtained dynamic range ratios of amplitude excitations could be quite high, which results in stringent requirements on various error tolerances for practical implementation. Time-modulated array (TMA) has the advantages of low sidelobe and reduced dynamic range ratio requirement of amplitude excitations. This paper takes full advantages of conformal antenna arrays and time-modulated arrays. The active-element-pattern, including element mutual coupling and platform effects, is employed in the whole design process. To optimize the pulse durations and the switch-on instants of the time-modulated elements, multiobjective invasive weed optimization (MOIWO) algorithm based on the nondominated sorting of the solutions is proposed. A S-band 8-element cylindrical conformal array is designed and a S-band 16-element cylindrical-parabolic conformal array is constructed and tested at two different steering angles.

Shape optimization of an autonomous underwater vehicle with a ducted propeller using computational fluid dynamics analysis

NASA Astrophysics Data System (ADS)

Joung, Tae-Hwan; Sammut, Karl; He, Fangpo; Lee, Seung-Keon

2012-03-01

Autonomous Underwater Vehicles (AUVs) provide a useful means of collecting detailed oceano-graphic information. The hull resistance of an AUV is an important factor in determining the power requirements and range of the vehicle. This paper describes a procedure using Computational Fluid Dynamics (CFD) for determining the hull resistance of an AUV under development, for a given propeller rotation speed and within a given range of AUV velocities. The CFD analysis results reveal the distribution of the hydrodynamic values (velocity, pressure, etc.) around the AUV hull and its ducted propeller. The paper then proceeds to present a methodology for optimizing the AUV profile in order to reduce the total resistance. This paper demonstrates that shape optimization of conceptual designs is possible using the commercial CFD package contained in Ansys™. The optimum design to minimize the drag force of the AUV was identified for a given object function and a set of constrained design parameters

Optimal deployment of resources for maximizing impact in spreading processes

PubMed Central

2017-01-01

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distribution of available resources hence results from an interplay between network topology and spreading dynamics. We show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples. PMID:28900013

The importance of functional form in optimal control solutions of problems in population dynamics

USGS Publications Warehouse

Runge, M.C.; Johnson, F.A.

2002-01-01

Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood profile may end up producing alternatives that do not differ as importantly as if different functional forms had been used. We recommend that biological knowledge be used to bracket a range of possible functional forms, and robustness of conclusions be checked over this range.

VEDA: a web-based virtual environment for dynamic atomic force microscopy.

PubMed

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

Invited Article: VEDA: A web-based virtual environment for dynamic atomic force microscopy

NASA Astrophysics Data System (ADS)

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

Optimal guidance for the space shuttle transition

NASA Technical Reports Server (NTRS)

Stengel, R. F.

1972-01-01

A guidance method for the space shuttle's transition from hypersonic entry to subsonic cruising flight is presented. The method evolves from a numerical trajectory optimization technique in which kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations. This allows the open end-time problem to be transformed to one of fixed terminal energy. In its ultimate form, E-Guidance obtains energy balance (including dynamic-pressure-rate damping) and path length control by angle-of-attack modulation and cross-range control by roll angle modulation. The guidance functions also form the basis for a pilot display of instantaneous maneuver limits and destination. Numerical results illustrate the E-Guidance concept and the optimal trajectories on which it is based.

Lewis Structures Technology, 1988. Volume 2: Structural Mechanics

NASA Technical Reports Server (NTRS)

1988-01-01

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

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

PubMed

Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

PubMed Central

2011-01-01

Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology. PMID:21989196

The forest and agricultural sector optimization model (FASOM): model structure and policy applications.

Treesearch

Darius M. Adams; Ralph J. Alig; J.M. Callaway; Bruce A. McCarl; Steven M. Winnett

1996-01-01

The Forest and Agricultural Sector Optimization Model (FASOM) is a dynamic, nonlinear programming model of the forest and agricultural sectors in the United States. The FASOM model initially was developed to evaluate welfare and market impacts of alternative policies for sequestering carbon in trees but also has been applied to a wider range of forest and agricultural...

Single-shot measurement of >1010 pulse contrast for ultra-high peak-power lasers

NASA Astrophysics Data System (ADS)

Wang, Yongzhi; Ma, Jingui; Wang, Jing; Yuan, Peng; Xie, Guoqiang; Ge, Xulei; Liu, Feng; Yuan, Xiaohui; Zhu, Heyuan; Qian, Liejia

2014-01-01

Real-time pulse-contrast observation with a high dynamic range is a prerequisite to tackle the contrast challenge in ultra-high peak-power lasers. However, the commonly used delay-scanning cross-correlator (DSCC) can only provide the time-consumed measurements for repetitive lasers. Single-shot cross-correlator (SSCC) becomes essential in optimizing laser systems and exploring contrast mechanisms. Here we report our progress in developing SSCC towards its practical use. By integrating both the techniques of scattering-noise reduction and sensitive parallel detection into SSCC, we demonstrate a high dynamic range of >1010, which, to our best knowledge, is the first demonstration of an SSCC with a dynamic range comparable to that of commercial DSCCs. The comparison of high-dynamic measurement performances between SSCC and a standard DSCC (Sequoia, Amplitude Technologies) is also carried out on a 200 TW Ti:sapphire laser, and the consistency of results verifies the veracity of our SSCC.

Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors.

PubMed

Mannan, Ahmad A; Liu, Di; Zhang, Fuzhong; Oyarzún, Diego A

2017-10-20

Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.

Dynamic range adaptation in primary motor cortical populations

PubMed Central

Rasmussen, Robert G; Schwartz, Andrew; Chase, Steven M

2017-01-01

Neural populations from various sensory regions demonstrate dynamic range adaptation in response to changes in the statistical distribution of their input stimuli. These adaptations help optimize the transmission of information about sensory inputs. Here, we show a similar effect in the firing rates of primary motor cortical cells. We trained monkeys to operate a brain-computer interface in both two- and three-dimensional virtual environments. We found that neurons in primary motor cortex exhibited a change in the amplitude of their directional tuning curves between the two tasks. We then leveraged the simultaneous nature of the recordings to test several hypotheses about the population-based mechanisms driving these changes and found that the results are most consistent with dynamic range adaptation. Our results demonstrate that dynamic range adaptation is neither limited to sensory regions nor to rescaling of monotonic stimulus intensity tuning curves, but may rather represent a canonical feature of neural encoding. DOI: http://dx.doi.org/10.7554/eLife.21409.001 PMID:28417848

Insight into the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} eutectic mixture from classical molecular dynamics: Thermodynamics, structure, and dynamics

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

Corradini, Dario; Vuilleumier, Rodolphe, E-mail: rodolphe.vuilleumier@ens.fr; Sorbonne Universités, UPMC Univ. Paris 06, PASTEUR, 75005 Paris

We use molecular dynamics simulations to study the thermodynamics, structure, and dynamics of the Li{sub 2}CO{sub 3}–K{sub 2}CO{sub 3} (62:38 mol. %) eutectic mixture. We present a new classical non-polarizable force field for this molten salt mixture, optimized using experimental and first principles molecular dynamics simulations data as reference. This simple force field allows efficient molecular simulations of phenomena at long time scales. We use this optimized force field to describe the behavior of the eutectic mixture in the 900–1100 K temperature range, at pressures between 0 and 5 GPa. After studying the equation of state in these thermodynamic conditions, wemore » present molecular insight into the structure and dynamics of the melt. In particular, we present an analysis of the temperature and pressure dependence of the eutectic mixture’s self-diffusion coefficients, viscosity, and ionic conductivity.« less

L10-MnGa based magnetic tunnel junction for high magnetic field sensor

NASA Astrophysics Data System (ADS)

Zhao, X. P.; Lu, J.; Mao, S. W.; Yu, Z. F.; Wang, H. L.; Wang, X. L.; Wei, D. H.; Zhao, J. H.

2017-07-01

We report on the investigation of the magnetic tunnel junction structure designed for high magnetic field sensors with a perpendicularly magnetized L10-MnGa reference layer and an in-plane magnetized Fe sensing layer. A large linear tunneling magnetoresistance ratio up to 27.4% and huge dynamic range up to 5600 Oe have been observed at 300 K, with a low nonlinearity of 0.23% in the optimized magnetic tunnel junction (MTJ). The field response of tunneling magnetoresistance is discussed to explain the field sensing properties in the dynamic range. These results indicate that L10-MnGa based orthogonal MTJ is a promising candidate for a high performance magnetic field sensor with a large dynamic range, high endurance and low power consumption.

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

NASA Astrophysics Data System (ADS)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

Optimization of Dynamic Aperture of PEP-X Baseline Design

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

Wang, Min-Huey; /SLAC; Cai, Yunhai

2010-08-23

SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-{angstrom} x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. Themore » latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.« less

A common optimization principle for motor execution in healthy subjects and parkinsonian patients.

PubMed

Baraduc, Pierre; Thobois, Stéphane; Gan, Jing; Broussolle, Emmanuel; Desmurget, Michel

2013-01-09

Recent research on Parkinson's disease (PD) has emphasized that parkinsonian movement, although bradykinetic, shares many attributes with healthy behavior. This observation led to the suggestion that bradykinesia in PD could be due to a reduction in motor motivation. This hypothesis can be tested in the framework of optimal control theory, which accounts for many characteristics of healthy human movement while providing a link between the motor behavior and a cost/benefit trade-off. This approach offers the opportunity to interpret movement deficits of PD patients in the light of a computational theory of normal motor control. We studied 14 PD patients with bilateral subthalamic nucleus (STN) stimulation and 16 age-matched healthy controls, and tested whether reaching movements were governed by similar rules in these two groups. A single optimal control model accounted for the reaching movements of healthy subjects and PD patients, whatever the condition of STN stimulation (on or off). The choice of movement speed was explained in all subjects by the existence of a preset dynamic range for the motor signals. This range was idiosyncratic and applied to all movements regardless of their amplitude. In PD patients this dynamic range was abnormally narrow and correlated with bradykinesia. STN stimulation reduced bradykinesia and widened this range in all patients, but did not restore it to a normal value. These results, consistent with the motor motivation hypothesis, suggest that constrained optimization of motor effort is the main determinant of movement planning (choice of speed) and movement production, in both healthy and PD subjects.

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Multi exposure image fusion algorithm based on YCbCr space

NASA Astrophysics Data System (ADS)

Yang, T. T.; Fang, P. Y.

2018-05-01

To solve the problem that scene details and visual effects are difficult to be optimized in high dynamic image synthesis, we proposes a multi exposure image fusion algorithm for processing low dynamic range images in YCbCr space, and weighted blending of luminance and chromatic aberration components respectively. The experimental results show that the method can retain color effect of the fused image while balancing details of the bright and dark regions of the high dynamic image.

Design optimization for 25 Gbit/s DML InGaAlAs/InGaAsP/InP SL-MQW laser diode incorporating temperature effect

NASA Astrophysics Data System (ADS)

Ke, Cheng; Li, Xun; Xi, Yanping; Yu, Yang

2017-11-01

In this paper, a detailed carrier dynamics model for quantum well lasers is used to study the modulation bandwidth of the directly modulated strained-layer multiple quantum well (SL-MQW) laser. The active region of the directly modulated laser (DML) is optimized in terms of the number of QWs and barrier height. To compromise the device dynamic performance at different operating temperatures, we present an overall optimized design for a 25 Gbps DML under an ambient temperature ranging from 25 to 85°C. To further enhance the modulation bandwidth, we have also proposed a mixed QWs design that increases the 3 dB bandwidth by almost 44% compared to the one without undergoing optimization. The experimental results show that the 3 dB bandwidth of the optimized DML can reach 19 GHz. A clear eye diagram with a bit rate of 25 Gbps was observed at 25°C.

Mutually beneficial relationship in optimization between search-space smoothing and stochastic search

NASA Astrophysics Data System (ADS)

Hasegawa, Manabu; Hiramatsu, Kotaro

2013-10-01

The effectiveness of the Metropolis algorithm (MA) (constant-temperature simulated annealing) in optimization by the method of search-space smoothing (SSS) (potential smoothing) is studied on two types of random traveling salesman problems. The optimization mechanism of this hybrid approach (MASSS) is investigated by analyzing the exploration dynamics observed in the rugged landscape of the cost function (energy surface). The results show that the MA can be successfully utilized as a local search algorithm in the SSS approach. It is also clarified that the optimization characteristics of these two constituent methods are improved in a mutually beneficial manner in the MASSS run. Specifically, the relaxation dynamics generated by employing the MA work effectively even in a smoothed landscape and more advantage is taken of the guiding function proposed in the idea of SSS; this mechanism operates in an adaptive manner in the de-smoothing process and therefore the MASSS method maintains its optimization function over a wider temperature range than the MA.

The Dynamic Range Paradox: A Central Auditory Model of Intensity Change Detection

PubMed Central

Simpson, Andrew J.R.; Reiss, Joshua D.

2013-01-01

In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10−6). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND constant of 5.5×10−5 sones per ms. Through our findings, we argue that loudness reflects peripheral neural coding, and the intensity JND reflects central neural coding. PMID:23536749

Can Structural Optimization Explain Slow Dynamics of Rocks?

NASA Astrophysics Data System (ADS)

Kim, H.; Vistisen, O.; Tencate, J. A.

2009-12-01

Slow dynamics is a recovery process that describes the return to an equilibrium state after some external energy input is applied and then removed. Experimental studies on many rocks have shown that a modest acoustic energy input results in slow dynamics. The recovery process of the stiffness has consistently been found to be linear to log(time) for a wide range of geomaterials and the time constants appear to be unique to the material [TenCate JA, Shankland TJ (1996), Geophys Res Lett 23, 3019-3022]. Measurements of this nonequilibrium effect in rocks (e.g. sandstones and limestones) have been linked directly to the cement holding the individual grains together [Darling TW, TenCate JA, Brown DW, Clausen B, Vogel SC (2004), Geophys Res Lett 31, L16604], also suggesting a potential link to porosity and permeability. Noting that slow dynamics consistently returns the overall stiffness of rocks to its maximum (original) state, it is hypothesized that the original state represents the global minimum strain energy state. Consequently the slow dynamics process represents the global minimization or optimization process. Structural optimization, which has been developed for engineering design, minimises the total strain energy by rearranging the material distribution [Kim H, Querin OM, Steven GP, Xie YM (2002), Struct Multidiscip Optim 24, 441-448]. The optimization process effectively rearranges the way the material is cemented. One of the established global optimization methods is simulated annealing (SA). Derived from cooling of metal to a thermal equilibrium, SA finds an optimum solution by iteratively moving the system towards the minimum energy state with a probability of 'uphill' moves. It has been established that the global optimum can be guaranteed by applying a log(time) linear cooling schedule [Hajek B (1988, Math Ops Res, 15, 311-329]. This work presents the original study of applying SA to the maximum stiffness optimization problem. Preliminary results indicate that the maximum stiffness solutions are achieved when using log(time) linear cooling schedule. The optimization history reveals that the overall stiffness of the structure is increased linearly to log(time). The results closely resemble the slow dynamics stiffness recovery of geomaterials and support the hypothesis that the slow dynamics is an optimization process for strain energy. [Work supported by the Department of Energy through the LANL/LDRD Program].

Case study on impact performance optimization of hydraulic breakers.

PubMed

Noh, Dae-Kyung; Kang, Young-Ky; Cho, Jae-Sang; Jang, Joo-Sup

2016-01-01

In order to expand the range of activities of an excavator, attachments, such as hydraulic breakers have been developed to be applied to buckets. However, it is very difficult to predict the dynamic behavior of hydraulic impact devices such as breakers because of high non-linearity. Thus, the purpose of this study is to optimize the impact performance of hydraulic breakers. The ultimate goal of the optimization is to increase the impact energy and impact frequency and to reduce the pressure pulsation of the supply and return lines. The optimization results indicated that the four parameters used to optimize the impact performance of the breaker showed considerable improvement over the results reported in the literature. A test was also conducted and the results were compared with those obtained through optimization in order to verify the optimization results. The comparison showed an average relative error of 8.24 %, which seems to be in good agreement. The results of this study can be used to optimize the impact performance of hydraulic impact devices such as breakers, thus facilitating its application to excavators and increasing the range of activities of an excavator.

Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

NASA Astrophysics Data System (ADS)

Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

2017-10-01

A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

Sequential estimation and satellite data assimilation in meteorology and oceanography

NASA Technical Reports Server (NTRS)

Ghil, M.

1986-01-01

The central theme of this review article is the role that dynamics plays in estimating the state of the atmosphere and of the ocean from incomplete and noisy data. Objective analysis and inverse methods represent an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Four-dimensional data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric or oceanic model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and oceanic sciences, namely, mesoscale meteorology, medium and long-range forecasting, and upper-ocean dynamics.

Performance Optimization Design for a High-Speed Weak FBG Interrogation System Based on DFB Laser.

PubMed

Yao, Yiqiang; Li, Zhengying; Wang, Yiming; Liu, Siqi; Dai, Yutang; Gong, Jianmin; Wang, Lixin

2017-06-22

A performance optimization design for a high-speed fiber Bragg grating (FBG) interrogation system based on a high-speed distributed feedback (DFB) swept laser is proposed. A time-division-multiplexing sensor network with identical weak FBGs is constituted to realize high-capacity sensing. In order to further improve the multiplexing capacity, a waveform repairing algorithm is designed to extend the dynamic demodulation range of FBG sensors. It is based on the fact that the spectrum of an FBG keeps stable over a long period of time. Compared with the pre-collected spectra, the distorted spectra waveform are identified and repaired. Experimental results show that all the identical weak FBGs are distinguished and demodulated at the speed of 100 kHz with a linearity of above 0.99, and the range of dynamic demodulation is extended by 40%.

Performance Optimization Design for a High-Speed Weak FBG Interrogation System Based on DFB Laser

PubMed Central

Yao, Yiqiang; Li, Zhengying; Wang, Yiming; Liu, Siqi; Dai, Yutang; Gong, Jianmin; Wang, Lixin

2017-01-01

A performance optimization design for a high-speed fiber Bragg grating (FBG) interrogation system based on a high-speed distributed feedback (DFB) swept laser is proposed. A time-division-multiplexing sensor network with identical weak FBGs is constituted to realize high-capacity sensing. In order to further improve the multiplexing capacity, a waveform repairing algorithm is designed to extend the dynamic demodulation range of FBG sensors. It is based on the fact that the spectrum of an FBG keeps stable over a long period of time. Compared with the pre-collected spectra, the distorted spectra waveform are identified and repaired. Experimental results show that all the identical weak FBGs are distinguished and demodulated at the speed of 100 kHz with a linearity of above 0.99, and the range of dynamic demodulation is extended by 40%. PMID:28640187

Microhard MHX2420 Orbital Performance Evaluation Using RT Logic T400CS

NASA Technical Reports Server (NTRS)

TintoreGazulla, Oriol; Lombardi, Mark

2012-01-01

RT Logic allows simulation of Ground Station - satellite communications: Static tests have been successful. Dynamic tests have been performed for simple passes. Future dynamic tests are needed to simulate real orbit communications. Satellite attitude changes antenna gain. Atmospheric and rain losses need to be added. STK Plug-in will be the next step to improve the dynamic tests. There is a possibility of running longer simulations. Simulation of different losses available in the STK Plug-in. Microhard optimization: Effect of Microhard settings on the data throughput have been understood. Optimized settings improve data throughput for LEO communications. Longer hop intervals make transfer of larger packets more efficient (more time between hops in frequency). Use of FEC (Reed-Solomon) reduces the number of retransmissions for long-range or noisy communications.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. V.; Yerazunis, S. W.

1973-01-01

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

Optimal deployment of resources for maximizing impact in spreading processes

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

Lokhov, Andrey Y.; Saad, David

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distributionmore » of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.« less

Optimal deployment of resources for maximizing impact in spreading processes

DOE PAGES

Lokhov, Andrey Y.; Saad, David

2017-09-12

The effective use of limited resources for controlling spreading processes on networks is of prime significance in diverse contexts, ranging from the identification of “influential spreaders” for maximizing information dissemination and targeted interventions in regulatory networks, to the development of mitigation policies for infectious diseases and financial contagion in economic systems. Solutions for these optimization tasks that are based purely on topological arguments are not fully satisfactory; in realistic settings, the problem is often characterized by heterogeneous interactions and requires interventions in a dynamic fashion over a finite time window via a restricted set of controllable nodes. The optimal distributionmore » of available resources hence results from an interplay between network topology and spreading dynamics. Here, we show how these problems can be addressed as particular instances of a universal analytical framework based on a scalable dynamic message-passing approach and demonstrate the efficacy of the method on a variety of real-world examples.« less

Aeroelastic, CFD, and Dynamic Computation and Optimization for Buffet and Flutter Application

NASA Technical Reports Server (NTRS)

Kandil, Osama A.

1997-01-01

The work presented in this paper include: 'Coupled and Uncoupled Bending-Torsion Responses of Twin-Tail Buffet'; 'Fluid/Structure Twin Tail Buffet Response Over a Wide Range of Angles of Attack'; 'Resent Advances in Multidisciplinary Aeronautical Problems of Fluids/Structures/Dynamics Interaction'; and'Development of a Coupled Fluid/Structure Aeroelastic Solver with Applications to Vortex Breakdown induced Twin Tail Buffeting.

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 1

NASA Technical Reports Server (NTRS)

Woodrow Whitlow, Jr. (Editor); Todd, Emily N. (Editor)

1999-01-01

These proceedings represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Design of a secondary ionization target for direct production of a C- beam from CO2 pulses for online AMS.

PubMed

Salazar, Gary; Ognibene, Ted

2013-01-01

We designed and optimized a novel device "target" that directs a CO 2 gas pulse onto a Ti surface where a Cs + beam generates C - from the CO 2 . This secondary ionization target enables an accelerator mass spectrometer to ionize pulses of CO 2 in the negative mode to measure 14 C/ 12 C isotopic ratios in real time. The design of the targets were based on computational flow dynamics, ionization mechanism and empirical optimization. As part of the ionization mechanism, the adsorption of CO 2 on the Ti surface was fitted with the Jovanovic-Freundlich isotherm model using empirical and simulation data. The inferred adsorption constants were in good agreement with other works. The empirical optimization showed that amount of injected carbon and the flow speed of the helium carrier gas improve the ionization efficiency and the amount of 12 C - produced until reaching a saturation point. Linear dynamic range between 150 and 1000 ng of C and optimum carrier gas flow speed of around 0.1 mL/min were shown. It was also shown that the ionization depends on the area of the Ti surface and Cs + beam cross-section. A range of ionization efficiency of 1-2.5% was obtained by optimizing the described parameters.

Low-power low-noise mixed-mode VLSI ASIC for infinite dynamic range imaging applications

NASA Astrophysics Data System (ADS)

Turchetta, Renato; Hu, Y.; Zinzius, Y.; Colledani, C.; Loge, A.

1998-11-01

Solid state solutions for imaging are mainly represented by CCDs and, more recently, by CMOS imagers. Both devices are based on the integration of the total charge generated by the impinging radiation, with no processing of the single photon information. The dynamic range of these devices is intrinsically limited by the finite value of noise. Here we present the design of an architecture which allows efficient, in-pixel, noise reduction to a practically zero level, thus allowing infinite dynamic range imaging. A detailed calculation of the dynamic range is worked out, showing that noise is efficiently suppressed. This architecture is based on the concept of single-photon counting. In each pixel, we integrate both the front-end, low-noise, low-power analog part and the digital part. The former consists of a charge preamplifier, an active filter for optimal noise bandwidth reduction, a buffer and a threshold comparator, and the latter is simply a counter, which can be programmed to act as a normal shift register for the readout of the counters' contents. Two different ASIC's based on this concept have been designed for different applications. The first one has been optimized for silicon edge-on microstrips detectors, used in a digital mammography R and D project. It is a 32-channel circuit, with a 16-bit binary static counter.It has been optimized for a relatively large detector capacitance of 5 pF. Noise has been measured to be equal to 100 + 7*Cd (pF) electron rms with the digital part, showing no degradation of the noise performances with respect to the design values. The power consumption is 3.8mW/channel for a peaking time of about 1 microsecond(s) . The second circuit is a prototype for pixel imaging. The total active area is about (250 micrometers )**2. The main differences of the electronic architecture with respect to the first prototype are: i) different optimization of the analog front-end part for low-capacitance detectors, ii) in- pixel 4-bit comparator-offset compensation, iii) 15-bit pseudo-random counter. The power consumption is 255 (mu) W/channel for a peaking time of 300 ns and an equivalent noise charge of 185 + 97*Cd electrons rms. Simulation and experimental result as well as imaging results will be presented.

The effect of delay line on the performance of a fiber optic interferometric sensor

NASA Astrophysics Data System (ADS)

Lin, Yung-Li; Lin, Ken-Huang; Lin, Wuu-Wen; Chen, Mao-Hsiung

2007-09-01

The optical fiber has the features of low loss and wide bandwidth; it has replaced the coaxial cable as the mainstream of the communication system in recent years. Because of its high sensitivity characteristic, the interferometer is usually applied to long distance, weak signal detection. In general, if the area to be monitored is located far away, the weak signal will make it uneasy to detect. An interferometer is used for phase detection. Thus, the hydrophone which is based on interferometric fiber optic sensor has extremely high sensitivity. Sagnac interferometric hydrophone has low noise of marine environment, which is more suitably used to detect underwater acoustic signal than that of a Mach-Zehnder interferometer. In this paper, we propose the configuration of dual Sagnac interferometer, and use the mathematical methods to drive and design optimal two delay fiber lengths, which can enlarge the dynamic range of underwater acoustic detection. In addition, we also use software simulation to design optimal two delay fiber lengths. The experimental configuration of dual Sagnac interferometer with two optical delay line is shown as Fig. 1. The maximum and minimum measurable phase signal value of dual Sagnac interferometer (L II=2 km, L 4=222.2 m), shown in Fig. 3. The fiber optic sensor head is of mandrel type. The acoustic window is made of silicon rubbers. It was shown that we can increase their sensitivities by increasing number of wrapping fiber coils. In our experiment, the result shows that among all the mandrel sensor heads, the highest dynamic range is up to 37.6 +/- 1.4 dB, and its sensitivity is -223.3 +/-1.7 dB re V / 1μ Pa. As for the configuration of the optical interferometers, the intensity of the dual Sagnac interferometer is 20 dB larger than its Sagnac counterpart. Its dynamic range is above 66 dB where the frequency ranges is between 50 ~ 400 Hz, which is 24 dB larger than that of the Sagnac interferometer with the sensitivity of -192.0 dB re V / l μPa. In addition, by using software simulation to design optimal lengths of delay fibers, we can increase the dynamic range of interferometer on underwater acoustic detection. This paper verifies that, by means of adjusting the length of these two delay fibers, we can actually increase the dynamic range of acoustic signal detection.

Forward and backward tone mapping of high dynamic range images based on subband architecture

NASA Astrophysics Data System (ADS)

Bouzidi, Ines; Ouled Zaid, Azza

2015-01-01

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

Transmitted wavefront testing with large dynamic range based on computer-aided deflectometry

NASA Astrophysics Data System (ADS)

Wang, Daodang; Xu, Ping; Gong, Zhidong; Xie, Zhongmin; Liang, Rongguang; Xu, Xinke; Kong, Ming; Zhao, Jun

2018-06-01

The transmitted wavefront testing technique is demanded for the performance evaluation of transmission optics and transparent glass, in which the achievable dynamic range is a key issue. A computer-aided deflectometric testing method with fringe projection is proposed for the accurate testing of transmitted wavefronts with a large dynamic range. Ray tracing of the modeled testing system is carried out to achieve the virtual ‘null’ testing of transmitted wavefront aberrations. The ray aberration is obtained from the ray tracing result and measured slope, with which the test wavefront aberration can be reconstructed. To eliminate testing system modeling errors, a system geometry calibration based on computer-aided reverse optimization is applied to realize accurate testing. Both numerical simulation and experiments have been carried out to demonstrate the feasibility and high accuracy of the proposed testing method. The proposed testing method can achieve a large dynamic range compared with the interferometric method, providing a simple, low-cost and accurate way for the testing of transmitted wavefronts from various kinds of optics and a large amount of industrial transmission elements.

Cooperative quantum-behaved particle swarm optimization with dynamic varying search areas and Lévy flight disturbance.

PubMed

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem.

Long range personalized cancer treatment strategies incorporating evolutionary dynamics.

PubMed

Yeang, Chen-Hsiang; Beckman, Robert A

2016-10-22

Current cancer precision medicine strategies match therapies to static consensus molecular properties of an individual's cancer, thus determining the next therapeutic maneuver. These strategies typically maintain a constant treatment while the cancer is not worsening. However, cancers feature complicated sub-clonal structure and dynamic evolution. We have recently shown, in a comprehensive simulation of two non-cross resistant therapies across a broad parameter space representing realistic tumors, that substantial improvement in cure rates and median survival can be obtained utilizing dynamic precision medicine strategies. These dynamic strategies explicitly consider intratumoral heterogeneity and evolutionary dynamics, including predicted future drug resistance states, and reevaluate optimal therapy every 45 days. However, the optimization is performed in single 45 day steps ("single-step optimization"). Herein we evaluate analogous strategies that think multiple therapeutic maneuvers ahead, considering potential outcomes at 5 steps ahead ("multi-step optimization") or 40 steps ahead ("adaptive long term optimization (ALTO)") when recommending the optimal therapy in each 45 day block, in simulations involving both 2 and 3 non-cross resistant therapies. We also evaluate an ALTO approach for situations where simultaneous combination therapy is not feasible ("Adaptive long term optimization: serial monotherapy only (ALTO-SMO)"). Simulations utilize populations of 764,000 and 1,700,000 virtual patients for 2 and 3 drug cases, respectively. Each virtual patient represents a unique clinical presentation including sizes of major and minor tumor subclones, growth rates, evolution rates, and drug sensitivities. While multi-step optimization and ALTO provide no significant average survival benefit, cure rates are significantly increased by ALTO. Furthermore, in the subset of individual virtual patients demonstrating clinically significant difference in outcome between approaches, by far the majority show an advantage of multi-step or ALTO over single-step optimization. ALTO-SMO delivers cure rates superior or equal to those of single- or multi-step optimization, in 2 and 3 drug cases respectively. In selected virtual patients incurable by dynamic precision medicine using single-step optimization, analogous strategies that "think ahead" can deliver long-term survival and cure without any disadvantage for non-responders. When therapies require dose reduction in combination (due to toxicity), optimal strategies feature complex patterns involving rapidly interleaved pulses of combinations and high dose monotherapy. This article was reviewed by Wendy Cornell, Marek Kimmel, and Andrzej Swierniak. Wendy Cornell and Andrzej Swierniak are external reviewers (not members of the Biology Direct editorial board). Andrzej Swierniak was nominated by Marek Kimmel.

Design and characterization of the ePix10k: a high dynamic range integrating pixel ASIC for LCLS detectors

NASA Astrophysics Data System (ADS)

Caragiulo, P.; Dragone, A.; Markovic, B.; Herbst, R.; Nishimura, K.; Reese, B.; Herrmann, S.; Hart, P.; Blaj, G.; Segal, J.; Tomada, A.; Hasi, J.; Carini, G.; Kenney, C.; Haller, G.

2015-05-01

ePix10k is a variant of a novel class of integrating pixel ASICs architectures optimized for the processing of signals in second generation LINAC Coherent Light Source (LCLS) X-Ray cameras. The ASIC is optimized for high dynamic range application requiring high spatial resolution and fast frame rates. ePix ASICs are based on a common platform composed of a random access analog matrix of pixel with global shutter, fast parallel column readout, and dedicated sigma-delta analog to digital converters per column. The ePix10k variant has 100um×100um pixels arranged in a 176×192 matrix, a resolution of 140e- r.m.s. and a signal range of 3.5pC (10k photons at 8keV). In its final version it will be able to sustain a frame rate of 2kHz. A first prototype has been fabricated and characterized. Performance in terms of noise, linearity, uniformity, cross-talk, together with preliminary measurements with bump bonded sensors are reported here.

[Reconstruction of Vehicle-human Crash Accident and Injury Analysis Based on 3D Laser Scanning, Multi-rigid-body Reconstruction and Optimized Genetic Algorithm].

PubMed

Sun, J; Wang, T; Li, Z D; Shao, Y; Zhang, Z Y; Feng, H; Zou, D H; Chen, Y J

2017-12-01

To reconstruct a vehicle-bicycle-cyclist crash accident and analyse the injuries using 3D laser scanning technology, multi-rigid-body dynamics and optimized genetic algorithm, and to provide biomechanical basis for the forensic identification of death cause. The vehicle was measured by 3D laser scanning technology. The multi-rigid-body models of cyclist, bicycle and vehicle were developed based on the measurements. The value range of optimal variables was set. A multi-objective genetic algorithm and the nondominated sorting genetic algorithm were used to find the optimal solutions, which were compared to the record of the surveillance video around the accident scene. The reconstruction result of laser scanning on vehicle was satisfactory. In the optimal solutions found by optimization method of genetic algorithm, the dynamical behaviours of dummy, bicycle and vehicle corresponded to that recorded by the surveillance video. The injury parameters of dummy were consistent with the situation and position of the real injuries on the cyclist in accident. The motion status before accident, damage process by crash and mechanical analysis on the injury of the victim can be reconstructed using 3D laser scanning technology, multi-rigid-body dynamics and optimized genetic algorithm, which have application value in the identification of injury manner and analysis of death cause in traffic accidents. Copyright© by the Editorial Department of Journal of Forensic Medicine

Runway Scheduling Using Generalized Dynamic Programming

NASA Technical Reports Server (NTRS)

Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar

2011-01-01

A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.

Optimization of Supersonic Transport Trajectories

NASA Technical Reports Server (NTRS)

Ardema, Mark D.; Windhorst, Robert; Phillips, James

1998-01-01

This paper develops a near-optimal guidance law for generating minimum fuel, time, or cost fixed-range trajectories for supersonic transport aircraft. The approach uses a choice of new state variables along with singular perturbation techniques to time-scale decouple the dynamic equations into multiple equations of single order (second order for the fast dynamics). Application of the maximum principle to each of the decoupled equations, as opposed to application to the original coupled equations, avoids the two point boundary value problem and transforms the problem from one of a functional optimization to one of multiple function optimizations. It is shown that such an approach produces well known aircraft performance results such as minimizing the Brequet factor for minimum fuel consumption and the energy climb path. Furthermore, the new state variables produce a consistent calculation of flight path angle along the trajectory, eliminating one of the deficiencies in the traditional energy state approximation. In addition, jumps in the energy climb path are smoothed out by integration of the original dynamic equations at constant load factor. Numerical results performed for a supersonic transport design show that a pushover dive followed by a pullout at nominal load factors are sufficient maneuvers to smooth the jump.

Single-shot measurement of >1010 pulse contrast for ultra-high peak-power lasers

PubMed Central

Wang, Yongzhi; Ma, Jingui; Wang, Jing; Yuan, Peng; Xie, Guoqiang; Ge, Xulei; Liu, Feng; Yuan, Xiaohui; Zhu, Heyuan; Qian, Liejia

2014-01-01

Real-time pulse-contrast observation with a high dynamic range is a prerequisite to tackle the contrast challenge in ultra-high peak-power lasers. However, the commonly used delay-scanning cross-correlator (DSCC) can only provide the time-consumed measurements for repetitive lasers. Single-shot cross-correlator (SSCC) becomes essential in optimizing laser systems and exploring contrast mechanisms. Here we report our progress in developing SSCC towards its practical use. By integrating both the techniques of scattering-noise reduction and sensitive parallel detection into SSCC, we demonstrate a high dynamic range of >1010, which, to our best knowledge, is the first demonstration of an SSCC with a dynamic range comparable to that of commercial DSCCs. The comparison of high-dynamic measurement performances between SSCC and a standard DSCC (Sequoia, Amplitude Technologies) is also carried out on a 200 TW Ti:sapphire laser, and the consistency of results verifies the veracity of our SSCC. PMID:24448655

Two Studies of Complex Nonlinear Systems: Engineered Granular Crystals and Coarse-Graining Optimization Problems

NASA Astrophysics Data System (ADS)

Pozharskiy, Dmitry

In recent years a nonlinear, acoustic metamaterial, named granular crystals, has gained prominence due to its high accessibility, both experimentally and computationally. The observation of a wide range of dynamical phenomena in the system, due to its inherent nonlinearities, has suggested its importance in many engineering applications related to wave propagation. In the first part of this dissertation, we explore the nonlinear dynamics of damped-driven granular crystals. In one case, we consider a highly nonlinear setting, also known as a sonic vacuum, and derive a nonlinear analogue of a linear spectrum, corresponding to resonant periodic propagation and antiresonances. Experimental studies confirm the computational findings and the assimilation of experimental data into a numerical model is demonstrated. In the second case, global bifurcations in a precompressed granular crystal are examined, and their involvement in the appearance of chaotic dynamics is demonstrated. Both results highlight the importance of exploring the nonlinear dynamics, to gain insight into how a granular crystal responds to different external excitations. In the second part, we borrow established ideas from coarse-graining of dynamical systems, and extend them to optimization problems. We combine manifold learning algorithms, such as Diffusion Maps, with stochastic optimization methods, such as Simulated Annealing, and show that we can retrieve an ensemble, of few, important parameters that should be explored in detail. This framework can lead to acceleration of convergence when dealing with complex, high-dimensional optimization, and could potentially be applied to design engineered granular crystals.

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

NASA Technical Reports Server (NTRS)

1988-01-01

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

DFTBaby: A software package for non-adiabatic molecular dynamics simulations based on long-range corrected tight-binding TD-DFT(B)

NASA Astrophysics Data System (ADS)

Humeniuk, Alexander; Mitrić, Roland

2017-12-01

A software package, called DFTBaby, is published, which provides the electronic structure needed for running non-adiabatic molecular dynamics simulations at the level of tight-binding DFT. A long-range correction is incorporated to avoid spurious charge transfer states. Excited state energies, their analytic gradients and scalar non-adiabatic couplings are computed using tight-binding TD-DFT. These quantities are fed into a molecular dynamics code, which integrates Newton's equations of motion for the nuclei together with the electronic Schrödinger equation. Non-adiabatic effects are included by surface hopping. As an example, the program is applied to the optimization of excited states and non-adiabatic dynamics of polyfluorene. The python and Fortran source code is available at http://www.dftbaby.chemie.uni-wuerzburg.de.

Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?

PubMed

Blagrove, Marcus S C; Caminade, Cyril; Waldmann, Elisabeth; Sutton, Elizabeth R; Wardeh, Maya; Baylis, Matthew

2017-06-01

Mosquito-borne viruses have been estimated to cause over 100 million cases of human disease annually. Many methodologies have been developed to help identify areas most at risk from transmission of these viruses. However, generally, these methodologies focus predominantly on the effects of climate on either the vectors or the pathogens they spread, and do not consider the dynamic interaction between the optimal conditions for both vector and virus. Here, we use a new approach that considers the complex interplay between the optimal temperature for virus transmission, and the optimal climate for the mosquito vectors. Using published geolocated data we identified temperature and rainfall ranges in which a number of mosquito vectors have been observed to co-occur with West Nile virus, dengue virus or chikungunya virus. We then investigated whether the optimal climate for co-occurrence of vector and virus varies between "warmer" and "cooler" adapted vectors for the same virus. We found that different mosquito vectors co-occur with the same virus at different temperatures, despite significant overlap in vector temperature ranges. Specifically, we found that co-occurrence correlates with the optimal climatic conditions for the respective vector; cooler-adapted mosquitoes tend to co-occur with the same virus in cooler conditions than their warmer-adapted counterparts. We conclude that mosquitoes appear to be most able to transmit virus in the mosquitoes' optimal climate range, and hypothesise that this may be due to proportionally over-extended vector longevity, and other increased fitness attributes, within this optimal range. These results suggest that the threat posed by vector-competent mosquito species indigenous to temperate regions may have been underestimated, whilst the threat arising from invasive tropical vectors moving to cooler temperate regions may be overestimated.

Role of dynamic capsomere supply for viral capsid self-assembly

NASA Astrophysics Data System (ADS)

Boettcher, Marvin A.; Klein, Heinrich C. R.; Schwarz, Ulrich S.

2015-02-01

Many viruses rely on the self-assembly of their capsids to protect and transport their genomic material. For many viral systems, in particular for human viruses like hepatitis B, adeno or human immunodeficiency virus, that lead to persistent infections, capsomeres are continuously produced in the cytoplasm of the host cell while completed capsids exit the cell for a new round of infection. Here we use coarse-grained Brownian dynamics simulations of a generic patchy particle model to elucidate the role of the dynamic supply of capsomeres for the reversible self-assembly of empty T1 icosahedral virus capsids. We find that for high rates of capsomere influx only a narrow range of bond strengths exists for which a steady state of continuous capsid production is possible. For bond strengths smaller and larger than this optimal value, the reaction volume becomes crowded by small and large intermediates, respectively. For lower rates of capsomere influx a broader range of bond strengths exists for which a steady state of continuous capsid production is established, although now the production rate of capsids is smaller. Thus our simulations suggest that the importance of an optimal bond strength for viral capsid assembly typical for in vitro conditions can be reduced by the dynamic influx of capsomeres in a cellular environment.

Dynamic Grover search: applications in recommendation systems and optimization problems

NASA Astrophysics Data System (ADS)

Chakrabarty, Indranil; Khan, Shahzor; Singh, Vanshdeep

2017-06-01

In the recent years, we have seen that Grover search algorithm (Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212-219, 1996) by using quantum parallelism has revolutionized the field of solving huge class of NP problems in comparisons to classical systems. In this work, we explore the idea of extending Grover search algorithm to approximate algorithms. Here we try to analyze the applicability of Grover search to process an unstructured database with a dynamic selection function in contrast to the static selection function used in the original work (Grover in Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212-219, 1996). We show that this alteration facilitates us to extend the application of Grover search to the field of randomized search algorithms. Further, we use the dynamic Grover search algorithm to define the goals for a recommendation system based on which we propose a recommendation algorithm which uses binomial similarity distribution space giving us a quadratic speedup over traditional classical unstructured recommendation systems. Finally, we see how dynamic Grover search can be used to tackle a wide range of optimization problems where we improve complexity over existing optimization algorithms.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exporation

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

The problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars were investigated. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; navigation, terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks were studied: vehicle model design, mathematical modeling of dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement and transport parameter evaluation.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

Investigation of problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars has been undertaken. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks have been under study: vehicle model design, mathematical modeling of a dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer sybsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement.

Parametrization and Optimization of Gaussian Non-Markovian Unravelings for Open Quantum Dynamics

NASA Astrophysics Data System (ADS)

Megier, Nina; Strunz, Walter T.; Viviescas, Carlos; Luoma, Kimmo

2018-04-01

We derive a family of Gaussian non-Markovian stochastic Schrödinger equations for the dynamics of open quantum systems. The different unravelings correspond to different choices of squeezed coherent states, reflecting different measurement schemes on the environment. Consequently, we are able to give a single shot measurement interpretation for the stochastic states and microscopic expressions for the noise correlations of the Gaussian process. By construction, the reduced dynamics of the open system does not depend on the squeezing parameters. They determine the non-Hermitian Gaussian correlation, a wide range of which are compatible with the Markov limit. We demonstrate the versatility of our results for quantum information tasks in the non-Markovian regime. In particular, by optimizing the squeezing parameters, we can tailor unravelings for improving entanglement bounds or for environment-assisted entanglement protection.

Effects of sample injection amount and time-of-flight mass spectrometric detection dynamic range on metabolome analysis by high-performance chemical isotope labeling LC-MS.

PubMed

Zhou, Ruokun; Li, Liang

2015-04-06

The effect of sample injection amount on metabolome analysis in a chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) platform was investigated. The performance of time-of-flight (TOF) mass spectrometers with and without a high-dynamic-range (HD) detection system was compared in the analysis of (12)C2/(13)C2-dansyl labeled human urine samples. An average of 1635 ± 21 (n = 3) peak pairs or putative metabolites was detected using the HD-TOF-MS, compared to 1429 ± 37 peak pairs from a conventional or non-HD TOF-MS. In both instruments, signal saturation was observed. However, in the HD-TOF-MS, signal saturation was mainly caused by the ionization process, while in the non-HD TOF-MS, it was caused by the detection process. To extend the MS detection range in the non-HD TOF-MS, an automated switching from using (12)C to (13)C-natural abundance peaks for peak ratio calculation when the (12)C peaks are saturated has been implemented in IsoMS, a software tool for processing CIL LC-MS data. This work illustrates that injecting an optimal sample amount is important to maximize the metabolome coverage while avoiding the sample carryover problem often associated with over-injection. A TOF mass spectrometer with an enhanced detection dynamic range can also significantly increase the number of peak pairs detected. In chemical isotope labeling (CIL) LC-MS, relative metabolite quantification is done by measuring the peak ratio of a (13)C2-/(12)C2-labeled peak pair for a given metabolite present in two comparative samples. The dynamic range of peak ratio measurement does not need to be very large, as only subtle changes of metabolite concentrations are encountered in most metabolomic studies where relative metabolome quantification of different groups of samples is performed. However, the absolute concentrations of different metabolites can be very different, requiring a technique to provide a wide detection dynamic range to allow the detection of as many peak pairs as possible. In this work, we demonstrated that controlling the sample injection amount into LC-MS was critical to achieve the optimal detectability while avoiding sample carry-over problem. In addition, the use of a high-dynamic-range TOF system increased the number of peak pairs detected, compared to a conventional TOF system. We also investigated the ionization and detection saturation factors limiting the dynamic range of detection. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras. Copyright © 2014 Elsevier B.V. All rights reserved.

