Practical exergy analysis of centrifugal compressor performance using ASME-PTC-10 data

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

Carranti, F.J.

1997-07-01

It has been shown that measures of performance currently in use for industrial and process compressors do not give a true measure of energy utilization, and that the required assumptions of isentropic or adiabatic behavior are now always valid. A better indication of machine or process performance can be achieved using exergetic (second law) efficiencies and by employing the second law of thermodynamics to indicate the nature of irreversibilities and entropy generation in the compression process. In this type of analysis, performance is related to an environmental equilibrium condition, or dead state. Often, the differences between avoidable and unavoidable irreversibilitiesmore » ca be interpreted from these results. A general overview of the techniques involved in exergy analysis as applied to compressors and blowers is presented. A practical method to allow the calculation of exergetic efficiencies by manufacturers and end users is demonstrated using data from ASME Power Test Code input. These data are often readily available from compressor manufacturers for both design and off-design conditions, or can sometimes be obtained from field measurements. The calculations involved are simple and straightforward, and can demonstrate the energy usage situation for a variety of conditions. Here off-design is taken to mean at different rates of flow, as well as at different environmental states. The techniques presented are also applicable to many other equipment and process types.« less

Exergy analysis of hybrid nanofluids with optimum concentration in a plate heat exchanger

NASA Astrophysics Data System (ADS)

Kumar, Vikas; Tiwari, Arun Kumar; Ghosh, Subrata Kumar

2018-06-01

This paper highlights an investigation on the comparative analyses of exergetic performance with optimum volume concentration of hybrid nanofluids in a plate heat exchanger (PHE). Different types of hybrid nanofluids (Al2O3 + MWCNT/water, TiO2 + MWCNT/water, ZnO + MWCNT/water, and CeO2 + MWCNT/water) as coolant have been tested. Proportion of 0.75% of nanofluid has been found to be the optimum volume concentration. The requisite thermal and physical properties of the hybrid nanofluids were measured at 35 °C. Various exergetic performance parameters have been examined for comparing different hybrid nanofluids. The highest reduction in exergy loss of CeO2 + MWCNT/water hybrid nanofluid has been obtained at a concentration of about 24.75%. Entropy generation decreased with the increase in volume concentration. The results established that CeO2 + MWCNT/water hybrid nanofluid can be a promising coolant for exergetic performances in a PHE.

Heat Transfer and Friction Characteristics of Artificially Roughened Duct used for Solar Air Heaters—a Review

NASA Astrophysics Data System (ADS)

Kumar, Khushmeet; Prajapati, D. R.; Samir, Sushant

2018-02-01

Solar air heater uses the energy coming from the sun to heat the air. The conversion rate of solar energy to heat depends upon the efficiency of the solar air heater and this efficiency can be increased by the use of artificial roughness on the surface of absorber plate. Various studies were carried out to analyse the effect of different roughness geometries on heat transfer and friction factor characteristics. The thermo-hydraulic performance of solar air heater can be evaluated in terms of effective efficiency, thermo-hydraulic performance parameter and exergetic efficiency. In this study various geometries used for artificial roughness and to improve the performance of solar air heaters were studied. Also correlations developed by various researchers are presented in this paper.

Performance assessment of an irreversible nano Brayton cycle operating with Maxwell-Boltzmann gas

NASA Astrophysics Data System (ADS)

Açıkkalp, Emin; Caner, Necmettin

2015-05-01

In the last decades, nano-technology has been developed very fast. According to this, nano-cycle thermodynamics should improve with a similar rate. In this paper, a nano-scale irreversible Brayton cycle working with helium is evaluated for different thermodynamic criteria. These are maximum work output, ecological function, ecological coefficient of performance, exergetic performance criteria and energy efficiency. Thermodynamic analysis was performed for these criteria and results were submitted numerically. In addition, these criteria are compared with each other and the most convenient methods for the optimum conditions are suggested.

Exergy Analysis of the Cryogenic Helium Distribution System for the Large Hadron Collider (lhc)

NASA Astrophysics Data System (ADS)

Claudet, S.; Lebrun, Ph.; Tavian, L.; Wagner, U.

2010-04-01

The Large Hadron Collider (LHC) at CERN features the world's largest helium cryogenic system, spreading over the 26.7 km circumference of the superconducting accelerator. With a total equivalent capacity of 145 kW at 4.5 K including 18 kW at 1.8 K, the LHC refrigerators produce an unprecedented exergetic load, which must be distributed efficiently to the magnets in the tunnel over the 3.3 km length of each of the eight independent sectors of the machine. We recall the main features of the LHC cryogenic helium distribution system at different temperature levels and present its exergy analysis, thus enabling to qualify second-principle efficiency and identify main remaining sources of irreversibility.

Multi-criteria assessment of energy conversion systems by means of thermodynamic, economic and environmental parameters

NASA Astrophysics Data System (ADS)

Becerra Lopez, Humberto Ruben

2007-12-01

High expansion of power demand is expected in the Upper Rio Grande region (El Paso, Hudspeth, Culberson, Jeff Davis, Presidio and Brewster counties) as a result of both electrical demand growth and decommissioning of installed capacity. On the supply side a notable deployment of renewable power technologies can be projected owing to the recent introduction of a new energy policy in Texas, which attempts to reach 10,000 installed-MWe of renewable capacity for 2025. Power generation fueled by natural-gas might consistently expand due to the encouraged use of this fuel. In this context the array of participating technologies can be optimized, which, within a sustainability framework, translates into a multidimensional problem. The solution to the problem is presented through this dissertation in two main parts. The first part solves the thermodynamic-environmental problem through developing a dynamic model to project maximum allowable expansion of technologies. Predetermined alternatives include diverse renewable energy technologies (wind turbine, photovoltaic conversion, hybrid solar thermal parabolic trough, and solid oxide fuel cells), a conventional fossil-fuel technology (natural gas combined-cycle), and a breakthrough fossil-fuel technology (solid oxide fuel cells). The analysis is based on the concept of cumulative exergy consumption, expanded to include abatement of emissions. A Gompertz sigmoid growth is assumed and constrained by both exergetic self-sustenance and regional energy resource availability. This part of the analysis assumes that power demand expansion is met by full deployment of alternative technologies backed up by conventional technology. Results show that through a proper allowance for exergy reinvestment the power demand expansion may be met largely by alternative technologies minimizing the primary resource depletion. The second part of the study makes use of the dynamic model to support a multi-objective optimization routine, where the exergetic and economic costs are established as primary competing factors. An optimization algorithm is implemented using the constraint method. The solution is given as Pareto optimality with arrays for minimum cost and possible arrays for the tradeoff front. These arrays are further analyzed in terms of sustainability, cumulative exergy loss (i.e. irreversibilities and waste exergy) and incremental economic cost, and the results are compared with the goals of current legislated energy policy.

Exergetic life cycle assessment of hydrogen production from renewables

NASA Astrophysics Data System (ADS)

Granovskii, Mikhail; Dincer, Ibrahim; Rosen, Marc A.

Life cycle assessment is extended to exergetic life cycle assessment and used to evaluate the exergy efficiency, economic effectiveness and environmental impact of producing hydrogen using wind and solar energy in place of fossil fuels. The product hydrogen is considered a fuel for fuel cell vehicles and a substitute for gasoline. Fossil fuel technologies for producing hydrogen from natural gas and gasoline from crude oil are contrasted with options using renewable energy. Exergy efficiencies and greenhouse gas and air pollution emissions are evaluated for all process steps, including crude oil and natural gas pipeline transportation, crude oil distillation and natural gas reforming, wind and solar electricity generation, hydrogen production through water electrolysis, and gasoline and hydrogen distribution and utilization. The use of wind power to produce hydrogen via electrolysis, and its application in a fuel cell vehicle, exhibits the lowest fossil and mineral resource consumption rate. However, the economic attractiveness, as measured by a "capital investment effectiveness factor," of renewable technologies depends significantly on the ratio of costs for hydrogen and natural gas. At the present cost ratio of about 2 (per unit of lower heating value or exergy), capital investments are about five times lower to produce hydrogen via natural gas rather than wind energy. As a consequence, the cost of wind- and solar-based electricity and hydrogen is substantially higher than that of natural gas. The implementation of a hydrogen fuel cell instead of an internal combustion engine permits, theoretically, an increase in a vehicle's engine efficiency of about of two times. Depending on the ratio in engine efficiencies, the substitution of gasoline with "renewable" hydrogen leads to (a) greenhouse gas (GHG) emissions reductions of 12-23 times for hydrogen from wind and 5-8 times for hydrogen from solar energy, and (b) air pollution (AP) emissions reductions of 38-76 times for hydrogen from wind and 16-32 times for hydrogen from solar energy. By comparison, substitution of gasoline with hydrogen from natural gas allows reductions in GHG emissions only as a result of the increased efficiency of a fuel cell engine, and a reduction of AP emissions of 2.5-5 times. These data suggest that "renewable" hydrogen represents a potential long-term solution to many environmental problems.

Environmental sustainability assessments of pharmaceuticals: an emerging need for simplification in life cycle assessments.

PubMed

De Soete, Wouter; Debaveye, Sam; De Meester, Steven; Van der Vorst, Geert; Aelterman, Wim; Heirman, Bert; Cappuyns, Philippe; Dewulf, Jo

2014-10-21

The pharmaceutical and fine chemical industries are eager to strive toward innovative products and technologies. This study first derives hotspots in resource consumption of 2839 Basic Operations in 40 Active Pharmaceutical Ingredient synthesis steps through Exergetic Life Cycle Assessment (ELCA). Second, since companies are increasingly obliged to quantify the environmental sustainability of their products, two alternative ways of simplifying (E)LCA are discussed. The usage of averaged product group values (R(2) = 3.40 × 10(-30)) is compared with multiple linear regression models (R(2) = 8.66 × 10(-01)) in order to estimate resource consumption of synthesis steps. An optimal set of predictor variables is postulated to balance model complexity and embedded information with usability and capability of merging models with existing Enterprise Resource Planning (ERP) data systems. The amount of organic solvents used, molar efficiency, and duration of a synthesis step were shown to be the most significant predictor variables. Including additional predictor variables did not contribute to the predictive power and eventually weakens the model interpretation. Ideally, an organization should be able to derive its environmental impact from readily available ERP data, linking supply chains back to the cradle of resource extraction, excluding the need for an approximation with product group averages.

Modeling and comparative assessment of bubbling fluidized bed gasification system for syngas production - a gateway for a cleaner future in Pakistan.

PubMed

Shehzad, Areeb; Bashir, Mohammed J K; Horttanainen, Mika; Manttari, Mika; Havukainen, Jouni; Abbas, Ghulam

2017-06-19

The present study explores the potential of MSW gasification for exergy analysis and has been recently given a premier attention in a region like Pakistan where the urbanization is rapidly growing and resources are few. The plant capacity was set at 50 MW based on reference data available and the total exergetic efficiency was recorded to be 31.5 MW. The largest irreversibility distribution appears in the gasifier followed by methanation unit and CO 2 capture. The effect of process temperature, equivalence ratio and MSW moisture content was explored for inspecting the variations in syngas composition, lower heating value, carbon conversion efficiency and cold gas efficiency. Special attention of the paper is paid to the comparative assessment of MSW gasification products in four regions, namely Pakistan, USA, UAE and Thailand. This extended study gave an insight into the spectrum of socioeconomic conditions with varying MSW compositions in order to explain the effect of MSW composition variance on the gasification products.

Thermodynamic and Mechanical Analysis of a Thermomagnetic Rotary Engine

NASA Astrophysics Data System (ADS)

Fajar, D. M.; Khotimah, S. N.; Khairurrijal

2016-08-01

A heat engine in magnetic system had three thermodynamic coordinates: magnetic intensity ℋ, total magnetization ℳ, and temperature T, where the first two of them are respectively analogous to that of gaseous system: pressure P and volume V. Consequently, Carnot cycle that constitutes the principle of a heat engine in gaseous system is also valid on that in magnetic system. A thermomagnetic rotary engine is one model of it that was designed in the form of a ferromagnetic wheel that can rotates because of magnetization change at Curie temperature. The study is aimed to describe the thermodynamic and mechanical analysis of a thermomagnetic rotary engine and calculate the efficiencies. In thermodynamic view, the ideal processes are isothermal demagnetization, adiabatic demagnetization, isothermal magnetization, and adiabatic magnetization. The values of thermodynamic efficiency depend on temperature difference between hot and cold reservoir. In mechanical view, a rotational work is determined through calculation of moment of inertia and average angular speed. The value of mechanical efficiency is calculated from ratio between rotational work and heat received by system. The study also obtains exergetic efficiency that states the performance quality of the engine.

Thermodynamic analysis of a new dual evaporator CO2 transcritical refrigeration cycle

NASA Astrophysics Data System (ADS)

Abdellaoui, Ezzaalouni Yathreb; Kairouani, Lakdar Kairouani

2017-03-01

In this work, a new dual-evaporator CO2 transcritical refrigeration cycle with two ejectors is proposed. In this new system, we proposed to recover the lost energy of condensation coming off the gas cooler and operate the refrigeration cycle ejector free and enhance the system performance and obtain dual-temperature refrigeration simultaneously. The effects of some key parameters on the thermodynamic performance of the modified cycle are theoretically investigated based on energetic and exergetic analysis. The simulation results for the modified cycle indicate more effective system performance improvement than the single ejector in the CO2 vapor compression cycle using ejector as an expander ranging up to 46%. The exergetic analysis for this system is made. The performance characteristics of the proposed cycle show its promise in dual-evaporator refrigeration system.

A methodology for thermodynamic simulation of high temperature, internal reforming fuel cell systems

NASA Astrophysics Data System (ADS)

Matelli, José Alexandre; Bazzo, Edson

This work presents a methodology for simulation of fuel cells to be used in power production in small on-site power/cogeneration plants that use natural gas as fuel. The methodology contemplates thermodynamics and electrochemical aspects related to molten carbonate and solid oxide fuel cells (MCFC and SOFC, respectively). Internal steam reforming of the natural gas hydrocarbons is considered for hydrogen production. From inputs as cell potential, cell power, number of cell in the stack, ancillary systems power consumption, reformed natural gas composition and hydrogen utilization factor, the simulation gives the natural gas consumption, anode and cathode stream gases temperature and composition, and thermodynamic, electrochemical and practical efficiencies. Both energetic and exergetic methods are considered for performance analysis. The results obtained from natural gas reforming thermodynamics simulation show that the hydrogen production is maximum around 700 °C, for a steam/carbon ratio equal to 3. As shown in the literature, the found results indicate that the SOFC is more efficient than MCFC.

Exergy analysis of helium liquefaction systems based on modified Claude cycle with two-expanders

NASA Astrophysics Data System (ADS)

Thomas, Rijo Jacob; Ghosh, Parthasarathi; Chowdhury, Kanchan

2011-06-01

Large-scale helium liquefaction systems, being energy-intensive, demand judicious selection of process parameters. An effective tool for design and analysis of thermodynamic cycles for these systems is exergy analysis, which is used to study the behavior of a helium liquefaction system based on modified Claude cycle. Parametric evaluation using process simulator Aspen HYSYS® helps to identify the effects of cycle pressure ratio and expander flow fraction on the exergetic efficiency of the liquefaction cycle. The study computes the distribution of losses at different refrigeration stages of the cycle and helps in selecting optimum cycle pressures, operating temperature levels of expanders and mass flow rates through them. Results from the analysis may help evolving guidelines for designing appropriate thermodynamic cycles for practical helium liquefaction systems.

Exergie /4th revised and enlarged edition/

NASA Astrophysics Data System (ADS)

Baloh, T.; Wittwer, E.

The theoretical concept of exergy is explained and its practical applications are discussed. Equilibrium and thermal equilibrium are reviewed as background, and exergy is considered as a reference point for solid-liquid, liquid-liquid, and liquid-gas systems. Exergetic calculations and their graphic depictions are covered. The concepts of enthalpy and entropy are reviewed in detail, including their applications to gas mixtures, solutions, and isolated substances. The exergy of gas mixtures, solutions, and isolated substances is discussed, including moist air, liquid water in water vapor, dry air, and saturation-limited solutions. Mollier exergy-enthalpy-entropy diagrams are presented for two-component systems, and exergy losses for throttling, isobaric mixing, and heat transfer are addressed. The relationship of exergy to various processes is covered, including chemical processes, combustion, and nuclear reactions. The optimization of evaporation plants through exergy is discussed. Calculative examples are presented for energy production and heating, industrial chemical processes, separation of liquid air, nuclear reactors, and others.

Energo- and exergo-technical assessment of ground-source heat pump systems for geothermal energy production from underground mines.

PubMed

Amiri, Leyla; Madadian, Edris; Hassani, Ferri P

2018-06-08

The objective of this study is to perform the energy and exergy analysis of an integrated ground-source heat pump (GSHP) system, along with technical assessment, for geothermal energy production by deployment of Engineering Equation Solver (EES). The system comprises heat pump cycle and ground heat exchanger for extracting geothermal energy from underground mine water. A simultaneous energy and exergy analysis of the system is brought off. These analyses provided persuasive outcomes due to the use of an economic and green source of energy. The energetic coefficient of performance (COP) of the entire system is 2.33 and the exergy efficiency of the system is 28.6%. The exergetic efficiencies of the compressor, ground heat exchanger, evaporator, expansion valve, condenser and fan are computed to be 38%, 42%, 53%, 55%, 60% and 64%, respectively. In the numerical investigation, different alteration such as changing the temperature and pressure of the condenser show promising potential for further application of GSHPs. The outcomes of this research can be used for developing and designing novel coupled heat and power systems.

Preliminary design of the beam screen cooling for the Future Circular Collider of hadron beams

NASA Astrophysics Data System (ADS)

Kotnig, C.; Tavian, L.

2015-12-01

Following recommendations of the recent update of the European strategy in particle physics, CERN has undertaken an international study of possible future circular colliders beyond the LHC. This study considers an option for a very high energy (100 TeV) hadron-hadron collider located in a quasi-circular underground tunnel having a circumference of 80 to 100 km. The synchrotron radiation emitted by the high-energy hadron beam increases by more than two orders of magnitude compared to the LHC. To reduce the entropic load on the superconducting magnets’ refrigeration system, beam screens are indispensable to extract the heat load at a higher temperature level. After illustrating the decisive constraints of the beam screen's refrigeration design, this paper presents a preliminary design of the length of a continuous cooling loop comparing helium and neon, for different cooling channel geometries with emphasis on the cooling length limitations and the exergetic efficiency.

Fuels and chemicals from equine-waste-derived tail gas reactive pyrolysis oil: technoeconomic analysis, environmental and exergetic life cycle assessment

USDA-ARS?s Scientific Manuscript database

Horse manure, whose improper disposal imposes considerable environmental costs, constitutes an apt feedstock for conversion to renewable fuels and chemicals when tail gas reactive pyrolysis (TGRP) is employed. TGRP is a modification of fast pyrolysis that recycles its non-condensable gases and produ...

Comparison between reverse Brayton and Kapitza based LNG boil-off gas reliquefaction system using exergy analysis

NASA Astrophysics Data System (ADS)

Kochunni, Sarun Kumar; Chowdhury, Kanchan

2017-02-01

LNG boil-off gas (BOG) reliquefaction systems in LNG carrier ships uses refrigeration devices which are based on reverse Brayton, Claude, Kapitza (modified Claude) or Cascade cycles. Some of these refrigeration devices use nitrogen as the refrigerants and hence nitrogen storage vessels or nitrogen generators needs to be installed in LNG carrier ships which consume space and add weight to the carrier. In the present work, a new configuration based on Kapitza liquefaction cycle which uses BOG itself as working fluid is proposed and has been compared with Reverse Brayton Cycle (RBC) on sizes of heat exchangers and compressor operating parameters. Exergy analysis is done after simulating at steady state with Aspen Hysys 8.6® and the comparison between RBC and Kapitza may help designers to choose reliquefaction system with appropriate process parameters and sizes of equipment. With comparable exergetic efficiency as that of an RBC, a Kaptiza system needs only BOG compressor without any need of nitrogen gas.

Experimental study of 2-layer regenerators using Mn-Fe-Si-P materials

NASA Astrophysics Data System (ADS)

Christiaanse, T. V.; Trevizoli, P. V.; Misra, Sumohan; Carroll, Colman; van Asten, David; Zhang, Lian; Teyber, R.; Govindappa, P.; Niknia, I.; Rowe, A.

2018-03-01

This work describes an experimental study of a two layer active magnetic regenerator with varying transition temperature spacing. The transition temperature of the materials is based on the specific heat peak of the materials. A transition temperature based on the average of the heating and cooling curves at zero Tesla field value is used to refer to the materials throughout this paper. This study uses five Mn-Fe-Si-P materials with transition temperatures of 294.6 K, 292.3 K, 290.7 K, 282.5 K and 281.4 K. Six different regenerators are tested. A reference configuration is tested using the 294.6 K material a hot side layer and with a second passive layer of lead spheres as cold side layer. Followed by four configurations that use the same 294.6 K material as hot side layer, but where each configuration uses a different cold side material. For the second active layer the materials are used in sequence; 292.3 K, 290.7 K, 282.5 K and 281.4K. Lastly, a sixth configuration uses the 292.3 K and 282.5 K materials. For each configuration, the temperature span is measured for rejection temperatures from 40 °C to 9 °C and at 0 W and 2 W applied load. Experimental results for temperature span and exergetic cooling power are compared based on the differences from the reference configuration. Materials are analysed based on material performance metrics such as peak adiabatic temperature change, peak entropy change and RCP(s) values. For the cases considered, a closer transition temperature spacing generally gives a greater temperature span and exergetic cooling power than further spaced materials, even when the combined materials have comparatively lower performance metrics. When two materials with higher RCP(s) values with large transition temperature spacing are compared to materials with lower RCP(s) values but, closer transition temperature spacing a higher exergetic cooling power and temperature span is found for the latter.

Process development and exergy cost sensitivity analysis of a hybrid molten carbonate fuel cell power plant and carbon dioxide capturing process

NASA Astrophysics Data System (ADS)

Mehrpooya, Mehdi; Ansarinasab, Hojat; Moftakhari Sharifzadeh, Mohammad Mehdi; Rosen, Marc A.

2017-10-01

An integrated power plant with a net electrical power output of 3.71 × 105 kW is developed and investigated. The electrical efficiency of the process is found to be 60.1%. The process includes three main sub-systems: molten carbonate fuel cell system, heat recovery section and cryogenic carbon dioxide capturing process. Conventional and advanced exergoeconomic methods are used for analyzing the process. Advanced exergoeconomic analysis is a comprehensive evaluation tool which combines an exergetic approach with economic analysis procedures. With this method, investment and exergy destruction costs of the process components are divided into endogenous/exogenous and avoidable/unavoidable parts. Results of the conventional exergoeconomic analyses demonstrate that the combustion chamber has the largest exergy destruction rate (182 MW) and cost rate (13,100 /h). Also, the total process cost rate can be decreased by reducing the cost rate of the fuel cell and improving the efficiency of the combustion chamber and heat recovery steam generator. Based on the total avoidable endogenous cost rate, the priority for modification is the heat recovery steam generator, a compressor and a turbine of the power plant, in rank order. A sensitivity analysis is done to investigate the exergoeconomic factor parameters through changing the effective parameter variations.

Simulation of high temperature thermal energy storage system based on coupled metal hydrides for solar driven steam power plants

DOE PAGES

d'Entremont, Anna; Corgnale, Claudio; Hardy, Bruce; ...

