Optimal control theory for non-scalar-valued performance criteria. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gerring, H. P.

1971-01-01

The theory of optimal control for nonscalar-valued performance criteria is discussed. In the space, where the performance criterion attains its value, the relations better than, worse than, not better than, and not worse than are defined by a partial order relation. The notion of optimality splits up into superiority and non-inferiority, because worse than is not the complement of better than, in general. A superior solution is better than every other solution. A noninferior solution is not worse than any other solution. Noninferior solutions have been investigated particularly for vector-valued performance criteria. Superior solutions for non-scalar-valued performance criteria attaining their values in abstract partially ordered spaces are emphasized. The main result is the infimum principle which constitutes necessary conditions for a control to be a superior solution to an optimal control problem.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

PubMed

Chang, Joshua; Paydarfar, David

2014-12-01

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Analytical solutions to optimal underactuated spacecraft formation reconfiguration

NASA Astrophysics Data System (ADS)

Huang, Xu; Yan, Ye; Zhou, Yang

2015-11-01

Underactuated systems can generally be defined as systems with fewer number of control inputs than that of the degrees of freedom to be controlled. In this paper, analytical solutions to optimal underactuated spacecraft formation reconfiguration without either the radial or the in-track control are derived. By using a linear dynamical model of underactuated spacecraft formation in circular orbits, controllability analysis is conducted for either underactuated case. Indirect optimization methods based on the minimum principle are then introduced to generate analytical solutions to optimal open-loop underactuated reconfiguration problems. Both fixed and free final conditions constraints are considered for either underactuated case and comparisons between these two final conditions indicate that the optimal control strategies with free final conditions require less control efforts than those with the fixed ones. Meanwhile, closed-loop adaptive sliding mode controllers for both underactuated cases are designed to guarantee optimal trajectory tracking in the presence of unmatched external perturbations, linearization errors, and system uncertainties. The adaptation laws are designed via a Lyapunov-based method to ensure the overall stability of the closed-loop system. The explicit expressions of the terminal convergent regions of each system states have also been obtained. Numerical simulations demonstrate the validity and feasibility of the proposed open-loop and closed-loop control schemes for optimal underactuated spacecraft formation reconfiguration in circular orbits.

Strong stabilization servo controller with optimization of performance criteria.

PubMed

Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor

2011-07-01

Synthesis of a simple robust controller with a pole placement technique and a H(∞) metrics is the method used for control of a servo mechanism with BLDC and BDC electric motors. The method includes solving a polynomial equation on the basis of the chosen characteristic polynomial using the Manabe standard polynomial form and parametric solutions. Parametric solutions are introduced directly into the structure of the servo controller. On the basis of the chosen parametric solutions the robustness of a closed-loop system is assessed through uncertainty models and assessment of the norm ‖•‖(∞). The design procedure and the optimization are performed with a genetic algorithm differential evolution - DE. The DE optimization method determines a suboptimal solution throughout the optimization on the basis of a spectrally square polynomial and Šiljak's absolute stability test. The stability of the designed controller during the optimization is being checked with Lipatov's stability condition. Both utilized approaches: Šiljak's test and Lipatov's condition, check the robustness and stability characteristics on the basis of the polynomial's coefficients, and are very convenient for automated design of closed-loop control and for application in optimization algorithms such as DE. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Imaging Tasks Scheduling for High-Altitude Airship in Emergency Condition Based on Energy-Aware Strategy

PubMed Central

Zhimeng, Li; Chuan, He; Dishan, Qiu; Jin, Liu; Manhao, Ma

2013-01-01

Aiming to the imaging tasks scheduling problem on high-altitude airship in emergency condition, the programming models are constructed by analyzing the main constraints, which take the maximum task benefit and the minimum energy consumption as two optimization objectives. Firstly, the hierarchy architecture is adopted to convert this scheduling problem into three subproblems, that is, the task ranking, value task detecting, and energy conservation optimization. Then, the algorithms are designed for the sub-problems, and the solving results are corresponding to feasible solution, efficient solution, and optimization solution of original problem, respectively. This paper makes detailed introduction to the energy-aware optimization strategy, which can rationally adjust airship's cruising speed based on the distribution of task's deadline, so as to decrease the total energy consumption caused by cruising activities. Finally, the application results and comparison analysis show that the proposed strategy and algorithm are effective and feasible. PMID:23864822

Optimal control solutions to sodic soil reclamation

NASA Astrophysics Data System (ADS)

Mau, Yair; Porporato, Amilcare

2016-05-01

We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang-bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang-bang solution is also shown to work for the reclamation of other soil conditions, such as saline-sodic soils. The novelty in our modeling approach is the capability of searching the entire "strategy space" for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities.

FDTD simulation of EM wave propagation in 3-D media

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

Wang, T.; Tripp, A.C.

1996-01-01

A finite-difference, time-domain solution to Maxwell`s equations has been developed for simulating electromagnetic wave propagation in 3-D media. The algorithm allows arbitrary electrical conductivity and permittivity variations within a model. The staggered grid technique of Yee is used to sample the fields. A new optimized second-order difference scheme is designed to approximate the spatial derivatives. Like the conventional fourth-order difference scheme, the optimized second-order scheme needs four discrete values to calculate a single derivative. However, the optimized scheme is accurate over a wider wavenumber range. Compared to the fourth-order scheme, the optimized scheme imposes stricter limitations on the time stepmore » sizes but allows coarser grids. The net effect is that the optimized scheme is more efficient in terms of computation time and memory requirement than the fourth-order scheme. The temporal derivatives are approximated by second-order central differences throughout. The Liao transmitting boundary conditions are used to truncate an open problem. A reflection coefficient analysis shows that this transmitting boundary condition works very well. However, it is subject to instability. A method that can be easily implemented is proposed to stabilize the boundary condition. The finite-difference solution is compared to closed-form solutions for conducting and nonconducting whole spaces and to an integral-equation solution for a 3-D body in a homogeneous half-space. In all cases, the finite-difference solutions are in good agreement with the other solutions. Finally, the use of the algorithm is demonstrated with a 3-D model. Numerical results show that both the magnetic field response and electric field response can be useful for shallow-depth and small-scale investigations.« less

Analysis of modal behavior at frequency cross-over

NASA Astrophysics Data System (ADS)

Costa, Robert N., Jr.

1994-11-01

The existence of the mode crossing condition is detected and analyzed in the Active Control of Space Structures Model 4 (ACOSS4). The condition is studied for its contribution to the inability of previous algorithms to successfully optimize the structure and converge to a feasible solution. A new algorithm is developed to detect and correct for mode crossings. The existence of the mode crossing condition is verified in ACOSS4 and found not to have appreciably affected the solution. The structure is then successfully optimized using new analytic methods based on modal expansion. An unrelated error in the optimization algorithm previously used is verified and corrected, thereby equipping the optimization algorithm with a second analytic method for eigenvector differentiation based on Nelson's Method. The second structure is the Control of Flexible Structures (COFS). The COFS structure is successfully reproduced and an initial eigenanalysis completed.

Rapid optimization of multiple-burn rocket flights.

NASA Technical Reports Server (NTRS)

Brown, K. R.; Harrold, E. F.; Johnson, G. W.

1972-01-01

Different formulations of the fuel optimization problem for multiple burn trajectories are considered. It is shown that certain customary idealizing assumptions lead to an ill-posed optimization problem for which no solution exists. Several ways are discussed for avoiding such difficulties by more realistic problem statements. An iterative solution of the boundary value problem is presented together with efficient coast arc computations, the right end conditions for various orbital missions, and some test results.

Solving fuel-optimal low-thrust orbital transfers with bang-bang control using a novel continuation technique

NASA Astrophysics Data System (ADS)

Zhu, Zhengfan; Gan, Qingbo; Yang, Xin; Gao, Yang

2017-08-01

We have developed a novel continuation technique to solve optimal bang-bang control for low-thrust orbital transfers considering the first-order necessary optimality conditions derived from Lawden's primer vector theory. Continuation on the thrust amplitude is mainly described in this paper. Firstly, a finite-thrust transfer with an ;On-Off-On; thrusting sequence is modeled using a two-impulse transfer as initial solution, and then the thrust amplitude is decreased gradually to find an optimal solution with minimum thrust. Secondly, the thrust amplitude is continued from its minimum value to positive infinity to find the optimal bang-bang control, and a thrust switching principle is employed to determine the control structure by monitoring the variation of the switching function. In the continuation process, a bifurcation of bang-bang control is revealed and the concept of critical thrust is proposed to illustrate this phenomenon. The same thrust switching principle is also applicable to the continuation on other parameters, such as transfer time, orbital phase angle, etc. By this continuation technique, fuel-optimal orbital transfers with variable mission parameters can be found via an automated algorithm, and there is no need to provide an initial guess for the costate variables. Moreover, continuation is implemented in the solution space of bang-bang control that is either optimal or non-optimal, which shows that a desired solution of bang-bang control is obtained via continuation on a single parameter starting from an existing solution of bang-bang control. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed continuation technique. Specifically, this continuation technique provides an approach to find multiple solutions satisfying the first-order necessary optimality conditions to the same orbital transfer problem, and a continuation strategy is presented as a preliminary approach for solving the bang-bang control of many-revolution orbital transfers.

[Study on the extraction process and macroporous resin for purification of Timosaponin B II].

PubMed

Liu, Yan-Ping; Ding, Yue; Zhang, Tong; Wang, Bing; Cai, Zhen-Zhen; Tao, Jian-Sheng

2013-06-01

To optimize the extraction process and macroporous resin for purification of Timosaponin B II from Anemarrhena asphodeloides. Orthogonal design L9 (34) was employed to optimize the circumfluence extraction conditions by taking the extraction yield of Timosaponin B II as index. The absorption-desorption characteristics of eight kinds of macroporous resins were evaluated, then the best resin was chosen to optimize the purification process conditions. The optimum extraction conditions were as follows: the herb was extracted for 2 times (2 hours each time) with 8.5-fold 50% ethanol at the first time and 6-fold 50% ethanol at the second time. HPD100 resin showed a good property for the absorption-desorption of Timosaponin B II. The optimum technological conditions of HPD100 resin were as follows:the solution concentration was 0.23 mg/mL, the amount of saturated adsorption at 4/5 body volumn (BV) resin, the HPD100 resin was washed with 3 BV water and 6 BV 20% ethanol solution to remove the impurity, then the Timosaponin B II was desorbed by 5 BV ethanol solution. The purity of Timosaponin B II was about 50%. The optimized extraction process and purification is stable, efficient and suitable for industrial production.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

NASA Astrophysics Data System (ADS)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Extended Analytic Device Optimization Employing Asymptotic Expansion

NASA Technical Reports Server (NTRS)

Mackey, Jonathan; Sehirlioglu, Alp; Dynsys, Fred

2013-01-01

Analytic optimization of a thermoelectric junction often introduces several simplifying assumptionsincluding constant material properties, fixed known hot and cold shoe temperatures, and thermallyinsulated leg sides. In fact all of these simplifications will have an effect on device performance,ranging from negligible to significant depending on conditions. Numerical methods, such as FiniteElement Analysis or iterative techniques, are often used to perform more detailed analysis andaccount for these simplifications. While numerical methods may stand as a suitable solution scheme,they are weak in gaining physical understanding and only serve to optimize through iterativesearching techniques. Analytic and asymptotic expansion techniques can be used to solve thegoverning system of thermoelectric differential equations with fewer or less severe assumptionsthan the classic case. Analytic methods can provide meaningful closed form solutions and generatebetter physical understanding of the conditions for when simplifying assumptions may be valid.In obtaining the analytic solutions a set of dimensionless parameters, which characterize allthermoelectric couples, is formulated and provide the limiting cases for validating assumptions.Presentation includes optimization of both classic rectangular couples as well as practically andtheoretically interesting cylindrical couples using optimization parameters physically meaningful toa cylindrical couple. Solutions incorporate the physical behavior for i) thermal resistance of hot andcold shoes, ii) variable material properties with temperature, and iii) lateral heat transfer through legsides.

Fuel-optimal low-thrust formation reconfiguration via Radau pseudospectral method

NASA Astrophysics Data System (ADS)

Li, Jing

2016-07-01

This paper investigates fuel-optimal low-thrust formation reconfiguration near circular orbit. Based on the Clohessy-Wiltshire equations, first-order necessary optimality conditions are derived from the Pontryagin's maximum principle. The fuel-optimal impulsive solution is utilized to divide the low-thrust trajectory into thrust and coast arcs. By introducing the switching times as optimization variables, the fuel-optimal low-thrust formation reconfiguration is posed as a nonlinear programming problem (NLP) via direct transcription using multiple-phase Radau pseudospectral method (RPM), which is then solved by a sparse nonlinear optimization software SNOPT. To facilitate optimality verification and, if necessary, further refinement of the optimized solution of the NLP, formulas for mass costate estimation and initial costates scaling are presented. Numerical examples are given to show the application of the proposed optimization method. To fix the problem, generic fuel-optimal low-thrust formation reconfiguration can be simplified as reconfiguration without any initial and terminal coast arcs, whose optimal solutions can be efficiently obtained from the multiple-phase RPM at the cost of a slight fuel increment. Finally, influence of the specific impulse and maximum thrust magnitude on the fuel-optimal low-thrust formation reconfiguration is analyzed. Numerical results shown the links and differences between the fuel-optimal impulsive and low-thrust solutions.

New trends in astrodynamics and applications: optimal trajectories for space guidance.

PubMed

Azimov, Dilmurat; Bishop, Robert

2005-12-01

This paper represents recent results on the development of optimal analytic solutions to the variation problem of trajectory optimization and their application in the construction of on-board guidance laws. The importance of employing the analytically integrated trajectories in a mission design is discussed. It is assumed that the spacecraft is equipped with a power-limited propulsion and moving in a central Newtonian field. Satisfaction of the necessary and sufficient conditions for optimality of trajectories is analyzed. All possible thrust arcs and corresponding classes of the analytical solutions are classified based on the propulsion system parameters and performance index of the problem. The solutions are presented in a form convenient for applications in escape, capture, and interorbital transfer problems. Optimal guidance and neighboring optimal guidance problems are considered. It is shown that the analytic solutions can be used as reference trajectories in constructing the guidance algorithms for the maneuver problems mentioned above. An illustrative example of a spiral trajectory that terminates on a given elliptical parking orbit is discussed.

A superlinear interior points algorithm for engineering design optimization

NASA Technical Reports Server (NTRS)

Herskovits, J.; Asquier, J.

1990-01-01

We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.

Primer vector theory applied to the linear relative-motion equations. [for N-impulse space trajectory optimization

NASA Technical Reports Server (NTRS)

Jezewski, D.

1980-01-01

Prime vector theory is used in analyzing a set of linear relative-motion equations - the Clohessy-Wiltshire (C/W) equations - to determine the criteria and necessary conditions for an optimal N-impulse trajectory. The analysis develops the analytical criteria for improving a solution by: (1) moving any dependent or independent variable in the initial and/or final orbit, and (2) adding intermediate impulses. If these criteria are violated, the theory establishes a sufficient number of analytical equations. The subsequent satisfaction of these equations will result in the optimal position vectors and times of an N-impulse trajectory. The solution is examined for the specific boundary conditions of: (1) fixed-end conditions, two impulse, and time-open transfer; (2) an orbit-to-orbit transfer; and (3) a generalized renezvous problem.

Ship Trim Optimization: Assessment of Influence of Trim on Resistance of MOERI Container Ship

PubMed Central

Duan, Wenyang

2014-01-01

Environmental issues and rising fuel prices necessitate better energy efficiency in all sectors. Shipping industry is a stakeholder in environmental issues. Shipping industry is responsible for approximately 3% of global CO2 emissions, 14-15% of global NOX emissions, and 16% of global SOX emissions. Ship trim optimization has gained enormous momentum in recent years being an effective operational measure for better energy efficiency to reduce emissions. Ship trim optimization analysis has traditionally been done through tow-tank testing for a specific hullform. Computational techniques are increasingly popular in ship hydrodynamics applications. The purpose of this study is to present MOERI container ship (KCS) hull trim optimization by employing computational methods. KCS hull total resistances and trim and sinkage computed values, in even keel condition, are compared with experimental values and found in reasonable agreement. The agreement validates that mesh, boundary conditions, and solution techniques are correct. The same mesh, boundary conditions, and solution techniques are used to obtain resistance values in different trim conditions at Fn = 0.2274. Based on attained results, optimum trim is suggested. This research serves as foundation for employing computational techniques for ship trim optimization. PMID:24578649

Regulation of Renewable Energy Sources to Optimal Power Flow Solutions Using ADMM

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers power distribution systems featuring renewable energy sources (RESs), and develops a distributed optimization method to steer the RES output powers to solutions of AC optimal power flow (OPF) problems. The design of the proposed method leverages suitable linear approximations of the AC-power flow equations, and is based on the Alternating Direction Method of Multipliers (ADMM). Convergence of the RES-inverter output powers to solutions of the OPF problem is established under suitable conditions on the stepsize as well as mismatches between the commanded setpoints and actual RES output powers. In a broad sense, the methods and results proposedmore » here are also applicable to other distributed optimization problem setups with ADMM and inexact dual updates.« less

Formulation and characterization of Turkish oregano microcapsules prepared by spray-drying technology.

PubMed

Baranauskaite, Juste; Ivanauskas, Liudas; Masteikova, Ruta; Kopustinskiene, Dalia; Baranauskas, Algirdas; Bernatoniene, Jurga

2017-09-01

The aim of this study was optimization of spray-drying process conditions for microencapsulation of Turkish oregano extract. Different concentrations of maltodextrin and gum arabic as encapsulating agents (wall material) as well as influence of selected processing variables were evaluated. The optimal conditions were maintained on the basis of the load of main bioactive compounds - ursolic, rosmarinic acids and carvacrol - in prepared microparticles after comparison of all significant response variables using desirability function. Physicomechanical properties of powders such as flowability, wettability, solubility, moisture content as well as product yield, encapsulation efficiency (EE), density, morphology and size distribution of prepared microparticles have been determined. The results demonstrated that the optimal conditions for spray-drying mixture consisted of two parts of wall material solution and one part of ethanolic oregano extract when the feed flow rate was 40 mL/min and air inlet temperature -170 °C. Optimal concentration of wall materials in solution was 20% while the ratio of maltodextrin and gum arabic was 8.74:1.26.

Approximate approach for optimization space flights with a low thrust on the basis of sufficient optimality conditions

NASA Astrophysics Data System (ADS)

Salmin, Vadim V.

2017-01-01

Flight mechanics with a low-thrust is a new chapter of mechanics of space flight, considered plurality of all problems trajectory optimization and movement control laws and the design parameters of spacecraft. Thus tasks associated with taking into account the additional factors in mathematical models of the motion of spacecraft becomes increasingly important, as well as additional restrictions on the possibilities of the thrust vector control. The complication of the mathematical models of controlled motion leads to difficulties in solving optimization problems. Author proposed methods of finding approximate optimal control and evaluating their optimality based on analytical solutions. These methods are based on the principle of extending the class of admissible states and controls and sufficient conditions for the absolute minimum. Developed procedures of the estimation enabling to determine how close to the optimal founded solution, and indicate ways to improve them. Authors describes procedures of estimate for approximately optimal control laws for space flight mechanics problems, in particular for optimization flight low-thrust between the circular non-coplanar orbits, optimization the control angle and trajectory movement of the spacecraft during interorbital flights, optimization flights with low-thrust between arbitrary elliptical orbits Earth satellites.

Removal of chromium(III) from aqueous waste solution by liquid-liquid extraction in a circular microchannel.

PubMed

Luo, Jian Hong; Li, Jun; Guo, Lei; Zhu, Xin Hua; Dai, Shuang; Li, Xing

2017-11-01

A new circular microchannel device has been proposed for the removal of chromium(III) from aqueous waste solution by using kerosene as a diluent and (2-ethylhexyl) 2-ethylhexyl phosphonate as an extractant. The proposed device has several advantages such as a flexible and easily adaptable design, easy maintenance, and cheap setup without the requirement of microfabrication. To study the extraction efficiency and advantages of the circular microchannel device in the removal of chromium(III), the effects of various operating conditions such as the inner diameter of the channel, the total flow velocity, the phase ratio, the initial pH of aqueous waste solution, the reaction temperature and the initial concentration of extractant on the extraction efficiency are investigated and the optimal process conditions are obtained. The results show that chromium(III) in aqueous waste solution can be effectively removed with (2-ethylhexyl) 2-ethylhexyl phosphonate in the circular microchannel. Under optimized conditions, an extraction efficiency of chromium(III) of more than 99% can be attained and the aqueous waste solution can be discharged directly, which can meet the Chinese national emission standards.

Large-angle slewing maneuvers for flexible spacecraft

NASA Technical Reports Server (NTRS)

Chun, Hon M.; Turner, James D.

1988-01-01

A new class of closed-form solutions for finite-time linear-quadratic optimal control problems is presented. The solutions involve Potter's solution for the differential matrix Riccati equation, which assumes the form of a steady-state plus transient term. Illustrative examples are presented which show that the new solutions are more computationally efficient than alternative solutions based on the state transition matrix. As an application of the closed-form solutions, the neighboring extremal path problem is presented for a spacecraft retargeting maneuver where a perturbed plant with off-nominal boundary conditions now follows a neighboring optimal trajectory. The perturbation feedback approach is further applied to three-dimensional slewing maneuvers of large flexible spacecraft. For this problem, the nominal solution is the optimal three-dimensional rigid body slew. The perturbation feedback then limits the deviations from this nominal solution due to the flexible body effects. The use of frequency shaping in both the nominal and perturbation feedback formulations reduces the excitation of high-frequency unmodeled modes. A modified Kalman filter is presented for estimating the plant states.

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

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

Kouri, Drew Philip; Surowiec, Thomas M.

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

DOE PAGES

Kouri, Drew Philip; Surowiec, Thomas M.

2018-06-05

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

Development of new UV-vis spectroscopic microwave-assisted method for determination of glucose in pharmaceutical samples

NASA Astrophysics Data System (ADS)

Mabood, Fazal; Hussain, Z.; Haq, H.; Arian, M. B.; Boqué, R.; Khan, K. M.; Hussain, K.; Jabeen, F.; Hussain, J.; Ahmed, M.; Alharasi, A.; Naureen, Z.; Hussain, H.; Khan, A.; Perveen, S.

2016-01-01

A new UV-Visible spectroscopic method assisted with microwave for the determination of glucose in pharmaceutical formulations was developed. In this study glucose solutions were oxidized by ammonium molybdate in the presence of microwave energy and reacted with aniline to produce a colored solution. Optimum conditions of the reaction including wavelength, temperature, and pH of the medium and relative concentration ratio of the reactants were investigated. It was found that the optimal wavelength for the reaction is 610 nm, the optimal reaction time is 80 s, the optimal reaction temperature is 160 °C, the optimal reaction pH is 4, and the optimal concentration ratio aniline/ammonium molybdate solution was found to be 1:1. The limits of detection and quantification of the method are 0.82 and 2.75 ppm for glucose solution, respectively. The use of microwaves improved the speed of the method while the use of aniline improved the sensitivity of the method by shifting the wavelength.

Discrete particle swarm optimization to solve multi-objective limited-wait hybrid flow shop scheduling problem

NASA Astrophysics Data System (ADS)

Santosa, B.; Siswanto, N.; Fiqihesa

2018-04-01

This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution

Global optimization methods for engineering design

NASA Technical Reports Server (NTRS)

Arora, Jasbir S.

1990-01-01

The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.

Biosurfactant-biopolymer driven microbial enhanced oil recovery (MEOR) and its optimization by an ANN-GA hybrid technique.

PubMed

Dhanarajan, Gunaseelan; Rangarajan, Vivek; Bandi, Chandrakanth; Dixit, Abhivyakti; Das, Susmita; Ale, Kranthikiran; Sen, Ramkrishna

2017-08-20

A lipopeptide biosurfactant produced by marine Bacillus megaterium and a biopolymer produced by thermophilic Bacillus licheniformis were tested for their application potential in the enhanced oil recovery. The crude biosurfactant obtained after acid precipitation effectively reduced the surface tension of deionized water from 70.5 to 28.25mN/m and the interfacial tension between lube oil and water from 18.6 to 1.5mN/m at a concentration of 250mgL -1 . The biosurfactant exhibited a maximum emulsification activity (E 24 ) of 81.66% against lube oil. The lipopeptide micelles were stabilized by addition of Ca 2+ ions to the biosurfactant solution. The oil recovery efficiency of Ca 2+ conditioned lipopeptide solution from a sand-packed column was optimized by using artificial neural network (ANN) modelling coupled with genetic algorithm (GA) optimization. Three important parameters namely lipopeptide concentration, Ca 2+ concentration and solution pH were considered for optimization studies. In order to further improve the recovery efficiency, a water soluble biopolymer produced by Bacillus licheniformis was used as a flooding agent after biosurfactant incubation. Upon ANN-GA optimization, 45% tertiary oil recovery was achieved, when biopolymer at a concentration of 3gL -1 was used as a flooding agent. Oil recovery was only 29% at optimal conditions predicted by ANN-GA, when only water was used as flooding solution. The important characteristics of biopolymers such as its viscosity, pore plugging capabilities and bio-cementing ability have also been tested. Thus, as a result of biosurfactant incubation and biopolymer flooding under the optimal process conditions, a maximum oil recovery of 45% was achieved. Therefore, this study is novel, timely and interesting for it showed the combined influence of biosurfactant and biopolymer on solubilisation and mobilization of oil from the soil. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Reister, D.B.; Lenhart, S.M.

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature ofmore » the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.« less

Optimal nonlinear filtering using the finite-volume method

NASA Astrophysics Data System (ADS)

Fox, Colin; Morrison, Malcolm E. K.; Norton, Richard A.; Molteno, Timothy C. A.

2018-01-01

Optimal sequential inference, or filtering, for the state of a deterministic dynamical system requires simulation of the Frobenius-Perron operator, that can be formulated as the solution of a continuity equation. For low-dimensional, smooth systems, the finite-volume numerical method provides a solution that conserves probability and gives estimates that converge to the optimal continuous-time values, while a Courant-Friedrichs-Lewy-type condition assures that intermediate discretized solutions remain positive density functions. This method is demonstrated in an example of nonlinear filtering for the state of a simple pendulum, with comparison to results using the unscented Kalman filter, and for a case where rank-deficient observations lead to multimodal probability distributions.

Homotopy approach to optimal, linear quadratic, fixed architecture compensation

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1991-01-01

Optimal linear quadratic Gaussian compensators with constrained architecture are a sensible way to generate good multivariable feedback systems meeting strict implementation requirements. The optimality conditions obtained from the constrained linear quadratic Gaussian are a set of highly coupled matrix equations that cannot be solved algebraically except when the compensator is centralized and full order. An alternative to the use of general parameter optimization methods for solving the problem is to use homotopy. The benefit of the method is that it uses the solution to a simplified problem as a starting point and the final solution is then obtained by solving a simple differential equation. This paper investigates the convergence properties and the limitation of such an approach and sheds some light on the nature and the number of solutions of the constrained linear quadratic Gaussian problem. It also demonstrates the usefulness of homotopy on an example of an optimal decentralized compensator.

Time optimal paths for high speed maneuvering

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

Reister, D.B.; Lenhart, S.M.

1993-01-01

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature ofmore » the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.« less

A Generalization of the Karush-Kuhn-Tucker Theorem for Approximate Solutions of Mathematical Programming Problems Based on Quadratic Approximation

NASA Astrophysics Data System (ADS)

Voloshinov, V. V.

2018-03-01

In computations related to mathematical programming problems, one often has to consider approximate, rather than exact, solutions satisfying the constraints of the problem and the optimality criterion with a certain error. For determining stopping rules for iterative procedures, in the stability analysis of solutions with respect to errors in the initial data, etc., a justified characteristic of such solutions that is independent of the numerical method used to obtain them is needed. A necessary δ-optimality condition in the smooth mathematical programming problem that generalizes the Karush-Kuhn-Tucker theorem for the case of approximate solutions is obtained. The Lagrange multipliers corresponding to the approximate solution are determined by solving an approximating quadratic programming problem.

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

Luo, Yousong, E-mail: yousong.luo@rmit.edu.au

This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.

Strong convergence and convergence rates of approximating solutions for algebraic Riccati equations in Hilbert spaces

NASA Technical Reports Server (NTRS)

Ito, Kazufumi

1987-01-01

The linear quadratic optimal control problem on infinite time interval for linear time-invariant systems defined on Hilbert spaces is considered. The optimal control is given by a feedback form in terms of solution pi to the associated algebraic Riccati equation (ARE). A Ritz type approximation is used to obtain a sequence pi sup N of finite dimensional approximations of the solution to ARE. A sufficient condition that shows pi sup N converges strongly to pi is obtained. Under this condition, a formula is derived which can be used to obtain a rate of convergence of pi sup N to pi. The results of the Galerkin approximation is demonstrated and applied for parabolic systems and the averaging approximation for hereditary differential systems.

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning

PubMed Central

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach. PMID:24616695

Synergetic motor control paradigm for optimizing energy efficiency of multijoint reaching via tacit learning.

PubMed

Hayashibe, Mitsuhiro; Shimoda, Shingo

2014-01-01

A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

Optimisation multi-objectif des systemes energetiques

NASA Astrophysics Data System (ADS)

Dipama, Jean

The increasing demand of energy and the environmental concerns related to greenhouse gas emissions lead to more and more private or public utilities to turn to nuclear energy as an alternative for the future. Nuclear power plants are then called to experience large expansion in the coming years. Improved technologies will then be put in place to support the development of these plants. This thesis considers the optimization of the thermodynamic cycle of the secondary loop of Gentilly-2 nuclear power plant in terms of output power and thermal efficiency. In this thesis, investigations are carried out to determine the optimal operating conditions of steam power cycles by the judicious use of the combination of steam extraction at the different stages of the turbines. Whether it is the case of superheating or regeneration, we are confronted in all cases to an optimization problem involving two conflicting objectives, as increasing the efficiency imply the decrease of mechanical work and vice versa. Solving this kind of problem does not lead to unique solution, but to a set of solutions that are tradeoffs between the conflicting objectives. To search all of these solutions, called Pareto optimal solutions, the use of an appropriate optimization algorithm is required. Before starting the optimization of the secondary loop, we developed a thermodynamic model of the secondary loop which includes models for the main thermal components (e.g., turbine, moisture separator-superheater, condenser, feedwater heater and deaerator). This model is used to calculate the thermodynamic state of the steam and water at the different points of the installation. The thermodynamic model has been developed with Matlab and validated by comparing its predictions with the operating data provided by the engineers of the power plant. The optimizer developed in VBA (Visual Basic for Applications) uses an optimization algorithm based on the principle of genetic algorithms, a stochastic optimization method which is very robust and widely used to solve problems usually difficult to handle by traditional methods. Genetic algorithms (GAs) have been used in previous research and proved to be efficient in optimizing heat exchangers networks (HEN) (Dipama et al., 2008). So, HEN have been synthesized to recover the maximum heat in an industrial process. The optimization problem formulated in the context of this work consists of a single objective, namely the maximization of energy recovery. The optimization algorithm developed in this thesis extends the ability of GAs by taking into account several objectives simultaneously. This algorithm provides an innovation in the method of finding optimal solutions, by using a technique which consist of partitioning the solutions space in the form of parallel grids called "watching corridors". These corridors permit to specify areas (the observation corridors) in which the most promising feasible solutions are found and used to guide the search towards optimal solutions. A measure of the progress of the search is incorporated into the optimization algorithm to make it self-adaptive through the use of appropriate genetic operators at each stage of optimization process. The proposed method allows a fast convergence and ensure a diversity of solutions. Moreover, this method gives the algorithm the ability to overcome difficulties associated with optimizing problems with complex Pareto front landscapes (e.g., discontinuity, disjunction, etc.). The multi-objective optimization algorithm has been first validated using numerical test problems found in the literature as well as energy systems optimization problems. Finally, the proposed optimization algorithm has been applied for the optimization of the secondary loop of Gentilly-2 nuclear power plant, and a set of solutions have been found which permit to make the power plant operate in optimal conditions. (Abstract shortened by UMI.)

Optimal boundary conditions for ORCA-2 model

NASA Astrophysics Data System (ADS)

Kazantsev, Eugene

2013-08-01

A 4D-Var data assimilation technique is applied to ORCA-2 configuration of the NEMO in order to identify the optimal parametrization of boundary conditions on the lateral boundaries as well as on the bottom and on the surface of the ocean. The influence of boundary conditions on the solution is analyzed both within and beyond the assimilation window. It is shown that the optimal bottom and surface boundary conditions allow us to better represent the jet streams, such as Gulf Stream and Kuroshio. Analyzing the reasons of the jets reinforcement, we notice that data assimilation has a major impact on parametrization of the bottom boundary conditions for u and v. Automatic generation of the tangent and adjoint codes is also discussed. Tapenade software is shown to be able to produce the adjoint code that can be used after a memory usage optimization.

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE PAGES

Liu, Jianfeng; Laird, Carl Damon

2017-09-22

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

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

Liu, Jianfeng; Laird, Carl Damon

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

Fuel optimal maneuvers of spacecraft about a circular orbit

NASA Technical Reports Server (NTRS)

Carter, T. E.

1982-01-01

Fuel optimal maneuvers of spacecraft relative to a body in circular orbit are investigated using a point mass model in which the magnitude of the thrust vector is bounded. All nonsingular optimal maneuvers consist of intervals of full thrust and coast and are found to contain at most seven such intervals in one period. Only four boundary conditions where singular solutions occur are possible. Computer simulation of optimal flight path shapes and switching functions are found for various boundary conditions. Emphasis is placed on the problem of soft rendezvous with a body in circular orbit.

Discontinuous solutions of Hamilton-Jacobi equations on networks

NASA Astrophysics Data System (ADS)

Graber, P. J.; Hermosilla, C.; Zidani, H.

2017-12-01

This paper studies optimal control problems on networks without controllability assumptions at the junctions. The Value Function associated with the control problem is characterized as the solution to a system of Hamilton-Jacobi equations with appropriate junction conditions. The novel feature of the result lies in that the controllability conditions are not needed and the characterization remains valid even when the Value Function is not continuous.

Micro-scale NMR Experiments for Monitoring the Optimization of Membrane Protein Solutions for Structural Biology.

PubMed

Horst, Reto; Wüthrich, Kurt

2015-07-20

Reconstitution of integral membrane proteins (IMP) in aqueous solutions of detergent micelles has been extensively used in structural biology, using either X-ray crystallography or NMR in solution. Further progress could be achieved by establishing a rational basis for the selection of detergent and buffer conditions, since the stringent bottleneck that slows down the structural biology of IMPs is the preparation of diffracting crystals or concentrated solutions of stable isotope labeled IMPs. Here, we describe procedures to monitor the quality of aqueous solutions of [ 2 H, 15 N]-labeled IMPs reconstituted in detergent micelles. This approach has been developed for studies of β-barrel IMPs, where it was successfully applied for numerous NMR structure determinations, and it has also been adapted for use with α-helical IMPs, in particular GPCRs, in guiding crystallization trials and optimizing samples for NMR studies (Horst et al ., 2013). 2D [ 15 N, 1 H]-correlation maps are used as "fingerprints" to assess the foldedness of the IMP in solution. For promising samples, these "inexpensive" data are then supplemented with measurements of the translational and rotational diffusion coefficients, which give information on the shape and size of the IMP/detergent mixed micelles. Using microcoil equipment for these NMR experiments enables data collection with only micrograms of protein and detergent. This makes serial screens of variable solution conditions viable, enabling the optimization of parameters such as the detergent concentration, sample temperature, pH and the composition of the buffer.

Optimized positioning of autonomous surgical lamps

NASA Astrophysics Data System (ADS)

Teuber, Jörn; Weller, Rene; Kikinis, Ron; Oldhafer, Karl-Jürgen; Lipp, Michael J.; Zachmann, Gabriel

2017-03-01

We consider the problem of finding automatically optimal positions of surgical lamps throughout the whole surgical procedure, where we assume that future lamps could be robotized. We propose a two-tiered optimization technique for the real-time autonomous positioning of those robotized surgical lamps. Typically, finding optimal positions for surgical lamps is a multi-dimensional problem with several, in part conflicting, objectives, such as optimal lighting conditions at every point in time while minimizing the movement of the lamps in order to avoid distractions of the surgeon. Consequently, we use multi-objective optimization (MOO) to find optimal positions in real-time during the entire surgery. Due to the conflicting objectives, there is usually not a single optimal solution for such kinds of problems, but a set of solutions that realizes a Pareto-front. When our algorithm selects a solution from this set it additionally has to consider the individual preferences of the surgeon. This is a highly non-trivial task because the relationship between the solution and the parameters is not obvious. We have developed a novel meta-optimization that considers exactly this challenge. It delivers an easy to understand set of presets for the parameters and allows a balance between the lamp movement and lamp obstruction. This metaoptimization can be pre-computed for different kinds of operations and it then used by our online optimization for the selection of the appropriate Pareto solution. Both optimization approaches use data obtained by a depth camera that captures the surgical site but also the environment around the operating table. We have evaluated our algorithms with data recorded during a real open abdominal surgery. It is available for use for scientific purposes. The results show that our meta-optimization produces viable parameter sets for different parts of an intervention even when trained on a small portion of it.

Dataset of working conditions and thermo-economic performances for hybrid organic Rankine plants fed by solar and low-grade energy sources.

PubMed

Scardigno, Domenico; Fanelli, Emanuele; Viggiano, Annarita; Braccio, Giacobbe; Magi, Vinicio

2016-06-01

This article provides the dataset of operating conditions of a hybrid organic Rankine plant generated by the optimization procedure employed in the research article "A genetic optimization of a hybrid organic Rankine plant for solar and low-grade energy sources" (Scardigno et al., 2015) [1]. The methodology used to obtain the data is described. The operating conditions are subdivided into two separate groups: feasible and unfeasible solutions. In both groups, the values of the design variables are given. Besides, the subset of feasible solutions is described in details, by providing the thermodynamic and economic performances, the temperatures at some characteristic sections of the thermodynamic cycle, the net power, the absorbed powers and the area of the heat exchange surfaces.

Optimal Artificial Boundary Condition Configurations for Sensitivity-Based Model Updating and Damage Detection

DTIC Science & Technology

2010-09-01

matrix is used in many methods, like Jacobi or Gauss Seidel , for solving linear systems. Also, no partial pivoting is necessary for a strictly column...problems that arise during the procedure, which in general, converges to the solving of a linear system. The most common issue with the solution is the... iterative procedure to find an appropriate subset of parameters that produce an optimal solution commonly known as forward selection. Then, the

A duality framework for stochastic optimal control of complex systems

DOE PAGES

Malikopoulos, Andreas A.

2016-01-01

In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less

Necessary optimality conditions for infinite dimensional state constrained control problems

NASA Astrophysics Data System (ADS)

Frankowska, H.; Marchini, E. M.; Mazzola, M.

2018-06-01

This paper is concerned with first order necessary optimality conditions for state constrained control problems in separable Banach spaces. Assuming inward pointing conditions on the constraint, we give a simple proof of Pontryagin maximum principle, relying on infinite dimensional neighboring feasible trajectories theorems proved in [20]. Further, we provide sufficient conditions guaranteeing normality of the maximum principle. We work in the abstract semigroup setting, but nevertheless we apply our results to several concrete models involving controlled PDEs. Pointwise state constraints (as positivity of the solutions) are allowed.

Nature-based agricultural solutions: Scaling perennial grains across Africa.

PubMed

Peter, Brad G; Mungai, Leah M; Messina, Joseph P; Snapp, Sieglinde S

2017-11-01

Modern plant breeding tends to focus on maximizing yield, with one of the most ubiquitous implementations being shorter-duration crop varieties. It is indisputable that these breeding efforts have resulted in greater yields in ideal circumstances; however, many farmed locations across Africa suffer from one or more conditions that limit the efficacy of modern short-duration hybrids. In view of global change and increased necessity for intensification, perennial grains and long-duration varieties offer a nature-based solution for improving farm productivity and smallholder livelihoods in suboptimal agricultural areas. Specific conditions where perennial grains should be considered include locations where biophysical and social constraints reduce agricultural system efficiency, and where conditions are optimal for crop growth. Using a time-series of remotely-sensed data, we locate the marginal agricultural lands of Africa, identifying suboptimal temperature and precipitation conditions for the dominant crop, i.e., maize, as well as optimal climate conditions for two perennial grains, pigeonpea and sorghum. We propose that perennial grains offer a lower impact, sustainable nature-based solution to this subset of climatic drivers of marginality. Using spatial analytic methods and satellite-derived climate information, we demonstrate the scalability of perennial pigeonpea and sorghum across Africa. As a nature-based solution, we argue that perennial grains offer smallholder farmers of marginal lands a sustainable solution for enhancing resilience and minimizing risk in confronting global change, while mitigating social and edaphic drivers of low and variable production. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Cocontraction of pairs of antagonistic muscles: analytical solution for planar static nonlinear optimization approaches.

PubMed

Herzog, W; Binding, P

1993-11-01

It has been stated in the literature that static, nonlinear optimization approaches cannot predict coactivation of pairs of antagonistic muscles; however, numerical solutions of such approaches have predicted coactivation of pairs of one-joint and multijoint antagonists. Analytical support for either finding is not available in the literature for systems containing more than one degree of freedom. The purpose of this study was to investigate analytically the possibility of cocontraction of pairs of antagonistic muscles using a static nonlinear optimization approach for a multidegree-of-freedom, two-dimensional system. Analytical solutions were found using the Karush-Kuhn-Tucker conditions, which were necessary and sufficient for optimality in this problem. The results show that cocontraction of pairs of one-joint antagonistic muscles is not possible, whereas cocontraction of pairs of multijoint antagonists is. These findings suggest that cocontraction of pairs of antagonistic muscles may be an "efficient" way to accomplish many movement tasks.

Optimal implicit 2-D finite differences to model wave propagation in poroelastic media

NASA Astrophysics Data System (ADS)

Itzá, Reymundo; Iturrarán-Viveros, Ursula; Parra, Jorge O.

2016-08-01

Numerical modeling of seismic waves in heterogeneous porous reservoir rocks is an important tool for the interpretation of seismic surveys in reservoir engineering. We apply globally optimal implicit staggered-grid finite differences (FD) to model 2-D wave propagation in heterogeneous poroelastic media at a low-frequency range (<10 kHz). We validate the numerical solution by comparing it to an analytical-transient solution obtaining clear seismic wavefields including fast P and slow P and S waves (for a porous media saturated with fluid). The numerical dispersion and stability conditions are derived using von Neumann analysis, showing that over a wide range of porous materials the Courant condition governs the stability and this optimal implicit scheme improves the stability of explicit schemes. High-order explicit FD can be replaced by some lower order optimal implicit FD so computational cost will not be as expensive while maintaining the accuracy. Here, we compute weights for the optimal implicit FD scheme to attain an accuracy of γ = 10-8. The implicit spatial differentiation involves solving tridiagonal linear systems of equations through Thomas' algorithm.

A Few Good Crystals Please

NASA Technical Reports Server (NTRS)

Judge, Russell A.; Snell, Edward H.

1999-01-01

Part of the challenge of macromolecular crystal growth for structure determination is obtaining an appropriate number of crystals with a crystal volume suitable for X-ray analysis. In this respect an understanding of the effect of solution conditions on macromolecule nucleation rates is advantageous. This study investigated the effects of solution conditions on the nucleation rate and final crystal size of two crystal systems; tetragonal lysozyme and glucose isomerase. Batch crystallization plates were prepared at given solution concentration and incubated at set temperatures over one week. The number of crystals per well with their size and axial ratios were recorded and correlated with solution conditions. Duplicate experiments indicate the reproducibility of the technique. Results for each system showing the effect of supersaturation, incubation temperature and solution pH on nucleation rates will be presented and discussed. In the case of lysozyme, having optimized solution conditions to produce an appropriate number of crystals of a suitable size, a batch of crystals were prepared under exactly the same conditions. Fifty of these crystals were analyzed by x-ray techniques. The results indicate that even under the same crystallization conditions, a marked variation in crystal properties exists.

Effect of Infusion Method and Parameters on Mass Transfer in Blueberries

USDA-ARS?s Scientific Manuscript database

In order to obtain optimal processing conditions for producing infused blueberries with high solid gain, we investigated the infusion characteristics of blueberries under various processing parameters in sugar solutions with 1:1 ratio of solution and berries. Static batch constant concentration inf...

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

NASA Astrophysics Data System (ADS)

Angjelichinoski, Marko; Scaglione, Anna; Popovski, Petar; Stefanovic, Cedomir

2018-06-01

We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to eliminate the need to rely on an external communication system for such purpose. The solution works within the primary droop control loops and uses only local bus voltage measurements. Each controller is able to estimate (i) the generation capacities of power sources, (ii) the load demands, and (iii) the conductances of the distribution lines. To define a well-conditioned estimation problem, we employ decentralized strategy where the primary droop controllers temporarily switch between operating points in a coordinated manner, following amplitude-modulated training sequences. We study the use of the estimator in a decentralized solution of the Optimal Economic Dispatch problem. The evaluations confirm the usefulness of the proposed solution for autonomous MicroGrid operation.

Extraction of Lithium from Brine Solution by Hydrolysis of Activated Aluminum Powder

NASA Astrophysics Data System (ADS)

Li, Yanhong; Chen, Xingyu; Liu, Xuheng; Zhao, Zhongwei; Liu, Chongwu

2018-05-01

Activated aluminum powder has been used to extract lithium from Mg-Li mixed solution via a hydrolysis-adsorption reaction. First, activated aluminum powder was prepared under the optimal conditions of NaCl addition of 70%, ball-milling time of 3 h, and ball-to-powder mass ratio of 20:1. Then, the activated aluminum powder was added into the Mg-Li mixed solution to extract lithium. X-ray diffraction analysis indicated that Li+ was adsorbed by freshly formed Al(OH)3 in the form of LADH-Cl [LiCl·2Al(OH)3·mH2O]. Under the optimal conditions of reaction time of 3 h, Al/Li molar ratio of 4:1 for activated aluminum powder addition, and reaction temperature of 70°C, lithium precipitation exceeded 90% while magnesium precipitation was controlled at 13%. These results indicate that activated aluminum powder can efficiently extract lithium from Mg-Li mixed solution via a hydrolysis-adsorption reaction.

Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach

NASA Technical Reports Server (NTRS)

Das, Santanu; Oza, Nikunj C.

2011-01-01

In this paper we propose an innovative learning algorithm - a variation of One-class nu Support Vector Machines (SVMs) learning algorithm to produce sparser solutions with much reduced computational complexities. The proposed technique returns an approximate solution, nearly as good as the solution set obtained by the classical approach, by minimizing the original risk function along with a regularization term. We introduce a bi-criterion optimization that helps guide the search towards the optimal set in much reduced time. The outcome of the proposed learning technique was compared with the benchmark one-class Support Vector machines algorithm which more often leads to solutions with redundant support vectors. Through out the analysis, the problem size for both optimization routines was kept consistent. We have tested the proposed algorithm on a variety of data sources under different conditions to demonstrate the effectiveness. In all cases the proposed algorithm closely preserves the accuracy of standard one-class nu SVMs while reducing both training time and test time by several factors.

A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion.

PubMed

Liu, Qingshan; Dang, Chuangyin; Huang, Tingwen

2013-02-01

This paper presents a decision-making model described by a recurrent neural network for dynamic portfolio optimization. The portfolio-optimization problem is first converted into a constrained fractional programming problem. Since the objective function in the programming problem is not convex, the traditional optimization techniques are no longer applicable for solving this problem. Fortunately, the objective function in the fractional programming is pseudoconvex on the feasible region. It leads to a one-layer recurrent neural network modeled by means of a discontinuous dynamic system. To ensure the optimal solutions for portfolio optimization, the convergence of the proposed neural network is analyzed and proved. In fact, the neural network guarantees to get the optimal solutions for portfolio-investment advice if some mild conditions are satisfied. A numerical example with simulation results substantiates the effectiveness and illustrates the characteristics of the proposed neural network.

Hybrid optimal scheduling for intermittent androgen suppression of prostate cancer

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; di Bernardo, Mario; Bruchovsky, Nicholas; Aihara, Kazuyuki

2010-12-01

We propose a method for achieving an optimal protocol of intermittent androgen suppression for the treatment of prostate cancer. Since the model that reproduces the dynamical behavior of the surrogate tumor marker, prostate specific antigen, is piecewise linear, we can obtain an analytical solution for the model. Based on this, we derive conditions for either stopping or delaying recurrent disease. The solution also provides a design principle for the most favorable schedule of treatment that minimizes the rate of expansion of the malignant cell population.

Trajectory Design Employing Convex Optimization for Landing on Irregularly Shaped Asteroids

NASA Technical Reports Server (NTRS)

Pinson, Robin M.; Lu, Ping

2016-01-01

Mission proposals that land on asteroids are becoming popular. However, in order to have a successful mission the spacecraft must reliably and softly land at the intended landing site. The problem under investigation is how to design a fuel-optimal powered descent trajectory that can be quickly computed on- board the spacecraft, without interaction from ground control. An optimal trajectory designed immediately prior to the descent burn has many advantages. These advantages include the ability to use the actual vehicle starting state as the initial condition in the trajectory design and the ease of updating the landing target site if the original landing site is no longer viable. For long trajectories, the trajectory can be updated periodically by a redesign of the optimal trajectory based on current vehicle conditions to improve the guidance performance. One of the key drivers for being completely autonomous is the infrequent and delayed communication between ground control and the vehicle. Challenges that arise from designing an asteroid powered descent trajectory include complicated nonlinear gravity fields, small rotating bodies and low thrust vehicles. There are two previous studies that form the background to the current investigation. The first set looked in-depth at applying convex optimization to a powered descent trajectory on Mars with promising results.1, 2 This showed that the powered descent equations of motion can be relaxed and formed into a convex optimization problem and that the optimal solution of the relaxed problem is indeed a feasible solution to the original problem. This analysis used a constant gravity field. The second area applied a successive solution process to formulate a second order cone program that designs rendezvous and proximity operations trajectories.3, 4 These trajectories included a Newtonian gravity model. The equivalence of the solutions between the relaxed and the original problem is theoretically established. The proposed solution for designing the asteroid powered descent trajectory is to use convex optimization, a gravity model with higher fidelity than Newtonian, and an iterative solution process to design the fuel optimal trajectory. The solution to the convex optimization problem is the thrust profile, magnitude and direction, that will yield the minimum fuel trajectory for a soft landing at the target site, subject to various mission and operational constraints. The equations of motion are formulated in a rotating coordinate system and includes a high fidelity gravity model. The vehicle's thrust magnitude can vary between maximum and minimum bounds during the burn. Also, constraints are included to ensure that the vehicle does not run out of propellant, or go below the asteroid's surface, and any vehicle pointing requirements. The equations of motion are discretized and propagated with the trapezoidal rule in order to produce equality constraints for the optimization problem. These equality constraints allow the optimization algorithm to solve the entire problem, without including a propagator inside the optimization algorithm.

Integer programming model for optimizing bus timetable using genetic algorithm

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Buono, A.; Silalahi, B. P.

2017-01-01

Bus timetable gave an information for passengers to ensure the availability of bus services. Timetable optimal condition happened when bus trips frequency could adapt and suit with passenger demand. In the peak time, the number of bus trips would be larger than the off-peak time. If the number of bus trips were more frequent than the optimal condition, it would make a high operating cost for bus operator. Conversely, if the number of trip was less than optimal condition, it would make a bad quality service for passengers. In this paper, the bus timetabling problem would be solved by integer programming model with modified genetic algorithm. Modification was placed in the chromosomes design, initial population recovery technique, chromosomes reconstruction and chromosomes extermination on specific generation. The result of this model gave the optimal solution with accuracy 99.1%.

Use of an Annular Silicon Drift Detector (SDD) Versus a Conventional SDD Makes Phase Mapping a Practical Solution for Rare Earth Mineral Characterization.

PubMed

Teng, Chaoyi; Demers, Hendrix; Brodusch, Nicolas; Waters, Kristian; Gauvin, Raynald

2018-06-04

A number of techniques for the characterization of rare earth minerals (REM) have been developed and are widely applied in the mining industry. However, most of them are limited to a global analysis due to their low spatial resolution. In this work, phase map analyses were performed on REM with an annular silicon drift detector (aSDD) attached to a field emission scanning electron microscope. The optimal conditions for the aSDD were explored, and the high-resolution phase maps generated at a low accelerating voltage identify phases at the micron scale. In comparisons between an annular and a conventional SDD, the aSDD performed at optimized conditions, making the phase map a practical solution for choosing an appropriate grinding size, judging the efficiency of different separation processes, and optimizing a REM beneficiation flowsheet.

Spacecraft Attitude Maneuver Planning Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2004-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This approach for attitude path planning makes full use of a priori constraint knowledge and is computationally tractable enough to be executed onboard a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used as is or as an initial solution to initialize additional deterministic optimization algorithms. A number of representative case examples for time-fixed and time-varying conditions yielded search times that are typically on the order of minutes, thus demonstrating the viability of this method. This approach is applicable to all deep space and planet Earth missions requiring greater spacecraft autonomy, and greatly facilitates navigation and science observation planning.

Pareto joint inversion of 2D magnetotelluric and gravity data

NASA Astrophysics Data System (ADS)

Miernik, Katarzyna; Bogacz, Adrian; Kozubal, Adam; Danek, Tomasz; Wojdyła, Marek

2015-04-01

In this contribution, the first results of the "Innovative technology of petrophysical parameters estimation of geological media using joint inversion algorithms" project were described. At this stage of the development, Pareto joint inversion scheme for 2D MT and gravity data was used. Additionally, seismic data were provided to set some constrains for the inversion. Sharp Boundary Interface(SBI) approach and description model with set of polygons were used to limit the dimensionality of the solution space. The main engine was based on modified Particle Swarm Optimization(PSO). This algorithm was properly adapted to handle two or more target function at once. Additional algorithm was used to eliminate non- realistic solution proposals. Because PSO is a method of stochastic global optimization, it requires a lot of proposals to be evaluated to find a single Pareto solution and then compose a Pareto front. To optimize this stage parallel computing was used for both inversion engine and 2D MT forward solver. There are many advantages of proposed solution of joint inversion problems. First of all, Pareto scheme eliminates cumbersome rescaling of the target functions, that can highly affect the final solution. Secondly, the whole set of solution is created in one optimization run, providing a choice of the final solution. This choice can be based off qualitative data, that are usually very hard to be incorporated into the regular inversion schema. SBI parameterisation not only limits the problem of dimensionality, but also makes constraining of the solution easier. At this stage of work, decision to test the approach using MT and gravity data was made, because this combination is often used in practice. It is important to mention, that the general solution is not limited to this two methods and it is flexible enough to be used with more than two sources of data. Presented results were obtained for synthetic models, imitating real geological conditions, where interesting density distributions are relatively shallow and resistivity changes are related to deeper parts. This kind of conditions are well suited for joint inversion of MT and gravity data. In the next stage of the solution development of further code optimization and extensive tests for real data will be realized. Presented work was supported by Polish National Centre for Research and Development under the contract number POIG.01.04.00-12-279/13

Optimal four-impulse rendezvous between coplanar elliptical orbits

NASA Astrophysics Data System (ADS)

Wang, JianXia; Baoyin, HeXi; Li, JunFeng; Sun, FuChun

2011-04-01

Rendezvous in circular or near circular orbits has been investigated in great detail, while rendezvous in arbitrary eccentricity elliptical orbits is not sufficiently explored. Among the various optimization methods proposed for fuel optimal orbital rendezvous, Lawden's primer vector theory is favored by many researchers with its clear physical concept and simplicity in solution. Prussing has applied the primer vector optimization theory to minimum-fuel, multiple-impulse, time-fixed orbital rendezvous in a near circular orbit and achieved great success. Extending Prussing's work, this paper will employ the primer vector theory to study trajectory optimization problems of arbitrary eccentricity elliptical orbit rendezvous. Based on linearized equations of relative motion on elliptical reference orbit (referred to as T-H equations), the primer vector theory is used to deal with time-fixed multiple-impulse optimal rendezvous between two coplanar, coaxial elliptical orbits with arbitrary large eccentricity. A parameter adjustment method is developed for the prime vector to satisfy the Lawden's necessary condition for the optimal solution. Finally, the optimal multiple-impulse rendezvous solution including the time, direction and magnitudes of the impulse is obtained by solving the two-point boundary value problem. The rendezvous error of the linearized equation is also analyzed. The simulation results confirmed the analyzed results that the rendezvous error is small for the small eccentricity case and is large for the higher eccentricity. For better rendezvous accuracy of high eccentricity orbits, a combined method of multiplier penalty function with the simplex search method is used for local optimization. The simplex search method is sensitive to the initial values of optimization variables, but the simulation results show that initial values with the primer vector theory, and the local optimization algorithm can improve the rendezvous accuracy effectively with fast convergence, because the optimal results obtained by the primer vector theory are already very close to the actual optimal solution. If the initial values are taken randomly, it is difficult to converge to the optimal solution.

Boundary control of elliptic solutions to enforce local constraints

NASA Astrophysics Data System (ADS)

Bal, G.; Courdurier, M.

We present a constructive method to devise boundary conditions for solutions of second-order elliptic equations so that these solutions satisfy specific qualitative properties such as: (i) the norm of the gradient of one solution is bounded from below by a positive constant in the vicinity of a finite number of prescribed points; (ii) the determinant of gradients of n solutions is bounded from below in the vicinity of a finite number of prescribed points. Such constructions find applications in recent hybrid medical imaging modalities. The methodology is based on starting from a controlled setting in which the constraints are satisfied and continuously modifying the coefficients in the second-order elliptic equation. The boundary condition is evolved by solving an ordinary differential equation (ODE) defined via appropriate optimality conditions. Unique continuations and standard regularity results for elliptic equations are used to show that the ODE admits a solution for sufficiently long times.

A master-slave parallel hybrid multi-objective evolutionary algorithm for groundwater remediation design under general hydrogeological conditions

NASA Astrophysics Data System (ADS)

Wu, J.; Yang, Y.; Luo, Q.; Wu, J.