Stochastic Models of Plant Diversity: Application to White Sands Missile Range

DTIC Science & Technology

2000-02-01

decades and its models have been well developed. These models fall in the categories: dynamic models and stochastic models. In their book , Modeling...Gelb 1974), and dendro- climatology (Visser and Molenaar 1988). Optimal Estimation An optimal estimator is a computational algorithm that...Evaluation, M.B. Usher, ed., Chapman and Hall, London. Visser, H., and J. Molenaar . 1990. "Estimating Trends in Tree-ring Data." For. Sei. 36(1): 87

Dual Transition Edge Sensor Bolometer for Enhanced Dynamic Range

NASA Technical Reports Server (NTRS)

Chervenak, J. A.; Benford, D. J.; Moseley, S. H.; Irwin, K. D.

2004-01-01

Broadband surveys at the millimeter and submillimeter wavelengths will require bolometers that can reach new limits of sensitivity and also operate under high background conditions. To address this need, we present results on a dual transition edge sensor (TES) device with two operating modes: one for low background, ultrasensitive detection and one for high background, enhanced dynamic range detection. The device consists of a detector element with two transition temperatures (T(sub c)) of 0.25 and 0.51 K located on the same micromachined, thermally isolated membrane structure. It can be biased on either transition, and features phonon-limited noise performance at the lower T(sub c). We measure noise performance on the lower transition 7 x 10(exp -18) W/rt(Hz) and the bias power on the upper transition of 12.5 pW, giving a factor of 10 enhancement of the dynamic range for the device. We discuss the biasable range of this type of device and present a design concept to optimize utility of the device.

Optimized "detectors" for dynamics analysis in solid-state NMR

NASA Astrophysics Data System (ADS)

Smith, Albert A.; Ernst, Matthias; Meier, Beat H.

2018-01-01

Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.

Is there a preference for linearity when viewing natural images?

NASA Astrophysics Data System (ADS)

Kane, David; Bertamío, Marcelo

2015-01-01

The system gamma of the imaging pipeline, defined as the product of the encoding and decoding gammas, is typically greater than one and is stronger for images viewed with a dark background (e.g. cinema) than those viewed in lighter conditions (e.g. office displays).1-3 However, for high dynamic range (HDR) images reproduced on a low dynamic range (LDR) monitor, subjects often prefer a system gamma of less than one,4 presumably reflecting the greater need for histogram equalization in HDR images. In this study we ask subjects to rate the perceived quality of images presented on a LDR monitor using various levels of system gamma. We reveal that the optimal system gamma is below one for images with a HDR and approaches or exceeds one for images with a LDR. Additionally, the highest quality scores occur for images where a system gamma of one is optimal, suggesting a preference for linearity (where possible). We find that subjective image quality scores can be predicted by computing the degree of histogram equalization of the lightness distribution. Accordingly, an optimal, image dependent system gamma can be computed that maximizes perceived image quality.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimal intravenous infusion to decrease the haematocrit level in patient of DHF infection

NASA Astrophysics Data System (ADS)

Handayani, D.; Nuraini, N.; Saragih, R.; Wijaya, K. P.; Naiborhu, J.

2014-02-01

The optimal control of infusion model for Dengue Hemorrhagic Fever (DHF) infection is formulated here. The infusion model will be presented in form of haematocrit level. The input control aim to normalize the haematocrit level and is expressed as infusion volume on mL/day. The stability near the equilibrium points will be analyzed. Numerical simulation shows the dynamic of each infection compartments which gives a description of within-host dynamic of dengue virus. These results show particularly that infected compartments tend to be vanished in ±15days after the onset of the virus. In fact, without any control added, the haematocrit level will decrease but not up to the normal level. Therefore the effective haematocrit normalization should be done with the treatment control. Control treatment for a fixed time using a control input can bring haematocrit level to normal range 42-47%. The optimal control in this paper is divided into three cases, i.e. fixed end point, constrained input, and tracking haematocrit state. Each case shows different infection condition in human body. However, all cases require that the haematocrit level to be in normal range in fixed final time.

Cooperative Quantum-Behaved Particle Swarm Optimization with Dynamic Varying Search Areas and Lévy Flight Disturbance

PubMed Central

Li, Desheng

2014-01-01

This paper proposes a novel variant of cooperative quantum-behaved particle swarm optimization (CQPSO) algorithm with two mechanisms to reduce the search space and avoid the stagnation, called CQPSO-DVSA-LFD. One mechanism is called Dynamic Varying Search Area (DVSA), which takes charge of limiting the ranges of particles' activity into a reduced area. On the other hand, in order to escape the local optima, Lévy flights are used to generate the stochastic disturbance in the movement of particles. To test the performance of CQPSO-DVSA-LFD, numerical experiments are conducted to compare the proposed algorithm with different variants of PSO. According to the experimental results, the proposed method performs better than other variants of PSO on both benchmark test functions and the combinatorial optimization issue, that is, the job-shop scheduling problem. PMID:24851085

An optimal output feedback gain variation scheme for the control of plants exhibiting gross parameter changes

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.

1987-01-01

A concept for optimally designing output feedback controllers for plants whose dynamics exhibit gross changes over their operating regimes was developed. This was to formulate the design problem in such a way that the implemented feedback gains vary as the output of a dynamical system whose independent variable is a scalar parameterization of the plant operating point. The results of this effort include derivation of necessary conditions for optimality for the general problem formulation, and for several simplified cases. The question of existence of a solution to the design problem was also examined, and it was shown that the class of gain variation schemes developed are capable of achieving gain variation histories which are arbitrarily close to the unconstrained gain solution for each point in the plant operating range. The theory was implemented in a feedback design algorithm, which was exercised in a numerical example. The results are applicable to the design of practical high-performance feedback controllers for plants whose dynamics vary significanly during operation. Many aerospace systems fall into this category.

Simulative method for determining the optimal operating conditions for a cooling plate for lithium-ion battery cell modules

NASA Astrophysics Data System (ADS)

Smith, Joshua; Hinterberger, Michael; Hable, Peter; Koehler, Juergen

2014-12-01

Extended battery system lifetime and reduced costs are essential to the success of electric vehicles. An effective thermal management strategy is one method of enhancing system lifetime increasing vehicle range. Vehicle-typical space restrictions favor the minimization of battery thermal management system (BTMS) size and weight, making their production and subsequent vehicle integration extremely difficult and complex. Due to these space requirements, a cooling plate as part of a water-glycerol cooling circuit is commonly implemented. This paper presents a computational fluid dynamics (CFD) model and multi-objective analysis technique for determining the thermal effect of coolant flow rate and inlet temperature in a cooling plate-at a range of vehicle operating conditions-on a battery system, thereby providing a dynamic input for one-dimensional models. Traditionally, one-dimensional vehicular thermal management system models assume a static heat input from components such as a battery system: as a result, the components are designed for a set coolant input (flow rate and inlet temperature). Such a design method is insufficient for dynamic thermal management models and control strategies, thereby compromising system efficiency. The presented approach allows for optimal BMTS design and integration in the vehicular coolant circuit.

Ultra-precise micro-motion stage for optical scanning test

NASA Astrophysics Data System (ADS)

Chen, Wen; Zhang, Jianhuan; Jiang, Nan

2009-05-01

This study aims at the application of optical sensing technology in a 2D flexible hinge test stage. Optical fiber sensor which is manufactured taking advantage of the various unique properties of optical fiber, such as good electric insulation properties, resistance of electromagnetic disturbance, sparkless property and availability in flammable and explosive environment, has lots of good properties, such as high accuracy and wide dynamic range, repeatable, etc. and is applied in 2D flexible hinge stage driven by PZT. Several micro-bending structures are designed utilizing the characteristics of the flexible hinge stage. And through experiments, the optimal micro-bending tooth structure and the scope of displacement sensor trip under this optimal micro-bending tooth structure are derived. These experiments demonstrate that the application of optical fiber displacement sensor in 2D flexible hinge stage driven by PZT substantially broadens the dynamic testing range and improves the sensitivity of this apparatus. Driving accuracy and positioning stability are enhanced as well. [1,2

An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

PubMed Central

2012-01-01

Background Synchronized bursting activity (SBA) is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i) In a network with an excitatory ratio (ER) of 80-90%, its connective ratio (CR) was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii) No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL) motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30%) optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA. PMID:22462685

Satellite image collection optimization

NASA Astrophysics Data System (ADS)

Martin, William

2002-09-01

Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

Strong scaling of general-purpose molecular dynamics simulations on GPUs

NASA Astrophysics Data System (ADS)

Glaser, Jens; Nguyen, Trung Dac; Anderson, Joshua A.; Lui, Pak; Spiga, Filippo; Millan, Jaime A.; Morse, David C.; Glotzer, Sharon C.

2015-07-01

We describe a highly optimized implementation of MPI domain decomposition in a GPU-enabled, general-purpose molecular dynamics code, HOOMD-blue (Anderson and Glotzer, 2013). Our approach is inspired by a traditional CPU-based code, LAMMPS (Plimpton, 1995), but is implemented within a code that was designed for execution on GPUs from the start (Anderson et al., 2008). The software supports short-ranged pair force and bond force fields and achieves optimal GPU performance using an autotuning algorithm. We are able to demonstrate equivalent or superior scaling on up to 3375 GPUs in Lennard-Jones and dissipative particle dynamics (DPD) simulations of up to 108 million particles. GPUDirect RDMA capabilities in recent GPU generations provide better performance in full double precision calculations. For a representative polymer physics application, HOOMD-blue 1.0 provides an effective GPU vs. CPU node speed-up of 12.5 ×.

Hydro-meteorological risk reduction through land restoration in Rangárvellir, Iceland - an overview of the HydroResilience project

NASA Astrophysics Data System (ADS)

Finger, David C.; Pétursdóttir, Þórunn; Halldórsson, Guðmundur

2017-04-01

Ecosystems that are in equilibrium provide vital resources to local inhabitants, including protection from naturally occurring disasters. Natural vegetation cover has been optimized over many years to retain a maximum of rainfall runoff by increasing the field capacity (FC) of the soil cover, securing water availability during droughts and reducing the flood risk during heavy precipitation events. In this presentation we will present the HydroResilience project, which will assess the effects of ecosystem restoration on the runoff dynamics of rainfall water in Rangárvellir, a restoration area in southern Iceland. The Rangárvellir area presents ideal conditions for such investigations. Dramatic deforestation during the last millennium and year round livestock grazing along with devastating ash depositions during volcanic eruptions and a harsh sub-polar oceanic climate have led to severe degradation in Rangárvellir. Since the beginning of the 20th century diverse restoration measures have been implemented making Rangárvellir an ideal case study to investigate the effects of restoration on hydro-meteorological risk reduction. In this project we will assess and quantify the evolution of water resources in Rangárvellir by assessing the runoff dynamics in the main rivers of Rangárvellir under four main scenarios: i) present conditions, ii) degraded conditions as was the case 100 years ago, iii) under hypothetical fully restored ecosystems and, finally, iv) under conditions of a scenario developed in collaboration with local stakeholder groups to optimize socio-ecological benefits. For this purpose the dynamics of the relevant hydrological processes in the area (incl. river runoff, ground water table, snow cover duration, and soil moisture dynamics) will be reconstructed using hydrological models to run the above mentioned scenarios. The scientific findings and conclusion of this project will generate valuable insights on the effects of land restoration on hydro-meteorological risk reduction. The presentations will outline the main methods used during the project and conclude by providing an outlook on the expected results.

Bayesian ensemble refinement by replica simulations and reweighting.

PubMed

Hummer, Gerhard; Köfinger, Jürgen

2015-12-28

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Bayesian ensemble refinement by replica simulations and reweighting

NASA Astrophysics Data System (ADS)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Fluid-dynamic design optimization of hydraulic proportional directional valves

NASA Astrophysics Data System (ADS)

Amirante, Riccardo; Catalano, Luciano Andrea; Poloni, Carlo; Tamburrano, Paolo

2014-10-01

This article proposes an effective methodology for the fluid-dynamic design optimization of the sliding spool of a hydraulic proportional directional valve: the goal is the minimization of the flow force at a prescribed flow rate, so as to reduce the required opening force while keeping the operation features unchanged. A full three-dimensional model of the flow field within the valve is employed to accurately predict the flow force acting on the spool. A theoretical analysis, based on both the axial momentum equation and flow simulations, is conducted to define the design parameters, which need to be properly selected in order to reduce the flow force without significantly affecting the flow rate. A genetic algorithm, coupled with a computational fluid dynamics flow solver, is employed to minimize the flow force acting on the valve spool at the maximum opening. A comparison with a typical single-objective optimization algorithm is performed to evaluate performance and effectiveness of the employed genetic algorithm. The optimized spool develops a maximum flow force which is smaller than that produced by the commercially available valve, mainly due to some major modifications occurring in the discharge section. Reducing the flow force and thus the electromagnetic force exerted by the solenoid actuators allows the operational range of direct (single-stage) driven valves to be enlarged.

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

In vitro evaluation of stiffness and load sharing in a two-level corpectomy: comparison of static and dynamic cervical plates.

PubMed

Fogel, Guy R; Li, Zhenyu; Liu, Weiqiang; Liao, Zhenhua; Wu, Jia; Zhou, Wenyu

2010-05-01

Anterior cervical plating has been accepted in corpectomy and fusion of the cervical spine. Constrained plates were criticized for stress shielding that may lead to subsidence and pseudarthrosis. A dynamic plate allows load sharing as the graft subsides. Ideally, the dynamic plate design should maintain adequate stiffness of the construct while providing a reasonable load sharing with the strut graft. The purpose of the study was to compare dynamic and static plate kinematics with graft subsidence. The study designed was an in vitro biomechanical study in a porcine cervical spine model. Twelve spines were initially tested in intact condition with 20-N axial load in 15 degrees of flexion and extension range of motion (ROM). Then, a two-level corpectomy was created in all specimens with spines randomized to receive either a static or dynamic plate. The spines were retested under identical conditions with optimal length and undersized graft. Range of motion and graft loading were analyzed with a one-way analysis of variance (p<.05). Both plates significantly limited ROM compared with the intact spine in both graft length conditions. In extension graft, load was significantly higher (p=.001) in the static plate with optimal length, and in flexion, there was a significant loss of graft load (p=.0004). In flexion, the dynamic plate with undersized graft demonstrated significantly more load sustained (p=.0004). Both plates reasonably limited the ROM of the corpectomy. The static plate had significantly higher graft loads in extension and significant loss of graft load in flexion, whereas the dynamic plate maintained a reasonable graft load in ROM even when graft contact was imperfect. Copyright 2010 Elsevier Inc. All rights reserved.

Inference of Stochastic Nonlinear Oscillators with Applications to Physiological Problems

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadim N.; Luchinsky, Dmitry G.

2004-01-01

A new method of inferencing of coupled stochastic nonlinear oscillators is described. The technique does not require extensive global optimization, provides optimal compensation for noise-induced errors and is robust in a broad range of dynamical models. We illustrate the main ideas of the technique by inferencing a model of five globally and locally coupled noisy oscillators. Specific modifications of the technique for inferencing hidden degrees of freedom of coupled nonlinear oscillators is discussed in the context of physiological applications.

A Wide Dynamic Range Tapped Linear Array Image Sensor

NASA Astrophysics Data System (ADS)

Washkurak, William D.; Chamberlain, Savvas G.; Prince, N. Daryl

1988-08-01

Detectors for acousto-optic signal processing applications require fast transient response as well as wide dynamic range. There are two major choices of detectors: conductive or integration mode. Conductive mode detectors have an initial transient period before they reach then' i equilibrium state. The duration of 1 his period is dependent on light level as well as detector capacitance. At low light levels a conductive mode detector is very slow; response time is typically on the order of milliseconds. Generally. to obtain fast transient response an integrating mode detector is preferred. With integrating mode detectors. the dynamic range is determined by the charge storage capability of the tran-sport shift registers and the noise level of the image sensor. The conventional net hod used to improve dynamic range is to increase the shift register charge storage capability. To achieve a dynamic range of fifty thousand assuming two hundred noise equivalent electrons, a charge storage capability of ten million electrons would be required. In order to accommodate this amount of charge. unrealistic shift registers widths would be required. Therefore, with an integrating mode detector it is difficult to achieve a dynamic range of over four orders of magnitude of input light intensity. Another alternative is to solve the problem at the photodetector aml not the shift, register. DALSA's wide dynamic range detector utilizes an optimized, ion implant doped, profiled MOSFET photodetector specifically designed for wide dynamic range. When this new detector operates at high speed and at low light levels the photons are collected and stored in an integrating fashion. However. at bright light levels where transient periods are short, the detector switches into a conductive mode. The light intensity is logarithmically compressed into small charge packets, easily carried by the CCD shift register. As a result of the logarithmic conversion, dynamic ranges of over six orders of magnitide are obtained. To achieve the short integration times necessary in acousto-optic applications. t he wide dynamic range detector has been implemented into a tapped array architecture with eight outputs and 256 photoelements. Operation of each 01)1,1)111 at 16 MHz yields detector integration times of 2 micro-seconds. Buried channel two phase CCD shift register technology is utilized to minimize image sensor noise improve video output rates and increase ease of operation.

Changes in the Coherent Dynamics of Nanoconfined Room Temperature Ionic Liquids

NASA Astrophysics Data System (ADS)

Vallejo, Kevin; Cano, Melissa; Li, Song; Rotner, Gernot; Faraone, Antonio; Banuelos, Jose

Confinement and temperature effects on the coherent dynamics of the room temperature ionic liquid (RTIL) [C10MPy+] [Tf2N-] were investigated using neutron spin-echo (NSE) in two silica matrices with different pore size. Several intermolecular forces give rise to the bulk molecular structure between anions and cations. NSE provided dynamics (via the coherent intermediate scattering function) in the time range of 0.004 to 10 ns, and at Q-values corresponding to intermediate range ordering and inter- and intra-molecular length scales of the RTIL. Pore wall effects were delineated by comparing bulk RTIL dynamics with those of the confined fluid in 2.8 nm and 8 nm pores. Analytical models were applied to the experimental data to extract decay times and amplitudes of each component. We find a fast relaxation outside the experiment time window, a primary relaxation, and slow, surface-induced dynamics, which all speed up with increased temperature, however, the temperature dependence differs between bulk and confinement. This study sheds light on the structure and dynamics of RTILs and is relevant to the optimization of RTILs for green technologies and applications.

Comparison of magnetic resonance imaging-compatible optical detectors for in-magnet tissue spectroscopy: photodiodes versus silicon photomultipliers

PubMed Central

El-Ghussein, Fadi; Jiang, Shudong; Pogue, Brian W.; Paulsen, Keith D.

2014-01-01

Abstract. Tissue spectroscopy inside the magnetic resonance imaging (MRI) system adds a significant value by measuring fast vascular hemoglobin responses or completing spectroscopic identification of diagnostically relevant molecules. Advances in this type of spectroscopy instrumentation have largely focused on fiber coupling into and out of the MRI; however, nonmagnetic detectors can now be placed inside the scanner with signal amplification performed remotely to the high field environment for optimized light detection. In this study, the two possible detector options, such as silicon photodiodes (PD) and silicon photomultipliers (SiPM), were systematically examined for dynamic range and wavelength performance. Results show that PDs offer 108 (160 dB) dynamic range with sensitivity down to 1 pW, whereas SiPMs have 107 (140 dB) dynamic range and sensitivity down to 10 pW. A second major difference is the spectral sensitivity of the two detectors. Here, wavelengths in the 940 nm range are efficiently captured by PDs (but not SiPMs), likely making them the superior choice for broadband spectroscopy guided by MRI. PMID:25006986

Characterization of Hot Deformation Behavior of a Fe-Cr-Ni-Mo-N Superaustenitic Stainless Steel Using Dynamic Materials Modeling

NASA Astrophysics Data System (ADS)

Pu, Enxiang; Zheng, Wenjie; Song, Zhigang; Feng, Han; Zhu, Yuliang

2017-03-01

Hot deformation behavior of a Fe-24Cr-22Ni-7Mo-0.5N superaustenitic stainless steel was investigated by hot compression tests in a wide temperature range of 950-1250 °C and strain rate range of 0.001-10 s-1. The flow curves show that the flow stress decreases as the deformation temperature increases or the strain rate decreases. The processing maps developed on the basis of the dynamic materials model and flow stress data were adopted to optimize the parameters of hot working. It was found that the strain higher than 0.2 has no significant effect on the processing maps. The optimum processing conditions were in the temperature range of 1125-1220 °C and strain rate range of 0.1-3 s-1. Comparing to other stable domains, microstructural observations in this domain revealed the complete dynamic recrystallization (DRX) with finer and more uniform grain size. Flow instability occurred in the domain of temperature lower than 1100 °C and strain rate higher than 0.1 s-1.

Holographic recording properties in thick films of ULSH-500 photopolymer

NASA Astrophysics Data System (ADS)

Waldman, David A.; Li, H.-Y. S.; Cetin, Erdem A.

1998-06-01

The photopolymer holographic recording materials, ULSH-500, based upon cationic ring-opening polymerization, has been further optimized for recording in an increased film thickness of 200 micrometers . The dynamic range attained, at least M/# equals 16, is substantially greater than previously reported, while concurrently the inherent low transverse shrinkage and high sensitivity characteristics of the material have been retained. Dynamic range or cumulative grating strength, (Sigma) (eta) i0.5, has been determined from co-locationally recorded peristrophic and angle multiplexed plane-wave gratings which exhibit low diffraction efficiencies between about 0.1 and 0.2%. Good Bragg selectivity consistent with the imaged thickness and sinc2 function behavior is observed for the multiplexed holograms, and both the angular response and the diffraction efficiency are stable without the need for post-imaging fixing procedures. Sensitivity is in the range of 1 to 10 cm/mJ, and the refractive index modulation achievable during consumption of the accessible dynamic range is n1 equals 1.3 X 10-2 at the read wavelength of 514.5 nm.

Impact of mechanism vibration characteristics by joint clearance and optimization design of its multi-objective robustness

NASA Astrophysics Data System (ADS)

Zeng, Baoping; Wang, Chao; Zhang, Yu; Gong, Yajun; Hu, Sanbao

2017-12-01

Joint clearances and friction characteristics significantly influence the mechanism vibration characteristics; for example: as for joint clearances, the shaft and bearing of its clearance joint collide to bring about the dynamic normal contact force and tangential coulomb friction force while the mechanism works; thus, the whole system may vibrate; moreover, the mechanism is under contact-impact with impact force constraint from free movement under action of the above dynamic forces; in addition, the mechanism topology structure also changes. The constraint relationship between joints may be established by a repeated complex nonlinear dynamic process (idle stroke - contact-impact - elastic compression - rebound - impact relief - idle stroke movement - contact-impact). Analysis of vibration characteristics of joint parts is still a challenging open task by far. The dynamic equations for any mechanism with clearance is often a set of strong coupling, high-dimensional and complex time-varying nonlinear differential equations which are solved very difficultly. Moreover, complicated chaotic motions very sensitive to initial values in impact and vibration due to clearance let high-precision simulation and prediction of their dynamic behaviors be more difficult; on the other hand, their subsequent wearing necessarily leads to some certain fluctuation of structure clearance parameters, which acts as one primary factor for vibration of the mechanical system. A dynamic model was established to the device for opening the deepwater robot cabin door with joint clearance by utilizing the finite element method and analysis was carried out to its vibration characteristics in this study. Moreover, its response model was carried out by utilizing the DOE method and then the robust optimization design was performed to sizes of the joint clearance and the friction coefficient change range so that the optimization design results may be regarded as reference data for selecting bearings and controlling manufacturing process parameters for the opening mechanism. Several optimization objectives such as x/y/z accelerations for various measuring points and dynamic reaction forces of mounting brackets, and a few constraints including manufacturing process were taken into account in the optimization models, which were solved by utilizing the multi-objective genetic algorithm (NSGA-II). The vibration characteristics of the optimized opening mechanism are superior to those of the original design. In addition, the numerical forecast results are in good agreement with the test results of the prototype.

Self-optimizing Pitch Control for Large Scale Wind Turbine Based on ADRC

NASA Astrophysics Data System (ADS)

Xia, Anjun; Hu, Guoqing; Li, Zheng; Huang, Dongxiao; Wang, Fengxiang

2018-01-01

Since wind turbine is a complex nonlinear and strong coupling system, traditional PI control method can hardly achieve good control performance. A self-optimizing pitch control method based on the active-disturbance-rejection control theory is proposed in this paper. A linear model of the wind turbine is derived by linearizing the aerodynamic torque equation and the dynamic response of wind turbine is transformed into a first-order linear system. An expert system is designed to optimize the amplification coefficient according to the pitch rate and the speed deviation. The purpose of the proposed control method is to regulate the amplification coefficient automatically and keep the variations of pitch rate and rotor speed in proper ranges. Simulation results show that the proposed pitch control method has the ability to modify the amplification coefficient effectively, when it is not suitable, and keep the variations of pitch rate and rotor speed in proper ranges

Laser development for optimal helicopter obstacle warning system LADAR performance

NASA Astrophysics Data System (ADS)

Yaniv, A.; Krupkin, V.; Abitbol, A.; Stern, J.; Lurie, E.; German, A.; Solomonovich, S.; Lubashitz, B.; Harel, Y.; Engart, S.; Shimoni, Y.; Hezy, S.; Biltz, S.; Kaminetsky, E.; Goldberg, A.; Chocron, J.; Zuntz, N.; Zajdman, A.

2005-04-01

Low lying obstacles present immediate danger to both military and civilian helicopters performing low-altitude flight missions. A LADAR obstacle detection system is the natural solution for enhancing helicopter safety and improving the pilot situation awareness. Elop is currently developing an advanced Surveillance and Warning Obstacle Ranging and Display (SWORD) system for the Israeli Air Force. Several key factors and new concepts have contributed to system optimization. These include an adaptive FOV, data memorization, autonomous obstacle detection and warning algorithms and the use of an agile laser transmitter. In the present work we describe the laser design and performance and discuss some of the experimental results. Our eye-safe laser is characterized by its pulse energy, repetition rate and pulse length agility. By dynamically controlling these parameters, we are able to locally optimize the system"s obstacle detection range and scan density in accordance with the helicopter instantaneous maneuver.

Optical biosensor optimized for continuous in-line glucose monitoring in animal cell culture.

PubMed

Tric, Mircea; Lederle, Mario; Neuner, Lisa; Dolgowjasow, Igor; Wiedemann, Philipp; Wölfl, Stefan; Werner, Tobias

2017-09-01

Biosensors for continuous glucose monitoring in bioreactors could provide a valuable tool for optimizing culture conditions in biotechnological applications. We have developed an optical biosensor for long-term continuous glucose monitoring and demonstrated a tight glucose level control during cell culture in disposable bioreactors. The in-line sensor is based on a commercially available oxygen sensor that is coated with cross-linked glucose oxidase (GOD). The dynamic range of the sensor was tuned by a hydrophilic perforated diffusion membrane with an optimized permeability for glucose and oxygen. The biosensor was thoroughly characterized by experimental data and numerical simulations, which enabled insights into the internal concentration profile of the deactivating by-product hydrogen peroxide. The simulations were carried out with a one-dimensional biosensor model and revealed that, in addition to the internal hydrogen peroxide concentration, the turnover rate of the enzyme GOD plays a crucial role for biosensor stability. In the light of this finding, the glucose sensor was optimized to reach a long functional stability (>52 days) under continuous glucose monitoring conditions with a dynamic range of 0-20 mM and a response time of t 90  ≤ 10 min. In addition, we demonstrated that the sensor was sterilizable with beta and UV irradiation and only subjected to minor cross sensitivity to oxygen, when an oxygen reference sensor was applied. Graphical abstract Measuring setup of a glucose biosensor in a shake flask for continuous glucose monitoring in mammalian cell culture.

Development of Advanced Methods of Structural and Trajectory Analysis for Transport Aircraft

NASA Technical Reports Server (NTRS)

Ardema, Mark D.; Windhorst, Robert; Phillips, James

1998-01-01

This paper develops a near-optimal guidance law for generating minimum fuel, time, or cost fixed-range trajectories for supersonic transport aircraft. The approach uses a choice of new state variables along with singular perturbation techniques to time-scale decouple the dynamic equations into multiple equations of single order (second order for the fast dynamics). Application of the maximum principle to each of the decoupled equations, as opposed to application to the original coupled equations, avoids the two point boundary value problem and transforms the problem from one of a functional optimization to one of multiple function optimizations. It is shown that such an approach produces well known aircraft performance results such as minimizing the Brequet factor for minimum fuel consumption and the energy climb path. Furthermore, the new state variables produce a consistent calculation of flight path angle along the trajectory, eliminating one of the deficiencies in the traditional energy state approximation. In addition, jumps in the energy climb path are smoothed out by integration of the original dynamic equations at constant load factor. Numerical results performed for a supersonic transport design show that a pushover dive followed by a pullout at nominal load factors are sufficient maneuvers to smooth the jump.

Structural acoustic control of plates with variable boundary conditions: design methodology.

PubMed

Sprofera, Joseph D; Cabell, Randolph H; Gibbs, Gary P; Clark, Robert L

2007-07-01

A method for optimizing a structural acoustic control system subject to variations in plate boundary conditions is provided. The assumed modes method is used to build a plate model with varying levels of rotational boundary stiffness to simulate the dynamics of a plate with uncertain edge conditions. A transducer placement scoring process, involving Hankel singular values, is combined with a genetic optimization routine to find spatial locations robust to boundary condition variation. Predicted frequency response characteristics are examined, and theoretically optimized results are discussed in relation to the range of boundary conditions investigated. Modeled results indicate that it is possible to minimize the impact of uncertain boundary conditions in active structural acoustic control by optimizing the placement of transducers with respect to those uncertainties.

Optimal variable flip angle schemes for dynamic acquisition of exchanging hyperpolarized substrates

NASA Astrophysics Data System (ADS)

Xing, Yan; Reed, Galen D.; Pauly, John M.; Kerr, Adam B.; Larson, Peder E. Z.

2013-09-01

In metabolic MRI with hyperpolarized contrast agents, the signal levels vary over time due to T1 decay, T2 decay following RF excitations, and metabolic conversion. Efficient usage of the nonrenewable hyperpolarized magnetization requires specialized RF pulse schemes. In this work, we introduce two novel variable flip angle schemes for dynamic hyperpolarized MRI in which the flip angle is varied between excitations and between metabolites. These were optimized to distribute the magnetization relatively evenly throughout the acquisition by accounting for T1 decay, prior RF excitations, and metabolic conversion. Simulation results are presented to confirm the flip angle designs and evaluate the variability of signal dynamics across typical ranges of T1 and metabolic conversion. They were implemented using multiband spectral-spatial RF pulses to independently modulate the flip angle at various chemical shift frequencies. With these schemes we observed increased SNR of [1-13C]lactate generated from [1-13C]pyruvate, particularly at later time points. This will allow for improved characterization of tissue perfusion and metabolic profiles in dynamic hyperpolarized MRI.

Optimal sensitometric curves of Kodak EDR2 film for dynamic intensity modulated radiation therapy verification

PubMed Central

Suriyapee, S; Pitaxtarnin, N; Oonsiri, S; Jumpangern, C; Israngkul Na Ayuthaya, I

2008-01-01

Purpose: To investigate the optimal sensitometric curves of extended dose range (EDR2) radiographic film in terms of depth, field size, dose range and processing conditions for dynamic intensity modulated radiation therapy (IMRT) dosimetry verification with 6 MV X-ray beams. Materials and methods: A Varian Clinac 23 EX linear accelerator with 6 MV X-ray beam was used to study the response of Kodak EDR2 film. Measurements were performed at depths of 5, 10 and 15 cm in MedTec virtual water phantom and with field sizes of 2x2, 3x3, 10x10 and 15x15 cm2. Doses ranging from 20 to 450 cGy were used. The film was developed with the Kodak RP X-OMAT Model M6B automatic film processor. Film response was measured with the Vidar model VXR-16 scanner. Sensitometric curves were applied to the dose profiles measured with film at 5 cm in the virtual water phantom with field sizes of 2x2 and 10x10 cm2 and compared with ion chamber data. Scanditronix/Wellhofer OmniProTM IMRT software was used for the evaluation of the IMRT plan calculated by Eclipse treatment planning. Results: Investigation of the reproducibility and accuracy of the film responses, which depend mainly on the film processor, was carried out by irradiating one film nine times with doses of 20 to 450 cGy. A maximum standard deviation of 4.9% was found which decreased to 1.9% for doses between 20 and 200 cGy. The sensitometric curves for various field sizes at fixed depth showed a maximum difference of 4.2% between 2x2 and 15x15 cm2 at 5 cm depth with a dose of 450 cGy. The shallow depth tended to show a greater effect of field size responses than the deeper depths. The sensitometric curves for various depths at fixed field size showed slightly different film responses; the difference due to depth was within 1.8% for all field sizes studied. Both field size and depth effect were reduced when the doses were lower than 450 cGy. The difference was within 2.5% in the dose range from 20 to 300 cGy for all field sizes and depths studied. Dose profiles measured with EDR2 film were consistent with those measured with an ion chamber. The optimal sensitometric curve was acquired by irradiating film at a depth of 5 cm with doses ranging from 20 to 450 cGy with a 3×3 cm2 multileaf collimator. The optimal sensitometric curve allowed accurate determination of the absolute dose distribution. In almost 200 cases of dynamic IMRT plan verification with EDR2 film, the difference between measured and calculated dose was generally less than 3% and with 3 mm distance to agreement when using gamma value verification. Conclusion: EDR2 film can be used for accurate verification of composite isodose distributions of dynamic IMRT when the optimal sensitometric curve has been established. PMID:21614315

Optimal sensitometric curves of Kodak EDR2 film for dynamic intensity modulated radiation therapy verification.

PubMed

Suriyapee, S; Pitaxtarnin, N; Oonsiri, S; Jumpangern, C; Israngkul Na Ayuthaya, I

2008-01-01

To investigate the optimal sensitometric curves of extended dose range (EDR2) radiographic film in terms of depth, field size, dose range and processing conditions for dynamic intensity modulated radiation therapy (IMRT) dosimetry verification with 6 MV X-ray beams. A Varian Clinac 23 EX linear accelerator with 6 MV X-ray beam was used to study the response of Kodak EDR2 film. Measurements were performed at depths of 5, 10 and 15 cm in MedTec virtual water phantom and with field sizes of 2x2, 3x3, 10x10 and 15x15 cm(2). Doses ranging from 20 to 450 cGy were used. The film was developed with the Kodak RP X-OMAT Model M6B automatic film processor. Film response was measured with the Vidar model VXR-16 scanner. Sensitometric curves were applied to the dose profiles measured with film at 5 cm in the virtual water phantom with field sizes of 2x2 and 10x10 cm(2) and compared with ion chamber data. Scanditronix/Wellhofer OmniPro(TM) IMRT software was used for the evaluation of the IMRT plan calculated by Eclipse treatment planning. Investigation of the reproducibility and accuracy of the film responses, which depend mainly on the film processor, was carried out by irradiating one film nine times with doses of 20 to 450 cGy. A maximum standard deviation of 4.9% was found which decreased to 1.9% for doses between 20 and 200 cGy. The sensitometric curves for various field sizes at fixed depth showed a maximum difference of 4.2% between 2x2 and 15x15 cm(2) at 5 cm depth with a dose of 450 cGy. The shallow depth tended to show a greater effect of field size responses than the deeper depths. The sensitometric curves for various depths at fixed field size showed slightly different film responses; the difference due to depth was within 1.8% for all field sizes studied. Both field size and depth effect were reduced when the doses were lower than 450 cGy. The difference was within 2.5% in the dose range from 20 to 300 cGy for all field sizes and depths studied. Dose profiles measured with EDR2 film were consistent with those measured with an ion chamber. The optimal sensitometric curve was acquired by irradiating film at a depth of 5 cm with doses ranging from 20 to 450 cGy with a 3×3 cm(2) multileaf collimator. The optimal sensitometric curve allowed accurate determination of the absolute dose distribution. In almost 200 cases of dynamic IMRT plan verification with EDR2 film, the difference between measured and calculated dose was generally less than 3% and with 3 mm distance to agreement when using gamma value verification. EDR2 film can be used for accurate verification of composite isodose distributions of dynamic IMRT when the optimal sensitometric curve has been established.

Differential dynamic microscopy of weakly scattering and polydisperse protein-rich clusters

NASA Astrophysics Data System (ADS)

Safari, Mohammad S.; Vorontsova, Maria A.; Poling-Skutvik, Ryan; Vekilov, Peter G.; Conrad, Jacinta C.

2015-10-01

Nanoparticle dynamics impact a wide range of biological transport processes and applications in nanomedicine and natural resource engineering. Differential dynamic microscopy (DDM) was recently developed to quantify the dynamics of submicron particles in solutions from fluctuations of intensity in optical micrographs. Differential dynamic microscopy is well established for monodisperse particle populations, but has not been applied to solutions containing weakly scattering polydisperse biological nanoparticles. Here we use bright-field DDM (BDDM) to measure the dynamics of protein-rich liquid clusters, whose size ranges from tens to hundreds of nanometers and whose total volume fraction is less than 10-5. With solutions of two proteins, hemoglobin A and lysozyme, we evaluate the cluster diffusion coefficients from the dependence of the diffusive relaxation time on the scattering wave vector. We establish that for weakly scattering populations, an optimal thickness of the sample chamber exists at which the BDDM signal is maximized at the smallest sample volume. The average cluster diffusion coefficient measured using BDDM is consistently lower than that obtained from dynamic light scattering at a scattering angle of 90∘. This apparent discrepancy is due to Mie scattering from the polydisperse cluster population, in which larger clusters preferentially scatter more light in the forward direction.

A New Distributed Optimization for Community Microgrids Scheduling

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

Starke, Michael R; Tomsovic, Kevin

This paper proposes a distributed optimization model for community microgrids considering the building thermal dynamics and customer comfort preference. The microgrid central controller (MCC) minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost and voluntary load shedding cost based on the customers' consumption, while the building energy management systems (BEMS) minimize their electricity bills as well as the cost associated with customer discomfort due to room temperature deviation from the set point. The BEMSs and the MCC exchange information on energy consumption and prices. When the optimization converges, the distributed generation scheduling,more » energy storage charging/discharging and customers' consumption as well as the energy prices are determined. In particular, we integrate the detailed thermal dynamic characteristics of buildings into the proposed model. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of proposed model.« less

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment‐Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

PubMed Central

Mondal, Milon; Radeva, Nedyalka; Fanlo‐Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard

2016-01-01

Abstract Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization. PMID:27400756

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

Belousov, O. A.; Muromtsev, D. Yu; Belyaev, M. P.

2018-04-01

The control of heat devices in a wide temperature range given thermophysical properties of an object is a topical issue. Optimal control systems of electric furnaces have to meet strict requirements in terms of accuracy of production procedures and efficiency of energy consumption. The fulfillment of these requirements is possible only if the dynamics model describing adequately the processes occurring in the furnaces is used to calculate the optimal control actions. One of the types of electric furnaces is the electric chamber furnace intended for heat treatment of various materials at temperatures from thousands of degrees Celsius and above. To solve the above-mentioned problem and to determine its place in the system of energy-efficient control of dynamic modes in the electric furnace, we propose the concept of an intelligent sensor and a method of synthesizing variables on sets of functioning states. The use of synthesis algorithms for optimal control in real time ensures the required accuracy when operating under different conditions and operating modes of the electric chamber furnace.

Determining landscape extent for succession and disturbance simulation modeling

Treesearch

Eva C. Karau; Robert E. Keane

2007-01-01

Dividing regions into manageable landscape units presents special problems in landscape ecology and land management. Ideally, a landscape should be large enough to capture a broad range of vegetation, environmental and disturbance dynamics, but small enough to be useful for focused management objectives. The purpose of this study was to determine the optimal landscape...

Influence of linear profile modification and loading conditions on the dynamic tooth load and stress of high contact ratio gears

NASA Technical Reports Server (NTRS)

Lee, Chinwai; Lin, Hsiang Hsi; Oswald, Fred B.; Townsend, Dennis P.

1990-01-01

A computer simulation for the dynamic response of high-contact-ratio spur gear transmissions is presented. High contact ratio gears have the potential to produce lower dynamic tooth loads and minimum root stress but they can be sensitive to tooth profile errors. The analysis presented examines various profile modifications under realistic loading conditions. The effect of these modifications on the dynamic load (force) between mating gear teeth and the dynamic root stress is presented. Since the contact stress is dependent on the dynamic load, minimizing dynamic loads will also minimize contact stresses. It is shown that the combination of profile modification and the applied load (torque) carried by a gear system has a significant influence on gear dynamics. The ideal modification at one value of applied load will not be the best solution for a different load. High-contact-ratio gears were found to require less modification than standard low-contact-ratio gears. High-contact-ratio gears are more adversely affected by excess modification than by under modification. In addition, the optimal profile modification required to minimize the dynamic load (hence the contact stress) on a gear tooth differs from the optimal modification required to minimize the dynamic root (bending) stress. Computer simulation can help find the design tradeoffs to determine the best profile modification to satisfy the conflicting constraints of minimizing both the load and root stress in gears which must operate over a range of applied loads.

COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U

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

Sun, Y.; Borland, Michael

Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.

CFD optimization of continuous stirred-tank (CSTR) reactor for biohydrogen production.

PubMed

Ding, Jie; Wang, Xu; Zhou, Xue-Fei; Ren, Nan-Qi; Guo, Wan-Qian

2010-09-01

There has been little work on the optimal configuration of biohydrogen production reactors. This paper describes three-dimensional computational fluid dynamics (CFD) simulations of gas-liquid flow in a laboratory-scale continuous stirred-tank reactor used for biohydrogen production. To evaluate the role of hydrodynamics in reactor design and optimize the reactor configuration, an optimized impeller design has been constructed and validated with CFD simulations of the normal and optimized impeller over a range of speeds and the numerical results were also validated by examination of residence time distribution. By integrating the CFD simulation with an ethanol-type fermentation process experiment, it was shown that impellers with different type and speed generated different flow patterns, and hence offered different efficiencies for biohydrogen production. The hydrodynamic behavior of the optimized impeller at speeds between 50 and 70 rev/min is most suited for economical biohydrogen production. Copyright 2010 Elsevier Ltd. All rights reserved.

Optimization of block-floating-point realizations for digital controllers with finite-word-length considerations.

PubMed

Wu, Jun; Hu, Xie-he; Chen, Sheng; Chu, Jian

2003-01-01

The closed-loop stability issue of finite-precision realizations was investigated for digital controllers implemented in block-floating-point format. The controller coefficient perturbation was analyzed resulting from using finite word length (FWL) block-floating-point representation scheme. A block-floating-point FWL closed-loop stability measure was derived which considers both the dynamic range and precision. To facilitate the design of optimal finite-precision controller realizations, a computationally tractable block-floating-point FWL closed-loop stability measure was then introduced and the method of computing the value of this measure for a given controller realization was developed. The optimal controller realization is defined as the solution that maximizes the corresponding measure, and a numerical optimization approach was adopted to solve the resulting optimal realization problem. A numerical example was used to illustrate the design procedure and to compare the optimal controller realization with the initial realization.

Autonomous Guidance of Agile Small-scale Rotorcraft

NASA Technical Reports Server (NTRS)

Mettler, Bernard; Feron, Eric

2004-01-01

This report describes a guidance system for agile vehicles based on a hybrid closed-loop model of the vehicle dynamics. The hybrid model represents the vehicle dynamics through a combination of linear-time-invariant control modes and pre-programmed, finite-duration maneuvers. This particular hybrid structure can be realized through a control system that combines trim controllers and a maneuvering control logic. The former enable precise trajectory tracking, and the latter enables trajectories at the edge of the vehicle capabilities. The closed-loop model is much simpler than the full vehicle equations of motion, yet it can capture a broad range of dynamic behaviors. It also supports a consistent link between the physical layer and the decision-making layer. The trajectory generation was formulated as an optimization problem using mixed-integer-linear-programming. The optimization is solved in a receding horizon fashion. Several techniques to improve the computational tractability were investigate. Simulation experiments using NASA Ames 'R-50 model show that this approach fully exploits the vehicle's agility.

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

HIRES the high-resolution spectrograph for the E-ELT: dynamics and control of the repositioning mechanism for the E-ELT HIRES polarimeter

NASA Astrophysics Data System (ADS)

Di Varano, I.; Strassmeier, K. G.; Woche, M.

2016-08-01

A full Stokes dual channel polarimeter for the E-ELT HIRES spectrograph has been envisioned for the intermediate focus f/4.4, operating within a spectral range of 0.4-1.6 μ. It will feed the EELT- HIRES instrument located on the Nasmyth platform via two pairs of dedicated fibers: one fibre pair optimized for the BVRI, the other one optimized for the JH band or any other feasible combination. The instrument must be retractable within a workspace in fulfillment with the ESO requirements on the allocated volume and the dynamic response of the AO tower. For such purpose a swinging arm has been designed with a rotation provided by 5 revolute joints and a jackscrew. Moreover repeatability in repositioning has to be guaranteed by a parallel manipulator, performing an alignment procedure mainly along 5 axes. Dynamics and control criteria with a feed forward chain to compensate for vibration forces and feedback chain for tracking procedure are hereafter presented.

Design of an ultra low power third order continuous time current mode ΣΔ modulator for WLAN applications.