2018-01-11

Concentrating solar power plants can achieve low cost and efficient renewable electricity production if equipped with adequate thermal energy storage systems. Metal hydride based thermal energy storage systems are appealing candidates due to their demonstrated potential for very high volumetric energy densities, high exergetic efficiencies, and low costs. The feasibility and performance of a thermal energy storage system based on NaMgH 2F hydride paired with TiCr 1.6Mn 0.2 is examined, discussing its integration with a solar-driven ultra-supercritical steam power plant. The simulated storage system is based on a laboratory-scale experimental apparatus. It is analyzed using a detailed transport model accountingmore » for the thermochemical hydrogen absorption and desorption reactions, including kinetics expressions adequate for the current metal hydride system. The results show that the proposed metal hydride pair can suitably be integrated with a high temperature steam power plant. The thermal energy storage system achieves output energy densities of 226 kWh/m 3, 9 times the DOE SunShot target, with moderate temperature and pressure swings. Also, simulations indicate that there is significant scope for performance improvement via heat-transfer enhancement strategies.« less

Simulation of high temperature thermal energy storage system based on coupled metal hydrides for solar driven steam power plants

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

d'Entremont, Anna; Corgnale, Claudio; Hardy, Bruce

Concentrating solar power plants can achieve low cost and efficient renewable electricity production if equipped with adequate thermal energy storage systems. Metal hydride based thermal energy storage systems are appealing candidates due to their demonstrated potential for very high volumetric energy densities, high exergetic efficiencies, and low costs. The feasibility and performance of a thermal energy storage system based on NaMgH 2F hydride paired with TiCr 1.6Mn 0.2 is examined, discussing its integration with a solar-driven ultra-supercritical steam power plant. The simulated storage system is based on a laboratory-scale experimental apparatus. It is analyzed using a detailed transport model accountingmore » for the thermochemical hydrogen absorption and desorption reactions, including kinetics expressions adequate for the current metal hydride system. The results show that the proposed metal hydride pair can suitably be integrated with a high temperature steam power plant. The thermal energy storage system achieves output energy densities of 226 kWh/m 3, 9 times the DOE SunShot target, with moderate temperature and pressure swings. Also, simulations indicate that there is significant scope for performance improvement via heat-transfer enhancement strategies.« less

Design of Particle-Based Thermal Energy Storage for a Concentrating Solar Power System

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

Ma, Zhiwen; Zhang, Ruichong; Sawaged, Fadi

Solid particles can operate at higher temperature than current molten salt or oil, and they can be a heat-transfer and storage medium in a concentrating solar power (CSP) system. By using inexpensive solid particles and containment material for thermal energy storage (TES), the particle-TES cost can be significantly lower than other TES methods such as a nitrate-salt system. The particle-TES system can hold hot particles at more than 800 degrees C with high thermal performance. The high particle temperatures increase the temperature difference between the hot and cold particles, and they improve the TES capacity. The particle-based CSP system ismore » able to support high-efficiency power generation, such as the supercritical carbon-dioxide Brayton power cycle, to achieve >50% thermal-electric conversion efficiency. This paper describes a solid particle-TES system that integrates into a CSP plant. The hot particles discharge to a heat exchanger to drive the power cycle. The returning cold particles circulate through a particle receiver to absorb solar heat and charge the TES. This paper shows the design of a particle-TES system including containment silos, foundation, silo insulation, and particle materials. The analysis provides results for four TES capacities and two silo configurations. The design analysis indicates that the system can achieve high thermal efficiency, storage effectiveness (i.e., percentage usage of the hot particles), and exergetic efficiency. An insulation method for the hot silo was considered. The particle-TES system can achieve high performance and low cost, and it holds potential for next-generation CSP technology.« less

Thermal Assessment of a Latent-Heat Energy Storage Module During Melting and Freezing for Solar Energy Applications

NASA Astrophysics Data System (ADS)

Ramos Archibold, Antonio

Capital investment reduction, exergetic efficiency improvement and material compatibility issues have been identified as the primary techno-economic challenges associated, with the near-term development and deployment of thermal energy storage (TES) in commercial-scale concentrating solar power plants. Three TES techniques have gained attention in the solar energy research community as possible candidates to reduce the cost of solar-generated electricity, namely (1) sensible heat storage, (2) latent heat (tank filled with phase change materials (PCMs) or encapsulated PCMs packed in a vessel) and (3) thermochemical storage. Among these the PCM macro-encapsulation approach seems to be one of the most-promising methods because of its potential to develop more effective energy exchange, reduce the cost associated with the tank and increase the exergetic efficiency. However, the technological barriers to this approach arise from the encapsulation techniques used to create a durable capsule, as well as an assessment of the fundamental thermal energy transport mechanisms during the phase change. A comprehensive study of the energy exchange interactions and induced fluid flow during melting and solidification of a confined storage medium is reported in this investigation from a theoretical perspective. Emphasis has been placed on the thermal characterization of a single constituent storage module rather than an entire storage system, in order to, precisely capture the energy exchange contributions of all the fundamental heat transfer mechanisms during the phase change processes. Two-dimensional, axisymmetric, transient equations for mass, momentum and energy conservation have been solved numerically by the finite volume scheme. Initially, the interaction between conduction and natural convection energy transport modes, in the absence of thermal radiation, is investigated for solar power applications at temperatures (300--400°C). Later, participating thermal radiation within the storage medium has been included in order to extend the conventional natural convection-dominated model and to analyze its influence on the melting and freezing dynamics at elevated temperatures (800-850°C). A parametric analysis has been performed in order to ascertain the effects of the controlling parameters on the melting/freezing rates and the total and radiative heat transfer rates at the inner surface of the shell. The results show that the presence of thermal radiation enhances the melting and solidification processes. Finally, a simplified model of the packed bed heat exchanger with multiple spherical capsules filled with the storage medium and positioned in a vertical array inside a cylindrical container is analyzed and numerically solved. The influence of the inlet mass flow rate, inner shell surface emissivity and PCM attenuation coefficient on the melting dynamics of the PCM has been analyzed and quantified.

High performance felt-metal-wick heat pipe for solar receivers

NASA Astrophysics Data System (ADS)

Andraka, Charles E.; Moss, Timothy A.; Baturkin, Volodymyr; Zaripov, Vladlen; Nishchyk, Oleksandr

2016-05-01

Sodium heat pipes have been identified as a potentially effective heat transport approach for CSP systems that require near-isothermal input to power cycles or storage, such as dish Stirling and highly recuperated reheat-cycle supercritical CO2 turbines. Heat pipes offer high heat flux capabilities, leading to small receivers, as well as low exergetic losses through isothermal coupling with the engine. Sandia developed a felt metal wick approach in the 1990's, and demonstrated very high performance1. However, multiple durability issues arose, primarily the structural collapse of the wick at temperature over short time periods. NTUU developed several methods of improving robustness of the wick2, but the resulting wick had limited performance capabilities. For application to CSP systems, the wick structures must retain high heat pipe performance with robustness for long term operation. In this paper we present our findings in developing an optimal balance between performance and ruggedness, including operation of a laboratory-scale heat pipe for over 5500 hours so far. Application of heat pipes to dish-Stirling systems has been shown to increase performance as much as 20%3, and application to supercritical CO2 systems has been proposed.

Comparative Assessment of Gasification Based Coal Power Plants with Various CO2 Capture Technologies Producing Electricity and Hydrogen

PubMed Central

2014-01-01

Seven different types of gasification-based coal conversion processes for producing mainly electricity and in some cases hydrogen (H2), with and without carbon dioxide (CO2) capture, were compared on a consistent basis through simulation studies. The flowsheet for each process was developed in a chemical process simulation tool “Aspen Plus”. The pressure swing adsorption (PSA), physical absorption (Selexol), and chemical looping combustion (CLC) technologies were separately analyzed for processes with CO2 capture. The performances of the above three capture technologies were compared with respect to energetic and exergetic efficiencies, and the level of CO2 emission. The effect of air separation unit (ASU) and gas turbine (GT) integration on the power output of all the CO2 capture cases is assessed. Sensitivity analysis was carried out for the CLC process (electricity-only case) to examine the effect of temperature and water-cooling of the air reactor on the overall efficiency of the process. The results show that, when only electricity production in considered, the case using CLC technology has an electrical efficiency 1.3% and 2.3% higher than the PSA and Selexol based cases, respectively. The CLC based process achieves an overall CO2 capture efficiency of 99.9% in contrast to 89.9% for PSA and 93.5% for Selexol based processes. The overall efficiency of the CLC case for combined electricity and H2 production is marginally higher (by 0.3%) than Selexol and lower (by 0.6%) than PSA cases. The integration between the ASU and GT units benefits all three technologies in terms of electrical efficiency. Furthermore, our results suggest that it is favorable to operate the air reactor of the CLC process at higher temperatures with excess air supply in order to achieve higher power efficiency. PMID:24578590

Comparative Assessment of Gasification Based Coal Power Plants with Various CO2 Capture Technologies Producing Electricity and Hydrogen.

PubMed

Mukherjee, Sanjay; Kumar, Prashant; Hosseini, Ali; Yang, Aidong; Fennell, Paul

2014-02-20

Seven different types of gasification-based coal conversion processes for producing mainly electricity and in some cases hydrogen (H 2 ), with and without carbon dioxide (CO 2 ) capture, were compared on a consistent basis through simulation studies. The flowsheet for each process was developed in a chemical process simulation tool "Aspen Plus". The pressure swing adsorption (PSA), physical absorption (Selexol), and chemical looping combustion (CLC) technologies were separately analyzed for processes with CO 2 capture. The performances of the above three capture technologies were compared with respect to energetic and exergetic efficiencies, and the level of CO 2 emission. The effect of air separation unit (ASU) and gas turbine (GT) integration on the power output of all the CO 2 capture cases is assessed. Sensitivity analysis was carried out for the CLC process (electricity-only case) to examine the effect of temperature and water-cooling of the air reactor on the overall efficiency of the process. The results show that, when only electricity production in considered, the case using CLC technology has an electrical efficiency 1.3% and 2.3% higher than the PSA and Selexol based cases, respectively. The CLC based process achieves an overall CO 2 capture efficiency of 99.9% in contrast to 89.9% for PSA and 93.5% for Selexol based processes. The overall efficiency of the CLC case for combined electricity and H 2 production is marginally higher (by 0.3%) than Selexol and lower (by 0.6%) than PSA cases. The integration between the ASU and GT units benefits all three technologies in terms of electrical efficiency. Furthermore, our results suggest that it is favorable to operate the air reactor of the CLC process at higher temperatures with excess air supply in order to achieve higher power efficiency.

Exergy-based efficiency and renewability assessment of biofuel production.

PubMed

Dewulf, J; Van Langenhove, H; Van De Velde, B

2005-05-15

This study presents an efficiency and renewability analysis of the production of three biofuels: rapeseed methyl ester (RME), soybean methyl ester (SME) and corn-based ethanol (EtOH). The overall production chains have been taken into account: not only the agricultural crop production and the industrial conversion into biofuel, but also production of the supply of agricultural resources (pesticides, fertilizers, fuel, seeding material) and industrial resources (energy and chemicals) to transform the crops into biofuel. Simultaneously, byproducts of the agricultural and industrial processes have been taken into account when resources have to be allocated to the biofuels. The technical analysis via the second law of thermodynamics revealed that corn-based EtOH results in the highest production rate with an exergetic fuel content of 68.8 GJ ha(-1) yr(-1), whereas the RME and SME results were limited to 47.5 and 16.4 GJ ha(-1) yr(-1). The allocated nonrenewable resource input to deliver these biofuels is significant: 16.5, 15.4, and 5.6 MJ ha(-1) yr(-1). This means that these biofuels, generally considered as renewable resources, embed a nonrenewable fraction of one-quarter for EtOH and even one-third for RME and SME. This type of analysis provides scientifically sound quantitative information that is necessarywith respect to the sustainability analysis of so-called renewable energy.

Comparison of Overall Resource Consumption of Biosolids Management System Processes Using Exergetic Life Cycle Assessment.

PubMed

Alanya, Sevda; Dewulf, Jo; Duran, Metin

2015-08-18

This study focused on the evaluation of biosolids management systems (BMS) from a natural resource consumption point of view. Additionally, the environmental impact of the facilities was benchmarked using Life Cycle Assessment (LCA) to provide a comprehensive assessment. This is the first study to apply a Cumulative Exergy Extraction from the Natural Environment (CEENE) method for an in-depth resource use assessment of BMS where two full-scale BMS and seven system variations were analyzed. CEENE allows better system evaluation and understanding of how much benefit is achievable from the products generated by BMS, which have valorization potential. LCA results showed that environmental burden is mostly from the intense electricity consumption. The CEENE analysis further revealed that the environmental burden is due to the high consumption of fossil and nuclear-based natural resources. Using Cumulative Degree of Perfection, higher resource-use efficiency, 53%, was observed in the PTA-2 where alkaline stabilization rather than anaerobic digestion is employed. However, an anaerobic digestion process is favorable over alkaline stabilization, with 35% lower overall natural resource use. The most significant reduction of the resource footprint occurred when the output biogas was valorized in a combined heat and power system.

Experimental comparison between R409A and R437A performance in a heat pump unit

NASA Astrophysics Data System (ADS)

Duarte, M. V.; Pires, L. C.; Silva, P. D.; Gaspar, P. D.

2017-04-01

This paper reports an experimental comparison between the use of the refrigerants R409A and R437A in a heat pump unit designed and developed to work with R12. Although the use of both refrigerants in new equipments were abolished in EU and US according the new F-Gas Regulation of EU and SNAP, they still being used as options for R12 in old equipments, especially in developing countries. Both refrigerants were studied for the same test conditions, according to two groups of tests: group A (variation of the heat source temperature) and group B (variation of refrigerant flow rate). The results obtained showed that the R437A presents a higher discharge pressure and a lower discharge temperature. The heating and cooling capacities of both refrigerants were similar, as well as the exergetic efficiency. For the group A of tests the COP of both refrigerants was similar and for the group B of tests the R409A presented an average COP 15% higher. According to the results obtained it is recommended the use of R409A in old equipments (as transition refrigerant) until the acquisition of equipments operating with refrigerants with low-GWP becomes technically and economic feasible.

Modeling of a thermal energy storage system based on coupled metal hydrides (magnesium iron – sodium alanate) for concentrating solar power plants

DOE PAGES

d'Entremont, A.; Corgnale, C.; Sulic, M.; ...

2017-08-31

Concentrating solar power plants represent low cost and efficient solutions for renewable electricity production only if adequate thermal energy storage systems are included. Metal hydride thermal energy storage systems have demonstrated the potential to achieve very high volumetric energy densities, high exergetic efficiencies, and low costs. The current work analyzes the technical feasibility and the performance of a storage system based on the high temperature Mg 2FeH 6 hydride coupled with the low temperature Na 3AlH 6 hydride. To accomplish this, a detailed transport model has been set up and the coupled metal hydride system has been simulated based onmore » a laboratory scale experimental configuration. Proper kinetics expressions have been developed and included in the model to replicate the absorption and desorption process in the high temperature and low temperature hydride materials. The system showed adequate hydrogen transfer between the two metal hydrides, with almost complete charging and discharging, during both thermal energy storage and thermal energy release. The system operating temperatures varied from 450°C to 500°C, with hydrogen pressures between 30 bar and 70 bar. This makes the thermal energy storage system a suitable candidate for pairing with a solar driven steam power plant. The model results, obtained for the selected experimental configuration, showed an actual thermal energy storage system volumetric energy density of about 132 kWh/m 3, which is more than 5 times the U.S. Department of Energy SunShot target (25 kWh/m 3).« less

Modeling of a thermal energy storage system based on coupled metal hydrides (magnesium iron – sodium alanate) for concentrating solar power plants

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

d'Entremont, A.; Corgnale, C.; Sulic, M.

Concentrating solar power plants represent low cost and efficient solutions for renewable electricity production only if adequate thermal energy storage systems are included. Metal hydride thermal energy storage systems have demonstrated the potential to achieve very high volumetric energy densities, high exergetic efficiencies, and low costs. The current work analyzes the technical feasibility and the performance of a storage system based on the high temperature Mg 2FeH 6 hydride coupled with the low temperature Na 3AlH 6 hydride. To accomplish this, a detailed transport model has been set up and the coupled metal hydride system has been simulated based onmore » a laboratory scale experimental configuration. Proper kinetics expressions have been developed and included in the model to replicate the absorption and desorption process in the high temperature and low temperature hydride materials. The system showed adequate hydrogen transfer between the two metal hydrides, with almost complete charging and discharging, during both thermal energy storage and thermal energy release. The system operating temperatures varied from 450°C to 500°C, with hydrogen pressures between 30 bar and 70 bar. This makes the thermal energy storage system a suitable candidate for pairing with a solar driven steam power plant. The model results, obtained for the selected experimental configuration, showed an actual thermal energy storage system volumetric energy density of about 132 kWh/m 3, which is more than 5 times the U.S. Department of Energy SunShot target (25 kWh/m 3).« less

Performance Evaluation of an Experimental Turbojet Engine

NASA Astrophysics Data System (ADS)

Ekici, Selcuk; Sohret, Yasin; Coban, Kahraman; Altuntas, Onder; Karakoc, T. Hikmet

2017-11-01

An exergy analysis is presented including design parameters and performance assessment, by identifying the losses and efficiency of a gas turbine engine. The aim of this paper is to determine the performance of a small turbojet engine with an exergetic analysis based on test data. Experimental data from testing was collected at full-load of small turbojet engine. The turbojet engine exhaust data contains CO2, CO, CH4, H2, H2O, NO, NO2, N2 and O2 with a relative humidity of 35 % for the ambient air of the performed experiments. The evaluated main components of the turbojet engine are the air compressor, the combustion chamber and the gas turbine. As a result of the thermodynamic analysis, exergy efficiencies (based on product/fuel) of the air compressor, the combustion chamber and the gas turbine are 81.57 %, 50.13 % and 97.81 %, respectively. A major proportion of the total exergy destruction was found for the combustion chamber at 167.33 kW. The exergy destruction rates are 8.20 %, 90.70 % and 1.08 % in the compressor, the combustion chamber and the gas turbine, respectively. The rates of exergy destruction within the system components are compared on the basis of the exergy rate of the fuel provided to the engine. Eventually, the exergy rate of the fuel is calculated to be 4.50 % of unusable due to exergy destruction within the compressor, 49.76 % unusable due to exergy destruction within the combustion chamber and 0.59 % unusable due to exergy destruction within the gas turbine. It can be stated that approximately 55 % of the exergy rate of the fuel provided to the engine can not be used by the engine.

Sustainability Efficiency Factor: Measuring Sustainability in Advanced Energy Systems through Exergy, Exergoeconomic, Life Cycle, and Economic Analyses

NASA Astrophysics Data System (ADS)

Boldon, Lauren

The Encyclopedia of Life Support Systems defines sustainability or industrial ecology as "the wise use of resources through critical attention to policy, social, economic, technological, and ecological management of natural and human engineered capital so as to promote innovations that assure a higher degree of human needs fulfilment, or life support, across all regions of the world, while at the same time ensuring intergenerational equity" (Encyclopedia of Life Support Systems 1998). Developing and integrating sustainable energy systems to meet growing energy demands is a daunting task. Although the technology to utilize renewable energies is well understood, there are limited locations which are ideally suited for renewable energy development. Even in areas with significant wind or solar availability, backup or redundant energy supplies are still required during periods of low renewable generation. This is precisely why it would be difficult to make the switch directly from fossil fuel to renewable energy generation. A transition period in which a base-load generation supports renewables is required, and nuclear energy suits this need well with its limited life cycle emissions and fuel price stability. Sustainability is achieved by balancing environmental, economic, and social considerations, such that energy is produced without detriment to future generations through loss of resources, harm to the environment, etcetera. In essence, the goal is to provide future generations with the same opportunities to produce energy that the current generation has. This research explores sustainability metrics as they apply to a small modular reactor (SMR)-hydrogen production plant coupled with wind energy and storage technologies to develop a new quantitative sustainability metric, the Sustainability Efficiency Factor (SEF), for comparison of energy systems. The SEF incorporates the three fundamental aspects of sustainability and provides SMR or nuclear hybrid energy system (NHES) reference case studies to (1) introduce sustainability metrics, such as life cycle assessment, (2) demonstrate the methods behind exergy and exergoeconomic analyses, (3) provide an economic analysis of the potential for SMR development from first-of-a-kind (FOAK) to nth-of-a-kind (NOAK), thereby illustrating possible cost reductions and deployment flexibility for SMRs over large conventional nuclear reactors, (4) assess the competitive potential for incorporation of storage and hydrogen production in NHES and in regulated and deregulated electricity markets, (5) compare an SMR-hydrogen production plant to a natural gas steam methane reforming plant using the SEF, and (6) identify and review the social considerations which would support future nuclear development domestically and abroad, such as public and political/regulatory needs and challenges. The Global Warming Potential (GWP) for the SMR (300 MWth)-wind (60 MWe)-high temperature steam electrolysis (200 tons Hydrogen per day) system was calculated as approximately 874 g CO2-equivalent as part of the life cycle assessment. This is 92.6% less than the GWP estimated for steam methane reforming production of hydrogen by Spath and Mann. The unit exergetic and exergoeconomic costs were determined for each flow within the NHES system as part of the exergy/exergoeconomic cost analyses. The unit exergetic cost is lower for components yielding more meaningful work like the one exiting the SMR with a unit exergetic cost of 1.075 MW/MW. In comparison, the flow exiting the turbine has a very high unit exergetic cost of 15.31, as most of the useful work was already removed through the turning of the generator/compressor shaft. In a similar manner, the high unit exergoeconomic cost of 12.45/MW*sec is observed for the return flow to the reactors, because there is very little exergy present. The first and second law efficiencies and the exergoeconomic factors were also determined over several cases. For the first or base SMR case, first and second law efficiencies of 81.5% and 93.3% were observed respectively. With an increase in reactor outlet temperature of only 20°C, both the SMR efficiencies increased, while the exergoeconomic factor decreased by 0.2%. As part of the SMR economic analysis, specific capital and total capital investment costs (TCIC) were determined in addition to conditional effects on the net present value (NPV), levelized cost of electricity (LCOE), and payback periods. For a 1260 MWe FOAK multi-module SMR site with 7 modules, the specific capital costs were 27-38% higher than that of a 1260 MWe single large reactor site. A NOAK site, on the other hand, may be 19% lower to 18% higher than the large reactor site, demonstrating that it may break even or be even more economical in average or favorable market conditions. The NOAK TCIC for single and multi-module SMR sites were determined to be 914-1,230 million and 660-967 million per module, respectively, reflecting the substantial savings incurred with sites designed for and deployed with multiple modules. For the same NOAK 7-unit multi-module site, the LCOE was calculated as 67-84/MWh, which is slightly less than that of the conventional large reactor LCOE of 89/MWh with a weighted average cost of capital of 10%, a 50%-50% share of debt and equity, and a corporate tax rate of 35%. The payback period for the SMR site, however, is 4 years longer. Construction delays were also analyzed to compare the SMR and large reactor sites, demonstrating the SMR NPV and LCOE are less sensitive to delays. For a 3 year delay, the SMR NPV decreased by 22%, while the large reactor NPV decreased by 34.1%. Similarly the SMR and large reactor LCOEs increased by 7.8% and 8.1%, respectively. An NHES case with hydrogen production and storage was performed, illustrating how the profit share of revenue is improved with the addition of hydrogen production. Although the costs are increased with the addition, 78% of the hydrogen revenue is profit, while only 50% of the electricity generation revenue is profit. A second NHES case study was analyzed to assess the NPV, LCOE, and payback differences in deregulated and regulated electricity markets. For a 60 year lifetime, Case C (with nuclear, wind, and hydrogen production) is economical in the deregulated market with an NPV of 66.3 million and a payback period of 10 years, but not in the regulated one with an NPV of approximately -115.3 million and a payback period of 11 years. With either market type, the plants levelized costs remain $82.82/MWh, which is still reasonable with respect to prior LCOE values determined for SMR and large reactor sites. Utilizing all the methodology and results obtained and presented in this thesis, the SEF may be calculated. The NHES SEF was determined to be 18.3% higher than that of natural gas steam methane reforming, illustrating a higher level of sustainability. The SEF quantitatively uses the exergoeconomic cost and irreversibilities obtained from the exergy analysis, the GWP obtained from the life cycle assessment and costs/fees associated with emissions and pollutants, and relevant economic data obtained from an economic analysis. This reflects the environmental, socio-political, and economic pillars of sustainability.

Performance Testing of Jefferson Lab 12 GeV Helium Screw Compressors

DOE PAGES

Knudsen, P.; Ganni, V.; Dixon, K.; ...