2012-12-01

This study presents a new hybrid multi-objective evolutionary algorithm, the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), whereby the global search ability of niched Pareto tabu search (NPTS) is improved by the diversification of candidate solutions arose from the evolving nondominated sorting genetic algorithm II (NSGA-II) population. Also, the NPTSGA coupled with the commonly used groundwater flow and transport codes, MODFLOW and MT3DMS, is developed for multi-objective optimal design of groundwater remediation systems. The proposed methodology is then applied to a large-scale field groundwater remediation system for cleanup of large trichloroethylene (TCE) plume at the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. Furthermore, a master-slave (MS) parallelization scheme based on the Message Passing Interface (MPI) is incorporated into the NPTSGA to implement objective function evaluations in distributed processor environment, which can greatly improve the efficiency of the NPTSGA in finding Pareto-optimal solutions to the real-world application. This study shows that the MS parallel NPTSGA in comparison with the original NPTS and NSGA-II can balance the tradeoff between diversity and optimality of solutions during the search process and is an efficient and effective tool for optimizing the multi-objective design of groundwater remediation systems under complicated hydrogeologic conditions.

Solution of the multiextreme optimization problem for low-thrust spacecraft flight to the asteroid apophis

NASA Astrophysics Data System (ADS)

Ivashkin, V. V.; Krylov, I. V.

2015-09-01

A method to optimize the flight trajectories to the asteroid Apophis that allows reliably to form a set of Pontryagin extremals for various boundary conditions of the flight, as well as effectively to search for a global problem optimum amongst its elements, is developed.

The mechanisms and boundary conditions of the Einstellung effect in chess: evidence from eye movements.

PubMed

Sheridan, Heather; Reingold, Eyal M

2013-01-01

In a wide range of problem-solving settings, the presence of a familiar solution can block the discovery of better solutions (i.e., the Einstellung effect). To investigate this effect, we monitored the eye movements of expert and novice chess players while they solved chess problems that contained a familiar move (i.e., the Einstellung move), as well as an optimal move that was located in a different region of the board. When the Einstellung move was an advantageous (but suboptimal) move, both the expert and novice chess players who chose the Einstellung move continued to look at this move throughout the trial, whereas the subset of expert players who chose the optimal move were able to gradually disengage their attention from the Einstellung move. However, when the Einstellung move was a blunder, all of the experts and the majority of the novices were able to avoid selecting the Einstellung move, and both the experts and novices gradually disengaged their attention from the Einstellung move. These findings shed light on the boundary conditions of the Einstellung effect, and provide convergent evidence for Bilalić, McLeod, & Gobet (2008)'s conclusion that the Einstellung effect operates by biasing attention towards problem features that are associated with the familiar solution rather than the optimal solution.

On the analytic and numeric optimisation of airplane trajectories under real atmospheric conditions

NASA Astrophysics Data System (ADS)

Gonzalo, J.; Domínguez, D.; López, D.

2014-12-01

From the beginning of aviation era, economic constraints have forced operators to continuously improve the planning of the flights. The revenue is proportional to the cost per flight and the airspace occupancy. Many methods, the first started in the middle of last century, have explore analytical, numerical and artificial intelligence resources to reach the optimal flight planning. In parallel, advances in meteorology and communications allow an almost real-time knowledge of the atmospheric conditions and a reliable, error-bounded forecast for the near future. Thus, apart from weather risks to be avoided, airplanes can dynamically adapt their trajectories to minimise their costs. International regulators are aware about these capabilities, so it is reasonable to envisage some changes to allow this dynamic planning negotiation to soon become operational. Moreover, current unmanned airplanes, very popular and often small, suffer the impact of winds and other weather conditions in form of dramatic changes in their performance. The present paper reviews analytic and numeric solutions for typical trajectory planning problems. Analytic methods are those trying to solve the problem using the Pontryagin principle, where influence parameters are added to state variables to form a split condition differential equation problem. The system can be solved numerically -indirect optimisation- or using parameterised functions -direct optimisation-. On the other hand, numerical methods are based on Bellman's dynamic programming (or Dijkstra algorithms), where the fact that two optimal trajectories can be concatenated to form a new optimal one if the joint point is demonstrated to belong to the final optimal solution. There is no a-priori conditions for the best method. Traditionally, analytic has been more employed for continuous problems whereas numeric for discrete ones. In the current problem, airplane behaviour is defined by continuous equations, while wind fields are given in a discrete grid at certain time intervals. The research demonstrates advantages and disadvantages of each method as well as performance figures of the solutions found for typical flight conditions under static and dynamic atmospheres. This provides significant parameters to be used in the selection of solvers for optimal trajectories.

Design of underwater robot lines based on a hybrid automatic optimization strategy

NASA Astrophysics Data System (ADS)

Lyu, Wenjing; Luo, Weilin

2014-09-01

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal; the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body's minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

Polyurethane foam loaded with SDS for the adsorption of cationic dyes from aqueous medium: Multivariate optimization of the loading process.

PubMed

Robaina, Nicolle F; Soriano, Silvio; Cassella, Ricardo J

2009-08-15

This paper reports the development of a new procedure for the adsorption of four cationic dyes (Rhodamine B, Methylene Blue, Crystal Violet and Malachite Green) from aqueous medium employing polyurethane foam (PUF) loaded with sodium dodecylsulfate (SDS) as solid phase. PUF loading process was based on the stirring of 200mg PUF cylinders with acidic solutions containing SDS. The conditions for loading were optimized by response surface methodology (RSM) using a Doehlert design with three variables that were SDS and HCl concentrations and stirring time. Results obtained in the optimization process showed that the stirring time is not a relevant parameter in the PUF loading, evidencing that the transport of SDS from solution to PUF surface is fast. On the other hand, both SDS and HCl concentrations were important parameters causing significant variation in the efficiency of the resulting solid phase for the removal of dyes from solution. At optimized conditions, SDS and HCl concentrations were 4.0 x 10(-4) and 0.90 mol L(-1), respectively. The influence of stirring time was evaluated by univariate methodology. A 20 min stirring time was established in order to make the PUF loading process fast and robust without losing efficiency. The procedure was tested for the removal of the four cationic dyes from aqueous solutions and removal efficiencies always better than 90% were achieved for the two concentrations tested (2.0 x 10(-5) and 1.0 x 10(-4)mol L(-1)).

A time-domain decomposition iterative method for the solution of distributed linear quadratic optimal control problems

NASA Astrophysics Data System (ADS)

Heinkenschloss, Matthias

2005-01-01

We study a class of time-domain decomposition-based methods for the numerical solution of large-scale linear quadratic optimal control problems. Our methods are based on a multiple shooting reformulation of the linear quadratic optimal control problem as a discrete-time optimal control (DTOC) problem. The optimality conditions for this DTOC problem lead to a linear block tridiagonal system. The diagonal blocks are invertible and are related to the original linear quadratic optimal control problem restricted to smaller time-subintervals. This motivates the application of block Gauss-Seidel (GS)-type methods for the solution of the block tridiagonal systems. Numerical experiments show that the spectral radii of the block GS iteration matrices are larger than one for typical applications, but that the eigenvalues of the iteration matrices decay to zero fast. Hence, while the GS method is not expected to convergence for typical applications, it can be effective as a preconditioner for Krylov-subspace methods. This is confirmed by our numerical tests.A byproduct of this research is the insight that certain instantaneous control techniques can be viewed as the application of one step of the forward block GS method applied to the DTOC optimality system.

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee the S 3 ONC admits FPTAS.

Optimal rendezvous in the neighborhood of a circular orbit

NASA Technical Reports Server (NTRS)

Jones, J. B.

1975-01-01

The minimum velocity change rendezvous solutions, when the motion may be linearized about a circular orbit, fall into two separate regions; the phase-for-free region and the general region. Phase-for-free solutions are derived from the optimum transfer solutions, require the same velocity change expenditure, but may not be unique. Analytic solutions are presented in two of the three subregions. An algorithm is presented for determining the unique solutions in the general region. Various sources of initial conditions are discussed and three examples presented.

Optimal policy for profit maximising in an EOQ model under non-linear holding cost and stock-dependent demand rate

NASA Astrophysics Data System (ADS)

Pando, V.; García-Laguna, J.; San-José, L. A.

2012-11-01

In this article, we integrate a non-linear holding cost with a stock-dependent demand rate in a maximising profit per unit time model, extending several inventory models studied by other authors. After giving the mathematical formulation of the inventory system, we prove the existence and uniqueness of the optimal policy. Relying on this result, we can obtain the optimal solution using different numerical algorithms. Moreover, we provide a necessary and sufficient condition to determine whether a system is profitable, and we establish a rule to check when a given order quantity is the optimal lot size of the inventory model. The results are illustrated through numerical examples and the sensitivity of the optimal solution with respect to changes in some values of the parameters is assessed.

Trajectory planning of mobile robots using indirect solution of optimal control method in generalized point-to-point task

NASA Astrophysics Data System (ADS)

Nazemizadeh, M.; Rahimi, H. N.; Amini Khoiy, K.

2012-03-01

This paper presents an optimal control strategy for optimal trajectory planning of mobile robots by considering nonlinear dynamic model and nonholonomic constraints of the system. The nonholonomic constraints of the system are introduced by a nonintegrable set of differential equations which represent kinematic restriction on the motion. The Lagrange's principle is employed to derive the nonlinear equations of the system. Then, the optimal path planning of the mobile robot is formulated as an optimal control problem. To set up the problem, the nonlinear equations of the system are assumed as constraints, and a minimum energy objective function is defined. To solve the problem, an indirect solution of the optimal control method is employed, and conditions of the optimality derived as a set of coupled nonlinear differential equations. The optimality equations are solved numerically, and various simulations are performed for a nonholonomic mobile robot to illustrate effectiveness of the proposed method.

Closed-loop endo-atmospheric ascent guidance for reusable launch vehicle

NASA Astrophysics Data System (ADS)

Sun, Hongsheng

This dissertation focuses on the development of a closed-loop endo-atmospheric ascent guidance algorithm for the 2nd generation reusable launch vehicle. Special attention has been given to the issues that impact on viability, complexity and reliability in on-board implementation. The algorithm is called once every guidance update cycle to recalculate the optimal solution based on the current flight condition, taking into account atmospheric effects and path constraints. This is different from traditional ascent guidance algorithms which operate in a simple open-loop mode inside atmosphere, and later switch to a closed-loop vacuum ascent guidance scheme. The classical finite difference method is shown to be well suited for fast solution of the constrained optimal three-dimensional ascent problem. The initial guesses for the solutions are generated using an analytical vacuum optimal ascent guidance algorithm. Homotopy method is employed to gradually introduce the aerodynamic forces to generate the optimal solution from the optimal vacuum solution. The vehicle chosen for this study is the Lockheed Martin X-33 lifting-body reusable launch vehicle. To verify the algorithm presented in this dissertation, a series of open-loop and closed-loop tests are performed for three different missions. Wind effects are also studied in the closed-loop simulations. For comparison, the solutions for the same missions are also obtained by two independent optimization softwares. The results clearly establish the feasibility of closed-loop endo-atmospheric ascent guidance of rocket-powered launch vehicles. ATO cases are also tested to assess the adaptability of the algorithm to autonomously incorporate the abort modes.

Scheduling Earth Observing Satellites with Evolutionary Algorithms

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna

2003-01-01

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

Rapid computation of directional wellbore drawdown in a confined aquifer via Poisson resummation

NASA Astrophysics Data System (ADS)

Blumenthal, Benjamin J.; Zhan, Hongbin

2016-08-01

We have derived a rapidly computed analytical solution for drawdown caused by a partially or fully penetrating directional wellbore (vertical, horizontal, or slant) via Green's function method. The mathematical model assumes an anisotropic, homogeneous, confined, box-shaped aquifer. Any dimension of the box can have one of six possible boundary conditions: 1) both sides no-flux; 2) one side no-flux - one side constant-head; 3) both sides constant-head; 4) one side no-flux; 5) one side constant-head; 6) free boundary conditions. The solution has been optimized for rapid computation via Poisson Resummation, derivation of convergence rates, and numerical optimization of integration techniques. Upon application of the Poisson Resummation method, we were able to derive two sets of solutions with inverse convergence rates, namely an early-time rapidly convergent series (solution-A) and a late-time rapidly convergent series (solution-B). From this work we were able to link Green's function method (solution-B) back to image well theory (solution-A). We then derived an equation defining when the convergence rate between solution-A and solution-B is the same, which we termed the switch time. Utilizing the more rapidly convergent solution at the appropriate time, we obtained rapid convergence at all times. We have also shown that one may simplify each of the three infinite series for the three-dimensional solution to 11 terms and still maintain a maximum relative error of less than 10-14.

Conditioning of Model Identification Task in Immune Inspired Optimizer SILO

NASA Astrophysics Data System (ADS)

Wojdan, K.; Swirski, K.; Warchol, M.; Maciorowski, M.

2009-10-01

Methods which provide good conditioning of model identification task in immune inspired, steady-state controller SILO (Stochastic Immune Layer Optimizer) are presented in this paper. These methods are implemented in a model based optimization algorithm. The first method uses a safe model to assure that gains of the process's model can be estimated. The second method is responsible for elimination of potential linear dependences between columns of observation matrix. Moreover new results from one of SILO implementation in polish power plant are presented. They confirm high efficiency of the presented solution in solving technical problems.

Reduction of mercury from mackerel fillet using combined solution of cysteine, EDTA, and sodium chloride.

PubMed

Hajeb, P; Jinap, S

2012-06-13

An acidic solution containing mercury chelating agents to eliminate mercury in raw fish (mackerel) fillet was developed. The solution contained hydrochloric acid, sodium hydroxide, cysteine, EDTA, and NaCl. The optimum conditions for mercury reduction were achieved using response surface methodology (RSM) at cysteine concentration of 1.25%, EDTA of 275 mg/L, NaCl of 0.5%, pH of 3.75, and exposure time of 18 min. The optimized conditions produced a solution which can remove up to 91% mercury from raw fish fillet. Cysteine and EDTA were identified as potential chelating agents with the greatest potential for use. The solution can be employed in fish industries to reduce mercury in highly contaminated fish.

Adsorption performance of mixed dyes on alkalization loofah fibers

NASA Astrophysics Data System (ADS)

Wang, Yongli; Liu, Jinyan; Li, Xingxing

2018-02-01

When the polyporous structures of loofah fiber is adequately exposed after alkali treatment,lignin, hemicellulose and pectin are removed. Specific surface area is increased to maximum, which means the efficiency of absorptivity is highest. In this paper, by using alkalization loofah (AL) as adsorbent, the effect of loofah fiber on waste water treatment is studied under the efficiency of loofah fiber which contain acridine yellow, methylene blue, mixed solution of the two dyes. The optimum treatment conditions of loofah fiber were studied from five aspects which include dosage, temperature, mixing time, pH and concentration. The results showed that the optimal conditions are 30°C, pH 8.0, 20mg dosage of loofah fiber in 40ml solution and mixing time 25min. The optimal treatment conditions of mixed dyes were studied from the aspects of mixing time, the dosage of AL and the molar ratio of the two components in the mixed dyes.

Optimization of Blended Wing Body Composite Panels Using Both NASTRAN and Genetic Algorithm

NASA Technical Reports Server (NTRS)

Lovejoy, Andrew E.

2006-01-01

The blended wing body (BWB) is a concept that has been investigated for improving the performance of transport aircraft. A trade study was conducted by evaluating four regions from a BWB design characterized by three fuselage bays and a 400,000 lb. gross take-off weight (GTW). This report describes the structural optimization of these regions via computational analysis and compares them to the baseline designs of the same construction. The identified regions were simplified for use in the optimization. The regions were represented by flat panels having appropriate classical boundary conditions and uniform force resultants along the panel edges. Panel-edge tractions and internal pressure values applied during the study were those determined by nonlinear NASTRAN analyses. Only one load case was considered in the optimization analysis for each panel region. Optimization was accomplished using both NASTRAN solution 200 and Genetic Algorithm (GA), with constraints imposed on stress, buckling, and minimum thicknesses. The NASTRAN optimization analyses often resulted in infeasible solutions due to violation of the constraints, whereas the GA enforced satisfaction of the constraints and, therefore, always ensured a feasible solution. However, both optimization methods encountered difficulties when the number of design variables was increased. In general, the optimized panels weighed less than the comparable baseline panels.

[Research on optimization of mathematical model of flow injection-hydride generation-atomic fluorescence spectrometry].

PubMed

Cui, Jian; Zhao, Xue-Hong; Wang, Yan; Xiao, Ya-Bing; Jiang, Xue-Hui; Dai, Li

2014-01-01

Flow injection-hydride generation-atomic fluorescence spectrometry was a widely used method in the industries of health, environmental, geological and metallurgical fields for the merit of high sensitivity, wide measurement range and fast analytical speed. However, optimization of this method was too difficult as there exist so many parameters affecting the sensitivity and broadening. Generally, the optimal conditions were sought through several experiments. The present paper proposed a mathematical model between the parameters and sensitivity/broadening coefficients using the law of conservation of mass according to the characteristics of hydride chemical reaction and the composition of the system, which was proved to be accurate as comparing the theoretical simulation and experimental results through the test of arsanilic acid standard solution. Finally, this paper has put a relation map between the parameters and sensitivity/broadening coefficients, and summarized that GLS volume, carrier solution flow rate and sample loop volume were the most factors affecting sensitivity and broadening coefficients. Optimizing these three factors with this relation map, the relative sensitivity was advanced by 2.9 times and relative broadening was reduced by 0.76 times. This model can provide a theoretical guidance for the optimization of the experimental conditions.

Multi objective genetic algorithm to optimize the local heat treatment of a hardenable aluminum alloy

NASA Astrophysics Data System (ADS)

Piccininni, A.; Palumbo, G.; Franco, A. Lo; Sorgente, D.; Tricarico, L.; Russello, G.

2018-05-01

The continuous research for lightweight components for transport applications to reduce the harmful emissions drives the attention to the light alloys as in the case of Aluminium (Al) alloys, capable to combine low density with high values of the strength-to-weight ratio. Such advantages are partially counterbalanced by the poor formability at room temperature. A viable solution is to adopt a localized heat treatment by laser of the blank before the forming process to obtain a tailored distribution of material properties so that the blank can be formed at room temperature by means of conventional press machines. Such an approach has been extensively investigated for age hardenable alloys, but in the present work the attention is focused on the 5000 series; in particular, the optimization of the deep drawing process of the alloy AA5754 H32 is proposed through a numerical/experimental approach. A preliminary investigation was necessary to correctly tune the laser parameters (focus length, spot dimension) to effectively obtain the annealed state. Optimal process parameters were then obtained coupling a 2D FE model with an optimization platform managed by a multi-objective genetic algorithm. The optimal solution (i.e. able to maximize the LDR) in terms of blankholder force and extent of the annealed region was thus evaluated and validated through experimental trials. A good matching between experimental and numerical results was found. The optimal solution allowed to obtain an LDR of the locally heat treated blank larger than the one of the material either in the wrought condition (H32) either in the annealed condition (H111).

Using Central Composite Experimental Design to Optimize the Degradation of Tylosin from Aqueous Solution by Photo-Fenton Reaction

PubMed Central

Sarrai, Abd Elaziz; Hanini, Salah; Merzouk, Nachida Kasbadji; Tassalit, Djilali; Szabó, Tibor; Hernádi, Klára; Nagy, László

2016-01-01

The feasibility of the application of the Photo-Fenton process in the treatment of aqueous solution contaminated by Tylosin antibiotic was evaluated. The Response Surface Methodology (RSM) based on Central Composite Design (CCD) was used to evaluate and optimize the effect of hydrogen peroxide, ferrous ion concentration and initial pH as independent variables on the total organic carbon (TOC) removal as the response function. The interaction effects and optimal parameters were obtained by using MODDE software. The significance of the independent variables and their interactions was tested by means of analysis of variance (ANOVA) with a 95% confidence level. Results show that the concentration of the ferrous ion and pH were the main parameters affecting TOC removal, while peroxide concentration had a slight effect on the reaction. The optimum operating conditions to achieve maximum TOC removal were determined. The model prediction for maximum TOC removal was compared to the experimental result at optimal operating conditions. A good agreement between the model prediction and experimental results confirms the soundness of the developed model. PMID:28773551

Application of multi-objective controller to optimal tuning of PID gains for a hydraulic turbine regulating system using adaptive grid particle swam optimization.

PubMed

Chen, Zhihuan; Yuan, Yanbin; Yuan, Xiaohui; Huang, Yuehua; Li, Xianshan; Li, Wenwu

2015-05-01

A hydraulic turbine regulating system (HTRS) is one of the most important components of hydropower plant, which plays a key role in maintaining safety, stability and economical operation of hydro-electrical installations. At present, the conventional PID controller is widely applied in the HTRS system for its practicability and robustness, and the primary problem with respect to this control law is how to optimally tune the parameters, i.e. the determination of PID controller gains for satisfactory performance. In this paper, a kind of multi-objective evolutionary algorithms, named adaptive grid particle swarm optimization (AGPSO) is applied to solve the PID gains tuning problem of the HTRS system. This newly AGPSO optimized method, which differs from a traditional one-single objective optimization method, is designed to take care of settling time and overshoot level simultaneously, in which a set of non-inferior alternatives solutions (i.e. Pareto solution) is generated. Furthermore, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto set. An illustrative example associated with the best compromise solution for parameter tuning of the nonlinear HTRS system is introduced to verify the feasibility and the effectiveness of the proposed AGPSO-based optimization approach, as compared with two another prominent multi-objective algorithms, i.e. Non-dominated Sorting Genetic Algorithm II (NSGAII) and Strength Pareto Evolutionary Algorithm II (SPEAII), for the quality and diversity of obtained Pareto solutions set. Consequently, simulation results show that this AGPSO optimized approach outperforms than compared methods with higher efficiency and better quality no matter whether the HTRS system works under unload or load conditions. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal conditions for peripheral nerve storage in green tea polyphenol: an experimental study in animals.

PubMed

Matsumoto, Taiichi; Kakinoki, Ryosuke; Ikeguchi, Ryosuke; Hyon, Suong-Hyu; Nakamura, Takashi

2005-06-30

Our previous study demonstrated successful peripheral nerve storage for 1 month using polyphenol solution. We here report two studies to solve residual problems in using polyphenols as a storage solution for peripheral nerves. Study 1 was designed to determine the optimal concentration of the polyphenol solution and the optimal immersion period for nerve storage. Rat sciatic nerve segments were immersed in polyphenol solution at three different concentrations (2.5, 1.0, and 0.5 mg/ml) for three different periods (1, 7, and 26 days). Electrophysiological and morphological studies demonstrated that nerve regeneration from nerve segments that had been immersed in 1mg/ml polyphenol solution for 1 week and in Dulbecco's modified Eagle's medium (DMEM) for the subsequent 3 weeks was superior to the regeneration in other treatment groups. In study 2, the permeability of nerve tissue to polyphenol solution was investigated using canine sciatic nerve segments stored in 1.0mg/ml polyphenol solution for 1 week and in DMEM for the subsequent 3 weeks. Electron microscopy revealed that the Schwann cell structure within 500-700 microm of the perineurium was preserved, but cells deeper than 500-700 microm were badly damaged or had disappeared. The infiltration limit for polyphenol solution into neural tissue is inferred to be 500-700 microm.

Optical solutions for unbundled access network

NASA Astrophysics Data System (ADS)

Bacîş Vasile, Irina Bristena

2015-02-01

The unbundling technique requires finding solutions to guarantee the economic and technical performances imposed by the nature of the services that can be offered. One of the possible solutions is the optic one; choosing this solution is justified for the following reasons: it optimizes the use of the access network, which is the most expensive part of a network (about 50% of the total investment in telecommunications networks) while also being the least used (telephone traffic on the lines has a low cost); it increases the distance between the master station/central and the terminal of the subscriber; the development of the services offered to the subscribers is conditioned by the subscriber network. For broadband services there is a need for support for the introduction of high-speed transport. A proper identification of the factors that must be satisfied and a comprehensive financial evaluation of all resources involved, both the resources that are in the process of being bought as well as extensions are the main conditions that would lead to a correct choice. As there is no single optimal technology for all development scenarios, which can take into account all access systems, a successful implementation is always done by individual/particularized scenarios. The method used today for the selection of an optimal solution is based on statistics and analysis of the various, already implemented, solutions, and on the experience that was already gained; the main evaluation criterion and the most unbiased one is the ratio between the cost of the investment and the quality of service, while serving an as large as possible number of customers.

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

Zhang, Yijian; Hong, Mingyi; Dall'Anese, Emiliano

This paper considers power distribution systems featuring renewable energy sources (RESs), and develops a distributed optimization method to steer the RES output powers to solutions of AC optimal power flow (OPF) problems. The design of the proposed method leverages suitable linear approximations of the AC-power flow equations, and is based on the Alternating Direction Method of Multipliers (ADMM). Convergence of the RES-inverter output powers to solutions of the OPF problem is established under suitable conditions on the stepsize as well as mismatches between the commanded setpoints and actual RES output powers. In a broad sense, the methods and results proposedmore » here are also applicable to other distributed optimization problem setups with ADMM and inexact dual updates.« less

OPTRAN- OPTIMAL LOW THRUST ORBIT TRANSFERS

NASA Technical Reports Server (NTRS)

Breakwell, J. V.

1994-01-01

OPTRAN is a collection of programs that solve the problem of optimal low thrust orbit transfers between non-coplanar circular orbits for spacecraft with chemical propulsion systems. The programs are set up to find Hohmann-type solutions, with burns near the perigee and apogee of the transfer orbit. They will solve both fairly long burn-arc transfers and "divided-burn" transfers. Program modeling includes a spherical earth gravity model and propulsion system models for either constant thrust or constant acceleration. The solutions obtained are optimal with respect to fuel use: i.e., final mass of the spacecraft is maximized with respect to the controls. The controls are the direction of thrust and the thrust on/off times. Two basic types of programs are provided in OPTRAN. The first type is for "exact solution" which results in complete, exact tkme-histories. The exact spacecraft position, velocity, and optimal thrust direction are given throughout the maneuver, as are the optimal thrust switch points, the transfer time, and the fuel costs. Exact solution programs are provided in two versions for non-coplanar transfers and in a fast version for coplanar transfers. The second basic type is for "approximate solutions" which results in approximate information on the transfer time and fuel costs. The approximate solution is used to estimate initial conditions for the exact solution. It can be used in divided-burn transfers to find the best number of burns with respect to time. The approximate solution is useful by itself in relatively efficient, short burn-arc transfers. These programs are written in FORTRAN 77 for batch execution and have been implemented on a DEC VAX series computer with the largest program having a central memory requirement of approximately 54K of 8 bit bytes. The OPTRAN program were developed in 1983.

Combined Homogeneous Surface Diffusion Model - Design of experiments approach to optimize dye adsorption considering both equilibrium and kinetic aspects.

PubMed

Muthukkumaran, A; Aravamudan, K

2017-12-15

Adsorption, a popular technique for removing azo dyes from aqueous streams, is influenced by several factors such as pH, initial dye concentration, temperature and adsorbent dosage. Any strategy that seeks to identify optimal conditions involving these factors, should take into account both kinetic and equilibrium aspects since they influence rate and extent of removal by adsorption. Hence rigorous kinetics and accurate equilibrium models are required. In this work, the experimental investigations pertaining to adsorption of acid orange 10 dye (AO10) on activated carbon were carried out using Central Composite Design (CCD) strategy. The significant factors that affected adsorption were identified to be solution temperature, solution pH, adsorbent dosage and initial solution concentration. Thermodynamic analysis showed the endothermic nature of the dye adsorption process. The kinetics of adsorption has been rigorously modeled using the Homogeneous Surface Diffusion Model (HSDM) after incorporating the non-linear Freundlich adsorption isotherm. Optimization was performed for kinetic parameters (color removal time and surface diffusion coefficient) as well as the equilibrium affected response viz. percentage removal. Finally, the optimum conditions predicted were experimentally validated. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Numerical Comparison of Barrier and Modified Barrier Methods for Large-Scale Bound-Constrained Optimization

NASA Technical Reports Server (NTRS)

Nash, Stephen G.; Polyak, R.; Sofer, Ariela

1994-01-01

When a classical barrier method is applied to the solution of a nonlinear programming problem with inequality constraints, the Hessian matrix of the barrier function becomes increasingly ill-conditioned as the solution is approached. As a result, it may be desirable to consider alternative numerical algorithms. We compare the performance of two methods motivated by barrier functions. The first is a stabilized form of the classical barrier method, where a numerically stable approximation to the Newton direction is used when the barrier parameter is small. The second is a modified barrier method where a barrier function is applied to a shifted form of the problem, and the resulting barrier terms are scaled by estimates of the optimal Lagrange multipliers. The condition number of the Hessian matrix of the resulting modified barrier function remains bounded as the solution to the constrained optimization problem is approached. Both of these techniques can be used in the context of a truncated-Newton method, and hence can be applied to large problems, as well as on parallel computers. In this paper, both techniques are applied to problems with bound constraints and we compare their practical behavior.

Topology optimization under stochastic stiffness

NASA Astrophysics Data System (ADS)

Asadpoure, Alireza

Topology optimization is a systematic computational tool for optimizing the layout of materials within a domain for engineering design problems. It allows variation of structural boundaries and connectivities. This freedom in the design space often enables discovery of new, high performance designs. However, solutions obtained by performing the optimization in a deterministic setting may be impractical or suboptimal when considering real-world engineering conditions with inherent variabilities including (for example) variabilities in fabrication processes and operating conditions. The aim of this work is to provide a computational methodology for topology optimization in the presence of uncertainties associated with structural stiffness, such as uncertain material properties and/or structural geometry. Existing methods for topology optimization under deterministic conditions are first reviewed. Modifications are then proposed to improve the numerical performance of the so-called Heaviside Projection Method (HPM) in continuum domains. Next, two approaches, perturbation and Polynomial Chaos Expansion (PCE), are proposed to account for uncertainties in the optimization procedure. These approaches are intrusive, allowing tight and efficient coupling of the uncertainty quantification with the optimization sensitivity analysis. The work herein develops a robust topology optimization framework aimed at reducing the sensitivity of optimized solutions to uncertainties. The perturbation-based approach combines deterministic topology optimization with a perturbation method for the quantification of uncertainties. The use of perturbation transforms the problem of topology optimization under uncertainty to an augmented deterministic topology optimization problem. The PCE approach combines the spectral stochastic approach for the representation and propagation of uncertainties with an existing deterministic topology optimization technique. The resulting compact representations for the response quantities allow for efficient and accurate calculation of sensitivities of response statistics with respect to the design variables. The proposed methods are shown to be successful at generating robust optimal topologies. Examples from topology optimization in continuum and discrete domains (truss structures) under uncertainty are presented. It is also shown that proposed methods lead to significant computational savings when compared to Monte Carlo-based optimization which involve multiple formations and inversions of the global stiffness matrix and that results obtained from the proposed method are in excellent agreement with those obtained from a Monte Carlo-based optimization algorithm.

Significance of the model considering mixed grain-size for inverse analysis of turbidites

NASA Astrophysics Data System (ADS)

Nakao, K.; Naruse, H.; Tokuhashi, S., Sr.

2016-12-01

A method for inverse analysis of turbidity currents is proposed for application to field observations. Estimation of initial condition of the catastrophic events from field observations has been important for sedimentological researches. For instance, there are various inverse analyses to estimate hydraulic conditions from topography observations of pyroclastic flows (Rossano et al., 1996), real-time monitored debris-flow events (Fraccarollo and Papa, 2000), tsunami deposits (Jaffe and Gelfenbaum, 2007) and ancient turbidites (Falcini et al., 2009). These inverse analyses need forward models and the most turbidity current models employ uniform grain-size particles. The turbidity currents, however, are the best characterized by variation of grain-size distribution. Though there are numerical models of mixed grain-sized particles, the models have difficulty in feasibility of application to natural examples because of calculating costs (Lesshaft et al., 2011). Here we expand the turbidity current model based on the non-steady 1D shallow-water equation at low calculation costs for mixed grain-size particles and applied the model to the inverse analysis. In this study, we compared two forward models considering uniform and mixed grain-size particles respectively. We adopted inverse analysis based on the Simplex method that optimizes the initial conditions (thickness, depth-averaged velocity and depth-averaged volumetric concentration of a turbidity current) with multi-point start and employed the result of the forward model [h: 2.0 m, U: 5.0 m/s, C: 0.01%] as reference data. The result shows that inverse analysis using the mixed grain-size model found the known initial condition of reference data even if the condition where the optimization started is deviated from the true solution, whereas the inverse analysis using the uniform grain-size model requires the condition in which the starting parameters for optimization must be in quite narrow range near the solution. The uniform grain-size model often reaches to local optimum condition that is significantly different from true solution. In conclusion, we propose a method of optimization based on the model considering mixed grain-size particles, and show its application to examples of turbidites in the Kiyosumi Formation, Boso Peninsula, Japan.

Zero-sum two-player game theoretic formulation of affine nonlinear discrete-time systems using neural networks.

PubMed

Mehraeen, Shahab; Dierks, Travis; Jagannathan, S; Crow, Mariesa L

2013-12-01

In this paper, the nearly optimal solution for discrete-time (DT) affine nonlinear control systems in the presence of partially unknown internal system dynamics and disturbances is considered. The approach is based on successive approximate solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which appears in optimal control. Successive approximation approach for updating control and disturbance inputs for DT nonlinear affine systems are proposed. Moreover, sufficient conditions for the convergence of the approximate HJI solution to the saddle point are derived, and an iterative approach to approximate the HJI equation using a neural network (NN) is presented. Then, the requirement of full knowledge of the internal dynamics of the nonlinear DT system is relaxed by using a second NN online approximator. The result is a closed-loop optimal NN controller via offline learning. A numerical example is provided illustrating the effectiveness of the approach.

A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour

NASA Technical Reports Server (NTRS)

Leyland, Jane Anne

1996-01-01

Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.

Optimal rendezvous in the neighborhood of a circular orbit

NASA Technical Reports Server (NTRS)

Jones, J. B.

1976-01-01

The minimum velocity-change rendezvous solutions, when the motion may be linearized about a circular orbit, fall into two separate regions; the phase-for-free region and the general region. Phase-for-free solutions are derived from the optimum transfer solutions, require the same velocity-change expenditure, but may not be unique. Analytic solutions are presented in two of the three subregions. An algorithm is presented for determining the unique solutions in the general region. Various sources of initial conditions are discussed and three examples are presented.

Nonconvex Sparse Logistic Regression With Weakly Convex Regularization

NASA Astrophysics Data System (ADS)

Shen, Xinyue; Gu, Yuantao

2018-06-01

In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the $\\ell_0$ pseudo norm is able to better induce sparsity than the commonly used $\\ell_1$ norm. For a class of weakly convex sparsity inducing functions, we prove the nonconvexity of the corresponding sparse logistic regression problem, and study its local optimality conditions and the choice of the regularization parameter to exclude trivial solutions. Despite the nonconvexity, a method based on proximal gradient descent is used to solve the general weakly convex sparse logistic regression, and its convergence behavior is studied theoretically. Then the general framework is applied to a specific weakly convex function, and a necessary and sufficient local optimality condition is provided. The solution method is instantiated in this case as an iterative firm-shrinkage algorithm, and its effectiveness is demonstrated in numerical experiments by both randomly generated and real datasets.

Pharmaceutical development and optimization of azithromycin suppository for paediatric use.

PubMed

Kauss, Tina; Gaubert, Alexandra; Boyer, Chantal; Ba, Boubakar B; Manse, Muriel; Massip, Stephane; Léger, Jean-Michel; Fawaz, Fawaz; Lembege, Martine; Boiron, Jean-Michel; Lafarge, Xavier; Lindegardh, Niklas; White, Nicholas J; Olliaro, Piero; Millet, Pascal; Gaudin, Karen

2013-01-30

Pharmaceutical development and manufacturing process optimization work was undertaken in order to propose a potential paediatric rectal formulation of azithromycin as an alternative to existing oral or injectable formulations. The target product profile was to be easy-to-use, cheap and stable in tropical conditions, with bioavailability comparable to oral forms, rapidly achieving and maintaining bactericidal concentrations. PEG solid solution suppositories were characterized in vitro using visual, HPLC, DSC, FTIR and XRD analyses. In vitro drug release and in vivo bioavailability were assessed; a study in rabbits compared the bioavailability of the optimized solid solution suppository to rectal solution and intra-venous product (as reference) and to the previous, non-optimized formulation (suspended azithromycin suppository). The bioavailability of azithromycin administered as solid solution suppositories relative to intra-venous was 43%, which compared well to the target of 38% (oral product in humans). The results of 3-month preliminary stability and feasibility studies were consistent with industrial production scale-up. This product has potential both as a classical antibiotic and as a product for use in severely ill children in rural areas. Industrial partners for further development are being sought. Copyright © 2012 Elsevier B.V. All rights reserved.

Pharmaceutical development and optimization of azithromycin suppository for paediatric use

PubMed Central

Kauss, Tina; Gaubert, Alexandra; Boyer, Chantal; Ba, Boubakar B.; Manse, Muriel; Massip, Stephane; Léger, Jean-Michel; Fawaz, Fawaz; Lembege, Martine; Boiron, Jean-Michel; Lafarge, Xavier; Lindegardh, Niklas; White, Nicholas J.; Olliaro, Piero; Millet, Pascal; Gaudin, Karen

2013-01-01

Pharmaceutical development and manufacturing process optimization work was undertaken in order to propose a potential paediatric rectal formulation of azithromycin as an alternative to existing oral or injectable formulations. The target product profile was to be easy-to-use, cheap and stable in tropical conditions, with bioavailability comparable to oral forms, rapidly achieving and maintaining bactericidal concentrations. PEG solid solution suppositories were characterized in vitro using visual, HPLC, DSC, FTIR and XRD analyses. In vitro drug release and in vivo bioavailability were assessed; a study in rabbits compared the bioavailability of the optimized solid solution suppository to rectal solution and intra-venous product (as reference) and to the previous, non-optimized formulation (suspended azithromycin suppository). The bioavailability of azithromycin administered as solid solution suppositories relative to intra-venous was 43%, which compared well to the target of 38% (oral product in humans). The results of 3-month preliminary stability and feasibility studies were consistent with industrial production scale-up. This product has potential both as a classical antibiotic and as a product for use in severely ill children in rural areas. Industrial partners for further development are being sought. PMID:23220079

A comparison of dynamic and static economic models of uneven-aged stand management

Treesearch

Robert G. Haight

1985-01-01

Numerical techniques have been used to compute the discrete-time sequence of residual diameter distributions that maximize the present net worth (PNW) of harvestable volume from an uneven-aged stand. Results contradicted optimal steady-state diameter distributions determined with static analysis. In this paper, optimality conditions for solutions to dynamic and static...

Multi-objective dynamic aperture optimization for storage rings

DOE PAGES

Li, Yongjun; Yang, Lingyun

2016-11-30

We report an efficient dynamic aperture (DA) optimization approach using multiobjective genetic algorithm (MOGA), which is driven by nonlinear driving terms computation. It was found that having small low order driving terms is a necessary but insufficient condition of having a decent DA. Then direct DA tracking simulation is implemented among the last generation candidates to select the best solutions. The approach was demonstrated successfully in optimizing NSLS-II storage ring DA.

Influence of pH, temperature, and concentration on stabilization of aqueous hornet silk solution and fabrication of salt-free materials.

PubMed

Kameda, Tsunenori

2015-01-01

We found that an aqueous solution of silk from cocoons produced by hornet larvae (hornet silk) can be obtained when the solution is adjusted to basic conditions of pH > 9.2. It is known that native hornet cocoons can be dissolved in concentrated aqueous solution of salts, such as lithium bromide (LiBr) and calcium chloride (CaCl2). Upon the removal of these salts from solution by dialysis, solidification, gelation, or sedimentation of hornet silk is known to occur. In the present study, under basic conditions, however, no such solidification occurred, even after salt removal. In this study, ammonia was used for alkalization of solution because it is volatilized during the casting process and pure hornet silk materials can be obtained after drying. The effects of the concentrations of hornet silk and ammonia, as well as dialysis temperature, on preventing gelation during dialysis were investigated. Dialysis conditions that limit the degradation of hornet silk by hydrolysis in alkali solution were identified. Moreover, casting conditions to prepare flexible and transparent hornet silk film from aqueous ammonia solution were optimized. Molecular structural analysis of hornet silk in aqueous ammonia solution and cast film indicated the formation of α-helix conformations. © 2014 Wiley Periodicals, Inc.

The Effect of Temperature and Solution pH on the Nucleation of Tetragonal Lysozyme Crystals

NASA Technical Reports Server (NTRS)

Judge, Russell A.; Jacobs, Randolph S.; Frazier, Tyralynn; Snell, Edward H.; Pusey, Marc L.

1999-01-01

Part of the challenge of macromolecular crystal growth for structure determination is obtaining crystals with a volume suitable for x-ray analysis. In this respect an understanding of the effect of solution conditions on macromolecule nucleation rates is advantageous. This study investigated the effects of supersaturation, temperature, and pH on the nucleation rate of tetragonal lysozyme crystals. Batch crystallization plates were prepared at given solution concentrations and incubated at set temperatures over 1 week. The number of crystals per well with their size and axial ratios were recorded and correlated with solution conditions. Crystal numbers were found to increase with increasing supersaturation and temperature. The most significant variable, however, was pH; crystal numbers changed by two orders of magnitude over the pH range 4.0-5.2. Crystal size also varied with solution conditions, with the largest crystals obtained at pH 5.2. Having optimized the crystallization conditions, we prepared a batch of crystals under the same initial conditions, and 50 of these crystals were analyzed by x-ray diffraction techniques. The results indicate that even under the same crystallization conditions, a marked variation in crystal properties exists.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE PAGES

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

2017-04-17

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

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

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Statistical efficiency of adaptive algorithms.

PubMed

Widrow, Bernard; Kamenetsky, Max

2003-01-01

The statistical efficiency of a learning algorithm applied to the adaptation of a given set of variable weights is defined as the ratio of the quality of the converged solution to the amount of data used in training the weights. Statistical efficiency is computed by averaging over an ensemble of learning experiences. A high quality solution is very close to optimal, while a low quality solution corresponds to noisy weights and less than optimal performance. In this work, two gradient descent adaptive algorithms are compared, the LMS algorithm and the LMS/Newton algorithm. LMS is simple and practical, and is used in many applications worldwide. LMS/Newton is based on Newton's method and the LMS algorithm. LMS/Newton is optimal in the least squares sense. It maximizes the quality of its adaptive solution while minimizing the use of training data. Many least squares adaptive algorithms have been devised over the years, but no other least squares algorithm can give better performance, on average, than LMS/Newton. LMS is easily implemented, but LMS/Newton, although of great mathematical interest, cannot be implemented in most practical applications. Because of its optimality, LMS/Newton serves as a benchmark for all least squares adaptive algorithms. The performances of LMS and LMS/Newton are compared, and it is found that under many circumstances, both algorithms provide equal performance. For example, when both algorithms are tested with statistically nonstationary input signals, their average performances are equal. When adapting with stationary input signals and with random initial conditions, their respective learning times are on average equal. However, under worst-case initial conditions, the learning time of LMS can be much greater than that of LMS/Newton, and this is the principal disadvantage of the LMS algorithm. But the strong points of LMS are ease of implementation and optimal performance under important practical conditions. For these reasons, the LMS algorithm has enjoyed very widespread application. It is used in almost every modem for channel equalization and echo cancelling. Furthermore, it is related to the famous backpropagation algorithm used for training neural networks.

Efficient control schemes with limited computation complexity for Tomographic AO systems on VLTs and ELTs

NASA Astrophysics Data System (ADS)

Petit, C.; Le Louarn, M.; Fusco, T.; Madec, P.-Y.

2011-09-01

Various tomographic control solutions have been proposed during the last decades to ensure efficient or even optimal closed-loop correction to tomographic Adaptive Optics (AO) concepts such as Laser Tomographic AO (LTAO), Multi-Conjugate AO (MCAO). The optimal solution, based on Linear Quadratic Gaussian (LQG) approach, as well as suboptimal but efficient solutions such as Pseudo-Open Loop Control (POLC) require multiple Matrix Vector Multiplications (MVM). Disregarding their respective performance, these efficient control solutions thus exhibit strong increase of on-line complexity and their implementation may become difficult in demanding cases. Among them, two cases are of particular interest. First, the system Real-Time Computer architecture and implementation is derived from past or present solutions and does not support multiple MVM. This is the case of the AO Facility which RTC architecture is derived from the SPARTA platform and inherits its simple MVM architecture, which does not fit with LTAO control solutions for instance. Second, considering future systems such as Extremely Large Telescopes, the number of degrees of freedom is twenty to one hundred times bigger than present systems. In these conditions, tomographic control solutions can hardly be used in their standard form and optimized implementation shall be considered. Single MVM tomographic control solutions represent a potential solution, and straightforward solutions such as Virtual Deformable Mirrors have been already proposed for LTAO but with tuning issues. We investigate in this paper the possibility to derive from tomographic control solutions, such as POLC or LQG, simplified control solutions ensuring simple MVM architecture and that could be thus implemented on nowadays systems or future complex systems. We theoretically derive various solutions and analyze their respective performance on various systems thanks to numerical simulation. We discuss the optimization of their performance and stability issues with respect to classic control solutions. We finally discuss off-line computation and implementation constraints.

Stochastic Optimal Prediction with Application to Averaged Euler Equations

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

Bell, John; Chorin, Alexandre J.; Crutchfield, William

Optimal prediction (OP) methods compensate for a lack of resolution in the numerical solution of complex problems through the use of an invariant measure as a prior measure in the Bayesian sense. In first-order OP, unresolved information is approximated by its conditional expectation with respect to the invariant measure. In higher-order OP, unresolved information is approximated by a stochastic estimator, leading to a system of random or stochastic differential equations. We explain the ideas through a simple example, and then apply them to the solution of Averaged Euler equations in two space dimensions.

The optimal modified variational iteration method for the Lane-Emden equations with Neumann and Robin boundary conditions

NASA Astrophysics Data System (ADS)

Singh, Randhir; Das, Nilima; Kumar, Jitendra

2017-06-01

An effective analytical technique is proposed for the solution of the Lane-Emden equations. The proposed technique is based on the variational iteration method (VIM) and the convergence control parameter h . In order to avoid solving a sequence of nonlinear algebraic or complicated integrals for the derivation of unknown constant, the boundary conditions are used before designing the recursive scheme for solution. The series solutions are found which converges rapidly to the exact solution. Convergence analysis and error bounds are discussed. Accuracy, applicability of the method is examined by solving three singular problems: i) nonlinear Poisson-Boltzmann equation, ii) distribution of heat sources in the human head, iii) second-kind Lane-Emden equation.

Rotorcraft Diagnostics

NASA Technical Reports Server (NTRS)

Haste, Deepak; Azam, Mohammad; Ghoshal, Sudipto; Monte, James

2012-01-01

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Optimal flow conditions of a tracheobronchial model to reengineer lung structures

NASA Astrophysics Data System (ADS)

Casarin, Stefano; Aletti, Federico; Baselli, Giuseppe; Garbey, Marc

2017-04-01

The high demand for lung transplants cannot be matched by an adequate number of lungs from donors. Since fully ex-novo lungs are far from being feasible, tissue engineering is actively considering implantation of engineered lungs where the devitalized structure of a donor is used as scaffold to be repopulated by stem cells of the receiving patient. A decellularized donated lung is treated inside a bioreactor where transport through the tracheobronchial tree (TBT) will allow for both deposition of stem cells and nourishment for their subsequent growth, thus developing new lung tissue. The key concern is to set optimally the boundary conditions to utilize in the bioreactor. We propose a predictive model of slow liquid ventilation, which combines a one-dimensional (1-D) mathematical model of the TBT and a solute deposition model strongly dependent on fluid velocity across the tree. With it, we were able to track and drive the concentration of a generic solute across the airways, looking for its optimal distribution. This was given by properly adjusting the pumps' regime serving the bioreactor. A feedback system, created by coupling the two models, allowed us to derive the optimal pattern. The TBT model can be easily invertible, thus yielding a straightforward flow/pressure law at the inlet to optimize the efficiency of the bioreactor.

A novel membrane-based process to isolate peroxidase from horseradish roots: optimization of operating parameters.

PubMed

Liu, Jianguo; Yang, Bo; Chen, Changzhen

2013-02-01

The optimization of operating parameters for the isolation of peroxidase from horseradish (Armoracia rusticana) roots with ultrafiltration (UF) technology was systemically studied. The effects of UF operating conditions on the transmission of proteins were quantified using the parameter scanning UF. These conditions included solution pH, ionic strength, stirring speed and permeate flux. Under optimized conditions, the purity of horseradish peroxidase (HRP) obtained was greater than 84 % after a two-stage UF process and the recovery of HRP from the feedstock was close to 90 %. The resulting peroxidase product was then analysed by isoelectric focusing, SDS-PAGE and circular dichroism, to confirm its isoelectric point, molecular weight and molecular secondary structure. The effects of calcium ion on HRP specific activities were also experimentally determined.

Optimal startup control of a jacketed tubular reactor.

NASA Technical Reports Server (NTRS)

Hahn, D. R.; Fan, L. T.; Hwang, C. L.

1971-01-01

The optimal startup policy of a jacketed tubular reactor, in which a first-order, reversible, exothermic reaction takes place, is presented. A distributed maximum principle is presented for determining weak necessary conditions for optimality of a diffusional distributed parameter system. A numerical technique is developed for practical implementation of the distributed maximum principle. This involves the sequential solution of the state and adjoint equations, in conjunction with a functional gradient technique for iteratively improving the control function.

Optimal starting conditions for the rendezvous maneuver: Analytical and computational approach

NASA Astrophysics Data System (ADS)

Ciarcia, Marco

The three-dimensional rendezvous between two spacecraft is considered: a target spacecraft on a circular orbit around the Earth and a chaser spacecraft initially on some elliptical orbit yet to be determined. The chaser spacecraft has variable mass, limited thrust, and its trajectory is governed by three controls, one determining the thrust magnitude and two determining the thrust direction. We seek the time history of the controls in such a way that the propellant mass required to execute the rendezvous maneuver is minimized. Two cases are considered: (i) time-to-rendezvous free and (ii) time-to-rendezvous given, respectively equivalent to (i) free angular travel and (ii) fixed angular travel for the target spacecraft. The above problem has been studied by several authors under the assumption that the initial separation coordinates and the initial separation velocities are given, hence known initial conditions for the chaser spacecraft. In this paper, it is assumed that both the initial separation coordinates and initial separation velocities are free except for the requirement that the initial chaser-to-target distance is given so as to prevent the occurrence of trivial solutions. Two approaches are employed: optimal control formulation (Part A) and mathematical programming formulation (Part B). In Part A, analyses are performed with the multiple-subarc sequential gradient-restoration algorithm for optimal control problems. They show that the fuel-optimal trajectory is zero-bang, namely it is characterized by two subarcs: a long coasting zero-thrust subarc followed by a short powered max-thrust braking subarc. While the thrust direction of the powered subarc is continuously variable for the optimal trajectory, its replacement with a constant (yet optimized) thrust direction produces a very efficient guidance trajectory. Indeed, for all values of the initial distance, the fuel required by the guidance trajectory is within less than one percent of the fuel required by the optimal trajectory. For the guidance trajectory, because of the replacement of the variable thrust direction of the powered subarc with a constant thrust direction, the optimal control problem degenerates into a mathematical programming problem with a relatively small number of degrees of freedom, more precisely: three for case (i) time-to-rendezvous free and two for case (ii) time-to-rendezvous given. In particular, we consider the rendezvous between the Space Shuttle (chaser) and the International Space Station (target). Once a given initial distance SS-to-ISS is preselected, the present work supplies not only the best initial conditions for the rendezvous trajectory, but simultaneously the corresponding final conditions for the ascent trajectory. In Part B, an analytical solution of the Clohessy-Wiltshire equations is presented (i) neglecting the change of the spacecraft mass due to the fuel consumption and (ii) and assuming that the thrust is finite, that is, the trajectory includes powered subarcs flown with max thrust and coasting subarc flown with zero thrust. Then, employing the found analytical solution, we study the rendezvous problem under the assumption that the initial separation coordinates and initial separation velocities are free except for the requirement that the initial chaser-to-target distance is given. The main contribution of Part B is the development of analytical solutions for the powered subarcs, an important extension of the analytical solutions already available for the coasting subarcs. One consequence is that the entire optimal trajectory can be described analytically. Another consequence is that the optimal control problems degenerate into mathematical programming problems. A further consequence is that, vis-a-vis the optimal control formulation, the mathematical programming formulation reduces the CPU time by a factor of order 1000. Key words. Space trajectories, rendezvous, optimization, guidance, optimal control, calculus of variations, Mayer problems, Bolza problems, transformation techniques, multiple-subarc sequential gradient-restoration algorithm.

A sequential solution for anisotropic total variation image denoising with interval constraints

NASA Astrophysics Data System (ADS)

Xu, Jingyan; Noo, Frédéric

2017-09-01

We show that two problems involving the anisotropic total variation (TV) and interval constraints on the unknown variables admit, under some conditions, a simple sequential solution. Problem 1 is a constrained TV penalized image denoising problem; problem 2 is a constrained fused lasso signal approximator. The sequential solution entails finding first the solution to the unconstrained problem, and then applying a thresholding to satisfy the constraints. If the interval constraints are uniform, this sequential solution solves problem 1. If the interval constraints furthermore contain zero, the sequential solution solves problem 2. Here uniform interval constraints refer to all unknowns being constrained to the same interval. A typical example of application is image denoising in x-ray CT, where the image intensities are non-negative as they physically represent linear attenuation coefficient in the patient body. Our results are simple yet seem unknown; we establish them using the Karush-Kuhn-Tucker conditions for constrained convex optimization.

A Simple Method for Amplifying RNA Targets (SMART)

PubMed Central

McCalla, Stephanie E.; Ong, Carmichael; Sarma, Aartik; Opal, Steven M.; Artenstein, Andrew W.; Tripathi, Anubhav

2012-01-01

We present a novel and simple method for amplifying RNA targets (named by its acronym, SMART), and for detection, using engineered amplification probes that overcome existing limitations of current RNA-based technologies. This system amplifies and detects optimal engineered ssDNA probes that hybridize to target RNA. The amplifiable probe-target RNA complex is captured on magnetic beads using a sequence-specific capture probe and is separated from unbound probe using a novel microfluidic technique. Hybridization sequences are not constrained as they are in conventional target-amplification reactions such as nucleic acid sequence amplification (NASBA). Our engineered ssDNA probe was amplified both off-chip and in a microchip reservoir at the end of the separation microchannel using isothermal NASBA. Optimal solution conditions for ssDNA amplification were investigated. Although KCl and MgCl2 are typically found in NASBA reactions, replacing 70 mmol/L of the 82 mmol/L total chloride ions with acetate resulted in optimal reaction conditions, particularly for low but clinically relevant probe concentrations (≤100 fmol/L). With the optimal probe design and solution conditions, we also successfully removed the initial heating step of NASBA, thus achieving a true isothermal reaction. The SMART assay using a synthetic model influenza DNA target sequence served as a fundamental demonstration of the efficacy of the capture and microfluidic separation system, thus bridging our system to a clinically relevant detection problem. PMID:22691910

Improving knowledge of garlic paste greening through the design of an experimental strategy.

PubMed

Aguilar, Miguel; Rincón, Francisco

2007-12-12

The furthering of scientific knowledge depends in part upon the reproducibility of experimental results. When experimental conditions are not set with sufficient precision, the resulting background noise often leads to poorly reproduced and even faulty experiments. An example of the catastrophic consequences of this background noise can be found in the design of strategies for the development of solutions aimed at preventing garlic paste greening, where reported results are contradictory. To avoid such consequences, this paper presents a two-step strategy based on the concept of experimental design. In the first step, the critical factors inherent to the problem are identified, using a 2(III)(7-4) Plackett-Burman experimental design, from a list of seven apparent critical factors (ACF); subsequently, the critical factors thus identified are considered as the factors to be optimized (FO), and optimization is performed using a Box and Wilson experimental design to identify the stationary point of the system. Optimal conditions for preventing garlic greening are examined after analysis of the complex process of green-pigment development, which involves both chemical and enzymatic reactions and is strongly influenced by pH, with an overall pH optimum of 4.5. The critical step in the greening process is the synthesis of thiosulfinates (allicin) from cysteine sulfoxides (alliin). Cysteine inhibits the greening process at this critical stage; no greening precursors are formed in the presence of around 1% cysteine. However, the optimal conditions for greening prevention are very sensitive both to the type of garlic and to manufacturing conditions. This suggests that optimal solutions for garlic greening prevention should be sought on a case-by-case basis, using the strategy presented here.

Algorithms for bilevel optimization

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Dennis, J. E., Jr.

1994-01-01

General multilevel nonlinear optimization problems arise in design of complex systems and can be used as a means of regularization for multi-criteria optimization problems. Here, for clarity in displaying our ideas, we restrict ourselves to general bi-level optimization problems, and we present two solution approaches. Both approaches use a trust-region globalization strategy, and they can be easily extended to handle the general multilevel problem. We make no convexity assumptions, but we do assume that the problem has a nondegenerate feasible set. We consider necessary optimality conditions for the bi-level problem formulations and discuss results that can be extended to obtain multilevel optimization formulations with constraints at each level.

Finite-Dimensional Representations for Controlled Diffusions with Delay

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

Federico, Salvatore, E-mail: salvatore.federico@unimi.it; Tankov, Peter, E-mail: tankov@math.univ-paris-diderot.fr

2015-02-15

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which the solution of the SDDE and a linear path functional of it admit a finite-dimensional Markovian representation. As a second contribution, we show how approximate finite-dimensional Markovian representations may be constructed when these conditions are not satisfied, and provide an estimate of the error corresponding to these approximations. These results are applied to optimal control and optimal stopping problems for stochastic systems with delay.

Electro-driven extraction of polar compounds using agarose gel as a new membrane: Determination of amino acids in fruit juice and human plasma samples.