PubMed

Behzadi, Kobra; Baghelani, Masoud

2014-05-01

This paper presents a third order continuous time current mode ΣΔ modulator for WLAN 802.11b standard applications. The proposed circuit utilized feedback architecture with scaled and optimized DAC coefficients. At circuit level, we propose a modified cascade current mirror integrator with reduced input impedance which results in more bandwidth and linearity and hence improves the dynamic range. Also, a very fast and precise novel dynamic latch based current comparator is introduced with low power consumption. This ultra fast comparator facilitates increasing the sampling rate toward GHz frequencies. The modulator exhibits dynamic range of more than 60 dB for 20 MHz signal bandwidth and OSR of 10 while consuming only 914 μW from 1.8 V power supply. The FoM of the modulator is calculated from two different methods, and excellent performance is achieved for proposed modulator.

Design of an ultra low power third order continuous time current mode ΣΔ modulator for WLAN applications

PubMed Central

Behzadi, Kobra; Baghelani, Masoud

2013-01-01

This paper presents a third order continuous time current mode ΣΔ modulator for WLAN 802.11b standard applications. The proposed circuit utilized feedback architecture with scaled and optimized DAC coefficients. At circuit level, we propose a modified cascade current mirror integrator with reduced input impedance which results in more bandwidth and linearity and hence improves the dynamic range. Also, a very fast and precise novel dynamic latch based current comparator is introduced with low power consumption. This ultra fast comparator facilitates increasing the sampling rate toward GHz frequencies. The modulator exhibits dynamic range of more than 60 dB for 20 MHz signal bandwidth and OSR of 10 while consuming only 914 μW from 1.8 V power supply. The FoM of the modulator is calculated from two different methods, and excellent performance is achieved for proposed modulator. PMID:25685504

Optimal multi-community network modularity for information diffusion

NASA Astrophysics Data System (ADS)

Wu, Jiaocan; Du, Ruping; Zheng, Yingying; Liu, Dong

2016-02-01

Studies demonstrate that community structure plays an important role in information spreading recently. In this paper, we investigate the impact of multi-community structure on information diffusion with linear threshold model. We utilize extended GN network that contains four communities and analyze dynamic behaviors of information that spreads on it. And we discover the optimal multi-community network modularity for information diffusion based on the social reinforcement. Results show that, within the appropriate range, multi-community structure will facilitate information diffusion instead of hindering it, which accords with the results derived from two-community network.

Demodulation System for Fiber Optic Bragg Grating Dynamic Pressure Sensing

NASA Technical Reports Server (NTRS)

Lekki, John D.; Adamovsky, Grigory; Floyd, Bertram

2001-01-01

Fiber optic Bragg gratings have been used for years to measure quasi-static phenomena. In aircraft engine applications there is a need to measure dynamic signals such as variable pressures. In order to monitor these pressures a detection system with broad dynamic range is needed. This paper describes an interferometric demodulator that was developed and optimized for this particular application. The signal to noise ratio was maximized through temporal coherence analysis. The demodulator was incorporated in a laboratory system that simulates conditions to be measured. Several pressure sensor configurations incorporating a fiber optic Bragg grating were also explored. The results of the experiments are reported in this paper.

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

PubMed

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

2017-03-01

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

Experimental validation of structural optimization methods

NASA Technical Reports Server (NTRS)

Adelman, Howard M.

1992-01-01

The topic of validating structural optimization methods by use of experimental results is addressed. The need for validating the methods as a way of effecting a greater and an accelerated acceptance of formal optimization methods by practicing engineering designers is described. The range of validation strategies is defined which includes comparison of optimization results with more traditional design approaches, establishing the accuracy of analyses used, and finally experimental validation of the optimization results. Examples of the use of experimental results to validate optimization techniques are described. The examples include experimental validation of the following: optimum design of a trussed beam; combined control-structure design of a cable-supported beam simulating an actively controlled space structure; minimum weight design of a beam with frequency constraints; minimization of the vibration response of helicopter rotor blade; minimum weight design of a turbine blade disk; aeroelastic optimization of an aircraft vertical fin; airfoil shape optimization for drag minimization; optimization of the shape of a hole in a plate for stress minimization; optimization to minimize beam dynamic response; and structural optimization of a low vibration helicopter rotor.

Optimization of CMOS image sensor utilizing variable temporal multisampling partial transfer technique to achieve full-frame high dynamic range with superior low light and stop motion capability

NASA Astrophysics Data System (ADS)

Kabir, Salman; Smith, Craig; Armstrong, Frank; Barnard, Gerrit; Schneider, Alex; Guidash, Michael; Vogelsang, Thomas; Endsley, Jay

2018-03-01

Differential binary pixel technology is a threshold-based timing, readout, and image reconstruction method that utilizes the subframe partial charge transfer technique in a standard four-transistor (4T) pixel CMOS image sensor to achieve a high dynamic range video with stop motion. This technology improves low light signal-to-noise ratio (SNR) by up to 21 dB. The method is verified in silicon using a Taiwan Semiconductor Manufacturing Company's 65 nm 1.1 μm pixel technology 1 megapixel test chip array and is compared with a traditional 4 × oversampling technique using full charge transfer to show low light SNR superiority of the presented technology.

The Global Optimization of Pt13 Cluster Using the First-Principle Molecular Dynamics with the Quenching Technique

NASA Astrophysics Data System (ADS)

Chen, Xiangping; Duan, Haiming; Cao, Biaobing; Long, Mengqiu

2018-03-01

The high-temperature first-principle molecular dynamics method used to obtain the low energy configurations of clusters [L. L. Wang and D. D. Johnson, PRB 75, 235405 (2007)] is extended to a considerably large temperature range by combination with the quenching technique. Our results show that there are strong correlations between the possibilities for obtaining the ground-state structure and the temperatures. Larger possibilities can be obtained at relatively low temperatures (as corresponds to the pre-melting temperature range). Details of the structural correlation with the temperature are investigated by taking the Pt13 cluster as an example, which suggests a quite efficient method to obtain the lowest-energy geometries of metal clusters.

Rate and timing cues associated with the cochlear amplifier: level discrimination based on monaural cross-frequency coincidence detection.

PubMed

Heinz, M G; Colburn, H S; Carney, L H

2001-10-01

The perceptual significance of the cochlear amplifier was evaluated by predicting level-discrimination performance based on stochastic auditory-nerve (AN) activity. Performance was calculated for three models of processing: the optimal all-information processor (based on discharge times), the optimal rate-place processor (based on discharge counts), and a monaural coincidence-based processor that uses a non-optimal combination of rate and temporal information. An analytical AN model included compressive magnitude and level-dependent-phase responses associated with the cochlear amplifier, and high-, medium-, and low-spontaneous-rate (SR) fibers with characteristic frequencies (CFs) spanning the AN population. The relative contributions of nonlinear magnitude and nonlinear phase responses to level encoding were compared by using four versions of the model, which included and excluded the nonlinear gain and phase responses in all possible combinations. Nonlinear basilar-membrane (BM) phase responses are robustly encoded in near-CF AN fibers at low frequencies. Strongly compressive BM responses at high frequencies near CF interact with the high thresholds of low-SR AN fibers to produce large dynamic ranges. Coincidence performance based on a narrow range of AN CFs was robust across a wide dynamic range at both low and high frequencies, and matched human performance levels. Coincidence performance based on all CFs demonstrated the "near-miss" to Weber's law at low frequencies and the high-frequency "mid-level bump." Monaural coincidence detection is a physiologically realistic mechanism that is extremely general in that it can utilize AN information (average-rate, synchrony, and nonlinear-phase cues) from all SR groups.

Development and application of an optimization procedure for flutter suppression using the aerodynamic energy concept

NASA Technical Reports Server (NTRS)

Nissim, E.; Abel, I.

1978-01-01

An optimization procedure is developed based on the responses of a system to continuous gust inputs. The procedure uses control law transfer functions which have been partially determined by using the relaxed aerodynamic energy approach. The optimization procedure yields a flutter suppression system which minimizes control surface activity in a gust environment. The procedure is applied to wing flutter of a drone aircraft to demonstrate a 44 percent increase in the basic wing flutter dynamic pressure. It is shown that a trailing edge control system suppresses the flutter instability over a wide range of subsonic mach numbers and flight altitudes. Results of this study confirm the effectiveness of the relaxed energy approach.

Constraint Force Equation Methodology for Modeling Multi-Body Stage Separation Dynamics

NASA Technical Reports Server (NTRS)

Toniolo, Matthew D.; Tartabini, Paul V.; Pamadi, Bandu N.; Hotchko, Nathaniel

2008-01-01

This paper discusses a generalized approach to the multi-body separation problems in a launch vehicle staging environment based on constraint force methodology and its implementation into the Program to Optimize Simulated Trajectories II (POST2), a widely used trajectory design and optimization tool. This development facilitates the inclusion of stage separation analysis into POST2 for seamless end-to-end simulations of launch vehicle trajectories, thus simplifying the overall implementation and providing a range of modeling and optimization capabilities that are standard features in POST2. Analysis and results are presented for two test cases that validate the constraint force equation methodology in a stand-alone mode and its implementation in POST2.

The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

NASA Astrophysics Data System (ADS)

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2016-05-01

Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

Prediction of pilot-aircraft stability boundaries and performance contours

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.

1977-01-01

Control-theoretic pilot models can provide important new insights regarding the stability and performance characteristics of the pilot-aircraft system. Optimal-control pilot models can be formed for a wide range of flight conditions, suggesting that the human pilot can maintain stability if he adapts his control strategy to the aircraft's changing dynamics. Of particular concern is the effect of sub-optimal pilot adaptation as an aircraft transitions from low to high angle-of-attack during rapid maneuvering, as the changes in aircraft stability and control response can be extreme. This paper examines the effects of optimal and sub-optimal effort during a typical 'high-g' maneuver, and it introduces the concept of minimum-control effort (MCE) adaptation. Limited experimental results tend to support the MCE adaptation concept.

Optimization of the molecular dynamics method for simulations of DNA and ion transport through biological nanopores.

PubMed

Wells, David B; Bhattacharya, Swati; Carr, Rogan; Maffeo, Christopher; Ho, Anthony; Comer, Jeffrey; Aksimentiev, Aleksei

2012-01-01

Molecular dynamics (MD) simulations have become a standard method for the rational design and interpretation of experimental studies of DNA translocation through nanopores. The MD method, however, offers a multitude of algorithms, parameters, and other protocol choices that can affect the accuracy of the resulting data as well as computational efficiency. In this chapter, we examine the most popular choices offered by the MD method, seeking an optimal set of parameters that enable the most computationally efficient and accurate simulations of DNA and ion transport through biological nanopores. In particular, we examine the influence of short-range cutoff, integration timestep and force field parameters on the temperature and concentration dependence of bulk ion conductivity, ion pairing, ion solvation energy, DNA structure, DNA-ion interactions, and the ionic current through a nanopore.

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

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

Zhao, Jing; Peter Grünberg Institute; Zhang, Yi

2014-05-15

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mAmore » to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs.« less

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

NASA Astrophysics Data System (ADS)

Zhao, Jing; Zhang, Yi; Lee, Yong-Ho; Krause, Hans-Joachim

2014-05-01

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mA to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs.

Performance metric comparison study for non-magnetic bi-stable energy harvesters

NASA Astrophysics Data System (ADS)

Udani, Janav P.; Wrigley, Cailin; Arrieta, Andres F.

2017-04-01

Energy harvesting employing non-linear systems offers considerable advantages over linear systems given the broadband resonant response which is favorable for applications involving diverse input vibrations. In this respect, the rich dynamics of bi-stable systems present a promising means for harvesting vibrational energy from ambient sources. Harvesters deriving their bi-stability from thermally induced stresses as opposed to magnetic forces are receiving significant attention as it reduces the need for ancillary components and allows for bio- compatible constructions. However, the design of these bi-stable harvesters still requires further optimization to completely exploit the dynamic behavior of these systems. This study presents a comparison of the harvesting capabilities of non-magnetic, bi-stable composite laminates under variations in the design parameters as evaluated utilizing established power metrics. Energy output characteristics of two bi-stable composite laminate plates with a piezoelectric patch bonded on the top surface are experimentally investigated for variations in the thickness ratio and inertial mass positions for multiple load conditions. A particular design configuration is found to perform better over the entire range of testing conditions which include single and multiple frequency excitation, thus indicating that design optimization over the geometry of the harvester yields robust performance. The experimental analysis further highlights the need for appropriate design guidelines for optimization and holistic performance metrics to account for the range of operational conditions.

The use of an integrated variable fuzzy sets in water resources management

NASA Astrophysics Data System (ADS)

Qiu, Qingtai; Liu, Jia; Li, Chuanzhe; Yu, Xinzhe; Wang, Yang

2018-06-01

Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

Measuring circuit

DOEpatents

Sun, Shan C.; Chaprnka, Anthony G.

1977-01-11

An automatic gain control circuit functions to adjust the magnitude of an input signal supplied to a measuring circuit to a level within the dynamic range of the measuring circuit while a log-ratio circuit adjusts the magnitude of the output signal from the measuring circuit to the level of the input signal and optimizes the signal-to-noise ratio performance of the measuring circuit.

An integrated platform for biomolecule interaction analysis

NASA Astrophysics Data System (ADS)

Jan, Chia-Ming; Tsai, Pei-I.; Chou, Shin-Ting; Lee, Shu-Sheng; Lee, Chih-Kung

2013-02-01

We developed a new metrology platform which can detect real-time changes in both a phase-interrogation mode and intensity mode of a SPR (surface plasmon resonance). We integrated a SPR and ellipsometer to a biosensor chip platform to create a new biomolecular interaction measurement mechanism. We adopted a conductive ITO (indium-tinoxide) film to the bio-sensor platform chip to expand the dynamic range and improve measurement accuracy. The thickness of the conductive film and the suitable voltage constants were found to enhance performance. A circularly polarized ellipsometry configuration was incorporated into the newly developed platform to measure the label-free interactions of recombinant human C-reactive protein (CRP) with immobilized biomolecule target monoclonal human CRP antibody at various concentrations. CRP was chosen as it is a cardiovascular risk biomarker and is an acute phase reactant as well as a specific prognostic indicator for inflammation. We found that the sensitivity of a phaseinterrogation SPR is predominantly dependent on the optimization of the sample incidence angle. The effect of the ITO layer effective index under DC and AC effects as well as an optimal modulation were experimentally performed and discussed. Our experimental results showed that the modulated dynamic range for phase detection was 10E-2 RIU based on a current effect and 10E-4 RIU based on a potential effect of which a 0.55 (°/RIU) measurement was found by angular-interrogation. The performance of our newly developed metrology platform was characterized to have a higher sensitivity and less dynamic range when compared to a traditional full-field measurement system.

Automated Calibration For Numerical Models Of Riverflow

NASA Astrophysics Data System (ADS)

Fernandez, Betsaida; Kopmann, Rebekka; Oladyshkin, Sergey

2017-04-01

Calibration of numerical models is fundamental since the beginning of all types of hydro system modeling, to approximate the parameters that can mimic the overall system behavior. Thus, an assessment of different deterministic and stochastic optimization methods is undertaken to compare their robustness, computational feasibility, and global search capacity. Also, the uncertainty of the most suitable methods is analyzed. These optimization methods minimize the objective function that comprises synthetic measurements and simulated data. Synthetic measurement data replace the observed data set to guarantee an existing parameter solution. The input data for the objective function derivate from a hydro-morphological dynamics numerical model which represents an 180-degree bend channel. The hydro- morphological numerical model shows a high level of ill-posedness in the mathematical problem. The minimization of the objective function by different candidate methods for optimization indicates a failure in some of the gradient-based methods as Newton Conjugated and BFGS. Others reveal partial convergence, such as Nelder-Mead, Polak und Ribieri, L-BFGS-B, Truncated Newton Conjugated, and Trust-Region Newton Conjugated Gradient. Further ones indicate parameter solutions that range outside the physical limits, such as Levenberg-Marquardt and LeastSquareRoot. Moreover, there is a significant computational demand for genetic optimization methods, such as Differential Evolution and Basin-Hopping, as well as for Brute Force methods. The Deterministic Sequential Least Square Programming and the scholastic Bayes Inference theory methods present the optimal optimization results. keywords: Automated calibration of hydro-morphological dynamic numerical model, Bayesian inference theory, deterministic optimization methods.

Optimization of auxiliary optics in active-optics telescopes

NASA Astrophysics Data System (ADS)

Ragazzoni, Roberto

1993-04-01

The a-priori knowledge of the availability of active optics in a telescope can be advantageous in the design, optimization, and specification of tolerances for auxiliary devices of such a telescope. A modification of the merit function to be used into the optimization process is given, together with some considerations about the design procedure. The different effects of aberrations typically depending upon the position of the field of view (like coma or astigmatism), with those typically constant over the whole field of view (like spherical aberration) are explicitly taken into account in the mathematical treatment. A possible range of applications (prime focus corrector, off-axis field corrector, field flattener, reducing camera, and so on) is discussed. A case study for a field flattener is shown. The general result that can be derived from this paper is that tolerances are generally strongly relaxed, while a significant improvement of the nominal performances can be obtained only in particular cases or assuming a high dynamic range of the active optics correction.

Design of voice coil motor dynamic focusing unit for a laser scanner

NASA Astrophysics Data System (ADS)

Lee, Moon G.; Kim, Gaeun; Lee, Chan-Woo; Lee, Soo-Hun; Jeon, Yongho

2014-04-01

Laser scanning systems have been used for material processing tasks such as welding, cutting, marking, and drilling. However, applications have been limited by the small range of motion and slow speed of the focusing unit, which carries the focusing optics. To overcome these limitations, a dynamic focusing system with a long travel range and high speed is needed. In this study, a dynamic focusing unit for a laser scanning system with a voice coil motor (VCM) mechanism is proposed to enable fast speed and a wide focusing range. The VCM has finer precision and higher speed than conventional step motors and a longer travel range than earlier lead zirconium titanate actuators. The system has a hollow configuration to provide a laser beam path. This also makes it compact and transmission-free and gives it low inertia. The VCM's magnetics are modeled using a permeance model. Its design parameters are determined by optimization using the Broyden-Fletcher-Goldfarb-Shanno method and a sequential quadratic programming algorithm. After the VCM is designed, the dynamic focusing unit is fabricated and assembled. The permeance model is verified by a magnetic finite element method simulation tool, Maxwell 2D and 3D, and by measurement data from a gauss meter. The performance is verified experimentally. The results show a resolution of 0.2 μm and travel range of 16 mm. These are better than those of conventional focusing systems; therefore, this focusing unit can be applied to laser scanning systems for good machining capability.

Design of voice coil motor dynamic focusing unit for a laser scanner.

PubMed

Lee, Moon G; Kim, Gaeun; Lee, Chan-Woo; Lee, Soo-Hun; Jeon, Yongho

2014-04-01

Laser scanning systems have been used for material processing tasks such as welding, cutting, marking, and drilling. However, applications have been limited by the small range of motion and slow speed of the focusing unit, which carries the focusing optics. To overcome these limitations, a dynamic focusing system with a long travel range and high speed is needed. In this study, a dynamic focusing unit for a laser scanning system with a voice coil motor (VCM) mechanism is proposed to enable fast speed and a wide focusing range. The VCM has finer precision and higher speed than conventional step motors and a longer travel range than earlier lead zirconium titanate actuators. The system has a hollow configuration to provide a laser beam path. This also makes it compact and transmission-free and gives it low inertia. The VCM's magnetics are modeled using a permeance model. Its design parameters are determined by optimization using the Broyden-Fletcher-Goldfarb-Shanno method and a sequential quadratic programming algorithm. After the VCM is designed, the dynamic focusing unit is fabricated and assembled. The permeance model is verified by a magnetic finite element method simulation tool, Maxwell 2D and 3D, and by measurement data from a gauss meter. The performance is verified experimentally. The results show a resolution of 0.2 μm and travel range of 16 mm. These are better than those of conventional focusing systems; therefore, this focusing unit can be applied to laser scanning systems for good machining capability.

Improved laser-based triangulation sensor with enhanced range and resolution through adaptive optics-based active beam control.

PubMed

Reza, Syed Azer; Khwaja, Tariq Shamim; Mazhar, Mohsin Ali; Niazi, Haris Khan; Nawab, Rahma

2017-07-20

Various existing target ranging techniques are limited in terms of the dynamic range of operation and measurement resolution. These limitations arise as a result of a particular measurement methodology, the finite processing capability of the hardware components deployed within the sensor module, and the medium through which the target is viewed. Generally, improving the sensor range adversely affects its resolution and vice versa. Often, a distance sensor is designed for an optimal range/resolution setting depending on its intended application. Optical triangulation is broadly classified as a spatial-signal-processing-based ranging technique and measures target distance from the location of the reflected spot on a position sensitive detector (PSD). In most triangulation sensors that use lasers as a light source, beam divergence-which severely affects sensor measurement range-is often ignored in calculations. In this paper, we first discuss in detail the limitations to ranging imposed by beam divergence, which, in effect, sets the sensor dynamic range. Next, we show how the resolution of laser-based triangulation sensors is limited by the interpixel pitch of a finite-sized PSD. In this paper, through the use of tunable focus lenses (TFLs), we propose a novel design of a triangulation-based optical rangefinder that improves both the sensor resolution and its dynamic range through adaptive electronic control of beam propagation parameters. We present the theory and operation of the proposed sensor and clearly demonstrate a range and resolution improvement with the use of TFLs. Experimental results in support of our claims are shown to be in strong agreement with theory.

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic processes.

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses.

PubMed

Zhang, Bingbing; Wang, Zhengtao; Zhou, Lv; Feng, Jiandi; Qiu, Yaodong; Li, Fupeng

2017-03-20

Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1-25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs) released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD) of 10 -2 mm/s in radial (R), along-track (T) and cross-track (N) directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD). During high ionospheric activity, the mean Root Mean Square (RMS) of Swarm GPS phase residuals is at 9-11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2-4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR) validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2-4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery.

Impact of dynamic distribution of floc particles on flocculation effect.

PubMed

Nan, Jun; He, Weipeng; Song, Xinin; Li, Guibai

2009-01-01

Polyaluminum chloride (PAC) was used as coagulant and suspended particles in kaolin water. Online instruments including turbidimeter and particle counter were used to monitor the flocculation process. An evaluation model for demonstrating the impact on the flocculation effect was established based on the multiple linear regression analysis method. The parameter of the index weight of channels quantitatively described how the variation of floc particle population in different size ranges cause the decrement of turbidity. The study showed that the floc particles in different size ranges contributed differently to the decrease of turbidity and that the index weight of channel could excellently indicate the impact degree of floc particles dynamic distribution on flocculation effect. Therefore, the parameter may significantly benefit the development of coagulation and sedimentation techniques as well as the optimal coagulant selection.

A Graphics Processing Unit Implementation of Coulomb Interaction in Molecular Dynamics.

PubMed

Jha, Prateek K; Sknepnek, Rastko; Guerrero-García, Guillermo Iván; Olvera de la Cruz, Monica

2010-10-12

We report a GPU implementation in HOOMD Blue of long-range electrostatic interactions based on the orientation-averaged Ewald sum scheme, introduced by Yakub and Ronchi (J. Chem. Phys. 2003, 119, 11556). The performance of the method is compared to an optimized CPU version of the traditional Ewald sum available in LAMMPS, in the molecular dynamics of electrolytes. Our GPU implementation is significantly faster than the CPU implementation of the Ewald method for small to a sizable number of particles (∼10(5)). Thermodynamic and structural properties of monovalent and divalent hydrated salts in the bulk are calculated for a wide range of ionic concentrations. An excellent agreement between the two methods was found at the level of electrostatic energy, heat capacity, radial distribution functions, and integrated charge of the electrolytes.

In-flight performance optimization for rotorcraft with redundant controls

NASA Astrophysics Data System (ADS)

Ozdemir, Gurbuz Taha

A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to establish a schedule. The method has been expanded to search a two-dimensional control space. Simulation results demonstrate the ability to maximize range by optimizing stabilator deflection and an airspeed set point. Another set of results minimize power required in high speed flight by optimizing collective pitch and stabilator deflection. Results show that the control laws effectively hold the flight condition while the FTO method is effective at improving performance. Optimizations show there can be issues when the control laws regulating altitude push the collective control towards it limits. So a modification was made to the control law to regulate airspeed and altitude using propeller pitch and angle of attack while the collective is held fixed or used as an optimization variable. A dynamic trim limit avoidance algorithm is applied to avoid control saturation in other axes during optimization maneuvers. Range and power optimization FTO simulations are compared with comprehensive sweeps of trim solutions and FTO optimization shown to be effective and reliable in reaching an optimal when optimizing up to two redundant controls. Use of redundant controls is shown to be beneficial for improving performance. The search method takes almost 25 minutes of simulated flight for optimization to be complete. The optimization maneuver itself can sometimes drive the power required to high values, so a power limit is imposed to restrict the search to avoid conditions where power is more than5% higher than that of the initial trim state. With this modification, the time the optimization maneuver takes to complete is reduced down to 21 minutes without any significant change in the optimal power value.

The Influences of Lamination Angles on the Interior Noise Levels of an Aircraft

NASA Technical Reports Server (NTRS)

Fernholz, Christian M.; Robinson, Jay H.

1996-01-01

The feasibility of reducing the interior noise levels of an aircraft passenger cabin through optimization of the composite lay up of the fuselage is investigated. MSC/NASTRAN, a commercially available finite element code, is used to perform the dynamic analysis and subsequent optimization of the fuselage. The numerical calculation of sensitivity of acoustic pressure to lamination angle is verified using a simple thin, cylindrical shell with point force excitations as noise sources. The thin shell used represents a geometry similar to the fuselage and analytic solutions are available for the cylindrical thin shell equations of motion. Optimization of lamination angle for the reduction of interior noise is performed using a finite element model of an actual aircraft fuselage. The aircraft modeled for this study is the Beech Starship. Point forces simulate the structure borne noise produced by the engines and are applied to the fuselage at the wing mounting locations. These forces are the noise source for the optimization problem. The acoustic pressure response is reduced at a number of points in the fuselage and over a number of frequencies. The objective function is minimized with the constraint that it be larger than the maximum sound pressure level at the response points in the passenger cabin for all excitation frequencies in the range of interest. Results from the study of the fuselage model indicate that a reduction in interior noise levels is possible over a finite frequency range through optimal configuration of the lamination angles in the fuselage. Noise reductions of roughly 4 dB were attained. For frequencies outside the optimization range, the acoustic pressure response may increase after optimization. The effects of changing lamination angle on the overall structural integrity of the airframe are not considered in this study.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin: Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry.

PubMed

Mondal, Milon; Radeva, Nedyalka; Fanlo-Virgós, Hugo; Otto, Sijbren; Klebe, Gerhard; Hirsch, Anna K H

2016-08-01

Fragment-based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit-identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X-ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis-acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240-fold improvement in potency compared to the parent hits. Subsequent X-ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit-identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit-to-lead optimization. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Three-dimensional Finite Element Formulation and Scalable Domain Decomposition for High Fidelity Rotor Dynamic Analysis

NASA Technical Reports Server (NTRS)

Datta, Anubhav; Johnson, Wayne R.

2009-01-01

This paper has two objectives. The first objective is to formulate a 3-dimensional Finite Element Model for the dynamic analysis of helicopter rotor blades. The second objective is to implement and analyze a dual-primal iterative substructuring based Krylov solver, that is parallel and scalable, for the solution of the 3-D FEM analysis. The numerical and parallel scalability of the solver is studied using two prototype problems - one for ideal hover (symmetric) and one for a transient forward flight (non-symmetric) - both carried out on up to 48 processors. In both hover and forward flight conditions, a perfect linear speed-up is observed, for a given problem size, up to the point of substructure optimality. Substructure optimality and the linear parallel speed-up range are both shown to depend on the problem size as well as on the selection of the coarse problem. With a larger problem size, linear speed-up is restored up to the new substructure optimality. The solver also scales with problem size - even though this conclusion is premature given the small prototype grids considered in this study.

Dynamic model of temperature impact on cell viability and major product formation during fed-batch and continuous ethanolic fermentation in Saccharomyces cerevisiae.

PubMed

Amillastre, Emilie; Aceves-Lara, César-Arturo; Uribelarrea, Jean-Louis; Alfenore, Sandrine; Guillouet, Stéphane E

2012-08-01

The impact of the temperature on an industrial yeast strain was investigated in very high ethanol performance fermentation fed-batch process within the range of 30-47 °C. As previously observed with a lab strain, decoupling between growth and glycerol formation occurred at temperature of 36 °C and higher. A dynamic model was proposed to describe the impact of the temperature on the total and viable biomass, ethanol and glycerol production. The model validation was implemented with experimental data sets from independent cultures under different temperatures, temperature variation profiles and cultivation modes. The proposed model fitted accurately the dynamic evolutions for products and biomass concentrations over a wide range of temperature profiles. R2 values were above 0.96 for ethanol and glycerol in most experiments. The best results were obtained at 37 °C in fed-batch and chemostat cultures. This dynamic model could be further used for optimizing and monitoring the ethanol fermentation at larger scale. Copyright © 2012 Elsevier Ltd. All rights reserved.

Programmable synaptic devices for electronic neural nets

NASA Technical Reports Server (NTRS)

Moopenn, A.; Thakoor, A. P.

1990-01-01

The architecture, design, and operational characteristics of custom VLSI and thin film synaptic devices are described. The devices include CMOS-based synaptic chips containing 1024 reprogrammable synapses with a 6-bit dynamic range, and nonvolatile, write-once, binary synaptic arrays based on memory switching in hydrogenated amorphous silicon films. Their suitability for embodiment of fully parallel and analog neural hardware is discussed. Specifically, a neural network solution to an assignment problem of combinatorial global optimization, implemented in fully parallel hardware using the synaptic chips, is described. The network's ability to provide optimal and near optimal solutions over a time scale of few neuron time constants has been demonstrated and suggests a speedup improvement of several orders of magnitude over conventional search methods.

The research of conformal optical design

NASA Astrophysics Data System (ADS)

Li, Lin; Li, Yan; Huang, Yi-fan; Du, Bao-lin

2009-07-01

Conformal optical domes are characterized as having external more elongated optical surfaces that are optimized to minimize drag, increased missile velocity and extended operational range. The outer surface of the conformal domes typically deviate greatly from spherical surface descriptions, so the inherent asymmetry of conformal surfaces leads to variations in the aberration content presented to the optical sensor as it is gimbaled across the field of regard, which degrades the sensor's ability to properly image targets of interest and then undermine the overall system performance. Consequently, the aerodynamic advantages of conformal domes cannot be realized in practical systems unless the dynamic aberration correction techniques are developed to restore adequate optical imaging capabilities. Up to now, many optical correction solutions have been researched in conformal optical design, including static aberrations corrections and dynamic aberrations corrections. There are three parts in this paper. Firstly, the combination of static and dynamic aberration correction is introduced. A system for correcting optical aberration created by a conformal dome has an outer surface and an inner surface. The optimization of the inner surface is regard as the static aberration correction; moreover, a deformable mirror is placed at the position of the secondary mirror in the two-mirror all reflective imaging system, which is the dynamic aberration correction. Secondly, the using of appropriate surface types is very important in conformal dome design. Better performing optical systems can result from surface types with adequate degrees of freedom to describe the proper corrector shape. Two surface types and the methods of using them are described, including Zernike polynomial surfaces used in correct elements and user-defined surfaces used in deformable mirror (DM). Finally, the Adaptive optics (AO) correction is presented. In order to correct the dynamical residual aberration in conformal optical design, the SPGD optimization algorithm is operated at each zoom position to calculate the optimized surface shape of the MEMS DM. The communication between MATLAB and Code V established via ActiveX technique is applied in simulation analysis.

An upstream burst-mode equalization scheme for 40 Gb/s TWDM PON based on optimized SOA cascade

NASA Astrophysics Data System (ADS)

Sun, Xiao; Chang, Qingjiang; Gao, Zhensen; Ye, Chenhui; Xiao, Simiao; Huang, Xiaoan; Hu, Xiaofeng; Zhang, Kaibin

2016-02-01

We present a novel upstream burst-mode equalization scheme based on optimized SOA cascade for 40 Gb/s TWDMPON. The power equalizer is placed at the OLT which consists of two SOAs, two circulators, an optical NOT gate, and a variable optical attenuator. The first SOA operates in the linear region which acts as a pre-amplifier to let the second SOA operate in the saturation region. The upstream burst signals are equalized through the second SOA via nonlinear amplification. From theoretical analysis, this scheme gives sufficient dynamic range suppression up to 16.7 dB without any dynamic control or signal degradation. In addition, a total power budget extension of 9.3 dB for loud packets and 26 dB for soft packets has been achieved to allow longer transmission distance and increased splitting ratio.

Autostereoscopic 3D display system with dynamic fusion of the viewing zone under eye tracking: principles, setup, and evaluation [Invited].

PubMed

Yoon, Ki-Hyuk; Kang, Min-Koo; Lee, Hwasun; Kim, Sung-Kyu

2018-01-01

We study optical technologies for viewer-tracked autostereoscopic 3D display (VTA3D), which provides improved 3D image quality and extended viewing range. In particular, we utilize a technique-the so-called dynamic fusion of viewing zone (DFVZ)-for each 3D optical line to realize image quality equivalent to that achievable at optimal viewing distance, even when a viewer is moving in a depth direction. In addition, we examine quantitative properties of viewing zones provided by the VTA3D system that adopted DFVZ, revealing that the optimal viewing zone can be formed at viewer position. Last, we show that the comfort zone is extended due to DFVZ. This is demonstrated by a viewer's subjective evaluation of the 3D display system that employs both multiview autostereoscopic 3D display and DFVZ.

The paradox of enrichment in an adaptive world

PubMed Central

Mougi, Akihiko; Nishimura, Kinya

2008-01-01

Paradoxically, enrichment can destabilize a predator–prey food web. While adaptive dynamics can greatly influence the stability of interaction systems, few theoretical studies have examined the effect of the adaptive dynamics of interaction-related traits on the possibility of resolution of the paradox of enrichment. We consider the evolution of attack and defence traits of a predator and two prey species in a one predator–two prey system in which the predator practises optimal diet use. The results showed that optimal foraging alone cannot eliminate a pattern of destabilization with enrichment, but trait evolution of the predator or prey can change the pattern to one of stabilization, implying a possible resolution of the paradox of enrichment. Furthermore, trait evolution in all species can broaden the parameter range of stabilization. Importantly, rapid evolution can stabilize this system, but weaken its stability in the face of enrichment. PMID:18700201

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

Robust Dynamic Multi-objective Vehicle Routing Optimization Method.

PubMed

Guo, Yi-Nan; Cheng, Jian; Luo, Sha; Gong, Dun-Wei

2017-03-21

For dynamic multi-objective vehicle routing problems, the waiting time of vehicle, the number of serving vehicles, the total distance of routes were normally considered as the optimization objectives. Except for above objectives, fuel consumption that leads to the environmental pollution and energy consumption was focused on in this paper. Considering the vehicles' load and the driving distance, corresponding carbon emission model was built and set as an optimization objective. Dynamic multi-objective vehicle routing problems with hard time windows and randomly appeared dynamic customers, subsequently, were modeled. In existing planning methods, when the new service demand came up, global vehicle routing optimization method was triggered to find the optimal routes for non-served customers, which was time-consuming. Therefore, robust dynamic multi-objective vehicle routing method with two-phase is proposed. Three highlights of the novel method are: (i) After finding optimal robust virtual routes for all customers by adopting multi-objective particle swarm optimization in the first phase, static vehicle routes for static customers are formed by removing all dynamic customers from robust virtual routes in next phase. (ii)The dynamically appeared customers append to be served according to their service time and the vehicles' statues. Global vehicle routing optimization is triggered only when no suitable locations can be found for dynamic customers. (iii)A metric measuring the algorithms' robustness is given. The statistical results indicated that the routes obtained by the proposed method have better stability and robustness, but may be sub-optimum. Moreover, time-consuming global vehicle routing optimization is avoided as dynamic customers appear.

Multidisciplinary Shape Optimization of a Composite Blended Wing Body Aircraft

NASA Astrophysics Data System (ADS)

Boozer, Charles Maxwell

A multidisciplinary shape optimization tool coupling aerodynamics, structure, and performance was developed for battery powered aircraft. Utilizing high-fidelity computational fluid dynamics analysis tools and a structural wing weight tool, coupled based on the multidisciplinary feasible optimization architecture; aircraft geometry is modified in the optimization of the aircraft's range or endurance. The developed tool is applied to three geometries: a hybrid blended wing body, delta wing UAS, the ONERA M6 wing, and a modified ONERA M6 wing. First, the optimization problem is presented with the objective function, constraints, and design vector. Next, the tool's architecture and the analysis tools that are utilized are described. Finally, various optimizations are described and their results analyzed for all test subjects. Results show that less computationally expensive inviscid optimizations yield positive performance improvements using planform, airfoil, and three-dimensional degrees of freedom. From the results obtained through a series of optimizations, it is concluded that the newly developed tool is both effective at improving performance and serves as a platform ready to receive additional performance modules, further improving its computational design support potential.

Evolutionary dynamics of host-plant specialization: a case study of the tribe Nymphalini.

PubMed

Janz, N; Nyblom, K; Nylin, S

2001-04-01

Two general patterns that have emerged from the intense studies on insect-host plant associations are a predominance of specialists over generalists and a taxonomic conservatism in host-plant use. In most insect-host plant systems, explanations for these patterns must be based on biases in the processes of host colonizations, host shifts, and specialization, rather than cospeciation. In the present paper, we investigate changes in host range in the nymphalid butterfly tribe Nymphalini, using parsimony optimizations of host-plant data on the butterfly phylogeny. In addition, we performed larval establishment tests to search for larval capacity to feed and survive on plants that have been lost from the female egg-laying repertoire. Optimizations suggested an ancestral association with Urticaceae, and most of the tested species showed a capacity to feed on Urtica dioica regardless of actual host-plant use. In addition, there was a bias among the successful establishments on nonhosts toward plants that are used as hosts by other species in the Nymphalini. An increased likelihood of colonizing ancestral or related plants could also provide an alternative explanation for the observed pattern that some plant families appear to have been colonized independently several times in the tribe. We also show that there is no directionality in host range evolution toward increased specialization, that is, specialization is not a dead end. Instead, changes in host range show a very dynamic pattern.

Contribution of limb momentum to power transfer in athletic wheelchair pushing.

PubMed

Masson, G; Bégin, M-A; Lopez Poncelas, M; Pelletier, S-K; Lessard, J-L; Laroche, J; Berrigan, F; Langelier, E; Smeesters, C; Rancourt, D

2016-09-06

Pushing capacity is a key parameter in athletic racing wheelchair performance. This study estimated the potential contribution of upper limb momentum to pushing. The question is relevant since it may affect the training strategy adopted by an athlete. A muscle-free Lagrangian dynamic model of the upper limb segments was developed and theoretical predictions of power transfer to the wheelchair were computed during the push phase. Results show that limb momentum capacity for pushing can be in the order of 40J per push cycle at 10m/s, but it varies with the specific pushing range chosen by the athlete. Although use of momentum could certainly help an athlete improve performance, quantifying the actual contribution of limb momentum to pushing is not trivial. A preliminary experimental investigation on an ergometer, along with a simplified model of the upper limb, suggests that momentum is not the sole contributor to power transfer to a wheelchair. Muscles substantially contribute to pushing, even at high speeds. Moreover, an optimal pushing range is challenging to find since it most likely differs if an athlete chooses a limb momentum pushing strategy versus a muscular exertion pushing strategy, or both at the same time. The study emphasizes the importance of controlling pushing range, although one should optimize it while also taking the dynamics of the recovery period into account. Copyright © 2016 Elsevier Ltd. All rights reserved.

Energy efficient sensor scheduling with a mobile sink node for the target tracking application.

PubMed

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance.

Energy Efficient Sensor Scheduling with a Mobile Sink Node for the Target Tracking Application

PubMed Central

Maheswararajah, Suhinthan; Halgamuge, Saman; Premaratne, Malin

2009-01-01

Measurement losses adversely affect the performance of target tracking. The sensor network's life span depends on how efficiently the sensor nodes consume energy. In this paper, we focus on minimizing the total energy consumed by the sensor nodes whilst avoiding measurement losses. Since transmitting data over a long distance consumes a significant amount of energy, a mobile sink node collects the measurements and transmits them to the base station. We assume that the default transmission range of the activated sensor node is limited and it can be increased to maximum range only if the mobile sink node is out-side the default transmission range. Moreover, the active sensor node can be changed after a certain time period. The problem is to select an optimal sensor sequence which minimizes the total energy consumed by the sensor nodes. In this paper, we consider two different problems depend on the mobile sink node's path. First, we assume that the mobile sink node's position is known for the entire time horizon and use the dynamic programming technique to solve the problem. Second, the position of the sink node is varied over time according to a known Markov chain, and the problem is solved by stochastic dynamic programming. We also present sub-optimal methods to solve our problem. A numerical example is presented in order to discuss the proposed methods' performance PMID:22399934

Determination of volatile organic compounds in pen inks by a dynamic headspace needle trap device combined with gas chromatography-mass spectrometry.

PubMed

Zang, Xiaohuan; Liang, Weiqian; Chang, Qingyun; Wu, Tong; Wang, Chun; Wang, Zhi

2017-09-01

Some harmful volatile organic compounds (VOCs), such as methylbenzene, ethylbenzene, xylene, chlorobenzene and bromobenzene, are the commonly found chemicals in pen inks. In this work, a dynamic headspace needle-trap device (D-HS-NTD) with a ZIF-8-derived nanoporous carbon (ZIF-8-NPC) as the adsorbent was developed for the extraction of some VOCs in different pen inks prior to GC-MS detection. The main important influencing experimental parameters including the flow rate of the purge gas N 2 , extraction temperature, extraction time, desorption temperature and desorption time for the extraction were optimized to obtain a high extraction efficiency. Under the optimized conditions, a good linearity was obtained in the concentration range of 0.1-400μgkg -1 with the correlation coefficients (r) ranging from 0.9911 to 0.9990 for the eleven VOCs. The LODs at a signal-to-noise ratio of 3 (S/N=3) were measured to be 10-20ngkg -1 for the VOCs. The developed method was applied to determine the VOCs from 20 pen inks. The recoveries of the VOCs for the method at the spiking levels of 0.5 and 20.0μgkg -1 fell in the range from 80.0% to 108%. Copyright © 2017. Published by Elsevier B.V.

Analysis and design of a genetic circuit for dynamic metabolic engineering.

PubMed

Anesiadis, Nikolaos; Kobayashi, Hideki; Cluett, William R; Mahadevan, Radhakrishnan

2013-08-16

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Online optimization of storage ring nonlinear beam dynamics

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

Huang, Xiaobiao; Safranek, James

2015-08-01

We propose to optimize the nonlinear beam dynamics of existing and future storage rings with direct online optimization techniques. This approach may have crucial importance for the implementation of diffraction limited storage rings. In this paper considerations and algorithms for the online optimization approach are discussed. We have applied this approach to experimentally improve the dynamic aperture of the SPEAR3 storage ring with the robust conjugate direction search method and the particle swarm optimization method. The dynamic aperture was improved by more than 5 mm within a short period of time. Experimental setup and results are presented.

Magnetic bearing design and control optimization for a four-stage centrifugal compressor

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

Pinckney, F.D.; Keesee, J.M.

1992-07-01

A four-stage centrifugal pipeline compressor with a flexible rotor was equipped with magnetic bearings. Magnetic bearing sizing, shaft rotor dynamics, and controller/bearing design are discussed. Controller changes during shop and field tuning and the resulting rotor dynamic effects are also presented. Results of the field operation of this compressor indicate no vibration-related problems, despite the shaft second and third undamped modes being within the operating speed range. During the first 14 months after field commissioning, 9900 operating hours had been accumulated, indicating a 97 percent unit availability. 6 refs.

Predictive display design for the vehicles with time delay in dynamic response

NASA Astrophysics Data System (ADS)

Efremov, A. V.; Tiaglik, M. S.; Irgaleev, I. H.; Efremov, E. V.

2018-02-01

The two ways for the improvement of flying qualities are considered: the predictive display (PD) and the predictive display integrated with the flight control system (FCS). The both ways allow to transforming the controlled element dynamics in the crossover frequency range, to improve the accuracy of tracking and to suppress the effect of time delay in the vehicle response too. The technique for optimization of the predictive law is applied to the landing task. The results of the mathematical modeling and experimental investigations carried out for this task are considered in the paper.

Generalized extended Lagrangian Born-Oppenheimer molecular dynamics

DOE PAGES

Niklasson, Anders M. N.; Cawkwell, Marc J.

2014-10-29

Extended Lagrangian Born-Oppenheimer molecular dynamics based on Kohn-Sham density functional theory is generalized in the limit of vanishing self-consistent field optimization prior to the force evaluations. The equations of motion are derived directly from the extended Lagrangian under the condition of an adiabatic separation between the nuclear and the electronic degrees of freedom. We show how this separation is automatically fulfilled and system independent. The generalized equations of motion require only one diagonalization per time step and are applicable to a broader range of materials with improved accuracy and stability compared to previous formulations.