2015-08-10

Oil injected screw compressors have essentially superseded all other types of compressors in modern helium refrigeration systems due to their large displacement capacity, reliability, minimal vibration, and capability of handling helium's high heat of compression. At the present state of compressor system designs for helium refrigeration systems, typically two-thirds of the lost input power is due to the compression system. It is important to understand the isothermal and volumetric efficiencies of these machines to help properly design the compression system to match the refrigeration process. It is also important to identify those primary compressor skid exergetic loss mechanisms which maymore » be reduced, thereby offering the possibility of significantly reducing the input power to helium refrigeration processes which are extremely energy intensive. This paper summarizes the results collected during the commissioning of the new compressor system for Jefferson Lab's (JLab's) 12 GeV upgrade. The compressor skid packages were designed by JLab and built to print by industry. They incorporate a number of modifications not typical of helium screw compressor packages and most importantly allow a very wide range of operation so that JLab's patented Floating Pressure Process can be fully utilized. This paper also summarizes key features of the skid design that allow this process and facilitate the maintenance and reliability of these helium compressor systems.« less

Performance Testing of Jefferson Lab 12 GeV Helium Screw Compressors

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

Knudsen, P.; Ganni, V.; Dixon, K.

Oil injected screw compressors have essentially superseded all other types of compressors in modern helium refrigeration systems due to their large displacement capacity, reliability, minimal vibration, and capability of handling helium's high heat of compression. At the present state of compressor system designs for helium refrigeration systems, typically two-thirds of the lost input power is due to the compression system. It is important to understand the isothermal and volumetric efficiencies of these machines to help properly design the compression system to match the refrigeration process. It is also important to identify those primary compressor skid exergetic loss mechanisms which maymore » be reduced, thereby offering the possibility of significantly reducing the input power to helium refrigeration processes which are extremely energy intensive. This paper summarizes the results collected during the commissioning of the new compressor system for Jefferson Lab's (JLab's) 12 GeV upgrade. The compressor skid packages were designed by JLab and built to print by industry. They incorporate a number of modifications not typical of helium screw compressor packages and most importantly allow a very wide range of operation so that JLab's patented Floating Pressure Process can be fully utilized. This paper also summarizes key features of the skid design that allow this process and facilitate the maintenance and reliability of these helium compressor systems.« less

Influence of the cooling degree upon performances of internal combustion engine

NASA Astrophysics Data System (ADS)

Grǎdinariu, Andrei Cristian; Mihai, Ioan

2016-12-01

Up to present, air cooling systems still raise several unsolved problems due to conditions imposed by the environment in terms of temperature and pollution levels. The present paper investigates the impact of the engine cooling degree upon its performances, as important specific power is desired for as low as possible fuel consumption. A technical solution advanced by the authors[1], consists of constructing a bi-flux compressor, which can enhance the engine's performances. The bi-flux axial compressor accomplishes two major functions, that is it cools down the engine and it also turbocharges it. The present paper investigates the temperature changes corresponding to the fresh load, during the use of a bi-flux axial compressor. This compressor is economically simple, compact, and offers an optimal response at low rotational speeds of the engine, when two compression steps are used. The influence of the relative coefficient of air temperature drop upon working agent temperature at the intercooler exit is also investigated in the present work. The variation of the thermal load coefficient by report to the working agent temperature is also investigated during engine cooling. The variation of the average combustion temperature is analyzed in correlation to the thermal load coefficient and the temperatures of the working fluid at its exit from the cooling system. An exergetic analysis was conducted upon the influence of the cooling degree on the motor fluid and the gases resulted from the combustion process.

Nuclear Hybrid Energy System: Molten Salt Energy Storage (Summer Report 2013)

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

Sabharwall, Piyush; mckellar, Michael George; Yoon, Su-Jong

2013-11-01

Effective energy use is a main focus and concern in the world today because of the growing demand for energy. The nuclear hybrid energy system (NHES) is a valuable technical concept that can potentially diversify and leverage existing energy technologies. This report considers a particular NHES design that combines multiple energy systems including a nuclear reactor, energy storage system (ESS), variable renewable generator (VRG), and additional process heat applications. Energy storage is an essential component of this particular NHES because its design allows the system to produce peak power while the nuclear reactor operates at constant power output. Many energymore » storage options are available, but this study mainly focuses on a molten salt ESS. The primary purpose of the molten salt ESS is to enable the nuclear reactor to be a purely constant heat source by acting as a heat storage component for the reactor during times of low demand, and providing additional capacity for thermo-electric power generation during times of peak electricity demand. This report will describe the rationale behind using a molten salt ESS and identify an efficient molten salt ESS configuration that may be used in load following power applications. Several criteria are considered for effective energy storage and are used to identify the most effective ESS within the NHES. Different types of energy storage are briefly described with their advantages and disadvantages. The general analysis to determine the most efficient molten salt ESS involves two parts: thermodynamic, in which energetic and exergetic efficiencies are considered; and economic. Within the molten salt ESS, the two-part analysis covers three major system elements: molten salt ESS designs (two tank direct and thermocline), the molten salt choice, and the different power cycles coupled with the molten salt ESS. Analysis models are formulated and analyzed to determine the most effective ESS. The results show that the most efficient idealized energy storage system is the two tank direct molten salt ESS with an Air Brayton combined cycle using LiF-NaF-KF as the molten salt, and the most economical is the same design with KCl MgCl2 as the molten salt. With energy production being a major worldwide industry, understanding the most efficient molten salt ESS boosts development of an effective NHES with cheap, clean, and steady power.« less

Evaluation of Hybrid Power Plants using Biomass, Photovoltaics and Steam Electrolysis for Hydrogen and Power Generation

NASA Astrophysics Data System (ADS)

Petrakopoulou, F.; Sanz, J.

2014-12-01

Steam electrolysis is a promising process of large-scale centralized hydrogen production, while it is also considered an excellent option for the efficient use of renewable solar and geothermal energy resources. This work studies the operation of an intermediate temperature steam electrolyzer (ITSE) and its incorporation into hybrid power plants that include biomass combustion and photovoltaic panels (PV). The plants generate both electricity and hydrogen. The reference -biomass- power plant and four variations of a hybrid biomass-PV incorporating the reference biomass plant and the ITSE are simulated and evaluated using exergetic analysis. The variations of the hybrid power plants are associated with (1) the air recirculation from the electrolyzer to the biomass power plant, (2) the elimination of the sweep gas of the electrolyzer, (3) the replacement of two electric heaters with gas/gas heat exchangers, and (4) the replacement two heat exchangers of the reference electrolyzer unit with one heat exchanger that uses steam from the biomass power plant. In all cases, 60% of the electricity required in the electrolyzer is covered by the biomass plant and 40% by the photovoltaic panels. When comparing the hybrid plants with the reference biomass power plant that has identical operation and structure as that incorporated in the hybrid plants, we observe an efficiency decrease that varies depending on the scenario. The efficiency decrease stems mainly from the low effectiveness of the photovoltaic panels (14.4%). When comparing the hybrid scenarios, we see that the elimination of the sweep gas decreases the power consumption due to the elimination of the compressor used to cover the pressure losses of the filter, the heat exchangers and the electrolyzer. Nevertheless, if the sweep gas is used to preheat the air entering the boiler of the biomass power plant, the efficiency of the plant increases. When replacing the electric heaters with gas-gas heat exchangers, the efficiency of the plant increases, although the higher pressure losses of the flue-gas path increase the requirements of the air compressor. Finally, replacing the two heat exchangers of the electrolyzer unit with one that uses extracted steam from the biomass power plant can lead to an overall decrease in the operating and investment costs of the plant.

Development and Analysis of New Integrated Energy Systems for Sustainable Buildings

NASA Astrophysics Data System (ADS)

Khalid, Farrukh

Excessive consumption of fossil fuels in the residential sector and their associated negative environmental impacts bring a significant challenge to engineers within research and industrial communities throughout the world to develop more environmentally benign methods of meeting energy needs of residential sector in particular. This thesis addresses potential solutions for the issue of fossils fuel consumption in residential buildings. Three novel renewable energy based multigeneration systems are proposed for different types of residential buildings, and a comprehensive assessment of energetic and exergetic performances is given on the basis of total occupancy, energy load, and climate conditions. System 1 is a multigeneration system based on two renewable energy sources. It uses biomass and solar resources. The outputs of System 1 are electricity, space heating, cooling, and hot water. The energy and exergy efficiencies of System 1 are 91.0% and 34.9%, respectively. The results of the optimisation analysis show that the net present cost of System 1 is 2,700,496 and that the levelised cost of electricity is 0.117/kWh. System 2 is a multigeneration system, integrating three renewable energy based subsystems; wind turbine, concentrated solar collector, and Organic Rankine Cycle supplied by a ground source heat exchanger. The outputs of the System 2 are electricity, hot water, heating and cooling. The optimisation analysis shows that net present cost is 35,502 and levelised cost of electricity is 0.186/kWh. The energy and exergy efficiencies of System 2 are found to be 34.6% and 16.2%, respectively. System 3 is a multigeneration system, comprising two renewable energy subsystems-- geothermal and solar to supply power, cooling, heating, and hot water. The optimisation analysis shows that the net present cost of System 3 is 598,474, and levelised cost of electricity of 0.111/kWh. The energy and exergy efficiencies of System 3 are 20.2% and 19.2%, respectively, with outputs of electricity, hot water, cooling and space heating. A performance assessment for identical conditions indicates that System 3 offers the best performance, with the minimum net present cost of 26,001 and levelised cost of electricity of 0.136/kWh.

Optimization under uncertainty of parallel nonlinear energy sinks

NASA Astrophysics Data System (ADS)

Boroson, Ethan; Missoum, Samy; Mattei, Pierre-Olivier; Vergez, Christophe

2017-04-01

Nonlinear Energy Sinks (NESs) are a promising technique for passively reducing the amplitude of vibrations. Through nonlinear stiffness properties, a NES is able to passively and irreversibly absorb energy. Unlike the traditional Tuned Mass Damper (TMD), NESs do not require a specific tuning and absorb energy over a wider range of frequencies. Nevertheless, they are still only efficient over a limited range of excitations. In order to mitigate this limitation and maximize the efficiency range, this work investigates the optimization of multiple NESs configured in parallel. It is well known that the efficiency of a NES is extremely sensitive to small perturbations in loading conditions or design parameters. In fact, the efficiency of a NES has been shown to be nearly discontinuous in the neighborhood of its activation threshold. For this reason, uncertainties must be taken into account in the design optimization of NESs. In addition, the discontinuities require a specific treatment during the optimization process. In this work, the objective of the optimization is to maximize the expected value of the efficiency of NESs in parallel. The optimization algorithm is able to tackle design variables with uncertainty (e.g., nonlinear stiffness coefficients) as well as aleatory variables such as the initial velocity of the main system. The optimal design of several parallel NES configurations for maximum mean efficiency is investigated. Specifically, NES nonlinear stiffness properties, considered random design variables, are optimized for cases with 1, 2, 3, 4, 5, and 10 NESs in parallel. The distributions of efficiency for the optimal parallel configurations are compared to distributions of efficiencies of non-optimized NESs. It is observed that the optimization enables a sharp increase in the mean value of efficiency while reducing the corresponding variance, thus leading to more robust NES designs.

Finite-size effect on optimal efficiency of heat engines.

PubMed

Tajima, Hiroyasu; Hayashi, Masahito

2017-07-01

The optimal efficiency of quantum (or classical) heat engines whose heat baths are n-particle systems is given by the strong large deviation. We give the optimal work extraction process as a concrete energy-preserving unitary time evolution among the heat baths and the work storage. We show that our optimal work extraction turns the disordered energy of the heat baths to the ordered energy of the work storage, by evaluating the ratio of the entropy difference to the energy difference in the heat baths and the work storage, respectively. By comparing the statistical mechanical optimal efficiency with the macroscopic thermodynamic bound, we evaluate the accuracy of the macroscopic thermodynamics with finite-size heat baths from the statistical mechanical viewpoint. We also evaluate the quantum coherence effect on the optimal efficiency of the cycle processes without restricting their cycle time by comparing the classical and quantum optimal efficiencies.

Efficiency Enhancement for an Inductive Wireless Power Transfer System by Optimizing the Impedance Matching Networks.

PubMed

Miao, Zhidong; Liu, Dake; Gong, Chen

2017-10-01

Inductive wireless power transfer (IWPT) is a promising power technology for implantable biomedical devices, where the power consumption is low and the efficiency is the most important consideration. In this paper, we propose an optimization method of impedance matching networks (IMN) to maximize the IWPT efficiency. The IMN at the load side is designed to achieve the optimal load, and the IMN at the source side is designed to deliver the required amount of power (no-more-no-less) from the power source to the load. The theoretical analyses and design procedure are given. An IWPT system for an implantable glaucoma therapeutic prototype is designed as an example. Compared with the efficiency of the resonant IWPT system, the efficiency of our optimized system increases with a factor of 1.73. Besides, the efficiency of our optimized IWPT system is 1.97 times higher than that of the IWPT system optimized by the traditional maximum power transfer method. All the discussions indicate that the optimization method proposed in this paper could achieve a high efficiency and long working time when the system is powered by a battery.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.

PubMed

Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-09-15

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks

PubMed Central

Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-01-01

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity. PMID:28914818

An approach for aerodynamic optimization of transonic fan blades

NASA Astrophysics Data System (ADS)

Khelghatibana, Maryam

Aerodynamic design optimization of transonic fan blades is a highly challenging problem due to the complexity of flow field inside the fan, the conflicting design requirements and the high-dimensional design space. In order to address all these challenges, an aerodynamic design optimization method is developed in this study. This method automates the design process by integrating a geometrical parameterization method, a CFD solver and numerical optimization methods that can be applied to both single and multi-point optimization design problems. A multi-level blade parameterization is employed to modify the blade geometry. Numerical analyses are performed by solving 3D RANS equations combined with SST turbulence model. Genetic algorithms and hybrid optimization methods are applied to solve the optimization problem. In order to verify the effectiveness and feasibility of the optimization method, a singlepoint optimization problem aiming to maximize design efficiency is formulated and applied to redesign a test case. However, transonic fan blade design is inherently a multi-faceted problem that deals with several objectives such as efficiency, stall margin, and choke margin. The proposed multi-point optimization method in the current study is formulated as a bi-objective problem to maximize design and near-stall efficiencies while maintaining the required design pressure ratio. Enhancing these objectives significantly deteriorate the choke margin, specifically at high rotational speeds. Therefore, another constraint is embedded in the optimization problem in order to prevent the reduction of choke margin at high speeds. Since capturing stall inception is numerically very expensive, stall margin has not been considered as an objective in the problem statement. However, improving near-stall efficiency results in a better performance at stall condition, which could enhance the stall margin. An investigation is therefore performed on the Pareto-optimal solutions to demonstrate the relation between near-stall efficiency and stall margin. The proposed method is applied to redesign NASA rotor 67 for single and multiple operating conditions. The single-point design optimization showed +0.28 points improvement of isentropic efficiency at design point, while the design pressure ratio and mass flow are, respectively, within 0.12% and 0.11% of the reference blade. Two cases of multi-point optimization are performed: First, the proposed multi-point optimization problem is relaxed by removing the choke margin constraint in order to demonstrate the relation between near-stall efficiency and stall margin. An investigation on the Pareto-optimal solutions of this optimization shows that the stall margin has been increased with improving near-stall efficiency. The second multi-point optimization case is performed with considering all the objectives and constraints. One selected optimized design on the Pareto front presents +0.41, +0.56 and +0.9 points improvement in near-peak efficiency, near-stall efficiency and stall margin, respectively. The design pressure ratio and mass flow are, respectively, within 0.3% and 0.26% of the reference blade. Moreover the optimized design maintains the required choking margin. Detailed aerodynamic analyses are performed to investigate the effect of shape optimization on shock occurrence, secondary flows, tip leakage and shock/tip-leakage interactions in both single and multi-point optimizations.

Considerations on the Optimal and Efficient Processing of Information-Bearing Signals

ERIC Educational Resources Information Center

Harms, Herbert Andrew

2013-01-01

Noise is a fundamental hurdle that impedes the processing of information-bearing signals, specifically the extraction of salient information. Processing that is both optimal and efficient is desired; optimality ensures the extracted information has the highest fidelity allowed by the noise, while efficiency ensures limited resource usage. Optimal…

Beam-steering efficiency optimization method based on a rapid-search algorithm for liquid crystal optical phased array.

PubMed

Xiao, Feng; Kong, Lingjiang; Chen, Jian

2017-06-01

A rapid-search algorithm to improve the beam-steering efficiency for a liquid crystal optical phased array was proposed and experimentally demonstrated in this paper. This proposed algorithm, in which the value of steering efficiency is taken as the objective function and the controlling voltage codes are considered as the optimization variables, consisted of a detection stage and a construction stage. It optimized the steering efficiency in the detection stage and adjusted its search direction adaptively in the construction stage to avoid getting caught in a wrong search space. Simulations had been conducted to compare the proposed algorithm with the widely used pattern-search algorithm using criteria of convergence rate and optimized efficiency. Beam-steering optimization experiments had been performed to verify the validity of the proposed method.

Efficiency bounds of molecular motors under a trade-off figure of merit

NASA Astrophysics Data System (ADS)

Zhang, Yanchao; Huang, Chuankun; Lin, Guoxing; Chen, Jincan

2017-05-01

On the basis of the theory of irreversible thermodynamics and an elementary model of the molecular motors converting chemical energy by ATP hydrolysis to mechanical work exerted against an external force, the efficiencies of the molecular motors at two different optimization configurations for trade-off figure of merit representing a best compromise between the useful energy and the lost energy are calculated. The upper and lower bounds for the efficiency at two different optimization configurations are determined. It is found that the optimal efficiencies at the two different optimization configurations are always larger than 1 / 2.

Zone-boundary optimization for direct laser writing of continuous-relief diffractive optical elements.

PubMed

Korolkov, Victor P; Nasyrov, Ruslan K; Shimansky, Ruslan V

2006-01-01

Enhancing the diffraction efficiency of continuous-relief diffractive optical elements fabricated by direct laser writing is discussed. A new method of zone-boundary optimization is proposed to correct exposure data only in narrow areas along the boundaries of diffractive zones. The optimization decreases the loss of diffraction efficiency related to convolution of a desired phase profile with a writing-beam intensity distribution. A simplified stepped transition function that describes optimized exposure data near zone boundaries can be made universal for a wide range of zone periods. The approach permits a similar increase in the diffraction efficiency as an individual-pixel optimization but with fewer computation efforts. Computer simulations demonstrated that the zone-boundary optimization for a 6 microm period grating increases the efficiency by 7% and 14.5% for 0.6 microm and 1.65 microm writing-spot diameters, respectively. The diffraction efficiency of as much as 65%-90% for 4-10 microm zone periods was obtained experimentally with this method.

Framework for computationally efficient optimal irrigation scheduling using ant colony optimization

USDA-ARS?s Scientific Manuscript database

A general optimization framework is introduced with the overall goal of reducing search space size and increasing the computational efficiency of evolutionary algorithm application for optimal irrigation scheduling. The framework achieves this goal by representing the problem in the form of a decisi...

Optimal ciliary beating patterns

NASA Astrophysics Data System (ADS)

Vilfan, Andrej; Osterman, Natan

2011-11-01

We introduce a measure for energetic efficiency of single or collective biological cilia. We define the efficiency of a single cilium as Q2 / P , where Q is the volume flow rate of the pumped fluid and P is the dissipated power. For ciliary arrays, we define it as (ρQ) 2 / (ρP) , with ρ denoting the surface density of cilia. We then numerically determine the optimal beating patterns according to this criterion. For a single cilium optimization leads to curly, somewhat counterintuitive patterns. But when looking at a densely ciliated surface, the optimal patterns become remarkably similar to what is observed in microorganisms like Paramecium. The optimal beating pattern then consists of a fast effective stroke and a slow sweeping recovery stroke. Metachronal waves lead to a significantly higher efficiency than synchronous beating. Efficiency also increases with an increasing density of cilia up to the point where crowding becomes a problem. We finally relate the pumping efficiency of cilia to the swimming efficiency of a spherical microorganism and show that the experimentally estimated efficiency of Paramecium is surprisingly close to the theoretically possible optimum.

Rapid Optimization of External Quantum Efficiency of Thin Film Solar Cells Using Surrogate Modeling of Absorptivity.

PubMed

Kaya, Mine; Hajimirza, Shima

2018-05-25

This paper uses surrogate modeling for very fast design of thin film solar cells with improved solar-to-electricity conversion efficiency. We demonstrate that the wavelength-specific optical absorptivity of a thin film multi-layered amorphous-silicon-based solar cell can be modeled accurately with Neural Networks and can be efficiently approximated as a function of cell geometry and wavelength. Consequently, the external quantum efficiency can be computed by averaging surrogate absorption and carrier recombination contributions over the entire irradiance spectrum in an efficient way. Using this framework, we optimize a multi-layer structure consisting of ITO front coating, metallic back-reflector and oxide layers for achieving maximum efficiency. Our required computation time for an entire model fitting and optimization is 5 to 20 times less than the best previous optimization results based on direct Finite Difference Time Domain (FDTD) simulations, therefore proving the value of surrogate modeling. The resulting optimization solution suggests at least 50% improvement in the external quantum efficiency compared to bare silicon, and 25% improvement compared to a random design.

Biological optimization systems for enhancing photosynthetic efficiency and methods of use

DOEpatents

Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim

2012-11-06

Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.

Conditions for optimal efficiency of PCBM-based terahertz modulators

NASA Astrophysics Data System (ADS)

Yoo, Hyung Keun; Lee, Hanju; Lee, Kiejin; Kang, Chul; Kee, Chul-Sik; Hwang, In-Wook; Lee, Joong Wook

2017-10-01

We demonstrate the conditions for optimal modulation efficiency of active terahertz modulators based on phenyl-C61-butyric acid methyl ester (PCBM)-silicon hybrid structures. Highly efficient active control of the terahertz wave modulation was realized by controlling organic film thickness, annealing temperature, and laser excitation wavelength. Under the optimal conditions, the modulation efficiency reached nearly 100%. Charge distributions measured with a near-field scanning microwave microscanning technique corroborated the fact that the increase of photo-excited carriers due to the PCBM-silicon hybrid structure enables the enhancement of active modulation efficiency.

Fuel Injector Design Optimization for an Annular Scramjet Geometry

NASA Technical Reports Server (NTRS)

Steffen, Christopher J., Jr.

2003-01-01

A four-parameter, three-level, central composite experiment design has been used to optimize the configuration of an annular scramjet injector geometry using computational fluid dynamics. The computational fluid dynamic solutions played the role of computer experiments, and response surface methodology was used to capture the simulation results for mixing efficiency and total pressure recovery within the scramjet flowpath. An optimization procedure, based upon the response surface results of mixing efficiency, was used to compare the optimal design configuration against the target efficiency value of 92.5%. The results of three different optimization procedures are presented and all point to the need to look outside the current design space for different injector geometries that can meet or exceed the stated mixing efficiency target.

Overall Traveling-Wave-Tube Efficiency Improved By Optimized Multistage Depressed Collector Design

NASA Technical Reports Server (NTRS)

Vaden, Karl R.

2002-01-01

Depressed Collector Design The microwave traveling wave tube (TWT) is used widely for space communications and high-power airborne transmitting sources. One of the most important features in designing a TWT is overall efficiency. Yet, overall TWT efficiency is strongly dependent on the efficiency of the electron beam collector, particularly for high values of collector efficiency. For these reasons, the NASA Glenn Research Center developed an optimization algorithm based on simulated annealing to quickly design highly efficient multistage depressed collectors (MDC's). Simulated annealing is a strategy for solving highly nonlinear combinatorial optimization problems. Its major advantage over other methods is its ability to avoid becoming trapped in local minima. Simulated annealing is based on an analogy to statistical thermodynamics, specifically the physical process of annealing: heating a material to a temperature that permits many atomic rearrangements and then cooling it carefully and slowly, until it freezes into a strong, minimum-energy crystalline structure. This minimum energy crystal corresponds to the optimal solution of a mathematical optimization problem. The TWT used as a baseline for optimization was the 32-GHz, 10-W, helical TWT developed for the Cassini mission to Saturn. The method of collector analysis and design used was a 2-1/2-dimensional computational procedure that employs two types of codes, a large signal analysis code and an electron trajectory code. The large signal analysis code produces the spatial, energetic, and temporal distributions of the spent beam entering the MDC. An electron trajectory code uses the resultant data to perform the actual collector analysis. The MDC was optimized for maximum MDC efficiency and minimum final kinetic energy of all collected electrons (to reduce heat transfer). The preceding figure shows the geometric and electrical configuration of an optimized collector with an efficiency of 93.8 percent. The results show the improvement in collector efficiency from 89.7 to 93.8 percent, resulting in an increase of three overall efficiency points. In addition, the time to design a highly efficient MDC was reduced from a month to a few days. All work was done in-house at Glenn for the High Rate Data Delivery Program. Future plans include optimizing the MDC and TWT interaction circuit in tandem to further improve overall TWT efficiency.

Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh

Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

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

NASA Astrophysics Data System (ADS)

Huang, Yuechen; Li, Haiyang

2018-06-01

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

Optimal Learning for Efficient Experimentation in Nanotechnology and Biochemistry

DTIC Science & Technology

2015-12-22

AFRL-AFOSR-VA-TR-2016-0018 Optimal Learning for Efficient Experimentation in Nanotechnology , Biochemistry Warren Powell TRUSTEES OF PRINCETON...3. DATES COVERED (From - To) 01-07-2012 to 30-09-2015 4. TITLE AND SUBTITLE Optimal Learning for Efficient Experimentation in Nanotechnology and...in Nanotechnology and Biochemistry Principal Investigators: Warren B. Powell Princeton University Department of Operations Research and

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

PubMed Central

Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

2017-01-01

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

PubMed

Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue

2017-08-18

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

NASA Astrophysics Data System (ADS)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Maximizing the efficiency of multienzyme process by stoichiometry optimization.

PubMed

Dvorak, Pavel; Kurumbang, Nagendra P; Bendl, Jaroslav; Brezovsky, Jan; Prokop, Zbynek; Damborsky, Jiri

2014-09-05

Multienzyme processes represent an important area of biocatalysis. Their efficiency can be enhanced by optimization of the stoichiometry of the biocatalysts. Here we present a workflow for maximizing the efficiency of a three-enzyme system catalyzing a five-step chemical conversion. Kinetic models of pathways with wild-type or engineered enzymes were built, and the enzyme stoichiometry of each pathway was optimized. Mathematical modeling and one-pot multienzyme experiments provided detailed insights into pathway dynamics, enabled the selection of a suitable engineered enzyme, and afforded high efficiency while minimizing biocatalyst loadings. Optimizing the stoichiometry in a pathway with an engineered enzyme reduced the total biocatalyst load by an impressive 56 %. Our new workflow represents a broadly applicable strategy for optimizing multienzyme processes. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-rendezvous low-thrust trajectory optimization using costate transforming and homotopic approach

NASA Astrophysics Data System (ADS)

Chen, Shiyu; Li, Haiyang; Baoyin, Hexi

2018-06-01

This paper investigates a method for optimizing multi-rendezvous low-thrust trajectories using indirect methods. An efficient technique, labeled costate transforming, is proposed to optimize multiple trajectory legs simultaneously rather than optimizing each trajectory leg individually. Complex inner-point constraints and a large number of free variables are one main challenge in optimizing multi-leg transfers via shooting algorithms. Such a difficulty is reduced by first optimizing each trajectory leg individually. The results may be, next, utilized as an initial guess in the simultaneous optimization of multiple trajectory legs. In this paper, the limitations of similar techniques in previous research is surpassed and a homotopic approach is employed to improve the convergence efficiency of the shooting process in multi-rendezvous low-thrust trajectory optimization. Numerical examples demonstrate that newly introduced techniques are valid and efficient.

Five-Junction Solar Cell Optimization Using Silvaco Atlas

DTIC Science & Technology

2017-09-01

experimental sources [1], [4], [6]. f. Numerical Method The method selected for solving the non -linear equations that make up the simulation can be...and maximize efficiency. Optimization of solar cell efficiency is carried out via nearly orthogonal balanced design of experiments methodology . Silvaco...Optimization of solar cell efficiency is carried out via nearly orthogonal balanced design of experiments methodology . Silvaco ATLAS is utilized to

Performance Limits of Non-Line-of-Sight Optical Communications

DTIC Science & Technology

2015-05-01

high efficiency solar blind photo detectors. In this project, we address the main challenges towards optimizing the UV communication system...LEDs), solar blind filters, and high efficiency solar blind photo detectors. In this project, we address the main challenges towards optimizing the UV...solar blind filters, and high efficiency solar blind photo detectors. In this project, we address the main challenges towards optimizing the UV

Energy-saving management modelling and optimization for lead-acid battery formation process

NASA Astrophysics Data System (ADS)

Wang, T.; Chen, Z.; Xu, J. Y.; Wang, F. Y.; Liu, H. M.

2017-11-01

In this context, a typical lead-acid battery producing process is introduced. Based on the formation process, an efficiency management method is proposed. An optimization model with the objective to minimize the formation electricity cost in a single period is established. This optimization model considers several related constraints, together with two influencing factors including the transformation efficiency of IGBT charge-and-discharge machine and the time-of-use price. An example simulation is shown using PSO algorithm to solve this mathematic model, and the proposed optimization strategy is proved to be effective and learnable for energy-saving and efficiency optimization in battery producing industries.

Optimization of the multi-turn injection efficiency for a medical synchrotron

NASA Astrophysics Data System (ADS)

Kim, J.; Yoon, M.; Yim, H.

2016-09-01

We present a method for optimizing the multi-turn injection efficiency for a medical synchrotron. We show that for a given injection energy, the injection efficiency can be greatly enhanced by choosing transverse tunes appropriately and by optimizing the injection bump and the number of turns required for beam injection. We verify our study by applying the method to the Korea Heavy Ion Medical Accelerator (KHIMA) synchrotron which is currently being built at the campus of Dongnam Institute of Radiological and Medical Sciences (DIRAMS) in Busan, Korea. First the frequency map analysis was performed with the help of the ELEGANT and the ACCSIM codes. The tunes that yielded good injection efficiency were then selected. With these tunes, the injection bump and the number of turns required for injection were then optimized by tracking a number of particles for up to one thousand turns after injection, beyond which no further beam loss occurred. Results for the optimization of the injection efficiency for proton ions are presented.

Methodology for the optimal design of an integrated first and second generation ethanol production plant combined with power cogeneration.

PubMed

Bechara, Rami; Gomez, Adrien; Saint-Antonin, Valérie; Schweitzer, Jean-Marc; Maréchal, François

2016-08-01

The application of methodologies for the optimal design of integrated processes has seen increased interest in literature. This article builds on previous works and applies a systematic methodology to an integrated first and second generation ethanol production plant with power cogeneration. The methodology breaks into process simulation, heat integration, thermo-economic evaluation, exergy efficiency vs. capital costs, multi-variable, evolutionary optimization, and process selection via profitability maximization. Optimization generated Pareto solutions with exergy efficiency ranging between 39.2% and 44.4% and capital costs from 210M$ to 390M$. The Net Present Value was positive for only two scenarios and for low efficiency, low hydrolysis points. The minimum cellulosic ethanol selling price was sought to obtain a maximum NPV of zero for high efficiency, high hydrolysis alternatives. The obtained optimal configuration presented maximum exergy efficiency, hydrolyzed bagasse fraction, capital costs and ethanol production rate, and minimum cooling water consumption and power production rate. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization on the impeller of a low-specific-speed centrifugal pump for hydraulic performance improvement

NASA Astrophysics Data System (ADS)

Pei, Ji; Wang, Wenjie; Yuan, Shouqi; Zhang, Jinfeng

2016-09-01

In order to widen the high-efficiency operating range of a low-specific-speed centrifugal pump, an optimization process for considering efficiencies under 1.0 Q d and 1.4 Q d is proposed. Three parameters, namely, the blade outlet width b 2, blade outlet angle β 2, and blade wrap angle φ, are selected as design variables. Impellers are generated using the optimal Latin hypercube sampling method. The pump efficiencies are calculated using the software CFX 14.5 at two operating points selected as objectives. Surrogate models are also constructed to analyze the relationship between the objectives and the design variables. Finally, the particle swarm optimization algorithm is applied to calculate the surrogate model to determine the best combination of the impeller parameters. The results show that the performance curve predicted by numerical simulation has a good agreement with the experimental results. Compared with the efficiencies of the original impeller, the hydraulic efficiencies of the optimized impeller are increased by 4.18% and 0.62% under 1.0 Q d and 1.4Qd, respectively. The comparison of inner flow between the original pump and optimized one illustrates the improvement of performance. The optimization process can provide a useful reference on performance improvement of other pumps, even on reduction of pressure fluctuations.

Displacement Based Multilevel Structural Optimization

NASA Technical Reports Server (NTRS)

Sobieszezanski-Sobieski, J.; Striz, A. G.

1996-01-01

In the complex environment of true multidisciplinary design optimization (MDO), efficiency is one of the most desirable attributes of any approach. In the present research, a new and highly efficient methodology for the MDO subset of structural optimization is proposed and detailed, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures is performed. In the system level optimization, the design variables are the coefficients of assumed polynomially based global displacement functions, and the load unbalance resulting from the solution of the global stiffness equations is minimized. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. The approach is expected to prove very efficient since the design task is broken down into a large number of small and efficient subtasks, each with a small number of variables, which are amenable to parallel computing.

Optimization of Dish Solar Collectors with and without Secondary Concentrators

NASA Technical Reports Server (NTRS)

Jaffe, L. D.

1982-01-01

Methods for optimizing parabolic dish solar collectors and the consequent effects of various optical, thermal, mechanical, and cost variables are examined. The most important performance optimization is adjusting the receiver aperture to maximize collector efficiency. Other parameters that can be adjusted to optimize efficiency include focal length, and, if a heat engine is used, the receiver temperature. The efficiency maxima associated with focal length and receiver temperature are relatively broad; it may, accordingly, be desirable to design somewhat away from the maxima. Performance optimization is sensitive to the slope and specularity errors of the concentrator. Other optical and thermal variables affecting optimization are the reflectance and blocking factor of the concentrator, the absorptance and losses of the receiver, and, if a heat engine is used, the shape of the engine efficiency versus temperature curve. Performance may sometimes be improved by use of an additional optical element (a secondary concentrator) or a receiver window if the errors of the primary concentrator are large or the receiver temperature is high.

A Method to Determine Supply Voltage of Permanent Magnet Motor at Optimal Design Stage

NASA Astrophysics Data System (ADS)

Matustomo, Shinya; Noguchi, So; Yamashita, Hideo; Tanimoto, Shigeya

The permanent magnet motors (PM motors) are widely used in electrical machinery, such as air conditioner, refrigerator and so on. In recent years, from the point of view of energy saving, it is necessary to improve the efficiency of PM motor by optimization. However, in the efficiency optimization of PM motor, many design variables and many restrictions are required. In this paper, the efficiency optimization of PM motor with many design variables was performed by using the voltage driven finite element analysis with the rotating simulation of the motor and the genetic algorithm.

The effect of dropout on the efficiency of D-optimal designs of linear mixed models.

PubMed

Ortega-Azurduy, S A; Tan, F E S; Berger, M P F

2008-06-30

Dropout is often encountered in longitudinal data. Optimal designs will usually not remain optimal in the presence of dropout. In this paper, we study D-optimal designs for linear mixed models where dropout is encountered. Moreover, we estimate the efficiency loss in cases where a D-optimal design for complete data is chosen instead of that for data with dropout. Two types of monotonically decreasing response probability functions are investigated to describe dropout. Our results show that the location of D-optimal design points for the dropout case will shift with respect to that for the complete and uncorrelated data case. Owing to this shift, the information collected at the D-optimal design points for the complete data case does not correspond to the smallest variance. We show that the size of the displacement of the time points depends on the linear mixed model and that the efficiency loss is moderate.

Optimal control, optimization and asymptotic analysis of Purcell's microswimmer model

NASA Astrophysics Data System (ADS)

Wiezel, Oren; Or, Yizhar

2016-11-01

Purcell's swimmer (1977) is a classic model of a three-link microswimmer that moves by performing periodic shape changes. Becker et al. (2003) showed that the swimmer's direction of net motion is reversed upon increasing the stroke amplitude of joint angles. Tam and Hosoi (2007) used numerical optimization in order to find optimal gaits for maximizing either net displacement or Lighthill's energetic efficiency. In our work, we analytically derive leading-order expressions as well as next-order corrections for both net displacement and energetic efficiency of Purcell's microswimmer. Using these expressions enables us to explicitly show the reversal in direction of motion, as well as obtaining an estimate for the optimal stroke amplitude. We also find the optimal swimmer's geometry for maximizing either displacement or energetic efficiency. Additionally, the gait optimization problem is revisited and analytically formulated as an optimal control system with only two state variables, which can be solved using Pontryagin's maximum principle. It can be shown that the optimal solution must follow a "singular arc". Numerical solution of the boundary value problem is obtained, which exactly reproduces Tam and Hosoi's optimal gait.

Carbon and nutrient use efficiencies optimally balance stoichiometric imbalances

NASA Astrophysics Data System (ADS)

Manzoni, Stefano; Čapek, Petr; Lindahl, Björn; Mooshammer, Maria; Richter, Andreas; Šantrůčková, Hana

2016-04-01

Decomposer organisms face large stoichiometric imbalances because their food is generally poor in nutrients compared to the decomposer cellular composition. The presence of excess carbon (C) requires adaptations to utilize nutrients effectively while disposing of or investing excess C. As food composition changes, these adaptations lead to variable C- and nutrient-use efficiencies (defined as the ratios of C and nutrients used for growth over the amounts consumed). For organisms to be ecologically competitive, these changes in efficiencies with resource stoichiometry have to balance advantages and disadvantages in an optimal way. We hypothesize that efficiencies are varied so that community growth rate is optimized along stoichiometric gradients of their resources. Building from previous theories, we predict that maximum growth is achieved when C and nutrients are co-limiting, so that the maximum C-use efficiency is reached, and nutrient release is minimized. This optimality principle is expected to be applicable across terrestrial-aquatic borders, to various elements, and at different trophic levels. While the growth rate maximization hypothesis has been evaluated for consumers and predators, in this contribution we test it for terrestrial and aquatic decomposers degrading resources across wide stoichiometry gradients. The optimality hypothesis predicts constant efficiencies at low substrate C:N and C:P, whereas above a stoichiometric threshold, C-use efficiency declines and nitrogen- and phosphorus-use efficiencies increase up to one. Thus, high resource C:N and C:P lead to low C-use efficiency, but effective retention of nitrogen and phosphorus. Predictions are broadly consistent with efficiency trends in decomposer communities across terrestrial and aquatic ecosystems.

FUZZY-LOGIC-BASED CONTROLLERS FOR EFFICIENCY OPTIMIZATION OF INVERTER-FED INDUCTION MOTOR DRIVES

EPA Science Inventory

This paper describes a fuzzy-logic-based energy optimizing controller to improve the efficiency of induction motor/drives operating at various load (torque) and speed conditions. Improvement of induction motor efficiency is important not only from the considerations of energy sav...

Publications | Grid Modernization | NREL

Science.gov Websites

Photovoltaics: Trajectories and Challenges Cover of Efficient Relaxations for Joint Chance Constrained AC Optimal Power Flow publication Efficient Relaxations for Joint Chance Constrained AC Optimal Power Flow

A logical approach to optimize the nanostructured lipid carrier system of irinotecan: efficient hybrid design methodology

NASA Astrophysics Data System (ADS)

Mohan Negi, Lalit; Jaggi, Manu; Talegaonkar, Sushama

2013-01-01

Development of an effective formulation involves careful optimization of a number of excipient and process variables. Sometimes the number of variables is so large that even the most efficient optimization designs require a very large number of trials which put stress on costs as well as time. A creative combination of a number of design methods leads to a smaller number of trials. This study was aimed at the development of nanostructured lipid carriers (NLCs) by using a combination of different optimization methods. A total of 11 variables were first screened using the Plackett-Burman design for their effects on formulation characteristics like size and entrapment efficiency. Four out of 11 variables were found to have insignificant effects on the formulation parameters and hence were screened out. Out of the remaining seven variables, four (concentration of tween-80, lecithin, sodium taurocholate, and total lipid) were found to have significant effects on the size of the particles while the other three (phase ratio, drug to lipid ratio, and sonication time) had a higher influence on the entrapment efficiency. The first four variables were optimized for their effect on size using the Taguchi L9 orthogonal array. The optimized values of the surfactants and lipids were kept constant for the next stage, where the sonication time, phase ratio, and drug:lipid ratio were varied using the Box-Behnken design response surface method to optimize the entrapment efficiency. Finally, by performing only 38 trials, we have optimized 11 variables for the development of NLCs with a size of 143.52 ± 1.2 nm, zeta potential of -32.6 ± 0.54 mV, and 98.22 ± 2.06% entrapment efficiency.

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.

Efficiency of quantum vs. classical annealing in nonconvex learning problems

PubMed Central

Zecchina, Riccardo

2018-01-01

Quantum annealers aim at solving nonconvex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists of designing a classical energy function whose ground states are the sought optimal solutions of the original optimization problem and add a controllable quantum transverse field to generate tunneling processes. A key challenge is to identify classes of nonconvex optimization problems for which quantum annealing remains efficient while thermal annealing fails. We show that this happens for a wide class of problems which are central to machine learning. Their energy landscapes are dominated by local minima that cause exponential slowdown of classical thermal annealers while simulated quantum annealing converges efficiently to rare dense regions of optimal solutions. PMID:29382764

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Optimal auxiliary-covariate-based two-phase sampling design for semiparametric efficient estimation of a mean or mean difference, with application to clinical trials.

PubMed

Gilbert, Peter B; Yu, Xuesong; Rotnitzky, Andrea

2014-03-15

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method. Copyright © 2013 John Wiley & Sons, Ltd.

Optimal Auxiliary-Covariate Based Two-Phase Sampling Design for Semiparametric Efficient Estimation of a Mean or Mean Difference, with Application to Clinical Trials

PubMed Central

Gilbert, Peter B.; Yu, Xuesong; Rotnitzky, Andrea

2014-01-01

To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semi-parametric efficient estimator is applied. This approach is made efficient by specifying the phase-two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. Simulations are performed to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. Proofs and R code are provided. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean “importance-weighted” breadth (Y) of the T cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y, and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24% in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y∣W] is important for realizing the efficiency gain, which is aided by an ample phase-two sample and by using a robust fitting method. PMID:24123289

Topology-optimized broadband surface relief transmission grating

NASA Astrophysics Data System (ADS)

Andkjær, Jacob; Ryder, Christian P.; Nielsen, Peter C.; Rasmussen, Thomas; Buchwald, Kristian; Sigmund, Ole

2014-03-01

We propose a design methodology for systematic design of surface relief transmission gratings with optimized diffraction efficiency. The methodology is based on a gradient-based topology optimization formulation along with 2D frequency domain finite element simulations for TE and TM polarized plane waves. The goal of the optimization is to find a grating design that maximizes diffraction efficiency for the -1st transmission order when illuminated by unpolarized plane waves. Results indicate that a surface relief transmission grating can be designed with a diffraction efficiency of more than 40% in a broadband range going from the ultraviolet region, through the visible region and into the near-infrared region.

Modeling and optimal designs for dislocation and radiation tolerant single and multijunction solar cells

NASA Astrophysics Data System (ADS)

Mehrotra, A.; Alemu, A.; Freundlich, A.

2011-02-01

Crystalline defects (e.g. dislocations or grain boundaries) as well as electron and proton induced defects cause reduction of minority carrier diffusion length which in turn results in degradation of efficiency of solar cells. Hetro-epitaxial or metamorphic III-V devices with low dislocation density have high BOL efficiencies but electron-proton radiation causes degradation in EOL efficiencies. By optimizing the device design (emitter-base thickness, doping) we can obtain highly dislocated metamorphic devices that are radiation resistant. Here we have modeled III-V single and multi junction solar cells using drift and diffusion equations considering experimental III-V material parameters, dislocation density, 1 Mev equivalent electron radiation doses, thicknesses and doping concentration. Thinner device thickness leads to increment in EOL efficiency of high dislocation density solar cells. By optimizing device design we can obtain nearly same EOL efficiencies from high dislocation solar cells than from defect free III-V multijunction solar cells. As example defect free GaAs solar cell after optimization gives 11.2% EOL efficiency (under typical 5x1015cm-2 1 MeV electron fluence) while a GaAs solar cell with high dislocation density (108 cm-2) after optimization gives 10.6% EOL efficiency. The approach provides an additional degree of freedom in the design of high efficiency space cells and could in turn be used to relax the need for thick defect filtering buffer in metamorphic devices.

Traveling-Wave Tube Efficiency Enhancement

NASA Technical Reports Server (NTRS)

Dayton, James A., Jr.

2011-01-01

Traveling-wave tubes (TWT's) are used to amplify microwave communication signals on virtually all NASA and commercial spacecraft. Because TWT's are a primary power user, increasing their power efficiency is important for reducing spacecraft weight and cost. NASA Glenn Research Center has played a major role in increasing TWT efficiency over the last thirty years. In particular, two types of efficiency optimization algorithms have been developed for coupled-cavity TWT's. The first is the phase-adjusted taper which was used to increase the RF power from 420 to 1000 watts and the RF efficiency from 9.6% to 22.6% for a Ka-band (29.5 GHz) TWT. This was a record efficiency at this frequency level. The second is an optimization algorithm based on simulated annealing. This improved algorithm is more general and can be used to optimize efficiency over a frequency bandwidth and to provide a robust design for very high frequency TWT's in which dimensional tolerance variations are significant.

Use of plan quality degradation to evaluate tradeoffs in delivery efficiency and clinical plan metrics arising from IMRT optimizer and sequencer compromises

PubMed Central

Wilkie, Joel R.; Matuszak, Martha M.; Feng, Mary; Moran, Jean M.; Fraass, Benedick A.

2013-01-01

Purpose: Plan degradation resulting from compromises made to enhance delivery efficiency is an important consideration for intensity modulated radiation therapy (IMRT) treatment plans. IMRT optimization and/or multileaf collimator (MLC) sequencing schemes can be modified to generate more efficient treatment delivery, but the effect those modifications have on plan quality is often difficult to quantify. In this work, the authors present a method for quantitative assessment of overall plan quality degradation due to tradeoffs between delivery efficiency and treatment plan quality, illustrated using comparisons between plans developed allowing different numbers of intensity levels in IMRT optimization and/or MLC sequencing for static segmental MLC IMRT plans. Methods: A plan quality degradation method to evaluate delivery efficiency and plan quality tradeoffs was developed and used to assess planning for 14 prostate and 12 head and neck patients treated with static IMRT. Plan quality was evaluated using a physician's predetermined “quality degradation” factors for relevant clinical plan metrics associated with the plan optimization strategy. Delivery efficiency and plan quality were assessed for a range of optimization and sequencing limitations. The “optimal” (baseline) plan for each case was derived using a clinical cost function with an unlimited number of intensity levels. These plans were sequenced with a clinical MLC leaf sequencer which uses >100 segments, assuring delivered intensities to be within 1% of the optimized intensity pattern. Each patient's optimal plan was also sequenced limiting the number of intensity levels (20, 10, and 5), and then separately optimized with these same numbers of intensity levels. Delivery time was measured for all plans, and direct evaluation of the tradeoffs between delivery time and plan degradation was performed. Results: When considering tradeoffs, the optimal number of intensity levels depends on the treatment site and on the stage in the process at which the levels are limited. The cost of improved delivery efficiency, in terms of plan quality degradation, increased as the number of intensity levels in the sequencer or optimizer decreased. The degradation was more substantial for the head and neck cases relative to the prostate cases, particularly when fewer than 20 intensity levels were used. Plan quality degradation was less severe when the number of intensity levels was limited in the optimizer rather than the sequencer. Conclusions: Analysis of plan quality degradation allows for a quantitative assessment of the compromises in clinical plan quality as delivery efficiency is improved, in order to determine the optimal delivery settings. The technique is based on physician-determined quality degradation factors and can be extended to other clinical situations where investigation of various tradeoffs is warranted. PMID:23822412

Improvement of energy efficiency via spectrum optimization of excitation sequence for multichannel simultaneously triggered airborne sonar system

NASA Astrophysics Data System (ADS)

Meng, Qing-Hao; Yao, Zhen-Jing; Peng, Han-Yang

2009-12-01

Both the energy efficiency and correlation characteristics are important in airborne sonar systems to realize multichannel ultrasonic transducers working together. High energy efficiency can increase echo energy and measurement range, and sharp autocorrelation and flat cross correlation can help eliminate cross-talk among multichannel transducers. This paper addresses energy efficiency optimization under the premise that cross-talk between different sonar transducers can be avoided. The nondominated sorting genetic algorithm-II is applied to optimize both the spectrum and correlation characteristics of the excitation sequence. The central idea of the spectrum optimization is to distribute most of the energy of the excitation sequence within the frequency band of the sonar transducer; thus, less energy is filtered out by the transducers. Real experiments show that a sonar system consisting of eight-channel Polaroid 600 series electrostatic transducers excited with 2 ms optimized pulse-position-modulation sequences can work together without cross-talk and can measure distances up to 650 cm with maximal 1% relative error.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks.