PubMed

Sedehi, Samira; Tabani, Hadi; Nojavan, Saeed

2018-03-01

In this work, polypropylene hollow fiber was replaced by agarose gel in conventional electro membrane extraction (EME) to develop a novel approach. The proposed EME method was then employed to extract two amino acids (tyrosine and phenylalanine) as model polar analytes, followed by HPLC-UV. The method showed acceptable results under optimized conditions. This green methodology outperformed conventional EME, and required neither organic solvents nor carriers. The effective parameters such as the pH values of the acceptor and the donor solutions, the thickness and pH of the gel, the extraction voltage, the stirring rate, and the extraction time were optimized. Under the optimized conditions (acceptor solution pH: 1.5; donor solution pH: 2.5; agarose gel thickness: 7mm; agarose gel pH: 1.5; stirring rate of the sample solution: 1000rpm; extraction potential: 40V; and extraction time: 15min), the limits of detection and quantification were 7.5ngmL -1 and 25ngmL -1 , respectively. The extraction recoveries were between 56.6% and 85.0%, and the calibration curves were linear with correlation coefficients above 0.996 over a concentration range of 25.0-1000.0ngmL -1 for both amino acids. The intra- and inter-day precisions were in the range of 5.5-12.5%, and relative errors were smaller than 12.0%. Finally, the optimized method was successfully applied to preconcentrate, clean up, and quantify amino acids in watermelon and grapefruit juices as well as a plasma sample, and acceptable relative recoveries in the range of 53.9-84.0% were obtained. Copyright © 2017 Elsevier B.V. All rights reserved.

The quasi-optimality criterion in the linear functional strategy

NASA Astrophysics Data System (ADS)

Kindermann, Stefan; Pereverzyev, Sergiy, Jr.; Pilipenko, Andrey

2018-07-01

The linear functional strategy for the regularization of inverse problems is considered. For selecting the regularization parameter therein, we propose the heuristic quasi-optimality principle and some modifications including the smoothness of the linear functionals. We prove convergence rates for the linear functional strategy with these heuristic rules taking into account the smoothness of the solution and the functionals and imposing a structural condition on the noise. Furthermore, we study these noise conditions in both a deterministic and stochastic setup and verify that for mildly-ill-posed problems and Gaussian noise, these conditions are satisfied almost surely, where on the contrary, in the severely-ill-posed case and in a similar setup, the corresponding noise condition fails to hold. Moreover, we propose an aggregation method for adaptively optimizing the parameter choice rule by making use of improved rates for linear functionals. Numerical results indicate that this method yields better results than the standard heuristic rule.

Modeling and multi-response optimization of pervaporation of organic aqueous solutions using desirability function approach.

PubMed

Cojocaru, C; Khayet, M; Zakrzewska-Trznadel, G; Jaworska, A

2009-08-15

The factorial design of experiments and desirability function approach has been applied for multi-response optimization in pervaporation separation process. Two organic aqueous solutions were considered as model mixtures, water/acetonitrile and water/ethanol mixtures. Two responses have been employed in multi-response optimization of pervaporation, total permeate flux and organic selectivity. The effects of three experimental factors (feed temperature, initial concentration of organic compound in feed solution, and downstream pressure) on the pervaporation responses have been investigated. The experiments were performed according to a 2(3) full factorial experimental design. The factorial models have been obtained from experimental design and validated statistically by analysis of variance (ANOVA). The spatial representations of the response functions were drawn together with the corresponding contour line plots. Factorial models have been used to develop the overall desirability function. In addition, the overlap contour plots were presented to identify the desirability zone and to determine the optimum point. The optimal operating conditions were found to be, in the case of water/acetonitrile mixture, a feed temperature of 55 degrees C, an initial concentration of 6.58% and a downstream pressure of 13.99 kPa, while for water/ethanol mixture a feed temperature of 55 degrees C, an initial concentration of 4.53% and a downstream pressure of 9.57 kPa. Under such optimum conditions it was observed experimentally an improvement of both the total permeate flux and selectivity.

Sequential quadratic programming-based fast path planning algorithm subject to no-fly zone constraints

NASA Astrophysics Data System (ADS)

Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang

2016-08-01

Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.

Transient Thermoelectric Solution Employing Green's Functions

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

The study works to formulate convenient solutions to the problem of a thermoelectric couple operating under a time varying condition. Transient operation of a thermoelectric will become increasingly common as thermoelectric technology permits applications in an increasing number of uses. A number of terrestrial applications, in contrast to steady-state space applications, can subject devices to time varying conditions. For instance thermoelectrics can be exposed to transient conditions in the automotive industry depending on engine system dynamics along with factors like driving style. In an effort to generalize the thermoelectric solution a Greens function method is used, so that arbitrary time varying boundary and initial conditions may be applied to the system without reformulation. The solution demonstrates that in thermoelectric applications of a transient nature additional factors must be taken into account and optimized. For instance, the materials specific heat and density become critical parameters in addition to the thermal mass of a heat sink or the details of the thermal profile, such as oscillating frequency. The calculations can yield the optimum operating conditions to maximize power output andor efficiency for a given type of device.

Salt controls feeding decisions in a blood-sucking insect.

PubMed

Pontes, Gina; Pereira, Marcos H; Barrozo, Romina B

2017-04-01

Salts are necessary for maintaining homeostatic conditions within the body of all living organisms. Like with all essential nutrients, deficient or excessive ingestion of salts can result in adverse health effects. The taste system is a primary sensory modality that helps animals to make adequate feeding decisions in terms of salt consumption. In this work we show that sodium and potassium chloride salts modulate the feeding behavior of Rhodnius prolixus in a concentration-dependent manner. Feeding is only triggered by an optimal concentration of any of these salts (0.1-0.15M) and in presence of the phagostimulant ATP. Conversely, feeding solutions that do not contain salts or have a high-salt concentration (>0.3M) are not ingested by insects. Notably, we show that feeding decisions of insects cannot be explained as an osmotic effect, because they still feed over hyperosmotic solutions bearing the optimal salt concentration. Insects perceive optimal-salt, no-salt and high-salt solutions as different gustatory information, as revealed the electromyogram recordings of the cibarial pump. Moreover, because insects do a continuous gustatory monitoring of the incoming food during feeding, sudden changes beyond the optimal sodium concentration decrease and even inhibit feeding. The administration of amiloride, a sodium channel blocker, noticeably reduces the ingestion of the optimal sodium solution but not of the optimal potassium solution. Salt detection seems to occur at least through two salt receptors, one amiloride-sensitive and another amiloride-insensitive. Our results confirm the importance of the gustatory system in R. prolixus, showing the relevant role that salts play on their feeding decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neuroperformance Imaging

DTIC Science & Technology

2014-10-01

computes such as magneto - and electrophysiology. Should additional funded become available, we will explore the effects of sleep quality on...neural stress that could inform not only optimal sleep durations and therapies under acute stress conditions, but therapeutic solutions to warfighters

The promise of macromolecular crystallization in microfluidic chips

NASA Technical Reports Server (NTRS)

van der Woerd, Mark; Ferree, Darren; Pusey, Marc

2003-01-01

Microfluidics, or lab-on-a-chip technology, is proving to be a powerful, rapid, and efficient approach to a wide variety of bioanalytical and microscale biopreparative needs. The low materials consumption, combined with the potential for packing a large number of experiments in a few cubic centimeters, makes it an attractive technique for both initial screening and subsequent optimization of macromolecular crystallization conditions. Screening operations, which require a macromolecule solution with a standard set of premixed solutions, are relatively straightforward and have been successfully demonstrated in a microfluidics platform. Optimization methods, in which crystallization solutions are independently formulated from a range of stock solutions, are considerably more complex and have yet to be demonstrated. To be competitive with either approach, a microfluidics system must offer ease of operation, be able to maintain a sealed environment over several weeks to months, and give ready access for the observation and harvesting of crystals as they are grown.

A Singular Differential Equation Stemming from an Optimal Control Problem in Financial Economics

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

Brunovsky, Pavol, E-mail: brunovsky@fmph.uniba.sk; Cerny, Ales, E-mail: ales.cerny.1@city.ac.uk; Winkler, Michael, E-mail: michael.winkler@uni-due.de

2013-10-15

We consider the ordinary differential equation x{sup 2} u'' = axu'+bu-c(u'-1){sup 2}, x Element-Of (0,x{sub 0}), with a Element-Of R, b Element-Of R , c>0 and the singular initial condition u(0)=0, which in financial economics describes optimal disposal of an asset in a market with liquidity effects. It is shown in the paper that if a+b<0 then no continuous solutions exist, whereas if a+b>0 then there are infinitely many continuous solutions with indistinguishable asymptotics near 0. Moreover, it is proved that in the latter case there is precisely one solution u corresponding to the choice x{sub 0}={infinity} which is suchmore » that 0{<=}u(x){<=}x for all x>0, and that this solution is strictly increasing and concave.« less

Solution-mediated cladding doping of commercial polymer optical fibers

NASA Astrophysics Data System (ADS)

Stajanca, Pavol; Topolniak, Ievgeniia; Pötschke, Samuel; Krebber, Katerina

2018-03-01

Solution doping of commercial polymethyl methacrylate (PMMA) polymer optical fibers (POFs) is presented as a novel approach for preparation of custom cladding-doped POFs (CD-POFs). The presented method is based on a solution-mediated diffusion of dopant molecules into the fiber cladding upon soaking of POFs in a methanol-dopant solution. The method was tested on three different commercial POFs using Rhodamine B as a fluorescent dopant. The dynamics of the diffusion process was studied in order to optimize the doping procedure in terms of selection of the most suitable POF, doping time and conditions. Using the optimized procedure, longer segment of fluorescent CD-POF was prepared and its performance was characterized. Fiber's potential for sensing and illumination applications was demonstrated and discussed. The proposed method represents a simple and cheap way for fabrication of custom, short to medium length CD-POFs with various dopants.

The use of methods of structural optimization at the stage of designing high-rise buildings with steel construction

NASA Astrophysics Data System (ADS)

Vasilkin, Andrey

2018-03-01

The more designing solutions at the search stage for design for high-rise buildings can be synthesized by the engineer, the more likely that the final adopted version will be the most efficient and economical. However, in modern market conditions, taking into account the complexity and responsibility of high-rise buildings the designer does not have the necessary time to develop, analyze and compare any significant number of options. To solve this problem, it is expedient to use the high potential of computer-aided designing. To implement automated search for design solutions, it is proposed to develop the computing facilities, the application of which will significantly increase the productivity of the designer and reduce the complexity of designing. Methods of structural and parametric optimization have been adopted as the basis of the computing facilities. Their efficiency in the synthesis of design solutions is shown, also the schemes, that illustrate and explain the introduction of structural optimization in the traditional design of steel frames, are constructed. To solve the problem of synthesis and comparison of design solutions for steel frames, it is proposed to develop the computing facilities that significantly reduces the complexity of search designing and based on the use of methods of structural and parametric optimization.

Particle swarm optimization of ascent trajectories of multistage launch vehicles

NASA Astrophysics Data System (ADS)

Pontani, Mauro

2014-02-01

Multistage launch vehicles are commonly employed to place spacecraft and satellites in their operational orbits. If the rocket characteristics are specified, the optimization of its ascending trajectory consists of determining the optimal control law that leads to maximizing the final mass at orbit injection. The numerical solution of a similar problem is not trivial and has been pursued with different methods, for decades. This paper is concerned with an original approach based on the joint use of swarming theory and the necessary conditions for optimality. The particle swarm optimization technique represents a heuristic population-based optimization method inspired by the natural motion of bird flocks. Each individual (or particle) that composes the swarm corresponds to a solution of the problem and is associated with a position and a velocity vector. The formula for velocity updating is the core of the method and is composed of three terms with stochastic weights. As a result, the population migrates toward different regions of the search space taking advantage of the mechanism of information sharing that affects the overall swarm dynamics. At the end of the process the best particle is selected and corresponds to the optimal solution to the problem of interest. In this work the three-dimensional trajectory of the multistage rocket is assumed to be composed of four arcs: (i) first stage propulsion, (ii) second stage propulsion, (iii) coast arc (after release of the second stage), and (iv) third stage propulsion. The Euler-Lagrange equations and the Pontryagin minimum principle, in conjunction with the Weierstrass-Erdmann corner conditions, are employed to express the thrust angles as functions of the adjoint variables conjugate to the dynamics equations. The use of these analytical conditions coming from the calculus of variations leads to obtaining the overall rocket dynamics as a function of seven parameters only, namely the unknown values of the initial state and costate components, the coast duration, and the upper stage thrust duration. In addition, a simple approach is introduced and successfully applied with the purpose of satisfying exactly the path constraint related to the maximum dynamical pressure in the atmospheric phase. The basic version of the swarming technique, which is used in this research, is extremely simple and easy to program. Nevertheless, the algorithm proves to be capable of yielding the optimal rocket trajectory with a very satisfactory numerical accuracy.

Multiple burn fuel-optimal orbit transfers: Numerical trajectory computation and neighboring optimal feedback guidance

NASA Technical Reports Server (NTRS)

Chuang, C.-H.; Goodson, Troy D.; Ledsinger, Laura A.

1995-01-01

This report describes current work in the numerical computation of multiple burn, fuel-optimal orbit transfers and presents an analysis of the second variation for extremal multiple burn orbital transfers as well as a discussion of a guidance scheme which may be implemented for such transfers. The discussion of numerical computation focuses on the use of multivariate interpolation to aid the computation in the numerical optimization. The second variation analysis includes the development of the conditions for the examination of both fixed and free final time transfers. Evaluations for fixed final time are presented for extremal one, two, and three burn solutions of the first variation. The free final time problem is considered for an extremal two burn solution. In addition, corresponding changes of the second variation formulation over thrust arcs and coast arcs are included. The guidance scheme discussed is an implicit scheme which implements a neighboring optimal feedback guidance strategy to calculate both thrust direction and thrust on-off times.

The solution of the optimization problem of small energy complexes using linear programming methods

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Director, L. B.

2016-11-01

Linear programming methods were used for solving the optimization problem of schemes and operation modes of distributed generation energy complexes. Applicability conditions of simplex method, applied to energy complexes, including installations of renewable energy (solar, wind), diesel-generators and energy storage, considered. The analysis of decomposition algorithms for various schemes of energy complexes was made. The results of optimization calculations for energy complexes, operated autonomously and as a part of distribution grid, are presented.

Optimal control of a variable spin speed CMG system for space vehicles. [Control Moment Gyros

NASA Technical Reports Server (NTRS)

Liu, T. C.; Chubb, W. B.; Seltzer, S. M.; Thompson, Z.

1973-01-01

Many future NASA programs require very high accurate pointing stability. These pointing requirements are well beyond anything attempted to date. This paper suggests a control system which has the capability of meeting these requirements. An optimal control law for the suggested system is specified. However, since no direct method of solution is known for this complicated system, a computation technique using successive approximations is used to develop the required solution. The method of calculus of variations is applied for estimating the changes of index of performance as well as those constraints of inequality of state variables and terminal conditions. Thus, an algorithm is obtained by the steepest descent method and/or conjugate gradient method. Numerical examples are given to show the optimal controls.

Photochemical decoration of magnetic composites with silver nanostructures for determination of creatinine in urine by surface-enhanced Raman spectroscopy.

PubMed

Alula, Melisew Tadele; Yang, Jyisy

2014-12-01

In this study, silver nanostructures decorated magnetic nanoparticles for surface-enhanced Raman scattering (SERS) measurements were prepared via photoreduction utilizing the catalytic activity of ZnO nanostructure. The ZnO/Fe3O4 composite was first prepared by dispersing pre-formed magnetic nanoparticles into alkaline zinc nitrate solutions. After annealing of the precipitates, the formed ZnO/Fe3O4 composites were successfully decorated with silver nanostructures by soaking the composites into silver nitrate/ethylene glycol solution following UV irradiations. To find the optimal condition when preparing Ag@ZnO/Fe3O4 composites for SERS measurements, factors such as the reaction conditions, photoreduction time, concentration of zinc nitrate and silver nitrate were studied. Results indicated that the photoreduction efficiency was significantly improved with the assistance of ZnO but the amount of ZnO in the composite is not critical. The concentration of silver nitrate and UV irradiation time affected the morphologies of the formed composites and optimal condition in preparation of the composites for SERS measurement was found using 20mM of silver nitrate with an irradiation time of 90 min. Under the optimized condition, the obtained SERS intensities were highly reproducible with a SERS enhancement factor in the order of 7. Quantitative analyses showed that a linear range up to 1 µM with a detection limit lower than 0.1 µM in the detection of creatinine in aqueous solution could be obtained. Successful applying of these prepared composites to determine creatinine in urine sample was obtained. Copyright © 2014 Elsevier B.V. All rights reserved.

Approximate solution of space and time fractional higher order phase field equation

NASA Astrophysics Data System (ADS)

Shamseldeen, S.

2018-03-01

This paper is concerned with a class of space and time fractional partial differential equation (STFDE) with Riesz derivative in space and Caputo in time. The proposed STFDE is considered as a generalization of a sixth-order partial phase field equation. We describe the application of the optimal homotopy analysis method (OHAM) to obtain an approximate solution for the suggested fractional initial value problem. An averaged-squared residual error function is defined and used to determine the optimal convergence control parameter. Two numerical examples are studied, considering periodic and non-periodic initial conditions, to justify the efficiency and the accuracy of the adopted iterative approach. The dependence of the solution on the order of the fractional derivative in space and time and model parameters is investigated.

The Effect of Temperature and Solution pH on Tetragonal Lysozyme Nucleation Kinetics

NASA Technical Reports Server (NTRS)

Judge, Russell A.; Jacobs, Randolph S.; Frazier, Tyralynn; Snell, Edward H.; Pusey, Marc L.

1998-01-01

Part of the challenge of macromolecular crystal growth for structure determination is obtaining an appropriate number of crystals with a crystal volume suitable for x-ray analysis. In this respect an understanding of the effect of solution conditions on macromolecule nucleation rates is advantageous. This study investigated the effects of supersaturation, temperature and pH on the nucleation rate of tetragonal lysozyme crystals. Batch crystallization plates were prepared at given solution concentrations and incubated at set temperatures over one week. The number of crystals per well with their size and axial ratios were recorded and correlated with solution conditions, Duplicate experiments indicate the reproducibility of the technique, Crystal numbers were found to increase with increasing supersaturation and temperature. The most significant variable however, was pH, where crystal numbers changed by two orders of magnitude over the pH range 4.0 to 5.2. Crystal size varied also with solution conditions, with the largest crystals being obtained at pH 5.2. Having optimized the crystallization conditions, a batch of crystals were prepared under exactly the same conditions and fifty of these crystals were analyzed by x-ray techniques. The results indicate that even under the same crystallization conditions, a marked variation in crystal properties exists.

A multi-product green supply chain under government supervision with price and demand uncertainty

NASA Astrophysics Data System (ADS)

Hafezalkotob, Ashkan; Zamani, Soma

2018-05-01

In this paper, a bi-level game-theoretic model is proposed to investigate the effects of governmental financial intervention on green supply chain. This problem is formulated as a bi-level program for a green supply chain that produces various products with different environmental pollution levels. The problem is also regard uncertainties in market demand and sale price of raw materials and products. The model is further transformed into a single-level nonlinear programming problem by replacing the lower-level optimization problem with its Karush-Kuhn-Tucker optimality conditions. Genetic algorithm is applied as a solution methodology to solve nonlinear programming model. Finally, to investigate the validity of the proposed method, the computational results obtained through genetic algorithm are compared with global optimal solution attained by enumerative method. Analytical results indicate that the proposed GA offers better solutions in large size problems. Also, we conclude that financial intervention by government consists of green taxation and subsidization is an effective method to stabilize green supply chain members' performance.

Optimization of Photooxidative Removal of Phenazopyridine from Water

NASA Astrophysics Data System (ADS)

Saeid, Soudabeh; Behnajady, Mohammad A.; Tolvanen, Pasi; Salmi, Tapio

2018-05-01

The photooxidative removal of analgesic pharmaceutical compound phenazopyridine (PhP) from aqueous solutions by UV/H2O2 system with a re-circulated photoreactor was investigated. Response surface methodology (RSM) was employed to optimize the effect of operational parameters on the photooxidative removal efficiency. The investigated variables were: the initial PhP and H2O2 concentrations, irradiation time, volume of solution and pH. The analysis of variance (ANOVA) of quadratic model demonstrated that the described model was highly significant. The predicted values of the photooxidative removal efficiency were found to be in a fair agreement with experimental values ( R 2 = 0.9832, adjusted R 2 = 0.9716). The model predicted that the optimal reaction conditions for a maximum removal of PhP (>98%) were: initial PhP concentration less than 23 mg L-1, initial concentration of H2O2 higher than 470 mg L-1, solution volume less than 500 mL, pH close to 2 and irradiation time longer than 6 min.

Optimization Parameters of Air-conditioning and Heat Insulation Systems of a Pressurized Cabins of Long-distance Airplanes

NASA Astrophysics Data System (ADS)

Gusev, Sergey A.; Nikolaev, Vladimir N.

2018-01-01

The method for determination of an aircraft compartment thermal condition, based on a mathematical model of a compartment thermal condition was developed. Development of solution techniques for solving heat exchange direct and inverse problems and for determining confidence intervals of parametric identification estimations was carried out. The required performance of air-conditioning, ventilation systems and heat insulation depth of crew and passenger cabins were received.

Testing the sensitivity of pumpage to increases in surficial aquifer system heads in the Cypress Creek well-field area, West-Central Florida : an optimization technique

USGS Publications Warehouse

Yobbi, Dann K.

2002-01-01

Tampa Bay depends on ground water for most of the water supply. Numerous wetlands and lakes in Pasco County have been impacted by the high demand for ground water. Central Pasco County, particularly the area within the Cypress Creek well field, has been greatly affected. Probable causes for the decline in surface-water levels are well-field pumpage and a decade-long drought. Efforts are underway to increase surface-water levels by developing alternative sources of water supply, thus reducing the quantity of well-field pumpage. Numerical ground-water flow simulations coupled with an optimization routine were used in a series of simulations to test the sensitivity of optimal pumpage to desired increases in surficial aquifer system heads in the Cypress Creek well field. The ground-water system was simulated using the central northern Tampa Bay ground-water flow model. Pumping solutions for 1987 equilibrium conditions and for a transient 6-month timeframe were determined for five test cases, each reflecting a range of desired target recovery heads at different head control sites in the surficial aquifer system. Results are presented in the form of curves relating average head recovery to total optimal pumpage. Pumping solutions are sensitive to the location of head control sites formulated in the optimization problem and as expected, total optimal pumpage decreased when desired target head increased. The distribution of optimal pumpage for individual production wells also was significantly affected by the location of head control sites. A pumping advantage was gained for test-case formulations where hydraulic heads were maximized in cells near the production wells, in cells within the steady-state pumping center cone of depression, and in cells within the area of the well field where confining-unit leakance is the highest. More water was pumped and the ratio of head recovery per unit decrease in optimal pumpage was more than double for test cases where hydraulic heads are maximized in cells located at or near the production wells. Additionally, the ratio of head recovery per unit decrease in pumpage was about three times more for the area where confining-unit leakance is the highest than for other leakance zone areas of the well field. For many head control sites, optimal heads corresponding to optimal pumpage deviated from the desired target recovery heads. Overall, pumping solutions were constrained by the limiting recovery values, initial head conditions, and by upper boundary conditions of the ground-water flow model.

Adaptive Decision Making Using Probabilistic Programming and Stochastic Optimization

DTIC Science & Technology

2018-01-01

world optimization problems (and hence 16 Approved for Public Release (PA); Distribution Unlimited Pred. demand (uncertain; discrete ...simplify the setting, we further assume that the demands are discrete , taking on values d1, . . . , dk with probabilities (conditional on x) (pθ)i ≡ p...Tyrrell Rockafellar. Implicit functions and solution mappings. Springer Monogr. Math ., 2009. Anthony V Fiacco and Yo Ishizuka. Sensitivity and stability

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

Li, Yongjun; Yang, Lingyun

We report an efficient dynamic aperture (DA) optimization approach using multiobjective genetic algorithm (MOGA), which is driven by nonlinear driving terms computation. It was found that having small low order driving terms is a necessary but insufficient condition of having a decent DA. Then direct DA tracking simulation is implemented among the last generation candidates to select the best solutions. The approach was demonstrated successfully in optimizing NSLS-II storage ring DA.

Relay Selection for Cooperative Relaying in Wireless Energy Harvesting Networks

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei; Li, Songsong; Jiang, Fengjiao; Cao, Lijie

2018-01-01

Energy harvesting from the surroundings is a promising solution to provide energy supply and extend the life of wireless sensor networks. Recently, energy harvesting has been shown as an attractive solution to prolong the operation of cooperative networks. In this paper, we propose a relay selection scheme to optimize the amplify-and-forward (AF) cooperative transmission in wireless energy harvesting cooperative networks. The harvesting energy and channel conditions are considered to select the optimal relay as cooperative relay to minimize the outage probability of the system. Simulation results show that our proposed relay selection scheme achieves better outage performance than other strategies.

Value function in economic growth model

NASA Astrophysics Data System (ADS)

Bagno, Alexander; Tarasyev, Alexandr A.; Tarasyev, Alexander M.

2017-11-01

Properties of the value function are examined in an infinite horizon optimal control problem with an unlimited integrand index appearing in the quality functional with a discount factor. Optimal control problems of such type describe solutions in models of economic growth. Necessary and sufficient conditions are derived to ensure that the value function satisfies the infinitesimal stability properties. It is proved that value function coincides with the minimax solution of the Hamilton-Jacobi equation. Description of the growth asymptotic behavior for the value function is provided for the logarithmic, power and exponential quality functionals and an example is given to illustrate construction of the value function in economic growth models.

Validation of a simple method of estimating plasma free cortisol: role of cortisol binding to albumin.

PubMed

Dorin, Richard I; Pai, Hemanth K; Ho, Jui T; Lewis, John G; Torpy, David J; Urban, Frank K; Qualls, Clifford R

2009-01-01

To develop, optimize, and validate a generalized mass action, equilibrium solution that incorporates measured concentrations of albumin as well as cortisol binding globulin (CBG) to estimate free cortisol. Free cortisol was estimated by Coolens method or by cubic equilibrium equation and compared to measured free cortisol, determined by ultrafiltration method, in subjects with septic shock (n=45), sepsis (n=19), and healthy controls (n=10) at 0, 30, and 60 min following administration of cosyntropin (250 mcg). The data set also included repeat testing in 30 subjects following recovery from sepsis/septic shock. The equilibrium dissociation constant for cortisol binding to albumin (K(A)) was optimized by non-linear regression. The cubic equilibrium solution was also used to model the influence of cortisol, CBG, and albumin concentration on free cortisol. Compared to measured free cortisol, the cubic solution, using an optimized K(A) of 137,800 nM, was less biased than Coolens solution, with mean percent error of -23.0% vs. -41.1% (paired t test, P<0.001). Standard deviation values were also significantly lower (Wilks' test, P<0.001) for the cubic solution (SD 35.8% vs. 40.8% for cubic vs. Coolens, respectively). Modeling studies using the cubic solution suggest an interaction effect by which low concentrations of CBG and albumin contribute to a greater increase in free cortisol than the sum of their independent effects. Mass action solutions that incorporate the measured concentration of albumin as well as CBG provide a reasonably accurate estimate of free cortisol that generalizes to conditions of health as well as a setting of hypercortisolism and low CBG and albumin concentrations associated with septic shock. Modeling studies emphasize the significant contribution of albumin deficiency and albumin-bound cortisol under conditions of CBG-deficiency, and identify a synergistic effect by which combined CBG and albumin deficiency contribute to elevation of free cortisol in septic shock.

Optimizing the synthesis conditions of silver nanoparticles using corn starch and their catalytic reduction of 4-nitrophenol

NASA Astrophysics Data System (ADS)

Salaheldin, Hosam I.

2018-06-01

In this study, silver nanoparticles (SNPs) were synthesised in an aqueous solution of corn starch. To fabricate the SNPs, reaction conditions, such as varying silver nitrate () concentration, time, temperature and solution pH of the reaction, were optimized. Since, the optimum reaction conditions were found 1 mmo l‑1, 15 min and , respectively. Then, to study the role of pH on SNP synthesis, varying pH values of the solution (3, 5, 7, 9 and 11) were investigated. Subsequently, the obtained silver/starch nanocomposites were characterised using different techniques. The x-ray diffraction (XRD) results revealed that the particles were face-centred cubic (FCC), and had an average particle size of 7.5 nm. This was confirmed by high-resolution transmission electron microscopy (HR-TEM) images. Moreover, the synthesised SNPs, at different pH values, were used as nanocatalyst for the reduction of 4-nitrophenol to 4-aminophenol in the presence of sodium borohydride. Under optimum reaction conditions, the higher catalytic activity was obtained with SNPs synthesised at pH 11 compared to lower pH of 7 or 9. Therefore, the rapid, reproducible, cost-effective silver/starch nanocomposite can be widely used for various applications such as drug manufacturing (e.g. analgesics and antipyretics) and the removal of pollutants from wastewater.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

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

Zhou, Z; Folkert, M; Wang, J

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidentialmore » reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.« less

Pressure leaching of chalcopyrite concentrate

NASA Astrophysics Data System (ADS)

Aleksei, Kritskii; Kirill, Karimov; Stanislav, Naboichenko

2018-05-01

The results of chalcopyrite concentrate processing using low-temperature and high-temperature sulfuric acid pressure leaching are presented. A material of the following composition was used, 21.5 Cu, 0.1 Zn, 0.05 Pb, 0.04 Ni, 26.59 S, 24.52 Fe, 16.28 SiO2 (in wt.%). The influence of technological parameters on the degree of copper and iron extraction into the leach solution was studied in the wide range of values. The following conditions were suggested as the optimal for the high-temperature pressure leaching: t = 190 °C, PO2 = 0.5 MPa, CH2SO4 = 15 g/L, L:S = 6:1. At the mentioned parameters, it is possible to extract at least 98% Cu from concentrate into the leaching solution during 100 minutes. The following conditions were suggested as optimal for the low-temperature pressure leaching: t = 105 °C, PO2 = 1.3-1.5 MPa, CH2SO4 = 90 g/L, L:S = 10:1. At the mentioned parameters, it is possible to extract up to 83% Cu from the concentrate into the leach solution during 300-360 minutes.

Scalable multi-objective control for large scale water resources systems under uncertainty

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower production, flood control, and water supply. Numerical results under historical as well as synthetically generated hydrologic conditions show that our approach is able to discover key system tradeoffs in the operations of the system. The ability of the algorithm to find near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. In addition, although significant performance degradation is observed when the solutions designed over history are re-evaluated over synthetically generated inflows, we successfully reduced these vulnerabilities by identifying alternative solutions that are more robust to hydrologic uncertainties, while also addressing the tradeoffs across the Red River multi-sector services.

Finite element solution of optimal control problems with inequality constraints

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Hodges, Dewey H.

1990-01-01

A finite-element method based on a weak Hamiltonian form of the necessary conditions is summarized for optimal control problems. Very crude shape functions (so simple that element numerical quadrature is not necessary) can be used to develop an efficient procedure for obtaining candidate solutions (i.e., those which satisfy all the necessary conditions) even for highly nonlinear problems. An extension of the formulation allowing for discontinuities in the states and derivatives of the states is given. A theory that includes control inequality constraints is fully developed. An advanced launch vehicle (ALV) model is presented. The model involves staging and control constraints, thus demonstrating the full power of the weak formulation to date. Numerical results are presented along with total elapsed computer time required to obtain the results. The speed and accuracy in obtaining the results make this method a strong candidate for a real-time guidance algorithm.

Pretreatment of corn straw using the alkaline solution of ionic liquids.

PubMed

Liu, Zhen; Li, Longfei; Liu, Cheng; Xu, Airong

2018-07-01

In the present work, the pretreatment of corn stalk with the solution of 1-ethyl-3-methylimidazolium acetate ([Emim]Ac) ionic liquid containing NaOH was explored for its lignin removal. The effects of reaction temperature, reaction time, and solid-liquid ratio on the lignin removal efficiency were determined by the response surface methodology (RSM). The pretreatment conditions were optimized by the Box-Behnken design and the comparative study of the composition and structure of corn straw before and after the pretreatment to be: reaction temperature 98.5 °C, reaction time 1.31 h, and solid-liquid ratio 1:8.7. Under the optimized conditions, the cellulose and hemicellulose contents of the corn straw were increased to 85.69% and 9.1%, respectively, and the lignin content was reduced to 2.27% with the lignin removal efficiency up to 87.4%. Copyright © 2018 Elsevier Ltd. All rights reserved.

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Optimal plant nitrogen use improves model representation of vegetation response to elevated CO2

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Kern, Melanie; Engel, Jan; Zaehle, Sönke

2017-04-01

Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.

Aircraft Range Optimization Using Singular Perturbations

NASA Technical Reports Server (NTRS)

Oconnor, Joseph Taffe

1973-01-01

An approximate analytic solution is developed for the problem of maximizing the range of an aircraft for a fixed end state. The problem is formulated as a singular perturbation and solved by matched inner and outer asymptotic expansions and the minimum principle of Pontryagin. Cruise in the stratosphere, and on transition to and from cruise at constant Mach number are discussed. The state vector includes altitude, flight path angle, and mass. Specific fuel consumption becomes a linear function of power approximating that of the cruise values. Cruise represents the outer solution; altitude and flight path angle are constants, and only mass changes. Transitions between cruise and the specified initial and final conditions correspond to the inner solutions. The mass is constant and altitude and velocity vary. A solution is developed which is valid for cruise but which is not for the initial and final conditions. Transforming of the independent variable near the initial and final conditions result in solutions which are valid for the two inner solutions but not for cruise. The inner solutions can not be obtained without simplifying the state equations. The singular perturbation approach overcomes this difficulty. A quadratic approximation of the state equations is made. The resulting problem is solved analytically, and the two inner solutions are matched to the outer solution.

Hybrid, experimental and computational, investigation of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1996-07-01

Computational and experimental methodologies have unique features for the analysis and solution of a wide variety of engineering problems. Computations provide results that depend on selection of input parameters such as geometry, material constants, and boundary conditions which, for correct modeling purposes, have to be appropriately chosen. In addition, it is relatively easy to modify the input parameters in order to computationally investigate different conditions. Experiments provide solutions which characterize the actual behavior of the object of interest subjected to specific operating conditions. However, it is impractical to experimentally perform parametric investigations. This paper discusses the use of a hybrid, computational and experimental, approach for study and optimization of mechanical components. Computational techniques are used for modeling the behavior of the object of interest while it is experimentally tested using noninvasive optical techniques. Comparisons are performed through a fringe predictor program used to facilitate the correlation between both techniques. In addition, experimentally obtained quantitative information, such as displacements and shape, can be applied in the computational model in order to improve this correlation. The result is a validated computational model that can be used for performing quantitative analyses and structural optimization. Practical application of the hybrid approach is illustrated with a representative example which demonstrates the viability of the approach as an engineering tool for structural analysis and optimization.

Analysis of a Two-Dimensional Thermal Cloaking Problem on the Basis of Optimization

NASA Astrophysics Data System (ADS)

Alekseev, G. V.

2018-04-01

For a two-dimensional model of thermal scattering, inverse problems arising in the development of tools for cloaking material bodies on the basis of a mixed thermal cloaking strategy are considered. By applying the optimization approach, these problems are reduced to optimization ones in which the role of controls is played by variable parameters of the medium occupying the cloaking shell and by the heat flux through a boundary segment of the basic domain. The solvability of the direct and optimization problems is proved, and an optimality system is derived. Based on its analysis, sufficient conditions on the input data are established that ensure the uniqueness and stability of optimal solutions.

Modification process optimization, characterization and adsorption property of granular fir-based activated carbon

NASA Astrophysics Data System (ADS)

Chen, Congjin; Li, Xin; Tong, Zhangfa; Li, Yue; Li, Mingfei

2014-10-01

Granular fir-based activated carbon (GFAC) was modified with H2O2, and orthogonal array experimental design method was used to optimize the process. The properties of the original and modified GFAC were characterized by N2 adsorption-desorption isotherms, Brunauer-Emmett-Teller (BET) equation, Barett-Joyner-Halenda (BJH) equation, field emission scanning electron microscopy (FESEM), and Fourier transform infrared spectroscopy (FT-IR) analysis, etc. When 10.00 g of GFAC with particle size of 0.25-0.85 mm was modified by 150.0 ml of aqueous H2O2 solution, the optimized conditions were found to be as follows: aqueous H2O2 solution concentration 1.0 mol·l-1, modification temperature 30.0 °C, modification time 4.0 h. Modified under the optimized conditions, decolonization of caramel, methylene blue adsorption, phenol adsorption and iodine number of the modified GFAC increased by 500.0%, 59.7%, 32.5%, and 15.1%, respectively. The original and optimally modified GFAC exhibited adsorption isotherms of hybrid Type I-IV isotherms with H4 hysteresis. BET surface area, micropore area, total pore volume, micropore volume, and microporosity of the modified GFAC increased by 7.33%, 11.25%, 3.89%, 14.23%, 9.91%, respectively. Whereas the average pore width decreased by 3.16%. In addition, the amount of surface oxygen groups (such as carbonyl or carboxyl) increased in the modified GFAC.

Cisplatin-Conjugated Porous Gelatin Particles: Assessment of Optimal Conditions for Binding and Release

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

Ohta, Shinichi, E-mail: junryuhei@yahoo.co.jp; Nitta, Norihisa; Sonoda, Akinaga

2010-08-15

This study was designed to evaluate the optimal conditions for binding cisplatin and porous gelatin particles (PGPs) and to establish in vivo drug release pharmacokinetics. PGPs were immersed in cisplatin solutions under different conditions: concentration, immersion time, and temperature. Thereafter, PGPs were washed in distilled water to remove uncombined cisplatin and were then freeze-dried. The platinum concentration (PC) in the PGPs was then measured. For the in vivo release test, 50 mg/kg of the cisplatin-conjugated PGPs was implanted subcutaneously in the abdominal region of two rabbits. PCs in the blood were measured at different time intervals. PCs significantly increased inmore » direct proportion to the concentration and immersion time (p < 0.01). Although PC increased at higher solution temperature, it was not a linear progression. For the in vivo release test, platinum was released from cisplatin-conjugated PGPs after 1 day, and the peak PC was confirmed 2 days after implantation. Platinum in the blood was detected until 7 days after implantation in one rabbit and 15 days after administration in the other rabbit. Platinum binding with PGPs increased with a higher concentration of cisplatin solution at a higher temperature over a longer duration of time. Release of cisplatin from cisplatin-conjugated PGPs was confirmed in vivo.« less

Optimization of Fermentation Conditions and Rheological Properties of Exopolysaccharide Produced by Deep-Sea Bacterium Zunongwangia profunda SM-A87

PubMed Central

Liu, Sheng-Bo; Qiao, Li-Ping; He, Hai-Lun; Zhang, Qian; Chen, Xiu-Lan; Zhou, Wei-Zhi; Zhou, Bai-Cheng; Zhang, Yu-Zhong

2011-01-01

Zunongwangia profunda SM-A87 isolated from deep-sea sediment can secrete large quantity of exopolysaccharide (EPS). Response surface methodology was applied to optimize the culture conditions for EPS production. Single-factor experiment showed that lactose was the best carbon source. Based on the Plackett–Burman design, lactose, peptone and temperature were selected as significant variables, which were further optimized by the steepest ascent (descent) method and central composite design. The optimal culture conditions for EPS production and broth viscosity were determined as 32.21 g/L lactose, 8.87 g/L peptone and an incubation temperature of 9.8°C. Under these conditions, the maximum EPS yield and broth viscosity were 8.90 g/L and 6551 mPa•s, respectively, which is the first report of such high yield of EPS from a marine bacterium. The aqueous solution of the EPS displayed high viscosity, interesting shearing thinning property and great tolerance to high temperature, a wide range of pH, and high salinity. PMID:22096500

Two retailer-supplier supply chain models with default risk under trade credit policy.

PubMed

Wu, Chengfeng; Zhao, Qiuhong

2016-01-01

The purpose of the paper is to formulate two uncooperative replenishment models with demand and default risk which are the functions of the trade credit period, i.e., a Nash equilibrium model and a supplier-Stackelberg model. Firstly, we present the optimal results of decentralized decision and centralized decision without trade credit. Secondly, we derive the existence and uniqueness conditions of the optimal solutions under the two games, respectively. Moreover, we present a set of theorems and corollary to determine the optimal solutions. Finally, we provide an example and sensitivity analysis to illustrate the proposed strategy and optimal solutions. Sensitivity analysis reveals that the total profits of supply chain under the two games both are better than the results under the centralized decision only if the optimal trade credit period isn't too short. It also reveals that the size of trade credit period, demand, retailer's profit and supplier's profit have strong relationship with the increasing demand coefficient, wholesale price, default risk coefficient and production cost. The major contribution of the paper is that we comprehensively compare between the results of decentralized decision and centralized decision without trade credit, Nash equilibrium and supplier-Stackelberg models with trade credit, and obtain some interesting managerial insights and practical implications.

Isolation of fish skin and bone gelatin from tilapia (Oreochromis niloticus): Response surface approach

NASA Astrophysics Data System (ADS)

Arpi, N.; Fahrizal; Novita, M.

2018-03-01

In this study, gelatin from fish collagen, as one of halal sources, was extracted from tilapia (Oreochromis niloticus) skin and bone, by using Response Surface Methodology to optimize gelatin extraction conditions. Concentrations of alkaline NaOH and acid HCl, in the pretreatment process, and temperatures in extraction process were chosen as independent variables, while dependent variables were yield, gel strength, and emulsion activity index (EAI). The result of investigation showed that lower NaOH pretreatment concentrations provided proper pH extraction conditions which combine with higher extraction temperatures resulted in high gelatin yield. However, gelatin emulsion activity index increased proportionally to the decreased in NaOH concentrations and extraction temperatures. No significant effect of the three independent variables on the gelatin gel strength. RSM optimization process resulted in optimum gelatin extraction process conditions using alkaline NaOH concentration of 0.77 N, acid HCl of 0.59 N, and extraction temperature of 66.80 °C. The optimal solution formula had optimization targets of 94.38%.

Method for Household Refrigerators Efficiency Increasing

NASA Astrophysics Data System (ADS)

Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.

2017-11-01

The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.

Optimization of activator solution and heat treatment of ground lignite type fly ash geopolymers

NASA Astrophysics Data System (ADS)

Molnár, Z.; Szabó, R.; Rácz, Á.; Lakatos, J.; Debreczeni, Á.; Mucsi, G.

2017-02-01

Geopolymers are inorganic polymers which can be produced by the reaction between silico aluminate oxides and alkali silicates in alkaline medium. Materialscontaining silica and alumina compounds are suitable for geopolymer production. These can beprimary materials or industrial wastes, i. e. fly ash, metallurgical slag and red mud. In this paper, the results of the systematic experimental series are presented which were carried out in order to optimize the geopolymer preparation process. Fly ash was ground for different residence time (0, 5, 10, 30, 60 min) in order to investigate the optimal specific surface area. NaOH activator solution concentration also varied (6, 8, 10, 12, 14 M). Furthermore, sodium silicate was added to NaOH as a network builder solution. In this last serie different heat curing temperatures (30, 60, 90°C) were also applied. After seven days of ageing the physical properties of the geopolymer(compressive strength and specimen density)were measured. Chemical leaching tests on the rawmaterial and the geopolymers were carried out to determine the elements which can be mobilized by different leaching solutions. It was found that the above mentioned parameters (fly ash fineness, molar concentration and composition of activator solution, heat curing) has great effect on the physical and chemical properties of geopolymer specimens. Optimal conditions were as follows: specific surface area of the fly ash above 2000 cm2/g, 10 M NaOH, 30°C heat curing temperature which resulted in 21 MPa compressive strength geopolymer.

Optimization of methylene blue removal by stable emulsified liquid membrane using Plackett–Burman and Box–Behnken designs of experiments

PubMed Central

Djenouhat, Meriem; Bendebane, Farida; Bahloul, Lynda; Samar, Mohamed E. H.

2018-01-01

The stability of an emulsified liquid membrane composed of Span80 as a surfactant, D2EHPA as an extractant and sulfuric acid as an internal phase was first studied according to different diluents and many operating parameters using the Plackett–Burman design of experiments. Then the removal of methylene blue from an aqueous solution has been carried out using this emulsified liquid membrane at its stability conditions. The effects of operating parameters were analysed from the Box–Behnken design of experiments. The optimization of the extraction has been realized applying the response surface methodology and the results showed that the dye extraction yielding 98.72% was achieved at optimized conditions. PMID:29515841

Formation of curcumin nanoparticles via solution-enhanced dispersion by supercritical CO2

PubMed Central

Zhao, Zheng; Xie, Maobin; Li, Yi; Chen, Aizheng; Li, Gang; Zhang, Jing; Hu, Huawen; Wang, Xinyu; Li, Shipu

2015-01-01

In order to enhance the bioavailability of poorly water-soluble curcumin, solution-enhanced dispersion by supercritical carbon dioxide (CO2) (SEDS) was employed to prepare curcumin nanoparticles for the first time. A 24 full factorial experiment was designed to determine optimal processing parameters and their influence on the size of the curcumin nanoparticles. Particle size was demonstrated to increase with increased temperature or flow rate of the solution, or with decreased precipitation pressure, under processing conditions with different parameters considered. The single effect of the concentration of the solution on particle size was not significant. Curcumin nanoparticles with a spherical shape and the smallest mean particle size of 325 nm were obtained when the following optimal processing conditions were adopted: P =20 MPa, T =35°C, flow rate of solution =0.5 mL·min−1, concentration of solution =0.5%. Fourier transform infrared (FTIR) spectroscopy measurement revealed that the chemical composition of curcumin basically remained unchanged. Nevertheless, X-ray powder diffraction (XRPD) and thermal analysis indicated that the crystalline state of the original curcumin decreased after the SEDS process. The solubility and dissolution rate of the curcumin nanoparticles were found to be higher than that of the original curcumin powder (approximately 1.4 μg/mL vs 0.2 μg/mL in 180 minutes). This study revealed that supercritical CO2 technologies had a great potential in fabricating nanoparticles and improving the bioavailability of poorly water-soluble drugs. PMID:25995627

Formation of curcumin nanoparticles via solution-enhanced dispersion by supercritical CO2.

PubMed

Zhao, Zheng; Xie, Maobin; Li, Yi; Chen, Aizheng; Li, Gang; Zhang, Jing; Hu, Huawen; Wang, Xinyu; Li, Shipu

2015-01-01

In order to enhance the bioavailability of poorly water-soluble curcumin, solution-enhanced dispersion by supercritical carbon dioxide (CO2) (SEDS) was employed to prepare curcumin nanoparticles for the first time. A 2(4) full factorial experiment was designed to determine optimal processing parameters and their influence on the size of the curcumin nanoparticles. Particle size was demonstrated to increase with increased temperature or flow rate of the solution, or with decreased precipitation pressure, under processing conditions with different parameters considered. The single effect of the concentration of the solution on particle size was not significant. Curcumin nanoparticles with a spherical shape and the smallest mean particle size of 325 nm were obtained when the following optimal processing conditions were adopted: P = 20 MPa, T = 35°C, flow rate of solution = 0.5 mL·min(-1), concentration of solution = 0.5%. Fourier transform infrared (FTIR) spectroscopy measurement revealed that the chemical composition of curcumin basically remained unchanged. Nevertheless, X-ray powder diffraction (XRPD) and thermal analysis indicated that the crystalline state of the original curcumin decreased after the SEDS process. The solubility and dissolution rate of the curcumin nanoparticles were found to be higher than that of the original curcumin powder (approximately 1.4 μg/mL vs 0.2 μg/mL in 180 minutes). This study revealed that supercritical CO2 technologies had a great potential in fabricating nanoparticles and improving the bioavailability of poorly water-soluble drugs.

Interactive optimization approach for optimal impulsive rendezvous using primer vector and evolutionary algorithms

NASA Astrophysics Data System (ADS)

Luo, Ya-Zhong; Zhang, Jin; Li, Hai-yang; Tang, Guo-Jin

2010-08-01

In this paper, a new optimization approach combining primer vector theory and evolutionary algorithms for fuel-optimal non-linear impulsive rendezvous is proposed. The optimization approach is designed to seek the optimal number of impulses as well as the optimal impulse vectors. In this optimization approach, adding a midcourse impulse is determined by an interactive method, i.e. observing the primer-magnitude time history. An improved version of simulated annealing is employed to optimize the rendezvous trajectory with the fixed-number of impulses. This interactive approach is evaluated by three test cases: coplanar circle-to-circle rendezvous, same-circle rendezvous and non-coplanar rendezvous. The results show that the interactive approach is effective and efficient in fuel-optimal non-linear rendezvous design. It can guarantee solutions, which satisfy the Lawden's necessary optimality conditions.

A Hamiltonian approach to the planar optimization of mid-course corrections

NASA Astrophysics Data System (ADS)

Iorfida, E.; Palmer, P. L.; Roberts, M.

2016-04-01

Lawden's primer vector theory gives a set of necessary conditions that characterize the optimality of a transfer orbit, defined accordingly to the possibility of adding mid-course corrections. In this paper a novel approach is proposed where, through a polar coordinates transformation, the primer vector components decouple. Furthermore, the case when transfer, departure and arrival orbits are coplanar is analyzed using a Hamiltonian approach. This procedure leads to approximate analytic solutions for the in-plane components of the primer vector. Moreover, the solution for the circular transfer case is proven to be the Hill's solution. The novel procedure reduces the mathematical and computational complexity of the original case study. It is shown that the primer vector is independent of the semi-major axis of the transfer orbit. The case with a fixed transfer trajectory and variable initial and final thrust impulses is studied. The acquired related optimality maps are presented and analyzed and they express the likelihood of a set of trajectories to be optimal. Furthermore, it is presented which kind of requirements have to be fulfilled by a set of departure and arrival orbits to have the same profile of primer vector.

Convex relaxations for gas expansion planning

DOE PAGES

Borraz-Sanchez, Conrado; Bent, Russell Whitford; Backhaus, Scott N.; ...

2016-01-01

Expansion of natural gas networks is a critical process involving substantial capital expenditures with complex decision-support requirements. Here, given the non-convex nature of gas transmission constraints, global optimality and infeasibility guarantees can only be offered by global optimisation approaches. Unfortunately, state-of-the-art global optimisation solvers are unable to scale up to real-world size instances. In this study, we present a convex mixed-integer second-order cone relaxation for the gas expansion planning problem under steady-state conditions. The underlying model offers tight lower bounds with high computational efficiency. In addition, the optimal solution of the relaxation can often be used to derive high-quality solutionsmore » to the original problem, leading to provably tight optimality gaps and, in some cases, global optimal solutions. The convex relaxation is based on a few key ideas, including the introduction of flux direction variables, exact McCormick relaxations, on/off constraints, and integer cuts. Numerical experiments are conducted on the traditional Belgian gas network, as well as other real larger networks. The results demonstrate both the accuracy and computational speed of the relaxation and its ability to produce high-quality solution« less

Characterization of cadmium biosorption by Exiguobacterium sp. isolated from farmland soil near Cu-Pb-Zn mine.

PubMed

Park, Jin Hee; Chon, Hyo-Taek

2016-06-01

Bacteria have the ability to bind heavy metals on their cell wall. Biosorption is a passive and energy-independent mechanism to adsorb heavy metals. The efficiency of heavy metal biosorption can vary depending on several factors such as the growth phase of bacteria, solution pH, and existence of competitive heavy metals. In this study, Exiguobacterium sp. isolated from farmland soil near a mine site were used, and optimal conditions for Cd biosorption in solution were investigated. As bacterial growth progressed, Cd biosorption increased, which is attributed to changes in the structure and composition of the cell wall during bacterial growth. The biosorption process was rapid and was completed within 30 min. Cadmium biosorption was highest at pH 7 due to the dissociation of hydrogen ions and the increase of negative charges with increasing pH. In the mixed metal solution of Cd, Pb, and Zn, the amount of biosorption was in the order of Pb>Cd>Zn while in a single metal solution, the order was Cd≥Pb>Zn. The maximum adsorption capacity for Cd by the isolated bacteria was 15.6 mg/g biomass, which was calculated from the Langmuir isotherm model. Different adsorption efficiencies under various environmental conditions indicate that, to control metal mobility, the conditions for biosorption should be optimized before applying bacteria. The results showed that the isolated bacteria can be used to immobilize metals in metal-contaminated wastewater.

Biochemical responses of Gammarus pulex to malachite green solutions decolorized by Coriolus versicolor as a biosorbent under batch adsorption conditions optimized with response surface methodology.

PubMed

Yildirim, Nuran Cikcikoglu; Tanyol, Mehtap; Yildirim, Numan; Serdar, Osman; Tatar, Sule

2018-07-30

The current study was aimed to investigate the detoxifying and antioxidant enzyme response of Gammarus pulex exposed to malachite green (MG) after decolorization by Coriolus versicolor. Response surface methodology (RSM) was utilized to optimize the decolorization conditions of MG synthetic solutions by C. versicolor. Glutathione (GSH), malondialdehyde (MDA) levels and glutathione peroxidase (GP X ), catalase (CAT), superoxide dismutase (SOD), glutathione S-transferase (GST), cytochrome P450 1A1 (CYP1A1) activities in G. pulex exposed to undecolorized (A1) and decolorized (A2) MG synthetic solution during 24 and 96 h were tested by using ELISA method. SOD and GP X enzyme activity was increased after decolorization (p > 0.05). CAT enzyme activity was increased in A2 group during 24 h (p > 0.05) but decreased during 96 h (p < 0.05). GSH levels were increased in A2 group during 24 and 96 h (p < 0.05). GST, CYP1A1 enzyme activity and MDA levels were decreased after decolorization during 96 h (p < 0.05). In this study, GSH levels, CAT, GST and CYP1A1 activities in G. pulex approved the capability of C. versicolor in MG decolorization, optimized with RSM. Copyright © 2018 Elsevier Inc. All rights reserved.

A novel Fe(III) dependent bioflocculant from Klebsiella oxytoca GS-4-08: culture conditions optimization and flocculation mechanism

PubMed Central

Yu, Lei; Tang, Qing-wen; Zhang, Yu-jia; Chen, Rong-ping; Liu, Xin; Qiao, Wei-chuan; Li, Wen-wei; Ruan, Hong-hua; Song, Xin

2016-01-01

In this work, the effect of cultivation factors on the flocculation efficiency (FE) of bioflocculant P-GS408 from Klebsiella oxytoca was optimized by the response surface methodology. The most significant factor, i.e. culture time, was determined by gray relational analysis. A total of 240 mg of purified P-GS408 was prepared from 1 liter of culture solution under the optimal conditions. GC-MS analysis results indicated that the polysaccharide of P-GS408 mainly contains Rhamnose and Galactose, and the existence of abundant hydroxyl, carboxyl and amino groups was evidenced by FTIR and XPS analyses. With the aid of Fe3+, the FE of kaolin solution by P-GS408 could achieve 99.48% in ten minutes. Functional groups of polysaccharide were involved in the first adsorption step and the zeta potential of kaolin solution changed from −39.0 mV to 43.4 mV in the presence of Fe3+ and P-GS408. Three-dimensional excitation-emission (EEM) fluorescence spectra demonstrates that the trivalent Fe3+ and Al3+ can bind efficiently with P-GS408, while those univalent and divalent cations cannot. With the help of SEM images, FTIR, zeta potential and EEM spectra, we proposed the P-GS408 flocculation mechanism, which consists of coordination bond combination, charge neutrality, adsorption and bridging, and net catching. PMID:27713559

A novel Fe(III) dependent bioflocculant from Klebsiella oxytoca GS-4-08: culture conditions optimization and flocculation mechanism.

PubMed

Yu, Lei; Tang, Qing-Wen; Zhang, Yu-Jia; Chen, Rong-Ping; Liu, Xin; Qiao, Wei-Chuan; Li, Wen-Wei; Ruan, Hong-Hua; Song, Xin

2016-10-07

In this work, the effect of cultivation factors on the flocculation efficiency (FE) of bioflocculant P-GS408 from Klebsiella oxytoca was optimized by the response surface methodology. The most significant factor, i.e. culture time, was determined by gray relational analysis. A total of 240 mg of purified P-GS408 was prepared from 1 liter of culture solution under the optimal conditions. GC-MS analysis results indicated that the polysaccharide of P-GS408 mainly contains Rhamnose and Galactose, and the existence of abundant hydroxyl, carboxyl and amino groups was evidenced by FTIR and XPS analyses. With the aid of Fe 3+ , the FE of kaolin solution by P-GS408 could achieve 99.48% in ten minutes. Functional groups of polysaccharide were involved in the first adsorption step and the zeta potential of kaolin solution changed from -39.0 mV to 43.4 mV in the presence of Fe 3+ and P-GS408. Three-dimensional excitation-emission (EEM) fluorescence spectra demonstrates that the trivalent Fe 3+ and Al 3+ can bind efficiently with P-GS408, while those univalent and divalent cations cannot. With the help of SEM images, FTIR, zeta potential and EEM spectra, we proposed the P-GS408 flocculation mechanism, which consists of coordination bond combination, charge neutrality, adsorption and bridging, and net catching.

Three-Axis Time-Optimal Attitude Maneuvers of a Rigid-Body

NASA Astrophysics Data System (ADS)

Wang, Xijing; Li, Jisheng

With the development trends for modern satellites towards macro-scale and micro-scale, new demands are requested for its attitude adjustment. Precise pointing control and rapid maneuvering capabilities have long been part of many space missions. While the development of computer technology enables new optimal algorithms being used continuously, a powerful tool for solving problem is provided. Many papers about attitude adjustment have been published, the configurations of the spacecraft are considered rigid body with flexible parts or gyrostate-type systems. The object function always include minimum time or minimum fuel. During earlier satellite missions, the attitude acquisition was achieved by using the momentum ex change devices, performed by a sequential single-axis slewing strategy. Recently, the simultaneous three-axis minimum-time maneuver(reorientation) problems have been studied by many researchers. It is important to research the minimum-time maneuver of a rigid spacecraft within onboard power limits, because of potential space application such as surveying multiple targets in space and academic value. The minimum-time maneuver of a rigid spacecraft is a basic problem because the solutions for maneuvering flexible spacecraft are based on the solution to the rigid body slew problem. A new method for the open-loop solution for a rigid spacecraft maneuver is presented. Having neglected all perturbation torque, the necessary conditions of spacecraft from one state to another state can be determined. There is difference between single-axis with multi-axis. For single- axis analytical solution is possible and the switching line passing through the state-space origin belongs to parabolic. For multi-axis, it is impossible to get analytical solution due to the dynamic coupling between the axes and must be solved numerically. Proved by modern research, Euler axis rotations are quasi-time-optimal in general. On the basis of minimum value principles, a research for reorienting an inertial syrnmetric spacecraft with time cost function from an initial state of rest to a final state of rest is deduced. And the solution to it is stated below: Firstly, the essential condition for solving the problem is deduced with the minimum value principle. The necessary conditions for optimality yield a two point boundary-value problem (TPBVP), which, when solved, produces the control history that minimize time performance index. In the nonsingular control, the solution is the' bang-bang maneuver. The control profile is characterized by Saturated controls for the entire maneuver. The singular control maybe existed. It is only singular in mathematics. According to physical principle, the bigger the mode of the control torque is, the shorter the time is. So saturated controls are used in singular control. Secondly, the control parameters are always in maximum, so the key problem is to determine switch point thus original problem is changed to find the changing time. By the use of adjusting the switch on/off time, the genetic algorithm, which is a new robust method is optimized to determine the switch features without the gyroscopic coupling. There is improvement upon the traditional GA in this research. The homotopy method to find the nonlinear algebra is based on rigorous topology continuum theory. Based on the idea of the homotopy, the relaxation parameters are introduced, and the switch point is figured out with simulated annealing. Computer simulation results using a rigid body show that the new method is feasible and efficient. A practical method of computing approximate solutions to the time-optimal control- switch times for rigid body reorientation has been developed.