A limited host immune range facilitates the creation and maintenance of diversity in parasite virulence

PubMed Central

Best, Alex; Hoyle, Andy

2013-01-01

A vast theoretical literature has explored the evolutionary dynamics of parasite virulence. The classic result from this modelling work is that, assuming a saturating transmission–virulence trade-off, there is a single evolutionary optimum where the parasite optimizes the epidemiological R0. However, there are an increasing number of models that have shown how ecological and epidemiological feedbacks to evolution can instead result in the creation and maintenance of multiple parasite strains. Here, we fully explore one such example, where recovered hosts have a limited ‘immune range’ resulting in partial cross-immunity to parasite strains that they have not previously encountered. Taking an adaptive dynamics approach, we show that, provided this immune range is not too wide, high levels of diversity can evolve and be maintained through multiple branching events. We argue that our model provides a more realistic picture of disease dynamics in vertebrate host populations and may be a key explanatory factor in the high levels of parasite diversity seen in natural systems. PMID:24516712

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.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Role of Interactions and Correlations on Collective Dynamics of Molecular Motors Along Parallel Filaments

NASA Astrophysics Data System (ADS)

Midha, Tripti; Gupta, Arvind Kumar

2017-11-01

Cytoskeletal motors known as motor proteins are molecules that drive cellular transport along several parallel cytoskeletal filaments and support many biological processes. Experimental evidences suggest that they interact with the nearest molecules of their filament while performing any mechanical work. These interactions modify the microscopic level properties of motor proteins. In this work, a new version of two-channel totally asymmetric simple exclusion process, that incorporates the intra-channel interactions in a thermodynamically consistent way, is proposed. As the existing approaches for multi-channel systems deviate from analyzing the combined effect of inter and intra-channel interactions, a new approach known as modified vertical cluster mean field is developed. The approach along with Monte Carlo simulations successfully encounters some correlations and computes the complex dynamic properties of the system. Role of symmetry of interactions and inter-channel coupling is observed on the phase diagrams, maximal particle current and its corresponding optimal interaction strength. Surprisingly, for all values of coupling rate and most of the interaction splittings, the optimal interaction strength corresponding to maximal current belongs to the case of weak repulsive interactions. Moreover, for weak interaction splittings and with an increase in the coupling rate, the optimal interaction strength tends towards the known experimental results. The effect of coupling as well as interaction energy is also measured for correlations. They are found to be short-range and weaker for repulsive and weak attractive interactions while they are long-range and stronger for large attractions.

Ab Initio and Monte Carlo Approaches For the MagnetocaloricEffect in Co- and In-Doped Ni-Mn-Ga Heusler Alloys

NASA Astrophysics Data System (ADS)

Sokolovskiy, Vladimir; Grünebohm, Anna; Buchelnikov, Vasiliy; Entel, Peter

2014-09-01

This special issue collects contributions from the participants of the "Information in Dynamical Systems and Complex Systems" workshop, which cover a wide range of important problems and new approaches that lie in the intersection of information theory and dynamical systems. The contributions include theoretical characterization and understanding of the different types of information flow and causality in general stochastic processes, inference and identification of coupling structure and parameters of system dynamics, rigorous coarse-grain modeling of network dynamical systems, and exact statistical testing of fundamental information-theoretic quantities such as the mutual information. The collective efforts reported herein reflect a modern perspective of the intimate connection between dynamical systems and information flow, leading to the promise of better understanding and modeling of natural complex systems and better/optimal design of engineering systems.

Recent advances in integrated multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Walsh, Joanne L.; Pritchard, Jocelyn I.

1992-01-01

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Recent advances in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Walsh, Joanne L.; Pritchard, Jocelyn I.

1992-01-01

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Optimization under variability and uncertainty: a case study for NOx emissions control for a gasification system.

PubMed

Chen, Jianjun; Frey, H Christopher

2004-12-15

Methods for optimization of process technologies considering the distinction between variability and uncertainty are developed and applied to case studies of NOx control for Integrated Gasification Combined Cycle systems. Existing methods of stochastic optimization (SO) and stochastic programming (SP) are demonstrated. A comparison of SO and SP results provides the value of collecting additional information to reduce uncertainty. For example, an expected annual benefit of 240,000 dollars is estimated if uncertainty can be reduced before a final design is chosen. SO and SP are typically applied to uncertainty. However, when applied to variability, the benefit of dynamic process control is obtained. For example, an annual savings of 1 million dollars could be achieved if the system is adjusted to changes in process conditions. When variability and uncertainty are treated distinctively, a coupled stochastic optimization and programming method and a two-dimensional stochastic programming method are demonstrated via a case study. For the case study, the mean annual benefit of dynamic process control is estimated to be 700,000 dollars, with a 95% confidence range of 500,000 dollars to 940,000 dollars. These methods are expected to be of greatest utility for problems involving a large commitment of resources, for which small differences in designs can produce large cost savings.

Phase Transitions in Living Neural Networks

NASA Astrophysics Data System (ADS)

Williams-Garcia, Rashid Vladimir

Our nervous systems are composed of intricate webs of interconnected neurons interacting in complex ways. These complex interactions result in a wide range of collective behaviors with implications for features of brain function, e.g., information processing. Under certain conditions, such interactions can drive neural network dynamics towards critical phase transitions, where power-law scaling is conjectured to allow optimal behavior. Recent experimental evidence is consistent with this idea and it seems plausible that healthy neural networks would tend towards optimality. This hypothesis, however, is based on two problematic assumptions, which I describe and for which I present alternatives in this thesis. First, critical transitions may vanish due to the influence of an environment, e.g., a sensory stimulus, and so living neural networks may be incapable of achieving "critical" optimality. I develop a framework known as quasicriticality, in which a relative optimality can be achieved depending on the strength of the environmental influence. Second, the power-law scaling supporting this hypothesis is based on statistical analysis of cascades of activity known as neuronal avalanches, which conflate causal and non-causal activity, thus confounding important dynamical information. In this thesis, I present a new method to unveil causal links, known as causal webs, between neuronal activations, thus allowing for experimental tests of the quasicriticality hypothesis and other practical applications.

OPTIMAL AIRCRAFT TRAJECTORIES FOR SPECIFIED RANGE

NASA Technical Reports Server (NTRS)

Lee, H.

1994-01-01

For an aircraft operating over a fixed range, the operating costs are basically a sum of fuel cost and time cost. While minimum fuel and minimum time trajectories are relatively easy to calculate, the determination of a minimum cost trajectory can be a complex undertaking. This computer program was developed to optimize trajectories with respect to a cost function based on a weighted sum of fuel cost and time cost. As a research tool, the program could be used to study various characteristics of optimum trajectories and their comparison to standard trajectories. It might also be used to generate a model for the development of an airborne trajectory optimization system. The program could be incorporated into an airline flight planning system, with optimum flight plans determined at takeoff time for the prevailing flight conditions. The use of trajectory optimization could significantly reduce the cost for a given aircraft mission. The algorithm incorporated in the program assumes that a trajectory consists of climb, cruise, and descent segments. The optimization of each segment is not done independently, as in classical procedures, but is performed in a manner which accounts for interaction between the segments. This is accomplished by the application of optimal control theory. The climb and descent profiles are generated by integrating a set of kinematic and dynamic equations, where the total energy of the aircraft is the independent variable. At each energy level of the climb and descent profiles, the air speed and power setting necessary for an optimal trajectory are determined. The variational Hamiltonian of the problem consists of the rate of change of cost with respect to total energy and a term dependent on the adjoint variable, which is identical to the optimum cruise cost at a specified altitude. This variable uniquely specifies the optimal cruise energy, cruise altitude, cruise Mach number, and, indirectly, the climb and descent profiles. If the optimum cruise cost is specified, an optimum trajectory can easily be generated; however, the range obtained for a particular optimum cruise cost is not known a priori. For short range flights, the program iteratively varies the optimum cruise cost until the computed range converges to the specified range. For long-range flights, iteration is unnecessary since the specified range can be divided into a cruise segment distance and full climb and descent distances. The user must supply the program with engine fuel flow rate coefficients and an aircraft aerodynamic model. The program currently includes coefficients for the Pratt-Whitney JT8D-7 engine and an aerodynamic model for the Boeing 727. Input to the program consists of the flight range to be covered and the prevailing flight conditions including pressure, temperature, and wind profiles. Information output by the program includes: optimum cruise tables at selected weights, optimal cruise quantities as a function of cruise weight and cruise distance, climb and descent profiles, and a summary of the complete synthesized optimal trajectory. This program is written in FORTRAN IV for batch execution and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 100K (octal) of 60 bit words. This aircraft trajectory optimization program was developed in 1979.

Economical Unsteady High-Fidelity Aerodynamics for Structural Optimization with a Flutter Constraint

NASA Technical Reports Server (NTRS)

Bartels, Robert E.; Stanford, Bret K.

2017-01-01

Structural optimization with a flutter constraint for a vehicle designed to fly in the transonic regime is a particularly difficult task. In this speed range, the flutter boundary is very sensitive to aerodynamic nonlinearities, typically requiring high-fidelity Navier-Stokes simulations. However, the repeated application of unsteady computational fluid dynamics to guide an aeroelastic optimization process is very computationally expensive. This expense has motivated the development of methods that incorporate aspects of the aerodynamic nonlinearity, classical tools of flutter analysis, and more recent methods of optimization. While it is possible to use doublet lattice method aerodynamics, this paper focuses on the use of an unsteady high-fidelity aerodynamic reduced order model combined with successive transformations that allows for an economical way of utilizing high-fidelity aerodynamics in the optimization process. This approach is applied to the common research model wing structural design. As might be expected, the high-fidelity aerodynamics produces a heavier wing than that optimized with doublet lattice aerodynamics. It is found that the optimized lower skin of the wing using high-fidelity aerodynamics differs significantly from that using doublet lattice aerodynamics.

Promoting Affordability in Defense Acquisitions: A Multi-Period Portfolio Approach

DTIC Science & Technology

2014-04-30

has evolved out of many areas of research, ranging from economics to modern control theory (Powell, 2011). The general form of a dynamic programming...states 5 School of Aeronautics & Astronautics A Portfolio Approach: Background • Balance expected profit (performance) against risk ( variance ) in...investments (Markowitz 1952) • Efficiency frontier of optimal portfolios given investor risk averseness • Extends to multi-period case with various

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Design of voice coil motor dynamic focusing unit for a laser scanner

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

Lee, Moon G.; Kim, Gaeun; Lee, Chan-Woo

2014-04-15

Laser scanning systems have been used for material processing tasks such as welding, cutting, marking, and drilling. However, applications have been limited by the small range of motion and slow speed of the focusing unit, which carries the focusing optics. To overcome these limitations, a dynamic focusing system with a long travel range and high speed is needed. In this study, a dynamic focusing unit for a laser scanning system with a voice coil motor (VCM) mechanism is proposed to enable fast speed and a wide focusing range. The VCM has finer precision and higher speed than conventional step motorsmore » and a longer travel range than earlier lead zirconium titanate actuators. The system has a hollow configuration to provide a laser beam path. This also makes it compact and transmission-free and gives it low inertia. The VCM's magnetics are modeled using a permeance model. Its design parameters are determined by optimization using the Broyden–Fletcher–Goldfarb–Shanno method and a sequential quadratic programming algorithm. After the VCM is designed, the dynamic focusing unit is fabricated and assembled. The permeance model is verified by a magnetic finite element method simulation tool, Maxwell 2D and 3D, and by measurement data from a gauss meter. The performance is verified experimentally. The results show a resolution of 0.2 μm and travel range of 16 mm. These are better than those of conventional focusing systems; therefore, this focusing unit can be applied to laser scanning systems for good machining capability.« less

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

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

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the controlmore » of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.« less

3D sensor placement strategy using the full-range pheromone ant colony system

NASA Astrophysics Data System (ADS)

Shuo, Feng; Jingqing, Jia

2016-07-01

An optimized sensor placement strategy will be extremely beneficial to ensure the safety and cost reduction considerations of structural health monitoring (SHM) systems. The sensors must be placed such that important dynamic information is obtained and the number of sensors is minimized. The practice is to select individual sensor directions by several 1D sensor methods and the triaxial sensors are placed in these directions for monitoring. However, this may lead to non-optimal placement of many triaxial sensors. In this paper, a new method, called FRPACS, is proposed based on the ant colony system (ACS) to solve the optimal placement of triaxial sensors. The triaxial sensors are placed as single units in an optimal fashion. And then the new method is compared with other algorithms using Dalian North Bridge. The computational precision and iteration efficiency of the FRPACS has been greatly improved compared with the original ACS and EFI method.

Design optimization of a high specific speed Francis turbine runner

NASA Astrophysics Data System (ADS)

Enomoto, Y.; Kurosawa, S.; Kawajiri, H.

2012-11-01

Francis turbine is used in many hydroelectric power stations. This paper presents the development of hydraulic performance in a high specific speed Francis turbine runner. In order to achieve the improvements of turbine efficiency throughout a wide operating range, a new runner design method which combines the latest Computational Fluid Dynamics (CFD) and a multi objective optimization method with an existing design system was applied in this study. The validity of the new design system was evaluated by model performance tests. As the results, it was confirmed that the optimized runner presented higher efficiency compared with an originally designed runner. Besides optimization of runner, instability vibration which occurred at high part load operating condition was investigated by model test and gas-liquid two-phase flow analysis. As the results, it was confirmed that the instability vibration was caused by oval cross section whirl which was caused by recirculation flow near runner cone wall.

An Introduction to System-Level, Steady-State and Transient Modeling and Optimization of High-Power-Density Thermoelectric Generator Devices Made of Segmented Thermoelectric Elements

NASA Astrophysics Data System (ADS)

Crane, D. T.

2011-05-01

High-power-density, segmented, thermoelectric (TE) elements have been intimately integrated into heat exchangers, eliminating many of the loss mechanisms of conventional TE assemblies, including the ceramic electrical isolation layer. Numerical models comprising simultaneously solved, nonlinear, energy balance equations have been created to simulate these novel architectures. Both steady-state and transient models have been created in a MATLAB/Simulink environment. The models predict data from experiments in various configurations and applications over a broad range of temperature, flow, and current conditions for power produced, efficiency, and a variety of other important outputs. Using the validated models, devices and systems are optimized using advanced multiparameter optimization techniques. Devices optimized for particular steady-state operating conditions can then be dynamically simulated in a transient operating model. The transient model can simulate a variety of operating conditions including automotive and truck drive cycles.

An Intrinsically Digital Amplification Scheme for Hearing Aids

NASA Astrophysics Data System (ADS)

Blamey, Peter J.; Macfarlane, David S.; Steele, Brenton R.

2005-12-01

Results for linear and wide-dynamic range compression were compared with a new 64-channel digital amplification strategy in three separate studies. The new strategy addresses the requirements of the hearing aid user with efficient computations on an open-platform digital signal processor (DSP). The new amplification strategy is not modeled on prior analog strategies like compression and linear amplification, but uses statistical analysis of the signal to optimize the output dynamic range in each frequency band independently. Using the open-platform DSP processor also provided the opportunity for blind trial comparisons of the different processing schemes in BTE and ITE devices of a high commercial standard. The speech perception scores and questionnaire results show that it is possible to provide improved audibility for sound in many narrow frequency bands while simultaneously improving comfort, speech intelligibility in noise, and sound quality.

Local and Global Bifurcations of Flow Fields During Physical Vapor Transport: Application to a Microgravity Experiment

NASA Technical Reports Server (NTRS)

Duval, W. M. B.; Singh, N. B.; Glicksman, M. E.

1996-01-01

The local bifurcation of the flow field, during physical vapor transport for a parametric range of experimental interest, shows that its dynamical state ranges from steady to aperiodic. Comparison of computationally predicted velocity profiles with laser doppler velocimetry measurements shows reasonable agreement in both magnitude and planform. Correlation of experimentally measured crystal quality with the predicted dynamical state of the flow field shows a degradation of quality with an increase in Rayleigh number. The global bifurcation of the flow field corresponding to low crystal quality indicates the presence of a traveling wave for Ra = 1.09 x 10(exp 5). For this Rayleigh number threshold a chaotic transport state occurs. However, a microgravity environment for this case effectively stabilizes the flow to diffusive-advective and provides the setting to grow crystals with optimal quality.

Multi-objective control of nonlinear boiler-turbine dynamics with actuator magnitude and rate constraints.

PubMed

Chen, Pang-Chia

2013-01-01

This paper investigates multi-objective controller design approaches for nonlinear boiler-turbine dynamics subject to actuator magnitude and rate constraints. System nonlinearity is handled by a suitable linear parameter varying system representation with drum pressure as the system varying parameter. Variation of the drum pressure is represented by suitable norm-bounded uncertainty and affine dependence on system matrices. Based on linear matrix inequality algorithms, the magnitude and rate constraints on the actuator and the deviations of fluid density and water level are formulated while the tracking abilities on the drum pressure and power output are optimized. Variation ranges of drum pressure and magnitude tracking commands are used as controller design parameters, determined according to the boiler-turbine's operation range. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics.

PubMed

Yao, Kun; Herr, John E; Toth, David W; Mckintyre, Ryker; Parkhill, John

2018-02-28

Traditional force fields cannot model chemical reactivity, and suffer from low generality without re-fitting. Neural network potentials promise to address these problems, offering energies and forces with near ab initio accuracy at low cost. However a data-driven approach is naturally inefficient for long-range interatomic forces that have simple physical formulas. In this manuscript we construct a hybrid model chemistry consisting of a nearsighted neural network potential with screened long-range electrostatic and van der Waals physics. This trained potential, simply dubbed "TensorMol-0.1", is offered in an open-source Python package capable of many of the simulation types commonly used to study chemistry: geometry optimizations, harmonic spectra, open or periodic molecular dynamics, Monte Carlo, and nudged elastic band calculations. We describe the robustness and speed of the package, demonstrating its millihartree accuracy and scalability to tens-of-thousands of atoms on ordinary laptops. We demonstrate the performance of the model by reproducing vibrational spectra, and simulating the molecular dynamics of a protein. Our comparisons with electronic structure theory and experimental data demonstrate that neural network molecular dynamics is poised to become an important tool for molecular simulation, lowering the resource barrier to simulating chemistry.

UCAV path planning in the presence of radar-guided surface-to-air missile threats

NASA Astrophysics Data System (ADS)

Zeitz, Frederick H., III

This dissertation addresses the problem of path planning for unmanned combat aerial vehicles (UCAVs) in the presence of radar-guided surface-to-air missiles (SAMs). The radars, collocated with SAM launch sites, operate within the structure of an Integrated Air Defense System (IADS) that permits communication and cooperation between individual radars. The problem is formulated in the framework of the interaction between three sub-systems: the aircraft, the IADS, and the missile. The main features of this integrated model are: The aircraft radar cross section (RCS) depends explicitly on both the aspect and bank angles; hence, the RCS and aircraft dynamics are coupled. The probabilistic nature of IADS tracking is accounted for; namely, the probability that the aircraft has been continuously tracked by the IADS depends on the aircraft RCS and range from the perspective of each radar within the IADS. Finally, the requirement to maintain tracking prior to missile launch and during missile flyout are also modeled. Based on this model, the problem of UCAV path planning is formulated as a minimax optimal control problem, with the aircraft bank angle serving as control. Necessary conditions of optimality for this minimax problem are derived. Based on these necessary conditions, properties of the optimal paths are derived. These properties are used to discretize the dynamic optimization problem into a finite-dimensional, nonlinear programming problem that can be solved numerically. Properties of the optimal paths are also used to initialize the numerical procedure. A homotopy method is proposed to solve the finite-dimensional, nonlinear programming problem, and a heuristic method is proposed to improve the discretization during the homotopy process. Based upon the properties of numerical solutions, a method is proposed for parameterizing and storing information for later recall in flight to permit rapid replanning in response to changing threats. Illustrative examples are presented that confirm the standard flying tactics of "denying range, aspect, and aim," by yielding flight paths that "weave" to avoid long exposures of aspects with large RCS.

Digital PCR Modeling for Maximal Sensitivity, Dynamic Range and Measurement Precision

PubMed Central

Majumdar, Nivedita; Wessel, Thomas; Marks, Jeffrey

2015-01-01

The great promise of digital PCR is the potential for unparalleled precision enabling accurate measurements for genetic quantification. A challenge associated with digital PCR experiments, when testing unknown samples, is to perform experiments at dilutions allowing the detection of one or more targets of interest at a desired level of precision. While theory states that optimal precision (Po) is achieved by targeting ~1.59 mean copies per partition (λ), and that dynamic range (R) includes the space spanning one positive (λL) to one negative (λU) result from the total number of partitions (n), these results are tempered for the practitioner seeking to construct digital PCR experiments in the laboratory. A mathematical framework is presented elucidating the relationships between precision, dynamic range, number of partitions, interrogated volume, and sensitivity in digital PCR. The impact that false reaction calls and volumetric variation have on sensitivity and precision is next considered. The resultant effects on sensitivity and precision are established via Monte Carlo simulations reflecting the real-world likelihood of encountering such scenarios in the laboratory. The simulations provide insight to the practitioner on how to adapt experimental loading concentrations to counteract any one of these conditions. The framework is augmented with a method of extending the dynamic range of digital PCR, with and without increasing n, via the use of dilutions. An example experiment demonstrating the capabilities of the framework is presented enabling detection across 3.33 logs of starting copy concentration. PMID:25806524

Method and system for training dynamic nonlinear adaptive filters which have embedded memory

NASA Technical Reports Server (NTRS)

Rabinowitz, Matthew (Inventor)

2002-01-01

Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.

A design of an on-orbit radiometric calibration device for high dynamic range infrared remote sensors

NASA Astrophysics Data System (ADS)

Sheng, Yicheng; Jin, Weiqi; Dun, Xiong; Zhou, Feng; Xiao, Si

2017-10-01

With the demand of quantitative remote sensing technology growing, high reliability as well as high accuracy radiometric calibration technology, especially the on-orbit radiometric calibration device has become an essential orientation in term of quantitative remote sensing technology. In recent years, global launches of remote sensing satellites are equipped with innovative on-orbit radiometric calibration devices. In order to meet the requirements of covering a very wide dynamic range and no-shielding radiometric calibration system, we designed a projection-type radiometric calibration device for high dynamic range sensors based on the Schmidt telescope system. In this internal radiometric calibration device, we select the EF-8530 light source as the calibration blackbody. EF-8530 is a high emittance Nichrome (Ni-Cr) reference source. It can operate in steady or pulsed state mode at a peak temperature of 973K. The irradiance from the source was projected to the IRFPA. The irradiance needs to ensure that the IRFPA can obtain different amplitude of the uniform irradiance through the narrow IR passbands and cover the very wide dynamic range. Combining the internal on-orbit radiometric calibration device with the specially designed adaptive radiometric calibration algorithms, an on-orbit dynamic non-uniformity correction can be accomplished without blocking the optical beam from outside the telescope. The design optimizes optics, source design, and power supply electronics for irradiance accuracy and uniformity. The internal on-orbit radiometric calibration device not only satisfies a series of indexes such as stability, accuracy, large dynamic range and uniformity of irradiance, but also has the advantages of short heating and cooling time, small volume, lightweight, low power consumption and many other features. It can realize the fast and efficient relative radiometric calibration without shielding the field of view. The device can applied to the design and manufacture of the scanning infrared imaging system, the infrared remote sensing system, the infrared early-warning satellite, and so on.

Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Lamarsh, William J., II; Adelman, Howard M.

1992-01-01

This paper describes a fully integrated aerodynamic/dynamic optimization procedure for helicopter rotor blades. The procedure combines performance and dynamics analyses with a general purpose optimizer. The procedure minimizes a linear combination of power required (in hover, forward flight, and maneuver) and vibratory hub shear. The design variables include pretwist, taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses, and tuning mass locations. Aerodynamic constraints consist of limits on power required in hover, forward flight and maneuver; airfoil section stall; drag divergence Mach number; minimum tip chord; and trim. Dynamic constraints are on frequencies, minimum autorotational inertia, and maximum blade weight. The procedure is demonstrated for two cases. In the first case the objective function involves power required (in hover, forward flight, and maneuver) and dynamics. The second case involves only hover power and dynamics. The designs from the integrated procedure are compared with designs from a sequential optimization approach in which the blade is first optimized for performance and then for dynamics. In both cases, the integrated approach is superior.

Fully integrated aerodynamic/dynamic optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Lamarsh, William J., II; Adelman, Howard M.

1992-01-01

A fully integrated aerodynamic/dynamic optimization procedure is described for helicopter rotor blades. The procedure combines performance and dynamic analyses with a general purpose optimizer. The procedure minimizes a linear combination of power required (in hover, forward flight, and maneuver) and vibratory hub shear. The design variables include pretwist, taper initiation, taper ratio, root chord, blade stiffnesses, tuning masses, and tuning mass locations. Aerodynamic constraints consist of limits on power required in hover, forward flight and maneuvers; airfoil section stall; drag divergence Mach number; minimum tip chord; and trim. Dynamic constraints are on frequencies, minimum autorotational inertia, and maximum blade weight. The procedure is demonstrated for two cases. In the first case, the objective function involves power required (in hover, forward flight and maneuver) and dynamics. The second case involves only hover power and dynamics. The designs from the integrated procedure are compared with designs from a sequential optimization approach in which the blade is first optimized for performance and then for dynamics. In both cases, the integrated approach is superior.

Optimization of fuel-cell tram operation based on two dimension dynamic programming

NASA Astrophysics Data System (ADS)

Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu

2018-02-01

This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Solikhin

2016-06-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

Quantitative Analysis of Bioactive Compounds from Aromatic Plants by Means of Dynamic Headspace Extraction and Multiple Headspace Extraction-Gas Chromatography-Mass Spectrometry.

PubMed

Omar, Jone; Olivares, Maitane; Alonso, Ibone; Vallejo, Asier; Aizpurua-Olaizola, Oier; Etxebarria, Nestor

2016-04-01

Seven monoterpenes in 4 aromatic plants (sage, cardamom, lavender, and rosemary) were quantified in liquid extracts and directly in solid samples by means of dynamic headspace-gas chromatography-mass spectrometry (DHS-GC-MS) and multiple headspace extraction-gas chromatography-mass spectrometry (MHSE), respectively. The monoterpenes were 1st extracted by means of supercritical fluid extraction (SFE) and analyzed by an optimized DHS-GC-MS. The optimization of the dynamic extraction step and the desorption/cryo-focusing step were tackled independently by experimental design assays. The best working conditions were set at 30 °C for the incubation temperature, 5 min of incubation time, and 40 mL of purge volume for the dynamic extraction step of these bioactive molecules. The conditions of the desorption/cryo-trapping step from the Tenax TA trap were set at follows: the temperature was increased from 30 to 300 °C at 150 °C/min, although the cryo-trapping was maintained at -70 °C. In order to estimate the efficiency of the SFE process, the analysis of monoterpenes in the 4 aromatic plants was directly carried out by means of MHSE because it did not require any sample preparation. Good linearity (r2) > 0.99) and reproducibility (relative standard deviation % <12) was obtained for solid and liquid quantification approaches, in the ranges of 0.5 to 200 ng and 10 to 500 ng/mL, respectively. The developed methods were applied to analyze the concentration of 7 monoterpenes in aromatic plants obtaining concentrations in the range of 2 to 6000 ng/g and 0.25 to 110 μg/mg, respectively. © 2016 Institute of Food Technologists®

Dynamic emulation modelling for the optimal operation of water systems: an overview

NASA Astrophysics Data System (ADS)

Castelletti, A.; Galelli, S.; Giuliani, M.

2014-12-01

Despite sustained increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems. As a result, increasing attention is now being devoted to emulation modelling (or model reduction) as a way of overcoming these limitations. An emulation model, or emulator, is a low-order approximation of the process-based model that can be substituted for it in order to solve high resource-demanding problems. In this talk, an overview of emulation modelling within the context of the optimal operation of water systems will be provided. Particular emphasis will be given to Dynamic Emulation Modelling (DEMo), a special type of model complexity reduction in which the dynamic nature of the original process-based model is preserved, with consequent advantages in a wide range of problems, particularly feedback control problems. This will be contrasted with traditional non-dynamic emulators (e.g. response surface and surrogate models) that have been studied extensively in recent years and are mainly used for planning purposes. A number of real world numerical experiences will be used to support the discussion ranging from multi-outlet water quality control in water reservoir through erosion/sedimentation rebalancing in the operation of run-off-river power plants to salinity control in lake and reservoirs.

Optimization of coupled device based on optical fiber with crystalline and integrated resonators

NASA Astrophysics Data System (ADS)

Bassir, David; Salzenstein, Patrice; Zhang, Mingjun

2017-05-01

Because of the advantages in terms of reproducibility for optical resonators on chip which are designed of various topologies and integration with optical devices. To increase the Q-factor from the lower rang [104 - 106 ] to higher one [108 -1010] [1-4] one use crystalline resonators. It is much complicated to couple an optical signal from a tapered fiber to crystalline resonator than from a defined ridge to a resonator designed on a chip. In this work, we will focus on the optimization of the crystalline resonators under straight wave guide (based on COMSOL multi-physic software) [5- 7] and subject also to technological constraints of manufacturing. The coupling problem at the Nano scale makes our optimizations problem more dynamics in term of design space.

Precise Orbit Solution for Swarm Using Space-Borne GPS Data and Optimized Pseudo-Stochastic Pulses

PubMed Central

Zhang, Bingbing; Wang, Zhengtao; Zhou, Lv; Feng, Jiandi; Qiu, Yaodong; Li, Fupeng

2017-01-01

Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospheric activity. We choose Swarm space-borne GPS data from 1–25 October 2014, and Swarm reduced-dynamic orbits are obtained. Orbit quality is assessed by GPS phase observation residuals and compared with Precise Science Orbits (PSOs) released by ESA. Results show that pseudo-stochastic pulses with a time interval of 6 min and a priori standard deviation (STD) of 10−2 mm/s in radial (R), along-track (T) and cross-track (N) directions are optimized to Swarm ZD reduced-dynamic precise orbit determination (POD). During high ionospheric activity, the mean Root Mean Square (RMS) of Swarm GPS phase residuals is at 9–11 mm, Swarm orbit solutions are also compared with Swarm PSOs released by ESA and the accuracy of Swarm orbits can reach 2–4 cm in R, T and N directions. Independent Satellite Laser Ranging (SLR) validation indicates that Swarm reduced-dynamic orbits have an accuracy of 2–4 cm. Swarm-B orbit quality is better than those of Swarm-A and Swarm-C. The Swarm orbits can be applied to the geomagnetic, geoelectric and gravity field recovery. PMID:28335538

[Determination of Al, Be, Cd, Co, Cr, Mn, Ni, Pb, Se and Tl in whole blood by atomic absorption spectrometry without preliminary sample digestion].

PubMed

Ivanenko, N B; Ivanenko, A A; Solov'ev, N D; Navolotskiĭ, D V; Pavlova, O V; Ganeev, A A

2014-01-01

Methods of whole blood trace element determination by Graphite furnace atomic absorption spectrometry (in the variant of Zeeman's modulation polarization spectrometry) have been proposed. They do not require preliminary sample digestion. Furnace programs, modifiers and blood dilution factors were optimized. Seronorm™ human whole blood reference materials were used for validation. Dynamic ranges (for undiluted blood samples) were: Al 8 ¸ 210 мg/L; Be 0.3 ¸ 50 мg/L; Cd 0.2 ¸ 75 мg/L; Сo 5 ¸ 350 мg/L; Cr 10 ¸ 100 мg/L; Mn 6 ¸ 250 мg/L; Ni 10 ¸ 350 мg/L; Pb 3 ¸ 240 мg/L; Se 10 ¸ 500 мg/L; Tl 2 ¸ 600 мg/L. Precision (RSD) for the middle of dynamic range ranged from 5% for Mn to 11 for Se.

Software-based stacking techniques to enhance depth of field and dynamic range in digital photomicrography.

PubMed

Piper, Jörg

2010-01-01

Several software solutions are powerful tools to enhance the depth of field and improve focus in digital photomicrography. By these means, the focal depth can be fundamentally optimized so that three-dimensional structures within specimens can be documented with superior quality. Thus, images can be created in light microscopy which will be comparable with scanning electron micrographs. The remaining sharpness will no longer be dependent on the specimen's vertical dimension or its range in regional thickness. Moreover, any potential lack of definition associated with loss of planarity and unsteadiness in the visual accommodation can be mitigated or eliminated so that the contour sharpness and resolution can be strongly enhanced.Through the use of complementary software, ultrahigh ranges in brightness and contrast (the so-called high-dynamic range) can be corrected so that the final images will also be free from locally over- or underexposed zones. Furthermore, fine detail in low natural contrast can be visualized in much higher clarity. Fundamental enhancements of the global visual information will result from both techniques.

A variational approach to probing extreme events in turbulent dynamical systems

PubMed Central

Farazmand, Mohammad; Sapsis, Themistoklis P.

2017-01-01

Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large-scale networks, and biological systems. We propose a variational framework for probing conditions that trigger intermittent extreme events in high-dimensional nonlinear dynamical systems. We seek the triggers as the probabilistically feasible solutions of an appropriately constrained optimization problem, where the function to be maximized is a system observable exhibiting intermittent extreme bursts. The constraints are imposed to ensure the physical admissibility of the optimal solutions, that is, significant probability for their occurrence under the natural flow of the dynamical system. We apply the method to a body-forced incompressible Navier-Stokes equation, known as the Kolmogorov flow. We find that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions. The global maximizer of the corresponding variational problem identifies the responsible triad, hence providing a precursor for the occurrence of extreme dissipation events. Specifically, monitoring the energy transfers within this triad allows us to develop a data-driven short-term predictor for the intermittent bursts of energy dissipation. We assess the performance of this predictor through direct numerical simulations. PMID:28948226

Application of numerical optimization techniques to control system design for nonlinear dynamic models of aircraft

NASA Technical Reports Server (NTRS)

Lan, C. Edward; Ge, Fuying

1989-01-01

Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians.

PubMed

Pang, Shengshi; Jordan, Andrew N

2017-03-09

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T 2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T 4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians

PubMed Central

Pang, Shengshi; Jordan, Andrew N.

2017-01-01

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case. PMID:28276428

A wave dynamics criterion for optimization of mammalian cardiovascular system.

PubMed

Pahlevan, Niema M; Gharib, Morteza

2014-05-07

The cardiovascular system in mammals follows various optimization criteria covering the heart, the vascular network, and the coupling of the two. Through a simple dimensional analysis we arrived at a non-dimensional number (wave condition number) that can predict the optimum wave state in which the left ventricular (LV) pulsatile power (LV workload) is minimized in a mammalian cardiovascular system. This number is also universal among all mammals independent of animal size maintaining a value of around 0.1. By utilizing a unique in vitro model of human aorta, we tested our hypothesis against a wide range of aortic compliance (pulse wave velocity). We concluded that the optimum value of the wave condition number remains to be around 0.1 for a wide range of aorta compliance that we could simulate in our in-vitro system. Copyright © 2014 Elsevier Ltd. All rights reserved.

LAMMPS strong scaling performance optimization on Blue Gene/Q

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

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

Supercomputer optimizations for stochastic optimal control applications

NASA Technical Reports Server (NTRS)

Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang

1991-01-01

Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

NASA Astrophysics Data System (ADS)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of each timestep and minimize computational overhead. Power generation for each reservoir is estimated using a 2-dimensional regression that accounts for both the available head and turbine efficiency. The object-oriented architecture makes run configuration easy to update. The dynamic model inputs include inflow and meteorological forecasts while static inputs include bathymetry data, reservoir and power generation characteristics, and topological descriptors. Ensemble forecasts of hydrological and meteorological conditions are supplied in real-time by Pacific Northwest National Laboratory and are used as a proxy for uncertainty, which is carried through the simulation and optimization process to produce output that describes the probability that different operational scenario's will be optimal. The full toolset, which includes HydroSCOPE, is currently being tested on the Feather River system in Northern California and the Upper Colorado Storage Project.

Optimization algorithms for large-scale multireservoir hydropower systems

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

Hiew, K.L.

Five optimization algorithms were vigorously evaluated based on applications on a hypothetical five-reservoir hydropower system. These algorithms are incremental dynamic programming (IDP), successive linear programing (SLP), feasible direction method (FDM), optimal control theory (OCT) and objective-space dynamic programming (OSDP). The performance of these algorithms were comparatively evaluated using unbiased, objective criteria which include accuracy of results, rate of convergence, smoothness of resulting storage and release trajectories, computer time and memory requirements, robustness and other pertinent secondary considerations. Results have shown that all the algorithms, with the exception of OSDP converge to optimum objective values within 1.0% difference from one another.more » The highest objective value is obtained by IDP, followed closely by OCT. Computer time required by these algorithms, however, differ by more than two orders of magnitude, ranging from 10 seconds in the case of OCT to a maximum of about 2000 seconds for IDP. With a well-designed penalty scheme to deal with state-space constraints, OCT proves to be the most-efficient algorithm based on its overall performance. SLP, FDM, and OCT were applied to the case study of Mahaweli project, a ten-powerplant system in Sri Lanka.« less

Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach.

PubMed

Kim, Woojae; Pitt, Mark A; Lu, Zhong-Lin; Myung, Jay I

2017-11-01

Experimentation is at the heart of scientific inquiry. In the behavioral and neural sciences, where only a limited number of observations can often be made, it is ideal to design an experiment that leads to the rapid accumulation of information about the phenomenon under study. Adaptive experimentation has the potential to accelerate scientific progress by maximizing inferential gain in such research settings. To date, most adaptive experiments have relied on myopic, one-step-ahead strategies in which the stimulus on each trial is selected to maximize inference on the next trial only. A lingering question in the field has been how much additional benefit would be gained by optimizing beyond the next trial. A range of technical challenges has prevented this important question from being addressed adequately. This study applies dynamic programming (DP), a technique applicable for such full-horizon, "global" optimization, to model-based perceptual threshold estimation, a domain that has been a major beneficiary of adaptive methods. The results provide insight into conditions that will benefit from optimizing beyond the next trial. Implications for the use of adaptive methods in cognitive science are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2006-01-01

Mystic software is designed to compute, analyze, and visualize optimal high-fidelity, low-thrust trajectories, The software can be used to analyze inter-planetary, planetocentric, and combination trajectories, Mystic also provides utilities to assist in the operation and navigation of low-thrust spacecraft. Mystic will be used to design and navigate the NASA's Dawn Discovery mission to orbit the two largest asteroids, The underlying optimization algorithm used in the Mystic software is called Static/Dynamic Optimal Control (SDC). SDC is a nonlinear optimal control method designed to optimize both 'static variables' (parameters) and dynamic variables (functions of time) simultaneously. SDC is a general nonlinear optimal control algorithm based on Bellman's principal.

Functionalized anatomical models for EM-neuron Interaction modeling

NASA Astrophysics Data System (ADS)

Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang

2016-06-01

The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

A Multiscale Vision Model applied to analyze EIT images of the solar corona

NASA Astrophysics Data System (ADS)

Portier-Fozzani, F.; Vandame, B.; Bijaoui, A.; Maucherat, A. J.; EIT Team

2001-07-01

The large dynamic range provided by the SOHO/EIT CCD (1 : 5000) is needed to observe the large EUV zoom of coronal structures from coronal homes up to flares. Histograms show that often a wide dynamic range is present in each image. Extracting hidden structures in the background level requires specific techniques such as the use of the Multiscale Vision Model (MVM, Bijaoui et al., 1998). This method, based on wavelet transformations optimizes detection of various size objects, however complex they may be. Bijaoui et al. built the Multiscale Vision Model to extract small dynamical structures from noise, mainly for studying galaxies. In this paper, we describe requirements for the use of this method with SOHO/EIT images (calibration, size of the image, dynamics of the subimage, etc.). Two different areas were studied revealing hidden structures: (1) classical coronal mass ejection (CME) formation and (2) a complex group of active regions with its evolution. The aim of this paper is to define carefully the constraints for this new method of imaging the solar corona with SOHO/EIT. Physical analysis derived from multi-wavelength observations will later complete these first results.

Inference of a Nonlinear Stochastic Model of the Cardiorespiratory Interaction

NASA Astrophysics Data System (ADS)

Smelyanskiy, V. N.; Luchinsky, D. G.; Stefanovska, A.; McClintock, P. V.

2005-03-01

We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.

Initial state-specific photodissociation dynamics of pyrrole via 1 π σ ∗/ S 0 conical intersection initiated with optimally controlled UV-laser pulses

NASA Astrophysics Data System (ADS)

Nandipati, K. R.; Kanakati, Arun Kumar; Singh, H.; Lan, Z.; Mahapatra, S.

2017-09-01

Optimal initiation of quantum dynamics of N-H photodissociation of pyrrole on the S0-1πσ∗(1A2) coupled electronic states by UV-laser pulses in an effort to guide the subsequent dynamics to dissociation limits is studied theoretically. Specifically, the task of designing optimal laser pulses that act on initial vibrational states of the system for an effective UV-photodissociation is considered by employing optimal control theory. The associated control mechanism(s) for the initial state dependent photodissociation dynamics of pyrrole in the presence of control pulses is examined and discussed in detail. The initial conditions determine implicitly the variation in the dissociation probabilities for the two channels, upon interaction with the field. The optimal pulse corresponds to the objective fixed as maximization of overall reactive flux subject to constraints of reasonable fluence and quantum dynamics. The simple optimal pulses obtained by the use of genetic algorithm based optimization are worth an experimental implementation given the experimental relevance of πσ∗-photochemistry in recent times.

Toward an Integration of Deep Learning and Neuroscience

PubMed Central

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P.

2016-01-01

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses. PMID:27683554

Benefits of incorporating the adaptive dynamic range optimization amplification scheme into an assistive listening device for people with mild or moderate hearing loss.

PubMed

Chang, Hung-Yue; Luo, Ching-Hsing; Lo, Tun-Shin; Chen, Hsiao-Chuan; Huang, Kuo-You; Liao, Wen-Huei; Su, Mao-Chang; Liu, Shu-Yu; Wang, Nan-Mai

2017-08-28

This study investigated whether a self-designed assistive listening device (ALD) that incorporates an adaptive dynamic range optimization (ADRO) amplification strategy can surpass a commercially available monaurally worn linear ALD, SM100. Both subjective and objective measurements were implemented. Mandarin Hearing-In-Noise Test (MHINT) scores were the objective measurement, whereas participant satisfaction was the subjective measurement. The comparison was performed in a mixed design (i.e., subjects' hearing status being mild or moderate, quiet versus noisy, and linear versus ADRO scheme). The participants were two groups of hearing-impaired subjects, nine mild and eight moderate, respectively. The results of the ADRO system revealed a significant difference in the MHINT sentence reception threshold (SRT) in noisy environments between monaurally aided and unaided conditions, whereas the linear system did not. The benchmark results showed that the ADRO scheme is effectively beneficial to people who experience mild or moderate hearing loss in noisy environments. The satisfaction rating regarding overall speech quality indicated that the participants were satisfied with the speech quality of both ADRO and linear schemes in quiet environments, and they were more satisfied with ADRO than they with the linear scheme in noisy environments.

High-dynamic range imaging techniques based on both color-separation algorithms used in conventional graphic arts and the human visual perception modeling

NASA Astrophysics Data System (ADS)

Lo, Mei-Chun; Hsieh, Tsung-Hsien; Perng, Ruey-Kuen; Chen, Jiong-Qiao

2010-01-01

The aim of this research is to derive illuminant-independent type of HDR imaging modules which can optimally multispectrally reconstruct of every color concerned in high-dynamic-range of original images for preferable cross-media color reproduction applications. Each module, based on either of broadband and multispectral approach, would be incorporated models of perceptual HDR tone-mapping, device characterization. In this study, an xvYCC format of HDR digital camera was used to capture HDR scene images for test. A tone-mapping module was derived based on a multiscale representation of the human visual system and used equations similar to a photoreceptor adaptation equation, proposed by Michaelis-Menten. Additionally, an adaptive bilateral type of gamut mapping algorithm, using approach of a multiple conversing-points (previously derived), was incorporated with or without adaptive Un-sharp Masking (USM) to carry out the optimization of HDR image rendering. An LCD with standard color space of Adobe RGB (D65) was used as a soft-proofing platform to display/represent HDR original RGB images, and also evaluate both renditionquality and prediction-performance of modules derived. Also, another LCD with standard color space of sRGB was used to test gamut-mapping algorithms, used to be integrated with tone-mapping module derived.

Dynamic conversion of solar generated heat to electricity

NASA Technical Reports Server (NTRS)

Powell, J. C.; Fourakis, E.; Hammer, J. M.; Smith, G. A.; Grosskreutz, J. C.; Mcbride, E.

1974-01-01

The effort undertaken during this program led to the selection of the water-superheated steam (850 psig/900 F) crescent central receiver as the preferred concept from among 11 candidate systems across the technological spectrum of the dynamic conversion of solar generated heat to electricity. The solar power plant designs were investigated in the range of plant capacities from 100 to 1000 Mw(e). The investigations considered the impacts of plant size, collector design, feed-water temperature ratio, heat rejection equipment, ground cover, and location on solar power technical and economic feasibility. For the distributed receiver systems, the optimization studies showed that plant capacities less than 100 Mw(e) may be best. Although the size of central receiver concepts was not parametrically investigated, all indications are that the optimal plant capacity for central receiver systems will be in the range from 50 to 200 Mw(e). Solar thermal power plant site selection criteria and methodology were also established and used to evaluate potentially suitable sites. The result of this effort was to identify a site south of Inyokern, California, as typically suitable for a solar thermal power plant. The criteria used in the selection process included insolation and climatological characteristics, topography, and seismic history as well as water availability.

Trajectory Optimization of Electric Aircraft Subject to Subsystem Thermal Constraints

NASA Technical Reports Server (NTRS)

Falck, Robert D.; Chin, Jeffrey C.; Schnulo, Sydney L.; Burt, Jonathan M.; Gray, Justin S.