PubMed

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-10-09

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

PubMed Central

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-01-01

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. PMID:28991200

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Seeding the initial population with feasible solutions in metaheuristic optimization of steel trusses

NASA Astrophysics Data System (ADS)

Kazemzadeh Azad, Saeid

2018-01-01

In spite of considerable research work on the development of efficient algorithms for discrete sizing optimization of steel truss structures, only a few studies have addressed non-algorithmic issues affecting the general performance of algorithms. For instance, an important question is whether starting the design optimization from a feasible solution is fruitful or not. This study is an attempt to investigate the effect of seeding the initial population with feasible solutions on the general performance of metaheuristic techniques. To this end, the sensitivity of recently proposed metaheuristic algorithms to the feasibility of initial candidate designs is evaluated through practical discrete sizing of real-size steel truss structures. The numerical experiments indicate that seeding the initial population with feasible solutions can improve the computational efficiency of metaheuristic structural optimization algorithms, especially in the early stages of the optimization. This paves the way for efficient metaheuristic optimization of large-scale structural systems.

Optimization of single photon detection model based on GM-APD

NASA Astrophysics Data System (ADS)

Chen, Yu; Yang, Yi; Hao, Peiyu

2017-11-01

One hundred kilometers high precision laser ranging hopes the detector has very strong detection ability for very weak light. At present, Geiger-Mode of Avalanche Photodiode has more use. It has high sensitivity and high photoelectric conversion efficiency. Selecting and designing the detector parameters according to the system index is of great importance to the improvement of photon detection efficiency. Design optimization requires a good model. In this paper, we research the existing Poisson distribution model, and consider the important detector parameters of dark count rate, dead time, quantum efficiency and so on. We improve the optimization of detection model, select the appropriate parameters to achieve optimal photon detection efficiency. The simulation is carried out by using Matlab and compared with the actual test results. The rationality of the model is verified. It has certain reference value in engineering applications.

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

NASA Astrophysics Data System (ADS)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

Optimization of blade motion of vertical axis turbine

NASA Astrophysics Data System (ADS)

Ma, Yong; Zhang, Liang; Zhang, Zhi-yang; Han, Duan-feng

2016-04-01

In this paper, a method is proposed to improve the energy efficiency of the vertical axis turbine. First of all, a single disk multiple stream-tube model is used to calculate individual fitness. Genetic algorithm is adopted to optimize blade pitch motion of vertical axis turbine with the maximum energy efficiency being selected as the optimization objective. Then, a particular data processing method is proposed, fitting the result data into a cosine-like curve. After that, a general formula calculating the blade motion is developed. Finally, CFD simulation is used to validate the blade pitch motion formula. The results show that the turbine's energy efficiency becomes higher after the optimization of blade pitch motion; compared with the fixed pitch turbine, the efficiency of variable-pitch turbine is significantly improved by the active blade pitch control; the energy efficiency declines gradually with the growth of speed ratio; besides, compactness has lager effect on the blade motion while the number of blades has little effect on it.

A Simulated Annealing Algorithm for the Optimization of Multistage Depressed Collector Efficiency

NASA Technical Reports Server (NTRS)

Vaden, Karl R.; Wilson, Jeffrey D.; Bulson, Brian A.

2002-01-01

The microwave traveling wave tube amplifier (TWTA) is widely used as a high-power transmitting source for space and airborne communications. One critical factor in designing a TWTA is the overall efficiency. However, overall efficiency is highly dependent upon collector efficiency; so collector design is critical to the performance of a TWTA. Therefore, NASA Glenn Research Center has developed an optimization algorithm based on Simulated Annealing to quickly design highly efficient multi-stage depressed collectors (MDC).

Econophysics and bio-chemical engineering thermodynamics: The exergetic analysis of a municipality

NASA Astrophysics Data System (ADS)

Lucia, Umberto

2016-11-01

Exergy is a fundamental quantity because it allows us to obtain information on the useful work obtainable in a process. The analyses of irreversibility are important not only in the design and development of the industrial devices, but also in fundamental thermodynamics and in the socio-economic analysis of municipality. Consequently, the link between entropy and exergy is discussed in order to link econophysics to the bio-chemical engineering thermodynamics. Last, this link holds to the fundamental role of fluxes and to the exergy exchanged in the interaction between the system and its environment. The result consists in a thermodynamic approach to the analysis of the unavailability of the economic, productive or social systems. The unavailability is what the system cannot use in relation to its internal processes. This quantity result is interesting also as a support to public manager for economic decisions. Here, the Alessandria Municipality is analyzed in order to highlight the application of the theoretical results.

Waste-to-energy: A review of life cycle assessment and its extension methods.

PubMed

Zhou, Zhaozhi; Tang, Yuanjun; Chi, Yong; Ni, Mingjiang; Buekens, Alfons

2018-01-01

This article proposes a comprehensive review of evaluation tools based on life cycle thinking, as applied to waste-to-energy. Habitually, life cycle assessment is adopted to assess environmental burdens associated with waste-to-energy initiatives. Based on this framework, several extension methods have been developed to focus on specific aspects: Exergetic life cycle assessment for reducing resource depletion, life cycle costing for evaluating its economic burden, and social life cycle assessment for recording its social impacts. Additionally, the environment-energy-economy model integrates both life cycle assessment and life cycle costing methods and judges simultaneously these three features for sustainable waste-to-energy conversion. Life cycle assessment is sufficiently developed on waste-to-energy with concrete data inventory and sensitivity analysis, although the data and model uncertainty are unavoidable. Compared with life cycle assessment, only a few evaluations are conducted to waste-to-energy techniques by using extension methods and its methodology and application need to be further developed. Finally, this article succinctly summarises some recommendations for further research.

Optimization methods and silicon solar cell numerical models

NASA Technical Reports Server (NTRS)

Girardini, K.

1986-01-01

The goal of this project is the development of an optimization algorithm for use with a solar cell model. It is possible to simultaneously vary design variables such as impurity concentrations, front junction depth, back junctions depth, and cell thickness to maximize the predicted cell efficiency. An optimization algorithm has been developed and interfaced with the Solar Cell Analysis Program in 1 Dimension (SCAPID). SCAPID uses finite difference methods to solve the differential equations which, along with several relations from the physics of semiconductors, describe mathematically the operation of a solar cell. A major obstacle is that the numerical methods used in SCAPID require a significant amount of computer time, and during an optimization the model is called iteratively until the design variables converge to the value associated with the maximum efficiency. This problem has been alleviated by designing an optimization code specifically for use with numerically intensive simulations, to reduce the number of times the efficiency has to be calculated to achieve convergence to the optimal solution. Adapting SCAPID so that it could be called iteratively by the optimization code provided another means of reducing the cpu time required to complete an optimization. Instead of calculating the entire I-V curve, as is usually done in SCAPID, only the efficiency is calculated (maximum power voltage and current) and the solution from previous calculations is used to initiate the next solution.

Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

NASA Astrophysics Data System (ADS)

Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

2017-06-01

In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

On the use of controls for subsonic transport performance improvement: Overview and future directions

NASA Technical Reports Server (NTRS)

Gilyard, Glenn; Espana, Martin

1994-01-01

Increasing competition among airline manufacturers and operators has highlighted the issue of aircraft efficiency. Fewer aircraft orders have led to an all-out efficiency improvement effort among the manufacturers to maintain if not increase their share of the shrinking number of aircraft sales. Aircraft efficiency is important in airline profitability and is key if fuel prices increase from their current low. In a continuing effort to improve aircraft efficiency and develop an optimal performance technology base, NASA Dryden Flight Research Center developed and flight tested an adaptive performance seeking control system to optimize the quasi-steady-state performance of the F-15 aircraft. The demonstrated technology is equally applicable to transport aircraft although with less improvement. NASA Dryden, in transitioning this technology to transport aircraft, is specifically exploring the feasibility of applying adaptive optimal control techniques to performance optimization of redundant control effectors. A simulation evaluation of a preliminary control law optimizes wing-aileron camber for minimum net aircraft drag. Two submodes are evaluated: one to minimize fuel and the other to maximize velocity. This paper covers the status of performance optimization of the current fleet of subsonic transports. Available integrated controls technologies are reviewed to define approaches using active controls. A candidate control law for adaptive performance optimization is presented along with examples of algorithm operation.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Optimization of segmented thermoelectric generator using Taguchi and ANOVA techniques.

PubMed

Kishore, Ravi Anant; Sanghadasa, Mohan; Priya, Shashank

2017-12-01

Recent studies have demonstrated that segmented thermoelectric generators (TEGs) can operate over large thermal gradient and thus provide better performance (reported efficiency up to 11%) as compared to traditional TEGs, comprising of single thermoelectric (TE) material. However, segmented TEGs are still in early stages of development due to the inherent complexity in their design optimization and manufacturability. In this study, we demonstrate physics based numerical techniques along with Analysis of variance (ANOVA) and Taguchi optimization method for optimizing the performance of segmented TEGs. We have considered comprehensive set of design parameters, such as geometrical dimensions of p-n legs, height of segmentation, hot-side temperature, and load resistance, in order to optimize output power and efficiency of segmented TEGs. Using the state-of-the-art TE material properties and appropriate statistical tools, we provide near-optimum TEG configuration with only 25 experiments as compared to 3125 experiments needed by the conventional optimization methods. The effect of environmental factors on the optimization of segmented TEGs is also studied. Taguchi results are validated against the results obtained using traditional full factorial optimization technique and a TEG configuration for simultaneous optimization of power and efficiency is obtained.

Optimization of insulation of a linear Fresnel collector

NASA Astrophysics Data System (ADS)

Ardekani, Mohammad Moghimi; Craig, Ken J.; Meyer, Josua P.

2017-06-01

This study presents a simulation based optimization study of insulation around the cavity receiver of a Linear Fresnel Collector. This optimization study focuses on minimizing heat losses from a cavity receiver (maximizing plant thermal efficiency), while minimizing insulation cross-sectional area (minimizing material cost and cavity dead load), which leads to a cheaper and thermally more efficient LFC cavity receiver.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

An efficiency study of the simultaneous analysis and design of structures

NASA Technical Reports Server (NTRS)

Striz, Alfred G.; Wu, Zhiqi; Sobieski, Jaroslaw

1995-01-01

The efficiency of the Simultaneous Analysis and Design (SAND) approach in the minimum weight optimization of structural systems subject to strength and displacement constraints as well as size side constraints is investigated. SAND allows for an optimization to take place in one single operation as opposed to the more traditional and sequential Nested Analysis and Design (NAND) method, where analyses and optimizations alternate. Thus, SAND has the advantage that the stiffness matrix is never factored during the optimization retaining its original sparsity. One of SAND's disadvantages is the increase in the number of design variables and in the associated number of constraint gradient evaluations. If SAND is to be an acceptable player in the optimization field, it is essential to investigate the efficiency of the method and to present a possible cure for any inherent deficiencies.

Improving Efficiency of Passive RFID Tag Anti-Collision Protocol Using Dynamic Frame Adjustment and Optimal Splitting.

PubMed

Memon, Muhammad Qasim; He, Jingsha; Yasir, Mirza Ammar; Memon, Aasma

2018-04-12

Radio frequency identification is a wireless communication technology, which enables data gathering and identifies recognition from any tagged object. The number of collisions produced during wireless communication would lead to a variety of problems including unwanted number of iterations and reader-induced idle slots, computational complexity in terms of estimation as well as recognition of the number of tags. In this work, dynamic frame adjustment and optimal splitting are employed together in the proposed algorithm. In the dynamic frame adjustment method, the length of frames is based on the quantity of tags to yield optimal efficiency. The optimal splitting method is conceived with smaller duration of idle slots using an optimal value for splitting level M o p t , where (M > 2), to vary slot sizes to get the minimal identification time for the idle slots. The application of the proposed algorithm offers the advantages of not going for the cumbersome estimation of the quantity of tags incurred and the size (number) of tags has no effect on its performance efficiency. Our experiment results show that using the proposed algorithm, the efficiency curve remains constant as the number of tags varies from 50 to 450, resulting in an overall theoretical gain in the efficiency of 0.032 compared to system efficiency of 0.441 and thus outperforming both dynamic binary tree slotted ALOHA (DBTSA) and binary splitting protocols.

Efficiency optimization in a correlation ratchet with asymmetric unbiased fluctuations

NASA Astrophysics Data System (ADS)

Ai, Bao-Quan; Wang, Xian-Ju; Liu, Guo-Tao; Wen, De-Hua; Xie, Hui-Zhang; Chen, Wei; Liu, Liang-Gang

2003-12-01

The efficiency of a Brownian particle moving in a periodic potential in the presence of asymmetric unbiased fluctuations is investigated. We found that even on the quasistatic limit there is a regime where the efficiency can be a peaked function of temperature, which proves that thermal fluctuations facilitate the efficiency of energy transformation, contradicting the earlier findings [H. Kamegawa et al., Phys. Rev. Lett. 80, 5251 (1998)]. It is also found that the mutual interplay between temporal asymmetry and spatial asymmetry may induce optimized efficiency at finite temperatures. The ratchet is not most efficient when it gives maximum current.

Enhanced Ungual Permeation of Terbinafine HCl Delivered Through Liposome-Loaded Nail Lacquer Formulation Optimized by QbD Approach.

PubMed

Shah, Viral H; Jobanputra, Amee

2018-01-01

The present investigation focused on developing, optimizing, and evaluating a novel liposome-loaded nail lacquer formulation for increasing the transungual permeation flux of terbinafine HCl for efficient treatment of onychomycosis. A three-factor, three-level, Box-Behnken design was employed for optimizing process and formulation parameters of liposomal formulation. Liposomes were formulated by thin film hydration technique followed by sonication. Drug to lipid ratio, sonication amplitude, and sonication time were screened as independent variables while particle size, PDI, entrapment efficiency, and zeta potential were selected as quality attributes for liposomal formulation. Multiple regression analysis was employed to construct a second-order quadratic polynomial equation and contour plots. Design space (overlay plot) was generated to optimize a liposomal system, with software-suggested levels of independent variables that could be transformed to desired responses. The optimized liposome formulation was characterized and dispersed in nail lacquer which was further evaluated for different parameters. Results depicted that the optimized terbinafine HCl-loaded liposome formulation exhibited particle size of 182 nm, PDI of 0.175, zeta potential of -26.8 mV, and entrapment efficiency of 80%. Transungual permeability flux of terbinafine HCl through liposome-dispersed nail lacquer formulation was observed to be significantly higher in comparison to nail lacquer with a permeation enhancer. The developed formulation was also observed to be as efficient as pure drug dispersion in its antifungal activity. Thus, it was concluded that the developed formulation can serve as an efficient tool for enhancing the permeability of terbinafine HCl across human nail plate thereby improving its therapeutic efficiency.

Power and Efficiency Optimized in Traveling-Wave Tubes Over a Broad Frequency Bandwidth

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.

2001-01-01

A traveling-wave tube (TWT) is an electron beam device that is used to amplify electromagnetic communication waves at radio and microwave frequencies. TWT's are critical components in deep space probes, communication satellites, and high-power radar systems. Power conversion efficiency is of paramount importance for TWT's employed in deep space probes and communication satellites. A previous effort was very successful in increasing efficiency and power at a single frequency (ref. 1). Such an algorithm is sufficient for narrow bandwidth designs, but for optimal designs in applications that require high radiofrequency power over a wide bandwidth, such as high-density communications or high-resolution radar, the variation of the circuit response with respect to frequency must be considered. This work at the NASA Glenn Research Center is the first to develop techniques for optimizing TWT efficiency and output power over a broad frequency bandwidth (ref. 2). The techniques are based on simulated annealing, which has the advantage over conventional optimization techniques in that it enables the best possible solution to be obtained (ref. 3). Two new broadband simulated annealing algorithms were developed that optimize (1) minimum saturated power efficiency over a frequency bandwidth and (2) simultaneous bandwidth and minimum power efficiency over the frequency band with constant input power. The algorithms were incorporated into the NASA coupled-cavity TWT computer model (ref. 4) and used to design optimal phase velocity tapers using the 59- to 64-GHz Hughes 961HA coupled-cavity TWT as a baseline model. In comparison to the baseline design, the computational results of the first broad-band design algorithm show an improvement of 73.9 percent in minimum saturated efficiency (see the top graph). The second broadband design algorithm (see the bottom graph) improves minimum radiofrequency efficiency with constant input power drive by a factor of 2.7 at the high band edge (64 GHz) and increases simultaneous bandwidth by 500 MHz.

Increase of Gas-Turbine Plant Efficiency by Optimizing Operation of Compressors

NASA Astrophysics Data System (ADS)

Matveev, V.; Goriachkin, E.; Volkov, A.

2018-01-01

The article presents optimization method for improving of the working process of axial compressors of gas turbine engines. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.

Improving the efficiency of single and multiple teleportation protocols based on the direct use of partially entangled states

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

Fortes, Raphael; Rigolin, Gustavo, E-mail: rigolin@ifi.unicamp.br

We push the limits of the direct use of partially pure entangled states to perform quantum teleportation by presenting several protocols in many different scenarios that achieve the optimal efficiency possible. We review and put in a single formalism the three major strategies known to date that allow one to use partially entangled states for direct quantum teleportation (no distillation strategies permitted) and compare their efficiencies in real world implementations. We show how one can improve the efficiency of many direct teleportation protocols by combining these techniques. We then develop new teleportation protocols employing multipartite partially entangled states. The threemore » techniques are also used here in order to achieve the highest efficiency possible. Finally, we prove the upper bound for the optimal success rate for protocols based on partially entangled Bell states and show that some of the protocols here developed achieve such a bound. -- Highlights: •Optimal direct teleportation protocols using directly partially entangled states. •We put in a single formalism all strategies of direct teleportation. •We extend these techniques for multipartite partially entangle states. •We give upper bounds for the optimal efficiency of these protocols.« less

Optimal design of implants for magnetically mediated hyperthermia: A wireless power transfer approach

NASA Astrophysics Data System (ADS)

Lang, Hans-Dieter; Sarris, Costas D.

2017-09-01

In magnetically mediated hyperthermia (MMH), an externally applied alternating magnetic field interacts with a mediator (such as a magnetic nanoparticle or an implant) inside the body to heat up the tissue in its proximity. Producing heat via induced currents in this manner is strikingly similar to wireless power transfer (WPT) for implants, where power is transferred from a transmitter outside of the body to an implanted receiver, in most cases via magnetic fields as well. Leveraging this analogy, a systematic method to design MMH implants for optimal heating efficiency is introduced, akin to the design of WPT systems for optimal power transfer efficiency. This paper provides analytical formulas for the achievable heating efficiency bounds as well as the optimal operating frequency and the implant material. Multiphysics simulations validate the approach and further demonstrate that optimization with respect to maximum heating efficiency is accompanied by minimizing heat delivery to healthy tissue. This is a property that is highly desirable when considering MMH as a key component or complementary method of cancer treatment and other applications.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1990-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Multidisciplinary optimization of aeroservoelastic systems using reduced-size models

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1992-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

Optimization methods and silicon solar cell numerical models

NASA Technical Reports Server (NTRS)

Girardini, K.; Jacobsen, S. E.

1986-01-01

An optimization algorithm for use with numerical silicon solar cell models was developed. By coupling an optimization algorithm with a solar cell model, it is possible to simultaneously vary design variables such as impurity concentrations, front junction depth, back junction depth, and cell thickness to maximize the predicted cell efficiency. An optimization algorithm was developed and interfaced with the Solar Cell Analysis Program in 1 Dimension (SCAP1D). SCAP1D uses finite difference methods to solve the differential equations which, along with several relations from the physics of semiconductors, describe mathematically the performance of a solar cell. A major obstacle is that the numerical methods used in SCAP1D require a significant amount of computer time, and during an optimization the model is called iteratively until the design variables converge to the values associated with the maximum efficiency. This problem was alleviated by designing an optimization code specifically for use with numerically intensive simulations, to reduce the number of times the efficiency has to be calculated to achieve convergence to the optimal solution.

Modeling and optimization of a concentrated solar supercritical CO2 power plant

NASA Astrophysics Data System (ADS)

Osorio, Julian D.

Renewable energy sources are fundamental alternatives to supply the rising energy demand in the world and to reduce or replace fossil fuel technologies. In order to make renewable-based technologies suitable for commercial and industrial applications, two main challenges need to be solved: the design and manufacture of highly efficient devices and reliable systems to operate under intermittent energy supply conditions. In particular, power generation technologies based on solar energy are one of the most promising alternatives to supply the world energy demand and reduce the dependence on fossil fuel technologies. In this dissertation, the dynamic behavior of a Concentrated Solar Power (CSP) supercritical CO2 cycle is studied under different seasonal conditions. The system analyzed is composed of a central receiver, hot and cold thermal energy storage units, a heat exchanger, a recuperator, and multi-stage compression-expansion subsystems with intercoolers and reheaters between compressors and turbines respectively. The effects of operating and design parameters on the system performance are analyzed. Some of these parameters are the mass flow rate, intermediate pressures, number of compression-expansion stages, heat exchangers' effectiveness, multi-tank thermal energy storage, overall heat transfer coefficient between the solar receiver and the environment and the effective area of the recuperator. Energy and exergy models for each component of the system are developed to optimize operating parameters in order to lead to maximum efficiency. From the exergy analysis, the components with high contribution to exergy destruction were identified. These components, which represent an important potential of improvement, are the recuperator, the hot thermal energy storage tank and the solar receiver. Two complementary alternatives to improve the efficiency of concentrated solar thermal systems are proposed in this dissertation: the optimization of the system's operating parameters and optimization of less efficient components. The parametric optimization is developed for a 1MW reference CSP system with CO2 as the working fluid. The component optimization, focused on the less efficient components, comprises some design modifications to the traditional component configuration for the recuperator, the hot thermal energy storage tank and the solar receiver. The proposed optimization alternatives include the heat exchanger's effectiveness enhancement by optimizing fins shapes, multi-tank thermal energy storage configurations for the hot thermal energy storage tank and the incorporation of a transparent insulation material into the solar receiver. Some of the optimizations are conducted in a generalized way, using dimensionless models to be applicable no only to the CSP but also to other thermal systems. This project is therefore an effort to improve the efficiency of power generation systems based on solar energy in order to make them competitive with conventional fossil fuel power generation devices. The results show that the parametric optimization leads the system to an efficiency of about 21% and a maximum power output close to 1.5 MW. The process efficiencies obtained in this work, of more than 21%, are relatively good for a solar-thermal conversion system and are also comparable with efficiencies of conversion of high performance PV panels. The thermal energy storage allows the system to operate for several hours after sunset. This operating time is approximately increased from 220 to 480 minutes after optimization. The hot and cold thermal energy storage also lessens the temperature fluctuations by providing smooth changes of temperatures at the turbines' and compressors' inlets. Additional improvements in the overall system efficiency are possible by optimizing the less efficient components. In particular, the fin's effectiveness can be improved in more than 5% after its shape is optimized, increments in the efficiency of the thermal energy storage of about 5.7% are possible when the mass is divided into four tanks, and solar receiver efficiencies up to 70% can be maintained for high operating temperatures (~ 1200°C) when a transparent insulation material is incorporated to the receiver. The results obtained in this dissertation indicate that concentrated solar systems using supercritical CO2 could be a viable alternative to satisfying energy needs in desert areas with scarce water and fossil fuel resources.