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks.

PubMed

Samal, Areejit

2008-12-01

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.

Application of shifted Jacobi pseudospectral method for solving (in)finite-horizon min-max optimal control problems with uncertainty

NASA Astrophysics Data System (ADS)

Nikooeinejad, Z.; Delavarkhalafi, A.; Heydari, M.

2018-03-01

The difficulty of solving the min-max optimal control problems (M-MOCPs) with uncertainty using generalised Euler-Lagrange equations is caused by the combination of split boundary conditions, nonlinear differential equations and the manner in which the final time is treated. In this investigation, the shifted Jacobi pseudospectral method (SJPM) as a numerical technique for solving two-point boundary value problems (TPBVPs) in M-MOCPs for several boundary states is proposed. At first, a novel framework of approximate solutions which satisfied the split boundary conditions automatically for various boundary states is presented. Then, by applying the generalised Euler-Lagrange equations and expanding the required approximate solutions as elements of shifted Jacobi polynomials, finding a solution of TPBVPs in nonlinear M-MOCPs with uncertainty is reduced to the solution of a system of algebraic equations. Moreover, the Jacobi polynomials are particularly useful for boundary value problems in unbounded domain, which allow us to solve infinite- as well as finite and free final time problems by domain truncation method. Some numerical examples are given to demonstrate the accuracy and efficiency of the proposed method. A comparative study between the proposed method and other existing methods shows that the SJPM is simple and accurate.

Improving alachlor biodegradability by ferrate oxidation.

PubMed

Zhu, Jian-Hang; Yan, Xi-Luan; Liu, Ye; Zhang, Bao

2006-07-31

Alachlor can be recalcitrant when present at high concentrations in wastewater. Ferrate oxidation was used as a pretreatment to improve its biodegradability and was evaluated by monitoring alachlor elimination and removal of COD(Cr) (chemical oxygen demand determined by potassium dichromate) during the oxidation process up to a value compatible with biological treatment. Ferrate oxidation resulted in elimination of alachlor followed by degradation of its intermediates. High pH suppressed alachlor removal and COD(Cr) removal due to the low redox potential of ferrate ions. Although alachlor can be totally eliminated within 10 min under optimized conditions (alachlor, 40 mg l(-1); ferrate:alachlor molar ratio, 2; and pH 7.0), its complete mineralization cannot be achieved by ferrate oxidation alone. Alachlor solution treated by ferrate for 10 min inhibited an up-flow biotreatment with activated sludge. The biodegradability of ferrate-pretreated solution improved when the treatment was increased to 20 min, at the point of which BOD(5)/COD(Cr) ratio of the treated solution was increased to 0.87 from 0.35 after 10 min treatment. Under optimized conditions, ferrate oxidation for 20 min resulted in total elimination of alachlor, partial removal of COD(Cr) and the ferrate-treated solution could be effectively treated by the up-flow activated sludge process.

Preparation of starch-poly-glutamic acid graft copolymers by microwave irradiation and the characterization of their properties

USDA-ARS?s Scientific Manuscript database

Graft copolymers of waxy maize starch and poly-y-glutamic acid (PGA) were produced in an aqueous solution using microwave irradiation. The microwave reaction conditions were optimized with regard to temperature and pH. The temperature of 180 deg C and pH 7.0 were the best reaction conditions resulti...

Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.

PubMed

2018-01-04

An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.

A coupling strategy for nonlocal and local diffusion models with mixed volume constraints and boundary conditions

DOE PAGES

D'Elia, Marta; Perego, Mauro; Bochev, Pavel B.; ...

2015-12-21

We develop and analyze an optimization-based method for the coupling of nonlocal and local diffusion problems with mixed volume constraints and boundary conditions. The approach formulates the coupling as a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the nonlocal and local domains, and the controls are virtual volume constraints and boundary conditions. When some assumptions on the kernel functions hold, we prove that the resulting optimization problem is well-posed and discuss its implementation using Sandia’s agile software components toolkit. As a result,more » the latter provides the groundwork for the development of engineering analysis tools, while numerical results for nonlocal diffusion in three-dimensions illustrate key properties of the optimization-based coupling method.« less

Optimal Harvesting in a Periodic Food Chain Model with Size Structures in Predators

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

Zhang, Feng-Qin, E-mail: zhafq@263.net; Liu, Rong; Chen, Yuming, E-mail: ychen@wlu.ca

In this paper, we investigate a periodic food chain model with harvesting, where the predators have size structures and are described by first-order partial differential equations. First, we establish the existence of a unique non-negative solution by using the Banach fixed point theorem. Then, we provide optimality conditions by means of normal cone and adjoint system. Finally, we derive the existence of an optimal strategy by means of Ekeland’s variational principle. Here the objective functional represents the net economic benefit yielded from harvesting.

Optimal multiple-pass aeroassisted plane change

NASA Technical Reports Server (NTRS)

Vinh, Nguyen X.; Ma, Der-Ming

1990-01-01

This paper presents the exact dimensionless equation of motion and the necessary conditions for the computation of the optimal trajectories of a hypervelocity vehicle flying through a non-rotating spherical planetary atmosphere. Numerical solution is then presented for the case when the vehicle makes several passages through the atmosphere near the perigee of its orbit. While the orbit is slowly contracting, aerodynamic maneuver is performed to obtain the maximum plane change. Several plots were presented to show the optimal variations of the lift coefficient and the bank angle and the various elements of the orbit.

A novel neural network for variational inequalities with linear and nonlinear constraints.

PubMed

Gao, Xing-Bao; Liao, Li-Zhi; Qi, Liqun

2005-11-01

Variational inequality is a uniform approach for many important optimization and equilibrium problems. Based on the sufficient and necessary conditions of the solution, this paper presents a novel neural network model for solving variational inequalities with linear and nonlinear constraints. Three sufficient conditions are provided to ensure that the proposed network with an asymmetric mapping is stable in the sense of Lyapunov and converges to an exact solution of the original problem. Meanwhile, the proposed network with a gradient mapping is also proved to be stable in the sense of Lyapunov and to have a finite-time convergence under some mild condition by using a new energy function. Compared with the existing neural networks, the new model can be applied to solve some nonmonotone problems, has no adjustable parameter, and has lower complexity. Thus, the structure of the proposed network is very simple. Since the proposed network can be used to solve a broad class of optimization problems, it has great application potential. The validity and transient behavior of the proposed neural network are demonstrated by several numerical examples.

Design of a compensation for an ARMA model of a discrete time system. M.S. Thesis

NASA Technical Reports Server (NTRS)

Mainemer, C. I.

1978-01-01

The design of an optimal dynamic compensator for a multivariable discrete time system is studied. Also the design of compensators to achieve minimum variance control strategies for single input single output systems is analyzed. In the first problem the initial conditions of the plant are random variables with known first and second order moments, and the cost is the expected value of the standard cost, quadratic in the states and controls. The compensator is based on the minimum order Luenberger observer and it is found optimally by minimizing a performance index. Necessary and sufficient conditions for optimality of the compensator are derived. The second problem is solved in three different ways; two of them working directly in the frequency domain and one working in the time domain. The first and second order moments of the initial conditions are irrelevant to the solution. Necessary and sufficient conditions are derived for the compensator to minimize the variance of the output.

Bayer Digester Optimization Studies using Computer Techniques

NASA Astrophysics Data System (ADS)

Kotte, Jan J.; Schleider, Victor H.

Theoretically required heat transfer performance by the multistaged flash heat reclaim system of a high pressure Bayer digester unit is determined for various conditions of discharge temperature, excess flash vapor and indirect steam addition. Solution of simultaneous heat balances around the digester vessels and the heat reclaim system yields the magnitude of available heat for representation of each case on a temperature-enthalpy diagram, where graphical fit of the number of flash stages fixes the heater requirements. Both the heat balances and the trial-and-error graphical solution are adapted to solution by digital computer techniques.

[Newly leaching method of copper from waste print circuit board using hydrochloric acid/n-butylamine/copper sulfate].

PubMed

Wang, Hong-Yan; Cui, Zhao-Jie; Yao, Ya-Wei

2010-12-01

A newly leaching method of copper from waste print circuit board was established by using hydrochloric acid-n-butylamine-copper sulfate mixed solution. The conditions of leaching were optimized by changing the hydrochloric acid, n-butylamine, copper sulfate,temperature and other conditions using copper as target mimics. The results indicated that copper could be leached completely after 8 h at 50 degrees C, hydrochloric acid concentration of 1.75 mol/L, n-butylamine concentration of 0.25 mol/L, and copper sulfate mass of 0.96 g. Under the conditions, copper leaching rates in waste print circuit board samples was up to 95.31% after 9 h. It has many advantages such as better effects, low cost, mild reaction conditions, leaching solution recycling.

A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process

NASA Astrophysics Data System (ADS)

Khalilpourazari, Soheyl; Khalilpourazary, Saman

2017-05-01

In this article a multi-objective mathematical model is developed to minimize total time and cost while maximizing the production rate and surface finish quality in the grinding process. The model aims to determine optimal values of the decision variables considering process constraints. A lexicographic weighted Tchebycheff approach is developed to obtain efficient Pareto-optimal solutions of the problem in both rough and finished conditions. Utilizing a polyhedral branch-and-cut algorithm, the lexicographic weighted Tchebycheff model of the proposed multi-objective model is solved using GAMS software. The Pareto-optimal solutions provide a proper trade-off between conflicting objective functions which helps the decision maker to select the best values for the decision variables. Sensitivity analyses are performed to determine the effect of change in the grain size, grinding ratio, feed rate, labour cost per hour, length of workpiece, wheel diameter and downfeed of grinding parameters on each value of the objective function.

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

Contribution to the optimal shape design of two-dimensional internal flows with embedded shocks

NASA Technical Reports Server (NTRS)

Iollo, Angelo; Salas, Manuel D.

1995-01-01

We explore the practicability of optimal shape design for flows modeled by the Euler equations. We define a functional whose minimum represents the optimality condition. The gradient of the functional with respect to the geometry is calculated with the Lagrange multipliers, which are determined by solving a co-state equation. The optimization problem is then examined by comparing the performance of several gradient-based optimization algorithms. In this formulation, the flow field can be computed to an arbitrary order of accuracy. Finally, some results for internal flows with embedded shocks are presented, including a case for which the solution to the inverse problem does not belong to the design space.

Method and system for fault accommodation of machines

NASA Technical Reports Server (NTRS)

Goebel, Kai Frank (Inventor); Subbu, Rajesh Venkat (Inventor); Rausch, Randal Thomas (Inventor); Frederick, Dean Kimball (Inventor)

2011-01-01

A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

The degradation of wheat straw lignin

NASA Astrophysics Data System (ADS)

Liang, Jiaqi

2017-03-01

Lignin is a kind of formed by polymerization of aromatic alcohol, prices are lower and sources of renewable resources. Using lignin as raw material, through the push to resolve together preparation phenolic high value-added fine chemicals alkanes and aromatic hydrocarbons, such as the high grade biofuels, can partly replace fossil fuels as raw material to the production process, biomass resources is an important part of the comprehensive utilization of effective components. In lignin push solve clustering method, catalytic hydrogenolysis can directly to the lignin into liquid fuels, low oxygen content in the use of biofuels shows great potential. In this paper, through the optimization of the reaction time, reaction temperature, catalyst type and solvent type, dosage of catalyst, etc factors, determines the alcoholysis - hydrogen solution two-step degradation of lignin, the optimal process conditions: lignin alcoholysis under 50% methanol and NaOH catalyst in the solution, the lignin in methanol solution and 50% hydrogen solution under the Pd/C catalyst. In this process, the degradation of lignin yield can reach 42%.

The Promise of Macromolecular Crystallization in Micro-fluidic Chips

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark; Ferree, Darren; Pusey, Marc

2003-01-01

Micro-fluidics, or lab on a chip technology, is proving to be a powerful, rapid, and efficient approach to a wide variety of bio-analytical and microscale bio-preparative needs. The low materials consumption, combined with the potential for packing a large number of experiments in a few cubic centimeters, makes it an attractive technique for both initial screening and subsequent optimization of macromolecular crystallization conditions. Screening operations, which require equilibrating macromolecule solution with a standard set of premixed solutions, are relatively straightforward and have been successfully demonstrated in a micro-fluidics platform. More complex optimization methods, where crystallization solutions are independently formulated from a range of stock solutions, are considerably more complex and have yet to be demonstrated. To be competitive with either approach, a micro-fluidics system must offer ease of operation, be able to maintain a sealed environment over several weeks to months, and give ready access for the observation of crystals as they are grown.

Genetic Algorithm Optimizes Q-LAW Control Parameters

NASA Technical Reports Server (NTRS)

Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard

2008-01-01

A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Automated Generation of Finite-Element Meshes for Aircraft Conceptual Design

NASA Technical Reports Server (NTRS)

Li, Wu; Robinson, Jay

2016-01-01

This paper presents a novel approach for automated generation of fully connected finite-element meshes for all internal structural components and skins of a given wing-body geometry model, controlled by a few conceptual-level structural layout parameters. Internal structural components include spars, ribs, frames, and bulkheads. Structural layout parameters include spar/rib locations in wing chordwise/spanwise direction and frame/bulkhead locations in longitudinal direction. A simple shell thickness optimization problem with two load conditions is used to verify versatility and robustness of the automated meshing process. The automation process is implemented in ModelCenter starting from an OpenVSP geometry and ending with a NASTRAN 200 solution. One subsonic configuration and one supersonic configuration are used for numerical verification. Two different structural layouts are constructed for each configuration and five finite-element meshes of different sizes are generated for each layout. The paper includes various comparisons of solutions of 20 thickness optimization problems, as well as discussions on how the optimal solutions are affected by the stress constraint bound and the initial guess of design variables.

Evaluation of experimental parameters for growth of homogeneous solid solutions

NASA Astrophysics Data System (ADS)

Scheel, Hans J.; Swendsen, Robert H.

2001-12-01

In this paper, we discuss the experimental conditions required to grow large two-component crystals from homogeneous solid solutions. Building on the work of Burton, Prim, and Slichter and that of Van Erk, we are able to establish that the concentration fluctuations for diffusion-limited growth are rather insensitive to hydrodynamic fluctuations. This enables a crystal grower to take advantage of forced convection to optimize growth rates without aggravating the striation problem.

Removal of Zinc from Aqueous Solution by Optimized Oil Palm Empty Fruit Bunches Biochar as Low Cost Adsorbent

PubMed Central

Salleh, M. A. Mohd; Asady, Bahareh

2017-01-01

This study aims to produce optimized biochar from oil palm empty fruit bunches (OPEFB), as a green, low cost adsorbent for uptake of zinc from aqueous solution. The impact of pyrolysis conditions, namely, highest treatment temperature (HTT), heating rate (HR), and residence time (RT) on biochar yield and adsorption capacity towards zinc, was investigated. Mathematical modeling and optimization of independent variables were performed employing response surface methodology (RSM). HTT was found to be the most influential variable, followed by residence time and heating rate. Based on the central composite design (CCD), two quadratic models were developed to correlate three independent variables to responses. The optimum production condition for OPEFB biochar was found as follows: HTT of 615°C, HR of 8°C/min, and RT of 128 minutes. The optimum biochar showed 15.18 mg/g adsorption capacity for zinc and 25.49% of yield which was in agreement with the predicted values, satisfactory. Results of the characterization of optimum product illustrated well-developed BET surface area and porous structure in optimum product which favored its sorptive ability. PMID:28420949

A robust ordering strategy for retailers facing a free shipping option.

PubMed

Meng, Qing-chun; Wan, Xiao-le; Rong, Xiao-xia

2015-01-01

Free shipping with conditions has become one of the most effective marketing tools available. An increasing number of companies, especially e-businesses, prefer to offer free shipping with some predetermined condition, such as a minimum purchase amount by the customer. However, in practice, the demands of buyers are uncertain; they are often affected by many factors, such as the weather and season. We begin by modeling the centralized ordering problem in which the supplier offers a free shipping service and retailers face stochastic demands. As these random data are considered, only partial information such as the known mean, support, and deviation is needed. The model is then analyzed via a robust optimization method, and the two types of equivalent sets of uncertainty constraints that are obtained provide good mathematical properties with consideration of the robustness of solutions. Subsequently, a numerical example is used to compare the results achieved from a robust optimization method and the linear decision rules. Additionally, the robustness of the optimal solution is discussed, as it is affected by the minimum quantity parameters. The increasing cost-threshold relationship is divided into three periods. In addition, the case study shows that the proposed method achieves better stability as well as computational complexity.

LC-MS determination of steroidal glycosides from Dioscorea deltoidea Wall cell suspension culture: Optimization of pre-LC-MS procedure parameters by Latin Square design.

PubMed

Sarvin, Boris; Fedorova, Elizaveta; Shpigun, Oleg; Titova, Maria; Nikitin, Mikhail; Kochkin, Dmitry; Rodin, Igor; Stavrianidi, Andrey

2018-03-30

In this paper, the ultrasound assisted extraction method for isolation of steroidal glycosides from D. deltoidea plant cell suspension culture with a subsequent HPLC-MS determination was developed. After the organic solvent was selected via a two-factor experiment the optimization via Latin Square 4 × 4 experimental design was carried out for the following parameters: extraction time, organic solvent concentration in extraction solution and the ratio of solvent to sample. It was also shown that the ultrasound assisted extraction method is not suitable for isolation of steroidal glycosides from the D. deltoidea plant material. The results were double-checked using the multiple successive extraction method and refluxing extraction. Optimal conditions for the extraction of steroidal glycosides by the ultrasound assisted extraction method were: extraction time, 60 min; acetonitrile (water) concentration in extraction solution, 50%; the ratio of solvent to sample, 400 mL/g. Also, the developed method was tested on D. deltoidea cell suspension cultures of different terms and conditions of cultivation. The completeness of the extraction was confirmed using the multiple successive extraction method. Copyright © 2018 Elsevier B.V. All rights reserved.

A simplified counter diffusion method combined with a 1D simulation program for optimizing crystallization conditions.

PubMed

Tanaka, Hiroaki; Inaka, Koji; Sugiyama, Shigeru; Takahashi, Sachiko; Sano, Satoshi; Sato, Masaru; Yoshitomi, Susumu

2004-01-01

We developed a new protein crystallization method has been developed using a simplified counter-diffusion method for optimizing crystallization condition. It is composed of only a single capillary, the gel in the silicon tube and the screw-top test tube, which are readily available in the laboratory. The one capillary can continuously scan a wide range of crystallization conditions (combination of the concentrations of the precipitant and the protein) unless crystallization occurs, which means that it corresponds to many drops in the vapor-diffusion method. The amount of the precipitant and the protein solutions can be much less than in conventional methods. In this study, lysozyme and alpha-amylase were used as model proteins for demonstrating the efficiency of this method. In addition, one-dimensional (1-D) simulations of the crystal growth were performed based on the 1-D diffusion model. The optimized conditions can be applied to the initial crystallization conditions for both other counter-diffusion methods with the Granada Crystallization Box (GCB) and for the vapor-diffusion method after some modification.

Process optimization for osmo-dehydrated carambola (Averrhoa carambola L) slices and its storage studies.

PubMed

Roopa, N; Chauhan, O P; Raju, P S; Das Gupta, D K; Singh, R K R; Bawa, A S

2014-10-01

An osmotic-dehydration process protocol for Carambola (Averrhoacarambola L.,), an exotic star shaped tropical fruit, was developed. The process was optimized using Response Surface Methodology (RSM) following Central Composite Rotatable Design (CCRD). The experimental variables selected for the optimization were soak solution concentration (°Brix), soaking temperature (°C) and soaking time (min) with 6 experiments at central point. The effect of process variables was studied on solid gain and water loss during osmotic dehydration process. The data obtained were analyzed employing multiple regression technique to generate suitable mathematical models. Quadratic models were found to fit well (R(2), 95.58 - 98.64 %) in describing the effect of variables on the responses studied. The optimized levels of the process variables were achieved at 70°Brix, 48 °C and 144 min for soak solution concentration, soaking temperature and soaking time, respectively. The predicted and experimental results at optimized levels of variables showed high correlation. The osmo-dehydrated product prepared at optimized conditions showed a shelf-life of 10, 8 and 6 months at 5 °C, ambient (30 ± 2 °C) and 37 °C, respectively.

Bernoulli substitution in the Ramsey model: Optimal trajectories under control constraints

NASA Astrophysics Data System (ADS)

Krasovskii, A. A.; Lebedev, P. D.; Tarasyev, A. M.

2017-05-01

We consider a neoclassical (economic) growth model. A nonlinear Ramsey equation, modeling capital dynamics, in the case of Cobb-Douglas production function is reduced to the linear differential equation via a Bernoulli substitution. This considerably facilitates the search for a solution to the optimal growth problem with logarithmic preferences. The study deals with solving the corresponding infinite horizon optimal control problem. We consider a vector field of the Hamiltonian system in the Pontryagin maximum principle, taking into account control constraints. We prove the existence of two alternative steady states, depending on the constraints. A proposed algorithm for constructing growth trajectories combines methods of open-loop control and closed-loop regulatory control. For some levels of constraints and initial conditions, a closed-form solution is obtained. We also demonstrate the impact of technological change on the economic equilibrium dynamics. Results are supported by computer calculations.

Stochastic Optimal Control via Bellman's Principle

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Sun, Jian Q.

2003-01-01

This paper presents a method for finding optimal controls of nonlinear systems subject to random excitations. The method is capable to generate global control solutions when state and control constraints are present. The solution is global in the sense that controls for all initial conditions in a region of the state space are obtained. The approach is based on Bellman's Principle of optimality, the Gaussian closure and the Short-time Gaussian approximation. Examples include a system with a state-dependent diffusion term, a system in which the infinite hierarchy of moment equations cannot be analytically closed, and an impact system with a elastic boundary. The uncontrolled and controlled dynamics are studied by creating a Markov chain with a control dependent transition probability matrix via the Generalized Cell Mapping method. In this fashion, both the transient and stationary controlled responses are evaluated. The results show excellent control performances.

Optical enhancement of a printed organic tandem solar cell using diffractive nanostructures.

PubMed

Mayer, Jan A; Offermans, Ton; Chrapa, Marek; Pfannmöller, Martin; Bals, Sara; Ferrini, Rolando; Nisato, Giovanni

2018-03-19

Solution processable organic tandem solar cells offer a promising approach to achieve cost-effective, lightweight and flexible photovoltaics. In order to further enhance the efficiency of optimized organic tandem cells, diffractive light-management nanostructures were designed for an optimal redistribution of the light as function of both wavelength and propagation angles in both sub-cells. As the fabrication of these optical structures is compatible with roll-to-roll production techniques such as hot-embossing or UV NIL imprinting, they present an optimal cost-effective solution for printed photovoltaics. Tandem cells with power conversion efficiencies of 8-10% were fabricated in the ambient atmosphere by doctor blade coating, selected to approximate the conditions during roll-to-roll manufacturing. Application of the light management structure onto an 8.7% efficient encapsulated tandem cell boosted the conversion efficiency of the cell to 9.5%.

Combinatorial optimization games

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

Deng, X.; Ibaraki, Toshihide; Nagamochi, Hiroshi

1997-06-01

We introduce a general integer programming formulation for a class of combinatorial optimization games, which immediately allows us to improve the algorithmic result for finding amputations in the core (an important solution concept in cooperative game theory) of the network flow game on simple networks by Kalai and Zemel. An interesting result is a general theorem that the core for this class of games is nonempty if and only if a related linear program has an integer optimal solution. We study the properties for this mathematical condition to hold for several interesting problems, and apply them to resolve algorithmic andmore » complexity issues for their cores along the line as put forward in: decide whether the core is empty; if the core is empty, find an imputation in the core; given an imputation x, test whether x is in the core. We also explore the properties of totally balanced games in this succinct formulation of cooperative games.« less

An Optimized Analytical Method for the Simultaneous Detection of Iodoform, Iodoacetic Acid, and Other Trihalomethanes and Haloacetic Acids in Drinking Water

PubMed Central

Jiang, Songhui; Templeton, Michael R.; He, Gengsheng; Qu, Weidong

2013-01-01

An optimized method is presented using liquid-liquid extraction and derivatization for the extraction of iodoacetic acid (IAA) and other haloacetic acids (HAA9) and direct extraction of iodoform (IF) and other trihalomethanes (THM4) from drinking water, followed by detection by gas chromatography with electron capture detection (GC-ECD). A Doehlert experimental design was performed to determine the optimum conditions for the five most significant factors in the derivatization step: namely, the volume and concentration of acidic methanol (optimized values  = 15%, 1 mL), the volume and concentration of Na2SO4 solution (129 g/L, 8.5 mL), and the volume of saturated NaHCO3 solution (1 mL). Also, derivatization time and temperature were optimized by a two-variable Doehlert design, resulting in the following optimized parameters: an extraction time of 11 minutes for IF and THM4 and 14 minutes for IAA and HAA9; mass of anhydrous Na2SO4 of 4 g for IF and THM4 and 16 g for IAA and HAA9; derivatization time of 160 min and temperature at 40°C. Under optimal conditions, the optimized procedure achieves excellent linearity (R2 ranges 0.9990–0.9998), low detection limits (0.0008–0.2 µg/L), low quantification limits (0.008–0.4 µg/L), and good recovery (86.6%–106.3%). Intra- and inter-day precision were less than 8.9% and 8.8%, respectively. The method was validated by applying it to the analysis of raw, flocculated, settled, and finished waters collected from a water treatment plant in China. PMID:23613747

Space-planning and structural solutions of low-rise buildings: Optimal selection methods

NASA Astrophysics Data System (ADS)

Gusakova, Natalya; Minaev, Nikolay; Filushina, Kristina; Dobrynina, Olga; Gusakov, Alexander

2017-11-01

The present study is devoted to elaboration of methodology used to select appropriately the space-planning and structural solutions in low-rise buildings. Objective of the study is working out the system of criteria influencing the selection of space-planning and structural solutions which are most suitable for low-rise buildings and structures. Application of the defined criteria in practice aim to enhance the efficiency of capital investments, energy and resource saving, create comfortable conditions for the population considering climatic zoning of the construction site. Developments of the project can be applied while implementing investment-construction projects of low-rise housing at different kinds of territories based on the local building materials. The system of criteria influencing the optimal selection of space-planning and structural solutions of low-rise buildings has been developed. Methodological basis has been also elaborated to assess optimal selection of space-planning and structural solutions of low-rise buildings satisfying the requirements of energy-efficiency, comfort and safety, and economical efficiency. Elaborated methodology enables to intensify the processes of low-rise construction development for different types of territories taking into account climatic zoning of the construction site. Stimulation of low-rise construction processes should be based on the system of approaches which are scientifically justified; thus it allows enhancing energy efficiency, comfort, safety and economical effectiveness of low-rise buildings.

Ultrasonic-assisted synthesis of superabsorbent hydrogels based on sodium lignosulfonate and their adsorption properties for Ni2.

PubMed

Wang, Xiaohong; Wang, Yingying; He, Shufu; Hou, Haiqian; Hao, Chen

2018-01-01

Nowadays, the attention of both academic and industrial research is paid to the novel materials based on renewable organic resources. Sodium lignosulphonate (SLS) is selected in this study to synthesize novel superabsorbent hydrogels by ultrasonic polymerization. The structure, morphology and stability of SLS-based hydrogel were confirmed by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). Under the optimal condition, SLS-based hydrogel possesses the water absorbency of 1328g·g -1 in distilled water and 110g·g -1 in 0.9wt% NaCl solution. In addition, the prepared SLS-hydrogel as an adsorbent was applied to remove Ni 2+ from an aqueous solution in virtue of its low cost and favorable adsorption capacity. The various experimental conditions that influence the adsorption capacity were investigated such as temperature (20-60°C), pH (2.0-7.0), contact time (0-360min) and initial concentration of the Ni 2+ solution (100-600mg·L -1 ). Then the adsorption capability could reach 293mg·g -1 under optimal conditions. The results revealed that the adsorption behavior is spontaneous and endothermic. Furthermore, it was observed that the adsorption mechanism and adsorption equilibrium data obeyed pseudo-second-order kinetic and Freundlich models. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework.

PubMed

Yang, Guoxiang; Best, Elly P H

2015-09-15

Best management practices (BMPs) can be used effectively to reduce nutrient loads transported from non-point sources to receiving water bodies. However, methodologies of BMP selection and placement in a cost-effective way are needed to assist watershed management planners and stakeholders. We developed a novel modeling-optimization framework that can be used to find cost-effective solutions of BMP placement to attain nutrient load reduction targets. This was accomplished by integrating a GIS-based BMP siting method, a WQM-TMDL-N modeling approach to estimate total nitrogen (TN) loading, and a multi-objective optimization algorithm. Wetland restoration and buffer strip implementation were the two BMP categories used to explore the performance of this framework, both differing greatly in complexity of spatial analysis for site identification. Minimizing TN load and BMP cost were the two objective functions for the optimization process. The performance of this framework was demonstrated in the Tippecanoe River watershed, Indiana, USA. Optimized scenario-based load reduction indicated that the wetland subset selected by the minimum scenario had the greatest N removal efficiency. Buffer strips were more effective for load removal than wetlands. The optimized solutions provided a range of trade-offs between the two objective functions for both BMPs. This framework can be expanded conveniently to a regional scale because the NHDPlus catchment serves as its spatial computational unit. The present study demonstrated the potential of this framework to find cost-effective solutions to meet a water quality target, such as a 20% TN load reduction, under different conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Validation of a stability-indicating hydrophilic interaction liquid chromatographic method for the quantitative determination of vitamin k3 (menadione sodium bisulfite) in injectable solution formulation.

PubMed

Ghanem, Mashhour M; Abu-Lafi, Saleh A; Hallak, Hussein O

2013-01-01

A simple, specific, accurate, and stability-indicating method was developed and validated for the quantitative determination of menadione sodium bisulfite in the injectable solution formulation. The method is based on zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) coupled with a photodiode array detector. The desired separation was achieved on the ZIC-HILIC column (250 mm × 4.6 mm, 5 μm) at 25°C temperature. The optimized mobile phase consisted of an isocratic solvent mixture of 200mM ammonium acetate (NH4AC) solution and acetonitrile (ACN) (20:80; v/v) pH-adjusted to 5.7 by glacial acetic acid. The mobile phase was fixed at 0.5 ml/min and the analytes were monitored at 261 nm using a photodiode array detector. The effects of the chromatographic conditions on the peak retention, peak USP tailing factor, and column efficiency were systematically optimized. Forced degradation experiments were carried out by exposing menadione sodium bisulfite standard and the injectable solution formulation to thermal, photolytic, oxidative, and acid-base hydrolytic stress conditions. The degradation products were well-resolved from the main peak and the excipients, thus proving that the method is a reliable, stability-indicating tool. The method was validated as per ICH and USP guidelines (USP34/NF29) and found to be adequate for the routine quantitative estimation of menadione sodium bisulfite in commercially available menadione sodium bisulfite injectable solution dosage forms.

Influence of oxalic acid on the dissolution kinetics of manganese oxide

NASA Astrophysics Data System (ADS)

Godunov, E. B.; Artamonova, I. V.; Gorichev, I. G.; Lainer, Yu. A.

2012-11-01

The kinetics and electrochemical processes of the dissolution of manganese oxides with various oxidation states in sulfuric acid solutions containing oxalate ion additives is studied under variable conditions (concentration, pH, temperature). The parameters favoring a higher degree of the dissolution of manganese oxides in acidic media are determined. The optimal conditions are found for the dissolution of manganese oxides in acidic media in the presence of oxalate ions. The mechanism proposed for the dissolution of manganese oxides in sulfuric acid solutions containing oxalic acid is based on the results of kinetic and electrochemical studies. The steps of the dissolution mechanism are discussed.

Improved distorted wave theory with the localized virial conditions

NASA Astrophysics Data System (ADS)

Hahn, Y. K.; Zerrad, E.

2009-12-01

The distorted wave theory is operationally improved to treat the full collision amplitude, such that the corrections to the distorted wave Born amplitude can be systematically calculated. The localized virial conditions provide the tools necessary to test the quality of successive approximations at each stage and to optimize the solution. The details of the theoretical procedure are explained in concrete terms using a collisional ionization model and variational trial functions. For the first time, adjustable parameters associated with an approximate scattering solution can be fully determined by the theory. A small number of linear parameters are introduced to examine the convergence property and the effectiveness of the new approach.

A new real-time guidance strategy for aerodynamic ascent flight

NASA Astrophysics Data System (ADS)

Yamamoto, Takayuki; Kawaguchi, Jun'ichiro

2007-12-01

Reusable launch vehicles are conceived to constitute the future space transportation system. If these vehicles use air-breathing propulsion and lift taking-off horizontally, the optimal steering for these vehicles exhibits completely different behavior from that in conventional rockets flight. In this paper, the new guidance strategy is proposed. This method derives from the optimality condition as for steering and an analysis concludes that the steering function takes the form comprised of Linear and Logarithmic terms, which include only four parameters. The parameter optimization of this method shows the acquired terminal horizontal velocity is almost same with that obtained by the direct numerical optimization. This supports the parameterized Liner Logarithmic steering law. And here is shown that there exists a simple linear relation between the terminal states and the parameters to be corrected. The relation easily makes the parameters determined to satisfy the terminal boundary conditions in real-time. The paper presents the guidance results for the practical application cases. The results show the guidance is well performed and satisfies the terminal boundary conditions specified. The strategy built and presented here does guarantee the robust solution in real-time excluding any optimization process, and it is found quite practical.

Optimized assembly and covalent coupling of single-molecule DNA origami nanoarrays.

PubMed

Gopinath, Ashwin; Rothemund, Paul W K

2014-12-23

Artificial DNA nanostructures, such as DNA origami, have great potential as templates for the bottom-up fabrication of both biological and nonbiological nanodevices at a resolution unachievable by conventional top-down approaches. However, because origami are synthesized in solution, origami-templated devices cannot easily be studied or integrated into larger on-chip architectures. Electrostatic self-assembly of origami onto lithographically defined binding sites on Si/SiO2 substrates has been achieved, but conditions for optimal assembly have not been characterized, and the method requires high Mg2+ concentrations at which most devices aggregate. We present a quantitative study of parameters affecting origami placement, reproducibly achieving single-origami binding at 94±4% of sites, with 90% of these origami having an orientation within ±10° of their target orientation. Further, we introduce two techniques for converting electrostatic DNA-surface bonds to covalent bonds, allowing origami arrays to be used under a wide variety of Mg2+-free solution conditions.

Optimized water vapor permeability of sodium alginate films using response surface methodology

NASA Astrophysics Data System (ADS)

Zhang, Qing; Xu, Jiachao; Gao, Xin; Fu, Xiaoting

2013-11-01

The water vapor permeability (WVP) of films is important when developing pharmaceutical applications. Films are frequently used as coatings, and as such directly influence the quality of the medicine. The optimization of processing conditions for sodium alginate films was investigated using response surface methodology. Single-factor tests and Box-Behnken experimental design were employed. WVP was selected as the response variable, and the operating parameters for the single-factor tests were sodium alginate concentration, carboxymethyl cellulose (CMC) concentration and CaCl2 solution immersion time. The coefficient of determination ( R 2) was 0.97, indicating statistical significance. A minimal WVP of 0.389 8 g·mm/(m2·h·kPa) was achieved under the optimum conditions. These were found to be a sodium alginate concentration, CMC concentration and CaCl2 solution immersion time at 8.04%, 0.13%, and 12 min, respectively. This provides a reference for potential applications in manufacturing film-coated hard capsule shells.

The effect of agency budgets on minimizing greenhouse gas emissions from road rehabilitation policies

NASA Astrophysics Data System (ADS)

Reger, Darren; Madanat, Samer; Horvath, Arpad

2015-11-01

Transportation agencies are being urged to reduce their greenhouse gas (GHG) emissions. One possible solution within their scope is to alter their pavement management system to include environmental impacts. Managing pavement assets is important because poor road conditions lead to increased fuel consumption of vehicles. Rehabilitation activities improve pavement condition, but require materials and construction equipment, which produce GHG emissions as well. The agency’s role is to decide when to rehabilitate the road segments in the network. In previous work, we sought to minimize total societal costs (user and agency costs combined) subject to an emissions constraint for a road network, and demonstrated that there exists a range of potentially optimal solutions (a Pareto frontier) with tradeoffs between costs and GHG emissions. However, we did not account for the case where the available financial budget to the agency is binding. This letter considers an agency whose main goal is to reduce its carbon footprint while operating under a constrained financial budget. A Lagrangian dual solution methodology is applied, which selects the optimal timing and optimal action from a set of alternatives for each segment. This formulation quantifies GHG emission savings per additional dollar of agency budget spent, which can be used in a cap-and-trade system or to make budget decisions. We discuss the importance of communication between agencies and their legislature that sets the financial budgets to implement sustainable policies. We show that for a case study of Californian roads, it is optimal to apply frequent, thin overlays as opposed to the less frequent, thick overlays recommended in the literature if the objective is to minimize GHG emissions. A promising new technology, warm-mix asphalt, will have a negligible effect on reducing GHG emissions for road resurfacing under constrained budgets.

Peak Seeking Control for Reduced Fuel Consumption with Preliminary Flight Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson

2012-01-01

The Environmentally Responsible Aviation project seeks to accomplish the simultaneous reduction of fuel burn, noise, and emissions. A project at NASA Dryden Flight Research Center is contributing to ERAs goals by exploring the practical application of real-time trim configuration optimization for enhanced performance and reduced fuel consumption. This peak-seeking control approach is based on Newton-Raphson algorithm using a time-varying Kalman filter to estimate the gradient of the performance function. In real-time operation, deflection of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of a modified F-18 are directly optimized, and the horizontal stabilators and angle of attack are indirectly optimized. Preliminary results from three research flights are presented herein. The optimization system found a trim configuration that required approximately 3.5% less fuel flow than the baseline trim at the given flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These preliminary results show the algorithm has good performance and is expected to show similar results at other flight conditions and aircraft configurations.

General solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging.

PubMed

Nakata, Toshihiko; Ninomiya, Takanori

2006-10-10

A general solution of undersampling frequency conversion and its optimization for parallel photodisplacement imaging is presented. Phase-modulated heterodyne interference light generated by a linear region of periodic displacement is captured by a charge-coupled device image sensor, in which the interference light is sampled at a sampling rate lower than the Nyquist frequency. The frequencies of the components of the light, such as the sideband and carrier (which include photodisplacement and topography information, respectively), are downconverted and sampled simultaneously based on the integration and sampling effects of the sensor. A general solution of frequency and amplitude in this downconversion is derived by Fourier analysis of the sampling procedure. The optimal frequency condition for the heterodyne beat signal, modulation signal, and sensor gate pulse is derived such that undesirable components are eliminated and each information component is converted into an orthogonal function, allowing each to be discretely reproduced from the Fourier coefficients. The optimal frequency parameters that maximize the sideband-to-carrier amplitude ratio are determined, theoretically demonstrating its high selectivity over 80 dB. Preliminary experiments demonstrate that this technique is capable of simultaneous imaging of reflectivity, topography, and photodisplacement for the detection of subsurface lattice defects at a speed corresponding to an acquisition time of only 0.26 s per 256 x 256 pixel area.

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.

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

PubMed

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

A Discontinuous Petrov-Galerkin Methodology for Adaptive Solutions to the Incompressible Navier-Stokes Equations

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

Roberts, Nathan V.; Demkowiz, Leszek; Moser, Robert

2015-11-15

The discontinuous Petrov-Galerkin methodology with optimal test functions (DPG) of Demkowicz and Gopalakrishnan [18, 20] guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. Whereas Bubnov-Galerkin methods use identical trial and test spaces, Petrov-Galerkin methods allow these function spaces to differ. In DPG, test functions are computed on the fly and are chosen to realize the supremum in the inf-sup condition; the method is equivalent to a minimum residual method. For well-posed problems with sufficiently regular solutions, DPG can be shown to converge at optimal rates—the inf-sup constants governing the convergence aremore » mesh-independent, and of the same order as those governing the continuous problem [48]. DPG also provides an accurate mechanism for measuring the error, and this can be used to drive adaptive mesh refinements. We employ DPG to solve the steady incompressible Navier-Stokes equations in two dimensions, building on previous work on the Stokes equations, and focusing particularly on the usefulness of the approach for automatic adaptivity starting from a coarse mesh. We apply our approach to a manufactured solution due to Kovasznay as well as the lid-driven cavity flow, backward-facing step, and flow past a cylinder problems.« less

Electrically assisted liquid-phase microextraction combined with capillary electrophoresis for quantification of propranolol enantiomers in human body fluids.

PubMed

Tabani, Hadi; Fakhari, Ali Reza; Shahsavani, Abolfath; Gharari Alibabaou, Hossein

2014-05-01

In this study, electromembrane extraction (EME) combined with cyclodextrin (CD)-modified capillary electrophoresis (CE) was applied for the extraction, separation, and quantification of propranolol (PRO) enantiomers from biological samples. The PRO enantiomers were extracted from aqueous donor solutions, through a supported liquid membrane (SLM) consisting of 2-nitrophenyl octyl ether (NPOE) impregnated on the wall of the hollow fiber, and into a 20-μL acidic aqueous acceptor solution into the lumen of hollow fiber. Important parameters affecting EME efficiency such as extraction voltage, extraction time, pH of the donor and acceptor solutions were optimized using a Box-Behnken design (BBD). Then, under these optimized conditions, the acceptor solution was analyzed using an optimized CD-modified CE. Several types of CD were evaluated and best results were obtained using a fused-silica capillary with ammonium acetate (80 mM, pH 2.5) containing 8 mM hydroxypropyl-β-CD as a chiral selector, applied voltage of 18 kV, and temperature of 20°C. The relative recoveries were obtained in the range of 78-95%. Finally, the performance of the present method was evaluated for the extraction and determination of PRO enantiomers in real biological samples. © 2014 Wiley Periodicals, Inc.

Development of a Nonequilibrium Radiative Heating Prediction Method for Coupled Flowfield Solutions

NASA Technical Reports Server (NTRS)

Hartung, Lin C.

1991-01-01

A method for predicting radiative heating and coupling effects in nonequilibrium flow-fields has been developed. The method resolves atomic lines with a minimum number of spectral points, and treats molecular radiation using the smeared band approximation. To further minimize computational time, the calculation is performed on an optimized spectrum, which is computed for each flow condition to enhance spectral resolution. Additional time savings are obtained by performing the radiation calculation on a subgrid optimally selected for accuracy. Representative results from the new method are compared to previous work to demonstrate that the speedup does not cause a loss of accuracy and is sufficient to make coupled solutions practical. The method is found to be a useful tool for studies of nonequilibrium flows.

Optimal solutions for the evolution of a social obesity epidemic model

NASA Astrophysics Data System (ADS)

Sikander, Waseem; Khan, Umar; Mohyud-Din, Syed Tauseef

2017-06-01

In this work, a novel modification in the traditional homotopy perturbation method (HPM) is proposed by embedding an auxiliary parameter in the boundary condition. The scheme is used to carry out a mathematical evaluation of the social obesity epidemic model. The incidence of excess weight and obesity in adulthood population and prediction of its behavior in the coming years is analyzed by using a modified algorithm. The proposed method increases the convergence of the approximate analytical solution over the domain of the problem. Furthermore, a convenient way is considered for choosing an optimal value of auxiliary parameters via minimizing the total residual error. The graphical comparison of the obtained results with the standard HPM explicitly reveals the accuracy and efficiency of the developed scheme.

A versatile multi-objective FLUKA optimization using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Vlachoudis, Vasilis; Antoniucci, Guido Arnau; Mathot, Serge; Kozlowska, Wioletta Sandra; Vretenar, Maurizio

2017-09-01

Quite often Monte Carlo simulation studies require a multi phase-space optimization, a complicated task, heavily relying on the operator experience and judgment. Examples of such calculations are shielding calculations with stringent conditions in the cost, in residual dose, material properties and space available, or in the medical field optimizing the dose delivered to a patient under a hadron treatment. The present paper describes our implementation inside flair[1] the advanced user interface of FLUKA[2,3] of a multi-objective Genetic Algorithm[Erreur ! Source du renvoi introuvable.] to facilitate the search for the optimum solution.

Optimal Limited Contingency Planning

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Smith, David E.

2003-01-01

For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-contingency planning. It is the first optimal algorithm for limited contingency planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.

Inversion of geophysical potential field data using the finite element method

NASA Astrophysics Data System (ADS)

Lamichhane, Bishnu P.; Gross, Lutz

2017-12-01

The inversion of geophysical potential field data can be formulated as an optimization problem with a constraint in the form of a partial differential equation (PDE). It is common practice, if possible, to provide an analytical solution for the forward problem and to reduce the problem to a finite dimensional optimization problem. In an alternative approach the optimization is applied to the problem and the resulting continuous problem which is defined by a set of coupled PDEs is subsequently solved using a standard PDE discretization method, such as the finite element method (FEM). In this paper, we show that under very mild conditions on the data misfit functional and the forward problem in the three-dimensional space, the continuous optimization problem and its FEM discretization are well-posed including the existence and uniqueness of respective solutions. We provide error estimates for the FEM solution. A main result of the paper is that the FEM spaces used for the forward problem and the Lagrange multiplier need to be identical but can be chosen independently from the FEM space used to represent the unknown physical property. We will demonstrate the convergence of the solution approximations in a numerical example. The second numerical example which investigates the selection of FEM spaces, shows that from the perspective of computational efficiency one should use 2 to 4 times finer mesh for the forward problem in comparison to the mesh of the physical property.

Application of an experimental design for the optimization and validation of a new HPLC method for the determination of vancomycin in an extemporaneous ophthalmic solution.

PubMed

Enrique, Montse; García-Montoya, Encarna; Miñarro, Montserrat; Orriols, Anna; Ticó, Joseph Ramon; Suñé-Negre, Joseph Maria; Pérez-Lozano, Pilar

2008-10-01

An experimental design has been used to develop and optimize a new high-performance liquid chromatographic (HPLC) method for the determination of Vancomycin in an extemporaneous ophthalmic solution. After the preliminary studies and literature review, the optimized method was carried out on a second generation of a C18 reverse-phase column (Luna 150 x 4.6 mm i.d., 5 microm particle size) and using methanol as organic phase, a less toxic solvent than acetonitrile, described in the extended literature. The experimental design consisted of a Placket-Burman design where six different variables were studied (flow rate, mL/min; temperature, degrees C; pH mobile phase; % buffer solution; wavelength; and injection volume) to obtain the best suitability parameters (Capacity factor-K', tailing factor, resolution, and theoretical plates). After the optimization of the chromatographic conditions and statistical treatment of the obtained results, the final method uses a mixture of a buffer solution of water-phosphoric acid (85%) (99.83:0.17, v/v) adjusted to pH 3.0 using triethylamine and mixed with methanol (87:13, v/v). The separation is achieved using a flow rate of 1.0 mL/min at 35 degrees C. The UV detector was operated at 280 nm. The validation study carried out, demonstrates the viability of the method, obtaining a good selectivity, linearity, precision, accuracy, and sensitivity.

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without linear bias to show optimal versus sub-optimal solution spaces. Basic analysis of the Actinobacillus succinogenes system using sampling shows that in order to achieve the maximal succinic acid production CO₂ must be taken into the system. Solutions involving release of CO₂ all give sub-optimal succinic acid production.

A Novel Consensus-Based Particle Swarm Optimization-Assisted Trust-Tech Methodology for Large-Scale Global Optimization.

PubMed

Zhang, Yong-Feng; Chiang, Hsiao-Dong

2017-09-01

A novel three-stage methodology, termed the "consensus-based particle swarm optimization (PSO)-assisted Trust-Tech methodology," to find global optimal solutions for nonlinear optimization problems is presented. It is composed of Trust-Tech methods, consensus-based PSO, and local optimization methods that are integrated to compute a set of high-quality local optimal solutions that can contain the global optimal solution. The proposed methodology compares very favorably with several recently developed PSO algorithms based on a set of small-dimension benchmark optimization problems and 20 large-dimension test functions from the CEC 2010 competition. The analytical basis for the proposed methodology is also provided. Experimental results demonstrate that the proposed methodology can rapidly obtain high-quality optimal solutions that can contain the global optimal solution. The scalability of the proposed methodology is promising.

Rapid indirect trajectory optimization on highly parallel computing architectures

NASA Astrophysics Data System (ADS)

Antony, Thomas

Trajectory optimization is a field which can benefit greatly from the advantages offered by parallel computing. The current state-of-the-art in trajectory optimization focuses on the use of direct optimization methods, such as the pseudo-spectral method. These methods are favored due to their ease of implementation and large convergence regions while indirect methods have largely been ignored in the literature in the past decade except for specific applications in astrodynamics. It has been shown that the shortcomings conventionally associated with indirect methods can be overcome by the use of a continuation method in which complex trajectory solutions are obtained by solving a sequence of progressively difficult optimization problems. High performance computing hardware is trending towards more parallel architectures as opposed to powerful single-core processors. Graphics Processing Units (GPU), which were originally developed for 3D graphics rendering have gained popularity in the past decade as high-performance, programmable parallel processors. The Compute Unified Device Architecture (CUDA) framework, a parallel computing architecture and programming model developed by NVIDIA, is one of the most widely used platforms in GPU computing. GPUs have been applied to a wide range of fields that require the solution of complex, computationally demanding problems. A GPU-accelerated indirect trajectory optimization methodology which uses the multiple shooting method and continuation is developed using the CUDA platform. The various algorithmic optimizations used to exploit the parallelism inherent in the indirect shooting method are described. The resulting rapid optimal control framework enables the construction of high quality optimal trajectories that satisfy problem-specific constraints and fully satisfy the necessary conditions of optimality. The benefits of the framework are highlighted by construction of maximum terminal velocity trajectories for a hypothetical long range weapon system. The techniques used to construct an initial guess from an analytic near-ballistic trajectory and the methods used to formulate the necessary conditions of optimality in a manner that is transparent to the designer are discussed. Various hypothetical mission scenarios that enforce different combinations of initial, terminal, interior point and path constraints demonstrate the rapid construction of complex trajectories without requiring any a-priori insight into the structure of the solutions. Trajectory problems of this kind were previously considered impractical to solve using indirect methods. The performance of the GPU-accelerated solver is found to be 2x--4x faster than MATLAB's bvp4c, even while running on GPU hardware that is five years behind the state-of-the-art.

Diamond, aromatic, aliphatic components of interstellar dust grains: Random covalent networks in carbonaceous grains

NASA Astrophysics Data System (ADS)

Duley, W. W.

1995-05-01

A formalism based on the theory of random covalent networks (RCNs) in amorphous solids is developed for carbonaceous dust grains. RCN solutions provide optimized structures and relative compositions for amorphous materials. By inclusion of aliphatic, aromatic, and diamond clusters, solutions specific to interstellar materials can be obtained and compared with infrared spectral data. It is found that distinct RCN solutions corresponding to diffuse cloud and molecular cloud materials are possible. Specific solutions are derived for three representative objects: VI Cyg No. 12, NGC 7538 (IRS 9), and GC IRS 7. While diffuse cloud conditions with a preponderance of sp2 and sp3 bonded aliphatic CH species can be reproduced under a variety of RCN conditions, the presence of an abundant tertiary CH or diamond component is highly constrained. These solutions are related quantitatively to carbon depletions and can be used to provide a quantitative estimate of carbon in these various dust components. Despite the abundance of C6 aromatic rings in many RCN solutions, the infrared absorption due to the aromatic stretch at approximately 3.3 micrometers is weak under all conditions. The RCN formalism is shown to provide a useful method for tracing the evolutionary properties of interstellar carbonaceous grains.

Optimal Control of Induction Machines to Minimize Transient Energy Losses

NASA Astrophysics Data System (ADS)

Plathottam, Siby Jose

Induction machines are electromechanical energy conversion devices comprised of a stator and a rotor. Torque is generated due to the interaction between the rotating magnetic field from the stator, and the current induced in the rotor conductors. Their speed and torque output can be precisely controlled by manipulating the magnitude, frequency, and phase of the three input sinusoidal voltage waveforms. Their ruggedness, low cost, and high efficiency have made them ubiquitous component of nearly every industrial application. Thus, even a small improvement in their energy efficient tend to give a large amount of electrical energy savings over the lifetime of the machine. Hence, increasing energy efficiency (reducing energy losses) in induction machines is a constrained optimization problem that has attracted attention from researchers. The energy conversion efficiency of induction machines depends on both the speed-torque operating point, as well as the input voltage waveform. It also depends on whether the machine is in the transient or steady state. Maximizing energy efficiency during steady state is a Static Optimization problem, that has been extensively studied, with commercial solutions available. On the other hand, improving energy efficiency during transients is a Dynamic Optimization problem that is sparsely studied. This dissertation exclusively focuses on improving energy efficiency during transients. This dissertation treats the transient energy loss minimization problem as an optimal control problem which consists of a dynamic model of the machine, and a cost functional. The rotor field oriented current fed model of the induction machine is selected as the dynamic model. The rotor speed and rotor d-axis flux are the state variables in the dynamic model. The stator currents referred to as d-and q-axis currents are the control inputs. A cost functional is proposed that assigns a cost to both the energy losses in the induction machine, as well as the deviations from desired speed-torque-magnetic flux setpoints. Using Pontryagin's minimum principle, a set of necessary conditions that must be satisfied by the optimal control trajectories are derived. The conditions are in the form a two-point boundary value problem, that can be solved numerically. The conjugate gradient method that was modified using the Hestenes-Stiefel formula was used to obtain the numerical solution of both the control and state trajectories. Using the distinctive shape of the numerical trajectories as inspiration, analytical expressions were derived for the state, and control trajectories. It was shown that the trajectory could be fully described by finding the solution of a one-dimensional optimization problem. The sensitivity of both the optimal trajectory and the optimal energy efficiency to different induction machine parameters were analyzed. A non-iterative solution that can use feedback for generating optimal control trajectories in real time was explored. It was found that an artificial neural network could be trained using the numerical solutions and made to emulate the optimal control trajectories with a high degree of accuracy. Hence a neural network along with a supervisory logic was implemented and used in a real-time simulation to control the Finite Element Method model of the induction machine. The results were compared with three other control regimes and the optimal control system was found to have the highest energy efficiency for the same drive cycle.

Meshless methods in shape optimization of linear elastic and thermoelastic solids

NASA Astrophysics Data System (ADS)

Bobaru, Florin

This dissertation proposes a meshless approach to problems in shape optimization of elastic and thermoelastic solids. The Element-free Galerkin (EFG) method is used for this purpose. The ability of the EFG to avoid remeshing, that is normally done in a Finite Element approach to correct highly distorted meshes, is clearly demonstrated by several examples. The shape optimization example of a thermal cooling fin shows a dramatic improvement in the objective compared to a previous FEM analysis. More importantly, the new solution, displaying large shape changes contrasted to the initial design, was completely missed by the FEM analysis. The EFG formulation given here for shape optimization "uncovers" new solutions that are, apparently, unobtainable via a FEM approach. This is one of the main achievements of our work. The variational formulations for the analysis problem and for the sensitivity problems are obtained with a penalty method for imposing the displacement boundary conditions. The continuum formulation is general and this facilitates 2D and 3D with minor differences from one another. Also, transient thermoelastic problems can use the present development at each time step to solve shape optimization problems for time-dependent thermal problems. For the elasticity framework, displacement sensitivity is obtained in the EFG context. Excellent agreements with analytical solutions for some test problems are obtained. The shape optimization of a fillet is carried out in great detail, and results show significant improvement of the EFG solution over the FEM or the Boundary Element Method solutions. In our approach we avoid differentiating the complicated EFG shape functions, with respect to the shape design parameters, by using a particular discretization for sensitivity calculations. Displacement and temperature sensitivities are formulated for the shape optimization of a linear thermoelastic solid. Two important examples considered in this work, the optimization of a thermal fin and of a uniformly loaded thermoelastic beam, reveal new characteristics of the EFG method in shape optimization applications. Among other advantages of the EFG method over traditional FEM treatments of shape optimization problems, some of the most important ones are shown to be: elimination of post-processing for stress and strain recovery that directly gives more accurate results in critical positions (near the boundaries, for example) for shape optimization problems; nodes movement flexibility that permits new, better shapes (previously missed by an FEM analysis) to be discovered. Several new research directions that need further consideration are exposed.

A zonal method for modeling powered-lift aircraft flow fields

NASA Technical Reports Server (NTRS)

Roberts, D. W.

1989-01-01

A zonal method for modeling powered-lift aircraft flow fields is based on the coupling of a three-dimensional Navier-Stokes code to a potential flow code. By minimizing the extent of the viscous Navier-Stokes zones the zonal method can be a cost effective flow analysis tool. The successful coupling of the zonal solutions provides the viscous/inviscid interations that are necessary to achieve convergent and unique overall solutions. The feasibility of coupling the two vastly different codes is demonstrated. The interzone boundaries were overlapped to facilitate the passing of boundary condition information between the codes. Routines were developed to extract the normal velocity boundary conditions for the potential flow zone from the viscous zone solution. Similarly, the velocity vector direction along with the total conditions were obtained from the potential flow solution to provide boundary conditions for the Navier-Stokes solution. Studies were conducted to determine the influence of the overlap of the interzone boundaries and the convergence of the zonal solutions on the convergence of the overall solution. The zonal method was applied to a jet impingement problem to model the suckdown effect that results from the entrainment of the inviscid zone flow by the viscous zone jet. The resultant potential flow solution created a lower pressure on the base of the vehicle which produces the suckdown load. The feasibility of the zonal method was demonstrated. By enhancing the Navier-Stokes code for powered-lift flow fields and optimizing the convergence of the coupled analysis a practical flow analysis tool will result.