2017-01-01

Electric aircraft pose a unique design challenge in that they lack a simple way to reject waste heat from the power train. While conventional aircraft reject most of their excess heat in the exhaust stream, for electric aircraft this is not an option. To examine the implications of this challenge on electric aircraft design and performance, we developed a model of the electric subsystems for the NASA X-57 electric testbed aircraft. We then coupled this model with a model of simple 2D aircraft dynamics and used a Legendre-Gauss-Lobatto collocation optimal control approach to find optimal trajectories for the aircraft with and without thermal constraints. The results show that the X-57 heat rejection systems are well designed for maximum-range and maximum-efficiency flight, without the need to deviate from an optimal trajectory. Stressing the thermal constraints by reducing the cooling capacity or requiring faster flight has a minimal impact on performance, as the trajectory optimization technique is able to find flight paths which honor the thermal constraints with relatively minor deviations from the nominal optimal trajectory.

Long-Range Self-Assembly via the Mutual Lorentz Force of Plasmon Radiation.

PubMed

Ji, Haojie; Trevino, Jacob; Tu, Raymond; Knapp, Ellen; McQuade, James; Yurkiv, Vitaliy; Mashayek, Farzad; Vuong, Luat T

2018-04-11

Long-range interactions often proceed as a sequence of hopping through intermediate, statistically favored events. Here, we demonstrate predictable mechanical dynamics of particles that arise from the Lorentz force between plasmons. Even if the radiation is weak, the nonconservative Lorentz force produces stable locations perpendicular to the plasmon oscillation; over time, distinct patterns emerge. Experimentally, linearly polarized light illumination leads to the formation of 80 nm diameter Au nanoparticle chains, perpendicularly aligned, with lengths that are orders of magnitude greater than their plasmon near-field interaction. There is a critical intensity threshold and optimal concentration for observing self-assembly.

Spectropolarimetry of blood plasma in optimal molecular targeted therapy

NASA Astrophysics Data System (ADS)

Voloshynska, Katerina; Ilashchuk, Tetjana; Yermolenko, Sergey

2015-02-01

The aim of the study was to establish objective parameters of the field of laser and incoherent radiation of different spectral ranges (UV, visible, IR) as a non-invasive optical method of interaction with different samples of biological tissues and fluids of patients to determine the dynamics of metabolic syndrome and choosing the best personal treatment. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues.

C-learning: A new classification framework to estimate optimal dynamic treatment regimes.

PubMed

Zhang, Baqun; Zhang, Min

2017-12-11

A dynamic treatment regime is a sequence of decision rules, each corresponding to a decision point, that determine that next treatment based on each individual's own available characteristics and treatment history up to that point. We show that identifying the optimal dynamic treatment regime can be recast as a sequential optimization problem and propose a direct sequential optimization method to estimate the optimal treatment regimes. In particular, at each decision point, the optimization is equivalent to sequentially minimizing a weighted expected misclassification error. Based on this classification perspective, we propose a powerful and flexible C-learning algorithm to learn the optimal dynamic treatment regimes backward sequentially from the last stage until the first stage. C-learning is a direct optimization method that directly targets optimizing decision rules by exploiting powerful optimization/classification techniques and it allows incorporation of patient's characteristics and treatment history to improve performance, hence enjoying advantages of both the traditional outcome regression-based methods (Q- and A-learning) and the more recent direct optimization methods. The superior performance and flexibility of the proposed methods are illustrated through extensive simulation studies. © 2017, The International Biometric Society.

Industrial SO2 emissions monitoring using a portable multi-channel gas analyzer with an optimized retrieval algorithm

NASA Astrophysics Data System (ADS)

Sun, Y. W.; Liu, C.; Xie, P. H.; Hartl, A.; Chan, K. L.; Tian, Y.; Wang, W.; Qin, M.; Liu, J. G.; Liu, W. Q.

2015-12-01

In this paper, we demonstrate achieving accurate industrial SO2 emissions monitoring using a portable multi-channel gas analyzer with an optimized retrieval algorithm. The introduced analyzer features with large dynamic measurement range and correction of interferences from other co-existing infrared absorbers, e.g., NO, CO, CO2, NO2, CH4, HC, N2O and H2O. Both effects have been the major limitations of industrial SO2 emissions monitoring. The multi-channel gas analyzer measures 11 different wavelength channels simultaneously in order to achieve correction of several major problems of an infrared gas analyzer, including system drift, conflict of sensitivity, interferences among different infrared absorbers and limitation of measurement range. The optimized algorithm makes use of a 3rd polynomial rather than a constant factor to quantify gas-to-gas interference. The measurement results show good performance in both linear and nonlinear range, thereby solving the problem that the conventional interference correction is restricted by the linearity of both intended and interfering channels. The result implies that the measurement range of the developed multi-channel analyzer can be extended to the nonlinear absorption region. The measurement range and accuracy are evaluated by experimental laboratory calibration. An excellent agreement was achieved with a Pearson correlation coefficient (r2) of 0.99977 with measurement range from ~5 ppmv to 10 000 ppmv and measurement error <2 %. The instrument was also deployed for field measurement. Emissions from 3 different factories were measured. The emissions of these factories have been characterized with different co-existing infrared absorbers, covering a wide range of concentration levels. We compared our measurements with the commercial SO2 analyzers. The overall good agreements are achieved.

Experimental optimization of a free vortex propeller runner for micro hydro application

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

Singh, Punit; Nestmann, Franz

2009-09-15

The turbine technology for low head application in the micro hydro range has been vastly neglected despite niche available in scattered regions of valley flows as well as in wastewater canals and other energy recovery schemes, where the available head does not exceed 2 meters. The goal of this study is to develop hydraulically optimized propeller turbines for the micro hydro range with a particular focus on ease of manufacture. This paper presents a wide range of geometrical optimization steps carried out on a propeller runner, whose blades have been designed using the free vortex theory, and operating with amore » gross head from 1.5 to 2 m and discharge of approximately 75 l/s. It further illustrates 3 stages of geometrical modifications carried out on the runner with an objective of optimizing the runner performance. These modifications comprised of changes to the tip angles (both at the runner inlet and exit) as well as the hub angles (at the runner inlet) of the runner blades. The paper also presents an interesting theoretical methodology to analyze the effects of each optimization stage. This method looks at the relative changes to shaft power and discharge at constant head and speed and gives wonderful insight as to how the internal parameters like Euler shaft work and runner hydraulic losses are behaving with respect to each optimization stage. It was found that the performance of the runner was very sensitive to changes to exit tip angle. At two levels of modification, the discharge increased in the range of 15-30%, while shaft power increased in the range of 12-45%, thus influencing the efficiency characteristics. The results of the runner inlet tip modification were very interesting in that a very significant rise of turbine efficiency was recorded from 55% to 74% at the best efficiency point, which was caused by a reduced discharge consumption as well as a higher power generation. It was also found that the optimization study on a propeller runner has reasonably validated the estimates of the free vortex theory despite small deviations. The final runner configuration demonstrated a maximum efficiency of 74% ({+-}1.8%), which is very encouraging from the perspectives of micro hydro application. The paper concludes with recommendations of a series of optimization steps to increase the efficiency of the runner. It also recommends the attempt of Computational Fluid Dynamics both as a validation and optimization tool for future research on propeller runners. (author)« less

Optimal estimation of suspended-sediment concentrations in streams

USGS Publications Warehouse

Holtschlag, D.J.

2001-01-01

Optimal estimators are developed for computation of suspended-sediment concentrations in streams. The estimators are a function of parameters, computed by use of generalized least squares, which simultaneously account for effects of streamflow, seasonal variations in average sediment concentrations, a dynamic error component, and the uncertainty in concentration measurements. The parameters are used in a Kalman filter for on-line estimation and an associated smoother for off-line estimation of suspended-sediment concentrations. The accuracies of the optimal estimators are compared with alternative time-averaging interpolators and flow-weighting regression estimators by use of long-term daily-mean suspended-sediment concentration and streamflow data from 10 sites within the United States. For sampling intervals from 3 to 48 days, the standard errors of on-line and off-line optimal estimators ranged from 52.7 to 107%, and from 39.5 to 93.0%, respectively. The corresponding standard errors of linear and cubic-spline interpolators ranged from 48.8 to 158%, and from 50.6 to 176%, respectively. The standard errors of simple and multiple regression estimators, which did not vary with the sampling interval, were 124 and 105%, respectively. Thus, the optimal off-line estimator (Kalman smoother) had the lowest error characteristics of those evaluated. Because suspended-sediment concentrations are typically measured at less than 3-day intervals, use of optimal estimators will likely result in significant improvements in the accuracy of continuous suspended-sediment concentration records. Additional research on the integration of direct suspended-sediment concentration measurements and optimal estimators applied at hourly or shorter intervals is needed.

Dynamics of Biomarkers in Relation to Aging and Mortality

PubMed Central

Arbeev, Konstantin G.; Ukraintseva, Svetlana V.; Yashin, Anatoliy I.

2016-01-01

Contemporary longitudinal studies collect repeated measurements of biomarkers allowing one to analyze their dynamics in relation to mortality, morbidity, or other health-related outcomes. Rich and diverse data collected in such studies provide opportunities to investigate how various socioeconomic, demographic, behavioral and other variables can interact with biological and genetic factors to produce differential rates of aging in individuals. In this paper, we review some recent publications investigating dynamics of biomarkers in relation to mortality, which use single biomarkers as well as cumulative measures combining information from multiple biomarkers. We also discuss the analytical approach, the stochastic process models, which conceptualizes several aging-related mechanisms in the structure of the model and allows evaluating “hidden” characteristics of aging-related changes indirectly from available longitudinal data on biomarkers and follow-up on mortality or onset of diseases taking into account other relevant factors (both genetic and non-genetic). We also discuss an extension of the approach, which considers ranges of “optimal values” of biomarkers rather than a single optimal value as in the original model. We discuss practical applications of the approach to single biomarkers and cumulative measures highlighting that the potential of applications to cumulative measures is still largely underused. PMID:27138087

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nonadiabatic quantum dynamics and laser control of Br2 in solid argon.

PubMed

Accardi, A; Borowski, A; Kühn, O

2009-07-02

A five-dimensional reaction surface-vibronic coupling model is introduced to describe the B- to C-state predissociation dynamics of Br(2) occupying a double substitutional lattice site in a face-centered cubic argon crystal at low temperatures. The quantum dynamics driven by a Franck-Condon vertical excitation is investigated, revealing the role of matrix cage compression for efficient nonadiabatic transitions. Vibrational preexcitation of the Br(2) bond in the electronic ground state can be used to access a different regime of predissociation which does not require substantial matrix compression because the Franck-Condon window shifts into the energetic range of the B-C level crossing. Using optimal control theory, it is shown how vibrational preexcitation can be achieved via a pump-dump-type mechanism involving the repulsive C state.

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 2

NASA Technical Reports Server (NTRS)

Whitlow, Jr., Woodrow (Editor); Todd, Emily N. (Editor)

1999-01-01

The proceedings of a workshop sponsored by the Confederation of European Aerospace Societies (CEAS), the American Institute of Aeronautics and Astronautics (AIAA), the National Aeronautics and Space Administration (NASA), Washington, D.C., and the Institute for Computer Applications in Science and Engineering (ICASE), Hampton, Virginia, and held in Williamsburg, Virginia June 22-25, 1999 represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Precise tracking of remote sensing satellites with the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong; Thornton, Catherine L.

1990-01-01

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Generalized Scaling and the Master Variable for Brownian Magnetic Nanoparticle Dynamics

PubMed Central

Reeves, Daniel B.; Shi, Yipeng; Weaver, John B.

2016-01-01

Understanding the dynamics of magnetic particles can help to advance several biomedical nanotechnologies. Previously, scaling relationships have been used in magnetic spectroscopy of nanoparticle Brownian motion (MSB) to measure biologically relevant properties (e.g., temperature, viscosity, bound state) surrounding nanoparticles in vivo. Those scaling relationships can be generalized with the introduction of a master variable found from non-dimensionalizing the dynamical Langevin equation. The variable encapsulates the dynamical variables of the surroundings and additionally includes the particles’ size distribution and moment and the applied field’s amplitude and frequency. From an applied perspective, the master variable allows tuning to an optimal MSB biosensing sensitivity range by manipulating both frequency and field amplitude. Calculation of magnetization harmonics in an oscillating applied field is also possible with an approximate closed-form solution in terms of the master variable and a single free parameter. PMID:26959493

Distributed dynamic simulations of networked control and building performance applications.

PubMed

Yahiaoui, Azzedine

2018-02-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper.

Distributed dynamic simulations of networked control and building performance applications

PubMed Central

Yahiaoui, Azzedine

2017-01-01

The use of computer-based automation and control systems for smart sustainable buildings, often so-called Automated Buildings (ABs), has become an effective way to automatically control, optimize, and supervise a wide range of building performance applications over a network while achieving the minimum energy consumption possible, and in doing so generally refers to Building Automation and Control Systems (BACS) architecture. Instead of costly and time-consuming experiments, this paper focuses on using distributed dynamic simulations to analyze the real-time performance of network-based building control systems in ABs and improve the functions of the BACS technology. The paper also presents the development and design of a distributed dynamic simulation environment with the capability of representing the BACS architecture in simulation by run-time coupling two or more different software tools over a network. The application and capability of this new dynamic simulation environment are demonstrated by an experimental design in this paper. PMID:29568135

High dynamic range fringe acquisition: A novel 3-D scanning technique for high-reflective surfaces

NASA Astrophysics Data System (ADS)

Jiang, Hongzhi; Zhao, Huijie; Li, Xudong

2012-10-01

This paper presents a novel 3-D scanning technique for high-reflective surfaces based on phase-shifting fringe projection method. High dynamic range fringe acquisition (HDRFA) technique is developed to process the fringe images reflected from the shiny surfaces, and generates a synthetic fringe image by fusing the raw fringe patterns, acquired with different camera exposure time and the illumination fringe intensity from the projector. Fringe image fusion algorithm is introduced to avoid saturation and under-illumination phenomenon by choosing the pixels in the raw fringes with the highest fringe modulation intensity. A method of auto-selection of HDRFA parameters is developed and largely increases the measurement automation. The synthetic fringes have higher signal-to-noise ratio (SNR) under ambient light by optimizing HDRFA parameters. Experimental results show that the proposed technique can successfully measure objects with high-reflective surfaces and is insensitive to ambient light.

Pseudo-polar drive patterns for brain electrical impedance tomography.

PubMed

Shi, Xuetao; Dong, Xiuzhen; Shuai, Wanjun; You, Fusheng; Fu, Feng; Liu, Ruigang

2006-11-01

Brain electrical impedance tomography (EIT) is a difficult task as brain tissues are enclosed by the skull of high resistance and cerebrospinal fluid (CSF) of low resistance, which makes internal resistivity information more difficult to extract. In order to seek a single source drive pattern that is more suitable for brain EIT, we built a more realistic experimental setting that simulates a head with the resistivity of the scalp, skull, CSF and brain, and compared the performance of adjacent, cross, polar and pseudo-polar drive patterns in terms of the boundary voltage dynamic range, independent measurement number, total boundary voltage changes and anti-noise performance based on it. The results demonstrate that the pseudo-polar drive pattern is optimal in all the aspects except for the dynamic range. The polar and cross drive patterns come next, and the adjacent drive pattern is the worst. Therefore, the pseudo-polar drive pattern should be chosen for brain EIT.

Synthetic Biology Toolbox for Controlling Gene Expression in the Cyanobacterium Synechococcus sp. strain PCC 7002

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

Markley, Andrew L.; Begemann, Matthew B.; Clarke, Ryan E.

The application of synthetic biology requires characterized tools to precisely control gene expression. This toolbox of genetic parts previously did not exist for the industrially promising cyanobacterium, Synechococcus sp. strain PCC 7002. To address this gap, two orthogonal constitutive promoter libraries, one based on a cyanobacterial promoter and the other ported from Escherichia coli, were built and tested in PCC 7002. The libraries demonstrated 3 and 2.5 log dynamic ranges, respectively, but correlated poorly with E. coli expression levels. These promoter libraries were then combined to create and optimize a series of IPTG inducible cassettes. The resultant induction system hadmore » a 48-fold dynamic range and was shown to out-perform P trc constructs. Finally, a RBS library was designed and tested in PCC 7002. The presented synthetic biology toolbox will enable accelerated engineering of PCC 7002.« less

Synthetic Biology Toolbox for Controlling Gene Expression in the Cyanobacterium Synechococcus sp. strain PCC 7002

DOE PAGES

Markley, Andrew L.; Begemann, Matthew B.; Clarke, Ryan E.; ...

2014-09-12

The application of synthetic biology requires characterized tools to precisely control gene expression. This toolbox of genetic parts previously did not exist for the industrially promising cyanobacterium, Synechococcus sp. strain PCC 7002. To address this gap, two orthogonal constitutive promoter libraries, one based on a cyanobacterial promoter and the other ported from Escherichia coli, were built and tested in PCC 7002. The libraries demonstrated 3 and 2.5 log dynamic ranges, respectively, but correlated poorly with E. coli expression levels. These promoter libraries were then combined to create and optimize a series of IPTG inducible cassettes. The resultant induction system hadmore » a 48-fold dynamic range and was shown to out-perform P trc constructs. Finally, a RBS library was designed and tested in PCC 7002. The presented synthetic biology toolbox will enable accelerated engineering of PCC 7002.« less

Video enhancement workbench: an operational real-time video image processing system

NASA Astrophysics Data System (ADS)

Yool, Stephen R.; Van Vactor, David L.; Smedley, Kirk G.

1993-01-01

Video image sequences can be exploited in real-time, giving analysts rapid access to information for military or criminal investigations. Video-rate dynamic range adjustment subdues fluctuations in image intensity, thereby assisting discrimination of small or low- contrast objects. Contrast-regulated unsharp masking enhances differentially shadowed or otherwise low-contrast image regions. Real-time removal of localized hotspots, when combined with automatic histogram equalization, may enhance resolution of objects directly adjacent. In video imagery corrupted by zero-mean noise, real-time frame averaging can assist resolution and location of small or low-contrast objects. To maximize analyst efficiency, lengthy video sequences can be screened automatically for low-frequency, high-magnitude events. Combined zoom, roam, and automatic dynamic range adjustment permit rapid analysis of facial features captured by video cameras recording crimes in progress. When trying to resolve small objects in murky seawater, stereo video places the moving imagery in an optimal setting for human interpretation.

Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy.

PubMed

Vargas-Rodriguez, Everardo; Guzman-Chavez, Ana Dinora; Baeza-Serrato, Roberto

2018-06-04

In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.

Gain-adaptive vector quantization for medium-rate speech coding

NASA Technical Reports Server (NTRS)

Chen, J.-H.; Gersho, A.

1985-01-01

A class of adaptive vector quantizers (VQs) that can dynamically adjust the 'gain' of codevectors according to the input signal level is introduced. The encoder uses a gain estimator to determine a suitable normalization of each input vector prior to VQ coding. The normalized vectors have reduced dynamic range and can then be more efficiently coded. At the receiver, the VQ decoder output is multiplied by the estimated gain. Both forward and backward adaptation are considered and several different gain estimators are compared and evaluated. An approach to optimizing the design of gain estimators is introduced. Some of the more obvious techniques for achieving gain adaptation are substantially less effective than the use of optimized gain estimators. A novel design technique that is needed to generate the appropriate gain-normalized codebook for the vector quantizer is introduced. Experimental results show that a significant gain in segmental SNR can be obtained over nonadaptive VQ with a negligible increase in complexity.

Merging spatially variant physical process models under an optimized systems dynamics framework.

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

Cain, William O.; Lowry, Thomas Stephen; Pierce, Suzanne A.

The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution systemmore » (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed.« less

Fluid dynamic characteristics of the VentrAssist rotary blood pump.

PubMed

Tansley, G; Vidakovic, S; Reizes, J

2000-06-01

The VentrAssist pump has no shaft or seal, and the device is unique in design because the rotor is suspended passively by hydrodynamic forces, and urging is accomplished by an integrated direct current motor rotor that also acts as the pump impeller. This device has led to many challenges in its fluidic design, namely large flow-blockage from impeller blades, low stiffness of bearings with concomitant impeller displacement under pulsatile load conditions, and very small running clearances. Low specific speed and radial blade off-flow were selected in order to minimize the hemolysis. Pulsatile and steady-flow tests show the impeller is stable under normal operating conditions. Computational fluid dynamics (CFD) has been used to optimize flow paths and reduce net axial force imbalance to acceptably small values. The latest design of the pump achieved a system efficiency of 18% (in 30% hematocrit of red blood cells suspended in phosphate-buffered saline), and efficiency was optimized over the range of operating conditions. Parameters critical to improving pump efficiency were investigated.

Effect of support flexibilty and damping on the dynamic response of a single mass flexible rotor in elastic bearings

NASA Technical Reports Server (NTRS)

Kirk, R. G.; Gunter, E. J.

1972-01-01

A steady state analysis of the shaft and the bearing housing motion was made by assuming synchronous precession of the system. The conditions under which the support system would act as a dynamic vibration absorber at the rotor critical speed were studied; plots of the rotor and support amplitudes, phase angles, and forces transmitted were evaluated by the computer, and the performance curves were automatically plotted by a CalComp plotter unit. Curves are presented on the optimization of the support housing characteristics to attenuate the rotor unbalance response over the entire rotor speed range. The complete transient motion including rotor unbalance was examined by integrating the equations of motion numerically using a modified fourth order Runge-Kutta procedure, and the resulting whirl orbits were plotted by the CalComp plotter unit. The results of the transient analysis are discussed with regards to the design optimization procedure derived from the steady-state analysis.

Optimizing Radiometric Fidelity to Enhance Aerial Image Change Detection Utilizing Digital Single Lens Reflex (DSLR) Cameras

NASA Astrophysics Data System (ADS)

Kerr, Andrew D.

Determining optimal imaging settings and best practices related to the capture of aerial imagery using consumer-grade digital single lens reflex (DSLR) cameras, should enable remote sensing scientists to generate consistent, high quality, and low cost image data sets. Radiometric optimization, image fidelity, image capture consistency and repeatability were evaluated in the context of detailed image-based change detection. The impetus for this research is in part, a dearth of relevant, contemporary literature, on the utilization of consumer grade DSLR cameras for remote sensing, and the best practices associated with their use. The main radiometric control settings on a DSLR camera, EV (Exposure Value), WB (White Balance), light metering, ISO, and aperture (f-stop), are variables that were altered and controlled over the course of several image capture missions. These variables were compared for their effects on dynamic range, intra-frame brightness variation, visual acuity, temporal consistency, and the detectability of simulated cracks placed in the images. This testing was conducted from a terrestrial, rather than an airborne collection platform, due to the large number of images per collection, and the desire to minimize inter-image misregistration. The results point to a range of slightly underexposed image exposure values as preferable for change detection and noise minimization fidelity. The makeup of the scene, the sensor, and aerial platform, influence the selection of the aperture and shutter speed which along with other variables, allow for estimation of the apparent image motion (AIM) motion blur in the resulting images. The importance of the image edges in the image application, will in part dictate the lowest usable f-stop, and allow the user to select a more optimal shutter speed and ISO. The single most important camera capture variable is exposure bias (EV), with a full dynamic range, wide distribution of DN values, and high visual contrast and acuity occurring around -0.7 to -0.3EV exposure bias. The ideal values for sensor gain, was found to be ISO 100, with ISO 200 a less desirable. This study offers researchers a better understanding of the effects of camera capture settings on RSI pairs and their influence on image-based change detection.

Rapid near-optimal trajectory generation and guidance law development for single-stage-to-orbit airbreathing vehicles

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1990-01-01

General problems associated with on-board trajectory optimization, propulsion system cycle selection, and with the synthesis of guidance laws were addressed for an ascent to low-earth-orbit of an air-breathing single-stage-to-orbit vehicle. The NASA Generic Hypersonic Aerodynamic Model Example and the Langley Accelerator aerodynamic sets were acquired and implemented. Work related to the development of purely analytic aerodynamic models was also performed at a low level. A generic model of a multi-mode propulsion system was developed that includes turbojet, ramjet, scramjet, and rocket engine cycles. Provisions were made in the dynamic model for a component of thrust normal to the flight path. Computational results, which characterize the nonlinear sensitivity of scramjet performance to changes in vehicle angle of attack, were obtained and incorporated into the engine model. Additional trajectory constraints were introduced: maximum dynamic pressure; maximum aerodynamic heating rate per unit area; angle of attack and lift limits; and limits on acceleration both along and normal to the flight path. The remainder of the effort focused on required modifications to a previously derived algorithm when the model complexity cited above was added. In particular, analytic switching conditions were derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another for two cases: the case in which engine cycle operations can overlap, and the case in which engine cycle operations are mutually exclusive. The resulting guidance algorithm was implemented in software and exercised extensively. It was found that the approximations associated with the assumed time scale separation employed in this work are reasonable except over the Mach range from roughly 5 to 8. This phenomenon is due to the very large thrust capability of scramjets in this Mach regime when sized to meet the requirement for ascent to orbit. By accounting for flight path angle and flight path angle rate in construction of the flight path over this Mach range, the resulting algorithm provides the means for rapid near-optimal trajectory generation and propulsion cycle selection over the entire Mach range from take-off to orbit.

Optimized balance rehabilitation training strategy for the elderly through an evaluation of balance characteristics in response to dynamic motions

PubMed Central

Jung, HoHyun; Chun, Keyoung Jin; Hong, Jaesoo; Lim, Dohyung

2015-01-01

Balance is important in daily activities and essential for maintaining an independent lifestyle in the elderly. Recent studies have shown that balance rehabilitation training can improve the balance ability of the elderly, and diverse balance rehabilitation training equipment has been developed. However, there has been little research into optimized strategies for balance rehabilitation training. To provide an optimized strategy, we analyzed the balance characteristics of participants in response to the rotation of a base plate on multiple axes. Seven male adults with no musculoskeletal or nervous system-related diseases (age: 25.5±1.7 years; height: 173.9±6.4 cm; body mass: 71.3±6.5 kg; body mass index: 23.6±2.4 kg/m2) were selected to investigate the balance rehabilitation training using customized rehabilitation equipment. Rotation of the base plate of the equipment was controlled to induce dynamic rotation of participants in the anterior–posterior, right-diagonal, medial–lateral, and left-diagonal directions. We used a three-dimensional motion capture system employing infrared cameras and the Pedar Flexible Insoles System to characterize the major lower-extremity joint angles, center of body mass, and center of pressure. We found statistically significant differences between the changes in joint angles in the lower extremities in response to dynamic rotation of the participants (P<0.05). The maximum was greater with anterior–posterior and medial–lateral dynamic rotation than with that in other directions (P<0.05). However, there were no statistically significant differences in the frequency of center of body mass deviations from the base of support (P>0.05). These results indicate that optimizing rotation control of the base plate of balance rehabilitation training equipment to induce anterior–posterior and medial–lateral dynamic rotation preferentially can lead to effective balance training. Additional tests with varied speeds and ranges of angles of base plate rotation are expected to be useful as well as an analysis of the balance characteristics considering a balance index that reflects the muscle activity and cooperative characteristics. PMID:26508847

Dynamics and Control of Three-Dimensional Perching Maneuver under Dynamic Stall Influence

NASA Astrophysics Data System (ADS)

Feroskhan, Mir Alikhan Bin Mohammad

Perching is a type of aggressive maneuver performed by the class 'Aves' species to attain precision point landing with a generally short landing distance. Perching capability is desirable on unmanned aerial vehicles (UAVs) due to its efficient deceleration process that potentially expands the functionality and flight envelope of the aircraft. This dissertation extends the previous works on perching, which is mostly limited to two-dimensional (2D) cases, to its state-of-the-art threedimensional (3D) variety. This dissertation presents the aerodynamic modeling and optimization framework adopted to generate unprecedented variants of the 3D perching maneuver that include the sideslip perching trajectory, which ameliorates the existing 2D perching concept by eliminating the undesirable undershoot and reliance on gravity. The sideslip perching technique methodically utilizes the lateral and longitudinal drag mechanisms through consecutive phases of yawing and pitching-up motion. Since perching maneuver involves high rates of change in the angles of attack and large turn rates, introduction of three internal variables thus becomes necessary for addressing the influence of dynamic stall delay on the UAV's transient post-stall behavior. These variables are then integrated into a static nonlinear aerodynamic model, developed using empirical and analytical methods, and into an optimization framework that generates a trajectory of sideslip perching maneuver, acquiring over 70% velocity reduction. An impact study of the dynamic stall influence on the optimal perching trajectories suggests that consideration of dynamic stall delay is essential due to the significant discrepancies in the corresponding control inputs required. A comparative study between 2D and 3D perching is also conducted to examine the different drag mechanisms employed by 2D and 3D perching respectively. 3D perching is presented as a more efficient deceleration technique with respect to spatial costs and initial altitude range. Contraction analysis is shown to be a useful technique in identifying the state variables that are required to be tracked for attaining stability of optimal perching trajectories. Based on the selected tracking variables, two sliding control strategies are proposed and comparatively examined to close the control loop and provide the required robustness and convergence to the optimal perching trajectory in the presence of perturbations and dynamic stall model inaccuracies. This dissertation concludes that the sliding controller with the adaptive gain feature is more effective and essential in providing better tracking performance through illustrations of the corresponding convergence area and at higher intensity of perturbations.

On the existence of the optimal order for wavefunction extrapolation in Born-Oppenheimer molecular dynamics

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

Fang, Jun; Wang, Han, E-mail: wang-han@iapcm.ac.cn; CAEP Software Center for High Performance Numerical Simulation, Beijing

2016-06-28

Wavefunction extrapolation greatly reduces the number of self-consistent field (SCF) iterations and thus the overall computational cost of Born-Oppenheimer molecular dynamics (BOMD) that is based on the Kohn–Sham density functional theory. Going against the intuition that the higher order of extrapolation possesses a better accuracy, we demonstrate, from both theoretical and numerical perspectives, that the extrapolation accuracy firstly increases and then decreases with respect to the order, and an optimal extrapolation order in terms of minimal number of SCF iterations always exists. We also prove that the optimal order tends to be larger when using larger MD time steps ormore » more strict SCF convergence criteria. By example BOMD simulations of a solid copper system, we show that the optimal extrapolation order covers a broad range when varying the MD time step or the SCF convergence criterion. Therefore, we suggest the necessity for BOMD simulation packages to open the user interface and to provide more choices on the extrapolation order. Another factor that may influence the extrapolation accuracy is the alignment scheme that eliminates the discontinuity in the wavefunctions with respect to the atomic or cell variables. We prove the equivalence between the two existing schemes, thus the implementation of either of them does not lead to essential difference in the extrapolation accuracy.« less

Characterization of classical static noise via qubit as probe

NASA Astrophysics Data System (ADS)

Javed, Muhammad; Khan, Salman; Ullah, Sayed Arif

2018-03-01

The dynamics of quantum Fisher information (QFI) of a single qubit coupled to classical static noise is investigated. The analytical relation for QFI fixes the optimal initial state of the qubit that maximizes it. An approximate limit for the time of coupling that leads to physically useful results is identified. Moreover, using the approach of quantum estimation theory and the analytical relation for QFI, the qubit is used as a probe to precisely estimate the disordered parameter of the environment. Relation for optimal interaction time with the environment is obtained, and condition for the optimal measurement of the noise parameter of the environment is given. It is shown that all values, in the mentioned range, of the noise parameter are estimable with equal precision. A comparison of our results with the previous studies in different classical environments is made.

Short-range correlation in high-momentum antisymmetrized molecular dynamics

NASA Astrophysics Data System (ADS)

Myo, Takayuki

2018-03-01

We propose a new variational method for treating short-range repulsion of bare nuclear force for nuclei in antisymmetrized molecular dynamics (AMD). In AMD, the short-range correlation is described in terms of large imaginary centroids of Gaussian wave packets of nucleon pairs in opposite signs, causing high-momentum components in the nucleon pairs. We superpose these AMD basis states and call this method "high-momentum AMD" (HM-AMD), which is capable of describing the strong tensor correlation [T. Myo et al., Prog. Theor. Exp. Phys., 2017, 111D01 (2017)]. In this letter, we extend HM-AMD by including up to two kinds of nucleon pairs in each AMD basis state utilizing the cluster expansion, which produces many-body correlations involving high-momentum components. We investigate how well HM-AMD describes the short-range correlation by showing the results for ^3H using the Argonne V4^' central potential. It is found that HM-AMD reproduces the results of few-body calculations and also the tensor-optimized AMD. This means that HM-AMD is a powerful approach to describe the short-range correlation in nuclei. In HM-AMD, the momentum directions of nucleon pairs isotropically contribute to the short-range correlation, which is different from the tensor correlation.

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the PJM Interconnect and show that it outperforms the baseline approach used in the industry.

A blood-mimicking fluid for particle image velocimetry with silicone vascular models

NASA Astrophysics Data System (ADS)

Yousif, Majid Y.; Holdsworth, David W.; Poepping, Tamie L.

2011-03-01

For accurate particle image velocimetry measurements in hemodynamics studies, it is important to use a fluid with a refractive index ( n) matching that of the vascular models (phantoms) and ideally a dynamic viscosity matching human blood. In this work, a blood-mimicking fluid (BMF) composed of water, glycerol, and sodium iodide was formulated for a range of refractive indices to match most common silicone elastomers ( n = 1.40-1.43) and with corresponding dynamic viscosity within the average cited range of healthy human blood (4.4 ± 0.5 cP). Both refractive index and viscosity were attained at room temperature (22.2 ± 0.2°C), which eliminates the need for a temperature-control system. An optimally matched BMF, suitable for use in a vascular phantom ( n = 1.4140 ± 0.0008, Sylgard 184), was demonstrated with composition (by weight) of 47.38% water, 36.94% glycerol (44:56 glycerol-water ratio), and 15.68% sodium iodide salt, resulting in a dynamic viscosity of 4 .31 ± 0 .03 cP.

Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework

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

Machnes, S.; Institute for Theoretical Physics, University of Ulm, D-89069 Ulm; Sander, U.

2011-08-15

For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions aremore » pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.« less

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

Global effectiveness of group decision-making strategies in coping with forage and price variabilities in commercial rangelands: A modelling assessment.

PubMed

Ibáñez, Javier; Martínez-Valderrama, Jaime

2018-07-01

This paper presents a modelling study that evaluated the global effectiveness of a range of group decision-making strategies for commercial farming areas in rangelands affected by temporal variations in forage production. The assessment utilised an integrated system dynamics model (86 equations) to examine the broad and long-term group decision outcomes. This model considers aspects usually neglected in related studies, such as the dynamics of the main local prices, the dynamics of the number of active farmers, the supplementary feeding of livestock, and certain behavioural traits of farmers and traders. The assessment procedure was based on an analysis of the outcomes of the model under 330,000 simulation scenarios. The results indicated that only if all the farmers in an area are either opportunistic or conservative that is, are either responsive or unresponsive to expected profits, the exploitation of the grazing resources were optimal in some senses. A widespread opportunism proved optimal only from an economic viewpoint. However, it is very unlikely that most of the farmers would agree to be opportunistic in practice. By contrast, a widespread conservatism, which in principle is perfectly feasible, proved optimal from economic, social, and ecological perspectives. Notably, it was found that the presence of a relatively small number of opportunistic farmers would suffice to considerably reduce the economic results of widespread conservatism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results.

PubMed

Orellana, Liliana; Rotnitzky, Andrea; Robins, James M

2010-03-03

In this companion article to "Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.

Evidence for Dynamic Network Regulation of Drosophila Photoreceptor Function from Mutants Lacking the Neurotransmitter Histamine

PubMed Central

Dau, An; Friederich, Uwe; Dongre, Sidhartha; Li, Xiaofeng; Bollepalli, Murali K.; Hardie, Roger C.; Juusola, Mikko

2016-01-01

Synaptic feedback from interneurons to photoreceptors can help to optimize visual information flow by balancing its allocation on retinal pathways under changing light conditions. But little is known about how this critical network operation is regulated dynamically. Here, we investigate this question by comparing signaling properties and performance of wild-type Drosophila R1–R6 photoreceptors to those of the hdcJK910 mutant, which lacks the neurotransmitter histamine and therefore cannot transmit information to interneurons. Recordings show that hdcJK910 photoreceptors sample similar amounts of information from naturalistic stimulation to wild-type photoreceptors, but this information is packaged in smaller responses, especially under bright illumination. Analyses reveal how these altered dynamics primarily resulted from network overload that affected hdcJK910 photoreceptors in two ways. First, the missing inhibitory histamine input to interneurons almost certainly depolarized them irrevocably, which in turn increased their excitatory feedback to hdcJK910 R1–R6s. This tonic excitation depolarized the photoreceptors to artificially high potentials, reducing their operational range. Second, rescuing histamine input to interneurons in hdcJK910 mutant also restored their normal phasic feedback modulation to R1–R6s, causing photoreceptor output to accentuate dynamic intensity differences at bright illumination, similar to the wild-type. These results provide mechanistic explanations of how synaptic feedback connections optimize information packaging in photoreceptor output and novel insight into the operation and design of dynamic network regulation of sensory neurons. PMID:27047343

A framework for modeling and optimizing dynamic systems under uncertainty

DOE PAGES

Nicholson, Bethany; Siirola, John

2017-11-11

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

A framework for modeling and optimizing dynamic systems under uncertainty

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

Nicholson, Bethany; Siirola, John

Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming.more » We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.« less

Dynamic optimization case studies in DYNOPT tool

NASA Astrophysics Data System (ADS)

Ozana, Stepan; Pies, Martin; Docekal, Tomas

2016-06-01

Dynamic programming is typically applied to optimization problems. As the analytical solutions are generally very difficult, chosen software tools are used widely. These software packages are often third-party products bound for standard simulation software tools on the market. As typical examples of such tools, TOMLAB and DYNOPT could be effectively applied for solution of problems of dynamic programming. DYNOPT will be presented in this paper due to its licensing policy (free product under GPL) and simplicity of use. DYNOPT is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimized, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parameterization both the control and the state profile vector. It is assumed, that the optimized dynamic model may be described by a set of ordinary differential equations (ODEs) or differential-algebraic equations (DAEs). This collection of functions extends the capability of the MATLAB Optimization Tool-box. The paper will introduce use of DYNOPT in the field of dynamic optimization problems by means of case studies regarding chosen laboratory physical educational models.

Theoretical and experimental investigation of the nonlinear dynamical trends of passively mode-locked quantum dot lasers

NASA Astrophysics Data System (ADS)

Raghunathan, Ravi

In recent years, passively mode-locked quantum dot lasers have shown great promise as compact, efficient and reliable pulsed sources of light for a range of precision and high performance applications, such as high bit-rate optical communications, diverse waveform generation, metrology, and clock distribution in high-performance computing (HPC) processors. For such applications, stable optical pulses with short picosecond pulse durations and multi-gigahertz repetition rates are required. In addition, a low pulse-to-pulse timing jitter is also necessary to prevent errors arising from the ambiguity between neighboring pulses. In order to optimize pulse quality in terms of optical characteristics such as pulse shape and pulse train behavior, as well as RF characteristics such as phase noise and timing jitter, understanding the nonlinear output dynamics of such devices is of critical importance, not only to get a sense of the regimes of operation where device output might be stable or unstable, but also to gain insight into the parameters that influence the output characteristics the most, and how they can be accessed and exploited to optimize design and performance for next generation applications. In this dissertation, theoretical and experimental studies have been combined to investigate the dynamical trends of two-section passively mode-locked quantum dot lasers. On the theoretical side, a novel numerical modeling scheme is presented as a powerful and versatile framework to study the nonlinear dynamics specific to a device, with device-specific parameters extracted over a range of operating conditions. The practical utility of this scheme is then demonstrated, first, in an analytical capability to interpret and explain dynamical trends observed in experiment, and subsequently, as a predictive tool to guide experiment to operate in a desired dynamical regime. Modeling results are compared to experimental findings where possible. Finally, optical feedback from an external reflector is experimentally studied as an additional control mechanism over the output dynamics of the device, and shown to enable invaluable insight into the behavior of the RF and optical spectra of the output. Together, the theoretical and experimental findings of this dissertation are shown to offer a systematic approach to understand, control and exploit the dynamical trends of passively mode-locked two-section quantum dot lasers.

Fission fragment charge and mass distributions in 239Pu(n, f ) in the adiabatic nuclear energy density functional theory

DOE PAGES

Regnier, D.; Dubray, N.; Schunck, N.; ...

2016-05-13

Here, accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r process to fuel cycle optimization for nuclear energy. The need for a predictive theory applicable where no data are available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics.

Integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades using multilevel decomposition

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1995-01-01

This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general-purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of global quantities (stiffness, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic designs are performed at a global level and the structural design is carried out at a detailed level with considerable dialog and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several examples.

Multilevel decomposition approach to integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1994-01-01

This paper describes an integrated aerodynamic, dynamic, and structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of local quantities (stiffnesses, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic design is performed at a global level and the structural design is carried out at a detailed level with considerable dialogue and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several cases.

High dynamic range CMOS-based mammography detector for FFDM and DBT

NASA Astrophysics Data System (ADS)

Peters, Inge M.; Smit, Chiel; Miller, James J.; Lomako, Andrey

2016-03-01

Digital Breast Tomosynthesis (DBT) requires excellent image quality in a dynamic mode at very low dose levels while Full Field Digital Mammography (FFDM) is a static imaging modality that requires high saturation dose levels. These opposing requirements can only be met by a dynamic detector with a high dynamic range. This paper will discuss a wafer-scale CMOS-based mammography detector with 49.5 μm pixels and a CsI scintillator. Excellent image quality is obtained for FFDM as well as DBT applications, comparing favorably with a-Se detectors that dominate the X-ray mammography market today. The typical dynamic range of a mammography detector is not high enough to accommodate both the low noise and the high saturation dose requirements for DBT and FFDM applications, respectively. An approach based on gain switching does not provide the signal-to-noise benefits in the low-dose DBT conditions. The solution to this is to add frame summing functionality to the detector. In one X-ray pulse several image frames will be acquired and summed. The requirements to implement this into a detector are low noise levels, high frame rates and low lag performance, all of which are unique characteristics of CMOS detectors. Results are presented to prove that excellent image quality is achieved, using a single detector for both DBT as well as FFDM dose conditions. This method of frame summing gave the opportunity to optimize the detector noise and saturation level for DBT applications, to achieve high DQE level at low dose, without compromising the FFDM performance.

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

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

PubMed

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

2018-01-15

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

A dynamic multi-level optimal design method with embedded finite-element modeling for power transformers

NASA Astrophysics Data System (ADS)

Zhang, Yunpeng; Ho, Siu-lau; Fu, Weinong

2018-05-01

This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

Preserving electron spin coherence in solids by optimal dynamical decoupling.

PubMed

Du, Jiangfeng; Rong, Xing; Zhao, Nan; Wang, Ya; Yang, Jiahui; Liu, R B

2009-10-29

To exploit the quantum coherence of electron spins in solids in future technologies such as quantum computing, it is first vital to overcome the problem of spin decoherence due to their coupling to the noisy environment. Dynamical decoupling, which uses stroboscopic spin flips to give an average coupling to the environment that is effectively zero, is a particularly promising strategy for combating decoherence because it can be naturally integrated with other desired functionalities, such as quantum gates. Errors are inevitably introduced in each spin flip, so it is desirable to minimize the number of control pulses used to realize dynamical decoupling having a given level of precision. Such optimal dynamical decoupling sequences have recently been explored. The experimental realization of optimal dynamical decoupling in solid-state systems, however, remains elusive. Here we use pulsed electron paramagnetic resonance to demonstrate experimentally optimal dynamical decoupling for preserving electron spin coherence in irradiated malonic acid crystals at temperatures from 50 K to room temperature. Using a seven-pulse optimal dynamical decoupling sequence, we prolonged the spin coherence time to about 30 mus; it would otherwise be about 0.04 mus without control or 6.2 mus under one-pulse control. By comparing experiments with microscopic theories, we have identified the relevant electron spin decoherence mechanisms in the solid. Optimal dynamical decoupling may be applied to other solid-state systems, such as diamonds with nitrogen-vacancy centres, and so lay the foundation for quantum coherence control of spins in solids at room temperature.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

Integrated aerodynamic/dynamic optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Chattopadhyay, Aditi; Walsh, Joanne L.; Riley, Michael F.

1989-01-01

An integrated aerodynamic/dynamic optimization procedure is used to minimize blade weight and 4 per rev vertical hub shear for a rotor blade in forward flight. The coupling of aerodynamics and dynamics is accomplished through the inclusion of airloads which vary with the design variables during the optimization process. Both single and multiple objective functions are used in the optimization formulation. The Global Criteria Approach is used to formulate the multiple objective optimization and results are compared with those obtained by using single objective function formulations. Constraints are imposed on natural frequencies, autorotational inertia, and centrifugal stress. The program CAMRAD is used for the blade aerodynamic and dynamic analyses, and the program CONMIN is used for the optimization. Since the spanwise and the azimuthal variations of loading are responsible for most rotor vibration and noise, the vertical airload distributions on the blade, before and after optimization, are compared. The total power required by the rotor to produce the same amount of thrust for a given area is also calculated before and after optimization. Results indicate that integrated optimization can significantly reduce the blade weight, the hub shear and the amplitude of the vertical airload distributions on the blade and the total power required by the rotor.

Anaerobic treatment of complex chemical wastewater in a sequencing batch biofilm reactor: process optimization and evaluation of factor interactions using the Taguchi dynamic DOE methodology.