Airfoil Design and Optimization by the One-Shot Method

NASA Technical Reports Server (NTRS)

Kuruvila, G.; Taasan, Shlomo; Salas, M. D.

1995-01-01

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Lagrange multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Topology-optimized metasurfaces: impact of initial geometric layout.

PubMed

Yang, Jianji; Fan, Jonathan A

2017-08-15

Topology optimization is a powerful iterative inverse design technique in metasurface engineering and can transform an initial layout into a high-performance device. With this method, devices are optimized within a local design phase space, making the identification of suitable initial geometries essential. In this Letter, we examine the impact of initial geometric layout on the performance of large-angle (75 deg) topology-optimized metagrating deflectors. We find that when conventional metasurface designs based on dielectric nanoposts are used as initial layouts for topology optimization, the final devices have efficiencies around 65%. In contrast, when random initial layouts are used, the final devices have ultra-high efficiencies that can reach 94%. Our numerical experiments suggest that device topologies based on conventional metasurface designs may not be suitable to produce ultra-high-efficiency, large-angle metasurfaces. Rather, initial geometric layouts with non-trivial topologies and shapes are required.

Airfoil optimization by the one-shot method

NASA Technical Reports Server (NTRS)

Kuruvila, G.; Taasan, Shlomo; Salas, M. D.

1994-01-01

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (Governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Language multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Optimal designs for copula models

PubMed Central

Perrone, E.; Müller, W.G.

2016-01-01

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well. PMID:27453616

Full space device optimization for solar cells.

PubMed

Baloch, Ahmer A B; Aly, Shahzada P; Hossain, Mohammad I; El-Mellouhi, Fedwa; Tabet, Nouar; Alharbi, Fahhad H

2017-09-20

Advances in computational materials have paved a way to design efficient solar cells by identifying the optimal properties of the device layers. Conventionally, the device optimization has been governed by single or double descriptors for an individual layer; mostly the absorbing layer. However, the performance of the device depends collectively on all the properties of the material and the geometry of each layer in the cell. To address this issue of multi-property optimization and to avoid the paradigm of reoccurring materials in the solar cell field, a full space material-independent optimization approach is developed and presented in this paper. The method is employed to obtain an optimized material data set for maximum efficiency and for targeted functionality for each layer. To ensure the robustness of the method, two cases are studied; namely perovskite solar cells device optimization and cadmium-free CIGS solar cell. The implementation determines the desirable optoelectronic properties of transport mediums and contacts that can maximize the efficiency for both cases. The resulted data sets of material properties can be matched with those in materials databases or by further microscopic material design. Moreover, the presented multi-property optimization framework can be extended to design any solid-state device.

Efficient Geometry Minimization and Transition Structure Optimization Using Interpolated Potential Energy Surfaces and Iteratively Updated Hessians.

PubMed

Zheng, Jingjing; Frisch, Michael J

2017-12-12

An efficient geometry optimization algorithm based on interpolated potential energy surfaces with iteratively updated Hessians is presented in this work. At each step of geometry optimization (including both minimization and transition structure search), an interpolated potential energy surface is properly constructed by using the previously calculated information (energies, gradients, and Hessians/updated Hessians), and Hessians of the two latest geometries are updated in an iterative manner. The optimized minimum or transition structure on the interpolated surface is used for the starting geometry of the next geometry optimization step. The cost of searching the minimum or transition structure on the interpolated surface and iteratively updating Hessians is usually negligible compared with most electronic structure single gradient calculations. These interpolated potential energy surfaces are often better representations of the true potential energy surface in a broader range than a local quadratic approximation that is usually used in most geometry optimization algorithms. Tests on a series of large and floppy molecules and transition structures both in gas phase and in solutions show that the new algorithm can significantly improve the optimization efficiency by using the iteratively updated Hessians and optimizations on interpolated surfaces.

Optimal robust control strategy of a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Wu, Xiaojuan; Gao, Danhui

2018-01-01

Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.

Optimization of nanostructured lipid carriers for topical delivery of nimesulide using Box-Behnken design approach.

PubMed

Moghddam, Seyedeh Marziyeh Mahdavi; Ahad, Abdul; Aqil, Mohd; Imam, Syed Sarim; Sultana, Yasmin

2017-05-01

The aim of the present study was to develop and optimize topically applied nimesulide-loaded nanostructured lipid carriers. Box-Behnken experimental design was applied for optimization of nanostructured lipid carriers. The independent variables were ratio of stearic acid: oleic acid (X 1 ), poloxamer 188 concentration (X 2 ) and lecithin concentration (X 3 ) while particle size (Y 1 ) and entrapment efficiency (Y 2 ) were the chosen responses. Further, skin penetration study, in vitro release, confocal laser scanning microscopy and stability study were also performed. The optimized nanostructured lipid carriers of nimesulide provide reasonable particle size, flux, and entrapment efficiency. Optimized formulation (F9) with mean particle size of 214.4 ± 11 nm showed 89.4 ± 3.40% entrapment efficiency and achieved mean flux 2.66 ± 0.09 μg/cm 2 /h. In vitro release study showed prolonged drug release from the optimized formulation following Higuchi release kinetics with R 2 value of 0.984. Confocal laser scanning microscopy revealed an enhanced penetration of Rhodamine B-loaded nanostructured lipid carriers to the deeper layers of the skin. The stability study confirmed that the optimized formulation was considerably stable at refrigerator temperature as compared to room temperature. Our results concluded that nanostructured lipid carriers are an efficient carrier for topical delivery of nimesulide.

Increased glycosylation efficiency of recombinant proteins in Escherichia coli by auto-induction.

PubMed

Ding, Ning; Yang, Chunguang; Sun, Shenxia; Han, Lichi; Ruan, Yao; Guo, Longhua; Hu, Xuejun; Zhang, Jianing

2017-03-25

Escherichia coli cells have been considered as promising hosts for producing N-glycosylated proteins since the successful production of N-glycosylated protein in E. coli with the pgl (N-linked protein glycosylation) locus from Campylobacter jejuni. However, one hurdle in producing N-glycosylated proteins in large scale using E. coli is inefficient glycan glycosylation. In this study, we developed a strategy for the production of N-glycosylated proteins with high efficiency via an optimized auto-induction method. The 10th human fibronectin type III domain (FN3) was engineered with native glycosylation sequon DFNRSK and optimized DQNAT sequon in C-terminus with flexible linker as acceptor protein models. The resulting glycosylation efficiencies were confirmed by Western blots with anti-FLAG M1 antibody. Increased efficiency of glycosylation was obtained by changing the conventional IPTG induction to auto-induction method, which increased the glycosylation efficiencies from 60% and 75% up to 90% and 100% respectively. Moreover, in the condition of inserting the glycosylation sequon in the loop of FN3 (the acceptor sequon with local structural conformation), the glycosylation efficiency was increased from 35% to 80% by our optimized auto-induction procedures. To justify the potential for general application of the optimized auto-induction method, the reconstituted lsg locus from Haemophilus influenzae and PglB from C. jejuni were utilized, and this led to 100% glycosylation efficiency. Our studies provided quantitative evidence that the optimized auto-induction method will facilitate the large-scale production of pure exogenous N-glycosylation proteins in E. coli cells. Copyright © 2017 Elsevier Inc. All rights reserved.

The unlikely high efficiency of a molecular motor based on active motion

NASA Astrophysics Data System (ADS)

Ebeling, W.

2015-07-01

The efficiency of a simple model of a motor converting chemical into mechanical energy is studied analytically. The model motor shows interesting properties corresponding qualitatively to motors investigated in experiments. The efficiency increases with the load and may for low loss reach high values near to 100 percent in a narrow regime of optimal load. It is shown that the optimal load and the maximal efficiency depend by universal power laws on the dimensionless loss parameter. Stochastic effects decrease the stability of motor regimes with high efficiency and make them unlikely. Numerical studies show efficiencies below the theoretical optimum and demonstrate that special ratchet profiles my stabilize efficient regimes.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

PubMed

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization

PubMed Central

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Chen, Chun-Hung

2017-01-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort. PMID:29170617

Modeling of defect-tolerant thin multi-junction solar cells for space application

NASA Astrophysics Data System (ADS)

Mehrotra, A.; Alemu, A.; Freundlich, A.

2012-02-01

Using drift-diffusion model and considering experimental III-V material parameters, AM0 efficiencies of lattice-matched multijunction solar cells have been calculated and the effects of dislocations and radiation damage have been analyzed. Ultrathin multi-junction devices perform better in presence of dislocations or/and radiation harsh environment compared to conventional thick multijunction devices. Our results show that device design optimization of Ga0.51In0.49P/GaAs multijunction devices leads to an improvement in EOL efficiency from 4.8%, for the conventional thick device design, to 12.7%, for the EOL optimized thin devices. In addition, an optimized defect free lattice matched Ga0.51In0.49P/GaAs solar cell under 1016cm-2 1Mev equivalent electron fluence is shown to give an EOL efficiency of 12.7%; while a Ga0.51In0.49P/GaAs solar cell with 108 cm-2 dislocation density under 1016cm-2 electron fluence gives an EOL efficiency of 12.3%. The results suggest that by optimizing the device design, we can obtain nearly the same EOL efficiencies for high dislocation metamorphic solar cells and defect filtered metamorphic multijunction solar cells. The findings relax the need for thick or graded buffer used for defect filtering in metamorphic devices. It is found that device design optimization allows highly dislocated devices to be nearly as efficient as defect free devices for space applications.

DSP code optimization based on cache

NASA Astrophysics Data System (ADS)

Xu, Chengfa; Li, Chengcheng; Tang, Bin

2013-03-01

DSP program's running efficiency on board is often lower than which via the software simulation during the program development, which is mainly resulted from the user's improper use and incomplete understanding of the cache-based memory. This paper took the TI TMS320C6455 DSP as an example, analyzed its two-level internal cache, and summarized the methods of code optimization. Processor can achieve its best performance when using these code optimization methods. At last, a specific algorithm application in radar signal processing is proposed. Experiment result shows that these optimization are efficient.

Optimization of freeform lightpipes for light-emitting-diode projectors.

PubMed

Fournier, Florian; Rolland, Jannick

2008-03-01

Standard nonimaging components used to collect and integrate light in light-emitting-diode-based projector light engines such as tapered rods and compound parabolic concentrators are compared to optimized freeform shapes in terms of transmission efficiency and spatial uniformity. We show that the simultaneous optimization of the output surface and the profile shape yields transmission efficiency within the étendue limit up to 90% and spatial uniformity higher than 95%, even for compact sizes. The optimization process involves a manual study of the trends for different shapes and the use of an optimization algorithm to further improve the performance of the freeform lightpipe.

Optimization of freeform lightpipes for light-emitting-diode projectors

NASA Astrophysics Data System (ADS)

Fournier, Florian; Rolland, Jannick

2008-03-01

Standard nonimaging components used to collect and integrate light in light-emitting-diode-based projector light engines such as tapered rods and compound parabolic concentrators are compared to optimized freeform shapes in terms of transmission efficiency and spatial uniformity. We show that the simultaneous optimization of the output surface and the profile shape yields transmission efficiency within the étendue limit up to 90% and spatial uniformity higher than 95%, even for compact sizes. The optimization process involves a manual study of the trends for different shapes and the use of an optimization algorithm to further improve the performance of the freeform lightpipe.

Optimization of output power and transmission efficiency of magnetically coupled resonance wireless power transfer system

NASA Astrophysics Data System (ADS)

Yan, Rongge; Guo, Xiaoting; Cao, Shaoqing; Zhang, Changgeng

2018-05-01

Magnetically coupled resonance (MCR) wireless power transfer (WPT) system is a promising technology in electric energy transmission. But, if its system parameters are designed unreasonably, output power and transmission efficiency will be low. Therefore, optimized parameters design of MCR WPT has important research value. In the MCR WPT system with designated coil structure, the main parameters affecting output power and transmission efficiency are the distance between the coils, the resonance frequency and the resistance of the load. Based on the established mathematical model and the differential evolution algorithm, the change of output power and transmission efficiency with parameters can be simulated. From the simulation results, it can be seen that output power and transmission efficiency of the two-coil MCR WPT system and four-coil one with designated coil structure are improved. The simulation results confirm the validity of the optimization method for MCR WPT system with designated coil structure.

Efficiency Management in Spaceflight Systems

NASA Technical Reports Server (NTRS)

Murphy, Karen

2016-01-01

Efficiency in spaceflight is often approached as “faster, better, cheaper – pick two”. The high levels of performance and reliability required for each mission suggest that planners can only control for two of the three. True efficiency comes by optimizing a system across all three parameters. The functional processes of spaceflight become technical requirements on three operational groups during mission planning: payload, vehicle, and launch operations. Given the interrelationships among the functions performed by the operational groups, optimizing function resources from one operational group to the others affects the efficiency of those groups and therefore the mission overall. This paper helps outline this framework and creates a context in which to understand the effects of resource trades on the overall system, improving the efficiency of the operational groups and the mission as a whole. This allows insight into and optimization of the controlling factors earlier in the mission planning stage.

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.

EFFICIENCY OPTIMIZATIN CONTROL OF AC INDUCTION MOTORS: INITIAL LABORATORY RESULTS

EPA Science Inventory

The report discusses the development of a fuzzy logic, energy-optimizing controller to improve the efficiency of motor/drive combinations that operate at varying loads and speeds. This energy optimizer is complemented by a sensorless speed controller that maintains motor shaft re...

Optimal shapes of surface-slip driven self-propelled swimmers

NASA Astrophysics Data System (ADS)

Vilfan, Andrej; Osterman, Natan

2012-11-01

If one defines the swimming efficiency of a microorganism as the power needed to move it against viscous drag, divided by the total dissipated power, one usually finds values no better than 1%. In order to find out how close this is to the theoretically achievable optimum, we first introduced a new efficiency measure at the level of a single cilium or an infinite ciliated surface and numerically determined the optimal beating patterns according to this criterion. In the following we also determined the optimal shape of a swimmer such that the total power is minimal while maintaining the volume and the swimming speed. The resulting shape depends strongly on the allowed maximum curvature. When sufficient curvature is allowed the optimal swimmer exhibits two protrusions along the symmetry axis. The results show that prolate swimmers such as Paramecium have an efficiency that is ~ 20% higher than that of a spherical body, whereas some microorganisms have shapes that allow even higher efficiency.

Hovering efficiency comparison of rotary and flapping flight for rigid rectangular wings via dimensionless multi-objective optimization.

PubMed

Bayiz, Yagiz; Ghanaatpishe, Mohammad; Fathy, Hosam; Cheng, Bo

2018-05-08

In this work, a multi-objective optimization framework is developed for optimizing low Reynolds number ([Formula: see text]) hovering flight. This framework is then applied to compare the efficiency of rigid revolving and flapping wings with rectangular shape under varying [Formula: see text] and Rossby number ([Formula: see text], or aspect ratio). The proposed framework is capable of generating sets of optimal solutions and Pareto fronts for maximizing the lift coefficient and minimizing the power coefficient in dimensionless space, explicitly revealing the trade-off between lift generation and power consumption. The results indicate that revolving wings are more efficient when the required average lift coefficient [Formula: see text] is low (<1 for [Formula: see text] and  <1.6 for [Formula: see text]), while flapping wings are more efficient in achieving higher [Formula: see text]. With the dimensionless power loading as the single-objective performance measure to be maximized, rotary flight is more efficient than flapping wings for [Formula: see text] regardless of the amount of energy storage assumed in the flapping wing actuation mechanism, while flapping flight is more efficient for [Formula: see text]. It is observed that wings with low [Formula: see text] perform better when higher [Formula: see text] is needed, whereas higher [Formula: see text] cases are more efficient at [Formula: see text] regions. However, for the selected geometry and [Formula: see text], the efficiency is weakly dependent on [Formula: see text] when the dimensionless power loading is maximized.

Design of A Cyclone Separator Using Approximation Method

NASA Astrophysics Data System (ADS)

Sin, Bong-Su; Choi, Ji-Won; Lee, Kwon-Hee

2017-12-01

A Separator is a device installed in industrial applications to separate mixed objects. The separator of interest in this research is a cyclone type, which is used to separate a steam-brine mixture in a geothermal plant. The most important performance of the cyclone separator is the collection efficiency. The collection efficiency in this study is predicted by performing the CFD (Computational Fluid Dynamics) analysis. This research defines six shape design variables to maximize the collection efficiency. Thus, the collection efficiency is set up as the objective function in optimization process. Since the CFD analysis requires a lot of calculation time, it is impossible to obtain the optimal solution by linking the gradient-based optimization algorithm. Thus, two approximation methods are introduced to obtain an optimum design. In this process, an L18 orthogonal array is adopted as a DOE method, and kriging interpolation method is adopted to generate the metamodel for the collection efficiency. Based on the 18 analysis results, the relative importance of each variable to the collection efficiency is obtained through the ANOVA (analysis of variance). The final design is suggested considering the results obtained from two optimization methods. The fluid flow analysis of the cyclone separator is conducted by using the commercial CFD software, ANSYS-CFX.

Efficiency optimization of wireless power transmission systems for active capsule endoscopes.

PubMed

Zhiwei, Jia; Guozheng, Yan; Jiangpingping; Zhiwu, Wang; Hua, Liu

2011-10-01

Multipurpose active capsule endoscopes have drawn considerable attention in recent years, but these devices continue to suffer from energy limitations. A wireless power supply system is regarded as a practical way to overcome the power shortage problem in such devices. This paper focuses on the efficiency optimization of a wireless energy supply system with size and safety constraints. A mathematical programming model in which these constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness. To verify the feasibility of the proposed method, we use a wireless active capsule endoscope as an illustrative example. The achieved efficiency can be regarded as an index for evaluating the system, and the proposed approach can be used to direct the design of transmitting and receiving coils.

Deposition efficiency optimization in cold spraying of metal-ceramic powder mixtures

NASA Astrophysics Data System (ADS)

Klinkov, S. V.; Kosarev, V. F.

2017-10-01

In the present paper, results of optimization of the cold spray deposition process of a metal-ceramic powder mixture involving impacts of ceramic particles onto coating surface are reported. In the optimization study, a two-probability model was used to take into account the surface activation induced by the ceramic component of the mixture. The dependence of mixture deposition efficiency on the concentration and size of ceramic particles was analysed to identify the ranges of both parameters in which the effect due to ceramic particles on the mixture deposition efficiency was positive. The dependences of the optimum size and concentration of ceramic particles, and also the maximum gain in deposition efficiency, on the probability of adhesion of metal particles to non-activated coating surface were obtained.

Sensitivity analysis and optimization method for the fabrication of one-dimensional beam-splitting phase gratings

PubMed Central

Pacheco, Shaun; Brand, Jonathan F.; Zaverton, Melissa; Milster, Tom; Liang, Rongguang

2015-01-01

A method to design one-dimensional beam-spitting phase gratings with low sensitivity to fabrication errors is described. The method optimizes the phase function of a grating by minimizing the integrated variance of the energy of each output beam over a range of fabrication errors. Numerical results for three 1x9 beam splitting phase gratings are given. Two optimized gratings with low sensitivity to fabrication errors were compared with a grating designed for optimal efficiency. These three gratings were fabricated using gray-scale photolithography. The standard deviation of the 9 outgoing beam energies in the optimized gratings were 2.3 and 3.4 times lower than the optimal efficiency grating. PMID:25969268

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments

PubMed Central

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-01-01

Objectives Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. Design and methods A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2–20), alternatives (2–5), attributes (2–20) and attribute levels (2–5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Outcome Relative d-efficiency was used to measure the optimality of each DCE design. Results DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Conclusions Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. PMID:27436671

Exploratory High-Fidelity Aerostructural Optimization Using an Efficient Monolithic Solution Method

NASA Astrophysics Data System (ADS)

Zhang, Jenmy Zimi

This thesis is motivated by the desire to discover fuel efficient aircraft concepts through exploratory design. An optimization methodology based on tightly integrated high-fidelity aerostructural analysis is proposed, which has the flexibility, robustness, and efficiency to contribute to this goal. The present aerostructural optimization methodology uses an integrated geometry parameterization and mesh movement strategy, which was initially proposed for aerodynamic shape optimization. This integrated approach provides the optimizer with a large amount of geometric freedom for conducting exploratory design, while allowing for efficient and robust mesh movement in the presence of substantial shape changes. In extending this approach to aerostructural optimization, this thesis has addressed a number of important challenges. A structural mesh deformation strategy has been introduced to translate consistently the shape changes described by the geometry parameterization to the structural model. A three-field formulation of the discrete steady aerostructural residual couples the mesh movement equations with the three-dimensional Euler equations and a linear structural analysis. Gradients needed for optimization are computed with a three-field coupled adjoint approach. A number of investigations have been conducted to demonstrate the suitability and accuracy of the present methodology for use in aerostructural optimization involving substantial shape changes. Robustness and efficiency in the coupled solution algorithms is crucial to the success of an exploratory optimization. This thesis therefore also focuses on the design of an effective monolithic solution algorithm for the proposed methodology. This involves using a Newton-Krylov method for the aerostructural analysis and a preconditioned Krylov subspace method for the coupled adjoint solution. Several aspects of the monolithic solution method have been investigated. These include appropriate strategies for scaling and matrix-vector product evaluation, as well as block preconditioning techniques that preserve the modularity between subproblems. The monolithic solution method is applied to problems with varying degrees of fluid-structural coupling, as well as a wing span optimization study. The monolithic solution algorithm typically requires 20%-70% less computing time than its partitioned counterpart. This advantage increases with increasing wing flexibility. The performance of the monolithic solution method is also much less sensitive to the choice of the solution parameter.

Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography.

PubMed

Shaw, Calvin B; Prakash, Jaya; Pramanik, Manojit; Yalavarthy, Phaneendra K

2013-08-01

A computationally efficient approach that computes the optimal regularization parameter for the Tikhonov-minimization scheme is developed for photoacoustic imaging. This approach is based on the least squares-QR decomposition which is a well-known dimensionality reduction technique for a large system of equations. It is shown that the proposed framework is effective in terms of quantitative and qualitative reconstructions of initial pressure distribution enabled via finding an optimal regularization parameter. The computational efficiency and performance of the proposed method are shown using a test case of numerical blood vessel phantom, where the initial pressure is exactly known for quantitative comparison.

Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network

PubMed Central

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. Summary We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding. PMID:29773979

Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network.

PubMed

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

Computational Efficiency of the Simplex Embedding Method in Convex Nondifferentiable Optimization

NASA Astrophysics Data System (ADS)

Kolosnitsyn, A. V.

2018-02-01

The simplex embedding method for solving convex nondifferentiable optimization problems is considered. A description of modifications of this method based on a shift of the cutting plane intended for cutting off the maximum number of simplex vertices is given. These modification speed up the problem solution. A numerical comparison of the efficiency of the proposed modifications based on the numerical solution of benchmark convex nondifferentiable optimization problems is presented.

An efficient multilevel optimization method for engineering design

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.; Yang, Y. J.; Kim, D. S.

1988-01-01

An efficient multilevel deisgn optimization technique is presented. The proposed method is based on the concept of providing linearized information between the system level and subsystem level optimization tasks. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to use. The disadvantage is that the coupling between subsystems is not dealt with in a precise mathematical manner.

Multi-objective shape optimization of runner blade for Kaplan turbine

NASA Astrophysics Data System (ADS)

Semenova, A.; Chirkov, D.; Lyutov, A.; Chemy, S.; Skorospelov, V.; Pylev, I.