Optimal control of LQR for discrete time-varying systems with input delays

NASA Astrophysics Data System (ADS)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

Shape Optimization for Navier-Stokes Equations with Algebraic Turbulence Model: Existence Analysis

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

Bulicek, Miroslav; Haslinger, Jaroslav; Malek, Josef

2009-10-15

We study a shape optimization problem for the paper machine headbox which distributes a mixture of water and wood fibers in the paper making process. The aim is to find a shape which a priori ensures the given velocity profile on the outlet part. The mathematical formulation leads to an optimal control problem in which the control variable is the shape of the domain representing the header, the state problem is represented by a generalized stationary Navier-Stokes system with nontrivial mixed boundary conditions. In this paper we prove the existence of solutions both to the generalized Navier-Stokes system and tomore » the shape optimization problem.« less

Characterizing L1-norm best-fit subspaces

NASA Astrophysics Data System (ADS)

Brooks, J. Paul; Dulá, José H.

2017-05-01

Fitting affine objects to data is the basis of many tools and methodologies in statistics, machine learning, and signal processing. The L1 norm is often employed to produce subspaces exhibiting a robustness to outliers and faulty observations. The L1-norm best-fit subspace problem is directly formulated as a nonlinear, nonconvex, and nondifferentiable optimization problem. The case when the subspace is a hyperplane can be solved to global optimality efficiently by solving a series of linear programs. The problem of finding the best-fit line has recently been shown to be NP-hard. We present necessary conditions for optimality for the best-fit subspace problem, and use them to characterize properties of optimal solutions.

A novel membrane based process to isolate photosystem-I membrane complex from spinach.

PubMed

Liu, Jianguo; Yin, Mengmeng; Wang, Meng; Zhang, Xuefang; Ge, Baosheng; Liu, Shuang; Lu, Jianren; Cui, Zhanfeng

2011-02-01

The isolation of photosystem-I (PS-I) from spinach has been conducted using ultrafiltration with 300 kDa molecular weight cut-off polyethersulfone membranes. The effects of ultrafiltration operating conditions on PS-I activity were optimized using parameter scanning ultrafiltration. These conditions included solution pH, ionic strength, stirring speed, and permeate flux. The effects of detergent (Triton X-100 and n-dodecyl-beta-D-maltoside) concentration on time dependent activity of PS-I were also studied using an O(2) electrode. Under optimized conditions, the PS-I purity obtained in the retentate was about 84% and the activity recovery was greater than 94% after ultrafiltration. To our knowledge, this is the first report of the isolation of a membrane protein using ultrafiltration alone.

Cryobanking the genetic diversity in the critically endangered Iberian lynx (Lynx pardinus) from skin biopsies. Investigating the cryopreservation and culture ability of highly valuable explants and cells.

PubMed

León-Quinto, Trinidad; Simón, Miguel A; Sánchez, Angel; Martín, Francisco; Soria, Bernat

2011-04-01

Cryobanking skin samples permit preserving a maximum of genetic representation from the population biodiversity. This is a relevant aspect for threatened species, potentially menaced by an epizooty and from which it is difficult to obtain gametes. As a first step for properly cryobanking skin samples of a given species, the optimal conditions of culture and freezing have to be studied by covering a broad range of possibilities. This paper presents, for the first time, a systematic study of such conditions for the Iberian lynx (Lynx pardinus). To that end, we have analyzed twenty different culture conditions and fifteen different freezing solutions for skin explants, as well as three freezing solutions for isolated cells derived from them. The culture conditions included both two different culture strategies and several combinations of nutritional supplements and mitotic agents. For the freezing solutions, we have considered different concentrations of the permeating cryoprotectant dimethyl sulfoxide (Me(2)SO) either alone (5%, 7.5%, 10%, 12.5% and 15% v/v for explants, 10% for isolated cells) or along with the non-permeating cryoprotectant sucrose (0.1 or 0.2M). Our results have been analyzed through several quantitative parameters and show that only thawed explants cryopreserved in Me(2)SO (10%) either alone or with sucrose (0.2M) presented similar properties to those in optimal fresh cultures. In addition, for these freezing conditions, isolated thawed cells also presented high survival rates (90%) and percentages of cellular functionality (85%). These results, focussed on the most endangered felid in the world, could be also useful for other threatened/endangered species. Copyright © 2011 Elsevier Inc. All rights reserved.

Enhancement of L(+)-Lactic Acid Production of Immobilized Rhizopus Oryzae Implanted by Ion Beams

NASA Astrophysics Data System (ADS)

Fan, Yonghong; Yang, Yingge; Zheng, Zhiming; Li, Wen; Wang, Peng; Yao, Liming; Yu, Zengliang

2008-02-01

Immobilized Rhizopus oryzae culturing may be a solution to the inhibited production of L(+)-lactic acid in submerged fermentation, which is caused by aggregated mycelia floc. In the present study, a R. oryzae mutant (RL6041) with a 90% conversion rate of glucose into L-lactic acid was obtained by N+ implantation under the optimized conditions of a beam energy of 15 keV and a dose of 2.6 × 1015 ions/cm2. Using polyurethane foam as the immobilization matrix, the optimal L-lactic acid production conditions were determined as 4 mm polyurethane foam, 150 r/min, 50 g/L ~ 80 g/L of initial glucose, 38°C and pH 6.0. 15-cycle repeated productions of L-lactic acid by immobilized RL6041 were performed under the optimized culturing conditions and over 80% of the glucose was converted into L-lactic acid in 30 hours on average. The results show that immobilized RL6041 is a promising candidate for continuous L-lactic acid production.

Automatic efficiency optimization of an axial compressor with adjustable inlet guide vanes

NASA Astrophysics Data System (ADS)

Li, Jichao; Lin, Feng; Nie, Chaoqun; Chen, Jingyi

2012-04-01

The inlet attack angle of rotor blade reasonably can be adjusted with the change of the stagger angle of inlet guide vane (IGV); so the efficiency of each condition will be affected. For the purpose to improve the efficiency, the DSP (Digital Signal Processor) controller is designed to adjust the stagger angle of IGV automatically in order to optimize the efficiency at any operating condition. The A/D signal collection includes inlet static pressure, outlet static pressure, outlet total pressure, rotor speed and torque signal, the efficiency can be calculated in the DSP, and the angle signal for the stepping motor which control the IGV will be sent out from the D/A. Experimental investigations are performed in a three-stage, low-speed axial compressor with variable inlet guide vanes. It is demonstrated that the DSP designed can well adjust the stagger angle of IGV online, the efficiency under different conditions can be optimized. This establishment of DSP online adjustment scheme may provide a practical solution for improving performance of multi-stage axial flow compressor when its operating condition is varied.

Review of optimum temperature, humidity, and vapour pressure deficit for microclimate evaluation and control in greenhouse cultivation of tomato: a review

NASA Astrophysics Data System (ADS)

Shamshiri, Redmond Ramin; Jones, James W.; Thorp, Kelly R.; Ahmad, Desa; Man, Hasfalina Che; Taheri, Sima

2018-04-01

Greenhouse technology is a flexible solution for sustainable year-round cultivation of Tomato (Lycopersicon esculentum Mill), particularly in regions with adverse climate conditions or limited land and resources. Accurate knowledge about plant requirements at different growth stages, and under various light conditions, can contribute to the design of adaptive control strategies for a more cost-effective and competitive production. In this context, different scientific publications have recommended different values of microclimate parameters at different tomato growth stages. This paper provides a detailed summary of optimal, marginal and failure air and root-zone temperatures, relative humidity and vapour pressure deficit for successful greenhouse cultivation of tomato. Graphical representations of the membership function model to define the optimality degrees of these three parameters are included with a view to determining how close the greenhouse microclimate is to the optimal condition. Several production constraints have also been discussed to highlight the short and long-term effects of adverse microclimate conditions on the quality and yield of tomato, which are associated with interactions between suboptimal parameters, greenhouse environment and growth responses.

Guidance and Control strategies for aerospace vehicles

NASA Technical Reports Server (NTRS)

Hibey, J. L.; Naidu, D. S.; Charalambous, C. D.

1989-01-01

A neighboring optimal guidance scheme was devised for a nonlinear dynamic system with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory was determined. Then, a neighboring, optimal guidance scheme was obtained for open loop and closed loop control configurations. Taking modelling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme was devised. Finally, the optimal trajectory was approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical vehicle. A fuel-optimal control problem in aeroassisted noncoplanar orbital transfer is also addressed. The equations of motion for the atmospheric maneuver are nonlinear and the optimal (nominal) trajectory and control are obtained. In order to follow the nominal trajectory under actual conditions, a neighboring optimum guidance scheme is designed using linear quadratic regulator theory for onboard real-time implementation. One of the state variables is used as the independent variable in reference to the time. The weighting matrices in the performance index are chosen by a combination of a heuristic method and an optimal modal approach. The necessary feedback control law is obtained in order to minimize the deviations from the nominal conditions.

Hepatitis C virus NS3 helicase forms oligomeric structures that exhibit optimal DNA unwinding activity in vitro.

PubMed

Sikora, Bartek; Chen, Yingfeng; Lichti, Cheryl F; Harrison, Melody K; Jennings, Thomas A; Tang, Yong; Tackett, Alan J; Jordan, John B; Sakon, Joshua; Cameron, Craig E; Raney, Kevin D

2008-04-25

HCV NS3 helicase exhibits activity toward DNA and RNA substrates. The DNA helicase activity of NS3 has been proposed to be optimal when multiple NS3 molecules are bound to the same substrate molecule. NS3 catalyzes little or no measurable DNA unwinding under single cycle conditions in which the concentration of substrate exceeds the concentration of enzyme by 5-fold. However, when NS3 (100 nm) is equimolar with the substrate, a small burst amplitude of approximately 8 nm is observed. The burst amplitude increases as the enzyme concentration increases, consistent with the idea that multiple molecules are needed for optimal unwinding. Protein-protein interactions may facilitate optimal activity, so the oligomeric properties of the enzyme were investigated. Chemical cross-linking indicates that full-length NS3 forms higher order oligomers much more readily than the NS3 helicase domain. Dynamic light scattering indicates that full-length NS3 exists as an oligomer, whereas NS3 helicase domain exists in a monomeric form in solution. Size exclusion chromatography also indicates that full-length NS3 behaves as an oligomer in solution, whereas the NS3 helicase domain behaves as a monomer. When NS3 was passed through a small pore filter capable of removing protein aggregates, greater than 95% of the protein and the DNA unwinding activity was removed from solution. In contrast, only approximately 10% of NS3 helicase domain and approximately 20% of the associated DNA unwinding activity was removed from solution after passage through the small pore filter. The results indicate that the optimally active form of full-length NS3 is part of an oligomeric species in vitro.

Infinite Dimensional Linear Systems with Unbounded Control and Observation: A Functional Analytic Approach.

DTIC Science & Technology

1985-02-01

In particular, the optimal control is characterized in terms S of the dual system and conditions are given under which the optimal control is...solution in general and has to be replaced by the differential inclusion x - ex 8 range fi. It is important to note that 0 is boundedly invertible on...above way in terms of operators B, C, T which satisfy the hypotheses (S2-4). -9- L ’- ". * The implications of this hypothesis for the inhomogeneous

A capillary electrophoresis chip for the analysis of print and film photographic developing agents in commercial processing solutions using indirect fluorescence detection.

PubMed

Sirichai, S; de Mello, A J

2001-01-01

The separation and detection of both print and film developing agents (CD-3 and CD-4) in photographic processing solutions using chip-based capillary electrophoresis is presented. For simultaneous detection of both analytes under identical experimental conditions a buffer pH of 11.9 is used to partially ionise the analytes. Detection is made possible by indirect fluorescence, where the ions of the analytes displace the anionic fluorescing buffer ion to create negative peaks. Under optimal conditions, both analytes can be analyzed within 30 s. The limits of detection for CD-3 and CD-4 are 0.17 mM and 0.39 mM, respectively. The applicability of the method for the analysis of seasoned photographic processing developer solutions is also examined.

Removal of Cr(VI) from Aqueous Environments Using Micelle-Clay Adsorption

PubMed Central

Qurie, Mohannad; Khamis, Mustafa; Manassra, Adnan; Ayyad, Ibrahim; Nir, Shlomo; Scrano, Laura; Bufo, Sabino A.; Karaman, Rafik

2013-01-01

Removal of Cr(VI) from aqueous solutions under different conditions was investigated using either clay (montmorillonite) or micelle-clay complex, the last obtained by adsorbing critical micelle concentration of octadecyltrimethylammonium ions onto montmorillonite. Batch experiments showed the effects of contact time, adsorbent dosage, and pH on the removal efficiency of Cr(VI) from aqueous solutions. Langmuir adsorption isotherm fitted the experimental data giving significant results. Filtration experiments using columns filled with micelle-clay complex mixed with sand were performed to assess Cr(VI) removal efficiency under continuous flow at different pH values. The micelle-clay complex used in this study was capable of removing Cr(VI) from aqueous solutions without any prior acidification of the sample. Results demonstrated that the removal effectiveness reached nearly 100% when using optimal conditions for both batch and continuous flow techniques. PMID:24222757

Adjoint optimization of natural convection problems: differentially heated cavity

NASA Astrophysics Data System (ADS)

Saglietti, Clio; Schlatter, Philipp; Monokrousos, Antonios; Henningson, Dan S.

2017-12-01

Optimization of natural convection-driven flows may provide significant improvements to the performance of cooling devices, but a theoretical investigation of such flows has been rarely done. The present paper illustrates an efficient gradient-based optimization method for analyzing such systems. We consider numerically the natural convection-driven flow in a differentially heated cavity with three Prandtl numbers (Pr=0.15{-}7) at super-critical conditions. All results and implementations were done with the spectral element code Nek5000. The flow is analyzed using linear direct and adjoint computations about a nonlinear base flow, extracting in particular optimal initial conditions using power iteration and the solution of the full adjoint direct eigenproblem. The cost function for both temperature and velocity is based on the kinetic energy and the concept of entransy, which yields a quadratic functional. Results are presented as a function of Prandtl number, time horizons and weights between kinetic energy and entransy. In particular, it is shown that the maximum transient growth is achieved at time horizons on the order of 5 time units for all cases, whereas for larger time horizons the adjoint mode is recovered as optimal initial condition. For smaller time horizons, the influence of the weights leads either to a concentric temperature distribution or to an initial condition pattern that opposes the mean shear and grows according to the Orr mechanism. For specific cases, it could also been shown that the computation of optimal initial conditions leads to a degenerate problem, with a potential loss of symmetry. In these situations, it turns out that any initial condition lying in a specific span of the eigenfunctions will yield exactly the same transient amplification. As a consequence, the power iteration converges very slowly and fails to extract all possible optimal initial conditions. According to the authors' knowledge, this behavior is illustrated here for the first time.

Cascade Optimization Strategy Maximizes Thrust for High-Speed Civil Transport Propulsion System Concept

NASA Technical Reports Server (NTRS)

1995-01-01

The design of a High-Speed Civil Transport (HSCT) air-breathing propulsion system for multimission, variable-cycle operations was successfully optimized through a soft coupling of the engine performance analyzer NASA Engine Performance Program (NEPP) to a multidisciplinary optimization tool COMETBOARDS that was developed at the NASA Lewis Research Center. The design optimization of this engine was cast as a nonlinear optimization problem, with engine thrust as the merit function and the bypass ratios, r-values of fans, fuel flow, and other factors as important active design variables. Constraints were specified on factors including the maximum speed of the compressors, the positive surge margins for the compressors with specified safety factors, the discharge temperature, the pressure ratios, and the mixer extreme Mach number. Solving the problem by using the most reliable optimization algorithm available in COMETBOARDS would provide feasible optimum results only for a portion of the aircraft flight regime because of the large number of mission points (defined by altitudes, Mach numbers, flow rates, and other factors), diverse constraint types, and overall poor conditioning of the design space. Only the cascade optimization strategy of COMETBOARDS, which was devised especially for difficult multidisciplinary applications, could successfully solve a number of engine design problems for their flight regimes. Furthermore, the cascade strategy converged to the same global optimum solution even when it was initiated from different design points. Multiple optimizers in a specified sequence, pseudorandom damping, and reduction of the design space distortion via a global scaling scheme are some of the key features of the cascade strategy. HSCT engine concept, optimized solution for HSCT engine concept. A COMETBOARDS solution for an HSCT engine (Mach-2.4 mixed-flow turbofan) along with its configuration is shown. The optimum thrust is normalized with respect to NEPP results. COMETBOARDS added value in the design optimization of the HSCT engine.

Post-Optimality Analysis In Aerospace Vehicle Design

NASA Technical Reports Server (NTRS)

Braun, Robert D.; Kroo, Ilan M.; Gage, Peter J.

1993-01-01

This analysis pertains to the applicability of optimal sensitivity information to aerospace vehicle design. An optimal sensitivity (or post-optimality) analysis refers to computations performed once the initial optimization problem is solved. These computations may be used to characterize the design space about the present solution and infer changes in this solution as a result of constraint or parameter variations, without reoptimizing the entire system. The present analysis demonstrates that post-optimality information generated through first-order computations can be used to accurately predict the effect of constraint and parameter perturbations on the optimal solution. This assessment is based on the solution of an aircraft design problem in which the post-optimality estimates are shown to be within a few percent of the true solution over the practical range of constraint and parameter variations. Through solution of a reusable, single-stage-to-orbit, launch vehicle design problem, this optimal sensitivity information is also shown to improve the efficiency of the design process, For a hierarchically decomposed problem, this computational efficiency is realized by estimating the main-problem objective gradient through optimal sep&ivity calculations, By reducing the need for finite differentiation of a re-optimized subproblem, a significant decrease in the number of objective function evaluations required to reach the optimal solution is obtained.

Optimization of Process Conditions for Enzymatic Modification of Alternan using Dextranase from Chaetomium erraticum

USDA-ARS?s Scientific Manuscript database

Alternan is a unique branched glucan with alternating a-(1 ' 6) and a-(1 ' 3) backbone linkages. We previously described the modification of alternan to a reduced molecular weight form using dextranase from Penicillium sp. The solution viscosity properties of this modified alternan resemble those ...

Categorical Biases in Spatial Memory: The Role of Certainty

ERIC Educational Resources Information Center

Holden, Mark P.; Newcombe, Nora S.; Shipley, Thomas F.

2015-01-01

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. The Category Adjustment (CA) model suggests that this bias is due to a Bayesian combination of categorical and metric information, which offers an optimal solution under conditions of uncertainty (Huttenlocher, Hedges, & Duncan,…

Optimization method for an evolutional type inverse heat conduction problem

NASA Astrophysics Data System (ADS)

Deng, Zui-Cha; Yu, Jian-Ning; Yang, Liu

2008-01-01

This paper deals with the determination of a pair (q, u) in the heat conduction equation u_t-u_{xx}+q(x,t)u=0, with initial and boundary conditions u(x,0)=u_0(x),\\qquad u_x|_{x=0}=u_x|_{x=1}=0, from the overspecified data u(x, t) = g(x, t). By the time semi-discrete scheme, the problem is transformed into a sequence of inverse problems in which the unknown coefficients are purely space dependent. Based on the optimal control framework, the existence, uniqueness and stability of the solution (q, u) are proved. A necessary condition which is a couple system of a parabolic equation and parabolic variational inequality is deduced.

Active vibration mitigation of distributed parameter, smart-type structures using Pseudo-Feedback Optimal Control (PFOC)

NASA Technical Reports Server (NTRS)

Patten, W. N.; Robertshaw, H. H.; Pierpont, D.; Wynn, R. H.

1989-01-01

A new, near-optimal feedback control technique is introduced that is shown to provide excellent vibration attenuation for those distributed parameter systems that are often encountered in the areas of aeroservoelasticity and large space systems. The technique relies on a novel solution methodology for the classical optimal control problem. Specifically, the quadratic regulator control problem for a flexible vibrating structure is first cast in a weak functional form that admits an approximate solution. The necessary conditions (first-order) are then solved via a time finite-element method. The procedure produces a low dimensional, algebraic parameterization of the optimal control problem that provides a rigorous basis for a discrete controller with a first-order like hold output. Simulation has shown that the algorithm can successfully control a wide variety of plant forms including multi-input/multi-output systems and systems exhibiting significant nonlinearities. In order to firmly establish the efficacy of the algorithm, a laboratory control experiment was implemented to provide planar (bending) vibration attenuation of a highly flexible beam (with a first clamped-free mode of approximately 0.5 Hz).

Real - time Optimization of Distributed Energy Storage System Operation Strategy Based on Peak Load Shifting

NASA Astrophysics Data System (ADS)

Wang, Qian; Lu, Guangqi; Li, Xiaoyu; Zhang, Yichi; Yun, Zejian; Bian, Di

2018-01-01

To take advantage of the energy storage system (ESS) sufficiently, the factors that the service life of the distributed energy storage system (DESS) and the load should be considered when establishing optimization model. To reduce the complexity of the load shifting of DESS in the solution procedure, the loss coefficient and the equal capacity ratio distribution principle were adopted in this paper. Firstly, the model was established considering the constraint conditions of the cycles, depth, power of the charge-discharge of the ESS, the typical daily load curves, as well. Then, dynamic programming method was used to real-time solve the model in which the difference of power Δs, the real-time revised energy storage capacity Sk and the permission error of depth of charge-discharge were introduced to optimize the solution process. The simulation results show that the optimized results was achieved when the load shifting in the load variance was not considered which means the charge-discharge of the energy storage system was not executed. In the meantime, the service life of the ESS would increase.

Evaluation and optimization of the conditions for an improved ferulic acid intercalation into a synthetic lamellar anionic clay.

PubMed

Schoubben, Aurélie; Blasi, Paolo; Giovagnoli, Stefano; Nocchetti, Morena; Ricci, Maurizio; Perioli, Luana; Rossi, Carlo

2006-03-01

The aim of the study is to optimize the intercalation conditions of ferulic acid (FERH), an antioxidant compound, into Mg-Al-hydrotalcite for a safe skin photoprotection. The intercalation products were prepared incubating hydrotalcite (HTlc) in aqueous solutions of FERH sodium salt at different temperatures over 4 and 8 days. Quantitative determination of intercalated FERH was performed by thermogravimetric analysis and morphology by scanning electron microscopy (SEM). FERH stability study was carried out at different pHs and temperatures. FERH was analyzed by reversed phase-high-performance liquid chromatography. Response surface methods (RSMs) were used to assess optimal intercalation conditions and FERH stability. In all intercalation products, FERH content was found to be about 48% w/w except when the intercalation process was carried out at 52 degrees C for 8 days and at 60 degrees C for both 4 and 8 days, which resulted to be 40.39, 39.99, and 34.99%, respectively. The RSM designs showed that intercalation improvement can be achieved by working at pH 6, at temperatures below 40 degrees C, and over 4 days of incubation. The optimal conditions for a proper FERH intercalation were assessed. The development of a new optimized protocol may improve HTlc-FER complex performances and safety by augmenting dosage and reducing the presence of harmful reactive species in the final formulation.

Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

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

Wang, Hong; Wang, Shaobu; Fan, Rui

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it hasmore » been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.« less

First-order convex feasibility algorithms for x-ray CT

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob S.; Pan, Xiaochuan

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution—thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle−Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144°. The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application. PMID:23464295

An efficient flexible-order model for 3D nonlinear water waves

NASA Astrophysics Data System (ADS)

Engsig-Karup, A. P.; Bingham, H. B.; Lindberg, O.

2009-04-01

The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal scaling of the solution effort multigrid is employed to precondition a GMRES iterative solution of the discretized Laplace problem. A robust multigrid method based on Gauss-Seidel smoothing is found to require special treatment of the boundary conditions along solid boundaries, and in particular on the sea bottom. A new discretization scheme using one layer of grid points outside the fluid domain is presented and shown to provide convergent solutions over the full physical and discrete parameter space of interest. Linear analysis of the fundamental properties of the scheme with respect to accuracy, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental measurements and other calculations from the literature.

A Framework for Multi-Stakeholder Decision-Making and ...

EPA Pesticide Factsheets

This contribution describes the implementation of the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. It is observed that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimizes average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework. We demonstrate the framework in a bio-waste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs. This conference presentation abstract explains a new decision-making framework that computes compromise solution alternatives (reach consensus) by mitigating dissatisfactions among stakeholders as needed for SHC Decision Science and Support Tools project.

Optimization of Aluminum Anodization Conditions for the Fabrication of Nanowires by Electrodeposition

NASA Technical Reports Server (NTRS)

Fucsko, Viola

2005-01-01

Anodized alumina nanotemplates have a variety of potential applications in the development of nanotechnology. Alumina nanotemplates are formed by oxidizing aluminum film in an electrolyte solution.During anodization, aluminum oxidizes, and, under the proper conditions, nanometer-sized pores develop. A series of experiments was conducted to determine the optimal conditions for anodization. Three-micrometer thick aluminum films on silicon and silicon oxide substrates were anodized using constant voltages of 13-25 V. 0.1-0.3M oxalic acid was used as the electrolyte. The anodization time was found to increase and the overshooting current decreased as both the voltage and the electrolyte concentrations were decreased. The samples were observed under a scanning electron microscope. Anodizing with 25V in 0.3M oxalic acid appears to be the best process conditions. The alumina nanotemplates are being used to fabricate nanowires by electrodeposition. The current-voltage characteristics of copper nanowires have also been studied.

The model and the planning method of volume and variety assessment of innovative products in an industrial enterprise

NASA Astrophysics Data System (ADS)

Anisimov, V. G.; Anisimov, E. G.; Saurenko, T. N.; Sonkin, M. A.

2017-01-01

In the long term, the innovative development strategy efficiency is considered as the most crucial condition for assurance of economic system competitiveness in market conditions. It determines the problem relevance of such justification strategies with regard to specific systems features and conditions of their operation. The problem solution for industrial enterprises can be based on mathematical models of supporting the decision-making on the elements of the innovative manufacturing program. An optimization model and the planning method of innovative products volume and variety are suggested. The feature of the suggested model lies in the nonlinear nature of the objective function. It allows taking into consideration the law of diminishing marginal utility. The suggested method of optimization takes into account the system features and enables the effective implementation of manufacturing capabilities in modern conditions of production organization and sales in terms of market saturation.

Explicit parametric solutions of lattice structures with proper generalized decomposition (PGD) - Applications to the design of 3D-printed architectured materials

NASA Astrophysics Data System (ADS)

Sibileau, Alberto; Auricchio, Ferdinando; Morganti, Simone; Díez, Pedro

2018-01-01

Architectured materials (or metamaterials) are constituted by a unit-cell with a complex structural design repeated periodically forming a bulk material with emergent mechanical properties. One may obtain specific macro-scale (or bulk) properties in the resulting architectured material by properly designing the unit-cell. Typically, this is stated as an optimal design problem in which the parameters describing the shape and mechanical properties of the unit-cell are selected in order to produce the desired bulk characteristics. This is especially pertinent due to the ease manufacturing of these complex structures with 3D printers. The proper generalized decomposition provides explicit parametic solutions of parametric PDEs. Here, the same ideas are used to obtain parametric solutions of the algebraic equations arising from lattice structural models. Once the explicit parametric solution is available, the optimal design problem is a simple post-process. The same strategy is applied in the numerical illustrations, first to a unit-cell (and then homogenized with periodicity conditions), and in a second phase to the complete structure of a lattice material specimen.

An extraction process to recover vanadium from low-grade vanadium-bearing titanomagnetite.

PubMed

Chen, Desheng; Zhao, Hongxin; Hu, Guoping; Qi, Tao; Yu, Hongdong; Zhang, Guozhi; Wang, Lina; Wang, Weijing

2015-08-30

An extraction process to recover vanadium from low-grade vanadium-bearing titanomagnetite was developed. In this study, a mixed solvent system of di(2-ethylhexyl) phosphate (D2EHPA) and tri-n-butyl phosphate (TBP) diluted with kerosene was used for the selective extraction of vanadium from a hydrochloric acid leaching solution that contained low vanadium concentration with high concentrations of iron and impurities of Ca, Mg, and Al. In the extraction process, the initial solution pH and the phase ratio had considerable functions in the extraction of vanadium from the hydrochloric acid leaching solution. Under optimal extraction conditions (i.e., 30-40°C for 10min, 1:3 phase ratio (O/A), 20% D2EHPA concentration (v/v), and 0-0.8 initial solution pH), 99.4% vanadium and only 4.2% iron were extracted by the three-stage counter-current extraction process. In the stripping process with H2SO4 as the stripping agent and under optimal stripping conditions (i.e., 20% H2SO4 concentration, 5:1 phase ratio (O/A), 20min stripping time, and 40°C stripping temperature), 99.6% vanadium and only 5.4% iron were stripped by the three-stage counter-current stripping process. The stripping solution contained 40.16g/LV2O5,0.691g/L Fe, 0.007g/L TiO2, 0.006g/L SiO2 and 0.247g/L CaO. A V2O5 product with a purity of 99.12% V2O5 and only 0.026% Fe was obtained after the oxidation, precipitation, and calcination processes. The total vanadium recovered from the hydrochloric acid leaching solution was 85.5%. Copyright © 2015 Elsevier B.V. All rights reserved.

A new sol-gel processing routine without chelating agents for preparing highly transparent solutions and nanothin films: engineering the role of chemistry to design the process

NASA Astrophysics Data System (ADS)

Ashiri, Rouholah

2015-01-01

The great sensitivity of titanium alkoxides to hydrolysis makes their sol-gel transformation very fast and thus difficult to control. A method was proposed to alleviate this drawback. Preparation of highly transparent solutions and nanothin films is another objective of the present research. Employing nanoemulsion method and optimizing the processing conditions, a clear solution of well-dispersed nanosized particles was obtained. With the proposed process BaTiO3 precursor sols and nanothin films with enhanced optical transparency towards the visible were prepared. The optimal formulation of the sol consists of acetic acid, barium acetate, 2-propanol, TTIP and deionized water with 6:1:1:1:150 M ratios, respectively. It was found that the reduction of the temperature in the initial stage of mixing of precursors controls the size of the forming species and accordingly improves the stability and transparency of the sol. The results also showed that the applied modifications and optimizations significantly downsize the particles within the sol to the nanometric scale and accordingly result in a significant improvement in the optical response of the products.

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions

PubMed Central

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time. PMID:28118384

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions.

PubMed

Guerrero, Jose; Oliver, Gabriel; Valero, Oscar

2017-01-01

Multi-robot task allocation is one of the main problems to address in order to design a multi-robot system, very especially when robots form coalitions that must carry out tasks before a deadline. A lot of factors affect the performance of these systems and among them, this paper is focused on the physical interference effect, produced when two or more robots want to access the same point simultaneously. To our best knowledge, this paper presents the first formal description of multi-robot task allocation that includes a model of interference. Thanks to this description, the complexity of the allocation problem is analyzed. Moreover, the main contribution of this paper is to provide the conditions under which the optimal solution of the aforementioned allocation problem can be obtained solving an integer linear problem. The optimal results are compared to previous allocation algorithms already proposed by the first two authors of this paper and with a new method proposed in this paper. The results obtained show how the new task allocation algorithms reach up more than an 80% of the median of the optimal solution, outperforming previous auction algorithms with a huge reduction of the execution time.

Electro-driven extraction of inorganic anions from water samples and water miscible organic solvents and analysis by ion chromatography.

PubMed

Nojavan, Saeed; Bidarmanesh, Tina; Memarzadeh, Farkhondeh; Chalavi, Soheila

2014-09-01

A simple electromembrane extraction (EME) procedure combined with ion chromatography (IC) was developed to quantify inorganic anions in different pure water samples and water miscible organic solvents. The parameters affecting extraction performance, such as supported liquid membrane (SLM) solvent, extraction time, pH of donor and acceptor solutions, and extraction voltage were optimized. The optimized EME conditions were as follows: 1-heptanol was used as the SLM solvent, the extraction time was 10 min, pHs of the acceptor and donor solutions were 10 and 7, respectively, and the extraction voltage was 15 V. The mobile phase used for IC was a combination of 1.8 mM sodium carbonate and 1.7 mM sodium bicarbonate. Under these optimized conditions, all anions had enrichment factors ranging from 67 to 117 with RSDs between 7.3 and 13.5% (n = 5). Good linearity values ranging from 2 to 1200 ng/mL with coefficients of determination (R(2) ) between 0.987 and 0.999 were obtained. The LODs of the EME-IC method ranged from 0.6 to 7.5 ng/mL. The developed method was applied to different samples to evaluate the feasibility of the method for real applications. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultrasound-assisted extraction and preliminary purification of proanthocyanidins and chlorogenic acid from almond (Prunus dulcis) skin.

PubMed

Ma, Xue; Zhou, Xin-Yu; Qiang, Qian-Qian; Zhang, Zhi-Qi

2014-07-01

An aqueous solution of polyethylene glycol (PEG) as a green solvent was employed for the first time to develop the ultrasound-assisted extraction of proanthocyanidins (PA) and chlorogenic acid (CA) from almond skin. The optimized extraction parameters were determined based on response surface methodology, and corresponded to an ultrasound power of 120 W, a liquid-to-solid ratio of 20:1 (mL/g), and a PEG concentration of 50% (v/v). Under these optimized conditions, the extraction yields of PAs and CA from almond skin were 32.68 ± 0.22 and 16.01 ± 0.19 mg/g, respectively. Compared with organic solvent extraction, PEG solution extraction produced higher yields. Different macroporous resins were compared for their performance in purifying PAs and CA from almond skin extract. Static adsorption/desorption experimental results demonstrated that AB-8 resin exhibits excellent purification performance at pH 4. Under the optimized dynamic adsorption/desorption conditions on the AB-8 column, the total recovery of purification for PAs and CA was 80.67%. The total content of PAs and CA in the preliminarily purified extract was 89.17% (with respective contents of 60.90 and 28.27%). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Robust Ordering Strategy for Retailers Facing a Free Shipping Option

PubMed Central

Meng, Qing-chun; Wan, Xiao-le; Rong, Xiao-xia

2015-01-01

Free shipping with conditions has become one of the most effective marketing tools available. An increasing number of companies, especially e-businesses, prefer to offer free shipping with some predetermined condition, such as a minimum purchase amount by the customer. However, in practice, the demands of buyers are uncertain; they are often affected by many factors, such as the weather and season. We begin by modeling the centralized ordering problem in which the supplier offers a free shipping service and retailers face stochastic demands. As these random data are considered, only partial information such as the known mean, support, and deviation is needed. The model is then analyzed via a robust optimization method, and the two types of equivalent sets of uncertainty constraints that are obtained provide good mathematical properties with consideration of the robustness of solutions. Subsequently, a numerical example is used to compare the results achieved from a robust optimization method and the linear decision rules. Additionally, the robustness of the optimal solution is discussed, as it is affected by the minimum quantity parameters. The increasing cost-threshold relationship is divided into three periods. In addition, the case study shows that the proposed method achieves better stability as well as computational complexity. PMID:25993533

Optimal shielding design for minimum materials cost or mass

DOE PAGES

Woolley, Robert D.

2015-12-02

The mathematical underpinnings of cost optimal radiation shielding designs based on an extension of optimal control theory are presented, a heuristic algorithm to iteratively solve the resulting optimal design equations is suggested, and computational results for a simple test case are discussed. A typical radiation shielding design problem can have infinitely many solutions, all satisfying the problem's specified set of radiation attenuation requirements. Each such design has its own total materials cost. For a design to be optimal, no admissible change in its deployment of shielding materials can result in a lower cost. This applies in particular to very smallmore » changes, which can be restated using the calculus of variations as the Euler-Lagrange equations. Furthermore, the associated Hamiltonian function and application of Pontryagin's theorem lead to conditions for a shield to be optimal.« less

Dispersion-relation-preserving finite difference schemes for computational acoustics

NASA Technical Reports Server (NTRS)

Tam, Christopher K. W.; Webb, Jay C.

1993-01-01

Time-marching dispersion-relation-preserving (DRP) schemes can be constructed by optimizing the finite difference approximations of the space and time derivatives in wave number and frequency space. A set of radiation and outflow boundary conditions compatible with the DRP schemes is constructed, and a sequence of numerical simulations is conducted to test the effectiveness of the DRP schemes and the radiation and outflow boundary conditions. Close agreement with the exact solutions is obtained.

Speciation of inorganic tellurium from seawater by ICP-MS following magnetic SPE separation and preconcentration.

PubMed

Huang, Chaozhang; Hu, Bin

2008-03-01

A new method was developed for the speciation of inorganic tellurium species in seawater by inductively coupled plasma-MS (ICP-MS) following selective magnetic SPE (MSPE) separation. Within the pH range of 2-9, tellurite (Te(IV)) could be quantitatively adsorbed on gamma-mercaptopropyltrimethoxysilane (gamma-MPTMS) modified silica-coated magnetic nanoparticles (MNPs), while the tellurate (Te(VI)) was not retained and remained in solution. Without filtration or centrifugation, these tellurite-loaded MNPs could be separated easily from the aqueous solution by simply applying external magnetic field. The Te(IV) adsorbed on the MNPs could be recovered quantitatively using a solution containing 2 mol/L HCl and 0.03 mol/L K2Cr2O7. Te(VI) was reduced to Te(IV) by L-cysteine prior to the determination of total tellurium, and its assay was based on subtracting Te(IV) from total tellurium. The parameters affecting the separation were investigated systematically and the optimal separation conditions were established. Under the optimal conditions, the LOD obtained for Te(IV) was 0.079 ng/L, while the precision was 7.0% (C = 10 ng/L, n = 7). The proposed method was successfully applied to the speciation of inorganic tellurium in seawater.

A natural macroalgae consortium for biosorption of copper from aqueous solution: Optimization, modeling and design studies.

PubMed

Deniz, Fatih; Ersanli, Elif Tezel

2018-03-21

In this study, the capacity of a natural macroalgae consortium consisting of Chaetomorpha sp., Polysiphonia sp., Ulva sp. and Cystoseira sp. species for the removal of copper ions from aqueous environment was investigated at different operating conditions, such as solution pH, copper ion concentration and contact time. These environmental parameters affecting the biosorption process were optimized on the basis of batch experiments. The experimentally obtained data for the biosorption of copper ions onto the macroalgae-based biosorbent were modeled using the isotherm models of Freundlich, Langmuir, Sips and Dubinin-Radushkevich and the kinetic models of pseudo-first-order, pseudo-second-order, Elovich and Weber and Morris. The pseudo-first-order and Sips equations were the most suitable models to describe the copper biosorption from aqueous solution. The thermodynamic data revealed the feasibility, spontaneity and physical nature of biosorption process. Based on the data of Sips isotherm model, the biosorption capacity of biosorbent for copper ions was calculated as 105.370 mg g -1 under the optimum operating conditions. A single-stage batch biosorption system was developed to predict the real-scale-based copper removal performance of biosorbent. The results of this investigation showed the potential utility of macroalgae consortium for the biosorption of copper ions from aqueous medium.

Microextraction of mebendazole across supported liquid membrane forced by pH gradient and electrical field.

PubMed

Eskandari, Mahboube; Yamini, Yadollah; Fotouhi, Lida; Seidi, Shahram

2011-04-05

In the present study, extraction of mebendazole across a supported-liquid membrane (SLM) was performed based on two different driving forces: (1) pH gradient over the SLM, and (2) electrical field sustained over the SLM. The extracted drug concentration was studied using reversed-phase HPLC-UV. At passive extraction conditions, mebendazole was extracted from alkaline samples (0.01 mmol L(-1) NaOH) into 1-undecanol immobilized in the pores of a porous hollow fiber of polypropylene (SLM), and then transported into 25 μL of 100mM HCl as the acceptor solution. Under electrokinetic migration conditions, mebendazole transported under applied voltage from acidic solutions (100 mmol L(-1) HCl) through 2-nitrophenyl octyl ether (NPOE) immobilized in the pores of hollow fiber, into 25 μL of 100 mmol L(-1) HCl as the acceptor solution. The effects of several factors including the nature of organic solvent, pH of donor and acceptor solutions, extraction time and stirring speed on the extraction efficiency of the drug were investigated and optimized. Under optimal conditions, preconcentration factors (PF) of 211 and 190 were obtained for the drug based on passive transport and electromembrane extraction (EME), respectively. Also, linear range of 0.5-1000 μg L(-1) with estimation of coefficient higher than 0.994 was obtained for both of the proposed methods. The results showed that EME has higher speed in comparison with simple passive transport. The methods were successfully applied to extract mebendazole from plasma and urine samples and satisfactory results were obtained. Copyright © 2010 Elsevier B.V. All rights reserved.

Global optimization of multicomponent distillation configurations: 2. Enumeration based global minimization algorithm

DOE PAGES

Nallasivam, Ulaganathan; Shah, Vishesh H.; Shenvi, Anirudh A.; ...

2016-02-10

We present a general Global Minimization Algorithm (GMA) to identify basic or thermally coupled distillation configurations that require the least vapor duty under minimum reflux conditions for separating any ideal or near-ideal multicomponent mixture into a desired number of product streams. In this algorithm, global optimality is guaranteed by modeling the system using Underwood equations and reformulating the resulting constraints to bilinear inequalities. The speed of convergence to the globally optimal solution is increased by using appropriate feasibility and optimality based variable-range reduction techniques and by developing valid inequalities. As a result, the GMA can be coupled with already developedmore » techniques that enumerate basic and thermally coupled distillation configurations, to provide for the first time, a global optimization based rank-list of distillation configurations.« less

Efficient protocols for Stirling heat engines at the micro-scale

NASA Astrophysics Data System (ADS)

Muratore-Ginanneschi, Paolo; Schwieger, Kay

2015-10-01

We investigate the thermodynamic efficiency of sub-micro-scale Stirling heat engines operating under the conditions described by overdamped stochastic thermodynamics. We show how to construct optimal protocols such that at maximum power the efficiency attains for constant isotropic mobility the universal law η=2 ηC/(4-ηC) , where ηC is the efficiency of an ideal Carnot cycle. We show that these protocols are specified by the solution of an optimal mass transport problem. Such solution can be determined explicitly using well-known Monge-Ampère-Kantorovich reconstruction algorithms. Furthermore, we show that the same law describes the efficiency of heat engines operating at maximum work over short time periods. Finally, we illustrate the straightforward extension of these results to cases when the mobility is anisotropic and temperature dependent.

Remediation of Cr(VI)-Contaminated Soil Using the Acidified Hydrazine Hydrate.

PubMed

Ma, Yameng; Li, Fangfang; Jiang, Yuling; Yang, Weihua; Lv, Lv; Xue, Haotian; Wang, Yangyang

2016-09-01

Acidified hydrazine hydrate was used to remediate Cr(VI)-contaminated soil. The content of water-soluble Cr(VI) in contaminated soil was 4977.53 mg/kg. The optimal initial pH of hydrazine hydrate solution, soil to solution ratio and molar ratio of Cr(VI) to hydrazine hydrate for remediation of Cr(VI)-contaminated soil were 5.0, 3:1 and 1:3, respectively. Over 99.50 % of water-soluble Cr(VI) in the contaminated soil was reduced at the optimal condition within 30 min. The remediated soil can keep stable within 4 months. Meanwhile the total phosphorus increased from 0.47 to 4.29 g/kg, indicating that using of acidified hydrazine hydrate is an effective method to remediate Cr(VI)-contaminated soil.

Optimal control of singularly perturbed nonlinear systems with state-variable inequality constraints

NASA Technical Reports Server (NTRS)

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

1990-01-01

The established necessary conditions for optimality in nonlinear control problems that involve state-variable inequality constraints are applied to a class of singularly perturbed systems. The distinguishing feature of this class of two-time-scale systems is a transformation of the state-variable inequality constraint, present in the full order problem, to a constraint involving states and controls in the reduced problem. It is shown that, when a state constraint is active in the reduced problem, the boundary layer problem can be of finite time in the stretched time variable. Thus, the usual requirement for asymptotic stability of the boundary layer system is not applicable, and cannot be used to construct approximate boundary layer solutions. Several alternative solution methods are explored and illustrated with simple examples.

Optimal lay-up design of variable stiffness laminated composite plates by a layer-wise optimization technique

NASA Astrophysics Data System (ADS)

Houmat, A.

2018-02-01

The optimal lay-up design for the maximum fundamental frequency of variable stiffness laminated composite plates is investigated using a layer-wise optimization technique. The design variables are two fibre orientation angles per ply. Thin plate theory is used in conjunction with a p-element to calculate the fundamental frequencies of symmetrically and antisymmetrically laminated composite plates. Comparisons with existing optimal solutions for constant stiffness symmetrically laminated composite plates show excellent agreement. It is observed that the maximum fundamental frequency can be increased considerably using variable stiffness design as compared to constant stiffness design. In addition, optimal lay-ups for the maximum fundamental frequency of variable stiffness symmetrically and antisymmetrically laminated composite plates with different aspect ratios and various combinations of free, simply supported and clamped edge conditions are presented. These should prove a useful benchmark for optimal lay-ups of variable stiffness laminated composite plates.

Theory and Computation of Optimal Low- and Medium- Thrust Orbit Transfers

NASA Technical Reports Server (NTRS)

Goodson, Troy D.; Chuang, Jason C. H.; Ledsinger, Laura A.

1996-01-01

This report presents new theoretical results which lead to new algorithms for the computation of fuel-optimal multiple-burn orbit transfers of low and medium thrust. Theoretical results introduced herein show how to add burns to an optimal trajectory and show that the traditional set of necessary conditions may be replaced with a much simpler set of equations. Numerical results are presented to demonstrate the utility of the theoretical results and the new algorithms. Two indirect methods from the literature are shown to be effective for the optimal orbit transfer problem with relatively small numbers of burns. These methods are the Minimizing Boundary Condition Method (MBCM) and BOUNDSCO. Both of these methods make use of the first-order necessary conditions exactly as derived by optimal control theory. Perturbations due to Earth's oblateness and atmospheric drag are considered. These perturbations are of greatest interest for transfers that take place between low Earth orbit altitudes and geosynchronous orbit altitudes. Example extremal solutions including these effects and computed by the aforementioned methods are presented. An investigation is also made into a suboptimal multiple-burn guidance scheme. The FORTRAN code developed for this study has been collected together in a package named ORBPACK. ORBPACK's user manual is provided as an appendix to this report.

Legendre spectral-collocation method for solving some types of fractional optimal control problems

PubMed Central

Sweilam, Nasser H.; Al-Ajami, Tamer M.

2014-01-01

In this paper, the Legendre spectral-collocation method was applied to obtain approximate solutions for some types of fractional optimal control problems (FOCPs). The fractional derivative was described in the Caputo sense. Two different approaches were presented, in the first approach, necessary optimality conditions in terms of the associated Hamiltonian were approximated. In the second approach, the state equation was discretized first using the trapezoidal rule for the numerical integration followed by the Rayleigh–Ritz method to evaluate both the state and control variables. Illustrative examples were included to demonstrate the validity and applicability of the proposed techniques. PMID:26257937

A Hybrid Interval–Robust Optimization Model for Water Quality Management

PubMed Central

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications

NASA Technical Reports Server (NTRS)

Aldrich, Jack B.; Okon, Avi B.

2012-01-01

The need to maintain optimal energy efficiency is critical during the drilling operations performed on future and current planetary rover missions (see figure). Specifically, this innovation seeks to solve the following problem. Given a spring-loaded percussive drill driven by a voice-coil motor, one needs to determine the optimal input voltage waveform (periodic function) and the optimal hammering period that minimizes the dissipated energy, while ensuring that the hammer-to-rock impacts are made with sufficient (user-defined) impact velocity (or impact energy). To solve this problem, it was first observed that when voice-coil-actuated percussive drills are driven at high power, it is of paramount importance to ensure that the electrical current of the device remains in phase with the velocity of the hammer. Otherwise, negative work is performed and the drill experiences a loss of performance (i.e., reduced impact energy) and an increase in Joule heating (i.e., reduction in energy efficiency). This observation has motivated many drilling products to incorporate the standard bang-bang control approach for driving their percussive drills. However, the bang-bang control approach is significantly less efficient than the optimal energy-efficient control approach solved herein. To obtain this solution, the standard tools of classical optimal control theory were applied. It is worth noting that these tools inherently require the solution of a two-point boundary value problem (TPBVP), i.e., a system of differential equations where half the equations have unknown boundary conditions. Typically, the TPBVP is impossible to solve analytically for high-dimensional dynamic systems. However, for the case of the spring-loaded vibro-impactor, this approach yields the exact optimal control solution as the sum of four analytic functions whose coefficients are determined using a simple, easy-to-implement algorithm. Once the optimal control waveform is determined, it can be used optimally in the context of both open-loop and closed-loop control modes (using standard realtime control hardware).

Optimization of the Determination Method for Dissolved Cyanobacterial Toxin BMAA in Natural Water.

PubMed

Yan, Boyin; Liu, Zhiquan; Huang, Rui; Xu, Yongpeng; Liu, Dongmei; Lin, Tsair-Fuh; Cui, Fuyi

2017-10-17

There is a serious dispute on the existence of β-N-methylamino-l-alanine (BMAA) in water, which is a neurotoxin that may cause amyotrophic lateral sclerosis/Parkinson's disease (ALS/PDC) and Alzheimer' disease. It is believed that a reliable and sensitive analytical method for the determination of BMAA is urgently required to resolve this dispute. In the present study, the solid phase extraction (SPE) procedure and the analytical method for dissolved BMAA in water were investigated and optimized. The results showed both derivatized and underivatized methods were qualified for the measurement of BMAA and its isomer in natural water, and the limit of detection and the precision of the two methods were comparable. Cartridge characteristics and SPE conditions could greatly affect the SPE performance, and the competition of natural organic matter is the primary factor causing the low recovery of BMAA, which was reduced from approximately 90% in pure water to 38.11% in natural water. The optimized SPE method for BMAA was a combination of rinsed SPE cartridges, controlled loading/elution rates and elution solution, evaporation at 55 °C, reconstitution of a solution mixture, and filtration by polyvinylidene fluoride membrane. This optimized method achieved > 88% recovery of BMAA in both algal solution and river water. The developed method can provide an efficient way to evaluate the actual concentration levels of BMAA in actual water environments and drinking water systems.

Electrospinning fundamentals: optimizing solution and apparatus parameters.

PubMed

Leach, Michelle K; Feng, Zhang-Qi; Tuck, Samuel J; Corey, Joseph M

2011-01-21

Electrospun nanofiber scaffolds have been shown to accelerate the maturation, improve the growth, and direct the migration of cells in vitro. Electrospinning is a process in which a charged polymer jet is collected on a grounded collector; a rapidly rotating collector results in aligned nanofibers while stationary collectors result in randomly oriented fiber mats. The polymer jet is formed when an applied electrostatic charge overcomes the surface tension of the solution. There is a minimum concentration for a given polymer, termed the critical entanglement concentration, below which a stable jet cannot be achieved and no nanofibers will form - although nanoparticles may be achieved (electrospray). A stable jet has two domains, a streaming segment and a whipping segment. While the whipping jet is usually invisible to the naked eye, the streaming segment is often visible under appropriate lighting conditions. Observing the length, thickness, consistency and movement of the stream is useful to predict the alignment and morphology of the nanofibers being formed. A short, non-uniform, inconsistent, and/or oscillating stream is indicative of a variety of problems, including poor fiber alignment, beading, splattering, and curlicue or wavy patterns. The stream can be optimized by adjusting the composition of the solution and the configuration of the electrospinning apparatus, thus optimizing the alignment and morphology of the fibers being produced. In this protocol, we present a procedure for setting up a basic electrospinning apparatus, empirically approximating the critical entanglement concentration of a polymer solution and optimizing the electrospinning process. In addition, we discuss some common problems and troubleshooting techniques.

Constrained minimization problems for the reproduction number in meta-population models.

PubMed

Poghotanyan, Gayane; Feng, Zhilan; Glasser, John W; Hill, Andrew N

2018-02-14

The basic reproduction number ([Formula: see text]) can be considerably higher in an SIR model with heterogeneous mixing compared to that from a corresponding model with homogeneous mixing. For example, in the case of measles, mumps and rubella in San Diego, CA, Glasser et al. (Lancet Infect Dis 16(5):599-605, 2016. https://doi.org/10.1016/S1473-3099(16)00004-9 ), reported an increase of 70% in [Formula: see text] when heterogeneity was accounted for. Meta-population models with simple heterogeneous mixing functions, e.g., proportionate mixing, have been employed to identify optimal vaccination strategies using an approach based on the gradient of the effective reproduction number ([Formula: see text]), which consists of partial derivatives of [Formula: see text] with respect to the proportions immune [Formula: see text] in sub-groups i (Feng et al. in J Theor Biol 386:177-187, 2015.  https://doi.org/10.1016/j.jtbi.2015.09.006 ; Math Biosci 287:93-104, 2017.  https://doi.org/10.1016/j.mbs.2016.09.013 ). These papers consider cases in which an optimal vaccination strategy exists. However, in general, the optimal solution identified using the gradient may not be feasible for some parameter values (i.e., vaccination coverages outside the unit interval). In this paper, we derive the analytic conditions under which the optimal solution is feasible. Explicit expressions for the optimal solutions in the case of [Formula: see text] sub-populations are obtained, and the bounds for optimal solutions are derived for [Formula: see text] sub-populations. This is done for general mixing functions and examples of proportionate and preferential mixing are presented. Of special significance is the result that for general mixing schemes, both [Formula: see text] and [Formula: see text] are bounded below and above by their corresponding expressions when mixing is proportionate and isolated, respectively.

Optimal control of anthracnose using mixed strategies.

PubMed

Fotsa Mbogne, David Jaures; Thron, Christopher

2015-11-01

In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street.

PubMed

Panaggio, Mark J; Ottino-Löffler, Bertand J; Hu, Peiguang; Abrams, Daniel M

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this "green-wave" scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Analysis of an operator-differential model for magnetostrictive energy harvesting

NASA Astrophysics Data System (ADS)

Davino, D.; Krejčí, P.; Pimenov, A.; Rachinskii, D.; Visone, C.

2016-10-01

We present a model of, and analysis of an optimization problem for, a magnetostrictive harvesting device which converts mechanical energy of the repetitive process such as vibrations of the smart material to electrical energy that is then supplied to an electric load. The model combines a lumped differential equation for a simple electronic circuit with an operator model for the complex constitutive law of the magnetostrictive material. The operator based on the formalism of the phenomenological Preisach model describes nonlinear saturation effects and hysteresis losses typical of magnetostrictive materials in a thermodynamically consistent fashion. We prove well-posedness of the full operator-differential system and establish global asymptotic stability of the periodic regime under periodic mechanical forcing that represents mechanical vibrations due to varying environmental conditions. Then we show the existence of an optimal solution for the problem of maximization of the output power with respect to a set of controllable parameters (for the periodically forced system). Analytical results are illustrated with numerical examples of an optimal solution.

Symmetry breaking in optimal timing of traffic signals on an idealized two-way street

NASA Astrophysics Data System (ADS)

Panaggio, Mark J.; Ottino-Löffler, Bertand J.; Hu, Peiguang; Abrams, Daniel M.

2013-09-01

Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal world, traffic signals would be timed such that consecutive lights turned green just as vehicles arrived, eliminating the need to stop at each block. Unfortunately, this “green-wave” scenario is generally unworkable due to frustration imposed by competing demands of traffic moving in different directions. Until now this has typically been resolved by numerical simulation and optimization. Here, we develop a theory for the flow in an idealized system consisting of a long two-way road with periodic intersections. We show that optimal signal timing can be understood analytically and that there are counterintuitive asymmetric solutions to this signal coordination problem. We further explore how these theoretical solutions degrade as traffic conditions vary and automotive density increases.

Minimization of required model runs in the Random Mixing approach to inverse groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Hoerning, Sebastian; Bardossy, Andras; du Plessis, Jaco

2017-04-01

Most geostatistical inverse groundwater flow and transport modelling approaches utilize a numerical solver to minimize the discrepancy between observed and simulated hydraulic heads and/or hydraulic concentration values. The optimization procedure often requires many model runs, which for complex models lead to long run times. Random Mixing is a promising new geostatistical technique for inverse modelling. The method is an extension of the gradual deformation approach. It works by finding a field which preserves the covariance structure and maintains observed hydraulic conductivities. This field is perturbed by mixing it with new fields that fulfill the homogeneous conditions. This mixing is expressed as an optimization problem which aims to minimize the difference between the observed and simulated hydraulic heads and/or concentration values. To preserve the spatial structure, the mixing weights must lie on the unit hyper-sphere. We present a modification to the Random Mixing algorithm which significantly reduces the number of model runs required. The approach involves taking n equally spaced points on the unit circle as weights for mixing conditional random fields. Each of these mixtures provides a solution to the forward model at the conditioning locations. For each of the locations the solutions are then interpolated around the circle to provide solutions for additional mixing weights at very low computational cost. The interpolated solutions are used to search for a mixture which maximally reduces the objective function. This is in contrast to other approaches which evaluate the objective function for the n mixtures and then interpolate the obtained values. Keeping the mixture on the unit circle makes it easy to generate equidistant sampling points in the space; however, this means that only two fields are mixed at a time. Once the optimal mixture for two fields has been found, they are combined to form the input to the next iteration of the algorithm. This process is repeated until a threshold in the objective function is met or insufficient changes are produced in successive iterations.

Moments and Legendre-Fourier Series for Measures Supported on Curves

NASA Astrophysics Data System (ADS)

Lasserre, Jean B.

2015-09-01

Some important problems (e.g., in optimal transport and optimal control) have a relaxed (or weak) formulation in a space of appropriate measures which is much easier to solve. However, an optimal solution μ of the latter solves the former if and only if the measure μ is supported on a ''trajectory'' {(t,x(t))\\colon tin [0,T]} for some measurable function x(t). We provide necessary and sufficient conditions on moments (γ_{ij}) of a measure dμ(x,t) on [0,1]^2 to ensure that μ is supported on a trajectory {(t,x(t))\\colon tin [0,1]}. Those conditions are stated in terms of Legendre-Fourier coefficients {f}_j=({f}_j(i)) associated with some functions f_j\\colon [0,1]to R, j=1,ldots, where each f_j is obtained from the moments γ_{ji}, i=0,1,ldots, of μ.