PubMed

Venkata Mohan, S; Chandrasekhara Rao, N; Krishna Prasad, K; Murali Krishna, P; Sreenivas Rao, R; Sarma, P N

2005-06-20

The Taguchi robust experimental design (DOE) methodology has been applied on a dynamic anaerobic process treating complex wastewater by an anaerobic sequencing batch biofilm reactor (AnSBBR). For optimizing the process as well as to evaluate the influence of different factors on the process, the uncontrollable (noise) factors have been considered. The Taguchi methodology adopting dynamic approach is the first of its kind for studying anaerobic process evaluation and process optimization. The designed experimental methodology consisted of four phases--planning, conducting, analysis, and validation connected sequence-wise to achieve the overall optimization. In the experimental design, five controllable factors, i.e., organic loading rate (OLR), inlet pH, biodegradability (BOD/COD ratio), temperature, and sulfate concentration, along with the two uncontrollable (noise) factors, volatile fatty acids (VFA) and alkalinity at two levels were considered for optimization of the anae robic system. Thirty-two anaerobic experiments were conducted with a different combination of factors and the results obtained in terms of substrate degradation rates were processed in Qualitek-4 software to study the main effect of individual factors, interaction between the individual factors, and signal-to-noise (S/N) ratio analysis. Attempts were also made to achieve optimum conditions. Studies on the influence of individual factors on process performance revealed the intensive effect of OLR. In multiple factor interaction studies, biodegradability with other factors, such as temperature, pH, and sulfate have shown maximum influence over the process performance. The optimum conditions for the efficient performance of the anaerobic system in treating complex wastewater by considering dynamic (noise) factors obtained are higher organic loading rate of 3.5 Kg COD/m3 day, neutral pH with high biodegradability (BOD/COD ratio of 0.5), along with mesophilic temperature range (40 degrees C), and low sulfate concentration (700 mg/L). The optimization resulted in enhanced anaerobic performance (56.7%) from a substrate degradation rate (SDR) of 1.99 to 3.13 Kg COD/m3 day. Considering the obtained optimum factors, further validation experiments were carried out, which showed enhanced process performance (3.04 Kg COD/m3-day from 1.99 Kg COD/m3 day) accounting for 52.13% improvement with the optimized process conditions. The proposed method facilitated a systematic mathematical approach to understand the complex multi-species manifested anaerobic process treating complex chemical wastewater by considering the uncontrollable factors. Copyright (c) 2005 Wiley Periodicals, Inc.

Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays

PubMed Central

Hsieh, Helen V.; Dantzler, Jeffrey L.; Weigl, Bernhard H.

2017-01-01

Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness. PMID:28555034

Definitive screening design enables optimization of LC-ESI-MS/MS parameters in proteomics.

PubMed

Aburaya, Shunsuke; Aoki, Wataru; Minakuchi, Hiroyoshi; Ueda, Mitsuyoshi

2017-12-01

In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC-ESI-MS/MS to comprehensively identify these peptides. However, there are many parameters for LC-ESI-MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC-ESI-MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC-ESI-MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC-ESI-MS/MS systems.

Control of wavepacket dynamics in mixed alkali metal clusters by optimally shaped fs pulses

NASA Astrophysics Data System (ADS)

Bartelt, A.; Minemoto, S.; Lupulescu, C.; Vajda, Š.; Wöste, L.

We have performed adaptive feedback optimization of phase-shaped femtosecond laser pulses to control the wavepacket dynamics of small mixed alkali-metal clusters. An optimization algorithm based on Evolutionary Strategies was used to maximize the ion intensities. The optimized pulses for NaK and Na2K converged to pulse trains consisting of numerous peaks. The timing of the elements of the pulse trains corresponds to integer and half integer numbers of the vibrational periods of the molecules, reflecting the wavepacket dynamics in their excited states.

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.

PubMed

Wang, Haizhou; Song, Mingzhou

2011-12-01

The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.

Optimal control of HIV/AIDS dynamic: Education and treatment

NASA Astrophysics Data System (ADS)

Sule, Amiru; Abdullah, Farah Aini

2014-07-01

A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Panorama parking assistant system with improved particle swarm optimization method

NASA Astrophysics Data System (ADS)

Cheng, Ruzhong; Zhao, Yong; Li, Zhichao; Jiang, Weigang; Wang, Xin'an; Xu, Yong

2013-10-01

A panorama parking assistant system (PPAS) for the automotive aftermarket together with a practical improved particle swarm optimization method (IPSO) are proposed in this paper. In the PPAS system, four fisheye cameras are installed in the vehicle with different views, and four channels of video frames captured by the cameras are processed as a 360-deg top-view image around the vehicle. Besides the embedded design of PPAS, the key problem for image distortion correction and mosaicking is the efficiency of parameter optimization in the process of camera calibration. In order to address this problem, an IPSO method is proposed. Compared with other parameter optimization methods, the proposed method allows a certain range of dynamic change for the intrinsic and extrinsic parameters, and can exploit only one reference image to complete all of the optimization; therefore, the efficiency of the whole camera calibration is increased. The PPAS is commercially available, and the IPSO method is a highly practical way to increase the efficiency of the installation and the calibration of PPAS in automobile 4S shops.

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Closed-cycle gas dynamic laser design investigation

NASA Technical Reports Server (NTRS)

Ketch, G. W.; Young, W. E.

1977-01-01

A conceptual design study was made of a closed cycle gas-dynamic laser to provide definition of the major components in the laser loop. The system potential application is for long range power transmission by way of high power laser beams to provide satellite propulsion energy for orbit changing or station keeping. A parametric cycle optimization was conducted to establish the thermodynamic requirements for the system components. A conceptual design was conducted of the closed cycle system and the individual components to define physical characteristics and establish the system size and weight. Technology confirmation experimental demonstration programs were outlined to develop, evaluate, and demonstrate the technology base needed for this closed cycle GDL system.

Efficient analysis of mode profiles in elliptical microcavity using dynamic-thermal electron-quantum medium FDTD method.

PubMed

Khoo, E H; Ahmed, I; Goh, R S M; Lee, K H; Hung, T G G; Li, E P

2013-03-11

The dynamic-thermal electron-quantum medium finite-difference time-domain (DTEQM-FDTD) method is used for efficient analysis of mode profile in elliptical microcavity. The resonance peak of the elliptical microcavity is studied by varying the length ratio. It is observed that at some length ratios, cavity mode is excited instead of whispering gallery mode. This depicts that mode profiles are length ratio dependent. Through the implementation of the DTEQM-FDTD on graphic processing unit (GPU), the simulation time is reduced by 300 times as compared to the CPU. This leads to an efficient optimization approach to design microcavity lasers for wide range of applications in photonic integrated circuits.

Minimal feedback to a rhythm generator improves the robustness to slope variations of a compass biped.

PubMed

Spitz, Jonathan; Evstrachin, Alexandrina; Zacksenhouse, Miriam

2015-08-20

In recent years there has been a growing interest in the field of dynamic walking and bio-inspired robots. However, while walking and running on a flat surface have been studied extensively, walking dynamically over terrains with varying slope remains a challenge. Previously we developed an open loop controller based on a central pattern generator (CPG). The controller applied predefined torque patterns to a compass-gait biped, and achieved stable gaits over a limited range of slopes. In this work, this range is greatly extended by applying a once per cycle feedback to the CPG controller. The terrain's slope is measured and used to modify both the CPG frequency and the torque amplitude once per step. A multi-objective optimization algorithm was used to tune the controller parameters for a simulated CB model. The resulting controller successfully traverses terrains with slopes ranging from +7° to -8°, comparable to most slopes found in human constructed environments. Gait stability was verified by computing the linearized Poincaré Map both numerically and analytically.

Determination of phenylalanine isotope ratio enrichment by liquid chromatography/time- of-flight mass spectrometry.

PubMed

Wu, Zhanpin; Zhang, Xiao-Jun; Cody, Robert B; Wolfe, Robert R

2004-01-01

The application of time-of-flight mass spectrometry to isotope ratio measurements has been limited by the relatively low dynamic range of the time-to-digital converter detectors available on commercial LC/ToF-MS systems. Here we report the measurement of phenylalanine isotope ratio enrichment by using a new LC/ToF-MS system with wide dynamic range. Underivatized phenylalanine was injected onto a C18 column directly with 0.1% formic acid/acetonitrile as the mobile phase. The optimal instrument parameters for the time-of-flight mass spectrometer were determined by tuning the instrument with a phenylalanine standard. The accuracy of the isotope enrichment measurement was determined by the injection of standard solutions with known isotope ratios ranging from 0.02% to 9.2%. A plot of the results against the theoretical values gave a linear curve with R2 of 0.9999. The coefficient of variation for the isotope ratio measurement was below 2%. The method is simple, rapid, and accurate and presents an attractive alternative to traditional GC/MS applications.

Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part II: Proofs of Results*

PubMed Central

Orellana, Liliana; Rotnitzky, Andrea; Robins, James M.

2010-01-01

In this companion article to “Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content” [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption. PMID:20405047

Online optimal obstacle avoidance for rotary-wing autonomous unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Keeryun

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. The flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.

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

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

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

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

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

DOE PAGES

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

2016-06-17

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

Optimized, unequal pulse spacing in multiple echo sequences improves refocusing in magnetic resonance.

PubMed

Jenista, Elizabeth R; Stokes, Ashley M; Branca, Rosa Tamara; Warren, Warren S

2009-11-28

A recent quantum computing paper (G. S. Uhrig, Phys. Rev. Lett. 98, 100504 (2007)) analytically derived optimal pulse spacings for a multiple spin echo sequence designed to remove decoherence in a two-level system coupled to a bath. The spacings in what has been called a "Uhrig dynamic decoupling (UDD) sequence" differ dramatically from the conventional, equal pulse spacing of a Carr-Purcell-Meiboom-Gill (CPMG) multiple spin echo sequence. The UDD sequence was derived for a model that is unrelated to magnetic resonance, but was recently shown theoretically to be more general. Here we show that the UDD sequence has theoretical advantages for magnetic resonance imaging of structured materials such as tissue, where diffusion in compartmentalized and microstructured environments leads to fluctuating fields on a range of different time scales. We also show experimentally, both in excised tissue and in a live mouse tumor model, that optimal UDD sequences produce different T(2)-weighted contrast than do CPMG sequences with the same number of pulses and total delay, with substantial enhancements in most regions. This permits improved characterization of low-frequency spectral density functions in a wide range of applications.

Study of the dynamics of poly(ethylene oxide) by combining molecular dynamic simulations and neutron scattering experiments

NASA Astrophysics Data System (ADS)

Brodeck, M.; Alvarez, F.; Arbe, A.; Juranyi, F.; Unruh, T.; Holderer, O.; Colmenero, J.; Richter, D.

2009-03-01

We performed quasielastic neutron scattering experiments and atomistic molecular dynamics simulations on a poly(ethylene oxide) (PEO) homopolymer system above the melting point. The excellent agreement found between both sets of data, together with a successful comparison with literature diffraction results, validates the condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field used to produce our dynamic runs and gives support to their further analysis. This provided direct information on magnitudes which are not accessible from experiments such as the radial probability distribution functions of specific atoms at different times and their moments. The results of our simulations on the H-motions and different experiments indicate that in the high-temperature range investigated the dynamics is Rouse-like for Q-values below ≈0.6 Å-1. We then addressed the single chain dynamic structure factor with the simulations. A mode analysis, not possible directly experimentally, reveals the limits of applicability of the Rouse model to PEO. We discuss the possible origins for the observed deviations.

Study of the dynamics of poly(ethylene oxide) by combining molecular dynamic simulations and neutron scattering experiments.

PubMed

Brodeck, M; Alvarez, F; Arbe, A; Juranyi, F; Unruh, T; Holderer, O; Colmenero, J; Richter, D

2009-03-07

We performed quasielastic neutron scattering experiments and atomistic molecular dynamics simulations on a poly(ethylene oxide) (PEO) homopolymer system above the melting point. The excellent agreement found between both sets of data, together with a successful comparison with literature diffraction results, validates the condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field used to produce our dynamic runs and gives support to their further analysis. This provided direct information on magnitudes which are not accessible from experiments such as the radial probability distribution functions of specific atoms at different times and their moments. The results of our simulations on the H-motions and different experiments indicate that in the high-temperature range investigated the dynamics is Rouse-like for Q-values below approximately 0.6 A(-1). We then addressed the single chain dynamic structure factor with the simulations. A mode analysis, not possible directly experimentally, reveals the limits of applicability of the Rouse model to PEO. We discuss the possible origins for the observed deviations.

Quadratic partial eigenvalue assignment in large-scale stochastic dynamic systems for resilient and economic design

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

Das, Sonjoy; Goswami, Kundan; Datta, Biswa N.

2014-12-10

Failure of structural systems under dynamic loading can be prevented via active vibration control which shifts the damped natural frequencies of the systems away from the dominant range of loading spectrum. The damped natural frequencies and the dynamic load typically show significant variations in practice. A computationally efficient methodology based on quadratic partial eigenvalue assignment technique and optimization under uncertainty has been formulated in the present work that will rigorously account for these variations and result in an economic and resilient design of structures. A novel scheme based on hierarchical clustering and importance sampling is also developed in this workmore » for accurate and efficient estimation of probability of failure to guarantee the desired resilience level of the designed system. Numerical examples are presented to illustrate the proposed methodology.« less

Characteristic Analysis and Experiment of a Dynamic Flow Balance Valve

NASA Astrophysics Data System (ADS)

Bin, Li; Song, Guo; Xuyao, Mao; Chao, Wu; Deman, Zhang; Jin, Shang; Yinshui, Liu

2017-12-01

Comprehensive characteristics of a dynamic flow balance valve of water system were analysed. The flow balance valve can change the drag efficient automatically according to the condition of system, and the effective control flowrate is constant in the range of job pressure. The structure of the flow balance valve was introduced, and the theoretical calculation formula for the variable opening of the valve core was derived. A rated pressure of 20kPa to 200kPa and a rated flowrate of 10m3/h were offered in the numerical work. Static and fluent CFX analyses show good behaviours: through the valve core structure optimization and improve design of the compressive spring, the dynamic flow balance valve can stabilize the flowrate of system evidently. And experiments show that the flow control accuracy is within 5%.

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors

PubMed Central

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-01-01

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison. PMID:29614028

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

PubMed

Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

A model for rotorcraft flying qualities studies

NASA Technical Reports Server (NTRS)

Mittal, Manoj; Costello, Mark F.

1993-01-01

This paper outlines the development of a mathematical model that is expected to be useful for rotorcraft flying qualities research. A computer model is presented that can be applied to a range of different rotorcraft configurations. The algorithm computes vehicle trim and a linear state-space model of the aircraft. The trim algorithm uses non linear optimization theory to solve the nonlinear algebraic trim equations. The linear aircraft equations consist of an airframe model and a flight control system dynamic model. The airframe model includes coupled rotor and fuselage rigid body dynamics and aerodynamics. The aerodynamic model for the rotors utilizes blade element theory and a three state dynamic inflow model. Aerodynamics of the fuselage and fuselage empennages are included. The linear state-space description for the flight control system is developed using standard block diagram data.

Au nanoparticle-based sensor for apomorphine detection in plasma

PubMed Central

Lucotti, Andrea; Tommasini, Matteo; Trusso, Sebastiano; de Grazia, Ugo; Ciusani, Emilio; Ossi, Paolo M

2015-01-01

Summary Artificially roughened gold surfaces with controlled nanostructure produced by pulsed laser deposition have been investigated as sensors for apomorphine detection aiming at clinical application. The use of such gold surfaces has been optimized using aqueous solutions of apomorphine in the concentration range between 3.3 × 10−4 M and 3.3 × 10−7 M. The experimental parameters have been investigated and the dynamic concentration range of the sensor has been assessed by the selection of two apomorphine surface enhanced Raman scattering (SERS) peaks. The sensor behavior used to detect apomorphine in unfiltered human blood plasma is presented and discussed. PMID:26734514

General solution for high dynamic range three-dimensional shape measurement using the fringe projection technique

NASA Astrophysics Data System (ADS)

Feng, Shijie; Zhang, Yuzhen; Chen, Qian; Zuo, Chao; Li, Rubin; Shen, Guochen

2014-08-01

This paper presents a general solution for realizing high dynamic range three-dimensional (3-D) shape measurement based on fringe projection. Three concrete techniques are involved in the solution for measuring object with large range of reflectivity (LRR) or one with shiny specular surface. For the first technique, the measured surface reflectivities are sub-divided into several groups based on its histogram distribution, then the optimal exposure time for each group can be predicted adaptively so that the bright as well as dark areas on the measured surface are able to be handled without any compromise. Phase-shifted images are then captured at the calculated exposure times and a composite phase-shifted image is generated by extracting the optimally exposed pixels in the raw fringes images. For the second technique, it is proposed by introducing two orthogonal polarizers which are placed separately in front of the camera and projector into the first technique and the third one is developed by combining the second technique with the strategy of properly altering the angle between the transmission axes of the two polarizers. Experimental results show that the first technique can effectively improve the measurement accuracy of diffuse objects with LRR, the second one is capable of measuring object with weak specular reflection (WSR: e.g. shiny plastic surface) and the third can inspect surface with strong specular reflection (SSR: e.g. highlight on aluminum alloy) precisely. Further, more complex scene, such as the one with LRR and WSR, or even the one simultaneously involving LRR, WSR and SSR, can be measured accurately by the proposed solution.

Kalman Orbit Optimized Loop Tracking

NASA Technical Reports Server (NTRS)

Young, Lawrence E.; Meehan, Thomas K.

2011-01-01

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Stability-Constrained Aerodynamic Shape Optimization with Applications to Flying Wings

NASA Astrophysics Data System (ADS)

Mader, Charles Alexander

A set of techniques is developed that allows the incorporation of flight dynamics metrics as an additional discipline in a high-fidelity aerodynamic optimization. Specifically, techniques for including static stability constraints and handling qualities constraints in a high-fidelity aerodynamic optimization are demonstrated. These constraints are developed from stability derivative information calculated using high-fidelity computational fluid dynamics (CFD). Two techniques are explored for computing the stability derivatives from CFD. One technique uses an automatic differentiation adjoint technique (ADjoint) to efficiently and accurately compute a full set of static and dynamic stability derivatives from a single steady solution. The other technique uses a linear regression method to compute the stability derivatives from a quasi-unsteady time-spectral CFD solution, allowing for the computation of static, dynamic and transient stability derivatives. Based on the characteristics of the two methods, the time-spectral technique is selected for further development, incorporated into an optimization framework, and used to conduct stability-constrained aerodynamic optimization. This stability-constrained optimization framework is then used to conduct an optimization study of a flying wing configuration. This study shows that stability constraints have a significant impact on the optimal design of flying wings and that, while static stability constraints can often be satisfied by modifying the airfoil profiles of the wing, dynamic stability constraints can require a significant change in the planform of the aircraft in order for the constraints to be satisfied.

Dynamic optimization approach for integrated supplier selection and tracking control of single product inventory system with product discount

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Heru Tjahjana, R.

2017-01-01

In this paper, we propose a mathematical model in the form of dynamic/multi-stage optimization to solve an integrated supplier selection problem and tracking control problem of single product inventory system with product discount. The product discount will be stated as a piece-wise linear function. We use dynamic programming to solve this proposed optimization to determine the optimal supplier and the optimal product volume that will be purchased from the optimal supplier for each time period so that the inventory level tracks a reference trajectory given by decision maker with minimal total cost. We give a numerical experiment to evaluate the proposed model. From the result, the optimal supplier was determined for each time period and the inventory level follows the given reference well.

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

DOE PAGES

Blazewicz, Marek; Hinder, Ian; Koppelman, David M.; ...

2013-01-01

Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, the Chemora framework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization ismore » based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.« less

Performance evaluation and optimization of multiband phase-modulated radio over IsOWC link with balanced coherent homodyne detection

NASA Astrophysics Data System (ADS)

Zong, Kang; Zhu, Jiang

2018-04-01

In this paper, we present a multiband phase-modulated (PM) radio over intersatellite optical wireless communication (IsOWC) link with balanced coherent homodyne detection. The proposed system can provide the transparent transport of multiband radio frequency (RF) signals with higher linearity and better receiver sensitivity than intensity modulated with direct detection (IM/DD) system. The expressions of RF gain, noise figure (NF) and third-order spurious-free dynamic range (SFDR) are derived considering the third-order intermodulation product and amplifier spontaneous emission (ASE) noise. The optimal power of local oscillator (LO) optical signal is also derived theoretically. Numerical results for RF gain, NF and third-order SFDR are given for demonstration. Results indicate that the gain of the optical preamplifier and the power of LO optical signal should be optimized to obtain the satisfactory performance.

CFD research, parallel computation and aerodynamic optimization

NASA Technical Reports Server (NTRS)

Ryan, James S.

1995-01-01

Over five years of research in Computational Fluid Dynamics and its applications are covered in this report. Using CFD as an established tool, aerodynamic optimization on parallel architectures is explored. The objective of this work is to provide better tools to vehicle designers. Submarine design requires accurate force and moment calculations in flow with thick boundary layers and large separated vortices. Low noise production is critical, so flow into the propulsor region must be predicted accurately. The High Speed Civil Transport (HSCT) has been the subject of recent work. This vehicle is to be a passenger vehicle with the capability of cutting overseas flight times by more than half. A successful design must surpass the performance of comparable planes. Fuel economy, other operational costs, environmental impact, and range must all be improved substantially. For all these reasons, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer and other disciplines.

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

A novel methodology for non-linear system identification of battery cells used in non-road hybrid electric vehicles

NASA Astrophysics Data System (ADS)

Unger, Johannes; Hametner, Christoph; Jakubek, Stefan; Quasthoff, Marcus

2014-12-01

An accurate state of charge (SoC) estimation of a traction battery in hybrid electric non-road vehicles, which possess higher dynamics and power densities than on-road vehicles, requires a precise battery cell terminal voltage model. This paper presents a novel methodology for non-linear system identification of battery cells to obtain precise battery models. The methodology comprises the architecture of local model networks (LMN) and optimal model based design of experiments (DoE). Three main novelties are proposed: 1) Optimal model based DoE, which aims to high dynamically excite the battery cells at load ranges frequently used in operation. 2) The integration of corresponding inputs in the LMN to regard the non-linearities SoC, relaxation, hysteresis as well as temperature effects. 3) Enhancements to the local linear model tree (LOLIMOT) construction algorithm, to achieve a physical appropriate interpretation of the LMN. The framework is applicable for different battery cell chemistries and different temperatures, and is real time capable, which is shown on an industrial PC. The accuracy of the obtained non-linear battery model is demonstrated on cells with different chemistries and temperatures. The results show significant improvement due to optimal experiment design and integration of the battery non-linearities within the LMN structure.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

PubMed Central

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

PubMed

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

Mechanisms of small molecule–DNA interactions probed by single-molecule force spectroscopy

PubMed Central

Almaqwashi, Ali A.; Paramanathan, Thayaparan; Rouzina, Ioulia; Williams, Mark C.

2016-01-01

There is a wide range of applications for non-covalent DNA binding ligands, and optimization of such interactions requires detailed understanding of the binding mechanisms. One important class of these ligands is that of intercalators, which bind DNA by inserting aromatic moieties between adjacent DNA base pairs. Characterizing the dynamic and equilibrium aspects of DNA-intercalator complex assembly may allow optimization of DNA binding for specific functions. Single-molecule force spectroscopy studies have recently revealed new details about the molecular mechanisms governing DNA intercalation. These studies can provide the binding kinetics and affinity as well as determining the magnitude of the double helix structural deformations during the dynamic assembly of DNA–ligand complexes. These results may in turn guide the rational design of intercalators synthesized for DNA-targeted drugs, optical probes, or integrated biological self-assembly processes. Herein, we survey the progress in experimental methods as well as the corresponding analysis framework for understanding single molecule DNA binding mechanisms. We discuss briefly minor and major groove binding ligands, and then focus on intercalators, which have been probed extensively with these methods. Conventional mono-intercalators and bis-intercalators are discussed, followed by unconventional DNA intercalation. We then consider the prospects for using these methods in optimizing conventional and unconventional DNA-intercalating small molecules. PMID:27085806

Dynamic Behavior and Optimization of Advanced Armor Ceramics: January-December 2012 Annual Report

DTIC Science & Technology

2015-03-01

tasks are reviewed: Nanostructured Armor Ceramics: Focus on Boron Carbide; The Role of Microstructure in the Impact Resistance for Silicon Carbide...Task 2: The Role of Microstructure in the Impact Resistance for Silicon Carbide (SiC), Core Program 22 3.1 Long-Range Goals 22 3.2 Background 22 3.3...from a 2-gr drop test using corn starch as a C source; D(0.9) = 1.27 μm ....................................................................12 Fig

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

PubMed

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

Optimizing local capture of atrial fibrillation by rapid pacing: study of the influence of tissue dynamics.

PubMed

Uldry, Laurent; Virag, Nathalie; Jacquemet, Vincent; Vesin, Jean-Marc; Kappenberger, Lukas

2010-12-01

While successful termination by pacing of organized atrial tachycardias has been observed in patients, rapid pacing of AF can induce a local capture of the atrial tissue but in general no termination. The purpose of this study was to perform a systematic evaluation of the ability to capture AF by rapid pacing in a biophysical model of the atria with different dynamics in terms of conduction velocity (CV) and action potential duration (APD). Rapid pacing was applied during 30 s at five locations on the atria, for pacing cycle lengths in the range 60-110% of the mean AF cycle length (AFCL(mean)). Local AF capture could be achieved using rapid pacing at pacing sites located distal to major anatomical obstacles. Optimal pacing cycle lengths were found in the range 74-80% AFCL(mean) (capture window width: 14.6 ± 3% AFCL(mean)). An increase/decrease in CV or APD led to a significant shrinking/stretching of the capture window. Capture did not depend on AFCL, but did depend on the atrial substrate as characterized by an estimate of its wavelength, a better capture being achieved at shorter wavelengths. This model-based study suggests that a proper selection of the pacing site and cycle length can influence local capture results and that atrial tissue properties (CV and APD) are determinants of the response to rapid pacing.

Low-Thrust Many-Revolution Trajectory Optimization via Differential Dynamic Programming and a Sundman Transformation

NASA Astrophysics Data System (ADS)

Aziz, Jonathan D.; Parker, Jeffrey S.; Scheeres, Daniel J.; Englander, Jacob A.

2018-01-01

Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging optimization problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory optimization about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to an orbit angle and performing the optimization with differential dynamic programming. Fuel-optimal geocentric transfers are computed with the transfer duration extended up to 2000 revolutions. The flexibility of the approach to higher fidelity dynamics is shown with Earth's J 2 perturbation and lunar gravity included for a 500 revolution transfer.

Low-Thrust Many-Revolution Trajectory Optimization via Differential Dynamic Programming and a Sundman Transformation

NASA Astrophysics Data System (ADS)

Aziz, Jonathan D.; Parker, Jeffrey S.; Scheeres, Daniel J.; Englander, Jacob A.

2018-06-01

Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging optimization problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory optimization about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to an orbit angle and performing the optimization with differential dynamic programming. Fuel-optimal geocentric transfers are computed with the transfer duration extended up to 2000 revolutions. The flexibility of the approach to higher fidelity dynamics is shown with Earth's J 2 perturbation and lunar gravity included for a 500 revolution transfer.

MIMO radar waveform design with peak and sum power constraints

NASA Astrophysics Data System (ADS)

Arulraj, Merline; Jeyaraman, Thiruvengadam S.

2013-12-01

Optimal power allocation for multiple-input multiple-output radar waveform design subject to combined peak and sum power constraints using two different criteria is addressed in this paper. The first one is by maximizing the mutual information between the random target impulse response and the reflected waveforms, and the second one is by minimizing the mean square error in estimating the target impulse response. It is assumed that the radar transmitter has knowledge of the target's second-order statistics. Conventionally, the power is allocated to transmit antennas based on the sum power constraint at the transmitter. However, the wide power variations across the transmit antenna pose a severe constraint on the dynamic range and peak power of the power amplifier at each antenna. In practice, each antenna has the same absolute peak power limitation. So it is desirable to consider the peak power constraint on the transmit antennas. A generalized constraint that jointly meets both the peak power constraint and the average sum power constraint to bound the dynamic range of the power amplifier at each transmit antenna is proposed recently. The optimal power allocation using the concept of waterfilling, based on the sum power constraint, is the special case of p = 1. The optimal solution for maximizing the mutual information and minimizing the mean square error is obtained through the Karush-Kuhn-Tucker (KKT) approach, and the numerical solutions are found through a nested Newton-type algorithm. The simulation results show that the detection performance of the system with both sum and peak power constraints gives better detection performance than considering only the sum power constraint at low signal-to-noise ratio.

Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.

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

PubMed Central

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

2018-01-01

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model’s performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models’ performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors. PMID:29342942

Using of multi-walled carbon nanotubes electrode for adsorptive stripping voltammetric determination of ultratrace levels of RDX explosive in the environmental samples.

PubMed

Rezaei, Behzad; Damiri, Sajjad

2010-11-15

A study of the electrochemical behavior and determination of RDX, a high explosive, is described on a multi-walled carbon nanotubes (MWCNTs) modified glassy carbon electrode (GCE) using adsorptive stripping voltammetry and electrochemical impedance spectroscopy (EIS) techniques. The results indicated that MWCNTs electrode remarkably enhances the sensitivity of the voltammetric method and provides measurements of this explosive down to the sub-mg/l level in a wide pH range. The operational parameters were optimized and a sensitive, simple and time-saving cyclic voltammetric procedure was developed for the analysis of RDX in ground and tap water samples. Under optimized conditions, the reduction peak have two linear dynamic ranges of 0.6-20.0 and 8.0-200.0 mM with a detection limit of 25.0 nM and a precision of <4% (RSD for 8 analysis). Copyright © 2010 Elsevier B.V. All rights reserved.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method.

PubMed

Zomorodian, Mehdi; Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system.

Development and application of coupled system dynamics and game theory: A dynamic water conflict resolution method

PubMed Central

Lai, Sai Hin; Homayounfar, Mehran; Ibrahim, Shaliza; Pender, Gareth

2017-01-01

Conflicts over water resources can be highly dynamic and complex due to the various factors which can affect such systems, including economic, engineering, social, hydrologic, environmental and even political, as well as the inherent uncertainty involved in many of these factors. Furthermore, the conflicting behavior, preferences and goals of stakeholders can often make such conflicts even more challenging. While many game models, both cooperative and non-cooperative, have been suggested to deal with problems over utilizing and sharing water resources, most of these are based on a static viewpoint of demand points during optimization procedures. Moreover, such models are usually developed for a single reservoir system, and so are not really suitable for application to an integrated decision support system involving more than one reservoir. This paper outlines a coupled simulation-optimization modeling method based on a combination of system dynamics (SD) and game theory (GT). The method harnesses SD to capture the dynamic behavior of the water system, utilizing feedback loops between the system components in the course of the simulation. In addition, it uses GT concepts, including pure-strategy and mixed-strategy games as well as the Nash Bargaining Solution (NBS) method, to find the optimum allocation decisions over available water in the system. To test the capability of the proposed method to resolve multi-reservoir and multi-objective conflicts, two different deterministic simulation-optimization models with increasing levels of complexity were developed for the Langat River basin in Malaysia. The later is a strategic water catchment that has a range of different stakeholders and managerial bodies, which are however willing to cooperate in order to avoid unmet demand. In our first model, all water users play a dynamic pure-strategy game. The second model then adds in dynamic behaviors to reservoirs to factor in inflow uncertainty and adjust the strategies for the reservoirs using the mixed-strategy game and Markov chain methods. The two models were then evaluated against three performance indices: Reliability, Resilience and Vulnerability (R-R-V). The results showed that, while both models were well capable of dealing with conflict resolution over water resources in the Langat River basin, the second model achieved a substantially improved performance through its ability to deal with dynamicity, complexity and uncertainty in the river system. PMID:29216200

Optimal dynamic pricing for deteriorating items with reference-price effects

NASA Astrophysics Data System (ADS)

Xue, Musen; Tang, Wansheng; Zhang, Jianxiong

2016-07-01

In this paper, a dynamic pricing problem for deteriorating items with the consumers' reference-price effect is studied. An optimal control model is established to maximise the total profit, where the demand not only depends on the current price, but also is sensitive to the historical price. The continuous-time dynamic optimal pricing strategy with reference-price effect is obtained through solving the optimal control model on the basis of Pontryagin's maximum principle. In addition, numerical simulations and sensitivity analysis are carried out. Finally, some managerial suggestions that firm may adopt to formulate its pricing policy are proposed.

Dynamic Stability Analysis of Blunt Body Entry Vehicles Using Time-Lagged Aftbody Pitching Moments

NASA Technical Reports Server (NTRS)

Kazemba, Cole D.; Braun, Robert D.; Schoenenberger, Mark; Clark, Ian G.

2013-01-01

This analysis defines an analytic model for the pitching motion of blunt bodies during atmospheric entry. The proposed model is independent of the pitch damping sum coefficient present in the standard formulation of the equations of motion describing pitch oscillations of a decelerating blunt body, instead using the principle of a time-lagged aftbody moment as the forcing function for oscillation divergence. Four parameters, all with intuitive physical relevance, are introduced to fully define the aftbody moment and the associated time delay. It is shown that the dynamic oscillation responses typical to blunt bodies can be produced using hysteresis of the aftbody moment in place of the pitch damping coefficient. The approach used in this investigation is shown to be useful in understanding the governing physical mechanisms for blunt body dynamic stability and in guiding vehicle and mission design requirements. A validation case study using simulated ballistic range test data is conducted. From this, parameter identification is carried out through the use of a least squares optimizing routine. Results show good agreement with the limited existing literature for the parameters identified, suggesting that the model proposed could be validated by an experimental ballistic range test series. The trajectories produced by the identified parameters were found to match closely those from the MER ballistic range tests for a wide array of initial conditions and can be identified with a reasonable number of ballistic range shots and computational effort.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Computational and Mathematical Modeling of Coupled Superconducting Quantum Interference Devices

NASA Astrophysics Data System (ADS)

Berggren, Susan Anne Elizabeth

This research focuses on conducting an extensive computational investigation and mathematical analysis into the average voltage response of arrays of Superconducting Quantum Interference Devices (SQUIDs). These arrays will serve as the basis for the development of a sensitive, low noise, significantly lower Size, Weight and Power (SWaP) antenna integrated with Low-Noise Amplifier (LNA) using the SQUID technology. The goal for this antenna is to be capable of meeting all requirements for Guided Missile Destroyers (DDG) 1000 class ships for Information Operations/Signals Intelligence (IO/SIGINT) applications in Very High Frequency/Ultra High Frequency (V/UHF) bands. The device will increase the listening capability of receivers by moving technology into a new regime of energy detection allowing wider band, smaller size, more sensitive, stealthier systems. The smaller size and greater sensitivity will allow for ships to be “de-cluttered” of their current large dishes and devices, replacing everything with fewer and smaller SQUID antenna devices. The fewer devices present on the deck of a ship, the more invisible the ship will be to enemy forces. We invent new arrays of SQUIDs, optimized for signal detection with very high dynamic range and excellent spur-free dynamic range, while maintaining extreme small size (and low radar cross section), wide bandwidth, and environmentally noise limited sensitivity, effectively shifting the bottle neck of receiver systems forever away from the antenna itself deeper into the receiver chain. To accomplish these goals we develop and validate mathematical models for different designs of SQUID arrays and use them to invent a new device and systems design. This design is capable of significantly exceeding, per size weight and power, state-of-the-art receiver system measures of performance, such as bandwidth, sensitivity, dynamic range, and spurious-free dynamic range.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Comparison of five cluster validity indices performance in brain [18 F]FET-PET image segmentation using k-means.

PubMed

Abualhaj, Bedor; Weng, Guoyang; Ong, Melissa; Attarwala, Ali Asgar; Molina, Flavia; Büsing, Karen; Glatting, Gerhard

2017-01-01

Dynamic [ 18 F]fluoro-ethyl-L-tyrosine positron emission tomography ([ 18 F]FET-PET) is used to identify tumor lesions for radiotherapy treatment planning, to differentiate glioma recurrence from radiation necrosis and to classify gliomas grading. To segment different regions in the brain k-means cluster analysis can be used. The main disadvantage of k-means is that the number of clusters must be pre-defined. In this study, we therefore compared different cluster validity indices for automated and reproducible determination of the optimal number of clusters based on the dynamic PET data. The k-means algorithm was applied to dynamic [ 18 F]FET-PET images of 8 patients. Akaike information criterion (AIC), WB, I, modified Dunn's and Silhouette indices were compared on their ability to determine the optimal number of clusters based on requirements for an adequate cluster validity index. To check the reproducibility of k-means, the coefficients of variation CVs of the objective function values OFVs (sum of squared Euclidean distances within each cluster) were calculated using 100 random centroid initialization replications RCI 100 for 2 to 50 clusters. k-means was performed independently on three neighboring slices containing tumor for each patient to investigate the stability of the optimal number of clusters within them. To check the independence of the validity indices on the number of voxels, cluster analysis was applied after duplication of a slice selected from each patient. CVs of index values were calculated at the optimal number of clusters using RCI 100 to investigate the reproducibility of the validity indices. To check if the indices have a single extremum, visual inspection was performed on the replication with minimum OFV from RCI 100 . The maximum CV of OFVs was 2.7 × 10 -2 from all patients. The optimal number of clusters given by modified Dunn's and Silhouette indices was 2 or 3 leading to a very poor segmentation. WB and I indices suggested in median 5, [range 4-6] and 4, [range 3-6] clusters, respectively. For WB, I, modified Dunn's and Silhouette validity indices the suggested optimal number of clusters was not affected by the number of the voxels. The maximum coefficient of variation of WB, I, modified Dunn's, and Silhouette validity indices were 3 × 10 -2 , 1, 2 × 10 -1 and 3 × 10 -3 , respectively. WB-index showed a single global maximum, whereas the other indices showed also local extrema. From the investigated cluster validity indices, the WB-index is best suited for automated determination of the optimal number of clusters for [ 18 F]FET-PET brain images for the investigated image reconstruction algorithm and the used scanner: it yields meaningful results allowing better differentiation of tissues with higher number of clusters, it is simple, reproducible and has an unique global minimum. © 2016 American Association of Physicists in Medicine.

Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1993-01-01

The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.

Robust planning of dynamic wireless charging infrastructure for battery electric buses

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

Liu, Zhaocai; Song, Ziqi

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

Robust planning of dynamic wireless charging infrastructure for battery electric buses

DOE PAGES

Liu, Zhaocai; Song, Ziqi

2017-10-01

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses formore » a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less

The Fusion of Membranes and Vesicles: Pathway and Energy Barriers from Dissipative Particle Dynamics

PubMed Central

Grafmüller, Andrea; Shillcock, Julian; Lipowsky, Reinhard

2009-01-01

The fusion of lipid bilayers is studied with dissipative particle dynamics simulations. First, to achieve control over membrane properties, the effects of individual simulation parameters are studied and optimized. Then, a large number of fusion events for a vesicle and a planar bilayer are simulated using the optimized parameter set. In the observed fusion pathway, configurations of individual lipids play an important role. Fusion starts with individual lipids assuming a splayed tail configuration with one tail inserted in each membrane. To determine the corresponding energy barrier, we measure the average work for interbilayer flips of a lipid tail, i.e., the average work to displace one lipid tail from one bilayer to the other. This energy barrier is found to depend strongly on a certain dissipative particle dynamics parameter, and, thus, can be adjusted in the simulations. Overall, three subprocesses have been identified in the fusion pathway. Their energy barriers are estimated to lie in the range 8–15 kBT. The fusion probability is found to possess a maximum at intermediate tension values. As one decreases the tension, the fusion probability seems to vanish before the tensionless membrane state is attained. This would imply that the tension has to exceed a certain threshold value to induce fusion. PMID:19348749

An Optimization Framework for Dynamic Hybrid Energy Systems

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

Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problemmore » takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.« less

A microfluidic microreactor for the synthesis of gold nanorods.

PubMed

Day, Daniel; Gu, Min

2009-03-11

A microfluidic microreactor for the synthesis of gold nanorods is fabricated using femtosecond pulse laser microfabrication techniques. Femtosecond pulse lasers are able to etch a wide range of materials that are required for a microreactor, from the photomasks to the microheaters. The heating of the fluid in the microreactor is achieved through the design and fabrication of a microscale heating element incorporated onto the bottom surface of the microreactor which is capable of reaching temperatures greater than 130 degrees C. Computational fluid dynamic simulations of the heating profile of an optimized microreactor show increased heating performance with respect to a serpentine microreactor. The synthesis of gold nanorods is demonstrated in the optimized microreactor, based on a flow rate of 0.5 microg min(-1).

Optimal design of tweezer control for chimera states

NASA Astrophysics Data System (ADS)

Omelchenko, Iryna; Omel'chenko, Oleh E.; Zakharova, Anna; Schöll, Eckehard

2018-01-01

Chimera states are complex spatio-temporal patterns which consist of coexisting domains of spatially coherent and incoherent dynamics in systems of coupled oscillators. In small networks, chimera states usually exhibit short lifetimes and erratic drifting of the spatial position of the incoherent domain. A tweezer feedback control scheme can stabilize and fix the position of chimera states. We analyze the action of the tweezer control in small nonlocally coupled networks of Van der Pol and FitzHugh-Nagumo oscillators, and determine the ranges of optimal control parameters. We demonstrate that the tweezer control scheme allows for stabilization of chimera states with different shapes, and can be used as an instrument for controlling the coherent domains size, as well as the maximum average frequency difference of the oscillators.

Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

PubMed

Mazandarani, Mehran; Pariz, Naser

2018-05-01

This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

TH-AB-207A-07: Radiation Dose Simulation for a Newly Proposed Dynamic Bowtie Filters for CT Using Fast Monte Carlo Methods

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

Liu, T; Lin, H; Gao, Y

Purpose: Dynamic bowtie filter is an innovative design capable of modulating the X-ray and balancing the flux in the detectors, and it introduces a new way of patient-specific CT scan optimizations. This study demonstrates the feasibility of performing fast Monte Carlo dose calculation for a type of dynamic bowtie filter for cone-beam CT (Liu et al. 2014 9(7) PloS one) using MIC coprocessors. Methods: The dynamic bowtie filter in question consists of a highly attenuating bowtie component (HB) and a weakly attenuating bowtie (WB). The HB is filled with CeCl3 solution and its surface is defined by a transcendental equation.more » The WB is an elliptical cylinder filled with air and immersed in the HB. As the scanner rotates, the orientation of WB remains the same with the static patient. In our Monte Carlo simulation, the HB was approximated by 576 boxes. The phantom was a voxelized elliptical cylinder composed of PMMA and surrounded by air (44cm×44cm×40cm, 1000×1000×1 voxels). The dose to the PMMA phantom was tallied with 0.15% statistical uncertainty under 100 kVp source. Two Monte Carlo codes ARCHER and MCNP-6.1 were compared. Both used double-precision. Compiler flags that may trade accuracy for speed were avoided. Results: The wall time of the simulation was 25.4 seconds by ARCHER on a 5110P MIC, 40 seconds on a X5650 CPU, and 523 seconds by the multithreaded MCNP on the same CPU. The high performance of ARCHER is attributed to the parameterized geometry and vectorization of the program hotspots. Conclusion: The dynamic bowtie filter modeled in this study is able to effectively reduce the dynamic range of the detected signals for the photon-counting detectors. With appropriate software optimization methods, the accelerator-based (MIC and GPU) Monte Carlo dose engines have shown good performance and can contribute to patient-specific CT scan optimizations.« less

Parametric optimization and design validation based on finite element analysis of hybrid socket adapter for transfemoral prosthetic knee.

PubMed

Kumar, Neelesh

2014-10-01

Finite element analysis has been universally employed for the stress and strain analysis in lower extremity prosthetics. The socket adapter was the principal subject of interest due to its importance in deciding the knee motion range. This article focused on the static and dynamic stress analysis of the designed hybrid adapter developed by the authors. A standard mechanical design validation approach using von Mises was followed. Four materials were considered for the analysis, namely, carbon fiber, oil-filled nylon, Al-6061, and mild steel. The paper analyses the static and dynamic stress on designed hybrid adapter which incorporates features of conventional male and female socket adapters. The finite element analysis was carried out for possible different angles of knee flexion simulating static and dynamic gait situation. Research was carried out on available design of socket adapter. Mechanical design of hybrid adapter was conceptualized and a CAD model was generated using Inventor modelling software. Static and dynamic stress analysis was carried out on different materials for optimization. The finite element analysis was carried out on the software Autodesk Inventor Professional Ver. 2011. The peak value of von Mises stress occurred in the neck region of the adapter and in the lower face region at rod eye-adapter junction in static and dynamic analyses, respectively. Oil-filled nylon was found to be the best material among the four with respect to strength, weight, and cost. Research investigations on newer materials for development of improved prosthesis will immensely benefit the amputees. The study analyze the static and dynamic stress on the knee joint adapter to provide better material used for hybrid design of adapter. © The International Society for Prosthetics and Orthotics 2013.

An Optimization Framework for Dynamic, Distributed Real-Time Systems

NASA Technical Reports Server (NTRS)

Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara

2003-01-01

Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

Dynamic remapping decisions in multi-phase parallel computations

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Reynolds, P. F., Jr.

1986-01-01

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

Analytical nuclear gradients for the range-separated many-body dispersion model of noncovalent interactions.