2014-03-01

Automatic runner shape optimization based on extensive CFD analysis proved to be a useful design tool in hydraulic turbomachinery. Previously the authors developed an efficient method for Francis runner optimization. It was successfully applied to the design of several runners with different specific speeds. In present work this method is extended to the task of a Kaplan runner optimization. Despite of relatively simpler blade shape, Kaplan turbines have several features, complicating the optimization problem. First, Kaplan turbines normally operate in a wide range of discharges, thus CFD analysis of each variant of the runner should be carried out for several operation points. Next, due to a high specific speed, draft tube losses have a great impact on the overall turbine efficiency, and thus should be accurately evaluated. Then, the flow in blade tip and hub clearances significantly affects the velocity profile behind the runner and draft tube behavior. All these features are accounted in the present optimization technique. Parameterization of runner blade surface using 24 geometrical parameters is described in details. For each variant of runner geometry steady state three-dimensional turbulent flow computations are carried out in the domain, including wicket gate, runner, draft tube, blade tip and hub clearances. The objectives are maximization of efficiency in best efficiency and high discharge operation points, with simultaneous minimization of cavitation area on the suction side of the blade. Multiobjective genetic algorithm is used for the solution of optimization problem, requiring the analysis of several thousands of runner variants. The method is applied to optimization of runner shape for several Kaplan turbines with different heads.

A novel composite adaptive flap controller design by a high-efficient modified differential evolution identification approach.

PubMed

Li, Nailu; Mu, Anle; Yang, Xiyun; Magar, Kaman T; Liu, Chao

2018-05-01

The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Bi-level Optimization Method of Air-conditioning System Based on Office Building Energy Storage Characteristics

NASA Astrophysics Data System (ADS)

Wang, Qingze; Chen, Xingying; Ji, Li; Liao, Yingchen; Yu, Kun

2017-05-01

The air-conditioning system of office building is a large power consumption terminal equipment, whose unreasonable operation mode leads to low energy efficiency. Realizing the optimization of the air-conditioning system has become one of the important research contents of the electric power demand response. In this paper, in order to save electricity cost and improve energy efficiency, bi-level optimization method of air-conditioning system based on TOU price is put forward by using the energy storage characteristics of the office building itself. In the upper level, the operation mode of the air-conditioning system is optimized in order to minimize the uses’ electricity cost in the premise of ensuring user’ comfort according to the information of outdoor temperature and TOU price, and the cooling load of the air-conditioning is output to the lower level; In the lower level, the distribution mode of cooling load among the multi chillers is optimized in order to maximize the energy efficiency according to the characteristics of each chiller. Finally, the experimental results under different modes demonstrate that the strategy can improve the energy efficiency of chillers and save the electricity cost for users.

Efficiency Improvements to the Displacement Based Multilevel Structural Optimization Algorithm

NASA Technical Reports Server (NTRS)

Plunkett, C. L.; Striz, A. G.; Sobieszczanski-Sobieski, J.

2001-01-01

Multilevel Structural Optimization (MSO) continues to be an area of research interest in engineering optimization. In the present project, the weight optimization of beams and trusses using Displacement based Multilevel Structural Optimization (DMSO), a member of the MSO set of methodologies, is investigated. In the DMSO approach, the optimization task is subdivided into a single system and multiple subsystems level optimizations. The system level optimization minimizes the load unbalance resulting from the use of displacement functions to approximate the structural displacements. The function coefficients are then the design variables. Alternately, the system level optimization can be solved using the displacements themselves as design variables, as was shown in previous research. Both approaches ensure that the calculated loads match the applied loads. In the subsystems level, the weight of the structure is minimized using the element dimensions as design variables. The approach is expected to be very efficient for large structures, since parallel computing can be utilized in the different levels of the problem. In this paper, the method is applied to a one-dimensional beam and a large three-dimensional truss. The beam was tested to study possible simplifications to the system level optimization. In previous research, polynomials were used to approximate the global nodal displacements. The number of coefficients of the polynomials equally matched the number of degrees of freedom of the problem. Here it was desired to see if it is possible to only match a subset of the degrees of freedom in the system level. This would lead to a simplification of the system level, with a resulting increase in overall efficiency. However, the methods tested for this type of system level simplification did not yield positive results. The large truss was utilized to test further improvements in the efficiency of DMSO. In previous work, parallel processing was applied to the subsystems level, where the derivative verification feature of the optimizer NPSOL had been utilized in the optimizations. This resulted in large runtimes. In this paper, the optimizations were repeated without using the derivative verification, and the results are compared to those from the previous work. Also, the optimizations were run on both, a network of SUN workstations using the MPICH implementation of the Message Passing Interface (MPI) and on the faster Beowulf cluster at ICASE, NASA Langley Research Center, using the LAM implementation of UP]. The results on both systems were consistent and showed that it is not necessary to verify the derivatives and that this gives a large increase in efficiency of the DMSO algorithm.

Parametric modeling and stagger angle optimization of an axial flow fan

NASA Astrophysics Data System (ADS)

Li, M. X.; Zhang, C. H.; Liu, Y.; Y Zheng, S.

2013-12-01

Axial flow fans are widely used in every field of social production. Improving their efficiency is a sustained and urgent demand of domestic industry. The optimization of stagger angle is an important method to improve fan performance. Parametric modeling and calculation process automation are realized in this paper to improve optimization efficiency. Geometric modeling and mesh division are parameterized based on GAMBIT. Parameter setting and flow field calculation are completed in the batch mode of FLUENT. A control program is developed in Visual C++ to dominate the data exchange of mentioned software. It also extracts calculation results for optimization algorithm module (provided by Matlab) to generate directive optimization control parameters, which as feedback are transferred upwards to modeling module. The center line of the blade airfoil, based on CLARK y profile, is constructed by non-constant circulation and triangle discharge method. Stagger angles of six airfoil sections are optimized, to reduce the influence of inlet shock loss as well as gas leak in blade tip clearance and hub resistance at blade root. Finally an optimal solution is obtained, which meets the total pressure requirement under given conditions and improves total pressure efficiency by about 6%.

Model-based optimal design of experiments - semidefinite and nonlinear programming formulations

PubMed Central

Duarte, Belmiro P.M.; Wong, Weng Kee; Oliveira, Nuno M.C.

2015-01-01

We use mathematical programming tools, such as Semidefinite Programming (SDP) and Nonlinear Programming (NLP)-based formulations to find optimal designs for models used in chemistry and chemical engineering. In particular, we employ local design-based setups in linear models and a Bayesian setup in nonlinear models to find optimal designs. In the latter case, Gaussian Quadrature Formulas (GQFs) are used to evaluate the optimality criterion averaged over the prior distribution for the model parameters. Mathematical programming techniques are then applied to solve the optimization problems. Because such methods require the design space be discretized, we also evaluate the impact of the discretization scheme on the generated design. We demonstrate the techniques for finding D–, A– and E–optimal designs using design problems in biochemical engineering and show the method can also be directly applied to tackle additional issues, such as heteroscedasticity in the model. Our results show that the NLP formulation produces highly efficient D–optimal designs but is computationally less efficient than that required for the SDP formulation. The efficiencies of the generated designs from the two methods are generally very close and so we recommend the SDP formulation in practice. PMID:26949279

Model-based optimal design of experiments - semidefinite and nonlinear programming formulations.

PubMed

Duarte, Belmiro P M; Wong, Weng Kee; Oliveira, Nuno M C

2016-02-15

We use mathematical programming tools, such as Semidefinite Programming (SDP) and Nonlinear Programming (NLP)-based formulations to find optimal designs for models used in chemistry and chemical engineering. In particular, we employ local design-based setups in linear models and a Bayesian setup in nonlinear models to find optimal designs. In the latter case, Gaussian Quadrature Formulas (GQFs) are used to evaluate the optimality criterion averaged over the prior distribution for the model parameters. Mathematical programming techniques are then applied to solve the optimization problems. Because such methods require the design space be discretized, we also evaluate the impact of the discretization scheme on the generated design. We demonstrate the techniques for finding D -, A - and E -optimal designs using design problems in biochemical engineering and show the method can also be directly applied to tackle additional issues, such as heteroscedasticity in the model. Our results show that the NLP formulation produces highly efficient D -optimal designs but is computationally less efficient than that required for the SDP formulation. The efficiencies of the generated designs from the two methods are generally very close and so we recommend the SDP formulation in practice.

Computer-intensive simulation of solid-state NMR experiments using SIMPSON.

PubMed

Tošner, Zdeněk; Andersen, Rasmus; Stevensson, Baltzar; Edén, Mattias; Nielsen, Niels Chr; Vosegaard, Thomas

2014-09-01

Conducting large-scale solid-state NMR simulations requires fast computer software potentially in combination with efficient computational resources to complete within a reasonable time frame. Such simulations may involve large spin systems, multiple-parameter fitting of experimental spectra, or multiple-pulse experiment design using parameter scan, non-linear optimization, or optimal control procedures. To efficiently accommodate such simulations, we here present an improved version of the widely distributed open-source SIMPSON NMR simulation software package adapted to contemporary high performance hardware setups. The software is optimized for fast performance on standard stand-alone computers, multi-core processors, and large clusters of identical nodes. We describe the novel features for fast computation including internal matrix manipulations, propagator setups and acquisition strategies. For efficient calculation of powder averages, we implemented interpolation method of Alderman, Solum, and Grant, as well as recently introduced fast Wigner transform interpolation technique. The potential of the optimal control toolbox is greatly enhanced by higher precision gradients in combination with the efficient optimization algorithm known as limited memory Broyden-Fletcher-Goldfarb-Shanno. In addition, advanced parallelization can be used in all types of calculations, providing significant time reductions. SIMPSON is thus reflecting current knowledge in the field of numerical simulations of solid-state NMR experiments. The efficiency and novel features are demonstrated on the representative simulations. Copyright © 2014 Elsevier Inc. All rights reserved.

Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

NASA Astrophysics Data System (ADS)

Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik

2015-05-01

In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.

Study and optimization of the ultrasound-enhanced cleaning of an ultrafiltration ceramic membrane through a combined experimental-statistical approach.

PubMed

Alventosa-deLara, E; Barredo-Damas, S; Alcaina-Miranda, M I; Iborra-Clar, M I

2014-05-01

Membrane fouling is one of the main drawbacks of ultrafiltration technology during the treatment of dye-containing effluents. Therefore, the optimization of the membrane cleaning procedure is essential to improve the overall efficiency. In this work, a study of the factors affecting the ultrasound-assisted cleaning of an ultrafiltration ceramic membrane fouled by dye particles was carried out. The effect of transmembrane pressure (0.5, 1.5, 2.5 bar), cross-flow velocity (1, 2, 3 ms(-1)), ultrasound power level (40%, 70%, 100%) and ultrasound frequency mode (37, 80 kHz and mixed wave) on the cleaning efficiency was evaluated. The lowest frequency showed better results, although the best cleaning performance was obtained using the mixed wave mode. A Box-Behnken Design was used to find the optimal conditions for the cleaning procedure through a response surface study. The optimal operating conditions leading to the maximum cleaning efficiency predicted (32.19%) were found to be 1.1 bar, 3 ms(-1) and 100% of power level. Finally, the optimized response was compared to the efficiency of a chemical cleaning with NaOH solution, with and without the use of ultrasound. By using NaOH, cleaning efficiency nearly triples, and it improves up to 25% by adding ultrasound. Copyright © 2013 Elsevier B.V. All rights reserved.

An Optimal Control Method for Maximizing the Efficiency of Direct Drive Ocean Wave Energy Extraction System

PubMed Central

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability. PMID:25152913

Optimization and characterization of liposome formulation by mixture design.

PubMed

Maherani, Behnoush; Arab-tehrany, Elmira; Kheirolomoom, Azadeh; Reshetov, Vadzim; Stebe, Marie José; Linder, Michel

2012-02-07

This study presents the application of the mixture design technique to develop an optimal liposome formulation by using the different lipids in type and percentage (DOPC, POPC and DPPC) in liposome composition. Ten lipid mixtures were generated by the simplex-centroid design technique and liposomes were prepared by the extrusion method. Liposomes were characterized with respect to size, phase transition temperature, ζ-potential, lamellarity, fluidity and efficiency in loading calcein. The results were then applied to estimate the coefficients of mixture design model and to find the optimal lipid composition with improved entrapment efficiency, size, transition temperature, fluidity and ζ-potential of liposomes. The response optimization of experiments was the liposome formulation with DOPC: 46%, POPC: 12% and DPPC: 42%. The optimal liposome formulation had an average diameter of 127.5 nm, a phase-transition temperature of 11.43 °C, a ζ-potential of -7.24 mV, fluidity (1/P)(TMA-DPH)((¬)) value of 2.87 and an encapsulation efficiency of 20.24%. The experimental results of characterization of optimal liposome formulation were in good agreement with those predicted by the mixture design technique.

An optimal control method for maximizing the efficiency of direct drive ocean wave energy extraction system.

PubMed

Chen, Zhongxian; Yu, Haitao; Wen, Cheng

2014-01-01

The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability.

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

On computing the global time-optimal motions of robotic manipulators in the presence of obstacles

NASA Technical Reports Server (NTRS)

Shiller, Zvi; Dubowsky, Steven

1991-01-01

A method for computing the time-optimal motions of robotic manipulators is presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem is reduced to a search for the time-optimal path in the n-dimensional position space. A small set of near-optimal paths is first efficiently selected from a grid, using a branch and bound search and a series of lower bound estimates on the traveling time along a given path. These paths are further optimized with a local path optimization to yield the global optimal solution. Obstacles are considered by eliminating the collision points from the tessellated space and by adding a penalty function to the motion time in the local optimization. The computational efficiency of the method stems from the reduced dimensionality of the searched spaced and from combining the grid search with a local optimization. The method is demonstrated in several examples for two- and six-degree-of-freedom manipulators with obstacles.

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

Optimal orientation in flows: providing a benchmark for animal movement strategies.

PubMed

McLaren, James D; Shamoun-Baranes, Judy; Dokter, Adriaan M; Klaassen, Raymond H G; Bouten, Willem

2014-10-06

Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal) orientation. We then define optimal orientation for movement in steady flow patterns and, using dynamic wind data, for short-distance mass movements of thrushes (Turdus sp.) and 6000 km non-stop migratory flights by great snipes, Gallinago media. Relative to the optimal benchmark, we assess the efficiency (travel speed) and reliability (success rate) of three generic orientation strategies: full compensation for lateral drift, vector orientation (single-heading movement) and goal orientation (continually heading towards the goal). Optimal orientation is characterized by detours to regions of high flow support, especially when flow speeds approach and exceed the animal's self-propelled speed. In strong predictable flow (short distance thrush flights), vector orientation adjusted to flow on departure is nearly optimal, whereas for unpredictable flow (inter-continental snipe flights), only goal orientation was near-optimally reliable and efficient. Optimal orientation provides a benchmark for assessing efficiency of responses to complex flow conditions, thereby offering insight into adaptive flow-orientation across taxa in the light of flow strength, predictability and navigation capacity.

Optimal orientation in flows: providing a benchmark for animal movement strategies

PubMed Central

McLaren, James D.; Shamoun-Baranes, Judy; Dokter, Adriaan M.; Klaassen, Raymond H. G.; Bouten, Willem

2014-01-01

Animal movements in air and water can be strongly affected by experienced flow. While various flow-orientation strategies have been proposed and observed, their performance in variable flow conditions remains unclear. We apply control theory to establish a benchmark for time-minimizing (optimal) orientation. We then define optimal orientation for movement in steady flow patterns and, using dynamic wind data, for short-distance mass movements of thrushes (Turdus sp.) and 6000 km non-stop migratory flights by great snipes, Gallinago media. Relative to the optimal benchmark, we assess the efficiency (travel speed) and reliability (success rate) of three generic orientation strategies: full compensation for lateral drift, vector orientation (single-heading movement) and goal orientation (continually heading towards the goal). Optimal orientation is characterized by detours to regions of high flow support, especially when flow speeds approach and exceed the animal's self-propelled speed. In strong predictable flow (short distance thrush flights), vector orientation adjusted to flow on departure is nearly optimal, whereas for unpredictable flow (inter-continental snipe flights), only goal orientation was near-optimally reliable and efficient. Optimal orientation provides a benchmark for assessing efficiency of responses to complex flow conditions, thereby offering insight into adaptive flow-orientation across taxa in the light of flow strength, predictability and navigation capacity. PMID:25056213

A Power-Optimized Cooperative MAC Protocol for Lifetime Extension in Wireless Sensor Networks.

PubMed

Liu, Kai; Wu, Shan; Huang, Bo; Liu, Feng; Xu, Zhen

2016-10-01

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime.

A Power-Optimized Cooperative MAC Protocol for Lifetime Extension in Wireless Sensor Networks

PubMed Central

Liu, Kai; Wu, Shan; Huang, Bo; Liu, Feng; Xu, Zhen

2016-01-01

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime. PMID:27706079

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency.

PubMed

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Liu, Bing; Feng, Dongru; Wang, Jinfa; Wang, Hong-Bin

2016-11-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. © 2016 American Society of Plant Biologists. All Rights Reserved.

Optimization of Light-Harvesting Pigment Improves Photosynthetic Efficiency1[OPEN

PubMed Central

Jin, Honglei; Li, Mengshu; Duan, Sujuan; Fu, Mei; Dong, Xiaoxiao; Feng, Dongru; Wang, Jinfa

2016-01-01

Maximizing light capture by light-harvesting pigment optimization represents an attractive but challenging strategy to improve photosynthetic efficiency. Here, we report that loss of a previously uncharacterized gene, HIGH PHOTOSYNTHETIC EFFICIENCY1 (HPE1), optimizes light-harvesting pigments, leading to improved photosynthetic efficiency and biomass production. Arabidopsis (Arabidopsis thaliana) hpe1 mutants show faster electron transport and increased contents of carbohydrates. HPE1 encodes a chloroplast protein containing an RNA recognition motif that directly associates with and regulates the splicing of target RNAs of plastid genes. HPE1 also interacts with other plastid RNA-splicing factors, including CAF1 and OTP51, which share common targets with HPE1. Deficiency of HPE1 alters the expression of nucleus-encoded chlorophyll-related genes, probably through plastid-to-nucleus signaling, causing decreased total content of chlorophyll (a+b) in a limited range but increased chlorophyll a/b ratio. Interestingly, this adjustment of light-harvesting pigment reduces antenna size, improves light capture, decreases energy loss, mitigates photodamage, and enhances photosynthetic quantum yield during photosynthesis. Our findings suggest a novel strategy to optimize light-harvesting pigments that improves photosynthetic efficiency and biomass production in higher plants. PMID:27609860

Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

NASA Astrophysics Data System (ADS)

Li, R. N.; Liu, X.; Liu, S. J.

2013-12-01

In order to ensure the high efficiency of the whole flexible drive train of the front-end speed adjusting wind turbine, the working principle of the main part of the drive train is analyzed. As critical parameters, rotating speed ratios of three planetary gear trains are selected as the research subject. The mathematical model of the torque converter speed ratio is established based on these three critical variable quantity, and the effect of key parameters on the efficiency of hydraulic mechanical transmission is analyzed. Based on the torque balance and the energy balance, refer to hydraulic mechanical transmission characteristics, the transmission efficiency expression of the whole drive train is established. The fitness function and constraint functions are established respectively based on the drive train transmission efficiency and the torque converter rotating speed ratio range. And the optimization calculation is carried out by using MATLAB genetic algorithm toolbox. The optimization method and results provide an optimization program for exact match of wind turbine rotor, gearbox, hydraulic mechanical transmission, hydraulic torque converter and synchronous generator, ensure that the drive train work with a high efficiency, and give a reference for the selection of the torque converter and hydraulic mechanical transmission.

Increasing efficiency of human mesenchymal stromal cell culture by optimization of microcarrier concentration and design of medium feed.

PubMed

Chen, Allen Kuan-Liang; Chew, Yi Kong; Tan, Hong Yu; Reuveny, Shaul; Weng Oh, Steve Kah

2015-02-01

Large amounts of human mesenchymal stromal cells (MSCs) are needed for clinical cellular therapy. In a previous publication, we described a microcarrier-based process for expansion of MSCs. The present study optimized this process by selecting suitable basal media, microcarrier concentration and feeding regime to achieve higher cell yields and more efficient medium utilization. MSCs were expanded in stirred cultures on Cytodex 3 microcarriers with media containing 10% fetal bovine serum. Process optimization was carried out in spinner flasks. A 2-L bioreactor with an automated feeding system was used to validate the optimized parameters explored in spinner flask cultures. Minimum essential medium-α-based medium supported faster MSC growth on microcarriers than did Dulbecco's modified Eagle's medium (doubling time, 31.6 ± 1.4 vs 42 ± 1.7 h) and shortened the process time. At microcarrier concentration of 8 mg/mL, a high cell concentration of 1.08 × 10(6) cells/mL with confluent cell concentration of 4.7 × 10(4)cells/cm(2) was achieved. Instead of 50% medium exchange every 2 days, we have designed a full medium feed that is based on glucose consumption rate. The optimal medium feed that consisted of 1.5 g/L glucose supported MSC growth to full confluency while achieving the low medium usage efficiency of 3.29 mL/10(6)cells. Finally, a controlled bioreactor with the optimized parameters achieved maximal confluent cell concentration with 16-fold expansion and a further improved medium usage efficiency of 1.68 mL/10(6)cells. We have optimized the microcarrier-based platform for expansion of MSCs that generated high cell yields in a more efficient and cost-effective manner. This study highlighted the critical parameters in the optimization of MSC production process. Copyright © 2015 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Optimization of Contrast Detection Power with Probabilistic Behavioral Information

PubMed Central

Cordes, Dietmar; Herzmann, Grit; Nandy, Rajesh; Curran, Tim

2012-01-01

Recent progress in the experimental design for event-related fMRI experiments made it possible to find the optimal stimulus sequence for maximum contrast detection power using a genetic algorithm. In this study, a novel algorithm is proposed for optimization of contrast detection power by including probabilistic behavioral information, based on pilot data, in the genetic algorithm. As a particular application, a recognition memory task is studied and the design matrix optimized for contrasts involving the familiarity of individual items (pictures of objects) and the recollection of qualitative information associated with the items (left/right orientation). Optimization of contrast efficiency is a complicated issue whenever subjects’ responses are not deterministic but probabilistic. Contrast efficiencies are not predictable unless behavioral responses are included in the design optimization. However, available software for design optimization does not include options for probabilistic behavioral constraints. If the anticipated behavioral responses are included in the optimization algorithm, the design is optimal for the assumed behavioral responses, and the resulting contrast efficiency is greater than what either a block design or a random design can achieve. Furthermore, improvements of contrast detection power depend strongly on the behavioral probabilities, the perceived randomness, and the contrast of interest. The present genetic algorithm can be applied to any case in which fMRI contrasts are dependent on probabilistic responses that can be estimated from pilot data. PMID:22326984

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Optimization of imprintable nanostructured a-Si solar cells: FDTD study.

PubMed

Fisker, Christian; Pedersen, Thomas Garm

2013-03-11

We present a finite-difference time-domain (FDTD) study of an amorphous silicon (a-Si) thin film solar cell, with nano scale patterns on the substrate surface. The patterns, based on the geometry of anisotropically etched silicon gratings, are optimized with respect to the period and anti-reflection (AR) coating thickness for maximal absorption in the range of the solar spectrum. The structure is shown to increase the cell efficiency by 10.2% compared to a similar flat solar cell with an optimized AR coating thickness. An increased back reflection can be obtained with a 50 nm zinc oxide layer on the back reflector, which gives an additional efficiency increase, leading to a total of 14.9%. In addition, the patterned cells are shown to be up to 3.8% more efficient than an optimized textured reference cell based on the Asahi U-type glass surface. The effects of variations of the optimized solar cell structure due to the manufacturing process are investigated, and shown to be negligible for variations below ±10%.