Optimization of PEG-based extraction of polysaccharides from Dendrobium nobile Lindl. and bioactivity study.

PubMed

Zhang, Yi; Wang, Hongxin; Wang, Peng; Ma, ChaoYang; He, GuoHua; Rahman, Md Ramim Tanver

2016-11-01

Polyethylene glycol (PEG) as a green solvent was employed to extract polysaccharide. The optimal conditions for PEG-based ultrasonic extraction of Dendrobium nobile Lindl. polysaccharide (JCP) were determined by response surface methodology. Under the optimal conditions: extraction temperature of 58.5°C; ultrasound power of 193W, and the concentration of polyethylene glycol-200 (PEG-200) solution of 45%, the highest JCP yield was obtained as 15.23±0.57%, which was close to the predicted yield, 15.57%. UV and FT-IR analysis revealed the general characteristic absorption peaks of both JCP with water extraction (JCP w ) and PEG-200 solvent extraction (JCP p ). Thermal analysis of both JCPs was performed with Thermal Gravimetric Analyzer (TGA) and Differential Scanning Calorimeter (DSC). Antioxidant activities of two polysaccharides were also compared and no significant difference in vitro was obtained. Copyright © 2016 Elsevier B.V. All rights reserved.

Analytical and numerical analysis of inverse optimization problems: conditions of uniqueness and computational methods

PubMed Central

Zatsiorsky, Vladimir M.

2011-01-01

One of the key problems of motor control is the redundancy problem, in particular how the central nervous system (CNS) chooses an action out of infinitely many possible. A promising way to address this question is to assume that the choice is made based on optimization of a certain cost function. A number of cost functions have been proposed in the literature to explain performance in different motor tasks: from force sharing in grasping to path planning in walking. However, the problem of uniqueness of the cost function(s) was not addressed until recently. In this article, we analyze two methods of finding additive cost functions in inverse optimization problems with linear constraints, so-called linear-additive inverse optimization problems. These methods are based on the Uniqueness Theorem for inverse optimization problems that we proved recently (Terekhov et al., J Math Biol 61(3):423–453, 2010). Using synthetic data, we show that both methods allow for determining the cost function. We analyze the influence of noise on the both methods. Finally, we show how a violation of the conditions of the Uniqueness Theorem may lead to incorrect solutions of the inverse optimization problem. PMID:21311907

Fuel optimal maneuvers for spacecraft with fixed thrusters

NASA Technical Reports Server (NTRS)

Carter, T. C.

1982-01-01

Several mathematical models, including a minimum integral square criterion problem, were used for the qualitative investigation of fuel optimal maneuvers for spacecraft with fixed thrusters. The solutions consist of intervals of "full thrust" and "coast" indicating that thrusters do not need to be designed as "throttleable" for fuel optimal performance. For the primary model considered, singular solutions occur only if the optimal solution is "pure translation". "Time optimal" singular solutions can be found which consist of intervals of "coast" and "full thrust". The shape of the optimal fuel consumption curve as a function of flight time was found to depend on whether or not the initial state is in the region admitting singular solutions. Comparisons of fuel optimal maneuvers in deep space with those relative to a point in circular orbit indicate that qualitative differences in the solutions can occur. Computation of fuel consumption for certain "pure translation" cases indicates that considerable savings in fuel can result from the fuel optimal maneuvers.

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

Nallasivam, Ulaganathan; Shah, Vishesh H.; Shenvi, Anirudh A.

We present a general Global Minimization Algorithm (GMA) to identify basic or thermally coupled distillation configurations that require the least vapor duty under minimum reflux conditions for separating any ideal or near-ideal multicomponent mixture into a desired number of product streams. In this algorithm, global optimality is guaranteed by modeling the system using Underwood equations and reformulating the resulting constraints to bilinear inequalities. The speed of convergence to the globally optimal solution is increased by using appropriate feasibility and optimality based variable-range reduction techniques and by developing valid inequalities. As a result, the GMA can be coupled with already developedmore » techniques that enumerate basic and thermally coupled distillation configurations, to provide for the first time, a global optimization based rank-list of distillation configurations.« less

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

NASA Astrophysics Data System (ADS)

Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

2014-12-01

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

Data Mining and Optimization Tools for Developing Engine Parameters Tools

NASA Technical Reports Server (NTRS)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Hydraulic performance improvement of the bidirectional pit pump installation based on CFD

NASA Astrophysics Data System (ADS)

Chen, H. X.; Zhou, D. Q.

2013-12-01

At present, the efficiency of bidirectional pit pump installation with lift under 2m is still low because of lack of research on it in the past. In the paper, the CFD numerical method and experimental test were applied to study flow characteristic of bidirectional pit pump installation under positive and reverse condition. Through changing airfoil type and position of blade and stay vane, the comprehensive performance of improved model were obtained by calculating many different models. The results showed that when improved model is obtained with type A runner with 4 blades that is 0.7D away from pit exit and unsymmetrical guide vane 0.25dh which away from the impeller outlet, and the flow pattern of the improved solution is steady with high efficiency. Compared with the original scheme, the efficiency of positive and reverse design condition reach to 67.23% and 58.32% respectively, which is increased 6% more than original model on the design condition and 5% on the optimum operating condition, and it achieved the purpose of improvement. According to the runner blade angle of the optimization solution, model synthetic characteristic curve was drawn and internal flow field characteristics was analyzed under optimal positive and reverse conditions. The numerical calculation shows that owing to the lack of stay vane to recycle the energy in outlet runner chamber, the water flow regime is not steady enough in the outlet passage, and that is the main reason for lower efficiency at reverse condition than that at positive condition.

Electrochemical degradation and mineralization of glyphosate herbicide.

PubMed

Tran, Nam; Drogui, Patrick; Doan, Tuan Linh; Le, Thanh Son; Nguyen, Hoai Chau

2017-12-01

The presence of herbicide is a concern for both human and ecological health. Glyphosate is occasionally detected as water contaminants in agriculture areas where the herbicide is used extensively. The removal of glyphosate in synthetic solution using advanced oxidation process is a possible approach for remediation of contaminated waters. The ability of electrochemical oxidation for the degradation and mineralization of glyphosate herbicide was investigated using Ti/PbO 2 anode. The current intensity, treatment time, initial concentration and pH of solution are the influent parameters on the degradation efficiency. An experimental design methodology was applied to determine the optimal condition (in terms of cost/effectiveness) based on response surface methodology. Glyphosate concentration (C 0  = 16.9 mg L -1 ) decreased up to 0.6 mg L -1 when the optimal conditions were imposed (current intensity of 4.77 A and treatment time of 173 min). The removal efficiencies of glyphosate and total organic carbon were 95 ± 16% and 90.31%, respectively. This work demonstrates that electrochemical oxidation is a promising process for degradation and mineralization of glyphosate.

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

Kail, Brian W; Link, Dirk D; Morreale, Bryan D

A method for selectively determining both free fatty acids (FFA) and triacylglycerides (TAGs) in biological oils was investigated and optimized using gas chromatography after esterification of the target species to their corresponding fatty acid methyl esters (FAMEs). The method used acid catalyzed esterification in methanolic solutions under conditions of varying severity to achieve complete conversion of more reactive FFAs while preserving the concentration of TAGs. Complete conversion of both free acids and glycerides to corresponding FAMEs was found to require more rigorous reaction conditions involving heating to 120°C for up to 2 h. Method validation was provided using gas chromatography–flamemore » ionization detection, gas chromatography–mass spectrometry, and liquid chromatography–mass spectrometry. The method improves on existing methods because it allows the total esterified lipid to be broken down by FAMEs contributed by FFA compared to FAMEs from both FFA and TAGs. Single and mixed-component solutions of pure fatty acids and triglycerides, as well as a sesame oil sample to simulate a complex biological oil, were used to optimize the methodologies. Key parameters that were investigated included: HCl-to-oil ratio, temperature and reaction time. Pure free fatty acids were found to esterify under reasonably mild conditions (10 min at 50°C with a 2.1:1 HCl to fatty acid ratio) with 97.6 ± 2.3% recovery as FAMEs, while triglycerides were largely unaffected under these reaction conditions. The optimized protocol demonstrated that it is possible to use esterification reactions to selectively determine the free acid content, total lipid content, and hence, glyceride content in biological oils. This protocol also allows gas chromatography analysis of FAMEs as a more ideal analyte than glyceride species in their native state.« less

Minimizing transient influence in WHPA delineation: An optimization approach for optimal pumping rate schemes

NASA Astrophysics Data System (ADS)

Rodriguez-Pretelin, A.; Nowak, W.

2017-12-01

For most groundwater protection management programs, Wellhead Protection Areas (WHPAs) have served as primarily protection measure. In their delineation, the influence of time-varying groundwater flow conditions is often underestimated because steady-state assumptions are commonly made. However, it has been demonstrated that temporary variations lead to significant changes in the required size and shape of WHPAs. Apart from natural transient groundwater drivers (e.g., changes in the regional angle of flow direction and seasonal natural groundwater recharge), anthropogenic causes such as transient pumping rates are of the most influential factors that require larger WHPAs. We hypothesize that WHPA programs that integrate adaptive and optimized pumping-injection management schemes can counter transient effects and thus reduce the additional areal demand in well protection under transient conditions. The main goal of this study is to present a novel management framework that optimizes pumping schemes dynamically, in order to minimize the impact triggered by transient conditions in WHPA delineation. For optimizing pumping schemes, we consider three objectives: 1) to minimize the risk of pumping water from outside a given WHPA, 2) to maximize the groundwater supply and 3) to minimize the involved operating costs. We solve transient groundwater flow through an available transient groundwater and Lagrangian particle tracking model. The optimization problem is formulated as a dynamic programming problem. Two different optimization approaches are explored: I) the first approach aims for single-objective optimization under objective (1) only. The second approach performs multiobjective optimization under all three objectives where compromise pumping rates are selected from the current Pareto front. Finally, we look for WHPA outlines that are as small as possible, yet allow the optimization problem to find the most suitable solutions.

System design optimization for a Mars-roving vehicle and perturbed-optimal solutions in nonlinear programming

NASA Technical Reports Server (NTRS)

Pavarini, C.

1974-01-01

Work in two somewhat distinct areas is presented. First, the optimal system design problem for a Mars-roving vehicle is attacked by creating static system models and a system evaluation function and optimizing via nonlinear programming techniques. The second area concerns the problem of perturbed-optimal solutions. Given an initial perturbation in an element of the solution to a nonlinear programming problem, a linear method is determined to approximate the optimal readjustments of the other elements of the solution. Then, the sensitivity of the Mars rover designs is described by application of this method.

A study of optimization techniques in HDR brachytherapy for the prostate

NASA Astrophysics Data System (ADS)

Pokharel, Ghana Shyam

Several studies carried out thus far are in favor of dose escalation to the prostate gland to have better local control of the disease. But optimal way of delivery of higher doses of radiation therapy to the prostate without hurting neighboring critical structures is still debatable. In this study, we proposed that real time high dose rate (HDR) brachytherapy with highly efficient and effective optimization could be an alternative means of precise delivery of such higher doses. This approach of delivery eliminates the critical issues such as treatment setup uncertainties and target localization as in external beam radiation therapy. Likewise, dosimetry in HDR brachytherapy is not influenced by organ edema and potential source migration as in permanent interstitial implants. Moreover, the recent report of radiobiological parameters further strengthen the argument of using hypofractionated HDR brachytherapy for the management of prostate cancer. Firstly, we studied the essential features and requirements of real time HDR brachytherapy treatment planning system. Automating catheter reconstruction with fast editing tools, fast yet accurate dose engine, robust and fast optimization and evaluation engine are some of the essential requirements for such procedures. Moreover, in most of the cases we performed, treatment plan optimization took significant amount of time of overall procedure. So, making treatment plan optimization automatic or semi-automatic with sufficient speed and accuracy was the goal of the remaining part of the project. Secondly, we studied the role of optimization function and constraints in overall quality of optimized plan. We have studied the gradient based deterministic algorithm with dose volume histogram (DVH) and more conventional variance based objective functions for optimization. In this optimization strategy, the relative weight of particular objective in aggregate objective function signifies its importance with respect to other objectives. Based on our study, DVH based objective function performed better than traditional variance based objective function in creating a clinically acceptable plan when executed under identical conditions. Thirdly, we studied the multiobjective optimization strategy using both DVH and variance based objective functions. The optimization strategy was to create several Pareto optimal solutions by scanning the clinically relevant part of the Pareto front. This strategy was adopted to decouple optimization from decision such that user could select final solution from the pool of alternative solutions based on his/her clinical goals. The overall quality of treatment plan improved using this approach compared to traditional class solution approach. In fact, the final optimized plan selected using decision engine with DVH based objective was comparable to typical clinical plan created by an experienced physicist. Next, we studied the hybrid technique comprising both stochastic and deterministic algorithm to optimize both dwell positions and dwell times. The simulated annealing algorithm was used to find optimal catheter distribution and the DVH based algorithm was used to optimize 3D dose distribution for given catheter distribution. This unique treatment planning and optimization tool was capable of producing clinically acceptable highly reproducible treatment plans in clinically reasonable time. As this algorithm was able to create clinically acceptable plans within clinically reasonable time automatically, it is really appealing for real time procedures. Next, we studied the feasibility of multiobjective optimization using evolutionary algorithm for real time HDR brachytherapy for the prostate. The algorithm with properly tuned algorithm specific parameters was able to create clinically acceptable plans within clinically reasonable time. However, the algorithm was let to run just for limited number of generations not considered optimal, in general, for such algorithms. This was done to keep time window desirable for real time procedures. Therefore, it requires further study with improved conditions to realize the full potential of the algorithm.

Impact of nanocrystal spray deposition on inorganic solar cells.

PubMed

Townsend, Troy K; Yoon, Woojun; Foos, Edward E; Tischler, Joseph G

2014-05-28

Solution-synthesized inorganic cadmium telluride nanocrystals (∼4 nm; 1.45 eV band gap) are attractive elements for the fabrication of thin-film-based low-cost photovoltaic (PV) devices. Their encapsulating organic ligand shell enables them to be easily dissolved in organic solvents, and the resulting solutions can be spray-cast onto indium-tin oxide (ITO)-coated glass under ambient conditions to produce photoactive thin films of CdTe. Following annealing at 380 °C in the presence of CdCl2(s) and evaporation of metal electrode contacts (glass/ITO/CdTe/Ca/Al), Schottky-junction PV devices were tested under simulated 1 sun conditions. An improved PV performance was found to be directly tied to control over the film morphology obtained by the adjustment of spray parameters such as the solution concentration, delivery pressure, substrate distance, and surface temperature. Higher spray pressures produced thinner layers (<60 nm) with lower surface roughness (<200 nm), leading to devices with improved open-circuit voltages (Voc) due to decreased surface roughness and higher short-circuit current (Jsc) as a result of enhanced annealing conditions. After process optimization, spray-cast Schottky devices rivaled those prepared by conventional spin-coating, showing Jsc = 14.6 ± 2.7 mA cm(-2), Voc = 428 ± 11 mV, FF = 42.8 ± 1.4%, and Eff. = 2.7 ± 0.5% under 1 sun illumination. This optimized condition of CdTe spray deposition was then applied to heterojunction devices (ITO/CdTe/ZnO/Al) to reach 3.0% efficiency after light soaking under forward bias. The film thickness, surface morphology, and light absorption were examined with scanning electron microscopy, optical profilometry, and UV/vis spectroscopy.

Discretized energy minimization in a wave guide with point sources

NASA Technical Reports Server (NTRS)

Propst, G.

1994-01-01

An anti-noise problem on a finite time interval is solved by minimization of a quadratic functional on the Hilbert space of square integrable controls. To this end, the one-dimensional wave equation with point sources and pointwise reflecting boundary conditions is decomposed into a system for the two propagating components of waves. Wellposedness of this system is proved for a class of data that includes piecewise linear initial conditions and piecewise constant forcing functions. It is shown that for such data the optimal piecewise constant control is the solution of a sparse linear system. Methods for its computational treatment are presented as well as examples of their applicability. The convergence of discrete approximations to the general optimization problem is demonstrated by finite element methods.

Optimal Diet Planning for Eczema Patient Using Integer Programming

NASA Astrophysics Data System (ADS)

Zhen Sheng, Low; Sufahani, Suliadi

2018-04-01

Human diet planning is conducted by choosing appropriate food items that fulfill the nutritional requirements into the diet formulation. This paper discusses the application of integer programming to build the mathematical model of diet planning for eczema patients. The model developed is used to solve the diet problem of eczema patients from young age group. The integer programming is a scientific approach to select suitable food items, which seeks to minimize the costs, under conditions of meeting desired nutrient quantities, avoiding food allergens and getting certain foods into the diet that brings relief to the eczema conditions. This paper illustrates that the integer programming approach able to produce the optimal and feasible solution to deal with the diet problem of eczema patient.

Construction of High Activity Titanium Dioxide Crystal Surface Heterostructures and Characterization of Its Basic Properties

NASA Astrophysics Data System (ADS)

Wang, Chunxiao; Li, DanQi; Shen, Tingting; Lu, Cheng; Sun, Jing; Wang, Xikui

2018-01-01

Heterogeneous photocatalytic materials, which combine the advantages of photocatalytic materials and heterojunction, have been developed rapidly in the field of environmental pollution control. In this paper, TiO2 surface heterojunction catalysts with different catalytic activity were prepared by controlling the amount of HF, and their XRD characterization was also carried out. In addition, the optimum amount of HF was determined by photocatalytic degradation of simulated dye wastewater by methylene blue solution. And the optimal amount of catalyst and the optimal pH reaction conditions for degradation experiments were used to screen the highly reactive titania surface heterojunction system and its optimum application conditions. It provides the possibility of application in the degradation of industrial wastewater and environmental treatment.

A comparative study on stress and compliance based structural topology optimization

NASA Astrophysics Data System (ADS)

Hailu Shimels, G.; Dereje Engida, W.; Fakhruldin Mohd, H.

2017-10-01

Most of structural topology optimization problems have been formulated and solved to either minimize compliance or weight of a structure under volume or stress constraints, respectively. Even if, a lot of researches are conducted on these two formulation techniques separately, there is no clear comparative study between the two approaches. This paper intends to compare these formulation techniques, so that an end user or designer can choose the best one based on the problems they have. Benchmark problems under the same boundary and loading conditions are defined, solved and results are compared based on these formulations. Simulation results shows that the two formulation techniques are dependent on the type of loading and boundary conditions defined. Maximum stress induced in the design domain is higher when the design domains are formulated using compliance based formulations. Optimal layouts from compliance minimization formulation has complex layout than stress based ones which may lead the manufacturing of the optimal layouts to be challenging. Optimal layouts from compliance based formulations are dependent on the material to be distributed. On the other hand, optimal layouts from stress based formulation are dependent on the type of material used to define the design domain. High computational time for stress based topology optimization is still a challenge because of the definition of stress constraints at element level. Results also shows that adjustment of convergence criterions can be an alternative solution to minimize the maximum stress developed in optimal layouts. Therefore, a designer or end user should choose a method of formulation based on the design domain defined and boundary conditions considered.

A Novel Technique that Enables Efficient Conduct of Simultaneous Isomerization and Fermentation (SIF) of Xylose

NASA Astrophysics Data System (ADS)

Rao, Kripa; Chelikani, Silpa; Relue, Patricia; Varanasi, Sasidhar

Of the sugars recovered from lignocellulose, D-glucose can be readily converted into ethanol by baker's or brewer's yeast (Saccharomyces cerevisiae). However, xylose that is obtained by the hydrolysis of the hemicellulosic portion is not fermentable by the same species of yeasts. Xylose fermentation by native yeasts can be achieved via isomerization of xylose to its ketose isomer, xylulose. Isomerization with exogenous xylose isomerase (XI) occurs optimally at a pH of 7-8, whereas subsequent fermentation of xylulose to ethanol occurs at a pH of 4-5. We present a novel scheme for efficient isomerization of xylose to xylulose at conditions suitable for the fermentation by using an immobilized enzyme system capable of sustaining two different pH microenvironments in a single vessel. The proof-of-concept of the two-enzyme pellet is presented, showing conversion of xylose to xylulose even when the immobilized enzyme pellets are suspended in a bulk solution whose pH is sub-optimal for XI activity. The co-immobilized enzyme pellets may prove extremely valuable in effectively conducting "simultaneous isomerization and fermentation" (SIF) of xylose. To help further shift the equilibrium in favor of xylulose formation, sodium tetraborate (borax) was added to the isomerization solution. Binding of tetrahydroxyborate ions to xylulose effectively reduces the concentration of xylulose and leads to increased xylose isomerization. The formation of tetrahydroxyborate ions and the enhancement in xylulose production resulting from the complexation was studied at two different bulk pH values. The addition of 0.05 M borax to the isomerization solution containing our co-immobilized enzyme pellets resulted in xylose to xylulose conversion as high as 86% under pH conditions that are suboptimal for XI activity. These initial findings, which can be optimized for industrial conditions, have significant potential for increasing the yield of ethanol from xylose in an SIF approach.

Wine and maths: mathematical solutions to wine-inspired problems

NASA Astrophysics Data System (ADS)

Cadeddu, L.; Cauli, A.

2018-04-01

We deal with an application of partial differential equations to the correct definition of a wine cellar. We present some historical details about this problem. We also discuss how to build or renew a wine cellar, creating ideal conditions for the ageing process and improving the quality of wines. Our goal is to calculate the optimal depth z0 of a wine cellar in order to attenuate the periodic temperature fluctuations. What follows is a kind of survey of wine-related and optimization problems which have been solved by means of powerful math tools.

On the optimization of endoreversible processes

NASA Astrophysics Data System (ADS)

Pescetti, D.

2014-03-01

This paper is intended for undergraduates and specialists in thermodynamics and related areas. We consider and discuss the optimization of endoreversible thermodynamic processes under the condition of maximum work production. Explicit thermodynamic analyses of the solutions are carried out for the Novikov and Agrawal processes. It is shown that the efficiencies at maximum work production and maximum power output are not necessarily equal. They are for the Novikov process but not for the Agrawal process. The role of the constraints is put into evidence. The physical aspects are enhanced by the simplicity of the involved mathematics.

Computational methods for aerodynamic design using numerical optimization

NASA Technical Reports Server (NTRS)

Peeters, M. F.

1983-01-01

Five methods to increase the computational efficiency of aerodynamic design using numerical optimization, by reducing the computer time required to perform gradient calculations, are examined. The most promising method consists of drastically reducing the size of the computational domain on which aerodynamic calculations are made during gradient calculations. Since a gradient calculation requires the solution of the flow about an airfoil whose geometry was slightly perturbed from a base airfoil, the flow about the base airfoil is used to determine boundary conditions on the reduced computational domain. This method worked well in subcritical flow.

Determining Optimal Microwave Antigen Retrieval Conditions for Microtubule-Associated Protein 2 Immunohistochemistry in the Guinea Pig Brain

DTIC Science & Technology

2002-12-01

sections of formalin-fixed guinea pig brains using different MAP-2 monoclonal antibodies. Brain sections were boiled in sodium citrate, citric acid...citric acid solution at pH 6.0 is the optimal microwave-assisted AR method for immunolabeling MAP-2 in formalin-fixed, paraffin-processed guinea pig brain...studies on archival guinea pig brain paraffin blocks, ultimately relaxing the use of additional animals to evaluate changes in MAP-2 expression between chemical warfare nerve agent-treated and control samples.

[Characterization and optimization of the NaOH-EDTA extracts for solution 31P-NMR analysis of organic phosphorus in river sediments].

PubMed

Zhang, Wen-Qiang; Shan, Bao-Qing; Zhang, Hong; Tang, Wen-Zhong

2014-01-01

Optimization and mechanism of NaOH-EDTA extraction solutions were studied in phosphorus (P) pollution river sediments, which were Fe, Al-rich sediment, by solution 31P nuclear magnetic resonance spectroscopy (31P-NMR). Different proportions of NaOH and EDTA showed different extraction efficiency on total P (TP) and organic P (Po) in the sediment. The concentration of Po in NaOH + EDTA extract was higher than that in NaOH extract. The mechanism was that the TP and Po were released under the conditions of EDTA chelating with Fe and Al. The concentration of TP and Po were the highest in 1.00 mol x L(-1) NaOH +75 mmol x L(-1) EDTA extract and 0.25 mol x L(-1) NaOH + 50 mmol x L(-1) EDTA extract, which were 3.88 mg x g(-1) and 0.24 mg x g(-1), respectively. The extractions of Fe, Mn, Ca, Mg, Al were increasing as the EDTA increased under the same NaOH concentration. Extraction efficiency of Fe, Mn, Ca showed negative correlation with the pH of the extracting solution (P < 0.01). Exponential relationship was found between the extraction of Al and the pH of the extraction solution (P < 0.01) because of the AlO2- and EDTA-Al complex. The quality of spectra of NaOH-EDTA extract was better than that of NaOH extract. Six P species were detected in different extractions, including phosphonates, orthophosphate, pyrophosphate, orthophosphate monoesters, phospholipids and deoxyribonucleic acids. Therefore, 0. 25 mol x L(-1) NaOH + 50 mmol x L(-1) EDTA was the optimization extraction solution for Po analysis in Fe and Al-rich river sediment by 31P-NMR.

Study on gold concentrate leaching by iodine-iodide

NASA Astrophysics Data System (ADS)

Wang, Hai-xia; Sun, Chun-bao; Li, Shao-ying; Fu, Ping-feng; Song, Yu-guo; Li, Liang; Xie, Wen-qing

2013-04-01

Gold extraction by iodine-iodide solution is an effective and environment-friendly method. In this study, the method using iodine-iodide for gold leaching is proved feasible through thermodynamic calculation. At the same time, experiments on flotation gold concentrates were carried out and encouraging results were obtained. Through optimizing the technological conditions, the attained high gold leaching rate is more than 85%. The optimum process conditions at 25°C are shown as follows: the initial iodine concentration is 1.0%, the iodine-to-iodide mole ratio is 1:8, the solution pH value is 7, the liquid-to-solid mass ratio is 4:1, the leaching time is 4 h, the stirring intensity is 200 r/mim, and the hydrogen peroxide consumption is 1%.

Precision of computer vision systems for real-time inspection of contact wire wear in railways

NASA Astrophysics Data System (ADS)

Borromeo, Susana; Aparicio, Jose L.

2005-02-01

This paper is oriented to study techniques to improve the precision of the systems for wear measurement of contact wire in the railways. The problematic of wear measurement characterized by some important determining factors like rate of sampling and auscultation conditions is studied in detail. The different solutions to resolve the problematic successfully are examined. Issues related to image acquisition and image processing are discussed. Type of illumination and sensors employed, image processing hardware and image processing algorithms are some topics studied. Once analyzed each one factor which have influence on the precision of the measurement system, there are proposed an assembly of solutions that allow to optimize the conditions under which the inspection can be carried out.

Cryopreservation of coconut (Cocos nucifera L.) zygotic embryos by vitrification.

PubMed

Sajini, K K; Karun, A; Amamath, C H; Engelmann, F

2011-01-01

The present study investigates the effect of preculture conditions, vitrification and unloading solutions on survival and regeneration of coconut zygotic embryos after cryopreservation. Among the seven plant vitrification solutions tested, PVS3 was found to be the most effective for regeneration of cryopreserved embryos. The optimal protocol involved preculture of embryos for 3 days on medium with 0.6 M sucrose, PVS3 treatment for 16 h, rapid cooling and rewarming and unloading in 1.2 M sucrose liquid medium for 1.5 h. Under these conditions, 70-80 survival (corresponding to size enlargement and weight gain) was observed with cryopreserved embryos and 20-25 percent of the plants regenerated (showing normal shoot and root growth) from cryopreserved embryos were established in pots.

Use of Taguchi methodology to enhance the yield of caffeine removal with growing cultures of Pseudomonas pseudoalcaligenes.

PubMed

Ashengroph, Morahem; Ababaf, Sajad

2014-12-01

Microbial caffeine removal is a green solution for treatment of caffeinated products and agro-industrial effluents. We directed this investigation to optimizing a bio-decaffeination process with growing cultures of Pseudomonas pseudoalcaligenes through Taguchi methodology which is a structured statistical approach that can be lowered variations in a process through Design of Experiments (DOE). Five parameters, i.e. initial fructose, tryptone, Zn(+2) ion and caffeine concentrations and also incubation time selected and an L16 orthogonal array was applied to design experiments with four 4-level factors and one 3-level factor (4(4) × 1(3)). Data analysis was performed using the statistical analysis of variance (ANOVA) method. Furthermore, the optimal conditions were determined by combining the optimal levels of the significant factors and verified by a confirming experiment. Measurement of residual caffeine concentration in the reaction mixture was performed using high-performance liquid chromatography (HPLC). Use of Taguchi methodology for optimization of design parameters resulted in about 86.14% reduction of caffeine in 48 h incubation when 5g/l fructose, 3 mM Zn(+2) ion and 4.5 g/l of caffeine are present in the designed media. Under the optimized conditions, the yield of degradation of caffeine (4.5 g/l) by the native strain of Pseudomonas pseudoalcaligenes TPS8 has been increased from 15.8% to 86.14% which is 5.4 fold higher than the normal yield. According to the experimental results, Taguchi methodology provides a powerful methodology for identifying the favorable parameters on caffeine removal using strain TPS8 which suggests that the approach also has potential application with similar strains to improve the yield of caffeine removal from caffeine containing solutions.

An improved hybrid of particle swarm optimization and the gravitational search algorithm to produce a kinetic parameter estimation of aspartate biochemical pathways.

PubMed

Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal

2017-12-01

Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

An Incentive-based Online Optimization Framework for Distribution Grids

DOE PAGES

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun; ...

2017-10-09

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

An Incentive-based Online Optimization Framework for Distribution Grids

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

Zhou, Xinyang; Dall'Anese, Emiliano; Chen, Lijun

This article formulates a time-varying social-welfare maximization problem for distribution grids with distributed energy resources (DERs) and develops online distributed algorithms to identify (and track) its solutions. In the considered setting, network operator and DER-owners pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. The proposed algorithm affords an online implementation to enable tracking of the solutions in the presence of time-varying operational conditions and changing optimization objectives. It involves a strategy where the network operator collects voltage measurements throughout the feeder to build incentive signals for the DER-owners in real time; DERs thenmore » adjust the generated/consumed powers in order to avoid the violation of the voltage constraints while maximizing given objectives. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Optimizing atomic force microscopy for characterization of diamond-protein interfaces

NASA Astrophysics Data System (ADS)

Rezek, Bohuslav; Ukraintsev, Egor; Kromka, Alexander

2011-12-01

Atomic force microscopy (AFM) in contact mode and tapping mode is employed for high resolution studies of soft organic molecules (fetal bovine serum proteins) on hard inorganic diamond substrates in solution and air. Various effects in morphology and phase measurements related to the cantilever spring constant, amplitude of tip oscillations, surface approach, tip shape and condition are demonstrated and discussed based on the proposed schematic models. We show that both diamond and proteins can be mechanically modified by Si AFM cantilever. We propose how to choose suitable cantilever type, optimize scanning parameters, recognize and minimize various artifacts, and obtain reliable AFM data both in solution and in air to reveal microscopic characteristics of protein-diamond interfaces. We also suggest that monocrystalline diamond is well defined substrate that can be applicable for fundamental studies of molecules on surfaces in general.

On the solution of evolution equations based on multigrid and explicit iterative methods

NASA Astrophysics Data System (ADS)

Zhukov, V. T.; Novikova, N. D.; Feodoritova, O. B.

2015-08-01

Two schemes for solving initial-boundary value problems for three-dimensional parabolic equations are studied. One is implicit and is solved using the multigrid method, while the other is explicit iterative and is based on optimal properties of the Chebyshev polynomials. In the explicit iterative scheme, the number of iteration steps and the iteration parameters are chosen as based on the approximation and stability conditions, rather than on the optimization of iteration convergence to the solution of the implicit scheme. The features of the multigrid scheme include the implementation of the intergrid transfer operators for the case of discontinuous coefficients in the equation and the adaptation of the smoothing procedure to the spectrum of the difference operators. The results produced by these schemes as applied to model problems with anisotropic discontinuous coefficients are compared.

Control of mechanical systems by the mixed "time and expenditure" criterion

NASA Astrophysics Data System (ADS)

Alesova, I. M.; Babadzanjanz, L. K.; Pototskaya, I. Yu.; Pupysheva, Yu. Yu.; Saakyan, A. T.

2018-05-01

The optimal controlled motion of a mechanical system, that is determined by the linear system ODE with constant coefficients and piecewise constant control components, is considered. The number of control switching points and the heights of control steps are considered as preset. The optimized functional is combination of classical time criteria and "Expenditure criteria", that is equal to the total area of all steps of all control components. In the absence of control, the solution of the system is equal to the sum of components (frequency components) corresponding to different eigenvalues of the matrix of the ODE system. Admissible controls are those that turn to zero (at a non predetermined time moment) the previously chosen frequency components of the solution. An algorithm for the finding of control switching points, based on the necessary minimum conditions for mixed criteria, is proposed.

Investigation of extractive microbial transformation in nonionic surfactant micelle aqueous solution using response surface methodology.

PubMed

Xue, Yingying; Qian, Chen; Wang, Zhilong; Xu, Jian-He; Yang, Rude; Qi, Hanshi

2010-01-01

Extractive microbial transformation of L-phenylacetylcarbinol (L-PAC) in nonionic surfactant Triton X-100 micelle aqueous solution was investigated by response surface methodology. Based on the Box-Behnken design, a mathematical model was developed for the predication of mutual interactions between benzaldehyde, Triton X-100, and glucose on L-PAC production. It indicated that the negative or positive effect of nonionic surfactant strongly depended on the substrate concentration. The model predicted that the optimal concentration of benzaldehyde, Triton X-100, and glucose was 1.2 ml, 15 g, and 2.76 g per 100 ml, respectively. Under the optimal condition, the maximum L-PAC production was 27.6 mM, which was verified by a time course of extractive microbial transformation. A discrete fed-batch process for verification of cell activity was also presented.

Singular-Arc Time-Optimal Trajectory of Aircraft in Two-Dimensional Wind Field

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2006-01-01

This paper presents a study of a minimum time-to-climb trajectory analysis for aircraft flying in a two-dimensional altitude dependent wind field. The time optimal control problem possesses a singular control structure when the lift coefficient is taken as a control variable. A singular arc analysis is performed to obtain an optimal control solution on the singular arc. Using a time-scale separation with the flight path angle treated as a fast state, the dimensionality of the optimal control solution is reduced by eliminating the lift coefficient control. A further singular arc analysis is used to decompose the original optimal control solution into the flight path angle solution and a trajectory solution as a function of the airspeed and altitude. The optimal control solutions for the initial and final climb segments are computed using a shooting method with known starting values on the singular arc The numerical results of the shooting method show that the optimal flight path angle on the initial and final climb segments are constant. The analytical approach provides a rapid means for analyzing a time optimal trajectory for aircraft performance.

Application of dragonfly algorithm for optimal performance analysis of process parameters in turn-mill operations- A case study

NASA Astrophysics Data System (ADS)

Vikram, K. Arun; Ratnam, Ch; Lakshmi, VVK; Kumar, A. Sunny; Ramakanth, RT

2018-02-01

Meta-heuristic multi-response optimization methods are widely in use to solve multi-objective problems to obtain Pareto optimal solutions during optimization. This work focuses on optimal multi-response evaluation of process parameters in generating responses like surface roughness (Ra), surface hardness (H) and tool vibration displacement amplitude (Vib) while performing operations like tangential and orthogonal turn-mill processes on A-axis Computer Numerical Control vertical milling center. Process parameters like tool speed, feed rate and depth of cut are considered as process parameters machined over brass material under dry condition with high speed steel end milling cutters using Taguchi design of experiments (DOE). Meta-heuristic like Dragonfly algorithm is used to optimize the multi-objectives like ‘Ra’, ‘H’ and ‘Vib’ to identify the optimal multi-response process parameters combination. Later, the results thus obtained from multi-objective dragonfly algorithm (MODA) are compared with another multi-response optimization technique Viz. Grey relational analysis (GRA).

On-board autonomous attitude maneuver planning for planetary spacecraft using genetic algorithms

NASA Technical Reports Server (NTRS)

Kornfeld, Richard P.

2003-01-01

A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.

Variational Methods in Sensitivity Analysis and Optimization for Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Hou, G. J.-W.; Tiwari, S. N. (Principal Investigator)

1996-01-01

Variational methods (VM) sensitivity analysis, which is the continuous alternative to the discrete sensitivity analysis, is employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The determination of the sensitivity derivatives of the performance index or functional entails the coupled solutions of the state and costate equations. As the stable and converged numerical solution of the costate equations with their boundary conditions are a priori unknown, numerical stability analysis is performed on both the state and costate equations. Thereafter, based on the amplification factors obtained by solving the generalized eigenvalue equations, the stability behavior of the costate equations is discussed and compared with the state (Euler) equations. The stability analysis of the costate equations suggests that the converged and stable solution of the costate equation is possible only if the computational domain of the costate equations is transformed to take into account the reverse flow nature of the costate equations. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Runway Exit Designs for Capacity Improvement Demonstrations. Phase 1: Algorithm Development

NASA Technical Reports Server (NTRS)

Trani, A. A.; Hobeika, A. G.; Sherali, H.; Kim, B. J.; Sadam, C. K.

1990-01-01

A description and results are presented of a study to locate and design rapid runway exits under realistic airport conditions. The study developed a PC-based computer simulation-optimization program called REDIM (runway exit design interactive model) to help future airport designers and planners to locate optimal exits under various airport conditions. The model addresses three sets of problems typically arising during runway exit design evaluations. These are the evaluations of existing runway configurations, addition of new rapid runway turnoffs, and the design of new runway facilities. The model is highly interactive and allows a quick estimation of the expected value of runway occupancy time. Aircraft populations and airport environmental conditions are among the multiple inputs to the model to execute a viable runway location and geometric design solution. The results presented suggest that possible reductions on runway occupancy time (ROT) can be achieved with the use of optimally tailored rapid runway designs for a given aircraft population. Reductions of up to 9 to 6 seconds are possible with the implementation of 30 m/sec variable geometry exits.

Enhancement of simultaneous gold and copper extraction from computer printed circuit boards using Bacillus megaterium.

PubMed

Arshadi, M; Mousavi, S M

2015-01-01

In this research simultaneous gold and copper recovery from computer printed circuit boards (CPCBs) was evaluated using central composite design of response surface methodology (CCD-RSM). To maximize simultaneous metals' extraction from CPCB waste four factors which affected bioleaching were selected to be optimized. A pure culture of Bacillus megaterium, a cyanogenic bacterium, was used to produce cyanide as a leaching agent. Initial pH 10, pulp density 2g/l, particle mesh#100 and glycine concentration 0.5g/l were obtained as optimal conditions. Gold and copper were extracted simultaneously at about 36.81 and 13.26% under optimum conditions, respectively. To decrease the copper effect as an interference agent in the leaching solution, a pretreatment strategy was examined. For this purpose firstly using Acidithiobacillus ferrooxidans copper in the CPCB powder was totally extracted, then the residual sediment was subjected to further experiments for gold recovery by B. megaterium. Using pretreated sample under optimal conditions 63.8% gold was extracted. Copyright © 2014 Elsevier Ltd. All rights reserved.

Necessary and sufficient optimality conditions for classical simulations of quantum communication processes

NASA Astrophysics Data System (ADS)

Montina, Alberto; Wolf, Stefan

2014-07-01

We consider the process consisting of preparation, transmission through a quantum channel, and subsequent measurement of quantum states. The communication complexity of the channel is the minimal amount of classical communication required for classically simulating it. Recently, we reduced the computation of this quantity to a convex minimization problem with linear constraints. Every solution of the constraints provides an upper bound on the communication complexity. In this paper, we derive the dual maximization problem of the original one. The feasible points of the dual constraints, which are inequalities, give lower bounds on the communication complexity, as illustrated with an example. The optimal values of the two problems turn out to be equal (zero duality gap). By this property, we provide necessary and sufficient conditions for optimality in terms of a set of equalities and inequalities. We use these conditions and two reasonable but unproven hypotheses to derive the lower bound n ×2n -1 for a noiseless quantum channel with capacity equal to n qubits. This lower bound can have interesting consequences in the context of the recent debate on the reality of the quantum state.

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

DOE PAGES

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok; ...

2016-01-01

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Unified theory for inhomogeneous thermoelectric generators and coolers including multistage devices.

PubMed

Gerstenmaier, York Christian; Wachutka, Gerhard

2012-11-01

A novel generalized Lagrange multiplier method for functional optimization with inclusion of subsidiary conditions is presented and applied to the optimization of material distributions in thermoelectric converters. Multistaged devices are considered within the same formalism by inclusion of position-dependent electric current in the legs leading to a modified thermoelectric equation. Previous analytical solutions for maximized efficiencies for generators and coolers obtained by Sherman [J. Appl. Phys. 31, 1 (1960)], Snyder [Phys. Rev. B 86, 045202 (2012)], and Seifert et al. [Phys. Status Solidi A 207, 760 (2010)] by a method of local optimization of reduced efficiencies are recovered by independent proof. The outstanding maximization problems for generated electric power and cooling power can be solved swiftly numerically by solution of a differential equation-system obtained within the new formalism. As far as suitable materials are available, the inhomogeneous TE converters can have increased performance by use of purely temperature-dependent material properties in the thermoelectric legs or by use of purely spatial variation of material properties or by a combination of both. It turns out that the optimization domain is larger for the second kind of device which can, thus, outperform the first kind of device.

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

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

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Calculating complete and exact Pareto front for multiobjective optimization: a new deterministic approach for discrete problems.

PubMed

Hu, Xiao-Bing; Wang, Ming; Di Paolo, Ezequiel

2013-06-01

Searching the Pareto front for multiobjective optimization problems usually involves the use of a population-based search algorithm or of a deterministic method with a set of different single aggregate objective functions. The results are, in fact, only approximations of the real Pareto front. In this paper, we propose a new deterministic approach capable of fully determining the real Pareto front for those discrete problems for which it is possible to construct optimization algorithms to find the k best solutions to each of the single-objective problems. To this end, two theoretical conditions are given to guarantee the finding of the actual Pareto front rather than its approximation. Then, a general methodology for designing a deterministic search procedure is proposed. A case study is conducted, where by following the general methodology, a ripple-spreading algorithm is designed to calculate the complete exact Pareto front for multiobjective route optimization. When compared with traditional Pareto front search methods, the obvious advantage of the proposed approach is its unique capability of finding the complete Pareto front. This is illustrated by the simulation results in terms of both solution quality and computational efficiency.

Optimization of palm oil extraction from Decanter cake of small crude palm oil mill by aqueous surfactant solution using RSM

NASA Astrophysics Data System (ADS)

Ahmadi Pirshahid, Shewa; Arirob, Wallop; Punsuvon, Vittaya

2018-04-01

The use of hexane to extract vegetable oil from oilseeds or seed cake is of growing concern due to its environmental impact such as its smelling and toxicity. In our method, used Response Surface Methodology (RSM) was applied to study the optimum condition of decanter cake obtained from small crude palm oil with aqueous surfactant solution. For the first time, we provide an optimum condition of preliminary study with decanter cake extraction to obtain the maximum of oil yield. The result from preliminary was further used in RSM study by using Central Composite Design (CCD) that consisted of thirty experiments. The effect of four independent variables: the concentration of Sodium Dodecyl Sulfate (SDS) as surfactant, temperature, the ratio by weight to volume of cake to surfactant solution and the amount of sodium chloride (NaCl) on dependent variables are studied. Data were analyzed using Design-Expert 8 software. The results showed that the optimum condition of decanter cake extraction were 0.016M of SDS solution concentration, 73°C of extraction temperature, 1:10 (g:ml) of the ratio of decanter cake to SDS solution and 2% (w/w) of NaCl amount. This condition gave 77.05% (w/w) oil yield. The chemical properties of the extracted palm oil from this aqueous surfactant extraction are further investigated compared with the hexane extraction. The obtained result showed that all properties of both extractions were nearly the same.

Molecular dynamics study on glycolic acid in the physiological salt solution

NASA Astrophysics Data System (ADS)

Matsunaga, S.

2018-05-01

Molecular dynamics (MD) study on glycolic acid in the physiological salt solution has been performed, which is a model of a biofuel cell. The structure and charge distribution of glycolic acid in aqueous solution used in MD is beforehand optimized by Gaussian09 utilizing the density functional theory. MD is performed in the NTV constant condition, i.e. the number of particles, temperature, and volume of MD cell are definite. The structure difference of the glycolic acid and oxalic acid is detected by the water distribution around the molecules using the pair distribution functions, gij(r), and the frequency dependent diffusion coefficients, Di(ν). The anomalous dielectric constant of the solution, i.e. about 12 times larger than that of water, has been obtained, which may be attributed to the ion pair formation in the solution.

A new approach for improving reliability of personal navigation devices under harsh GNSS signal conditions.

PubMed

Dhital, Anup; Bancroft, Jared B; Lachapelle, Gérard

2013-11-07

In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach.

A New Approach for Improving Reliability of Personal Navigation Devices under Harsh GNSS Signal Conditions

PubMed Central

Dhital, Anup; Bancroft, Jared B.; Lachapelle, Gérard

2013-01-01

In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach. PMID:24212120

Optimal Stabilization of Social Welfare under Small Variation of Operating Condition with Bifurcation Analysis

NASA Astrophysics Data System (ADS)

Chanda, Sandip; De, Abhinandan

2016-12-01

A social welfare optimization technique has been proposed in this paper with a developed state space based model and bifurcation analysis to offer substantial stability margin even in most inadvertent states of power system networks. The restoration of the power market dynamic price equilibrium has been negotiated in this paper, by forming Jacobian of the sensitivity matrix to regulate the state variables for the standardization of the quality of solution in worst possible contingencies of the network and even with co-option of intermittent renewable energy sources. The model has been tested in IEEE 30 bus system and illustrious particle swarm optimization has assisted the fusion of the proposed model and methodology.

Optimal plane change during constant altitude hypersonic flight

NASA Technical Reports Server (NTRS)

Mease, K. D.; Vinh, N. X.; Kuo, S. H.

1988-01-01

Future spacecraft operating in the vicinity of the earth may have resort to the atmosphere as an aid in effecting orbital change. While a previous treatment of this technique chose constant altitude, speed, and angle-of-attack values in order to maximize the plane change for a fixed amount of propellant consumption during hypersonic flight, the former two parameters are presently released from the constraint of constancy. The general characteristics of the optimal controls are described on the basis of the domain of maneuverability, and numerical solutions are obtained for several specific cases. Under the condition of constant-altitude flight, it is generally not optimal to fly at constant angle-of-attack.

A note on resource allocation scheduling with group technology and learning effects on a single machine

NASA Astrophysics Data System (ADS)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

Englander, Jacob; Englander, Arnold

2014-01-01

Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.

A Convex Formulation for Learning a Shared Predictive Structure from Multiple Tasks

PubMed Central

Chen, Jianhui; Tang, Lei; Liu, Jun; Ye, Jieping

2013-01-01

In this paper, we consider the problem of learning from multiple related tasks for improved generalization performance by extracting their shared structures. The alternating structure optimization (ASO) algorithm, which couples all tasks using a shared feature representation, has been successfully applied in various multitask learning problems. However, ASO is nonconvex and the alternating algorithm only finds a local solution. We first present an improved ASO formulation (iASO) for multitask learning based on a new regularizer. We then convert iASO, a nonconvex formulation, into a relaxed convex one (rASO). Interestingly, our theoretical analysis reveals that rASO finds a globally optimal solution to its nonconvex counterpart iASO under certain conditions. rASO can be equivalently reformulated as a semidefinite program (SDP), which is, however, not scalable to large datasets. We propose to employ the block coordinate descent (BCD) method and the accelerated projected gradient (APG) algorithm separately to find the globally optimal solution to rASO; we also develop efficient algorithms for solving the key subproblems involved in BCD and APG. The experiments on the Yahoo webpages datasets and the Drosophila gene expression pattern images datasets demonstrate the effectiveness and efficiency of the proposed algorithms and confirm our theoretical analysis. PMID:23520249

Fabrication and performance of PET mesh enhanced cellulose acetate membranes for forward osmosis.

PubMed

Li, Guoliang; Wang, Jun; Hou, Deyin; Bai, Yu; Liu, Huijuan

2016-07-01

Polyethylene terephthalate mesh (PET) enhanced cellulose acetate membranes were fabricated via a phase inversion process. The membrane fabrication parameters that may affect the membrane performance were systematically evaluated including the concentration and temperature of the casting polymer solution and the temperature and time of the evaporation, coagulation and annealing processes. The water permeability and reverse salt flux were measured in forward osmosis (FO) mode for determination of the optimal membrane fabrication conditions. The optimal FO membrane shows a typical asymmetric sandwich structure with a mean thickness of about 148.2μm. The performance of the optimal FO membrane was tested using 0.2mol/L NaCl as the feed solution and 1.5mol/L glucose as the draw solution. The membrane displayed a water flux of 3.47L/(m(2)·hr) and salt rejection of 95.48% in FO mode. While in pressure retarded osmosis (PRO) mode, the water flux was 4.74L/(m(2)·hr) and salt rejection 96.03%. The high ratio of water flux in FO mode to that in PRO mode indicates that the fabricated membrane has a lower degree of internal concentration polarization than comparable membranes. Copyright © 2016. Published by Elsevier B.V.

Preparation and optimization of submicron chitosan capsules by water-based electrospraying for food and bioactive packaging applications.

PubMed

Sreekumar, Sruthi; Lemke, Philipp; Moerschbacher, Bruno M; Torres-Giner, Sergio; Lagaron, Jose M

2017-10-01

In the present study, a well-defined set of chitosans, with different degrees of acetylation (DA) and degrees of polymerization (DP), were processed by solution electrospraying from a water-based solvent. The solution properties, in terms of surface tension, conductivity, viscosity, and pH, were characterized and related to the physico-chemical properties of the chitosans. It was observed that both DA and DP values of a given chitosan, in combination with biopolymer concentration, mainly determined solution viscosity. This was, in turn, the major driving factor that defined the electrosprayability of chitosan. In addition, the physico-chemical properties of chitosans highly influenced solution conductivity and results indicated that the chitosan solutions with low or low-to-medium values of conductivity were the most optimal for electrospraying. The results obtained here also demonstrate that a good process control can be achieved by adjusting the working conditions, i.e. applied voltage, flow-rate, and tip-to-collector distance. Finally, it was also shown that electrosprayability of chitosan with inadequate physico-chemical properties can be improved by solution mixing of very different kinds of this polysaccharide. The resultant electrosprayed submicron chitosan capsules can be applied for encapsulation of food additives and to develop bioactive coatings of interest in food packaging, where these particles alone or containing functional ingredients can be released from the package into the food to promote a health benefit.

Optimal control of multiplicative control systems arising from cancer therapy

NASA Technical Reports Server (NTRS)

Bahrami, K.; Kim, M.

1975-01-01

This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.

Optimal thrust level for orbit insertion

NASA Astrophysics Data System (ADS)

Cerf, Max

2017-07-01

The minimum-fuel orbital transfer is analyzed in the case of a launcher upper stage using a constantly thrusting engine. The thrust level is assumed to be constant and its value is optimized together with the thrust direction. A closed-loop solution for the thrust direction is derived from the extremal analysis for a planar orbital transfer. The optimal control problem reduces to two unknowns, namely the thrust level and the final time. Guessing and propagating the costates is no longer necessary and the optimal trajectory is easily found from a rough initialization. On the other hand the initial costates are assessed analytically from the initial conditions and they can be used as initial guess for transfers at different thrust levels. The method is exemplified on a launcher upper stage targeting a geostationary transfer orbit.

Wine and Maths: Mathematical Solutions to Wine-Inspired Problems

ERIC Educational Resources Information Center

Cadeddu, L.; Cauli, A.

2018-01-01

We deal with an application of partial differential equations to the correct definition of a wine cellar. We present some historical details about this problem. We also discuss how to build or renew a wine cellar, creating ideal conditions for the ageing process and improving the quality of wines. Our goal is to calculate the optimal depth…

LDRD Final Report: Global Optimization for Engineering Science Problems

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

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Optimizing Cu(II) removal from aqueous solution by magnetic nanoparticles immobilized on activated carbon using Taguchi method.

PubMed

Ebrahimi Zarandi, Mohammad Javad; Sohrabi, Mahmoud Reza; Khosravi, Morteza; Mansouriieh, Nafiseh; Davallo, Mehran; Khosravan, Azita

2016-01-01

This study synthesized magnetic nanoparticles (Fe(3)O(4)) immobilized on activated carbon (AC) and used them as an effective adsorbent for Cu(II) removal from aqueous solution. The effect of three parameters, including the concentration of Cu(II), dosage of Fe(3)O(4)/AC magnetic nanocomposite and pH on the removal of Cu(II) using Fe(3)O(4)/AC nanocomposite were studied. In order to examine and describe the optimum condition for each of the mentioned parameters, Taguchi's optimization method was used in a batch system and L9 orthogonal array was used for the experimental design. The removal percentage (R%) of Cu(II) and uptake capacity (q) were transformed into an accurate signal-to-noise ratio (S/N) for a 'larger-the-better' response. Taguchi results, which were analyzed based on choosing the best run by examining the S/N, were statistically tested using analysis of variance; the tests showed that all the parameters' main effects were significant within a 95% confidence level. The best conditions for removal of Cu(II) were determined at pH of 7, nanocomposite dosage of 0.1 gL(-1) and initial Cu(II) concentration of 20 mg L(-1) at constant temperature of 25 °C. Generally, the results showed that the simple Taguchi's method is suitable to optimize the Cu(II) removal experiments.

Engineering of layered, lipid-encapsulated drug nanoparticles through spray-drying.

PubMed

Sapra, Mahak; Mayya, Y S; Venkataraman, Chandra

2017-06-01

Drug-containing nanoparticles have been synthesized through the spray-drying of submicron droplet aerosols by using matrix materials such as lipids and biopolymers. Understanding layer formation in composite nanoparticles is essential for the appropriate engineering of particle substructures. The present study developed a droplet-shrinkage model for predicting the solid-phase formation of two non-volatile solutes-stearic acid lipid and a set of drugs, by considering molecular volume and solubility. Nanoparticle formation was simulated to define the parameter space of material properties and process conditions for the formation of a layered structure with the preferential accumulation of the lipid in the outer layer. Moreover, lipid-drug demarcation diagrams representing a set of critical values of ratios of solute properties at which the two solutes precipitate simultaneously were developed. The model was validated through the preparation of stearic acid-isoniazid nanoparticles under controlled processing conditions. The developed model can guide the selection of solvents, lipids, and processing conditions such that drug loading and lipid encapsulation in composite nanoparticles are optimized. Copyright © 2017 Elsevier B.V. All rights reserved.

Unsteady-flow-field predictions for oscillating cascades

NASA Technical Reports Server (NTRS)

Huff, Dennis L.

1991-01-01

The unsteady flow field around an oscillating cascade of flat plates with zero stagger was studied by using a time marching Euler code. This case had an exact solution based on linear theory and served as a model problem for studying pressure wave propagation in the numerical solution. The importance of using proper unsteady boundary conditions, grid resolution, and time step size was shown for a moderate reduced frequency. Results show that an approximate nonreflecting boundary condition based on linear theory does a good job of minimizing reflections from the inflow and outflow boundaries and allows the placement of the boundaries to be closer to the airfoils than when reflective boundaries are used. Stretching the boundary to dampen the unsteady waves is another way to minimize reflections. Grid clustering near the plates captures the unsteady flow field better than when uniform grids are used as long as the 'Courant Friedrichs Levy' (CFL) number is less than 1 for a sufficient portion of the grid. Finally, a solution based on an optimization of grid, CFL number, and boundary conditions shows good agreement with linear theory.

Dwell time algorithm based on the optimization theory for magnetorheological finishing

NASA Astrophysics Data System (ADS)

Zhang, Yunfei; Wang, Yang; Wang, Yajun; He, Jianguo; Ji, Fang; Huang, Wen

2010-10-01

Magnetorheological finishing (MRF) is an advanced polishing technique capable of rapidly converging to the required surface figure. This process can deterministically control the amount of the material removed by varying a time to dwell at each particular position on the workpiece surface. The dwell time algorithm is one of the most important key techniques of the MRF. A dwell time algorithm based on the1 matrix equation and optimization theory was presented in this paper. The conventional mathematical model of the dwell time was transferred to a matrix equation containing initial surface error, removal function and dwell time function. The dwell time to be calculated was just the solution to the large, sparse matrix equation. A new mathematical model of the dwell time based on the optimization theory was established, which aims to minimize the 2-norm or ∞-norm of the residual surface error. The solution meets almost all the requirements of precise computer numerical control (CNC) without any need for extra data processing, because this optimization model has taken some polishing condition as the constraints. Practical approaches to finding a minimal least-squares solution and a minimal maximum solution are also discussed in this paper. Simulations have shown that the proposed algorithm is numerically robust and reliable. With this algorithm an experiment has been performed on the MRF machine developed by ourselves. After 4.7 minutes' polishing, the figure error of a flat workpiece with a 50 mm diameter is improved by PV from 0.191λ(λ = 632.8 nm) to 0.087λ and RMS 0.041λ to 0.010λ. This algorithm can be constructed to polish workpieces of all shapes including flats, spheres, aspheres, and prisms, and it is capable of improving the polishing figures dramatically.