PubMed

Blood-Forsythe, Martin A; Markovich, Thomas; DiStasio, Robert A; Car, Roberto; Aspuru-Guzik, Alán

2016-03-01

An accurate treatment of the long-range electron correlation energy, including van der Waals (vdW) or dispersion interactions, is essential for describing the structure, dynamics, and function of a wide variety of systems. Among the most accurate models for including dispersion into density functional theory (DFT) is the range-separated many-body dispersion (MBD) method [A. Ambrosetti et al. , J. Chem. Phys. , 2014, 140 , 18A508], in which the correlation energy is modeled at short-range by a semi-local density functional and at long-range by a model system of coupled quantum harmonic oscillators. In this work, we develop analytical gradients of the MBD energy with respect to nuclear coordinates, including all implicit coordinate dependencies arising from the partitioning of the charge density into Hirshfeld effective volumes. To demonstrate the efficiency and accuracy of these MBD gradients for geometry optimizations of systems with intermolecular and intramolecular interactions, we optimized conformers of the benzene dimer and isolated small peptides with aromatic side-chains. We find excellent agreement with the wavefunction theory reference geometries of these systems (at a fraction of the computational cost) and find that MBD consistently outperforms the popular TS and D3(BJ) dispersion corrections. To demonstrate the performance of the MBD model on a larger system with supramolecular interactions, we optimized the C 60 @C 60 H 28 buckyball catcher host-guest complex. In our analysis, we also find that neglecting the implicit nuclear coordinate dependence arising from the charge density partitioning, as has been done in prior numerical treatments, leads to an unacceptable error in the MBD forces, with relative errors of ∼20% (on average) that can extend well beyond 100%.

Integrated multidisciplinary design optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1989-01-01

The NASA/Army research plan for developing the logic elements for helicopter rotor design optimization by integrating appropriate disciplines and accounting for important interactions among the disciplines is discussed. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and an initial effort at defining the interdisciplinary coupling is summarized. Results are presented on the achievements made in the rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Some dynamics of signaling games.

PubMed

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-07-22

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions.

Some dynamics of signaling games

PubMed Central

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-01-01

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions. PMID:25024209

Dynamics of open quantum systems by interpolation of von Neumann and classical master equations, and its application to quantum annealing

NASA Astrophysics Data System (ADS)

Kadowaki, Tadashi

2018-02-01

We propose a method to interpolate dynamics of von Neumann and classical master equations with an arbitrary mixing parameter to investigate the thermal effects in quantum dynamics. The two dynamics are mixed by intervening to continuously modify their solutions, thus coupling them indirectly instead of directly introducing a coupling term. This maintains the quantum system in a pure state even after the introduction of thermal effects and obtains not only a density matrix but also a state vector representation. Further, we demonstrate that the dynamics of a two-level system can be rewritten as a set of standard differential equations, resulting in quantum dynamics that includes thermal relaxation. These equations are equivalent to the optical Bloch equations at the weak coupling and asymptotic limits, implying that the dynamics cause thermal effects naturally. Numerical simulations of ferromagnetic and frustrated systems support this idea. Finally, we use this method to study thermal effects in quantum annealing, revealing nontrivial performance improvements for a spin glass model over a certain range of annealing time. This result may enable us to optimize the annealing time of real annealing machines.

COPS: Large-scale nonlinearly constrained optimization problems

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

Bondarenko, A.S.; Bortz, D.M.; More, J.J.

2000-02-10

The authors have started the development of COPS, a collection of large-scale nonlinearly Constrained Optimization Problems. The primary purpose of this collection is to provide difficult test cases for optimization software. Problems in the current version of the collection come from fluid dynamics, population dynamics, optimal design, and optimal control. For each problem they provide a short description of the problem, notes on the formulation of the problem, and results of computational experiments with general optimization solvers. They currently have results for DONLP2, LANCELOT, MINOS, SNOPT, and LOQO.

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

PubMed

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Dynamic optimization and its relation to classical and quantum constrained systems

NASA Astrophysics Data System (ADS)

Contreras, Mauricio; Pellicer, Rely; Villena, Marcelo

2017-08-01

We study the structure of a simple dynamic optimization problem consisting of one state and one control variable, from a physicist's point of view. By using an analogy to a physical model, we study this system in the classical and quantum frameworks. Classically, the dynamic optimization problem is equivalent to a classical mechanics constrained system, so we must use the Dirac method to analyze it in a correct way. We find that there are two second-class constraints in the model: one fix the momenta associated with the control variables, and the other is a reminder of the optimal control law. The dynamic evolution of this constrained system is given by the Dirac's bracket of the canonical variables with the Hamiltonian. This dynamic results to be identical to the unconstrained one given by the Pontryagin equations, which are the correct classical equations of motion for our physical optimization problem. In the same Pontryagin scheme, by imposing a closed-loop λ-strategy, the optimality condition for the action gives a consistency relation, which is associated to the Hamilton-Jacobi-Bellman equation of the dynamic programming method. A similar result is achieved by quantizing the classical model. By setting the wave function Ψ(x , t) =e iS(x , t) in the quantum Schrödinger equation, a non-linear partial equation is obtained for the S function. For the right-hand side quantization, this is the Hamilton-Jacobi-Bellman equation, when S(x , t) is identified with the optimal value function. Thus, the Hamilton-Jacobi-Bellman equation in Bellman's maximum principle, can be interpreted as the quantum approach of the optimization problem.

Particle swarm optimization with recombination and dynamic linkage discovery.

PubMed

Chen, Ying-Ping; Peng, Wen-Chih; Jian, Ming-Chung

2007-12-01

In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 Institute of Electrical and Electronics Engineers Congress on Evolutionary Computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.

Optimal control on hybrid ode systems with application to a tick disease model.

PubMed

Ding, Wandi

2007-10-01

We are considering an optimal control problem for a type of hybrid system involving ordinary differential equations and a discrete time feature. One state variable has dynamics in only one season of the year and has a jump condition to obtain the initial condition for that corresponding season in the next year. The other state variable has continuous dynamics. Given a general objective functional, existence, necessary conditions and uniqueness for an optimal control are established. We apply our approach to a tick-transmitted disease model with age structure in which the tick dynamics changes seasonally while hosts have continuous dynamics. The goal is to maximize disease-free ticks and minimize infected ticks through an optimal control strategy of treatment with acaricide. Numerical examples are given to illustrate the results.

Comparative experimental study of dynamic compressive strength of mortar with glass and basalt fibres

NASA Astrophysics Data System (ADS)

Kruszka, Leopold; Moćko, Wojciech; Fenu, Luigi; Cadoni, Ezio

2015-09-01

Specimen reinforced with glass and basalt fibers were prepared using Standard Portland cement (CEM I, 52.5 R as prescribed by EN 197-1) and standard sand, in accordance with EN 196-1. From this cementitious mixture, a reference cement mortar without fibers was first prepared. Compressive strength, modulus of elasticity, and mod of fracture were determined for all specimens. Static and dynamic properties were investigated using Instron testing machine and split Hopkinson pressure bar, respectively. Content of the glass fibers in the mortar does not influence the fracture stress at static loading conditions in a clearly observed way. Moreover at dynamic range 5% content of the fiber results in a significant drop of fracture stress. Analysis of the basalt fibers influence on the fracture stress shows that optimal content of this reinforcement is equal to 3% for both static and dynamic loading conditions. Further increase of the fiber share gives the opposite effect, i.e. drop of the fracture stress.

RVB signatures in the spin dynamics of the square-lattice Heisenberg antiferromagnet

NASA Astrophysics Data System (ADS)

Ghioldi, E. A.; Gonzalez, M. G.; Manuel, L. O.; Trumper, A. E.

2016-03-01

We investigate the spin dynamics of the square-lattice spin-\\frac{1}{2} Heisenberg antiferromagnet by means of an improved mean-field Schwinger boson calculation. By identifying both, the long-range Néel and the RVB-like components of the ground state, we propose an educated guess for the mean-field magnetic excitation consisting on a linear combination of local and bond spin flips to compute the dynamical structure factor. Our main result is that when this magnetic excitation is optimized in such a way that the corresponding sum rule is fulfilled, we recover the low- and high-energy spectral weight features of the experimental spectrum. In particular, the anomalous spectral weight depletion at (π,0) found in recent inelastic neutron scattering experiments can be attributed to the interference of the triplet bond excitations of the RVB component of the ground state. We conclude that the Schwinger boson theory seems to be a good candidate to adequately interpret the dynamic properties of the square-lattice Heisenberg antiferromagnet.

Motion-Compensated Compression of Dynamic Voxelized Point Clouds.

PubMed

De Queiroz, Ricardo L; Chou, Philip A

2017-05-24

Dynamic point clouds are a potential new frontier in visual communication systems. A few articles have addressed the compression of point clouds, but very few references exist on exploring temporal redundancies. This paper presents a novel motion-compensated approach to encoding dynamic voxelized point clouds at low bit rates. A simple coder breaks the voxelized point cloud at each frame into blocks of voxels. Each block is either encoded in intra-frame mode or is replaced by a motion-compensated version of a block in the previous frame. The decision is optimized in a rate-distortion sense. In this way, both the geometry and the color are encoded with distortion, allowing for reduced bit-rates. In-loop filtering is employed to minimize compression artifacts caused by distortion in the geometry information. Simulations reveal that this simple motion compensated coder can efficiently extend the compression range of dynamic voxelized point clouds to rates below what intra-frame coding alone can accommodate, trading rate for geometry accuracy.

Exploring dynamics of molybdate in living animal cells by a genetically encoded FRET nanosensor.

PubMed

Nakanishi, Yoichi; Iida, Syuntaro; Ueoka-Nakanishi, Hanayo; Niimi, Tomoaki; Tomioka, Rie; Maeshima, Masayoshi

2013-01-01

Molybdenum (Mo) is an essential trace element for almost all living organisms including animals. Mo is used as a catalytic center of molybdo-enzymes for oxidation/reduction reactions of carbon, nitrogen, and sulfur metabolism. Whilst living cells are known to import inorganic molybdate oxyanion from the surrounding environment, the in vivo dynamics of cytosolic molybdate remain poorly understood as no appropriate indicator is available for this trace anion. We here describe a genetically encoded Förester-resonance-energy-transfer (FRET)-based nanosensor composed of CFP, YFP and the bacterial molybdate-sensor protein ModE. The nanosensor MolyProbe containing an optimized peptide-linker responded to nanomolar-range molybdate selectively, and increased YFP:CFP fluorescence intensity ratio by up to 109%. By introduction of the nanosensor, we have been able to successfully demonstrate the real-time dynamics of molybdate in living animal cells. Furthermore, time course analyses of the dynamics suggest that novel oxalate-sensitive- and sulfate-resistant- transporter(s) uptake molybdate in a model culture cell.

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.

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Psychosocial Domain.

PubMed

Sutin, Angelina R; Boutelle, Kerri; Czajkowski, Susan M; Epel, Elissa S; Green, Paige A; Hunter, Christine M; Rice, Elise L; Williams, David M; Young-Hyman, Deborah; Rothman, Alexander J

2018-04-01

Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, the psychosocial domain addresses how psychosocial processes underlie the influence of obesity treatment strategies on weight loss and weight maintenance. The subgroup for the psychosocial domain identified an initial list of high-priority constructs and measures that ranged from relatively stable characteristics about the person (cognitive function, personality) to dynamic characteristics that may change over time (motivation, affect). This paper describes (a) how the psychosocial domain fits into the broader model of weight loss and weight maintenance as conceptualized by ADOPT; (b) the guiding principles used to select constructs and measures for recommendation; (c) the high-priority constructs recommended for inclusion; (d) domain-specific issues for advancing the science; and (e) recommendations for future research. The inclusion of similar measures across trials will help to better identify how psychosocial factors mediate and moderate the weight loss and weight maintenance process, facilitate research into dynamic interactions with factors in the other ADOPT domains, and ultimately improve the design and delivery of effective interventions. © 2018 The Obesity Society.

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

PubMed

Benevicius, Vincas; Ostasevicius, Vytautas; Gaidys, Rimvydas

2013-08-22

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

Vehicle systems design optimization study

NASA Technical Reports Server (NTRS)

Gilmour, J. L.

1980-01-01

The optimum vehicle configuration and component locations are determined for an electric drive vehicle based on using the basic structure of a current production subcompact vehicle. The optimization of an electric vehicle layout requires a weight distribution in the range of 53/47 to 62/38 in order to assure dynamic handling characteristics comparable to current internal combustion engine vehicles. Necessary modification of the base vehicle can be accomplished without major modification of the structure or running gear. As long as batteries are as heavy and require as much space as they currently do, they must be divided into two packages, one at front under the hood and a second at the rear under the cargo area, in order to achieve the desired weight distribution. The weight distribution criteria requires the placement of batteries at the front of the vehicle even when the central tunnel is used for the location of some batteries. The optimum layout has a front motor and front wheel drive. This configuration provides the optimum vehicle dynamic handling characteristics and the maximum passenger and cargo space for a given size vehicle.

Analytically optimal parameters of dynamic vibration absorber with negative stiffness

NASA Astrophysics Data System (ADS)

Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu

2017-02-01

In this paper the optimal parameters of a dynamic vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.

Fixed-Order Mixed Norm Designs for Building Vibration Control

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Calise, Anthony J.

2000-01-01

This study investigates the use of H2, mu-synthesis, and mixed H2/mu methods to construct full order controllers and optimized controllers of fixed dimensions. The benchmark problem definition is first extended to include uncertainty within the controller bandwidth in the form of parametric uncertainty representative of uncertainty in the natural frequencies of the design model. The sensitivity of H2 design to unmodeled dynamics and parametric uncertainty is evaluated for a range of controller levels of authority. Next, mu-synthesis methods are applied to design full order compensators that are robust to both unmodeled dynamics and to parametric uncertainty. Finally, a set of mixed H2/mu compensators are designed which are optimized for a fixed compensator dimension. These mixed norm designs recover the H2 design performance levels while providing the same levels of robust stability as the mu designs. It is shown that designing with the mixed norm approach permits higher levels of controller authority for which the H2 designs are destabilizing. The benchmark problem is that of an active tendon system. The controller designs are all based on the use of acceleration feedback.

Three-dimensional-printed gas dynamic virtual nozzles for x-ray laser sample delivery

PubMed Central

Nelson, Garrett; Kirian, Richard A.; Weierstall, Uwe; Zatsepin, Nadia A.; Faragó, Tomáš; Baumbach, Tilo; Wilde, Fabian; Niesler, Fabian B. P.; Zimmer, Benjamin; Ishigami, Izumi; Hikita, Masahide; Bajt, Saša; Yeh, Syun-Ru; Rousseau, Denis L.; Chapman, Henry N.; Spence, John C. H.; Heymann, Michael

2016-01-01

Reliable sample delivery is essential to biological imaging using X-ray Free Electron Lasers (XFELs). Continuous injection using the Gas Dynamic Virtual Nozzle (GDVN) has proven valuable, particularly for time-resolved studies. However, many important aspects of GDVN functionality have yet to be thoroughly understood and/or refined due to fabrication limitations. We report the application of 2-photon polymerization as a form of high-resolution 3D printing to fabricate high-fidelity GDVNs with submicron resolution. This technique allows rapid prototyping of a wide range of different types of nozzles from standard CAD drawings and optimization of crucial dimensions for optimal performance. Three nozzles were tested with pure water to determine general nozzle performance and reproducibility, with nearly reproducible off-axis jetting being the result. X-ray tomography and index matching were successfully used to evaluate the interior nozzle structures and identify the cause of off-axis jetting. Subsequent refinements to fabrication resulted in straight jetting. A performance test of printed nozzles at an XFEL provided high quality femtosecond diffraction patterns. PMID:27410079

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

A comparison between the first-fit settings of two multichannel digital signal-processing strategies: music quality ratings and speech-in-noise scores.

PubMed

Higgins, Paul; Searchfield, Grant; Coad, Gavin

2012-06-01

The aim of this study was to determine which level-dependent hearing aid digital signal-processing strategy (DSP) participants preferred when listening to music and/or performing a speech-in-noise task. Two receiver-in-the-ear hearing aids were compared: one using 32-channel adaptive dynamic range optimization (ADRO) and the other wide dynamic range compression (WDRC) incorporating dual fast (4 channel) and slow (15 channel) processing. The manufacturers' first-fit settings based on participants' audiograms were used in both cases. Results were obtained from 18 participants on a quick speech-in-noise (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) task and for 3 music listening conditions (classical, jazz, and rock). Participants preferred the quality of music and performed better at the QuickSIN task using the hearing aids with ADRO processing. A potential reason for the better performance of the ADRO hearing aids was less fluctuation in output with change in sound dynamics. ADRO processing has advantages for both music quality and speech recognition in noise over the multichannel WDRC processing that was used in the study. Further evaluations of which DSP aspects contribute to listener preference are required.

Combustion Efficiency, Flameout Operability Limits and General Design Optimization for Integrated Ramjet-Scramjet Hypersonic Vehicles

NASA Astrophysics Data System (ADS)

Mbagwu, Chukwuka Chijindu

High speed, air-breathing hypersonic vehicles encounter a varied range of engine and operating conditions traveling along cruise/ascent missions at high altitudes and dynamic pressures. Variations of ambient pressure, temperature, Mach number, and dynamic pressure can affect the combustion conditions in conflicting ways. Computations were performed to understand propulsion tradeoffs that occur when a hypersonic vehicle travels along an ascent trajectory. Proper Orthogonal Decomposition methods were applied for the reduction of flamelet chemistry data in an improved combustor model. Two operability limits are set by requirements that combustion efficiency exceed selected minima and flameout be avoided. A method for flameout prediction based on empirical Damkohler number measurements is presented. Operability limits are plotted that define allowable flight corridors on an altitude versus flight Mach number performance map; fixed-acceleration ascent trajectories were considered for this study. Several design rules are also presented for a hypersonic waverider with a dual-mode scramjet engine. Focus is placed on ''vehicle integration" design, differing from previous ''propulsion-oriented" design optimization. The well-designed waverider falls between that of an aircraft (high lift-to-drag ratio) and a rocket (high thrust-to-drag ratio). 84 variations of an X-43-like vehicle were run using the MASIV scramjet reduced order model to examine performance tradeoffs. Informed by the vehicle design study, variable-acceleration trajectory optimization was performed for three constant dynamic pressures ascents. Computed flameout operability limits were implemented as additional constraints to the optimization problem. The Michigan-AFRL Scramjet In-Vehicle (MASIV) waverider model includes finite-rate chemistry, applied scaling laws for 3-D turbulent mixing, ram-scram transition and an empirical value of the flameout Damkohler number. A reduced-order modeling approach is justified (in lieu of higher-fidelity computational simulations) because all vehicle forces are computed multiple thousands of times to generate multi-dimensional performance maps. The findings of this thesis work present a number of compelling conclusions. It is found that the ideal operating conditions of a scramjet engine are heavily dependent on the ambient and combustor pressure (and less strongly on temperature). Combustor pressures of approximately 1.0 bar or greater achieve the highest combustion efficiency, in line with industry standards of more than 0.5 bar. Ascent trajectory analysis of combustion efficiency and lean-limit flameout dictate best operation at higher dynamic pressures and lower altitudes, but these goals are traded off by current structural limitations whereby dynamic pressures must remain below 100 kPa. Hypersonic waverider designs varied between an "airplane" and a "rocket" are found to have better performance with the latter design, with controllability and minimum elevon/rudder surface area as a stability constraint for the vehicle trim. Ultimately, these findings are beneficial and contribute to the overall understanding of dynamically stable waverider vehicles at hypersonic speeds. These types of vehicles have a range of applications from technology demonstration, to earth-to-low orbit payload transit, to most compellingly another step in the development and realization of viable supersonic commercial transport.

Dynamic microwave assisted extraction coupled with dispersive micro-solid-phase extraction of herbicides in soybeans.

PubMed

Li, Na; Wu, Lijie; Nian, Li; Song, Ying; Lei, Lei; Yang, Xiao; Wang, Kun; Wang, Zhibing; Zhang, Liyuan; Zhang, Hanqi; Yu, Aimin; Zhang, Ziwei

2015-09-01

Non-polar solvent dynamic microwave assisted extraction was firstly applied to the treatment of high-fat soybean samples. In the dispersive micro-solid-phase extraction (D-µ-SPE), the herbicides in the high-fat extract were directly adsorbed on metal-organic frameworks MIL-101(Cr). The effects of several experimental parameters, including extraction solvent, microwave absorption medium, microwave power, volume and flow rate of extraction solvent, amount of MIL-101(Cr), and D-µ-SPE time, were investigated. At the optimal conditions, the limits of detection for the herbicides ranged from 1.56 to 2.00 μg kg(-1). The relative recoveries of the herbicides were in the range of 91.1-106.7%, and relative standard deviations were equal to or lower than 6.7%. The present method was simple, rapid and effective. A large amount of fat was also removed. This method was demonstrated to be suitable for treatment of high-fat samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Dynamic Determination of Oxygenation and Lung Compliance in Murine Pneumonectomy

PubMed Central

Gibney, Barry; Lee, Grace S.; Houdek, Jan; Lin, Miao; Miele, Lino; Chamoto, Kenji; Konerding, Moritz A.; Tsuda, Akira; Mentzer, Steven J.

2012-01-01

Thoracic surgical procedures in mice have been applied to a wide range of investigations, but little is known about the murine physiologic response to pulmonary surgery. Using continuous arterial oximetry monitoring and the FlexiVent murine ventilator, we investigated the effect of anesthesia and pneumonectomy on mouse oxygen saturation and lung mechanics. Sedation resulted in a dose-dependent decline of oxygen saturation that ranged from 55–82%. Oxygen saturation was restored by mechanical ventilation with increased rate and tidal volumes. In the mouse strain studied, optimal ventilatory rates were a rate of 200/minute and a tidal volume of 10ml/kg. Sustained inflation pressures, referred to as a "recruitment maneuver," improved lung volumes, lung compliance and arterial oxygenation. In contrast, positive end expiratory pressure (PEEP) had a detrimental effect on oxygenation; an effect that was ameliorated after pneumonectomy. Our results confirm that lung volumes in the mouse are dynamically determined and suggest a threshold level of mechanical ventilation to maintain perioperative oxygen saturation. PMID:21574875

High dynamic range bio-molecular ion microscopy with the Timepix detector.

PubMed

Jungmann, Julia H; MacAleese, Luke; Visser, Jan; Vrakking, Marc J J; Heeren, Ron M A

2011-10-15

Highly parallel, active pixel detectors enable novel detection capabilities for large biomolecules in time-of-flight (TOF) based mass spectrometry imaging (MSI). In this work, a 512 × 512 pixel, bare Timepix assembly combined with chevron microchannel plates (MCP) captures time-resolved images of several m/z species in a single measurement. Mass-resolved ion images from Timepix measurements of peptide and protein standards demonstrate the capability to return both mass-spectral and localization information of biologically relevant analytes from matrix-assisted laser desorption ionization (MALDI) on a commercial ion microscope. The use of a MCP-Timepix assembly delivers an increased dynamic range of several orders of magnitude. The Timepix returns defined mass spectra already at subsaturation MCP gains, which prolongs the MCP lifetime and allows the gain to be optimized for image quality. The Timepix peak resolution is only limited by the resolution of the in-pixel measurement clock. Oligomers of the protein ubiquitin were measured up to 78 kDa. © 2011 American Chemical Society

Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum.

PubMed

Yasuma, Fumihito; Mitsunaga, Tomoo; Iso, Daisuke; Nayar, Shree K

2010-09-01

We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at least some of the filter types. This leads to reconstructed images with strong aliasing. We make four contributions in this paper: 1) we present a comprehensive optimization method to arrive at the spatial and spectral layout of the color filter array of a GAP camera. 2) We develop a novel algorithm for reconstructing the under-sampled channels of the image while minimizing aliasing artifacts. 3) We demonstrate how the user can capture a single image and then control the tradeoff of spatial resolution to generate a variety of images, including monochrome, high dynamic range (HDR) monochrome, RGB, HDR RGB, and multispectral images. 4) Finally, the performance of our GAP camera has been verified using extensive simulations that use multispectral images of real world scenes. A large database of these multispectral images has been made available at http://www1.cs.columbia.edu/CAVE/projects/gap_camera/ for use by the research community.

An automated approach for tone mapping operator parameter adjustment in security applications

NASA Astrophysics Data System (ADS)

Krasula, LukáÅ.¡; Narwaria, Manish; Le Callet, Patrick

2014-05-01

High Dynamic Range (HDR) imaging has been gaining popularity in recent years. Different from the traditional low dynamic range (LDR), HDR content tends to be visually more appealing and realistic as it can represent the dynamic range of the visual stimuli present in the real world. As a result, more scene details can be faithfully reproduced. As a direct consequence, the visual quality tends to improve. HDR can be also directly exploited for new applications such as video surveillance and other security tasks. Since more scene details are available in HDR, it can help in identifying/tracking visual information which otherwise might be difficult with typical LDR content due to factors such as lack/excess of illumination, extreme contrast in the scene, etc. On the other hand, with HDR, there might be issues related to increased privacy intrusion. To display the HDR content on the regular screen, tone-mapping operators (TMO) are used. In this paper, we present the universal method for TMO parameters tuning, in order to maintain as many details as possible, which is desirable in security applications. The method's performance is verified on several TMOs by comparing the outcomes from tone-mapping with default and optimized parameters. The results suggest that the proposed approach preserves more information which could be of advantage for security surveillance but, on the other hand, makes us consider possible increase in privacy intrusion.

Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

PubMed

Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

2016-08-03

Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.

Future contingencies and photovoltaic system worth

NASA Astrophysics Data System (ADS)

Jones, G. J.; Thomas, M. G.; Bonk, G. J.

1982-09-01

The value of dispersed photovoltaic systems connected to the utility grid was calculated using the optimized generation planning program. The 1986 to 2001 time period was used for this study. Photovoltaic systems were dynamically integrated, up to 5% total capacity, into 9 NERC based regions under a range of future fuel and economic contingencies. Value was determined by the change in revenue requirements due to the photovoltaic additions. Displacement of high cost fuel was paramount to value, while capacity displacement was highly variable and dependent upon regional fuel mix.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Moyer, W. R.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1973-01-01

The following tasks related to the design, construction, and evaluation of a mobile planetary vehicle for unmanned exploration of Mars are discussed: (1) design and construction of a 0.5 scale dynamic vehicle; (2) mathematical modeling of vehicle dynamics; (3) experimental 0.4 scale vehicle dynamics measurements and interpretation; (4) vehicle electro-mechanical control systems; (5) remote control systems; (6) collapsibility and deployment concepts and hardware; (7) design, construction and evaluation of a wheel with increased lateral stiffness, (8) system design optimization; (9) design of an on-board computer; (10) design and construction of a laser range finder; (11) measurement of reflectivity of terrain surfaces; (12) obstacle perception by edge detection; (13) terrain modeling based on gradients; (14) laser scan systems; (15) path selection system simulation and evaluation; (16) gas chromatograph system concepts; (17) experimental chromatograph separation measurements and chromatograph model improvement and evaluation.

Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity

NASA Astrophysics Data System (ADS)

Manfredi, S.; Di Tucci, E.; Latora, V.

2018-02-01

Multilayer networks describe well many real interconnected communication and transportation systems, ranging from computer networks to multimodal mobility infrastructures. Here, we introduce a model in which the nodes have a limited capacity of storing and processing the agents moving over a multilayer network, and their congestions trigger temporary faults which, in turn, dynamically affect the routing of agents seeking for uncongested paths. The study of the network performance under different layer velocities and node maximum capacities reveals the existence of delicate trade-offs between the number of served agents and their time to travel to destination. We provide analytical estimates of the optimal buffer size at which the travel time is minimum and of its dependence on the velocity and number of links at the different layers. Phenomena reminiscent of the slower is faster effect and of the Braess' paradox are observed in our dynamical multilayer setup.

Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity.

PubMed

Manfredi, S; Di Tucci, E; Latora, V

2018-02-09

Multilayer networks describe well many real interconnected communication and transportation systems, ranging from computer networks to multimodal mobility infrastructures. Here, we introduce a model in which the nodes have a limited capacity of storing and processing the agents moving over a multilayer network, and their congestions trigger temporary faults which, in turn, dynamically affect the routing of agents seeking for uncongested paths. The study of the network performance under different layer velocities and node maximum capacities reveals the existence of delicate trade-offs between the number of served agents and their time to travel to destination. We provide analytical estimates of the optimal buffer size at which the travel time is minimum and of its dependence on the velocity and number of links at the different layers. Phenomena reminiscent of the slower is faster effect and of the Braess' paradox are observed in our dynamical multilayer setup.

Automated identification of functional dynamic networks from X-ray crystallography

PubMed Central

van den Bedem, Henry; Bhabha, Gira; Yang, Kun; Wright, Peter E.; Fraser, James S.

2013-01-01

Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active site conformations and consequently alter protein function. In addition to comparing independently determined X-ray crystal structures, alternative conformations observed at low levels of electron density have the potential to provide mechanistic insights into conformational dynamics. Here, we report a new multi-conformer contact network algorithm (CONTACT) that identifies networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks in Escherichia coli dihydrofolate reductase (ecDHFR) predict the long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild type and mutant ecDHFR suggests how mutations that alter optimized networks of coordinated motions can impair catalytic function. Thus, CONTACT-guided mutagenesis will allow the structure-dynamics-function relationship to be exploited in protein engineering and design. PMID:23913260

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

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

Huang, Xiaobiao; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Neural dynamic optimization for control systems. I. Background.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Neural dynamic optimization for control systems.III. Applications.

PubMed

Seong, C Y; Widrow, B

2001-01-01

For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.

Neural dynamic optimization for control systems.II. Theory.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Robust input design for nonlinear dynamic modeling of AUV.

PubMed

Nouri, Nowrouz Mohammad; Valadi, Mehrdad

2017-09-01

Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Improving the Dynamic Characteristics of Body-in-White Structure Using Structural Optimization

PubMed Central

Yahaya Rashid, Aizzat S.; Mohamed Haris, Sallehuddin; Alias, Anuar

2014-01-01

The dynamic behavior of a body-in-white (BIW) structure has significant influence on the noise, vibration, and harshness (NVH) and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process. PMID:25101312

Multi-frame X-ray Phase Contrast Imaging (MPCI) for Dynamic Experiments

NASA Astrophysics Data System (ADS)

Iverson, Adam; Carlson, Carl; Sanchez, Nathaniel; Jensen, Brian

2017-06-01

Recent advances in coupling synchrotron X-ray diagnostics to dynamic experiments are providing new information about the response of materials at extremes. For example, propagation based X-ray Phase Contrast Imaging (PCI) which is sensitive to differences in density has been successfully used to study a wide range of phenomena, e.g. jet-formation, compression of additive manufactured (AM) materials, and detonator dynamics. In this talk, we describe the current multi-frame X-ray phase contrast imaging (MPCI) system which allows up to eight frames per experiment, remote optimization, and an improved optical design that increases optical efficiency and accommodates dual-magnification during a dynamic event. Data will be presented that used the dual-magnification feature to obtain multiple images of an exploding foil initiator. In addition, results from static testing will be presented that used a multiple scintillator configuration required to extend the density retrieval to multi-constituent, or heterogeneous systems. The continued development of this diagnostic is fundamentally important to capabilities at the APS including IMPULSE and the Dynamic Compression Sector (DCS), and will benefit future facilities such as MaRIE at Los Alamos National Laboratory.

Diffusion dynamics of the Li+ ion on a model surface of amorphous carbon: a direct molecular orbital dynamics study.

PubMed

Tachikawa, Hiroto; Shimizu, Akira

2005-07-14

Diffusion processes of the Li+ ion on a model surface of amorphous carbon (Li+C96H24 system) have been investigated by means of the direct molecular orbital (MO) dynamics method at the semiempirical AM1 level. The total energy and energy gradient on the full-dimensional AM1 potential energy surface were calculated at each time step in the dynamics calculation. The optimized structure, where Li+ is located in the center of the cluster, was used as the initial structure at time zero. The dynamics calculation was carried out in the temperature range 100-1000 K. The calculations showed that the Li+ ion vibrates around the equilibrium point below 200 K, while the Li+ ion moves on the surface above 250 K. At intermediate temperatures (300 K < T < 400 K), the ion moves on the surface and falls in the edge regions of the cluster. At higher temperatures (600 K < T), the Li+ ion transfers freely on the surface and edge regions. The diffusion pathway of the Li+ ion was discussed on the basis of theoretical results.

Ion dynamics in a trapped ion mobility spectrometer†

PubMed Central

Hernandez, Diana Rosa; DeBord, John Daniel; Ridgeway, Mark E.; Kaplan, Desmond A.; Park, Melvin A.; Fernandez-Lima, Francisco

2014-01-01

In the present paper, theoretical simulations and experimental observations are used to describe the ion dynamics in a trapped ion mobility spectrometer. In particular, the ion motion, ion transmission and mobility separation are discussed as a function of the bath gas velocity, radial confinement, analysis time and speed. Mobility analysis and calibration procedure are reported for the case of sphere-like molecules for positive and negative ion modes. Results showed that a maximal mobility resolution can be achieved by optimizing the gas velocity, radial confinement (RF amplitude) and ramp speed (voltage range and ramp time). The mobility resolution scales with the electric field and gas velocity and R = 100–250 can be routinely obtained at room temperature. PMID:24571000

Investigation of monolithic passively mode-locked quantum dot lasers with extremely low repetition frequency.

PubMed

Xu, Tianhong; Cao, Juncheng; Montrosset, Ivo

2015-01-01

The dynamical regimes and performance optimization of quantum dot monolithic passively mode-locked lasers with extremely low repetition rate are investigated using the numerical method. A modified multisection delayed differential equation model is proposed to accomplish simulations of both two-section and three-section passively mode-locked lasers with long cavity. According to the numerical simulations, it is shown that fundamental and harmonic mode-locking regimes can be multistable over a wide current range. These dynamic regimes are studied, and the reasons for their existence are explained. In addition, we demonstrate that fundamental pulses with higher peak power can be achieved when the laser is designed to work in a region with smaller differential gain.

Assessing Electrolyte Transport Properties with Molecular Dynamics

DOE PAGES

Jones, R. E.; Ward, D. K.; Gittleson, F. S.; ...

2017-04-15

Here in this work we use estimates of ionic transport properties obtained from molecular dynamics to rank lithium electrolytes of different compositions. We develop linear response methods to obtain the Onsager diffusivity matrix for all chemical species, its Fickian counterpart, and the mobilities of the ionic species. We apply these methods to the well-studied propylene carbonate/ethylene carbonate solvent with dissolved LiBF 4 and O 2. The results show that, over a range of lithium concentrations and carbonate mixtures, trends in the transport coefficients can be identified and optimal electrolytes can be selected for experimental focus; however, refinement of these estimationmore » techniques is necessary for a reliable ranking of a large set of electrolytes.« less

Adaptive critics for dynamic optimization.

PubMed

Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar

2010-06-01

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. Copyright 2010 Elsevier Ltd. All rights reserved.

Optimal control of Atlantic population Canada geese

USGS Publications Warehouse

Hauser, C.E.; Runge, M.C.; Cooch, E.G.; Johnson, F.A.; Harvey, W.F.

2007-01-01

Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy.

A globally nonsingular quaternion-based formulation for all-electric satellite trajectory optimization

NASA Astrophysics Data System (ADS)

Libraro, Paola

The general electric propulsion orbit-raising maneuver of a spacecraft must contend with four main limiting factors: the longer time of flight, multiple eclipses prohibiting continuous thrusting, long exposure to radiation from the Van Allen belt and high power requirement of the electric engines. In order to optimize a low-thrust transfer with respect to these challenges, the choice of coordinates and corresponding equations of motion used to describe the kinematical and dynamical behavior of the satellite is of critical importance. This choice can potentially affect the numerical optimization process as well as limit the set of mission scenarios that can be investigated. To increase the ability to determine the feasible set of mission scenarios able to address the challenges of an all-electric orbit-raising, a set of equations free of any singularities is required to consider a completely arbitrary injection orbit. For this purpose a new quaternion-based formulation of a spacecraft translational dynamics that is globally nonsingular has been developed. The minimum-time low-thrust problem has been solved using the new set of equations of motion inside a direct optimization scheme in order to investigate optimal low-thrust trajectories over the full range of injection orbit inclinations between 0 and 90 degrees with particular focus on high-inclinations. The numerical results consider a specific mission scenario in order to analyze three key aspects of the problem: the effect of the initial guess on the shape and duration of the transfer, the effect of Earth oblateness on transfer time and the role played by, radiation damage and power degradation in all-electric minimum-time transfers. Finally trade-offs between mass and cost savings are introduced through a test case.

Optimal dynamic pricing and replenishment policy for perishable items with inventory-level-dependent demand

NASA Astrophysics Data System (ADS)

Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng

2016-04-01

An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the optimal joint dynamic pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a dynamic decision variable, is presented to compare with the joint dynamic policy. Numerical results demonstrate the advantages of the joint dynamic one, and further show the effects of different system parameters on the optimal joint dynamic policy and the maximal total profit.

Fast optimization of glide vehicle reentry trajectory based on genetic algorithm

NASA Astrophysics Data System (ADS)

Jia, Jun; Dong, Ruixing; Yuan, Xuejun; Wang, Chuangwei

2018-02-01

An optimization method of reentry trajectory based on genetic algorithm is presented to meet the need of reentry trajectory optimization for glide vehicle. The dynamic model for the glide vehicle during reentry period is established. Considering the constraints of heat flux, dynamic pressure, overload etc., the optimization of reentry trajectory is investigated by utilizing genetic algorithm. The simulation shows that the method presented by this paper is effective for the optimization of reentry trajectory of glide vehicle. The efficiency and speed of this method is comparative with the references. Optimization results meet all constraints, and the on-line fast optimization is potential by pre-processing the offline samples.

Comparative dynamics in a health investment model.

PubMed

Eisenring, C

1999-10-01

The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.

Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization

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

Barragán, A. M., E-mail: ana.barragan@uclouvain.be; Differding, S.; Lee, J. A.

Purpose: To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system. Methods: For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTV{sub PET}) was calculated from {sup 18}FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number ofmore » fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTV{sub PET} inevitably leads to overdosing, which was compared for both optimization schemes. Results: The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTV{sub PET} (worst case) were above 5% of DPBN prescription for robust-optimized plans, while they were more than 50% for PTV plans. Low dose to organs at risk (OARs) could be achieved for both PTV and robust-optimized plans. Conclusions: DPBN in proton therapy is feasible with the use of a sufficient number subcontours, automatically generated scanning patterns, and no more than three beams are needed. Robust optimization ensured the required target coverage and minimal overdosing, while PTV-approach led to nonrobust plans with excessive overdose. Low dose to OARs can be achieved even in the presence of a high-dose escalation as in DPBN.« less

Optimization technique of wavefront coding system based on ZEMAX externally compiled programs

NASA Astrophysics Data System (ADS)

Han, Libo; Dong, Liquan; Liu, Ming; Zhao, Yuejin; Liu, Xiaohua

2016-10-01

Wavefront coding technique as a means of athermalization applied to infrared imaging system, the design of phase plate is the key to system performance. This paper apply the externally compiled programs of ZEMAX to the optimization of phase mask in the normal optical design process, namely defining the evaluation function of wavefront coding system based on the consistency of modulation transfer function (MTF) and improving the speed of optimization by means of the introduction of the mathematical software. User write an external program which computes the evaluation function on account of the powerful computing feature of the mathematical software in order to find the optimal parameters of phase mask, and accelerate convergence through generic algorithm (GA), then use dynamic data exchange (DDE) interface between ZEMAX and mathematical software to realize high-speed data exchanging. The optimization of the rotational symmetric phase mask and the cubic phase mask have been completed by this method, the depth of focus increases nearly 3 times by inserting the rotational symmetric phase mask, while the other system with cubic phase mask can be increased to 10 times, the consistency of MTF decrease obviously, the maximum operating temperature of optimized system range between -40°-60°. Results show that this optimization method can be more convenient to define some unconventional optimization goals and fleetly to optimize optical system with special properties due to its externally compiled function and DDE, there will be greater significance for the optimization of unconventional optical system.

Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.

2009-01-01

An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and dynamic grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

Design optimization of dual-axis driving mechanism for satellite antenna with two planar revolute clearance joints

NASA Astrophysics Data System (ADS)

Bai, Zheng Feng; Zhao, Ji Jun; Chen, Jun; Zhao, Yang

2018-03-01

In the dynamic analysis of satellite antenna dual-axis driving mechanism, it is usually assumed that the joints are ideal or perfect without clearances. However, in reality, clearances in joints are unavoidable due to assemblage, manufacturing errors and wear. When clearance is introduced to the mechanism, it will lead to poor dynamic performances and undesirable vibrations due to impact forces in clearance joint. In this paper, a design optimization method is presented to reduce the undesirable vibrations of satellite antenna considering clearance joints in dual-axis driving mechanism. The contact force model in clearance joint is established using a nonlinear spring-damper model and the friction effect is considered using a modified Coulomb friction model. Firstly, the effects of clearances on dynamic responses of satellite antenna are investigated. Then the optimization method for dynamic design of the dual-axis driving mechanism with clearance is presented. The objective of the optimization is to minimize the maximum absolute vibration peak of antenna acceleration by reducing the impact forces in clearance joint. The main consideration here is to optimize the contact parameters of the joint elements. The contact stiffness coefficient, damping coefficient and the dynamic friction coefficient for clearance joint elements are taken as the optimization variables. A Generalized Reduced Gradient (GRG) algorithm is used to solve this highly nonlinear optimization problem for dual-axis driving mechanism with clearance joints. The results show that the acceleration peaks of satellite antenna and contact forces in clearance joints are reduced obviously after design optimization, which contributes to a better performance of the satellite antenna. Also, the application and limitation of the proposed optimization method are discussed.

Multiobjective optimization of temporal processes.

PubMed

Song, Zhe; Kusiak, Andrew

2010-06-01

This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data. An evolutionary strategy algorithm is then applied to solve the optimization problem guided by the knowledge extracted by the DM algorithm. The concept presented in this paper is illustrated with the data from a power plant, where the goal is to maximize the boiler efficiency and minimize the limestone consumption. This multiobjective optimization problem can be either transformed into a single-objective optimization problem through preference aggregation approaches or into a Pareto-optimal optimization problem. The computational results have shown the effectiveness of the proposed optimization framework.

Optimal Guaranteed Cost Sliding Mode Control for Constrained-Input Nonlinear Systems With Matched and Unmatched Disturbances.

PubMed

Zhang, Huaguang; Qu, Qiuxia; Xiao, Geyang; Cui, Yang

2018-06-01

Based on integral sliding mode and approximate dynamic programming (ADP) theory, a novel optimal guaranteed cost sliding mode control is designed for constrained-input nonlinear systems with matched and unmatched disturbances. When the system moves on the sliding surface, the optimal guaranteed cost control problem of sliding mode dynamics is transformed into the optimal control problem of a reformulated auxiliary system with a modified cost function. The ADP algorithm based on single critic neural network (NN) is applied to obtain the approximate optimal control law for the auxiliary system. Lyapunov techniques are used to demonstrate the convergence of the NN weight errors. In addition, the derived approximate optimal control is verified to guarantee the sliding mode dynamics system to be stable in the sense of uniform ultimate boundedness. Some simulation results are presented to verify the feasibility of the proposed control scheme.

A weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1989-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

A weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1990-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

Weak Hamiltonian finite element method for optimal control problems

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Bless, Robert R.

1991-01-01

A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.

A dynamic model of functioning of a bank

NASA Astrophysics Data System (ADS)

Malafeyev, Oleg; Awasthi, Achal; Zaitseva, Irina; Rezenkov, Denis; Bogdanova, Svetlana

2018-04-01

In this paper, we analyze dynamic programming as a novel approach to solve the problem of maximizing the profits of a bank. The mathematical model of the problem and the description of bank's work is described in this paper. The problem is then approached using the method of dynamic programming. Dynamic programming makes sure that the solutions obtained are globally optimal and numerically stable. The optimization process is set up as a discrete multi-stage decision process and solved with the help of dynamic programming.

Terahertz Josephson spectral analysis and its applications

NASA Astrophysics Data System (ADS)

Snezhko, A. V.; Gundareva, I. I.; Lyatti, M. V.; Volkov, O. Y.; Pavlovskiy, V. V.; Poppe, U.; Divin, Y. Y.

2017-04-01

Principles of Hilbert-transform spectral analysis (HTSA) are presented and advantages of the technique in the terahertz (THz) frequency range are discussed. THz HTSA requires Josephson junctions with high values of characteristic voltages I c R n and dynamics described by a simple resistively shunted junction (RSJ) model. To meet these requirements, [001]- and [100]-tilt YBa2Cu3O7-x bicrystal junctions with deviations from the RSJ model less than 1% have been developed. Demonstrators of Hilbert-transform spectrum analyzers with various cryogenic environments, including integration into Stirling coolers, are described. Spectrum analyzers have been characterized in the spectral range from 50 GHz to 3 THz. Inside a power dynamic range of five orders, an instrumental function of the analyzers has been found to have a Lorentz form around a single frequency of 1.48 THz with a spectral resolution as low as 0.9 GHz. Spectra of THz radiation from optically pumped gas lasers and semiconductor frequency multipliers have been studied with these spectrum analyzers and the regimes of these radiation sources were optimized for a single-frequency operation. Future applications of HTSA will be related with quick and precise spectral characterization of new radiation sources and identification of substances in the THz frequency range.

Comparison of two microextraction methods based on solidification of floating organic droplet for the determination of multiclass analytes in river water samples by liquid chromatography tandem mass spectrometry using Central Composite Design.