Multi-objective optimization of radiotherapy: distributed Q-learning and agent-based simulation

NASA Astrophysics Data System (ADS)

Jalalimanesh, Ammar; Haghighi, Hamidreza Shahabi; Ahmadi, Abbas; Hejazian, Hossein; Soltani, Madjid

2017-09-01

Radiotherapy (RT) is among the regular techniques for the treatment of cancerous tumours. Many of cancer patients are treated by this manner. Treatment planning is the most important phase in RT and it plays a key role in therapy quality achievement. As the goal of RT is to irradiate the tumour with adequately high levels of radiation while sparing neighbouring healthy tissues as much as possible, it is a multi-objective problem naturally. In this study, we propose an agent-based model of vascular tumour growth and also effects of RT. Next, we use multi-objective distributed Q-learning algorithm to find Pareto-optimal solutions for calculating RT dynamic dose. We consider multiple objectives and each group of optimizer agents attempt to optimise one of them, iteratively. At the end of each iteration, agents compromise the solutions to shape the Pareto-front of multi-objective problem. We propose a new approach by defining three schemes of treatment planning created based on different combinations of our objectives namely invasive, conservative and moderate. In invasive scheme, we enforce killing cancer cells and pay less attention about irradiation effects on normal cells. In conservative scheme, we take more care of normal cells and try to destroy cancer cells in a less stressed manner. The moderate scheme stands in between. For implementation, each of these schemes is handled by one agent in MDQ-learning algorithm and the Pareto optimal solutions are discovered by the collaboration of agents. By applying this methodology, we could reach Pareto treatment plans through building different scenarios of tumour growth and RT. The proposed multi-objective optimisation algorithm generates robust solutions and finds the best treatment plan for different conditions.

Controlled surface morphology and hydrophilicity of polycaprolactone toward human retinal pigment epithelium cells.

PubMed

Shahmoradi, Saleheh; Yazdian, Fatemeh; Tabandeh, Fatemeh; Soheili, Zahra-Soheila; Hatamian Zarami, Ashraf Sadat; Navaei-Nigjeh, Mona

2017-04-01

Applying scaffolds as a bed to enhance cell proliferation and even differentiation is one of the treatment of retina diseases such as age-related macular degeneration (AMD) which deteriorating photoreceptors and finally happening blindness. In this study, aligned polycaprolactone (PCL) nanofibers were electrospun and at different conditions and their characteristics were measured by scanning electron microscope (SEM) and contact angle. Response surface methodology (RSM) was used to optimize the diameter of fabricated nanofibers. Two factors as solution concentration and voltage value were considered as independent variables and their effects on nanofibers' diameters were evaluated by central composite design and the optimum conditions were obtained as 0.12g/mL and 20kV, respectively. In order to decrease the hydrophobicity of PCL, the surface of the fabricated scaffolds was modified by alkaline hydrolysis method. Contact time of the scaffolds and alkaline solution and concentration of alkaline solution were optimized using Box Behnken design and (120min and 5M were the optimal, respectively). Contact angle measurement showed the high hydrophilicity of treated scaffolds (with contact angle 7.48°). Plasma surface treatment was applied to compare the effect of using two kinds of surface modification methods simultaneously on hydrolyzed scaffolds. The RPE cells grown on scaffolds were examined by immunocytochemistry (ICC), MTT and continuous inspection of cellular morphology. Interestingly, Human RPE cells revealed their characteristic morphology on hydrolyzed scaffold well. As a result, we introduced a culture substrate with low diameter (185.8nm), high porosity (82%) and suitable hydrophilicity (with contact angle 7.48 degree) which can be promising for hRPE cell transplantation. Copyright © 2016. Published by Elsevier B.V.

The cardiac tumors - some exceptional heart conditions.

PubMed

Cristian, Ana Maria; Moraru, Oriana Elena; Goleanu, Viorel Constantin; Butuşină, Marian; Pinte, Florina; Cotoi, Bogdan Virgil; Cristian, Gabriel

2018-01-01

Cardiac tumors are exceptional cardiac conditions, since they have a minimal occurrence, according to statistics. The cardiac myxoma cases are the most dominant for the representative examples for these clinical situations. Those tumors being benign, the patients enjoy a reasonable life expectancy provided they receive an early diagnosis. In the absence of potential complications, the symptoms can vary very much and they may often be non-specific, a fact which makes it more difficult to establish a proper diagnosis and to quickly tailor the optimal therapeutic solutions. Surgery is, in the most cases, a comfortable solution, allowing the cases to be permanently healed. Nowadays, cardiac surgery provides all the needed facilities to diagnose cases at an early stage, when diagnosis is quick and accurate. This paper illustrates, by the means of two suggestive cases, how difficult it is to establish a quick positive diagnosis, which is vital for healing this condition with an evolutionary risk frequently worsen by major complications.

Optimal Design of Dialyzers.

PubMed

Mineshima, Michio

2017-01-01

Several types of synthetic dialysis membranes, including polysulfone, polyethersulfone, and polyester polymer alloy membranes, have asymmetrical structures. Dialyzers with these membranes show higher water and solute transport performance because the actual membrane thickness, which is related to the water and solute transfer resistance, is quite small compared with that in membranes with a homogeneous structure. The performance of a dialyzer depends not only on membrane permeability to water and solutes, but also on flow conditions of the blood and dialysate, which are determined during dialyzer fabrication. Many types of high-flux dialyzers with high-performance membranes have a high internal filtration/backfiltration (IF/BF) flow rate. In the enhanced IF/BF dialyzer, membrane fouling occurs more readily than with the conventional dialyzer because of the high local transmembrane pressure needed to enhance the IF/BF flow rate. To select the optimal enhanced IF/BF dialyzer for individual patients, we need to balance the disadvantage of membrane fouling with the advantage of increased convective transport. Key Messages: The following principles should guide dialyzer development in the near term. (1) Dialyzers should show high performance for the removal of low-molecular-weight proteins related to certain complications under conditions of low albumin and amino acid loss. (2) Dialyzers with biocompatible membranes are required to prevent severe adverse reactions, even though the causal relationship between these reactions and some complications remains to be clarified. © 2017 S. Karger AG, Basel.

Electrochemical synthesis and characterization of zinc oxalate nanoparticles

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

Shamsipur, Mojtaba, E-mail: mshamsipur@yahoo.com; Roushani, Mahmoud; Department of Chemistry, Ilam University, Ilam

2013-03-15

Highlights: ► Synthesis of zinc oxalate nanoparticles via electrolysis of a zinc plate anode in sodium oxalate solutions. ► Design of a Taguchi orthogonal array to identify the optimal experimental conditions. ► Controlling the size and shape of particles via applied voltage and oxalate concentration. ► Characterization of zinc oxalate nanoparticles by SEM, UV–vis, FT-IR and TG–DTA. - Abstract: A rapid, clean and simple electrodeposition method was designed for the synthesis of zinc oxalate nanoparticles. Zinc oxalate nanoparticles in different size and shapes were electrodeposited by electrolysis of a zinc plate anode in sodium oxalate aqueous solutions. It was foundmore » that the size and shape of the product could be tuned by electrolysis voltage, oxalate ion concentration, and stirring rate of electrolyte solution. A Taguchi orthogonal array design was designed to identify the optimal experimental conditions. The morphological characterization of the product was carried out by scanning electron microscopy. UV–vis and FT-IR spectroscopies were also used to characterize the electrodeposited nanoparticles. The TG–DTA studies of the nanoparticles indicated that the main thermal degradation occurs in two steps over a temperature range of 350–430 °C. In contrast to the existing methods, the present study describes a process which can be easily scaled up for the production of nano-sized zinc oxalate powder.« less

Enforcing the Courant-Friedrichs-Lewy condition in explicitly conservative local time stepping schemes

NASA Astrophysics Data System (ADS)

Gnedin, Nickolay Y.; Semenov, Vadim A.; Kravtsov, Andrey V.

2018-04-01

An optimally efficient explicit numerical scheme for solving fluid dynamics equations, or any other parabolic or hyperbolic system of partial differential equations, should allow local regions to advance in time with their own, locally constrained time steps. However, such a scheme can result in violation of the Courant-Friedrichs-Lewy (CFL) condition, which is manifestly non-local. Although the violations can be considered to be "weak" in a certain sense and the corresponding numerical solution may be stable, such calculation does not guarantee the correct propagation speed for arbitrary waves. We use an experimental fluid dynamics code that allows cubic "patches" of grid cells to step with independent, locally constrained time steps to demonstrate how the CFL condition can be enforced by imposing a constraint on the time steps of neighboring patches. We perform several numerical tests that illustrate errors introduced in the numerical solutions by weak CFL condition violations and show how strict enforcement of the CFL condition eliminates these errors. In all our tests the strict enforcement of the CFL condition does not impose a significant performance penalty.

Tip-Enhanced Raman Scattering Imaging of Two-Dimensional Tungsten Disulfide with Optimized Tip Fabrication Process.

PubMed

Lee, Chanwoo; Kim, Sung Tae; Jeong, Byeong Geun; Yun, Seok Joon; Song, Young Jae; Lee, Young Hee; Park, Doo Jae; Jeong, Mun Seok

2017-01-13

We successfully achieve the tip-enhanced nano Raman scattering images of a tungsten disulfide monolayer with optimizing a fabrication method of gold nanotip by controlling the concentration of etchant in an electrochemical etching process. By applying a square-wave voltage supplied from an arbitrary waveform generator to a gold wire, which is immersed in a hydrochloric acid solution diluted with ethanol at various ratios, we find that both the conical angle and radius of curvature of the tip apex can be varied by changing the ratio of hydrochloric acid and ethanol. We also suggest a model to explain the origin of these variations in the tip shape. From the systematic study, we find an optimal condition for achieving the yield of ~60% with the radius of ~34 nm and the cone angle of ~35°. Using representative tips fabricated under the optimal etching condition, we demonstrate the tip-enhanced Raman scattering experiment of tungsten disulfide monolayer grown by a chemical vapor deposition method with a spatial resolution of ~40 nm and a Raman enhancement factor of ~4,760.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-Test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Flight-test Results

NASA Technical Reports Server (NTRS)

Brown, Nelson Andrew; Schaefer, Jacob Robert

2013-01-01

A peak-seeking control algorithm for real-time trim optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control algorithm is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are used for optimization of fuel flow. Results from six research flights are presented herein. The optimization algorithm found a trim configuration that required approximately 3 percent less fuel flow than the baseline trim at the same flight condition. The algorithm consistently rediscovered the solution from several initial conditions. These results show that the algorithm has good performance in a relevant environment.

Modeling of organic solar cell using response surface methodology

NASA Astrophysics Data System (ADS)

Suliman, Rajab; Mitul, Abu Farzan; Mohammad, Lal; Djira, Gemechis; Pan, Yunpeng; Qiao, Qiquan

Polymer solar cells have drawn much attention during the past few decades due to their low manufacturing cost and incompatibility for flexible substrates. In solution-processed organic solar cells, the optimal thickness, annealing temperature, and morphology are key components to achieving high efficiency. In this work, response surface methodology (RSM) is used to find optimal fabrication conditions for polymer solar cells. In order to optimize cell efficiency, the central composite design (CCD) with three independent variables polymer concentration, polymer-fullerene ratio, and active layer spinning speed was used. Optimal device performance was achieved using 10.25 mg/ml polymer concentration, 0.42 polymer-fullerene ratio, and 1624 rpm of active layer spinning speed. The predicted response (the efficiency) at the optimum stationary point was found to be 5.23% for the Poly(diketopyrrolopyrrole-terthiophene) (PDPP3T)/PC60BM solar cells. Moreover, 97% of the variation in the device performance was explained by the best model. Finally, the experimental results are consistent with the CCD prediction, which proves that this is a promising and appropriate model for optimum device performance and fabrication conditions.

Optimal estimation of spatially variable recharge and transmissivity fields under steady-state groundwater flow. Part 2. Case study

NASA Astrophysics Data System (ADS)

Graham, Wendy D.; Neff, Christina R.

1994-05-01

The first-order analytical solution of the inverse problem for estimating spatially variable recharge and transmissivity under steady-state groundwater flow, developed in Part 1 is applied to the Upper Floridan Aquifer in NE Florida. Parameters characterizing the statistical structure of the log-transmissivity and head fields are estimated from 152 measurements of transmissivity and 146 measurements of hydraulic head available in the study region. Optimal estimates of the recharge, transmissivity and head fields are produced throughout the study region by conditioning on the nearest 10 available transmissivity measurements and the nearest 10 available head measurements. Head observations are shown to provide valuable information for estimating both the transmissivity and the recharge fields. Accurate numerical groundwater model predictions of the aquifer flow system are obtained using the optimal transmissivity and recharge fields as input parameters, and the optimal head field to define boundary conditions. For this case study, both the transmissivity field and the uncertainty of the transmissivity field prediction are poorly estimated, when the effects of random recharge are neglected.

Simultaneous Optimization of Tooth Flank Form of Involute Helical Gears in Terms of Both Vibration and Load Carrying Capacity

NASA Astrophysics Data System (ADS)

Komori, Masaharu; Kubo, Aizoh; Suzuki, Yoshitomo

The alignment condition of automotive gears changes considerably during operation due to the deformation of shafts, bearings, and gear box by transmission of load. Under such conditions, the gears are required to satisfy not only reliability in strength and durability under maximum loading conditions, but also low vibrational characteristics under light loading conditions during the cruising of a car. In this report, the characteristics of the optimum tooth flank form of gears in terms of both vibration and load carrying capacity are clarified. The local optimum tooth flank form appears in each excitation valley, where the vibrational excitation is low and the actual contact ratio takes a specific value. The influence of the choice of different local optimum solutions on the vibrational performance of the optimized gears is investigated. The practical design algorithm for the optimum tooth flank form of a gear set in terms of both vibration and load carrying capacity is then proposed and its result is evaluated by field experience.

Optimal Electric Vehicle Scheduling: A Co-Optimized System and Customer Perspective

NASA Astrophysics Data System (ADS)

Maigha

Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivising the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle.

Effective removal of tetracycline from aqueous solution using activated carbon prepared from tomato (Lycopersicon esculentum Mill.) industrial processing waste.

PubMed

Sayğılı, Hasan; Güzel, Fuat

2016-09-01

Activated carbon (TAC) prepared under optimized conditions with ZnCl2 activation from a new precursor; tomato industrial processing waste (TW), was applied as an adsorbent to remove tetracycline (TC) from aqueous solution. The factors (TAC dosage, initial TC concentration, contact time, ionic strength and solution temperature) affecting the adsorption process were examined at natural pH (5.7) of TAC-TC system in aqueous solution. Kinetic data was found to be best complied by the pseudo-second order model. The isotherm analysis indicated that the equilibrium data could be represented by the Langmuir model. The maximum adsorption capacity was identified as 500.0mgg(-1) at 308K. Copyright © 2016 Elsevier Inc. All rights reserved.

Variational analysis of the coupling between a geometrically exact Cosserat rod and an elastic continuum

NASA Astrophysics Data System (ADS)

Sander, Oliver; Schiela, Anton

2014-12-01

We formulate the static mechanical coupling of a geometrically exact Cosserat rod to a nonlinearly elastic continuum. In this setting, appropriate coupling conditions have to connect a one-dimensional model with director variables to a three-dimensional model without directors. Two alternative coupling conditions are proposed, which correspond to two different configuration trace spaces. For both, we show existence of solutions of the coupled problems, using the direct method of the calculus of variations. From the first-order optimality conditions, we also derive the corresponding conditions for the dual variables. These are then interpreted in mechanical terms.

How Near is a Near-Optimal Solution: Confidence Limits for the Global Optimum.

DTIC Science & Technology

1980-05-01

or near-optimal solutions are the only practical solutions available. This paper identifies and compares some procedures which use independent near...approximate or near-optimal solutions are the only practical solutions available. This paper identifies and compares some procedures which use inde- pendent...The objective of this paper is to indicate some relatively new statistical procedures for obtaining an upper confidence limit on G Each of these

Trajectory optimization for lunar rover performing vertical takeoff vertical landing maneuvers in the presence of terrain

NASA Astrophysics Data System (ADS)

Ma, Lin; Wang, Kexin; Xu, Zuhua; Shao, Zhijiang; Song, Zhengyu; Biegler, Lorenz T.

2018-05-01

This study presents a trajectory optimization framework for lunar rover performing vertical takeoff vertical landing (VTVL) maneuvers in the presence of terrain using variable-thrust propulsion. First, a VTVL trajectory optimization problem with three-dimensional kinematics and dynamics model, boundary conditions, and path constraints is formulated. Then, a finite-element approach transcribes the formulated trajectory optimization problem into a nonlinear programming (NLP) problem solved by a highly efficient NLP solver. A homotopy-based backtracking strategy is applied to enhance the convergence in solving the formulated VTVL trajectory optimization problem. The optimal thrust solution typically has a "bang-bang" profile considering that bounds are imposed on the magnitude of engine thrust. An adaptive mesh refinement strategy based on a constant Hamiltonian profile is designed to address the difficulty in locating the breakpoints in the thrust profile. Four scenarios are simulated. Simulation results indicate that the proposed trajectory optimization framework has sufficient adaptability to handle VTVL missions efficiently.

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

DTIC Science & Technology

2016-09-09

prenticeship Scheduling (COVAS), which performs ma- chine learning using human expert demonstration, in conjunction with optimization, to automatically and ef...ficiently produce optimal solutions to challenging real- world scheduling problems. COVAS first learns a policy from human scheduling demonstration via...apprentice- ship learning , then uses this initial solution to provide a tight bound on the value of the optimal solution, thereby substantially

Solution Behavior and Activity of a Halophilic Esterase under High Salt Concentration

PubMed Central

Rao, Lang; Zhao, Xiubo; Pan, Fang; Li, Yin; Xue, Yanfen; Ma, Yanhe; Lu, Jian R.

2009-01-01

Background Halophiles are extremophiles that thrive in environments with very high concentrations of salt. Although the salt reliance and physiology of these extremophiles have been widely investigated, the molecular working mechanisms of their enzymes under salty conditions have been little explored. Methodology/Principal Findings A halophilic esterolytic enzyme LipC derived from archeaon Haloarcula marismortui was overexpressed from Escherichia coli BL21. The purified enzyme showed a range of hydrolytic activity towards the substrates of p-nitrophenyl esters with different alkyl chains (n = 2−16), with the highest activity being observed for p-nitrophenyl acetate, consistent with the basic character of an esterase. The optimal esterase activities were found to be at pH 9.5 and [NaCl] = 3.4 M or [KCl] = 3.0 M and at around 45°C. Interestingly, the hydrolysis activity showed a clear reversibility against changes in salt concentration. At the ambient temperature of 22°C, enzyme systems working under the optimal salt concentrations were very stable against time. Increase in temperature increased the activity but reduced its stability. Circular dichroism (CD), dynamic light scattering (DLS) and small angle neutron scattering (SANS) were deployed to determine the physical states of LipC in solution. As the salt concentration increased, DLS revealed substantial increase in aggregate sizes, but CD measurements revealed the maximal retention of the α-helical structure at the salt concentration matching the optimal activity. These observations were supported by SANS analysis that revealed the highest proportion of unimers and dimers around the optimal salt concentration, although the coexistent larger aggregates showed a trend of increasing size with salt concentration, consistent with the DLS data. Conclusions/Significance The solution α-helical structure and activity relation also matched the highest proportion of enzyme unimers and dimers. Given that all the solutions studied were structurally inhomogeneous, it is important for future work to understand how the LipC's solution aggregation affected its activity. PMID:19759821

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

Fuel optimization for low-thrust Earth-Moon transfer via indirect optimal control

NASA Astrophysics Data System (ADS)

Pérez-Palau, Daniel; Epenoy, Richard

2018-02-01

The problem of designing low-energy transfers between the Earth and the Moon has attracted recently a major interest from the scientific community. In this paper, an indirect optimal control approach is used to determine minimum-fuel low-thrust transfers between a low Earth orbit and a Lunar orbit in the Sun-Earth-Moon Bicircular Restricted Four-Body Problem. First, the optimal control problem is formulated and its necessary optimality conditions are derived from Pontryagin's Maximum Principle. Then, two different solution methods are proposed to overcome the numerical difficulties arising from the huge sensitivity of the problem's state and costate equations. The first one consists in the use of continuation techniques. The second one is based on a massive exploration of the set of unknown variables appearing in the optimality conditions. The dimension of the search space is reduced by considering adapted variables leading to a reduction of the computational time. The trajectories found are classified in several families according to their shape, transfer duration and fuel expenditure. Finally, an analysis based on the dynamical structure provided by the invariant manifolds of the two underlying Circular Restricted Three-Body Problems, Earth-Moon and Sun-Earth is presented leading to a physical interpretation of the different families of trajectories.

An Iterative Approach for the Optimization of Pavement Maintenance Management at the Network Level

PubMed Central

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach. PMID:24741352

An iterative approach for the optimization of pavement maintenance management at the network level.

PubMed

Torres-Machí, Cristina; Chamorro, Alondra; Videla, Carlos; Pellicer, Eugenio; Yepes, Víctor

2014-01-01

Pavement maintenance is one of the major issues of public agencies. Insufficient investment or inefficient maintenance strategies lead to high economic expenses in the long term. Under budgetary restrictions, the optimal allocation of resources becomes a crucial aspect. Two traditional approaches (sequential and holistic) and four classes of optimization methods (selection based on ranking, mathematical optimization, near optimization, and other methods) have been applied to solve this problem. They vary in the number of alternatives considered and how the selection process is performed. Therefore, a previous understanding of the problem is mandatory to identify the most suitable approach and method for a particular network. This study aims to assist highway agencies, researchers, and practitioners on when and how to apply available methods based on a comparative analysis of the current state of the practice. Holistic approach tackles the problem considering the overall network condition, while the sequential approach is easier to implement and understand, but may lead to solutions far from optimal. Scenarios defining the suitability of these approaches are defined. Finally, an iterative approach gathering the advantages of traditional approaches is proposed and applied in a case study. The proposed approach considers the overall network condition in a simpler and more intuitive manner than the holistic approach.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.

Nonlinear dynamics under varying temperature conditions of the resonating beams of a differential resonant accelerometer

NASA Astrophysics Data System (ADS)

Zhang, Jing; Wang, Yagang; Zega, Valentina; Su, Yan; Corigliano, Alberto

2018-07-01

In this work the nonlinear dynamic behaviour under varying temperature conditions of the resonating beams of a differential resonant accelerometer is studied from the theoretical, numerical and experimental points of view. A complete analytical model based on the Hamilton’s principle is proposed to describe the nonlinear behaviour of the resonators under varying temperature conditions and numerical solutions are presented in comparison with experimental data. This provides a novel perspective to examine the relationship between temperature and nonlinearity, which helps predicting the dynamic behaviour of resonant devices and can guide their optimal design.

Sequentially Integrated Optimization of the Conditions to Obtain a High-Protein and Low-Antinutritional Factors Protein Isolate from Edible Jatropha curcas Seed Cake.

PubMed

León-López, Liliana; Dávila-Ortiz, Gloria; Jiménez-Martínez, Cristian; Hernández-Sánchez, Humberto

2013-01-01

Jatropha curcas seed cake is a protein-rich byproduct of oil extraction which could be used to produce protein isolates. The purpose of this study was the optimization of the protein isolation process from the seed cake of an edible provenance of J. curcas by an alkaline extraction followed by isoelectric precipitation method via a sequentially integrated optimization approach. The influence of four different factors (solubilization pH, extraction temperature, NaCl addition, and precipitation pH) on the protein and antinutritional compounds content of the isolate was evaluated. The estimated optimal conditions were an extraction temperature of 20°C, a precipitation pH of 4, and an amount of NaCl in the extraction solution of 0.6 M for a predicted protein content of 93.3%. Under these conditions, it was possible to obtain experimentally a protein isolate with 93.21% of proteins, 316.5 mg 100 g(-1) of total phenolics, 2891.84 mg 100 g(-1) of phytates and 168 mg 100 g(-1) of saponins. The protein content of the this isolate was higher than the content reported by other authors.

Sequentially Integrated Optimization of the Conditions to Obtain a High-Protein and Low-Antinutritional Factors Protein Isolate from Edible Jatropha curcas Seed Cake

PubMed Central

León-López, Liliana; Dávila-Ortiz, Gloria; Jiménez-Martínez, Cristian; Hernández-Sánchez, Humberto

2013-01-01

Jatropha curcas seed cake is a protein-rich byproduct of oil extraction which could be used to produce protein isolates. The purpose of this study was the optimization of the protein isolation process from the seed cake of an edible provenance of J. curcas by an alkaline extraction followed by isoelectric precipitation method via a sequentially integrated optimization approach. The influence of four different factors (solubilization pH, extraction temperature, NaCl addition, and precipitation pH) on the protein and antinutritional compounds content of the isolate was evaluated. The estimated optimal conditions were an extraction temperature of 20°C, a precipitation pH of 4, and an amount of NaCl in the extraction solution of 0.6 M for a predicted protein content of 93.3%. Under these conditions, it was possible to obtain experimentally a protein isolate with 93.21% of proteins, 316.5 mg 100 g−1 of total phenolics, 2891.84 mg 100 g−1 of phytates and 168 mg 100 g−1 of saponins. The protein content of the this isolate was higher than the content reported by other authors. PMID:25937971

Analytical approach to cross-layer protocol optimization in wireless sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In the distributed operations of route discovery and maintenance, strong interaction occurs across mobile ad hoc network (MANET) protocol layers. Quality of service (QoS) requirements of multimedia service classes must be satisfied by the cross-layer protocol, along with minimization of the distributed power consumption at nodes and along routes to battery-limited energy constraints. In previous work by the author, cross-layer interactions in the MANET protocol are modeled in terms of a set of concatenated design parameters and associated resource levels by multivariate point processes (MVPPs). Determination of the "best" cross-layer design is carried out using the optimal control of martingale representations of the MVPPs. In contrast to the competitive interaction among nodes in a MANET for multimedia services using limited resources, the interaction among the nodes of a wireless sensor network (WSN) is distributed and collaborative, based on the processing of data from a variety of sensors at nodes to satisfy common mission objectives. Sensor data originates at the nodes at the periphery of the WSN, is successively transported to other nodes for aggregation based on information-theoretic measures of correlation and ultimately sent as information to one or more destination (decision) nodes. The "multimedia services" in the MANET model are replaced by multiple types of sensors, e.g., audio, seismic, imaging, thermal, etc., at the nodes; the QoS metrics associated with MANETs become those associated with the quality of fused information flow, i.e., throughput, delay, packet error rate, data correlation, etc. Significantly, the essential analytical approach to MANET cross-layer optimization, now based on the MVPPs for discrete random events occurring in the WSN, can be applied to develop the stochastic characteristics and optimality conditions for cross-layer designs of sensor network protocols. Functional dependencies of WSN performance metrics are described in terms of the concatenated protocol parameters. New source-to-destination routes are sought that optimize cross-layer interdependencies to achieve the "best available" performance in the WSN. The protocol design, modified from a known reactive protocol, adapts the achievable performance to the transient network conditions and resource levels. Control of network behavior is realized through the conditional rates of the MVPPs. Optimal cross-layer protocol parameters are determined by stochastic dynamic programming conditions derived from models of transient packetized sensor data flows. Moreover, the defining conditions for WSN configurations, grouping sensor nodes into clusters and establishing data aggregation at processing nodes within those clusters, lead to computationally tractable solutions to the stochastic differential equations that describe network dynamics. Closed-form solution characteristics provide an alternative to the "directed diffusion" methods for resource-efficient WSN protocols published previously by other researchers. Performance verification of the resulting cross-layer designs is found by embedding the optimality conditions for the protocols in actual WSN scenarios replicated in a wireless network simulation environment. Performance tradeoffs among protocol parameters remain for a sequel to the paper.

Electric Field Tuning Molecular Packing and Electrical Properties of Solution-Shearing Coated Organic Semiconducting Thin Films

DOE PAGES

Molina-Lopez, Francisco; Yan, Hongping; Gu, Xiaodan; ...

2017-01-17

Recent improvements in solution-coated organic semiconductors (OSCs) evidence their high potential for cost-efficient organic electronics and sensors. Molecular packing structure determines the charge transport property of molecular solids. However, it remains challenging to control the molecular packing structure for a given OSC. Here, the application of alternating electric fields is reported to fine-tune the crystal packing of OSC solution-shearing coated at ambient conditions. First, a theoretical model based on dielectrophoresis is developed to guide the selection of the optimal conditions (frequency and amplitude) of the electric field applied through the solution-shearing blade during coating of OSC thin films. Next, electricmore » field-induced polymorphism is demonstrated for OSCs with both herringbone and 2D brick-wall packing motifs in 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene and 6,13-bis(triisopropylsilylethynyl) pentacene, respectively. Favorable molecular packing can be accessible in some cases, resulting in higher charge carrier mobilities. In conclusion, this work provides a new approach to tune the properties of solution-coated OSCs in functional devices for high-performance printed electronics.« less

Viscous Corrections of the Time Incremental Minimization Scheme and Visco-Energetic Solutions to Rate-Independent Evolution Problems

NASA Astrophysics Data System (ADS)

Minotti, Luca; Savaré, Giuseppe

2018-02-01

We propose the new notion of Visco-Energetic solutions to rate-independent systems {(X, E,} d) driven by a time dependent energy E and a dissipation quasi-distance d in a general metric-topological space X. As for the classic Energetic approach, solutions can be obtained by solving a modified time Incremental Minimization Scheme, where at each step the dissipation quasi-distance d is incremented by a viscous correction {δ} (for example proportional to the square of the distance d), which penalizes far distance jumps by inducing a localized version of the stability condition. We prove a general convergence result and a typical characterization by Stability and Energy Balance in a setting comparable to the standard energetic one, thus capable of covering a wide range of applications. The new refined Energy Balance condition compensates for the localized stability and provides a careful description of the jump behavior: at every jump the solution follows an optimal transition, which resembles in a suitable variational sense the discrete scheme that has been implemented for the whole construction.

Acute toxicity assessment of explosive-contaminated soil extracting solution by luminescent bacteria assays.

PubMed

Xu, Wenjie; Jiang, Zhenming; Zhao, Quanlin; Zhang, Zhenzhong; Su, Hongping; Gao, Xuewen; Ye, Zhengfang

2016-11-01

Explosive-contaminated soil is harmful to people's health and the local ecosystem. The acute toxicity of its extracting solution was tested by bacterial luminescence assay using three kinds of luminescent bacteria to characterize the toxicity of the soil. An orthogonal test L 16 (4 5 ) was designed to optimize the soil extracting conditions. The optimum extracting conditions were obtained when the ultrasonic extraction time, ultrasonic extraction temperature, and the extraction repeat times were 6 h, 40 °C, and three, respectively. Fourier transform infrared spectroscopy (FTIR) results showed that the main components of the contaminated soil's extracting solution were 2,4-dinitrotoluene-3-sulfonate (2,4-DNT-3-SO 3 - ); 2,4-dinitrotoluene-5-sulfonate (2,4-DNT-5-SO 3 - ); and 2,6-dinitrotoluene (2,6-DNT). Compared with Photobacterium phosphoreum and Vibrio fischeri, Vibrio qinghaiensis sp. Nov. is more suitable for assessing the soil extracting solution's acute toxicity. Soil washing can remove most of the contaminants toxic to luminescent bacterium Vibrio qinghaiensis sp. Nov., suggesting that it may be a potential effective remediation method for explosive-contaminated soil.

Autonomous optimal trajectory design employing convex optimization for powered descent on an asteroid

NASA Astrophysics Data System (ADS)

Pinson, Robin Marie

Mission proposals that land spacecraft on asteroids are becoming increasingly popular. However, in order to have a successful mission the spacecraft must reliably and softly land at the intended landing site with pinpoint precision. The problem under investigation is how to design a propellant (fuel) optimal powered descent trajectory that can be quickly computed onboard the spacecraft, without interaction from ground control. The goal is to autonomously design the optimal powered descent trajectory onboard the spacecraft immediately prior to the descent burn for use during the burn. Compared to a planetary powered landing problem, the challenges that arise from designing an asteroid powered descent trajectory include complicated nonlinear gravity fields, small rotating bodies, and low thrust vehicles. The nonlinear gravity fields cannot be represented by a constant gravity model nor a Newtonian model. The trajectory design algorithm needs to be robust and efficient to guarantee a designed trajectory and complete the calculations in a reasonable time frame. This research investigates the following questions: Can convex optimization be used to design the minimum propellant powered descent trajectory for a soft landing on an asteroid? Is this method robust and reliable to allow autonomy onboard the spacecraft without interaction from ground control? This research designed a convex optimization based method that rapidly generates the propellant optimal asteroid powered descent trajectory. The solution to the convex optimization problem is the thrust magnitude and direction, which designs and determines the trajectory. The propellant optimal problem was formulated as a second order cone program, a subset of convex optimization, through relaxation techniques by including a slack variable, change of variables, and incorporation of the successive solution method. Convex optimization solvers, especially second order cone programs, are robust, reliable, and are guaranteed to find the global minimum provided one exists. In addition, an outer optimization loop using Brent's method determines the optimal flight time corresponding to the minimum propellant usage over all flight times. Inclusion of additional trajectory constraints, solely vertical motion near the landing site and glide slope, were evaluated. Through a theoretical proof involving the Minimum Principle from Optimal Control Theory and the Karush-Kuhn-Tucker conditions it was shown that the relaxed problem is identical to the original problem at the minimum point. Therefore, the optimal solution of the relaxed problem is an optimal solution of the original problem, referred to as lossless convexification. A key finding is that this holds for all levels of gravity model fidelity. The designed thrust magnitude profiles were the bang-bang predicted by Optimal Control Theory. The first high fidelity gravity model employed was the 2x2 spherical harmonics model assuming a perfect triaxial ellipsoid and placement of the coordinate frame at the asteroid's center of mass and aligned with the semi-major axes. The spherical harmonics model is not valid inside the Brillouin sphere and this becomes relevant for irregularly shaped asteroids. Then, a higher fidelity model was implemented combining the 4x4 spherical harmonics gravity model with the interior spherical Bessel gravity model. All gravitational terms in the equations of motion are evaluated with the position vector from the previous iteration, creating the successive solution method. Methodology success was shown by applying the algorithm to three triaxial ellipsoidal asteroids with four different rotation speeds using the 2x2 gravity model. Finally, the algorithm was tested using the irregularly shaped asteroid, Castalia.

Topology optimization analysis based on the direct coupling of the boundary element method and the level set method

NASA Astrophysics Data System (ADS)

Vitório, Paulo Cezar; Leonel, Edson Denner

2017-12-01

The structural design must ensure suitable working conditions by attending for safe and economic criteria. However, the optimal solution is not easily available, because these conditions depend on the bodies' dimensions, materials strength and structural system configuration. In this regard, topology optimization aims for achieving the optimal structural geometry, i.e. the shape that leads to the minimum requirement of material, respecting constraints related to the stress state at each material point. The present study applies an evolutionary approach for determining the optimal geometry of 2D structures using the coupling of the boundary element method (BEM) and the level set method (LSM). The proposed algorithm consists of mechanical modelling, topology optimization approach and structural reconstruction. The mechanical model is composed of singular and hyper-singular BEM algebraic equations. The topology optimization is performed through the LSM. Internal and external geometries are evolved by the LS function evaluated at its zero level. The reconstruction process concerns the remeshing. Because the structural boundary moves at each iteration, the body's geometry change and, consequently, a new mesh has to be defined. The proposed algorithm, which is based on the direct coupling of such approaches, introduces internal cavities automatically during the optimization process, according to the intensity of Von Mises stress. The developed optimization model was applied in two benchmarks available in the literature. Good agreement was observed among the results, which demonstrates its efficiency and accuracy.

Optimization of Ultrasound-Assisted Extraction, HPLC and UHPLC-ESI-Q-TOF-MS/MS Analysis of Main Macamides and Macaenes from Maca (Cultivars of Lepidium meyenii Walp).

PubMed

Chen, Shu-Xiao; Li, Ke-Ke; Pubu, Duoji; Jiang, Si-Ping; Chen, Bin; Chen, Li-Rong; Yang, Zhen; Ma, Chao; Gong, Xiao-Jie

2017-12-10

Ultrasound-assisted extraction (UAE), using petroleum ether as the solvent, was systematically applied to extract main macamides and macaenes from Maca hypocotyls. Extraction yield was related with four variables, including ratio of solution to solid, extraction temperature, extraction time, and extraction power. On the basis of response surface methodology (RSM), the optimal conditions were determined to be the ratio of solution to solid as 10:1 (mL/g), the extraction temperature of 40 °C, the extraction time of 30 min, and the extraction power of 200 W. Based on the optimal extraction method of UAE, the total contents of ten main macamides and two main macaenes of Maca cultivated in twenty different areas of Tibet were analyzed by HPLC and UHPLC-ESI-Q-TOF-MS/MS. This study indicated that UAE was able to effectively extract macamides alkaloids from Maca hypocotyls. Quantitative analysis showed that geographical origins, not ecotypes, played a more important role on the accumulation of active macamides in Maca.

Application of modern control theory to the design of optimum aircraft controllers

NASA Technical Reports Server (NTRS)

Power, L. J.

1973-01-01

The synthesis procedure presented is based on the solution of the output regulator problem of linear optimal control theory for time-invariant systems. By this technique, solution of the matrix Riccati equation leads to a constant linear feedback control law for an output regulator which will maintain a plant in a particular equilibrium condition in the presence of impulse disturbances. Two simple algorithms are presented that can be used in an automatic synthesis procedure for the design of maneuverable output regulators requiring only selected state variables for feedback. The first algorithm is for the construction of optimal feedforward control laws that can be superimposed upon a Kalman output regulator and that will drive the output of a plant to a desired constant value on command. The second algorithm is for the construction of optimal Luenberger observers that can be used to obtain feedback control laws for the output regulator requiring measurement of only part of the state vector. This algorithm constructs observers which have minimum response time under the constraint that the magnitude of the gains in the observer filter be less than some arbitrary limit.

Optimization of a Solution-Processed SiO2 Gate Insulator by Plasma Treatment for Zinc Oxide Thin Film Transistors.

PubMed

Jeong, Yesul; Pearson, Christopher; Kim, Hyun-Gwan; Park, Man-Young; Kim, Hongdoo; Do, Lee-Mi; Petty, Michael C

2016-01-27

We report on the optimization of the plasma treatment conditions for a solution-processed silicon dioxide gate insulator for application in zinc oxide thin film transistors (TFTs). The SiO2 layer was formed by spin coating a perhydropolysilazane (PHPS) precursor. This thin film was subsequently thermally annealed, followed by exposure to an oxygen plasma, to form an insulating (leakage current density of ∼10(-7) A/cm(2)) SiO2 layer. Optimized ZnO TFTs (40 W plasma treatment of the gate insulator for 10 s) possessed a carrier mobility of 3.2 cm(2)/(V s), an on/off ratio of ∼10(7), a threshold voltage of -1.3 V, and a subthreshold swing of 0.2 V/decade. In addition, long-term exposure (150 min) of the pre-annealed PHPS to the oxygen plasma enabled the maximum processing temperature to be reduced from 180 to 150 °C. The resulting ZnO TFT exhibited a carrier mobility of 1.3 cm(2)/(V s) and on/off ratio of ∼10(7).

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.

[Conversion of 17 alpha-methyltestosterone to methandrostenolone by the bacterium Pimelobacter simplex VKPM Ac-1632 with the presence of cyclodextrins].

PubMed

Druzhinina, A V; Andriushina, V A; Stytsenko, T S; Voĭshvillo, N E

2008-01-01

Conditions of conversion of 17 alpha-methyltestosterone to methandrostenolone with the presence of modified beta-cyclodextrins (methylcyclodextrin, hydroxypropylcyclodextrin, and hydroxyethylcyclodextrin) in the steroid:cyclodextrin ratio 1:1 were studied. The experimental solutions of modified beta-cyclodextrins were prepared in deionized water with 5-7% methanol. Under the conditions found to be optimal, 1,2-dehydrogenation of 17 alpha-methyltestosterone was carried out with 2-4 g/l Pimelobacter simplex VKPM Ac-1632 biomass. At the substrate concentration 5-20 g/l, the reaction occurred for 1-15 h without any by-products. The maximum rate of methandrostenolone accumulation was observed with hydroxypropylcyclodextrin. The methylcyclodextrin solution can be reused for complete 17 alpha-methyltestosterone conversion at the concentration 5 g/l.

Air traffic simulation in chemistry-climate model EMAC 2.41: AirTraf 1.0

NASA Astrophysics Data System (ADS)

Yamashita, Hiroshi; Grewe, Volker; Jöckel, Patrick; Linke, Florian; Schaefer, Martin; Sasaki, Daisuke

2016-09-01

Mobility is becoming more and more important to society and hence air transportation is expected to grow further over the next decades. Reducing anthropogenic climate impact from aviation emissions and building a climate-friendly air transportation system are required for a sustainable development of commercial aviation. A climate optimized routing, which avoids climate-sensitive regions by re-routing horizontally and vertically, is an important measure for climate impact reduction. The idea includes a number of different routing strategies (routing options) and shows a great potential for the reduction. To evaluate this, the impact of not only CO2 but also non-CO2 emissions must be considered. CO2 is a long-lived gas, while non-CO2 emissions are short-lived and are inhomogeneously distributed. This study introduces AirTraf (version 1.0) that performs global air traffic simulations, including effects of local weather conditions on the emissions. AirTraf was developed as a new submodel of the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model. Air traffic information comprises Eurocontrol's Base of Aircraft Data (BADA Revision 3.9) and International Civil Aviation Organization (ICAO) engine performance data. Fuel use and emissions are calculated by the total energy model based on the BADA methodology and Deutsches Zentrum für Luft- und Raumfahrt (DLR) fuel flow method. The flight trajectory optimization is performed by a genetic algorithm (GA) with respect to a selected routing option. In the model development phase, benchmark tests were performed for the great circle and flight time routing options. The first test showed that the great circle calculations were accurate to -0.004 %, compared to those calculated by the Movable Type script. The second test showed that the optimal solution found by the algorithm sufficiently converged to the theoretical true-optimal solution. The difference in flight time between the two solutions is less than 0.01 %. The dependence of the optimal solutions on the initial set of solutions (called population) was analyzed and the influence was small (around 0.01 %). The trade-off between the accuracy of GA optimizations and computational costs is clarified and the appropriate population and generation (one iteration of GA) sizing is discussed. The results showed that a large reduction in the number of function evaluations of around 90 % can be achieved with only a small decrease in the accuracy of less than 0.1 %. Finally, AirTraf simulations are demonstrated with the great circle and the flight time routing options for a typical winter day. The 103 trans-Atlantic flight plans were used, assuming an Airbus A330-301 aircraft. The results confirmed that AirTraf simulates the air traffic properly for the two routing options. In addition, the GA successfully found the time-optimal flight trajectories for the 103 airport pairs, taking local weather conditions into account. The consistency check for the AirTraf simulations confirmed that calculated flight time, fuel consumption, NOx emission index and aircraft weights show good agreement with reference data.

Analytical Models of Cross-Layer Protocol Optimization in Real-Time Wireless Sensor Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

The real-time interactions among the nodes of a wireless sensor network (WSN) to cooperatively process data from multiple sensors are modeled. Quality-of-service (QoS) metrics are associated with the quality of fused information: throughput, delay, packet error rate, etc. Multivariate point process (MVPP) models of discrete random events in WSNs establish stochastic characteristics of optimal cross-layer protocols. Discrete-event, cross-layer interactions in mobile ad hoc network (MANET) protocols have been modeled using a set of concatenated design parameters and associated resource levels by the MVPPs. Characterization of the "best" cross-layer designs for a MANET is formulated by applying the general theory of martingale representations to controlled MVPPs. Performance is described in terms of concatenated protocol parameters and controlled through conditional rates of the MVPPs. Modeling limitations to determination of closed-form solutions versus explicit iterative solutions for ad hoc WSN controls are examined.

Minimization of Roll Firings for Optimal Propellant Maneuvers

NASA Astrophysics Data System (ADS)

Leach, Parker C.

Attitude control of the International Space Station (ISS) is critical for operations, impacting power, communications, and thermal systems. The station uses gyroscopes and thrusters for attitude control, and reorientations are normally assisted by thrusters on docked vehicles. When the docked vehicles are unavailable, the reduction in control authority in the roll axis results in frequent jet firings and massive fuel consumption. To improve this situation, new guidance and control schemes are desired that provide control with fewer roll firings. Optimal control software was utilized to solve for potential candidates that satisfied desired conditions with the goal of minimizing total propellant. An ISS simulation too was then used to test these solutions for feasibility. After several problem reformulations, multiple candidate solutions minimizing or completely eliminating roll firings were found. Flight implementation would not only save massive amounts of fuel and thus money, but also reduce ISS wear and tear, thereby extending its lifetime.

Insights Into the Solution Crystallization of Oriented Alq3 and Znq2 Microprisms and Nanorods.

PubMed

Boulet, Joel; Mohammadpour, Arash; Shankar, Karthik

2015-09-01

Optimized solution-based methods to grow high quality micro- and nanocrystals of organic semi-conductors with defined size, shape and orientation are important to a variety of optoelectronic applications. In this context, we report the growth of single crystal micro- and nanostructures of the organic semiconductors Tris(8-hydroxyquinoline)aluminum (Alq3) and bis(8-hydroxyquinoline)zinc (Znq2) terminating in flat crystal planes using a combination of evaporative and antisolvent crystallization. By controlling substrate-specific nucleation and optimizing the conditions of growth, we generate vertically-oriented hexagonal prism arrays of Alq3, and vertical half-disks and sharp-edged rectangular prisms of Znq2. The effect of process variables such as ambient vapour pressure, choice of anti-solvent and temperature on the morphology and crystal habit of the nanostructures were studied and the results of varying them catalogued to gain a better understanding of the mechanism of growth.

SLFP: a stochastic linear fractional programming approach for sustainable waste management.

PubMed

Zhu, H; Huang, G H

2011-12-01

A stochastic linear fractional programming (SLFP) approach is developed for supporting sustainable municipal solid waste management under uncertainty. The SLFP method can solve ratio optimization problems associated with random information, where chance-constrained programming is integrated into a linear fractional programming framework. It has advantages in: (1) comparing objectives of two aspects, (2) reflecting system efficiency, (3) dealing with uncertainty expressed as probability distributions, and (4) providing optimal-ratio solutions under different system-reliability conditions. The method is applied to a case study of waste flow allocation within a municipal solid waste (MSW) management system. The obtained solutions are useful for identifying sustainable MSW management schemes with maximized system efficiency under various constraint-violation risks. The results indicate that SLFP can support in-depth analysis of the interrelationships among system efficiency, system cost and system-failure risk. Copyright © 2011 Elsevier Ltd. All rights reserved.

Variational Methods in Design Optimization and Sensitivity Analysis for Two-Dimensional Euler Equations

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Tiwari, S. N.; Smith, R. E.

1997-01-01

Variational methods (VM) sensitivity analysis employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

To Demonstrate an Integrated Solution for Plasma-Material Interfaces Compatible with an Optimized Core Plasma

NASA Astrophysics Data System (ADS)

Goldston, Robert; Brooks, Jeffrey; Hubbard, Amanda; Leonard, Anthony; Lipschultz, Bruce; Maingi, Rajesh; Ulrickson, Michael; Whyte, Dennis

2009-11-01

The plasma facing components in a Demo reactor will face much more extreme boundary plasma conditions and operating requirements than any present or planned experiment. These include 1) Power density a factor of four or more greater than in ITER, 2) Continuous operation resulting in annual energy and particle throughput 100-200 times larger than ITER, 3) Elevated surface operating temperature for efficient electricity production, 4) Tritium fuel cycle control for safety and breeding requirements, and 5) Steady state plasma confinement and control. Consistent with ReNeW Thrust 12, design options are being explored for a new moderate-scale facility to assess core-edge interaction issues and solutions. Key desired features include high power density, sufficient pulse length and duty cycle, elevated wall temperature, steady-state control of an optimized core plasma, and flexibility in changing boundary components as well as access for comprehensive measurements.

Optimization of ultrasound extraction of phenolic compounds from coconut (Cocos nucifera) shell powder by response surface methodology.

PubMed

Rodrigues, Sueli; Pinto, Gustavo A S; Fernandes, Fabiano A N

2008-01-01

Coconut is a tropical fruit largely consumed in many countries. In some areas of the Brazilian coast, coconut shell represents more than 60% of the domestic waste volume. The coconut shell is composed mainly of lignin and cellulose, having a chemical composition very similar to wood and suitable for phenolic extraction. In this work, the use of ultrasound to extract phenolic compounds from coconut shell was evaluated. The effect of temperature, solution to solid ratio, pH and extraction time were evaluated through a 2(4) experimental planning. The extraction process was also optimized using surface response methodology. At the optimum operating condition (30 degrees C, solution to solid ratio of 50, 15 min of extraction and pH 6.5) the process yielded 22.44 mg of phenolic compounds per gram of coconut shell.

Optimizing the recovery of copper from electroplating rinse bath solution by hollow fiber membrane.

PubMed

Oskay, Kürşad Oğuz; Kul, Mehmet

2015-01-01

This study aimed to recover and remove copper from industrial model wastewater solution by non-dispersive solvent extraction (NDSX). Two mathematical models were developed to simulate the performance of an integrated extraction-stripping process, based on the use of hollow fiber contactors using the response surface method. The models allow one to predict the time dependent efficiencies of the two phases involved in individual extraction or stripping processes. The optimal recovery efficiency parameters were determined as 227 g/L of H2SO4 concentration, 1.22 feed/strip ratio, 450 mL/min flow rate (115.9 cm/min. flow velocity) and 15 volume % LIX 84-I concentration in 270 min by central composite design (CCD). At these optimum conditions, the experimental value of recovery efficiency was 95.88%, which was in close agreement with the 97.75% efficiency value predicted by the model. At the end of the process, almost all the copper in the model wastewater solution was removed and recovered as CuSO4.5H2O salt, which can be reused in the copper electroplating industry.

Sensitive determination of cadmium using solidified floating organic drop microextraction-slotted quartz tube-flame atomic absorption spectroscopy.

PubMed

Akkaya, Erhan; Chormey, Dotse Selali; Bakırdere, Sezgin

2017-09-20

In this study, solidified floating organic drop microextraction (SFODME) by 1-undecanol was combined with slotted quartz tube flame atomic absorption spectrometry (SQT-FAAS) for the determination of cadmium at trace levels. Formation of a complex with 4,4'-dimethyl-2,2'-bipyridine facilitated the extraction of cadmium from aqueous solutions. Several chemical variables were optimized in order to obtain high extraction outputs. Parameters such as concentration of the ligand, pH, and amount of buffer solution were optimized to enhance the formation of cadmium complex. The SFODME method was assisted by dispersion of extractor solvent into aqueous solutions using 2-propanol. Under the optimum extraction and instrumental conditions, the limit of detection and limit of quantitation values obtained for cadmium using the combined methods (SFODME-SQT-FAAS) were found to be 0.4 and 1.3 μg L -1 , respectively. Matrix effects on the method were also examined for tap water and wastewater, and spiked recovery results were found to be very satisfactory. Graphical Abstract SFODME-SQT-FAAS system for sensitive determination of cadmium.

Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method

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

Carlberg, Kevin; Forstall, Virginia; Tuminaro, Ray

This paper presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation strategies used in recycling such as deflation, we propose a truncation method inspired by goal-oriented proper orthogonal decomposition (POD) from model reduction. This idea is based on the observation that model reduction aims to compute a low-dimensional subspace that contains an accurate solution; as such, we expect the proposed method to generate a low-dimensional subspace that is well suited for computing solutions that can satisfy inexact tolerances. In particular, we proposemore » specific goal-oriented POD `ingredients' that align the optimality properties of POD with the objective of Krylov-subspace recycling. To compute solutions in the resulting 'augmented' POD subspace, we propose a hybrid direct/iterative three-stage method that leverages 1) the optimal ordering of POD basis vectors, and 2) well-conditioned reduced matrices. Numerical experiments performed on solid-mechanics problems highlight the benefits of the proposed method over existing approaches for Krylov-subspace recycling.« less

Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method

DOE PAGES

Carlberg, Kevin; Forstall, Virginia; Tuminaro, Ray

2016-01-01

This paper presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation strategies used in recycling such as deflation, we propose a truncation method inspired by goal-oriented proper orthogonal decomposition (POD) from model reduction. This idea is based on the observation that model reduction aims to compute a low-dimensional subspace that contains an accurate solution; as such, we expect the proposed method to generate a low-dimensional subspace that is well suited for computing solutions that can satisfy inexact tolerances. In particular, we proposemore » specific goal-oriented POD `ingredients' that align the optimality properties of POD with the objective of Krylov-subspace recycling. To compute solutions in the resulting 'augmented' POD subspace, we propose a hybrid direct/iterative three-stage method that leverages 1) the optimal ordering of POD basis vectors, and 2) well-conditioned reduced matrices. Numerical experiments performed on solid-mechanics problems highlight the benefits of the proposed method over existing approaches for Krylov-subspace recycling.« less

GLOBAL SOLUTIONS TO FOLDED CONCAVE PENALIZED NONCONVEX LEARNING

PubMed Central

Liu, Hongcheng; Yao, Tao; Li, Runze

2015-01-01

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, there lack optimization techniques that guarantee global optimality in a general setting. In this paper, we show that a class of nonconvex learning problems are equivalent to general quadratic programs. This equivalence facilitates us in developing mixed integer linear programming reformulations, which admit finite algorithms that find a provably global optimal solution. We refer to this reformulation-based technique as the mixed integer programming-based global optimization (MIPGO). To our knowledge, this is the first global optimization scheme with a theoretical guarantee for folded concave penalized nonconvex learning with the SCAD penalty (Fan and Li, 2001) and the MCP penalty (Zhang, 2010). Numerical results indicate a significant outperformance of MIPGO over the state-of-the-art solution scheme, local linear approximation, and other alternative solution techniques in literature in terms of solution quality. PMID:27141126

Stochastic search, optimization and regression with energy applications

NASA Astrophysics Data System (ADS)

Hannah, Lauren A.

Designing clean energy systems will be an important task over the next few decades. One of the major roadblocks is a lack of mathematical tools to economically evaluate those energy systems. However, solutions to these mathematical problems are also of interest to the operations research and statistical communities in general. This thesis studies three problems that are of interest to the energy community itself or provide support for solution methods: R&D portfolio optimization, nonparametric regression and stochastic search with an observable state variable. First, we consider the one stage R&D portfolio optimization problem to avoid the sequential decision process associated with the multi-stage. The one stage problem is still difficult because of a non-convex, combinatorial decision space and a non-convex objective function. We propose a heuristic solution method that uses marginal project values---which depend on the selected portfolio---to create a linear objective function. In conjunction with the 0-1 decision space, this new problem can be solved as a knapsack linear program. This method scales well to large decision spaces. We also propose an alternate, provably convergent algorithm that does not exploit problem structure. These methods are compared on a solid oxide fuel cell R&D portfolio problem. Next, we propose Dirichlet Process mixtures of Generalized Linear Models (DPGLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We prove conditions for the asymptotic unbiasedness of the DP-GLM regression mean function estimate. We also give examples for when those conditions hold, including models for compactly supported continuous distributions and a model with continuous covariates and categorical response. We empirically analyze the properties of the DP-GLM and why it provides better results than existing Dirichlet process mixture regression models. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression like CART, Bayesian trees and Gaussian processes. Compared to existing techniques, the DP-GLM provides a single model (and corresponding inference algorithms) that performs well in many regression settings. Finally, we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no general purpose algorithm to solve this class of problems. We use nonparametric density estimation to take observations from the joint state-outcome distribution and use them to infer the optimal decision for a given query state. We propose two solution methods that depend on the problem characteristics: function-based and gradient-based optimization. We examine two weighting schemes, kernel-based weights and Dirichlet process-based weights, for use with the solution methods. The weights and solution methods are tested on a synthetic multi-product newsvendor problem and the hour-ahead wind commitment problem. Our results show that in some cases Dirichlet process weights offer substantial benefits over kernel based weights and more generally that nonparametric estimation methods provide good solutions to otherwise intractable problems.

Fast Optimization for Aircraft Descent and Approach Trajectory

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John

2017-01-01

We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.

Fluoride release from fluoride varnishes under acidic conditions.

PubMed

Lippert, F

2014-01-01

The aim was to investigate the in vitro fluoride release from fluoride varnishes under acidic conditions. Poly(methyl methacrylate) blocks (Perspex, n=3 per group) were painted with 80 ± 5 mg fluoride varnish (n=10) and placed into artificial saliva for 30 min. Then, blocks were placed into either 1% citric acid (pH 2.27) or 0.3% citric acid (pH 3.75) solutions (n=3 per solution and varnish) for 30 min with the solutions being replaced every 5 min. Saliva and acid solutions were analyzed for fluoride content. Data were analyzed using three-way ANOVA (varnish, solution, time). The three-way interaction was significant (p>0.0001). Fluoride release and release patterns varied considerably between varnishes. Fluoride release in saliva varied by a factor of more than 10 between varnishes. Some varnishes (CavityShield, Nupro, ProFluorid, Vanish) showed higher fluoride release in saliva than during the first 5 min of acid exposure, whereas other varnishes (Acclean, Enamel-Pro, MI Varnish, Vella) showed the opposite behavior. There was little difference between acidic solutions. Fluoride release from fluoride varnishes varies considerably and also depends on the dissolution medium. Bearing in mind the limitations of laboratory research, the consumption of acidic drinks after fluoride varnish application should be avoided to optimize the benefit/risk ratio.

Model selection for integrated pest management with stochasticity.

PubMed

Akman, Olcay; Comar, Timothy D; Hrozencik, Daniel

2018-04-07

In Song and Xiang (2006), an integrated pest management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an integrated pest management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time-domain finite elements in optimal control with application to launch-vehicle guidance. PhD. Thesis

NASA Technical Reports Server (NTRS)

Bless, Robert R.

1991-01-01

A time-domain finite element method is developed for optimal control problems. The theory derived is general enough to handle a large class of problems including optimal control problems that are continuous in the states and controls, problems with discontinuities in the states and/or system equations, problems with control inequality constraints, problems with state inequality constraints, or problems involving any combination of the above. The theory is developed in such a way that no numerical quadrature is necessary regardless of the degree of nonlinearity in the equations. Also, the same shape functions may be employed for every problem because all strong boundary conditions are transformed into natural or weak boundary conditions. In addition, the resulting nonlinear algebraic equations are very sparse. Use of sparse matrix solvers allows for the rapid and accurate solution of very difficult optimization problems. The formulation is applied to launch-vehicle trajectory optimization problems, and results show that real-time optimal guidance is realizable with this method. Finally, a general problem solving environment is created for solving a large class of optimal control problems. The algorithm uses both FORTRAN and a symbolic computation program to solve problems with a minimum of user interaction. The use of symbolic computation eliminates the need for user-written subroutines which greatly reduces the setup time for solving problems.