PubMed

Asati, Ankita; Satyanarayana, G N V; Patel, Devendra K

2017-09-01

Two low density organic solvents based liquid-liquid microextraction methods, namely Vortex assisted liquid-liquid microextraction based on solidification of floating organic droplet (VALLME-SFO) and Dispersive liquid-liquid microextraction based on solidification of floating organic droplet(DLLME-SFO) have been compared for the determination of multiclass analytes (pesticides, plasticizers, pharmaceuticals and personal care products) in river water samples by using liquid chromatography tandem mass spectrometry (LC-MS/MS). The effect of various experimental parameters on the efficiency of the two methods and their optimum values were studied with the aid of Central Composite Design (CCD) and Response Surface Methodology(RSM). Under optimal conditions, VALLME-SFO was validated in terms of limit of detection, limit of quantification, dynamic linearity range, determination of coefficient, enrichment factor and extraction recovery for which the respective values were (0.011-0.219ngmL -1 ), (0.035-0.723ngmL -1 ), (0.050-0.500ngmL -1 ), (R 2 =0.992-0.999), (40-56), (80-106%). However, when the DLLME-SFO method was validated under optimal conditions, the range of values of limit of detection, limit of quantification, dynamic linearity range, determination of coefficient, enrichment factor and extraction recovery were (0.025-0.377ngmL -1 ), (0.083-1.256ngmL -1 ), (0.100-1.000ngmL -1 ), (R 2 =0.990-0.999), (35-49), (69-98%) respectively. Interday and intraday precisions were calculated as percent relative standard deviation (%RSD) and the values were ≤15% for VALLME-SFO and DLLME-SFO methods. Both methods were successfully applied for determining multiclass analytes in river water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Mechanical design optimization of a single-axis MOEMS accelerometer based on a grating interferometry cavity for ultrahigh sensitivity

NASA Astrophysics Data System (ADS)

Lu, Qianbo; Bai, Jian; Wang, Kaiwei; Lou, Shuqi; Jiao, Xufen; Han, Dandan; Yang, Guoguang

2016-08-01

The ultrahigh static displacement-acceleration sensitivity of a mechanical sensing chip is essential primarily for an ultrasensitive accelerometer. In this paper, an optimal design to implement to a single-axis MOEMS accelerometer consisting of a grating interferometry cavity and a micromachined sensing chip is presented. The micromachined sensing chip is composed of a proof mass along with its mechanical cantilever suspension and substrate. The dimensional parameters of the sensing chip, including the length, width, thickness and position of the cantilevers are evaluated and optimized both analytically and by finite-element-method (FEM) simulation to yield an unprecedented acceleration-displacement sensitivity. Compared with one of the most sensitive single-axis MOEMS accelerometers reported in the literature, the optimal mechanical design can yield a profound sensitivity improvement with an equal footprint area, specifically, 200% improvement in displacement-acceleration sensitivity with moderate resonant frequency and dynamic range. The modified design was microfabricated, packaged with the grating interferometry cavity and tested. The experimental results demonstrate that the MOEMS accelerometer with modified design can achieve the acceleration-displacement sensitivity of about 150μm/g and acceleration sensitivity of greater than 1500V/g, which validates the effectiveness of the optimal design.

Digital radiography: optimization of image quality and dose using multi-frequency software.

PubMed

Precht, H; Gerke, O; Rosendahl, K; Tingberg, A; Waaler, D

2012-09-01

New developments in processing of digital radiographs (DR), including multi-frequency processing (MFP), allow optimization of image quality and radiation dose. This is particularly promising in children as they are believed to be more sensitive to ionizing radiation than adults. To examine whether the use of MFP software reduces the radiation dose without compromising quality at DR of the femur in 5-year-old-equivalent anthropomorphic and technical phantoms. A total of 110 images of an anthropomorphic phantom were imaged on a DR system (Canon DR with CXDI-50 C detector and MLT[S] software) and analyzed by three pediatric radiologists using Visual Grading Analysis. In addition, 3,500 images taken of a technical contrast-detail phantom (CDRAD 2.0) provide an objective image-quality assessment. Optimal image-quality was maintained at a dose reduction of 61% with MLT(S) optimized images. Even for images of diagnostic quality, MLT(S) provided a dose reduction of 88% as compared to the reference image. Software impact on image quality was found significant for dose (mAs), dynamic range dark region and frequency band. By optimizing image processing parameters, a significant dose reduction is possible without significant loss of image quality.

Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

NASA Astrophysics Data System (ADS)

Kania, Adhe; Sidarto, Kuntjoro Adji

2016-02-01

Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

Multivariate constrained shape optimization: Application to extrusion bell shape for pasta production

NASA Astrophysics Data System (ADS)

Sarghini, Fabrizio; De Vivo, Angela; Marra, Francesco

2017-10-01

Computational science and engineering methods have allowed a major change in the way products and processes are designed, as validated virtual models - capable to simulate physical, chemical and bio changes occurring during production processes - can be realized and used in place of real prototypes and performing experiments, often time and money consuming. Among such techniques, Optimal Shape Design (OSD) (Mohammadi & Pironneau, 2004) represents an interesting approach. While most classical numerical simulations consider fixed geometrical configurations, in OSD a certain number of geometrical degrees of freedom is considered as a part of the unknowns: this implies that the geometry is not completely defined, but part of it is allowed to move dynamically in order to minimize or maximize the objective function. The applications of optimal shape design (OSD) are uncountable. For systems governed by partial differential equations, they range from structure mechanics to electromagnetism and fluid mechanics or to a combination of the three. This paper presents one of possible applications of OSD, particularly how extrusion bell shape, for past production, can be designed by applying a multivariate constrained shape optimization.

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

PubMed

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-08-14

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

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

PubMed Central

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-01-01

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

Natural mortality estimation and rational exploitation of purpleback flying squid Sthenoteuthis oualaniensis in the southern South China Sea

NASA Astrophysics Data System (ADS)

Wang, Xuehui; Qiu, Yongsong; Zhang, Peng; Du, Feiyan

2017-07-01

Based on the biological data of purpleback flying squid ( Sthenoteuthis oualaniensis) collected by light falling-net in the southern South China Sea (SCS) during September to October 2012 and March to April 2013, growth and mortality of `Medium' and `Dwarf' forms of squid are derived using the Powell-Wetherall, ELEFAN methods and length-converted catch curves (FiSAT package). Given a lack of commercial exploitation, we assume total mortality to be due entirely to natural mortality. We estimate these squid have fast growth, with growth coefficients ( k) ranging from 1.42 to 2.39, and high natural mortality ( M), with estimates ranging from 1.61 to 2.92. To sustainably exploit these squid stocks, yield per recruitment based on growth and natural mortality was determined using the Beverton-Holt dynamic pool model. We demonstrate squid stocks could sustain high fishing mortality and low ages at first capture, with an optimal fishing mortality >3.0, with the optimal age at first capture increased to 0.4-0.6 years when fishing mortality approached optimal levels. On the basis of our analyses and estimates of stock biomass, we believe considerable potential exists to expand the squid fishery into the open SCS, relieving fishing pressure on coastal waters.

Using a Pareto-optimal solution set to characterize trade-offs between a broad range of values and preferences in climate risk management

NASA Astrophysics Data System (ADS)

Garner, Gregory; Reed, Patrick; Keller, Klaus

2015-04-01

Integrated assessment models (IAMs) are often used to inform the design of climate risk management strategies. Previous IAM studies have broken important new ground on analyzing the effects of parametric uncertainties, but they are often silent on the implications of uncertainties regarding the problem formulation. Here we use the Dynamic Integrated model of Climate and the Economy (DICE) to analyze the effects of uncertainty surrounding the definition of the objective(s). The standard DICE model adopts a single objective to maximize a weighted sum of utilities of per-capita consumption. Decision makers, however, are often concerned with a broader range of values and preferences that may be poorly captured by this a priori definition of utility. We reformulate the problem by introducing three additional objectives that represent values such as (i) reliably limiting global average warming to two degrees Celsius and minimizing (ii) the costs of abatement and (iii) the climate change damages. We use advanced multi-objective optimization methods to derive a set of Pareto-optimal solutions over which decision makers can trade-off and assess performance criteria a posteriori. We illustrate the potential for myopia in the traditional problem formulation and discuss the capability of this multiobjective formulation to provide decision support.

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

PubMed

Lin, Yi-Chung; Pandy, Marcus G

2017-07-05

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking. Copyright © 2017 Elsevier Ltd. All rights reserved.

TU-AB-303-01: A Feasibility Study for Dynamic Adaptive Therapy of Non-Small Cell Lung Cancer

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

Kim, M; Phillips, M

2015-06-15

Purpose: To compare plans for NSCLC optimized using Dynamic Adaptive Therapy (DAT) with conventional IMRT optimization. DAT adapts plans based on changes in the target volume by using dynamic programing techniques to consider expected changes into the optimization process. Information gathered during treatment, e.g. from CBCT, is incorporated into the optimization. Methods and materials: DAT is formulated using stochastic control formalism, which minimizes the total expected number of tumor cells at the end of a treatment course subject to uncertainty inherent in the tumor response and organs-at-risk (OAR) dose constraints. This formulation allows for non-stationary dose distribution as well asmore » non-stationary fractional dose as needed to achieve a series of optimal plans that are conformal to tumor over time. Sixteen phantom cases with various sizes and locations of tumors, and OAR geometries were generated. Each case was planned with DAT and conventional IMRT (60Gy/30fx). Tumor volume change over time was obtained by using, daily MVCT-based, two-level cell population model. Monte Carlo simulations have been performed for each treatment course to account for uncertainty in tumor response. Same OAR dose constraints were applied for both methods. The frequency of plan modification was varied to 1, 2, 5 (weekly), and 29 (daily). The final average tumor dose and OAR doses have been compared to quantify the potential benefit of DAT. Results: The average tumor max, min, mean, and D95 resulted from DAT were 124.0–125.2%, 102.1–114.7%, 113.7–123.4%, and 102.0–115.9% (range dependent on the frequency of plan modification) of those from conventional IMRT. Cord max, esophagus max, lung mean, heart mean, and unspecified tissue D05 resulted from AT were 84–102.4%, 99.8–106.9%, 66.9–85.6%, 58.2–78.8%, and 85.2–94.0% of those from conventional IMRT. Conclusions: Significant tumor dose increase and OAR dose reduction, especially with parallel OAR with mean or dose-volume constraints, can be achieved using DAT.« less

Management of a stage-structured insect pest: an application of approximate optimization.

PubMed

Hackett, Sean C; Bonsall, Michael B

2018-06-01

Ecological decision problems frequently require the optimization of a sequence of actions over time where actions may have both immediate and downstream effects. Dynamic programming can solve such problems only if the dimensionality is sufficiently low. Approximate dynamic programming (ADP) provides a suite of methods applicable to problems of arbitrary complexity at the expense of guaranteed optimality. The most easily generalized method is the look-ahead policy: a brute-force algorithm that identifies reasonable actions by constructing and solving a series of temporally truncated approximations of the full problem over a defined planning horizon. We develop and apply this approach to a pest management problem inspired by the Mediterranean fruit fly, Ceratitis capitata. The model aims to minimize the cumulative costs of management actions and medfly-induced losses over a single 16-week season. The medfly population is stage-structured and grows continuously while management decisions are made at discrete, weekly intervals. For each week, the model chooses between inaction, insecticide application, or one of six sterile insect release ratios. Look-ahead policy performance is evaluated over a range of planning horizons, two levels of crop susceptibility to medfly and three levels of pesticide persistence. In all cases, the actions proposed by the look-ahead policy are contrasted to those of a myopic policy that minimizes costs over only the current week. We find that look-ahead policies always out-performed a myopic policy and decision quality is sensitive to the temporal distribution of costs relative to the planning horizon: it is beneficial to extend the planning horizon when it excludes pertinent costs. However, longer planning horizons may reduce decision quality when major costs are resolved imminently. ADP methods such as the look-ahead-policy-based approach developed here render questions intractable to dynamic programming amenable to inference but should be applied carefully as their flexibility comes at the expense of guaranteed optimality. However, given the complexity of many ecological management problems, the capacity to propose a strategy that is "good enough" using a more representative problem formulation may be preferable to an optimal strategy derived from a simplified model. © 2018 by the Ecological Society of America.

Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System

PubMed Central

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch. PMID:25540814

Optimal control strategy design based on dynamic programming for a dual-motor coupling-propulsion system.

PubMed

Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui

2014-01-01

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

NASA Astrophysics Data System (ADS)

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-12-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10-3 s-1 to 1 s-1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, Tβ (880 890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above Tβ, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

PubMed Central

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

Abstract This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10−3 s−1 to 1 s−1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region. PMID:29152021

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure.

PubMed

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10 -3  s -1 to 1 s -1 ) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β , continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+ β ) region.

Nonlinear histogram binning for quantitative analysis of lung tissue fibrosis in high-resolution CT data

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Bartholmai, Brian J.; Robb, Richard A.

2007-03-01

Diffuse lung diseases, such as idiopathic pulmonary fibrosis (IPF), can be characterized and quantified by analysis of volumetric high resolution CT scans of the lungs. These data sets typically have dimensions of 512 x 512 x 400. It is too subjective and labor intensive for a radiologist to analyze each slice and quantify regional abnormalities manually. Thus, computer aided techniques are necessary, particularly texture analysis techniques which classify various lung tissue types. Second and higher order statistics which relate the spatial variation of the intensity values are good discriminatory features for various textures. The intensity values in lung CT scans range between [-1024, 1024]. Calculation of second order statistics on this range is too computationally intensive so the data is typically binned between 16 or 32 gray levels. There are more effective ways of binning the gray level range to improve classification. An optimal and very efficient way to nonlinearly bin the histogram is to use a dynamic programming algorithm. The objective of this paper is to show that nonlinear binning using dynamic programming is computationally efficient and improves the discriminatory power of the second and higher order statistics for more accurate quantification of diffuse lung disease.

Rapid convergence of optimal control in NMR using numerically-constructed toggling frames

NASA Astrophysics Data System (ADS)

Coote, Paul; Anklin, Clemens; Massefski, Walter; Wagner, Gerhard; Arthanari, Haribabu

2017-08-01

We present a numerical method for rapidly solving the Bloch equation for an arbitrary time-varying spin-1/2 Hamiltonian. The method relies on fast, vectorized computations such as summation and quaternion multiplication, rather than slow computations such as matrix exponentiation. A toggling frame is constructed in which the Hamiltonian is time-invariant, and therefore has a simple analytical solution. The key insight is that constructing this frame is faster than solving the system dynamics in the original frame. Rapidly solving the Bloch equations for an arbitrary Hamiltonian is particularly useful in the context of NMR optimal control. Optimal control theory can be used to design pulse shapes for a range of tasks in NMR spectroscopy. However, it requires multiple simulations of the Bloch equations at each stage of the algorithm, and for each relevant set of parameters (e.g. chemical shift frequencies). This is typically time consuming. We demonstrate that by working in an appropriate toggling frame, optimal control pulses can be generated much faster. We present a new alternative to the well-known GRAPE algorithm to continuously update the toggling-frame as the optimal pulse is generated, and demonstrate that this approach is extremely fast. The use and benefit of rapid optimal pulse generation is demonstrated for 19F fragment screening experiments.

Recursive multibody dynamics and discrete-time optimal control

NASA Technical Reports Server (NTRS)

Deleuterio, G. M. T.; Damaren, C. J.

1989-01-01

A recursive algorithm is developed for the solution of the simulation dynamics problem for a chain of rigid bodies. Arbitrary joint constraints are permitted, that is, joints may allow translational and/or rotational degrees of freedom. The recursive procedure is shown to be identical to that encountered in a discrete-time optimal control problem. For each relevant quantity in the multibody dynamics problem, there exists an analog in the context of optimal control. The performance index that is minimized in the control problem is identified as Gibbs' function for the chain of bodies.

Comparison of kinematic and dynamic leg trajectory optimization techniques for biped robot locomotion

NASA Astrophysics Data System (ADS)

Khusainov, R.; Klimchik, A.; Magid, E.

2017-01-01

The paper presents comparison analysis of two approaches in defining leg trajectories for biped locomotion. The first one operates only with kinematic limitations of leg joints and finds the maximum possible locomotion speed for given limits. The second approach defines leg trajectories from the dynamic stability point of view and utilizes ZMP criteria. We show that two methods give different trajectories and demonstrate that trajectories based on pure dynamic optimization cannot be realized due to joint limits. Kinematic optimization provides unstable solution which can be balanced by upper body movement.

Optimal Least-Squares Unidimensional Scaling: Improved Branch-and-Bound Procedures and Comparison to Dynamic Programming

ERIC Educational Resources Information Center

Brusco, Michael J.; Stahl, Stephanie

2005-01-01

There are two well-known methods for obtaining a guaranteed globally optimal solution to the problem of least-squares unidimensional scaling of a symmetric dissimilarity matrix: (a) dynamic programming, and (b) branch-and-bound. Dynamic programming is generally more efficient than branch-and-bound, but the former is limited to matrices with…

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content.

PubMed

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.

Rad-hard Dual-threshold High-count-rate Silicon Pixel-array Detector

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

Lee, Adam

In this program, a Voxtel-led team demonstrates a full-format (192 x 192, 100-µm pitch, VX-810) high-dynamic-range x-ray photon-counting sensor—the Dual Photon Resolved Energy Acquisition (DUPREA) sensor. Within the Phase II program the following tasks were completed: 1) system analysis and definition of the DUPREA sensor requirements; 2) design, simulation, and fabrication of the full-format VX-810 ROIC design; 3) design, optimization, and fabrication of thick, fully depleted silicon photodiodes optimized for x-ray photon collection; 4) hybridization of the VX-810 ROIC to the photodiode array in the creation of the optically sensitive focal-plane array; 5) development of an evaluation camera; and 6)more » electrical and optical characterization of the sensor.« less

Review of dynamic optimization methods in renewable natural resource management

USGS Publications Warehouse

Williams, B.K.

1989-01-01

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

Stochastic dynamics and combinatorial optimization

NASA Astrophysics Data System (ADS)

Ovchinnikov, Igor V.; Wang, Kang L.

2017-11-01

Natural dynamics is often dominated by sudden nonlinear processes such as neuroavalanches, gamma-ray bursts, solar flares, etc., that exhibit scale-free statistics much in the spirit of the logarithmic Ritcher scale for earthquake magnitudes. On phase diagrams, stochastic dynamical systems (DSs) exhibiting this type of dynamics belong to the finite-width phase (N-phase for brevity) that precedes ordinary chaotic behavior and that is known under such names as noise-induced chaos, self-organized criticality, dynamical complexity, etc. Within the recently proposed supersymmetric theory of stochastic dynamics, the N-phase can be roughly interpreted as the noise-induced “overlap” between integrable and chaotic deterministic dynamics. As a result, the N-phase dynamics inherits the properties of the both. Here, we analyze this unique set of properties and conclude that the N-phase DSs must naturally be the most efficient optimizers: on one hand, N-phase DSs have integrable flows with well-defined attractors that can be associated with candidate solutions and, on the other hand, the noise-induced attractor-to-attractor dynamics in the N-phase is effectively chaotic or aperiodic so that a DS must avoid revisiting solutions/attractors thus accelerating the search for the best solution. Based on this understanding, we propose a method for stochastic dynamical optimization using the N-phase DSs. This method can be viewed as a hybrid of the simulated and chaotic annealing methods. Our proposition can result in a new generation of hardware devices for efficient solution of various search and/or combinatorial optimization problems.

Dynamic modeling of photothermal interactions for laser-induced interstitial thermotherapy: parameter sensitivity analysis.

PubMed

Jiang, S C; Zhang, X X

2005-12-01

A two-dimensional model was developed to model the effects of dynamic changes in the physical properties on tissue temperature and damage to simulate laser-induced interstitial thermotherapy (LITT) treatment procedures with temperature monitoring. A modified Monte Carlo method was used to simulate photon transport in the tissue in the non-uniform optical property field with the finite volume method used to solve the Pennes bioheat equation to calculate the temperature distribution and the Arrhenius equation used to predict the thermal damage extent. The laser light transport and the heat transfer as well as the damage accumulation were calculated iteratively at each time step. The influences of different laser sources, different applicator sizes, and different irradiation modes on the final damage volume were analyzed to optimize the LITT treatment. The numerical results showed that damage volume was the smallest for the 1,064-nm laser, with much larger, similar damage volumes for the 980- and 850-nm lasers at normal blood perfusion rates. The damage volume was the largest for the 1,064-nm laser with significantly smaller, similar damage volumes for the 980- and 850-nm lasers with temporally interrupted blood perfusion. The numerical results also showed that the variations in applicator sizes, laser powers, heating durations and temperature monitoring ranges significantly affected the shapes and sizes of the thermal damage zones. The shapes and sizes of the thermal damage zones can be optimized by selecting different applicator sizes, laser powers, heating duration times, temperature monitoring ranges, etc.

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning optimal filters automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal filters optimized using the proposed learning approach. PMID:18364986

An engineering optimization method with application to STOL-aircraft approach and landing trajectories

NASA Technical Reports Server (NTRS)

Jacob, H. G.

1972-01-01

An optimization method has been developed that computes the optimal open loop inputs for a dynamical system by observing only its output. The method reduces to static optimization by expressing the inputs as series of functions with parameters to be optimized. Since the method is not concerned with the details of the dynamical system to be optimized, it works for both linear and nonlinear systems. The method and the application to optimizing longitudinal landing paths for a STOL aircraft with an augmented wing are discussed. Noise, fuel, time, and path deviation minimizations are considered with and without angle of attack, acceleration excursion, flight path, endpoint, and other constraints.

Dynamic programming for optimization of timber production and grazing in ponderosa pine

Treesearch

Kurt H. Riitters; J. Douglas Brodie; David W. Hann

1982-01-01

Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...

Population dynamics and potential of fisheries stock enhancement: practical theory for assessment and policy analysis.

PubMed

Lorenzen, Kai

2005-01-29

The population dynamics of fisheries stock enhancement, and its potential for generating benefits over and above those obtainable from optimal exploitation of wild stocks alone are poorly understood and highly controversial. I review pertinent knowledge of fish population biology, and extend the dynamic pool theory of fishing to stock enhancement by unpacking recruitment, incorporating regulation in the recruited stock, and accounting for biological differences between wild and hatchery fish. I then analyse the dynamics of stock enhancement and its potential role in fisheries management, using the candidate stock of North Sea sole as an example and considering economic as well as biological criteria. Enhancement through release of recruits or advanced juveniles is predicted to increase total yield and stock abundance, but reduce abundance of the naturally recruited stock component through compensatory responses or overfishing. Economic feasibility of enhancement is subject to strong constraints, including trade-offs between the costs of fishing and hatchery releases. Costs of hatchery fish strongly influence optimal policy, which may range from no enhancement at high cost to high levels of stocking and fishing effort at low cost. Release of genetically maladapted fish reduces the effectiveness of enhancement, and is most detrimental overall if fitness of hatchery fish is only moderately compromised. As a temporary measure for the rebuilding of depleted stocks, enhancement cannot substitute for effort limitation, and is advantageous as an auxiliary measure only if the population has been reduced to a very low proportion of its unexploited biomass. Quantitative analysis of population dynamics is central to the responsible use of stock enhancement in fisheries management, and the necessary tools are available.

Automated Dynamic Demand Response Implementation on a Micro-grid

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

Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less

Bifunctional ultrasound assisted extraction and determination of Elettaria cardamomum Maton essential oil.

PubMed

Sereshti, Hassan; Rohanifar, Ahmad; Bakhtiari, Sadjad; Samadi, Soheila

2012-05-18

A new hyphenated extraction method composed of ultrasound assisted extraction (UAE)-optimized ultrasound assisted emulsification microextraction (USAEME) was developed for the extraction and preconcentration of the essential oil of Elettaria cardamomum Maton. The essential oil was analyzed by gas chromatography-mass spectrometry (GC-MS) and optimization was performed using gas chromatography-flame ionization detection (GC-FID). Ultrasound played two different roles in the extraction of the essential oil. First, as a source of sufficient energy to break the oil-containing glands in order to release the oil, and second as an emulsifier to disperse the organic phase within water. The effective parameters (factors) of USAEME including volume of extraction solvent (C(2)H(4)Cl(2)), extraction temperature and ultrasonic time were optimized by using a central composite design (CCD). The optimal conditions were 120 μL for extraction solvent volume, 32.5 °C for temperature and 10.5 min for ultrasonic time. The linear dynamic ranges (LDRs) were 0.01-50 mg L(-1) with the determination coefficients in the range of 0.9990-0.9999. The limits of detection (LODs) and the relative standard deviations (RSDs) were 0.001-0.007 mg L(-1) and 3.6-6.3%, respectively. The enrichment factors were 93-98. The main components of the extracted essential oil were α-terpenyl acetate (46.0%), 1,8-cineole (27.7%), linalool (5.3%), α-terpineol (4.0%), linalyl acetate (3.5%). Copyright © 2012 Elsevier B.V. All rights reserved.

Molecular dynamics simulation for the test of calibrated OPLS-AA force field for binary liquid mixture of tri-iso-amyl phosphate and n-dodecane.

PubMed

Das, Arya; Ali, Sk Musharaf

2018-02-21

Tri-isoamyl phosphate (TiAP) has been proposed to be an alternative for tri-butyl phosphate (TBP) in the Plutonium Uranium Extraction (PUREX) process. Recently, we have successfully calibrated and tested all-atom optimized potentials for liquid simulations using Mulliken partial charges for pure TiAP, TBP, and dodecane by performing molecular dynamics (MD) simulation. It is of immense importance to extend this potential for the various molecular properties of TiAP and TiAP/n-dodecane binary mixtures using MD simulation. Earlier, efforts were devoted to find out a suitable force field which can explain both structural and dynamical properties by empirical parameterization. Therefore, the present MD study reports the structural, dynamical, and thermodynamical properties with different mole fractions of TiAP-dodecane mixtures at the entire range of mole fraction of 0-1 employing our calibrated Mulliken embedded optimized potentials for liquid simulation (OPLS) force field. The calculated electric dipole moment of TiAP was seen to be almost unaffected by the TiAP concentration in the dodecane diluent. The calculated liquid densities of the TiAP-dodecane mixture are in good agreement with the experimental data. The mixture densities at different temperatures are also studied which was found to be reduced with temperature as expected. The plot of diffusivities for TiAP and dodecane against mole fraction in the binary mixture intersects at a composition in the range of 25%-30% of TiAP in dodecane, which is very much closer to the TBP/n-dodecane composition used in the PUREX process. The excess volume of mixing was found to be positive for the entire range of mole fraction and the excess enthalpy of mixing was shown to be endothermic for the TBP/n-dodecane mixture as well as TiAP/n-dodecane mixture as reported experimentally. The spatial pair correlation functions are evaluated between TiAP-TiAP and TiAP-dodecane molecules. Further, shear viscosity has been computed by performing the non-equilibrium molecular dynamics employing the periodic perturbation method. The calculated shear viscosity of the binary mixture is found to be in excellent agreement with the experimental values. The use of the newly calibrated OPLS force field embedding Mulliken charges is shown to be equally reliable in predicting the structural and dynamical properties for the mixture without incorporating any arbitrary scaling in the force field or Lennard-Jones parameters. Further, the present MD simulation results demonstrate that the Stokes-Einstein relation breaks down at the molecular level. The present methodology might be adopted to evaluate the liquid state properties of an aqueous-organic biphasic system, which is of great significance in the interfacial science and technology.

Molecular dynamics simulation for the test of calibrated OPLS-AA force field for binary liquid mixture of tri-iso-amyl phosphate and n-dodecane

NASA Astrophysics Data System (ADS)

Das, Arya; Ali, Sk. Musharaf

2018-02-01

Tri-isoamyl phosphate (TiAP) has been proposed to be an alternative for tri-butyl phosphate (TBP) in the Plutonium Uranium Extraction (PUREX) process. Recently, we have successfully calibrated and tested all-atom optimized potentials for liquid simulations using Mulliken partial charges for pure TiAP, TBP, and dodecane by performing molecular dynamics (MD) simulation. It is of immense importance to extend this potential for the various molecular properties of TiAP and TiAP/n-dodecane binary mixtures using MD simulation. Earlier, efforts were devoted to find out a suitable force field which can explain both structural and dynamical properties by empirical parameterization. Therefore, the present MD study reports the structural, dynamical, and thermodynamical properties with different mole fractions of TiAP-dodecane mixtures at the entire range of mole fraction of 0-1 employing our calibrated Mulliken embedded optimized potentials for liquid simulation (OPLS) force field. The calculated electric dipole moment of TiAP was seen to be almost unaffected by the TiAP concentration in the dodecane diluent. The calculated liquid densities of the TiAP-dodecane mixture are in good agreement with the experimental data. The mixture densities at different temperatures are also studied which was found to be reduced with temperature as expected. The plot of diffusivities for TiAP and dodecane against mole fraction in the binary mixture intersects at a composition in the range of 25%-30% of TiAP in dodecane, which is very much closer to the TBP/n-dodecane composition used in the PUREX process. The excess volume of mixing was found to be positive for the entire range of mole fraction and the excess enthalpy of mixing was shown to be endothermic for the TBP/n-dodecane mixture as well as TiAP/n-dodecane mixture as reported experimentally. The spatial pair correlation functions are evaluated between TiAP-TiAP and TiAP-dodecane molecules. Further, shear viscosity has been computed by performing the non-equilibrium molecular dynamics employing the periodic perturbation method. The calculated shear viscosity of the binary mixture is found to be in excellent agreement with the experimental values. The use of the newly calibrated OPLS force field embedding Mulliken charges is shown to be equally reliable in predicting the structural and dynamical properties for the mixture without incorporating any arbitrary scaling in the force field or Lennard-Jones parameters. Further, the present MD simulation results demonstrate that the Stokes-Einstein relation breaks down at the molecular level. The present methodology might be adopted to evaluate the liquid state properties of an aqueous-organic biphasic system, which is of great significance in the interfacial science and technology.

Aerodynamic performance of two-dimensional, chordwise flexible flapping wings at fruit fly scale in hover flight.

PubMed

Sridhar, Madhu; Kang, Chang-kwon

2015-05-06

Fruit flies have flexible wings that deform during flight. To explore the fluid-structure interaction of flexible flapping wings at fruit fly scale, we use a well-validated Navier-Stokes equation solver, fully-coupled with a structural dynamics solver. Effects of chordwise flexibility on a two dimensional hovering wing is studied. Resulting wing rotation is purely passive, due to the dynamic balance between aerodynamic loading, elastic restoring force, and inertial force of the wing. Hover flight is considered at a Reynolds number of Re = 100, equivalent to that of fruit flies. The thickness and density of the wing also corresponds to a fruit fly wing. The wing stiffness and motion amplitude are varied to assess their influences on the resulting aerodynamic performance and structural response. Highest lift coefficient of 3.3 was obtained at the lowest-amplitude, highest-frequency motion (reduced frequency of 3.0) at the lowest stiffness (frequency ratio of 0.7) wing within the range of the current study, although the corresponding power required was also the highest. Optimal efficiency was achieved for a lower reduced frequency of 0.3 and frequency ratio 0.35. Compared to the water tunnel scale with water as the surrounding fluid instead of air, the resulting vortex dynamics and aerodynamic performance remained similar for the optimal efficiency motion, while the structural response varied significantly. Despite these differences, the time-averaged lift scaled with the dimensionless shape deformation parameter γ. Moreover, the wing kinematics that resulted in the optimal efficiency motion was closely aligned to the fruit fly measurements, suggesting that fruit fly flight aims to conserve energy, rather than to generate large forces.

Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics.

PubMed

Dong, Bing; Li, Yan; Han, Xin-Li; Hu, Bin

2016-09-02

For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10(-5) in optimized correction and is 1.427 × 10(-5) in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method.

Applying a Dynamic Stomatal Optimization to Predict Shifts in the Functional Composition of Tropical Forests Under Increased Drought And CO2

NASA Astrophysics Data System (ADS)

Bartlett, M. K.; Detto, M.; Pacala, S. W.

2017-12-01

The accurate prediction of tropical forest carbon fluxes is key to forecasting global climate, but forest responses to projected increases in CO2 and drought are highly uncertain. Here we present a dynamic optimization that derives the trajectory of stomatal conductance (gs) during drought, a key source of model uncertainty, from plant and soil water relations and the carbon economy of the plant hydraulic system. This optimization scheme is novel in two ways. First, by accounting for the ability of capacitance (i.e., the release of water from plant storage tissue; C) to buffer evaporative water loss and maintain gs during drought, this optimization captures both drought tolerant and avoidant hydraulic strategies. Second, by determining the optimal trajectory of plant and soil water potentials, this optimization quantifies species' impacts on the water available to competing plants. These advances allowed us to apply this optimization across the range of physiology trait values observed in tropical species to evaluate shifts in the competitively optimal trait values, or evolutionarily stable hydraulic strategy (ESS), under increased drought and CO2. Increasing the length of the dry season shifted the ESS towards more drought tolerant, rather than avoidant, trait values, and these shifts were larger for longer individual drought periods (i.e., more consecutive days without rainfall), even if the total time spent in drought was the same. Concurrently doubling the CO2 level reduced the magnitude of these shifts and slightly favored drought avoidant strategies under wet conditions. Overall, these analyses predicted that short, frequent droughts would allow elevated CO2 to shift the functional composition in tropical forests towards more drought avoidant species, while infrequent but long drought periods would shift the ESS to more drought tolerant trait values, despite increased CO2. Overall, these analyses quantified the impact of physiology traits on plant performance and competitive ability, and provide a mechanistic, trait-based approach to predict shifts in the functional composition of tropical forests under projected climatic conditions.

Dynamic positioning configuration and its first-order optimization

NASA Astrophysics Data System (ADS)

Xue, Shuqiang; Yang, Yuanxi; Dang, Yamin; Chen, Wu

2014-02-01

Traditional geodetic network optimization deals with static and discrete control points. The modern space geodetic network is, on the other hand, composed of moving control points in space (satellites) and on the Earth (ground stations). The network configuration composed of these facilities is essentially dynamic and continuous. Moreover, besides the position parameter which needs to be estimated, other geophysical information or signals can also be extracted from the continuous observations. The dynamic (continuous) configuration of the space network determines whether a particular frequency of signals can be identified by this system. In this paper, we employ the functional analysis and graph theory to study the dynamic configuration of space geodetic networks, and mainly focus on the optimal estimation of the position and clock-offset parameters. The principle of the D-optimization is introduced in the Hilbert space after the concept of the traditional discrete configuration is generalized from the finite space to the infinite space. It shows that the D-optimization developed in the discrete optimization is still valid in the dynamic configuration optimization, and this is attributed to the natural generalization of least squares from the Euclidean space to the Hilbert space. Then, we introduce the principle of D-optimality invariance under the combination operation and rotation operation, and propose some D-optimal simplex dynamic configurations: (1) (Semi) circular configuration in 2-dimensional space; (2) the D-optimal cone configuration and D-optimal helical configuration which is close to the GPS constellation in 3-dimensional space. The initial design of GPS constellation can be approximately treated as a combination of 24 D-optimal helixes by properly adjusting the ascending node of different satellites to realize a so-called Walker constellation. In the case of estimating the receiver clock-offset parameter, we show that the circular configuration, the symmetrical cone configuration and helical curve configuration are still D-optimal. It shows that the given total observation time determines the optimal frequency (repeatability) of moving known points and vice versa, and one way to improve the repeatability is to increase the rotational speed. Under the Newton's law of motion, the frequency of satellite motion determines the orbital altitude. Furthermore, we study three kinds of complex dynamic configurations, one of which is the combination of D-optimal cone configurations and a so-called Walker constellation composed of D-optimal helical configuration, the other is the nested cone configuration composed of n cones, and the last is the nested helical configuration composed of n orbital planes. It shows that an effective way to achieve high coverage is to employ the configuration composed of a certain number of moving known points instead of the simplex configuration (such as D-optimal helical configuration), and one can use the D-optimal simplex solutions or D-optimal complex configurations in any combination to achieve powerful configurations with flexile coverage and flexile repeatability. Alternately, how to optimally generate and assess the discrete configurations sampled from the continuous one is discussed. The proposed configuration optimization framework has taken the well-known regular polygons (such as equilateral triangle and quadrangular) in two-dimensional space and regular polyhedrons (regular tetrahedron, cube, regular octahedron, regular icosahedron, or regular dodecahedron) into account. It shows that the conclusions made by the proposed technique are more general and no longer limited by different sampling schemes. By the conditional equation of D-optimal nested helical configuration, the relevance issues of GNSS constellation optimization are solved and some examples are performed by GPS constellation to verify the validation of the newly proposed optimization technique. The proposed technique is potentially helpful in maintenance and quadratic optimization of single GNSS of which the orbital inclination and the orbital altitude change under the precession, as well as in optimally nesting GNSSs to perform global homogeneous coverage of the Earth.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Parallel and Preemptable Dynamically Dimensioned Search Algorithms for Single and Multi-objective Optimization in Water Resources

NASA Astrophysics Data System (ADS)

Tolson, B.; Matott, L. S.; Gaffoor, T. A.; Asadzadeh, M.; Shafii, M.; Pomorski, P.; Xu, X.; Jahanpour, M.; Razavi, S.; Haghnegahdar, A.; Craig, J. R.

2015-12-01

We introduce asynchronous parallel implementations of the Dynamically Dimensioned Search (DDS) family of algorithms including DDS, discrete DDS, PA-DDS and DDS-AU. These parallel algorithms are unique from most existing parallel optimization algorithms in the water resources field in that parallel DDS is asynchronous and does not require an entire population (set of candidate solutions) to be evaluated before generating and then sending a new candidate solution for evaluation. One key advance in this study is developing the first parallel PA-DDS multi-objective optimization algorithm. The other key advance is enhancing the computational efficiency of solving optimization problems (such as model calibration) by combining a parallel optimization algorithm with the deterministic model pre-emption concept. These two efficiency techniques can only be combined because of the asynchronous nature of parallel DDS. Model pre-emption functions to terminate simulation model runs early, prior to completely simulating the model calibration period for example, when intermediate results indicate the candidate solution is so poor that it will definitely have no influence on the generation of further candidate solutions. The computational savings of deterministic model preemption available in serial implementations of population-based algorithms (e.g., PSO) disappear in synchronous parallel implementations as these algorithms. In addition to the key advances above, we implement the algorithms across a range of computation platforms (Windows and Unix-based operating systems from multi-core desktops to a supercomputer system) and package these for future modellers within a model-independent calibration software package called Ostrich as well as MATLAB versions. Results across multiple platforms and multiple case studies (from 4 to 64 processors) demonstrate the vast improvement over serial DDS-based algorithms and highlight the important role model pre-emption plays in the performance of parallel, pre-emptable DDS algorithms. Case studies include single- and multiple-objective optimization problems in water resources model calibration and in many cases linear or near linear speedups are observed.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

PubMed Central

Tian, Le; Latré, Steven

2017-01-01

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

PubMed

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

A low complexity, low spur digital IF conversion circuit for high-fidelity GNSS signal playback

NASA Astrophysics Data System (ADS)

Su, Fei; Ying, Rendong

2016-01-01

A low complexity high efficiency and low spur digital intermediate frequency (IF) conversion circuit is discussed in the paper. This circuit is key element in high-fidelity GNSS signal playback instrument. We analyze the spur performance of a finite state machine (FSM) based numerically controlled oscillators (NCO), by optimization of the control algorithm, a FSM based NCO with 3 quantization stage can achieves 65dB SFDR in the range of the seventh harmonic. Compare with traditional lookup table based NCO design with the same Spurious Free Dynamic Range (SFDR) performance, the logic resource require to implemented the NCO is reduced to 1/3. The proposed design method can be extended to the IF conversion system with good SFDR in the range of higher harmonic components by increasing the quantization stage.

Dynamic Control of Adsorption Sensitivity for Photo-EMF-Based Ammonia Gas Sensors Using a Wireless Network

PubMed Central

Vashpanov, Yuriy; Choo, Hyunseung; Kim, Dongsoo Stephen

2011-01-01

This paper proposes an adsorption sensitivity control method that uses a wireless network and illumination light intensity in a photo-electromagnetic field (EMF)-based gas sensor for measurements in real time of a wide range of ammonia concentrations. The minimum measurement error for a range of ammonia concentration from 3 to 800 ppm occurs when the gas concentration magnitude corresponds with the optimal intensity of the illumination light. A simulation with LabView-engineered modules for automatic control of a new intelligent computer system was conducted to improve measurement precision over a wide range of gas concentrations. This gas sensor computer system with wireless network technology could be useful in the chemical industry for automatic detection and measurement of hazardous ammonia gas levels in real time. PMID:22346680

Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

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

Turner, D P; Ritts, W D; Wharton, S

2009-02-26

The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors.more » FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.« less

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

PubMed

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of generic distributed biological systems.

Body Bias usage in UTBB FDSOI designs: A parametric exploration approach

NASA Astrophysics Data System (ADS)

Puschini, Diego; Rodas, Jorge; Beigne, Edith; Altieri, Mauricio; Lesecq, Suzanne

2016-03-01

Some years ago, UTBB FDSOI has appeared in the horizon of low-power circuit designers. With the 14 nm and 10 nm nodes in the road-map, the industrialized 28 nm platform promises highly efficient designs with Ultra-Wide Voltage Range (UWVR) thanks to extended Body Bias properties. From the power management perspective, this new opportunity is considered as a new degree of freedom in addition to the classic Dynamic Voltage Scaling (DVS), increasing the complexity of the power optimization problem at design time. However, so far no formal or empiric tool allows to early evaluate the real need for a Dynamic Body Bias (DBB) mechanism on future designs. This paper presents a parametric exploration approach that analyzes the benefits of using Body Bias in 28 nm UTBB FDSOI circuits. The exploration is based on electrical simulations of a ring-oscillator structure. These experiences show that a Body Bias strategy is not always required but, they underline the large power reduction that can be achieved when mandatory. Results are summarized in order to help designers to analyze how to choose the best dynamic power management strategy for a given set of operating conditions in terms of temperature, circuit activity and process choice. This exploration contributes to the identification of conditions that make DBB more efficient than DVS, and vice versa, and when both methods are mandatory to optimize power consumption.

Parametric geometric model and shape optimization of an underwater glider with blended-wing-body

NASA Astrophysics Data System (ADS)

Sun, Chunya; Song, Baowei; Wang, Peng

2015-11-01

Underwater glider, as a new kind of autonomous underwater vehicles, has many merits such as long-range, extended-duration and low costs. The shape of underwater glider is an important factor in determining the hydrodynamic efficiency. In this paper, a high lift to drag ratio configuration, the Blended-Wing-Body (BWB), is used to design a small civilian under water glider. In the parametric geometric model of the BWB underwater glider, the planform is defined with Bezier curve and linear line, and the section is defined with symmetrical airfoil NACA 0012. Computational investigations are carried out to study the hydrodynamic performance of the glider using the commercial Computational Fluid Dynamics (CFD) code Fluent. The Kriging-based genetic algorithm, called Efficient Global Optimization (EGO), is applied to hydrodynamic design optimization. The result demonstrates that the BWB underwater glider has excellent hydrodynamic performance, and the lift to drag ratio of initial design is increased by 7% in the EGO process.

Response surface optimized peroxyoxalate chemiluminescence of octahydro-Schiff base derivative as new luminophor and study of the quenching effect of some cations, amino acids and cholesterol.

PubMed

Yeganeh Faal, Ali; Jamalyan, Bahare; Bordbar, Maryam; Shayeste, Tavakol Heidary; Salavati-Niasari, Masoud

2014-12-01

We report the first detailed study of the characteristics of an octahydro-Schiff base derivative as a new luminophor in the peroxyoxalate chemiluminescence (POCL) system. The effect of reagents on this new POCL system was investigated. In addition, the response surface methodology was used for evaluating the relative significance of variables in this POCL system, establishing models and determining optimal conditions. The quenching effect of some cations and compounds such as Cu(2+), Fe(3+), Hg(2+), imidazole, histidine and cholesterol on an optimized POCL reaction were studied. The dynamic ranges were up to approximaterly 100 and 175 × 10(-6) M for Cu(2+) and cholesterol respectively. The detection limits were 3.3 × 10(-6) m and 2.58 × 10(-6) m for Cu(2+) and histidine, respectively. In all cases the relative standard deviations were 4-5% (n = 4). Copyright © 2014 John Wiley & Sons, Ltd.

Intelligent automated surface grid generation

NASA Technical Reports Server (NTRS)

Yao, Ke-Thia; Gelsey, Andrew

1995-01-01

The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking

NASA Astrophysics Data System (ADS)

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

A mathematical tool to generate complex whole body motor tasks and test hypotheses on underlying motor planning.

PubMed

Tagliabue, Michele; Pedrocchi, Alessandra; Pozzo, Thierry; Ferrigno, Giancarlo

2008-01-01

In spite of the complexity of human motor behavior, difficulties in mathematical modeling have restricted to rather simple movements attempts to identify the motor planning criterion used by the central nervous system. This paper presents a novel-simulation technique able to predict the "desired trajectory" corresponding to a wide range of kinematic and kinetic optimality criteria for tasks involving many degrees of freedom and the coordination between goal achievement and balance maintenance. Employment of proper time discretization, inverse dynamic methods and constrained optimization technique are combined. The application of this simulator to a planar whole body pointing movement shows its effectiveness in managing system nonlinearities and instability as well as in ensuring the anatomo-physiological feasibility of predicted motor plans. In addition, the simulator's capability to simultaneously optimize competing movement aspects represents an interesting opportunity for the motor control community, in which the coexistence of several controlled variables has been hypothesized.

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking.

PubMed

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J; Jian, Yifan; Sarunic, Marinko V

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.