Short-term Operation of Multi-purpose Reservoir using Model Predictive Control

NASA Astrophysics Data System (ADS)

Uysal, Gokcen; Schwanenberg, Dirk; Alvarado Montero, Rodolfo; Sensoy, Aynur; Arda Sorman, Ali

2017-04-01

Operation of water structures especially with conflicting water supply and flood mitigation objectives is under more stress attributed to growing water demand and changing hydro-climatic conditions. Model Predictive Control (MPC) based optimal control solutions has been successfully applied to different water resources applications. In this study, Feedback Control (FBC) and MPC get combined and an improved joint optimization-simulation operating scheme is proposed. Water supply and flood control objectives are fulfilled by incorporating the long term water supply objectives into a time-dependent variable guide curve policy whereas the extreme floods are attenuated by means of short-term optimization based on MPC. A final experiment is carried out to assess the lead time performance and reliability of forecasts in a hindcasting experiment with imperfect, perturbed forecasts. The framework is tested in Yuvacık Dam reservoir where the main water supply reservoir of Kocaeli City in the northwestern part of Turkey (the Marmara region) and it requires a challenging gate operation due to restricted downstream flow conditions.

Estimating 3D positions and velocities of projectiles from monocular views.

PubMed

Ribnick, Evan; Atev, Stefan; Papanikolopoulos, Nikolaos P

2009-05-01

In this paper, we consider the problem of localizing a projectile in 3D based on its apparent motion in a stationary monocular view. A thorough theoretical analysis is developed, from which we establish the minimum conditions for the existence of a unique solution. The theoretical results obtained have important implications for applications involving projectile motion. A robust, nonlinear optimization-based formulation is proposed, and the use of a local optimization method is justified by detailed examination of the local convexity structure of the cost function. The potential of this approach is validated by experimental results.

Formulation analysis and computation of an optimization-based local-to-nonlocal coupling method.

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

D'Elia, Marta; Bochev, Pavel Blagoveston

2017-01-01

In this paper, we present an optimization-based coupling method for local and nonlocal continuum models. Our approach couches the coupling of the models into a control problem where the states are the solutions of the nonlocal and local equations, the objective is to minimize their mismatch on the overlap of the local and nonlocal problem domains, and the virtual controls are the nonlocal volume constraint and the local boundary condition. We present the method in the context of Local-to-Nonlocal di usion coupling. Numerical examples illustrate the theoretical properties of the approach.

Application of Artificial Neural Networks to the Design of Turbomachinery Airfoils

NASA Technical Reports Server (NTRS)

Rai, Man Mohan; Madavan, Nateri

1997-01-01

Artificial neural networks are widely used in engineering applications, such as control, pattern recognition, plant modeling and condition monitoring to name just a few. In this seminar we will explore the possibility of applying neural networks to aerodynamic design, in particular, the design of turbomachinery airfoils. The principle idea behind this effort is to represent the design space using a neural network (within some parameter limits), and then to employ an optimization procedure to search this space for a solution that exhibits optimal performance characteristics. Results obtained for design problems in two spatial dimensions will be presented.

Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

PubMed

Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

2017-11-20

A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

Optimal Earth's reentry disposal of the Galileo constellation

NASA Astrophysics Data System (ADS)

Armellin, Roberto; San-Juan, Juan F.

2018-02-01

Nowadays there is international consensus that space activities must be managed to minimize debris generation and risk. The paper presents a method for the end-of-life (EoL) disposal of spacecraft in Medium Earth Orbit (MEO). The problem is formulated as a multiobjective optimisation one, which is solved with an evolutionary algorithm. An impulsive manoeuvre is optimised to reenter the spacecraft in Earth's atmosphere within 100 years. Pareto optimal solutions are obtained using the manoeuvre Δv and the time-to-reentry as objective functions to be minimised. To explore at the best the search space a semi-analytical orbit propagator, which can propagate an orbit for 100 years in few seconds, is adopted. An in-depth analysis of the results is carried out to understand the conditions leading to a fast reentry with minimum propellant. For this aim a new way of representing the disposal solutions is introduced. With a single 2D plot we are able to fully describe the time evolution of all the relevant orbital parameters as well as identify the conditions that enables the eccentricity build-up. The EoL disposal of the Galileo constellation is used as test case.

SPORT: An Algorithm for Divisible Load Scheduling with Result Collection on Heterogeneous Systems

NASA Astrophysics Data System (ADS)

Ghatpande, Abhay; Nakazato, Hidenori; Beaumont, Olivier; Watanabe, Hiroshi

Divisible Load Theory (DLT) is an established mathematical framework to study Divisible Load Scheduling (DLS). However, traditional DLT does not address the scheduling of results back to source (i. e., result collection), nor does it comprehensively deal with system heterogeneity. In this paper, the DLSRCHETS (DLS with Result Collection on HET-erogeneous Systems) problem is addressed. The few papers to date that have dealt with DLSRCHETS, proposed simplistic LIFO (Last In, First Out) and FIFO (First In, First Out) type of schedules as solutions to DLSRCHETS. In this paper, a new polynomial time heuristic algorithm, SPORT (System Parameters based Optimized Result Transfer), is proposed as a solution to the DLSRCHETS problem. With the help of simulations, it is proved that the performance of SPORT is significantly better than existing algorithms. The other major contributions of this paper include, for the first time ever, (a) the derivation of the condition to identify the presence of idle time in a FIFO schedule for two processors, (b) the identification of the limiting condition for the optimality of FIFO and LIFO schedules for two processors, and (c) the introduction of the concept of equivalent processor in DLS for heterogeneous systems with result collection.

Multi-responses optimization of simultaneous biosorption of cationic dyes by live yeast Yarrowia lipolytica 70562 from binary solution: Application of first order derivative spectrophotometry.

PubMed

Dil, Ebrahim Alipanahpour; Ghaedi, Mehrorang; Ghezelbash, Gholam Reza; Asfaram, Arash

2017-05-01

Present study is based on application of live yeast Yarrowia lipolytica 70562 as new biosorbent was investigated for the simultaneous biosorption of Crystal Violet (CV) and Brilliant Green (BG) from wastewater. The effect of operating parameters such as initial dye concentrations (6-14mgL -1 ), solution pH (4.0-8.0) and contact time (4-20h) was investigated by response surface methodology (RSM) for modeling and optimization of biosorption process and accordingly the best operational conditions was set as: initial CV and BG concentration of 8.0, and 10mgL -1 , pH of 7.0 and contact time of 16h. Above specified conditions lead to achievement of maximum biosorption of 98.823% and 99.927% for CV and BG dyes, respectively. The experimental equilibrium data well explained according to Langmuir isotherm model with maximum biosorption capacity of 65.359 and 56.497mgg -1 for BG and CV, respectively. The second order and intraparticle diffusion models as cooperative mechanism has high efficiency and performance for interpretation of real data. Copyright © 2017. Published by Elsevier Inc.

Combination of micelle collapse and field-amplified sample stacking in capillary electrophoresis for determination of trimethoprim and sulfamethoxazole in animal-originated foodstuffs.

PubMed

Liu, Lihong; Wan, Qian; Xu, Xiaoying; Duan, Shunshan; Yang, Chunli

2017-03-15

An on-line preconcentration method combining micelle to solvent stacking (MSS) with field-amplified sample stacking (FASS) was employed for the analysis of trimethoprim (TMP) and sulfamethoxazole (SMZ) by capillary zone electrophoresis (CZE). The optimized experimental conditions were as followings: (1) sample matrix, 10.0mM SDS-5% (v/v) methanol; (2) trapping solution (TS), 35mM H 3 PO 4 -60% acetonitrile (CH 3 CN); (3) running buffer, 30mM Na 2 HPO 4 (pH=7.3); (4) sample solution volume, 168nL; TS volume, 168nL; and (5) 9kV voltage, 214nm UV detection. Under the optimized conditions, the limits of detection (LODs) for SMZ and TMP were 7.7 and 8.5ng/mL, and they were 301 and 329 times better compared to a typical injection, respectively. The contents of TMP and SMZ in animal foodstuffs such as dairy products, eggs and honey were analyzed, too. Recoveries of 80-104% were acquired with relative standard deviations of 0.5-5.4%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Protection of copper surface with phytic acid against corrosion in chloride solution.

PubMed

Peca, Dunja; Pihlar, Boris; Ingrid, Milošev

2014-01-01

Phytic acid (inositol hexaphosphate) was tested as a corrosion inhibitor for copper in 3% sodium chloride. Phytic acid is a natural compound derived from plants, it is not toxic and can be considered as a green inhibitor. Electrochemical methods of linear polarization and potentiodynamic polarization were used to study the electrochemical behaviour and evaluate the inhibition effectiveness. To obtain the optimal corrosion protection the following experimental conditions were investigated: effect of surface pre-treatment (abrasion and three procedures of surface roughening), pre-formation of the layer of phytic acid, time of immersion and concentration of phytic acid. To evaluate the surface pre-treatment procedures the surface roughness and contact angle were measured. Optimal conditions for formation of phytic layer were selected resulting in the inhibition effectiveness of nearly 80%. Morphology and composition of the layer were further studied by scanning electron microscopy, energy dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy. The layer of phytic acid with thickness in the nanometer range homogeneously covers the copper surface. The obtained results show that this natural compound can be used as a mildly effective corrosion inhibitor for copper in chloride solution.

[The effect of pemolin on the mitotic activity of Vicia faba L (author's transl)].

PubMed

Brabec, F; Röper, W

1976-02-01

The effect of diverse concentrations of 5-phenyl-2-imino-4-oxazolidone (PIO, pemolin, Tradon) on the mitotic activity in lateral roots of Vicia faba L. was studied by aerated and non-aerated hydrocultivation with and without mineral nutrition, respectively. With optimal conditions (aerated nutrient solution) weak PIO-concentrations, most significantly 10(-6) g/ml, effected a marked increase of the mitotic index. Contrarily, strong PIO-concentrations (10(-4) and 3 X 10(-4) g/ml = saturated solution) significantly decreased the mitotic index though simultaneously preserving the mitotic activity in long-term experiments, when on account of nutrient deficiency it had already collapsed in weak PIO-concentrations and the controls. The activating effect of weak PIO-concentrations compared with the controls is more significant in stress situations (nutrient deficiency, O2-deficiency) than under optimal conditions. Furthermore a slight acceleration of mid-mitotic phases (metaphase--anaphase) recognized by a marked decrease in percentage of these phases, can be stated with weak PIO-concentrations, again particularly so with 10(-6) g/ml. In total, dependent on concentration, pemolin presumably may either activate or suppress cell metabolism and particularly the mitotic cycle. The exact site of action of the substance is still unknown.

Optimal impulsive manoeuvres and aerodynamic braking

NASA Technical Reports Server (NTRS)

Jezewski, D. J.

1985-01-01

A method developed for obtaining solutions to the aerodynamic braking problem, using impulses in the exoatmospheric phases is discussed. The solution combines primer vector theory and the results of a suboptimal atmospheric guidance program. For a specified initial and final orbit, the solution determines: (1) the minimum impulsive cost using a maximum of four impulses, (2) the optimal atmospheric entry and exit-state vectors subject to equality and inequality constraints, and (3) the optimal coast times. Numerical solutions which illustrate the characteristics of the solution are presented.

Hybridization of decomposition and local search for multiobjective optimization.

PubMed

Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

2014-10-01

Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems.

Extremal Optimization: Methods Derived from Co-Evolution

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

Boettcher, S.; Percus, A.G.

1999-07-13

We describe a general-purpose method for finding high-quality solutions to hard optimization problems, inspired by self-organized critical models of co-evolution such as the Bak-Sneppen model. The method, called Extremal Optimization, successively eliminates extremely undesirable components of sub-optimal solutions, rather than ''breeding'' better components. In contrast to Genetic Algorithms which operate on an entire ''gene-pool'' of possible solutions, Extremal Optimization improves on a single candidate solution by treating each of its components as species co-evolving according to Darwinian principles. Unlike Simulated Annealing, its non-equilibrium approach effects an algorithm requiring few parameters to tune. With only one adjustable parameter, its performance provesmore » competitive with, and often superior to, more elaborate stochastic optimization procedures. We demonstrate it here on two classic hard optimization problems: graph partitioning and the traveling salesman problem.« less

The terminal area automated path generation problem

NASA Technical Reports Server (NTRS)

Hsin, C.-C.

1977-01-01

The automated terminal area path generation problem in the advanced Air Traffic Control System (ATC), has been studied. Definitions, input, output and the interrelationships with other ATC functions have been discussed. Alternatives in modeling the problem have been identified. Problem formulations and solution techniques are presented. In particular, the solution of a minimum effort path stretching problem (path generation on a given schedule) has been carried out using the Newton-Raphson trajectory optimization method. Discussions are presented on the effect of different delivery time, aircraft entry position, initial guess on the boundary conditions, etc. Recommendations are made on real-world implementations.

Enhancing Polyhedral Relaxations for Global Optimization

ERIC Educational Resources Information Center

Bao, Xiaowei

2009-01-01

During the last decade, global optimization has attracted a lot of attention due to the increased practical need for obtaining global solutions and the success in solving many global optimization problems that were previously considered intractable. In general, the central question of global optimization is to find an optimal solution to a given…

Method of determining the optimal dilution ratio for fluorescence fingerprint of food constituents.

PubMed

Trivittayasil, Vipavee; Tsuta, Mizuki; Kokawa, Mito; Yoshimura, Masatoshi; Sugiyama, Junichi; Fujita, Kaori; Shibata, Mario

2015-01-01

Quantitative determination by fluorescence spectroscopy is possible because of the linear relationship between the intensity of emitted fluorescence and the fluorophore concentration. However, concentration quenching may cause the relationship to become nonlinear, and thus, the optimal dilution ratio has to be determined. In the case of fluorescence fingerprint (FF) measurement, fluorescence is measured under multiple wavelength conditions and a method of determining the optimal dilution ratio for multivariate data such as FFs has not been reported. In this study, the FFs of mixed solutions of tryptophan and epicatechin of different concentrations and composition ratios were measured. Principal component analysis was applied, and the resulting loading plots were found to contain useful information about each constituent. The optimal concentration ranges could be determined by identifying the linear region of the PC score plotted against total concentration.

An artificial neural network controller based on MPSO-BFGS hybrid optimization for spherical flying robot

NASA Astrophysics Data System (ADS)

Liu, Xiaolin; Li, Lanfei; Sun, Hanxu

2017-12-01

Spherical flying robot can perform various tasks in the complex and varied environment to reduce labor costs. However, it is difficult to guarantee the stability of the spherical flying robot in the case of strong coupling and time-varying disturbance. In this paper, an artificial neural network controller (ANNC) based on MPSO-BFGS hybrid optimization algorithm is proposed. The MPSO algorithm is used to optimize the initial weights of the controller to avoid the local optimal solution. The BFGS algorithm is introduced to improve the convergence ability of the network. We use Lyapunov method to analyze the stability of ANNC. The controller is simulated under the condition of nonlinear coupling disturbance. The experimental results show that the proposed controller can obtain the expected value in shoter time compared with the other considered methods.

Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

NASA Astrophysics Data System (ADS)

Rahmalia, Dinita

2017-08-01

Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Size exclusion chromatography for analyses of fibroin in silk: optimization of sampling and separation conditions

NASA Astrophysics Data System (ADS)

Pawcenis, Dominika; Koperska, Monika A.; Milczarek, Jakub M.; Łojewski, Tomasz; Łojewska, Joanna

2014-02-01

A direct goal of this paper was to improve the methods of sample preparation and separation for analyses of fibroin polypeptide with the use of size exclusion chromatography (SEC). The motivation for the study arises from our interest in natural polymers included in historic textile and paper artifacts, and is a logical response to the urgent need for developing rationale-based methods for materials conservation. The first step is to develop a reliable analytical tool which would give insight into fibroin structure and its changes caused by both natural and artificial ageing. To investigate the influence of preparation conditions, two sets of artificially aged samples were prepared (with and without NaCl in sample solution) and measured by the means of SEC with multi angle laser light scattering detector. It was shown that dialysis of fibroin dissolved in LiBr solution allows removal of the salt which destroys stacks chromatographic columns and prevents reproducible analyses. Salt rich (NaCl) water solutions of fibroin improved the quality of chromatograms.

Numerical analysis for electrokinetic soil processing enhanced by chemical conditioning of the electrode reservoirs.

PubMed

Park, Jin-Soo; Kim, Soon-Oh; Kim, Kyoung-Woong; Kim, Byung Ro; Moon, Seung-Hyeon

2003-04-04

A numerical analysis was undertaken for enhanced electrokinetic soil processing. To perform chemical conditioning of the electrode reservoirs, the electrokinetic soil process employed a membrane as a barrier between the electrode reservoirs and the contaminated soil. An alkaline solution was purged in the anode reservoir that was bounded by the membrane. A mathematical model was used for demonstration of pH change and phenol removal from a kaolinite soil bed, the prediction of pH variations in both electrode reservoirs, and the determination of an optimized injection time of the anode-purging solution. The time-dependent dispersion coefficient was employed in consideration of the averaging effect of the velocity profile on a one-dimensional transport. The estimation of pH and phenol profiles in the soil bed reasonably agreed with the experimental data. The simulation revealed that the removal efficiency of phenol from the kaolinite soil could be improved by maintaining pH of the anode solution.

[Determination of ru, rh and Pd in 30% trialkyl phosphine oxide (TRPO)-kerosene by inductively coupled plasma-atomic emission spectrum (ICP-AES)].

PubMed

Wang, Jian-Chen; Zhang, Lin

2013-07-01

The determination method of Ru, Rh and Pd in 30% TRPO-kerosene ICP-AES was studied by using aqueous calibration reference solution and choosing ethanol as diluent. The effects of the contents of 30% TRPO-kerosene and aqueous solution and the concentration of HNO3 in 30% TRPO-kerosene on the intensities of Ru, Rh and Pd were described. The optimized condition for preparing samples and calibration solutions was chosen as follows: The contents of 30% TRPO-kerosene and aqueous phase were 10% (V/V) and 5% (V/V) respectively and the concentration of HNO3 30% TRPO-kerosene was 0.20 mol x L(-1). The determination method of Au, Ru and Pd was set up according to the above condition. The detection limit, precision and recovery ratio of Ru, Rh and Pd are well. The method is not only used in determination of Au, Ru and Pd in 30% TRPO-kerosene, but also used in other organic phases.

Enforcing the Courant–Friedrichs–Lewy condition in explicitly conservative local time stepping schemes

DOE PAGES

Gnedin, Nickolay Y.; Semenov, Vadim A.; Kravtsov, Andrey V.

2018-01-30

In this study, an optimally efficient explicit numerical scheme for solving fluid dynamics equations, or any other parabolic or hyperbolic system of partial differential equations, should allow local regions to advance in time with their own, locally constrained time steps. However, such a scheme can result in violation of the Courant-Friedrichs-Lewy (CFL) condition, which is manifestly non-local. Although the violations can be considered to be "weak" in a certain sense and the corresponding numerical solution may be stable, such calculation does not guarantee the correct propagation speed for arbitrary waves. We use an experimental fluid dynamics code that allows cubicmore » "patches" of grid cells to step with independent, locally constrained time steps to demonstrate how the CFL condition can be enforced by imposing a condition on the time steps of neighboring patches. We perform several numerical tests that illustrate errors introduced in the numerical solutions by weak CFL condition violations and show how strict enforcement of the CFL condition eliminates these errors. In all our tests the strict enforcement of the CFL condition does not impose a significant performance penalty.« less

Optimal plant water use across temporal scales: bridging eco-hydrological theories and plant eco-physiological responses

NASA Astrophysics Data System (ADS)

Manzoni, S.; Vico, G.; Palmroth, S.; Katul, G. G.; Porporato, A. M.

2013-12-01

In terrestrial ecosystems, plant photosynthesis occurs at the expense of water losses through stomata, thus creating an inherent hydrologic constrain to carbon (C) gains and productivity. While such a constraint cannot be overcome, evolution has led to a number of adaptations that allow plants to thrive under highly variable and often limiting water availability. It may be hypothesized that these adaptations are optimal and allow maximum C gain for a given water availability. A corollary hypothesis is that these adaptations manifest themselves as coordination between the leaf photosynthetic machinery and the plant hydraulic system. This coordination leads to functional relations between the mean hydrologic state, plant hydraulic traits, and photosynthetic parameters that can be used as bridge across temporal scales. Here, optimality theories describing the behavior of stomata and plant morphological features in a fluctuating soil moisture environment are proposed. The overarching goal is to explain observed global patterns of plant water use and their ecological and biogeochemical consequences. The problem is initially framed as an optimal control problem of stomatal closure during drought of a given duration, where maximizing the total photosynthesis under limited and diminishing water availability is the objective function. Analytical solutions show that commonly used transpiration models (in which stomatal conductance is assumed to depend on soil moisture) are particular solutions emerging from the optimal control problem. Relations between stomatal conductance, vapor pressure deficit, and atmospheric CO2 are also obtained without any a priori assumptions under this framework. Second, the temporal scales of the model are expanded by explicitly considering the stochasticity of rainfall. In this context, the optimal control problem becomes a maximization problem for the mean photosynthetic rate. Results show that to achieve maximum C gains under these unpredictable rainfall conditions, plant hydraulic traits (xylem and stomatal response to water availability) and morphological features (leaf and sapwood areas) must be coordinated - thus providing an ecohydrological interpretation of observed coordination (or homeostasis) among hydraulic traits. Moreover, the combinations of hydraulic traits and responses to drought that are optimal are found to depend on both total rainfall and its distribution during the growing season. Both drier conditions and more intense rainfall events interspaced by longer dry periods favor plants with high resistance to cavitation and delayed stomatal closure as soils dry. In contrast, plants in mesic conditions benefit from cavitation prevention through earlier stomatal closure. The proposed ecohydrological optimality criteria can be used as analytical tools to interpret variability in plant water use and predict trends in plant productivity and species composition under future climates.

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

Multi-objective optimization of an industrial penicillin V bioreactor train using non-dominated sorting genetic algorithm.

PubMed

Lee, Fook Choon; Rangaiah, Gade Pandu; Ray, Ajay Kumar

2007-10-15

Bulk of the penicillin produced is used as raw material for semi-synthetic penicillin (such as amoxicillin and ampicillin) and semi-synthetic cephalosporins (such as cephalexin and cefadroxil). In the present paper, an industrial penicillin V bioreactor train is optimized for multiple objectives simultaneously. An industrial train, comprising a bank of identical bioreactors, is run semi-continuously in a synchronous fashion. The fermentation taking place in a bioreactor is modeled using a morphologically structured mechanism. For multi-objective optimization for two and three objectives, the elitist non-dominated sorting genetic algorithm (NSGA-II) is chosen. Instead of a single optimum as in the traditional optimization, a wide range of optimal design and operating conditions depicting trade-offs of key performance indicators such as batch cycle time, yield, profit and penicillin concentration, is successfully obtained. The effects of design and operating variables on the optimal solutions are discussed in detail. Copyright 2007 Wiley Periodicals, Inc.

Concentrating molasses distillery wastewater using biomimetic forward osmosis (FO) membranes.

PubMed

Singh, N; Petrinic, I; Hélix-Nielsen, C; Basu, S; Balakrishnan, M

2018-03-01

Treatment of sugarcane molasses distillery wastewater is challenging due to the presence of complex phenolic compounds (melanoidins and polyphenols) having antioxidant properties. Due to zero liquid discharge regulations, Indian distilleries continue to explore effective treatment options. This work examines the concentration of distillery wastewater by forward osmosis (FO) using aquaporin biomimetic membranes and magnesium chloride hexahydrate (MgCl 2 .6H 2 O) as draw solution. The operational parameters viz. feed solution and draw solution flow rate and draw solution concentration were optimized using 10% v/v melanoidins model feed solution. This was followed by trials with distillery wastewater. Under the conditions of this work, feed and draw flow rates of 1 L/min and draw solution concentration of 2M MgCl 2 .6H 2 O for melanoidins model solution and 3M MgCl 2 .6H 2 O for distillery wastewater were optimal for maximum rejection. Rejection of 90% melanoidins, 96% antioxidant activity and 84% COD was obtained with melanoidins model feed, with a corresponding water flux of 6.3 L/m 2 h. With as-received distillery wastewater, the rejection was similar (85-90%) to the melanoidins solution, but the water flux was lower (2.8 L/m 2 h). Water recovery from distillery wastewater over 24 h study period was higher with FO (70%) than reported for RO (35-45%). Repeated use of the FO membrane over five consecutive 24 h cycles with fresh feed and draw solutions and periodic cleaning showed consistent average water flux and rejection of the feed constituents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Solving Single Machine Total Weighted Tardiness Problem with Unequal Release Date Using Neurohybrid Particle Swarm Optimization Approach.

PubMed

Cakar, Tarik; Koker, Rasit

2015-01-01

A particle swarm optimization algorithm (PSO) has been used to solve the single machine total weighted tardiness problem (SMTWT) with unequal release date. To find the best solutions three different solution approaches have been used. To prepare subhybrid solution system, genetic algorithms (GA) and simulated annealing (SA) have been used. In the subhybrid system (GA and SA), GA obtains a solution in any stage, that solution is taken by SA and used as an initial solution. When SA finds better solution than this solution, it stops working and gives this solution to GA again. After GA finishes working the obtained solution is given to PSO. PSO searches for better solution than this solution. Later it again sends the obtained solution to GA. Three different solution systems worked together. Neurohybrid system uses PSO as the main optimizer and SA and GA have been used as local search tools. For each stage, local optimizers are used to perform exploitation to the best particle. In addition to local search tools, neurodominance rule (NDR) has been used to improve performance of last solution of hybrid-PSO system. NDR checked sequential jobs according to total weighted tardiness factor. All system is named as neurohybrid-PSO solution system.

Biosorption of formic and acetic acids from aqueous solution using activated carbon from shea butter seed shells

NASA Astrophysics Data System (ADS)

Adekola, Folahan A.; Oba, Ismaila A.

2017-10-01

The efficiency of prepared activated carbon from shea butter seed shells (SB-AC) for the adsorption of formic acid (FA) and acetic acid (AA) from aqueous solution was investigated. The effect of optimization parameters including initial concentration, agitation time, adsorbent dosage and temperature of adsorbate solution on the sorption capacity were studied. The SB-AC was characterized for the following parameters: bulk density, moisture content, ash content, pH, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The optimal conditions for the adsorption were established and the adsorption data for AA fitted Dubinin-Radushkevich (D-R) isotherm well, whereas FA followed Langmuir isotherm. The kinetic data were examined. It was found that pseudo-second-order kinetic model was found to adequately explain the sorption kinetic of AA and FA from aqueous solution. It was again found that intraparticle diffusion was found to explain the adsorption mechanism. Adsorption thermodynamic parameters were estimated and the negative values of Δ G showed that the adsorption process was feasible and spontaneous in nature, while the negative values of Δ H indicate that the adsorption process was exothermic. It is therefore established that SB-AC has good potential for the removal of AA and FA from aqueous solution. Hence, it should find application in the regular treatment of polluted water in aquaculture and fish breeding system.

A methodology for commonality analysis, with applications to selected space station systems

NASA Technical Reports Server (NTRS)

Thomas, Lawrence Dale

1989-01-01

The application of commonality in a system represents an attempt to reduce costs by reducing the number of unique components. A formal method for conducting commonality analysis has not been established. In this dissertation, commonality analysis is characterized as a partitioning problem. The cost impacts of commonality are quantified in an objective function, and the solution is that partition which minimizes this objective function. Clustering techniques are used to approximate a solution, and sufficient conditions are developed which can be used to verify the optimality of the solution. This method for commonality analysis is general in scope. It may be applied to the various types of commonality analysis required in the conceptual, preliminary, and detail design phases of the system development cycle.

Electrode effects on temporal changes in electrolyte pH and redox potential for water treatment

PubMed Central

Ciblak, Ali; Mao, Xuhui; Padilla, Ingrid; Vesper, Dorothy; Alshawabkeh, Iyad; Alshawabkeh, Akram N.

2012-01-01

The performance of electrochemical remediation methods could be optimized by controlling the physicochemical conditions of the electrochemical redox system. The effects of anode type (reactive or inert), current density and electrolyte composition on the temporal changes in pH and redox potential of the electrolyte were evaluated in divided and mixed electrolytes. Two types of electrodes were used: iron as a reactive electrode and mixed metal oxide coated titanium (MMO) as an inert electrode. Electric currents of 15, 30, 45 and 60 mA (37.5 mA L−1, 75 mA L−1, 112.5 mA L−1 and 150 mA L−1) were applied. Solutions of NaCl, Na2SO4 and NaHCO3 were selected to mimic different wastewater or groundwater composition. Iron anodes resulted in highly reducing electrolyte conditions compared to inert anodes. Electrolyte pH was dependent on electrode type, electrolyte composition and current density. The pH of mixed-electrolyte was stable when MMO electrodes were used. When iron electrodes were used, the pH of electrolyte with relatively low current density (37.5 mA L−1) did not show significant changes but the pH increased sharply for relatively high current density (150 mA L−1). Sulfate solution showed more basic and relatively more reducing electrolyte condition compared to bicarbonate and chloride solution. The study shows that a highly reducing environment could be achieved using iron anodes in divided or mixed electrolytes and the pH and redox potential could be optimized by using appropriate current and polarity reversal. PMID:22416866

A new frequency domain analytical solution of a cascade of diffusive channels for flood routing

NASA Astrophysics Data System (ADS)

Cimorelli, Luigi; Cozzolino, Luca; Della Morte, Renata; Pianese, Domenico; Singh, Vijay P.

2015-04-01

Simplified flood propagation models are often employed in practical applications for hydraulic and hydrologic analyses. In this paper, we present a new numerical method for the solution of the Linear Parabolic Approximation (LPA) of the De Saint Venant equations (DSVEs), accounting for the space variation of model parameters and the imposition of appropriate downstream boundary conditions. The new model is based on the analytical solution of a cascade of linear diffusive channels in the Laplace Transform domain. The time domain solutions are obtained using a Fourier series approximation of the Laplace Inversion formula. The new Inverse Laplace Transform Diffusive Flood Routing model (ILTDFR) can be used as a building block for the construction of real-time flood forecasting models or in optimization models, because it is unconditionally stable and allows fast and fairly precise computation.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

PubMed

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A Cascade Optimization Strategy for Solution of Difficult Multidisciplinary Design Problems

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Hopkins, Dale A.; Berke, Laszlo

1996-01-01

A research project to comparatively evaluate 10 nonlinear optimization algorithms was recently completed. A conclusion was that no single optimizer could successfully solve all 40 problems in the test bed, even though most optimizers successfully solved at least one-third of the problems. We realized that improved search directions and step lengths, available in the 10 optimizers compared, were not likely to alleviate the convergence difficulties. For the solution of those difficult problems we have devised an alternative approach called cascade optimization strategy. The cascade strategy uses several optimizers, one followed by another in a specified sequence, to solve a problem. A pseudorandom scheme perturbs design variables between the optimizers. The cascade strategy has been tested successfully in the design of supersonic and subsonic aircraft configurations and air-breathing engines for high-speed civil transport applications. These problems could not be successfully solved by an individual optimizer. The cascade optimization strategy, however, generated feasible optimum solutions for both aircraft and engine problems. This paper presents the cascade strategy and solutions to a number of these problems.

Mechanisms of EDDHA effects on the promotion of floral induction in the long-day plant Lemna minor (L.).

PubMed

Krajncic, Bozidar; Nemec, Joze

2003-02-01

EDDHA added in an optimal concentration (20.5 mumol.L-1) to a modified Pirson-Seidel nutrient solution induces flowering in some clones of the species Lemna minor, Lemna gibba and Spirodela polyrrhiza, which in the absence of EDDHA in the same nutrient solution do not flower. By adding EDDHA (20.5 mumol.L-1), floral induction under LD conditions is optimally promoted in the long-day (LD) species Lemna minor. After adding EDDHA to the nutrient solution, before floral induction and during flowering, Zn, Mn and Cu content is significantly increased in plants. Zn-EDDHA (0.86 mumol.L-1), Mn-EDDHA (1.51 mumol.L-1) and Cu-EDDHA (0.12 mumol.L-1), when used individually, greatly promote flowering under LD conditions as compared to flowering in the same nutrient solution with an equivalent quantity of Zn, Mn or Cu in the nonchelate form. If, on the other hand, Zn-EDDHA and Mn-EDDHA are added to the nutrient solution together (instead of Zn and Mn in nonchelate form), their effect on the promotion of flowering is less than in the case of their individual use. This shows that there is antagonism between Zn-EDDHA and Mn-EDDHA that is eliminated by adding EDDHA to the nutrient solution. We obtained the highest percentage of flowering plants (i.e. 74%) if we added EDDHA (20.5 mumol.L-1) to the nutrient solution containing Mn, Zn and Cu in chelate form. 74% of flowering plants actually means that flowering was achieved in all physiologically mature plants. Our results show that EDDHA promotes floral induction in Lemna minor under LD conditions, especially through chelating Zn, Mn and Cu, and, in addition, through eliminating the antagonism between Mn and Zn chelates EDDHA. Zn-EDDHA (0.86 mumol.L-1) also promote floral differentiation, especially cell division of microspore mother cells into dyads and those into microspore tetrads, which can be seen in microphotographs. When investigating possible pathways through which Mn-EDDHA, Zn-EDDHA and Cu-EDDHA promote flowering, we studied the effects of various concentrations of IAA and sucrose added to the nutrient solution as well. The results support the hypothesis that one of the possible pathways in which Mn-EDDHA promotes floral induction is through auxin oxidase, whereas Zn-EDDHA and Cu-EDDHA probably promote it through the enhancement of the photosynthesis and synthesis of sucrose.

Optimal transfers between unstable periodic orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.; Anderson, Rodney L.; Scheeres, Daniel J.; Born, George H.

2011-03-01

This paper presents a method to construct optimal transfers between unstable periodic orbits of differing energies using invariant manifolds. The transfers constructed in this method asymptotically depart the initial orbit on a trajectory contained within the unstable manifold of the initial orbit and later, asymptotically arrive at the final orbit on a trajectory contained within the stable manifold of the final orbit. Primer vector theory is applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connects the unstable and stable manifold trajectories. Transfers are constructed between unstable periodic orbits in the Sun-Earth, Earth-Moon, and Jupiter-Europa three-body systems. Multiple solutions are found between the same initial and final orbits, where certain solutions retrace interior portions of the trajectory. All transfers created satisfy the conditions for optimality. The costs of transfers constructed using manifolds are compared to the costs of transfers constructed without the use of manifolds. In all cases, the total cost of the transfer is significantly lower when invariant manifolds are used in the transfer construction. In many cases, the transfers that employ invariant manifolds are three times more efficient, in terms of fuel expenditure, than the transfer that do not. The decrease in transfer cost is accompanied by an increase in transfer time of flight.

Initial Results of an MDO Method Evaluation Study

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia M.; Kodiyalam, Srinivas

1998-01-01

The NASA Langley MDO method evaluation study seeks to arrive at a set of guidelines for using promising MDO methods by accumulating and analyzing computational data for such methods. The data are collected by conducting a series of re- producible experiments. In the first phase of the study, three MDO methods were implemented in the SIGHT: framework and used to solve a set of ten relatively simple problems. In this paper, we comment on the general considerations for conducting method evaluation studies and report some initial results obtained to date. In particular, although the results are not conclusive because of the small initial test set, other formulations, optimality conditions, and sensitivity of solutions to various perturbations. Optimization algorithms are used to solve a particular MDO formulation. It is then appropriate to speak of local convergence rates and of global convergence properties of an optimization algorithm applied to a specific formulation. An analogous distinction exists in the field of partial differential equations. On the one hand, equations are analyzed in terms of regularity, well-posedness, and the existence and unique- ness of solutions. On the other, one considers numerous algorithms for solving differential equations. The area of MDO methods studies MDO formulations combined with optimization algorithms, although at times the distinction is blurred. It is important to

Optimization and evaluation of lipid emulsions for intravenous co-delivery of artemether and lumefantrine in severe malaria treatment.

PubMed

Yang, Yinxian; Gao, Hailing; Zhou, Shuang; Kuang, Xiao; Wang, Zhenjie; Liu, Hongzhuo; Sun, Jin

2018-05-10

Parenteral therapy for severe and complicated malaria is necessary, but currently available parenteral antimalarials have their own drawbacks. As for recommended artemisinin-based combination therapy, antimalarial artemether and lumefantrine are limited in parenteral delivery due to their poor water solubility. Herein, the aim of this study was to develop the lipid-based emulsions for intravenous co-delivery of artemether and lumefantrine. The lipid emulsion was prepared by high-speed shear and high-pressure homogenization, and the formulations were optimized mainly by monitoring particle size distribution under autoclaved conditions. The final optimal formulation was with uniform particle size distribution (~ 220 nm), high encapsulation efficiency (~ 99%), good physiochemical stability, and acceptable hemolysis potential. The pharmacokinetic study in rats showed that C max of artemether and lumefantrine for the optimized lipid emulsions were significantly increased than the injectable solution, which was critical for rapid antimalarial activity. Furthermore, the AUC 0-t of artemether and lumefantrine in the lipid emulsion group were 5.01- and 1.39-fold of those from the solution, respectively, suggesting enhanced bioavailability. With these findings, the developed lipid emulsion is a promising alternative parenteral therapy for the malaria treatment, especially for severe or complicated malaria.

Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels

NASA Technical Reports Server (NTRS)

Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.

2011-01-01

We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Englander, Arnold C.

2014-01-01

Trajectory optimization methods using monotonic basin hopping (MBH) have become well developed during the past decade [1, 2, 3, 4, 5, 6]. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing random variable (RV)s from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by J. Englander [3, 6]) significantly improves monotonic basin hopping (MBH) performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness. Efficiency is finding better solutions in less time. Robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive random walks (RWs) originally developed in the field of statistical physics.

Biosorption of neodymium on Chlorella vulgaris in aqueous solution obtained from hard disk drive magnets

PubMed Central

Kucuker, Mehmet Ali; Wieczorek, Nils; Kuchta, Kerstin; Copty, Nadim K.

2017-01-01

In recent years, biosorption is being considered as an environmental friendly technology for the recovery of rare earth metals (REE). This study investigates the optimal conditions for the biosorption of neodymium (Nd) from an aqueous solution derived from hard drive disk magnets using green microalgae (Chlorella vulgaris). The parameters considered include solution pH, temperature and biosorbent dosage. Best-fit equilibrium as well as kinetic biosorption models were also developed. At the optimal pH of 5, the maximum experimental Nd uptakes at 21, 35 and 50°C and an initial Nd concentration of 250 mg/L were 126.13, 157.40 and 77.10 mg/g, respectively. Analysis of the optimal equilibrium sorption data showed that the data fitted well (R2 = 0.98) to the Langmuir isotherm model, with maximum monolayer coverage capacity (qmax) of 188.68 mg/g, and Langmuir isotherm constant (KL) of 0.029 L/mg. The corresponding separation factor (RL) is 0.12 indicating that the equilibrium sorption was favorable. The sorption kinetics of Nd ion follows well a pseudo-second order model (R2>0.99), even at low initial concentrations. These results show that Chlorella vulgaris has greater biosorption affinity for Nd than activated carbon and other algae types such as: A. Gracilis, Sargassum sp. and A. Densus. PMID:28388641

Polyaspartate extraction of cadmium ions from contaminated soil: Evaluation and optimization using central composite design.

PubMed

Mu'azu, Nuhu Dalhat; Haladu, Shamsuddeen A; Jarrah, Nabeel; Zubair, Mukarram; Essa, Mohammad H; Ali, Shaikh A

2018-01-15

The occurrences of heavy metal contaminated sites and soils and the need for devising environmentally friendly solutions have become global issues of serious concern. In this study, polyaspartate (a highly biodegradable agent) was synthesized using L-Aspartic acid via a new modified thermal procedure and employed for extraction of cadmium ions (Cd) from contaminated soil. Response surface methodology approach using 3 5 full faced centered central composite design was employed for modeling, evaluating and optimizing the influence of polyaspartate concentration (36-145mM), polyaspartate/soil ratio (5-25), initial heavy metal concentration (100-500mg/kg), initial pH (3-6) and extraction time (6-24h) on Cd ions extracted into the polyaspartate solution and its residual concentration in the treated soil. The Cd extraction efficacy obtained reached up to 98.8%. Increase in Cd extraction efficiency was associated with increase in the polyaspartate and Cd concentration coupled with lower polyaspertate/soil ratio and initial pH. Under the optimal conditions characterized with minimal utilization of the polyaspartate and high Cd ions removal, the extractible Cd in the polyaspartate solution reached up to 84.4mg/L which yielded 85% Cd extraction efficacy. This study demonstrates the suitability of using polyaspartate as an effective environmentally friendly chelating agent for Cd extraction from contaminated soils. Copyright © 2017 Elsevier B.V. All rights reserved.

Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback

NASA Astrophysics Data System (ADS)

Bruni, Renato; Celani, Fabio

2016-10-01

The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.

Optimization of cyanide extraction from wastewater using emulsion liquid membrane system by response surface methodology.

PubMed

Xue, Juan Qin; Liu, Ni Na; Li, Guo Ping; Dang, Long Tao

To solve the disposal problem of cyanide wastewater, removal of cyanide from wastewater using a water-in-oil emulsion type of emulsion liquid membrane (ELM) was studied in this work. Specifically, the effects of surfactant Span-80, carrier trioctylamine (TOA), stripping agent NaOH solution and the emulsion-to-external-phase-volume ratio on removal of cyanide were investigated. Removal of total cyanide was determined using the silver nitrate titration method. Regression analysis and optimization of the conditions were conducted using the Design-Expert software and response surface methodology (RSM). The actual cyanide removals and the removals predicted using RSM analysis were in close agreement, and the optimal conditions were determined to be as follows: the volume fraction of Span-80, 4% (v/v); the volume fraction of TOA, 4% (v/v); the concentration of NaOH, 1% (w/v); and the emulsion-to-external-phase volume ratio, 1:7. Under the optimum conditions, the removal of total cyanide was 95.07%, and the RSM predicted removal was 94.90%, with a small exception. The treatment of cyanide wastewater using an ELM is an effective technique for application in industry.

Simulation and Optimization of Large Scale Subsurface Environmental Impacts; Investigations, Remedial Design and Long Term Monitoring

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

Deschaine, L.M.; Chalmers Univ. of Technology, Dept. of Physical Resources, Complex Systems Group, Goteborg

2008-07-01

The global impact to human health and the environment from large scale chemical / radionuclide releases is well documented. Examples are the wide spread release of radionuclides from the Chernobyl nuclear reactors, the mobilization of arsenic in Bangladesh, the formation of Environmental Protection Agencies in the United States, Canada and Europe, and the like. The fiscal costs of addressing and remediating these issues on a global scale are astronomical, but then so are the fiscal and human health costs of ignoring them. An integrated methodology for optimizing the response(s) to these issues is needed. This work addresses development of optimalmore » policy design for large scale, complex, environmental issues. It discusses the development, capabilities, and application of a hybrid system of algorithms that optimizes the environmental response. It is important to note that 'optimization' does not singularly refer to cost minimization, but to the effective and efficient balance of cost, performance, risk, management, and societal priorities along with uncertainty analysis. This tool integrates all of these elements into a single decision framework. It provides a consistent approach to designing optimal solutions that are tractable, traceable, and defensible. The system is modular and scalable. It can be applied either as individual components or in total. By developing the approach in a complex systems framework, a solution methodology represents a significant improvement over the non-optimal 'trial and error' approach to environmental response(s). Subsurface environmental processes are represented by linear and non-linear, elliptic and parabolic equations. The state equations solved using numerical methods include multi-phase flow (water, soil gas, NAPL), and multicomponent transport (radionuclides, heavy metals, volatile organics, explosives, etc.). Genetic programming is used to generate the simulators either when simulation models do not exist, or to extend the accuracy of them. The uncertainty and sparse nature of information in earth science simulations necessitate stochastic representations. For discussion purposes, the solution to these site-wide challenges is divided into three sub-components; plume finding, long term monitoring, and site-wide remediation. Plume finding is the optimal estimation of the plume fringe(s) at a specified time. It is optimized by fusing geo-stochastic flow and transport simulations with the information content of data using a Kalman filter. The result is an optimal monitoring sensor network; the decision variable is location(s) of sensor in three dimensions. Long term monitoring extends this approach concept, and integrates the spatial-time correlations to optimize the decision variables of where to sample and when to sample over the project life cycle. Optimization of location and timing of samples to meet the desired accuracy of temporal plume movement is accomplished using enumeration or genetic algorithms. The remediation optimization solves the multi-component, multiphase system of equations and incorporates constraints on life-cycle costs, maximum annual costs, maximum allowable annual discharge (for assessing the monitored natural attenuation solution) and constraints on where remedial system component(s) can be located, including management overrides to force certain solutions to be chosen are incorporated for solution design. It uses a suite of optimization techniques, including the outer approximation method, Lipchitz global optimization, genetic algorithms, and the like. The automated optimal remedial design algorithm requires a stable simulator be available for the simulated process. This is commonly the case for all above specifications sans true three-dimensional multiphase flow. Much work is currently being conducted in the industry to develop stable 3D, three-phase simulators. If needed, an interim heuristic algorithm is available to get close to optimal for these conditions. This system process provides the full capability to optimize multi-source, multiphase, and multicomponent sites. The results of applying just components of these algorithms have produced predicted savings of as much as $90,000,000(US), when compared to alternative solutions. Investment in a pilot program to test the model saved 100% of the $20,000,000 predicted for the smaller test implementation. This was done without loss of effectiveness, and received an award from the Vice President - and now Nobel peace prize winner - Al Gore of the United States. (authors)« less

Guidance law development for aeroassisted transfer vehicles using matched asymptotic expansions

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Melamed, Nahum

1993-01-01

This report addresses and clarifies a number of issues related to the Matched Asymptotic Expansion (MAE) analysis of skip trajectories, or any class of problems that give rise to inner layers that are not associated directly with satisfying boundary conditions. The procedure for matching inner and outer solutions, and using the composite solution to satisfy boundary conditions is developed and rigorously followed to obtain a set of algebraic equations for the problem of inclination change with minimum energy loss. A detailed evaluation of the zeroth order guidance algorithm for aeroassisted orbit transfer is performed. It is shown that by exploiting the structure of the MAE solution procedure, the original problem, which requires the solution of a set of 20 implicit algebraic equations, can be reduced to a problem of 6 implicit equations in 6 unknowns. A solution that is near optimal, requires a minimum of computation, and thus can be implemented in real time and on-board the vehicle, has been obtained. Guidance law implementation entails treating the current state as a new initial state and repetitively solving the zeroth order MAE problem to obtain the feedback controls. Finally, a general procedure is developed for constructing a MAE solution up to first order, of the Hamilton-Jacobi-Bellman equation based on the method of characteristics. The development is valid for a class of perturbation problems whose solution exhibits two-time-scale behavior. A regular expansion for problems of this type is shown to be inappropriate since it is not valid over a narrow range of the independent variable. That is, it is not uniformly valid. Of particular interest here is the manner in which matching and boundary conditions are enforced when the expansion is carried out to first order. Two cases are distinguished-one where the left boundary condition coincides with, or lies to the right of, the singular region, and another one where the left boundary condition lies to the left of the singular region. A simple example is used to illustrate the procedure where the obtained solution is uniformly valid to O(Epsilon(exp 2)). The potential application of this procedure to aeroassisted plane change is also described and partially evaluated.

Preparation of acryloyl β-cyclodextrin-silica hybrid monolithic column and its application in pipette tip solid-phase extraction and HPLC analysis of methyl parathion and fenthion.

PubMed

Chen, Ling; Dang, Xueping; Ai, Youhong; Chen, Huaixia

2018-05-07

An acryloyl β-cyclodextrin-silica hybrid monolithic column for pipette tip solid-phase extraction and high-performance liquid chromatography determination of methyl parathion and fenthion have been prepared through a sol-gel polymerization method. The synthesis conditions, including the volume of cross-linker and the ratio of inorganic solution to organic solution, were optimized. The prepared monolithic column was characterized by thermogravimetric analysis, scanning electron microscopy and Fourier transform infrared spectroscopy. The eluent type, volume and flow rate, sample volume, flow rate, acidity and ionic strength were optimized in detail. Under the optimized conditions, a simple and sensitive pipette tip solid-phase extraction with high-performance liquid chromatography method was developed for the determination of methyl parathion and fenthion in lettuce. The method yielded a linear calibration curve in the concentration ranges of 15-400 μg/kg for methyl parathion and 20-400 μg/kg for fenthion with correlation coefficients of above 0.9957. The limits of detection were 4.5 μg/kg for methyl parathion and 6.0 μg/kg for fenthion, respectively. The recoveries of methyl parathion and fenthion spiked in lettuce ranged from 96.0 to 104.2% with relative standard deviations less than 8.4%. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Development and application of a gradient method for solving differential games

NASA Technical Reports Server (NTRS)

Roberts, D. A.; Montgomery, R. C.

1971-01-01

A technique for solving n-dimensional games is developed and applied to two pursuit-evasion games. The first is a two-dimensional game similar to the homicidal chauffeur but modified to resemble an airplane-helicopter engagement. The second is a five-dimensional game of two airplanes at constant altitude and with thrust and turning controls. The performance function to be optimized by the pursuer and evader was the distance between the evader and a given target point in front of the pursuer. The analytic solution to the first game reveals that both unique and nonunique solutions exist. A comparison between the gradient results and the analytic solution shows a dependence on the nominal controls in regions where nonunique solutions exist. In the unique solution region, the results from the two methods agree closely. The results for the five-dimensional two-airplane game are also shown to be dependent on the nominal controls selected and indicate that initial conditions are in a region of nonunique solutions.

Connecting the solution chemistry of PbI2 and MAI: a cyclodextrin-based supramolecular approach to the formation of hybrid halide perovskites† †Electronic supplementary information (ESI) available: Experimental section; Section 1: solution characterization; Section 2: solar cell optimization and characterization; Section 3: thin film characterization; Section 4: advanced structural characterization. See DOI: 10.1039/c7sc05095j

PubMed Central

Masi, Sofia; Aiello, Federica; Listorti, Andrea; Balzano, Federica; Altamura, Davide; Giannini, Cinzia; Caliandro, Rocco; Uccello-Barretta, Gloria

2018-01-01

The evolution from solvated precursors to hybrid halide perovskite films dictates most of the photophysical and optoelectronic properties of the final polycrystalline material. Specifically, the complex equilibria and the importantly different solubilities of lead iodide (PbI2) and methylammonium iodide (MAI) induce inhomogeneous crystal growth, often leading to a defect dense film showing non-optimal optoelectronic properties and intrinsic instability. Here, we explore a supramolecular approach based on the use of cyclodextrins (CDs) to modify the underlying solution chemistry. The peculiar phenomenon demonstrated is a tunable complexation between different CDs and MA+ cations concurrent to an out of cage PbI2 intercalation, representing the first report of a connection between the solvation equilibria of the two perovskite precursors. The optimal conditions in terms of CD cavity size and polarity translate to a neat enhancement of PbI2 solubility in the reaction media, leading to an equilibration of the availability of the precursors in solution. The macroscopic result of this is an improved nucleation process, leading to a perovskite material with higher crystallinity, better optical properties and improved moisture resistance. Remarkably, the use of CDs presents a great potential for a wide range of device-related applications, as well as for the development of tailored composite materials. PMID:29732103

Regenerative Life Support Systems Test Bed performance - Lettuce crop characterization

NASA Technical Reports Server (NTRS)

Barta, Daniel J.; Edeen, Marybeth A.; Eckhardt, Bradley D.

1992-01-01

System performance in terms of human life support requirements was evaluated for two crops of lettuce (Lactuca sative cv. Waldmann's Green) grown in the Regenerative Life Support Systems Test Bed. Each crop, grown in separate pots under identical environmental and cultural conditions, was irrigated with half-strength Hoagland's nutrient solution, with the frequency of irrigation being increased as the crop aged over the 30-day crop tests. Averaging over both crop tests, the test bed met the requirements of 2.1 person-days of oxygen production, 2.4 person-days of CO2 removal, and 129 person-days of potential potable water production. Gains in the mass of water and O2 produced and CO2 removed could be achieved by optimizing environmental conditions to increase plant growth rate and by optimizing cultural management methods.

Sensitivity enhancement by multiple-contact cross-polarization under magic-angle spinning.

PubMed

Raya, J; Hirschinger, J

2017-08-01

Multiple-contact cross-polarization (MC-CP) is applied to powder samples of ferrocene and l-alanine under magic-angle spinning (MAS) conditions. The method is described analytically through the density matrix formalism. The combination of a two-step memory function approach and the Anderson-Weiss approximation is found to be particularly useful to derive approximate analytical solutions for single-contact Hartmann-Hahn CP (HHCP) and MC-CP dynamics under MAS. We show that the MC-CP sequence requiring no pulse-shape optimization yields higher polarizations at short contact times than optimized adiabatic passage through the HH condition CP (APHH-CP) when the MAS frequency is comparable to the heteronuclear dipolar coupling, i.e., when APHH-CP through a single sideband matching condition is impossible or difficult to perform. It is also shown that the MC-CP sideband HH conditions are generally much broader than for single-contact HHCP and that efficient polarization transfer at the centerband HH condition can be reintroduced by rotor-asynchronous multiple equilibrations-re-equilibrations with the proton spin bath. Boundary conditions for the successful use of the MC-CP experiment when relying on spin-lattice relaxation for repolarization are also examined. Copyright © 2017 Elsevier Inc. All rights reserved.

Sensitivity enhancement by multiple-contact cross-polarization under magic-angle spinning

NASA Astrophysics Data System (ADS)

Raya, J.; Hirschinger, J.

2017-08-01

Multiple-contact cross-polarization (MC-CP) is applied to powder samples of ferrocene and L-alanine under magic-angle spinning (MAS) conditions. The method is described analytically through the density matrix formalism. The combination of a two-step memory function approach and the Anderson-Weiss approximation is found to be particularly useful to derive approximate analytical solutions for single-contact Hartmann-Hahn CP (HHCP) and MC-CP dynamics under MAS. We show that the MC-CP sequence requiring no pulse-shape optimization yields higher polarizations at short contact times than optimized adiabatic passage through the HH condition CP (APHH-CP) when the MAS frequency is comparable to the heteronuclear dipolar coupling, i.e., when APHH-CP through a single sideband matching condition is impossible or difficult to perform. It is also shown that the MC-CP sideband HH conditions are generally much broader than for single-contact HHCP and that efficient polarization transfer at the centerband HH condition can be reintroduced by rotor-asynchronous multiple equilibrations-re-equilibrations with the proton spin bath. Boundary conditions for the successful use of the MC-CP experiment when relying on spin-lattice relaxation for repolarization are also examined.

Removal of methylene blue from aqueous solution by wood millet carbon optimization using response surface methodology

NASA Astrophysics Data System (ADS)

Ghaedi, Mehrorang; Kokhdan, Syamak Nasiri

2015-02-01

The use of cheep, non-toxic, safe and easily available adsorbent are efficient and recommended material and alternative to the current expensive substance for pollutant removal from wastewater. The activated carbon prepared from wood waste of local tree (millet) extensively was applied for quantitative removal of methylene blue (MB), while simply. It was used to re-used after heating and washing with alkaline solution of ethanol. This new adsorbent was characterized by using BET surface area measurement, FT-IR, pH determination at zero point of charge (pHZPC) and Boehm titration method. Response surface methodology (RSM) by at least the number of experiments main and interaction of experimental conditions such as pH of solution, contact time, initial dye concentration and adsorbent dosage was optimized and set as pH 7, contact time 18 min, initial dye concentration 20 ppm and 0.2 g of adsorbent. It was found that variable such as pH and amount of adsorbent as solely or combination effects seriously affect the removal percentage. The fitting experimental data with conventional models reveal the applicability of isotherm models Langmuir model for their well presentation and description and Kinetic real rate of adsorption at most conditions efficiently can be represented pseudo-second order, and intra-particle diffusion. It novel material is good candidate for removal of huge amount of MB (20 ppm) in short time (18 min) by consumption of small amount (0.2 g).

A modified multi-objective particle swarm optimization approach and its application to the design of a deepwater composite riser

NASA Astrophysics Data System (ADS)

Zheng, Y.; Chen, J.

2017-09-01

A modified multi-objective particle swarm optimization method is proposed for obtaining Pareto-optimal solutions effectively. Different from traditional multi-objective particle swarm optimization methods, Kriging meta-models and the trapezoid index are introduced and integrated with the traditional one. Kriging meta-models are built to match expensive or black-box functions. By applying Kriging meta-models, function evaluation numbers are decreased and the boundary Pareto-optimal solutions are identified rapidly. For bi-objective optimization problems, the trapezoid index is calculated as the sum of the trapezoid's area formed by the Pareto-optimal solutions and one objective axis. It can serve as a measure whether the Pareto-optimal solutions converge to the Pareto front. Illustrative examples indicate that to obtain Pareto-optimal solutions, the method proposed needs fewer function evaluations than the traditional multi-objective particle swarm optimization method and the non-dominated sorting genetic algorithm II method, and both the accuracy and the computational efficiency are improved. The proposed method is also applied to the design of a deepwater composite riser example in which the structural performances are calculated by numerical analysis. The design aim was to enhance the tension strength and minimize the cost. Under the buckling constraint, the optimal trade-off of tensile strength and material volume is obtained. The results demonstrated that the proposed method can effectively deal with multi-objective optimizations with black-box functions.

Rapid Generation of Optimal Asteroid Powered Descent Trajectories Via Convex Optimization

NASA Technical Reports Server (NTRS)

Pinson, Robin; Lu, Ping

2015-01-01

This paper investigates a convex optimization based method that can rapidly generate the fuel optimal asteroid powered descent trajectory. The ultimate goal is to autonomously design the optimal powered descent trajectory on-board the spacecraft immediately prior to the descent burn. Compared to a planetary powered landing problem, the major difficulty is the complex gravity field near the surface of an asteroid that cannot be approximated by a constant gravity field. This paper uses relaxation techniques and a successive solution process that seeks the solution to the original nonlinear, nonconvex problem through the solutions to a sequence of convex optimal control problems.

Design Optimization Toolkit: Users' Manual

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

Aguilo Valentin, Miguel Alejandro

The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLABmore » command window.« less