Improved Ant Algorithms for Software Testing Cases Generation

PubMed Central

Yang, Shunkun; Xu, Jiaqi

2014-01-01

Existing ant colony optimization (ACO) for software testing cases generation is a very popular domain in software testing engineering. However, the traditional ACO has flaws, as early search pheromone is relatively scarce, search efficiency is low, search model is too simple, positive feedback mechanism is easy to porduce the phenomenon of stagnation and precocity. This paper introduces improved ACO for software testing cases generation: improved local pheromone update strategy for ant colony optimization, improved pheromone volatilization coefficient for ant colony optimization (IPVACO), and improved the global path pheromone update strategy for ant colony optimization (IGPACO). At last, we put forward a comprehensive improved ant colony optimization (ACIACO), which is based on all the above three methods. The proposed technique will be compared with random algorithm (RND) and genetic algorithm (GA) in terms of both efficiency and coverage. The results indicate that the improved method can effectively improve the search efficiency, restrain precocity, promote case coverage, and reduce the number of iterations. PMID:24883391

Multi-objective Optimization of a Solar Humidification Dehumidification Desalination Unit

NASA Astrophysics Data System (ADS)

Rafigh, M.; Mirzaeian, M.; Najafi, B.; Rinaldi, F.; Marchesi, R.

2017-11-01

In the present paper, a humidification-dehumidification desalination unit integrated with solar system is considered. In the first step mathematical model of the whole plant is represented. Next, taking into account the logical constraints, the performance of the system is optimized. On one hand it is desired to have higher energetic efficiency, while on the other hand, higher efficiency results in an increment in the required area for each subsystem which consequently leads to an increase in the total cost of the plant. In the present work, the optimum solution is achieved when the specific energy of the solar heater and also the areas of humidifier and dehumidifier are minimized. Due to the fact that considered objective functions are in conflict, conventional optimization methods are not applicable. Hence, multi objective optimization using genetic algorithm which is an efficient tool for dealing with problems with conflicting objectives has been utilized and a set of optimal solutions called Pareto front each of which is a tradeoff between the mentioned objectives is generated.

New generation photoelectric converter structure optimization using nano-structured materials

NASA Astrophysics Data System (ADS)

Dronov, A.; Gavrilin, I.; Zheleznyakova, A.

2014-12-01

In present work the influence of anodizing process parameters on PAOT geometric parameters for optimizing and increasing ETA-cell efficiency was studied. During the calculations optimal geometrical parameters were obtained. Parameters such as anodizing current density, electrolyte composition and temperature, as well as the anodic oxidation process time were selected for this investigation. Using the optimized TiO2 photoelectrode layer with 3,6 μm porous layer thickness and pore diameter more than 80 nm the ETA-cell efficiency has been increased by 3 times comparing to not nanostructured TiO2 photoelectrode.

[Optimization of riboflavin sodium phosphate loading to calcium alginate floating microspheres by response surface methodology].

PubMed

Zhang, An-yang; Fan, Tian-yuan

2009-12-18

To investigate the preparation, optimization and in vitro properties of riboflavin sodium phosphate floating microspheres. The floating microspheres composed of riboflavin sodium phosphate and calcium alginate were prepared using ion gelatin-oven drying method. The properties of the microspheres were investigated, including the buoyancy, release, appearance and entrapment efficiency. The formulation was optimized by response surface methodology (RSM). The optimized microspheres were round. The entrapment efficiency was 57.49%. All the microspheres could float on the artificial gastric juice over 8 hours. The release of the drug from the microspheres complied with Fick's diffusion.

Automation of On-Board Flightpath Management

NASA Technical Reports Server (NTRS)

Erzberger, H.

1981-01-01

The status of concepts and techniques for the design of onboard flight path management systems is reviewed. Such systems are designed to increase flight efficiency and safety by automating the optimization of flight procedures onboard aircraft. After a brief review of the origins and functions of such systems, two complementary methods are described for attacking the key design problem, namely, the synthesis of efficient trajectories. One method optimizes en route, the other optimizes terminal area flight; both methods are rooted in optimal control theory. Simulation and flight test results are reviewed to illustrate the potential of these systems for fuel and cost savings.

Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

NASA Astrophysics Data System (ADS)

Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li

2018-03-01

In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.

Optimizing a three-stage Compton camera for measuring prompt gamma rays emitted during proton radiotherapy

PubMed Central

Peterson, S W; Robertson, D; Polf, J

2011-01-01

In this work, we investigate the use of a three-stage Compton camera to measure secondary prompt gamma rays emitted from patients treated with proton beam radiotherapy. The purpose of this study was (1) to develop an optimal three-stage Compton camera specifically designed to measure prompt gamma rays emitted from tissue and (2) to determine the feasibility of using this optimized Compton camera design to measure and image prompt gamma rays emitted during proton beam irradiation. The three-stage Compton camera was modeled in Geant4 as three high-purity germanium detector stages arranged in parallel-plane geometry. Initially, an isotropic gamma source ranging from 0 to 15 MeV was used to determine lateral width and thickness of the detector stages that provided the optimal detection efficiency. Then, the gamma source was replaced by a proton beam irradiating a tissue phantom to calculate the overall efficiency of the optimized camera for detecting emitted prompt gammas. The overall calculated efficiencies varied from ~10−6 to 10−3 prompt gammas detected per proton incident on the tissue phantom for several variations of the optimal camera design studied. Based on the overall efficiency results, we believe it feasible that a three-stage Compton camera could detect a sufficient number of prompt gammas to allow measurement and imaging of prompt gamma emission during proton radiotherapy. PMID:21048295

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

Hart, William; Laird, Carl; Siirola, John

Pyomo provides a rich software environment for formulating and analyzing optimization applications. Pyomo supports the algebraic specification of complex sets of objectives and constraints, which enables optimization solvers to exploit problem structure to efficiently perform optimization.

Recent experience in simultaneous control-structure optimization

NASA Technical Reports Server (NTRS)

Salama, M.; Ramaker, R.; Milman, M.

1989-01-01

To show the feasibility of simultaneous optimization as design procedure, low order problems were used in conjunction with simple control formulations. The numerical results indicate that simultaneous optimization is not only feasible, but also advantageous. Such advantages come at the expense of introducing complexities beyond those encountered in structure optimization alone, or control optimization alone. Examples include: larger design parameter space, optimization may combine continuous and combinatoric variables, and the combined objective function may be nonconvex. Future extensions to include large order problems, more complex objective functions and constraints, and more sophisticated control formulations will require further research to ensure that the additional complexities do not outweigh the advantages of simultaneous optimization. Some areas requiring more efficient tools than currently available include: multiobjective criteria and nonconvex optimization. Efficient techniques to deal with optimization over combinatoric and continuous variables, and with truncation issues for structure and control parameters of both the model space as well as the design space need to be developed.

Efficiencies of joint non-local update moves in Monte Carlo simulations of coarse-grained polymers

NASA Astrophysics Data System (ADS)

Austin, Kieran S.; Marenz, Martin; Janke, Wolfhard

2018-03-01

In this study four update methods are compared in their performance in a Monte Carlo simulation of polymers in continuum space. The efficiencies of the update methods and combinations thereof are compared with the aid of the autocorrelation time with a fixed (optimal) acceptance ratio. Results are obtained for polymer lengths N = 14, 28 and 42 and temperatures below, at and above the collapse transition. In terms of autocorrelation, the optimal acceptance ratio is approximately 0.4. Furthermore, an overview of the step sizes of the update methods that correspond to this optimal acceptance ratio is given. This shall serve as a guide for future studies that rely on efficient computer simulations.

Optimal Shapes of Surface Slip Driven Self-Propelled Microswimmers

NASA Astrophysics Data System (ADS)

Vilfan, Andrej

2012-09-01

We study the efficiency of self-propelled swimmers at low Reynolds numbers, assuming that the local energetic cost of maintaining a propulsive surface slip velocity is proportional to the square of that velocity. We determine numerically the optimal shape of a swimmer such that the total power is minimal while maintaining the volume and the swimming speed. The resulting shape depends strongly on the allowed maximum curvature. When sufficient curvature is allowed the optimal swimmer exhibits two protrusions along the symmetry axis. The results show that prolate swimmers such as Paramecium have an efficiency that is ˜20% higher than that of a spherical body, whereas some microorganisms have shapes that allow even higher efficiency.

Design and optimization of a high-efficiency array generator in the mid-IR with binary subwavelength grooves.

PubMed

Bloom, Guillaume; Larat, Christian; Lallier, Eric; Lee-Bouhours, Mane-Si Laure; Loiseaux, Brigitte; Huignard, Jean-Pierre

2011-02-10

We have designed a high-efficiency array generator composed of subwavelength grooves etched in a GaAs substrate for operation at 4.5 μm. The method used combines rigorous coupled wave analysis with an optimization algorithm. The optimized beam splitter has both a high efficiency (∼96%) and a good intensity uniformity (∼0.2%). The fabrication error tolerances are numerically calculated, and it is shown that this subwavelength array generator could be fabricated with current electron beam writers and inductively coupled plasma etching. Finally, we studied the effect of a simple and realistic antireflection coating on the performance of the beam splitter.

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments.

PubMed

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-07-19

Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2-20), alternatives (2-5), attributes (2-20) and attribute levels (2-5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Relative d-efficiency was used to measure the optimality of each DCE design. DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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.

Comparative Evaluation of Different Optimization Algorithms for Structural Design Applications

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Non-linear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Centre, a project was initiated to assess the performance of eight different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using the eight different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems, however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with Sequential Unconstrained Minimizations Technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Multi-Constraint Multi-Variable Optimization of Source-Driven Nuclear Systems

NASA Astrophysics Data System (ADS)

Watkins, Edward Francis

1995-01-01

A novel approach to the search for optimal designs of source-driven nuclear systems is investigated. Such systems include radiation shields, fusion reactor blankets and various neutron spectrum-shaping assemblies. The novel approach involves the replacement of the steepest-descents optimization algorithm incorporated in the code SWAN by a significantly more general and efficient sequential quadratic programming optimization algorithm provided by the code NPSOL. The resulting SWAN/NPSOL code system can be applied to more general, multi-variable, multi-constraint shield optimization problems. The constraints it accounts for may include simple bounds on variables, linear constraints, and smooth nonlinear constraints. It may also be applied to unconstrained, bound-constrained and linearly constrained optimization. The shield optimization capabilities of the SWAN/NPSOL code system is tested and verified in a variety of optimization problems: dose minimization at constant cost, cost minimization at constant dose, and multiple-nonlinear constraint optimization. The replacement of the optimization part of SWAN with NPSOL is found feasible and leads to a very substantial improvement in the complexity of optimization problems which can be efficiently handled.

Performance Trend of Different Algorithms for Structural Design Optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Inverse Statistics and Asset Allocation Efficiency

NASA Astrophysics Data System (ADS)

Bolgorian, Meysam

In this paper using inverse statistics analysis, the effect of investment horizon on the efficiency of portfolio selection is examined. Inverse statistics analysis is a general tool also known as probability distribution of exit time that is used for detecting the distribution of the time in which a stochastic process exits from a zone. This analysis was used in Refs. 1 and 2 for studying the financial returns time series. This distribution provides an optimal investment horizon which determines the most likely horizon for gaining a specific return. Using samples of stocks from Tehran Stock Exchange (TSE) as an emerging market and S&P 500 as a developed market, effect of optimal investment horizon in asset allocation is assessed. It is found that taking into account the optimal investment horizon in TSE leads to more efficiency for large size portfolios while for stocks selected from S&P 500, regardless of portfolio size, this strategy does not only not produce more efficient portfolios, but also longer investment horizons provides more efficiency.

Current and efficiency optimization under oscillating forces in entropic barriers

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Aydıner, Ekrem

2016-09-01

The transport of externally overdriven particles confined in entropic barriers is investigated under various types of oscillating and temporal forces. Temperature, load, and amplitude dependence of the particle current and energy conversion efficiency are investigated in three dimensions. For oscillating forces, the optimized temperature-load, amplitude-temperature, and amplitude-load intervals are determined when fixing the amplitude, load, and temperature, respectively. By using three-dimensional plots rather than two-dimensional ones, it is clearly shown that oscillating forces provide more efficiency compared with a temporal one in specified optimized parameter regions. Furthermore, the dependency of efficiency to the angle between the unbiased driving force and a constant force is investigated and an asymmetric angular dependence is found for all types of forces. Finally, it is shown that oscillating forces with a high amplitude and under a moderate load lead to higher efficiencies than a temporal force at both low and high temperatures for the entire range of contact angle. Project supported by the Istanbul University, Turkey (Grant No. 55383).

Analysis and Evaluation of Parameters Determining Maximum Efficiency of Fish Protection

NASA Astrophysics Data System (ADS)

Khetsuriani, E. D.; Kostyukov, V. P.; Khetsuriani, T. E.

2017-11-01

The article is concerned with experimental research findings. The efficiency of fish fry protection from entering water inlets is the main criterion of any fish protection facility or device. The research was aimed to determine an adequate mathematical model E = f(PCT, Vp, α), where PCT, Vp and α are controlled factors influencing the process of fish fry protection. The result of the processing of experimental data was an adequate regression model. We determined the maximum of fish protection Emax=94,21 and the minimum of optimization function Emin=44,41. As a result of the statistical processing of experimental data we obtained adequate dependences for determining an optimal rotational speed of tip and fish protection efficiency. The analysis of fish protection efficiency dependence E% = f(PCT, Vp, α) allowed the authors to recommend the following optimized operating modes for it: the maximum fish protection efficiency is achieved at the process pressure PCT=3 atm, stream velocity Vp=0,42 m/s and nozzle inclination angle α=47°49’. The stream velocity Vp has the most critical influence on fish protection efficiency. The maximum efficiency of fish protection is obtained at the tip rotational speed of 70.92 rpm.

Development of an improved high efficiency thin silicon solar cell

NASA Technical Reports Server (NTRS)

Lindmayer, J.

1978-01-01

Efforts were concerned with optimizing techniques for thinning silicon slices in NaOH etches, initial investigations of surface texturing, variation of furnace treatments to improve cell efficiency, initial efforts on optimization of gridline and cell sizes and Pilot Line fabrication of quantities of 2 cm x 2 cm 50 micron thick cells.

Fast optimization of binary clusters using a novel dynamic lattice searching method.

PubMed

Wu, Xia; Cheng, Wen

2014-09-28

Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.

Optimizing the recovery efficiency of Finnish oil combating vessels in the Gulf of Finland using Bayesian Networks.

PubMed

Lehikoinen, Annukka; Luoma, Emilia; Mäntyniemi, Samu; Kuikka, Sakari

2013-02-19

Oil transport has greatly increased in the Gulf of Finland over the years, and risks of an oil accident occurring have risen. Thus, an effective oil combating strategy is needed. We developed a Bayesian Network (BN) to examine the recovery efficiency and optimal disposition of the Finnish oil combating vessels in the Gulf of Finland (GoF), Eastern Baltic Sea. Four alternative home harbors, five accident points, and ten oil combating vessels were included in the model to find the optimal disposition policy that would maximize the recovery efficiency. With this composition, the placement of the oil combating vessels seems not to have a significant effect on the recovery efficiency. The process seems to be strongly controlled by certain random factors independent of human action, e.g. wave height and stranding time of the oil. Therefore, the success of oil combating is rather uncertain, so it is also important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this type of multidecision optimization. The methodology, results, and practices are further discussed.

Shape optimization for aerodynamic efficiency and low observability

NASA Technical Reports Server (NTRS)

Vinh, Hoang; Van Dam, C. P.; Dwyer, Harry A.

1993-01-01

Field methods based on the finite-difference approximations of the time-domain Maxwell's equations and the potential-flow equation have been developed to solve the multidisciplinary problem of airfoil shaping for aerodynamic efficiency and low radar cross section (RCS). A parametric study and an optimization study employing the two analysis methods are presented to illustrate their combined capabilities. The parametric study shows that for frontal radar illumination, the RCS of an airfoil is independent of the chordwise location of maximum thickness but depends strongly on the maximum thickness, leading-edge radius, and leadingedge shape. In addition, this study shows that the RCS of an airfoil can be reduced without significant effects on its transonic aerodynamic efficiency by reducing the leading-edge radius and/or modifying the shape of the leading edge. The optimization study involves the minimization of wave drag for a non-lifting, symmetrical airfoil with constraints on the airfoil maximum thickness and monostatic RCS. This optimization study shows that the two analysis methods can be used effectively to design aerodynamically efficient airfoils with certain desired RCS characteristics.

Diagnostic Utility of the Posttraumatic Stress Disorder (PTSD) Checklist for Identifying Full and Partial PTSD in Active-Duty Military.

PubMed

Dickstein, Benjamin D; Weathers, Frank W; Angkaw, Abigail C; Nievergelt, Caroline M; Yurgil, Kate; Nash, William P; Baker, Dewleen G; Litz, Brett T

2015-06-01

The aim of this study was to determine optimally efficient cutoff scores on the Posttraumatic Stress Disorder Checklist (PCL) for identifying full posttraumatic stress disorder (PTSD) and partial PTSD (P-PTSD) in active-duty Marines and Sailors. Participants were 1,016 Marines and Sailors who were administered the PCL and Clinician-Administered PTSD Scale (CAPS) 3 months after returning from Operations Iraqi and Enduring Freedom. PCL cutoffs were tested against three CAPS-based classifications: full PTSD, stringent P-PTSD, and lenient P-PTSD. A PCL score of 39 was found to be optimally efficient for identifying full PTSD. Scores of 38 and 33 were found to be optimally efficient for identifying stringent and lenient P-PTSD, respectively. Findings suggest that the PCL cutoff that is optimally efficient for detecting PTSD in active-duty Marines and Sailors is substantially lower than the score of 50 commonly used by researchers. In addition, findings provide scores useful for identifying P-PTSD in returning service members. © The Author(s) 2014.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

DOE PAGES

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.; ...

2014-09-18

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

An Efficient, Optimized Synthesis of Fentanyl and Related Analogs

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

Valdez, Carlos A.; Leif, Roald N.; Mayer, Brian P.

The alternate and optimized syntheses of the parent opioid fentanyl and its analogs are described. The routes presented exhibit high-yielding transformations leading to these powerful analgesics after optimization studies were carried out for each synthetic step. The general three-step strategy produced a panel of four fentanyls in excellent yields (73–78%) along with their more commonly encountered hydrochloride and citric acid salts. In conclusion, the following strategy offers the opportunity for the gram-scale, efficient production of this interesting class of opioid alkaloids.

All-optical nanomechanical heat engine.

PubMed

Dechant, Andreas; Kiesel, Nikolai; Lutz, Eric

2015-05-08

We propose and theoretically investigate a nanomechanical heat engine. We show how a levitated nanoparticle in an optical trap inside a cavity can be used to realize a Stirling cycle in the underdamped regime. The all-optical approach enables fast and flexible control of all thermodynamical parameters and the efficient optimization of the performance of the engine. We develop a systematic optimization procedure to determine optimal driving protocols. Further, we perform numerical simulations with realistic parameters and evaluate the maximum power and the corresponding efficiency.

All-Optical Nanomechanical Heat Engine

NASA Astrophysics Data System (ADS)

Dechant, Andreas; Kiesel, Nikolai; Lutz, Eric

2015-05-01

We propose and theoretically investigate a nanomechanical heat engine. We show how a levitated nanoparticle in an optical trap inside a cavity can be used to realize a Stirling cycle in the underdamped regime. The all-optical approach enables fast and flexible control of all thermodynamical parameters and the efficient optimization of the performance of the engine. We develop a systematic optimization procedure to determine optimal driving protocols. Further, we perform numerical simulations with realistic parameters and evaluate the maximum power and the corresponding efficiency.

Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong-Kyu; Im, Yong-Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

2015-04-01

This article proposes an efficient metaheuristic based on hybridization of teaching-learning-based optimization and differential evolution for optimization to improve the flatness of a strip during a strip coiling process. Differential evolution operators were integrated into the teaching-learning-based optimization with a Latin hypercube sampling technique for generation of an initial population. The objective function was introduced to reduce axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love's elastic solution within the thin strip, which may cause an irregular surface profile of the strip during the strip coiling process. The hybrid optimizer and several well-established evolutionary algorithms (EAs) were used to solve the optimization problem. The comparative studies show that the proposed hybrid algorithm outperformed other EAs in terms of convergence rate and consistency. It was found that the proposed hybrid approach was powerful for process optimization, especially with a large-scale design problem.

Deterministic Design Optimization of Structures in OpenMDAO Framework

NASA Technical Reports Server (NTRS)

Coroneos, Rula M.; Pai, Shantaram S.

2012-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

A novel adaptive Cuckoo search for optimal query plan generation.

PubMed

Gomathi, Ramalingam; Sharmila, Dhandapani

2014-01-01

The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

Optimization of gear ratio and power distribution for a multimotor powertrain of an electric vehicle

NASA Astrophysics Data System (ADS)

Urbina Coronado, Pedro Daniel; Orta Castañón, Pedro; Ahuett-Garza, Horacio

2018-02-01

The architecture and design of the propulsion system of electric vehicles are highly important for the reduction of energy losses. This work presents a powertrain composed of four electric motors in which each motor is connected with a different gear ratio to the differential of the rear axle. A strategy to reduce energy losses is proposed, in which two phases are applied. Phase 1 uses a divide-and-conquer approach to increase the overall output efficiency by obtaining the optimal torque distribution for the electric motors. Phase 2 applies a genetic algorithm to find the optimal value of the gear ratios, in which each individual of each generation applies Phase 1. The results show an optimized efficiency map for the output torque and speed of the powertrain. The increase in efficiency and the reduction of energy losses are validated by the use of numerical experiments in various driving cycles.

Efficient Simulation Budget Allocation for Selecting an Optimal Subset

NASA Technical Reports Server (NTRS)

Chen, Chun-Hung; He, Donghai; Fu, Michael; Lee, Loo Hay

2008-01-01

We consider a class of the subset selection problem in ranking and selection. The objective is to identify the top m out of k designs based on simulated output. Traditional procedures are conservative and inefficient. Using the optimal computing budget allocation framework, we formulate the problem as that of maximizing the probability of correc tly selecting all of the top-m designs subject to a constraint on the total number of samples available. For an approximation of this corre ct selection probability, we derive an asymptotically optimal allocat ion and propose an easy-to-implement heuristic sequential allocation procedure. Numerical experiments indicate that the resulting allocatio ns are superior to other methods in the literature that we tested, and the relative efficiency increases for larger problems. In addition, preliminary numerical results indicate that the proposed new procedur e has the potential to enhance computational efficiency for simulation optimization.

Design of multi-energy Helds coupling testing system of vertical axis wind power system

NASA Astrophysics Data System (ADS)

Chen, Q.; Yang, Z. X.; Li, G. S.; Song, L.; Ma, C.

2016-08-01

The conversion efficiency of wind energy is the focus of researches and concerns as one of the renewable energy. The present methods of enhancing the conversion efficiency are mostly improving the wind rotor structure, optimizing the generator parameters and energy storage controller and so on. Because the conversion process involves in energy conversion of multi-energy fields such as wind energy, mechanical energy and electrical energy, the coupling effect between them will influence the overall conversion efficiency. In this paper, using system integration analysis technology, a testing system based on multi-energy field coupling (MEFC) of vertical axis wind power system is proposed. When the maximum efficiency of wind rotor is satisfied, it can match to the generator function parameters according to the output performance of wind rotor. The voltage controller can transform the unstable electric power to the battery on the basis of optimizing the parameters such as charging times, charging voltage. Through the communication connection and regulation of the upper computer system (UCS), it can make the coupling parameters configure to an optimal state, and it improves the overall conversion efficiency. This method can test the whole wind turbine (WT) performance systematically and evaluate the design parameters effectively. It not only provides a testing method for system structure design and parameter optimization of wind rotor, generator and voltage controller, but also provides a new testing method for the whole performance optimization of vertical axis wind energy conversion system (WECS).

Modeling and Optimization of Class-E Amplifier at Subnominal Condition in a Wireless Power Transfer System for Biomedical Implants.

PubMed

Liu, Hao; Shao, Qi; Fang, Xuelin

2017-02-01

For the class-E amplifier in a wireless power transfer (WPT) system, the design parameters are always determined by the nominal model. However, this model neglects the conduction loss and voltage stress of MOSFET and cannot guarantee the highest efficiency in the WPT system for biomedical implants. To solve this problem, this paper proposes a novel circuit model of the subnominal class-E amplifier. On a WPT platform for capsule endoscope, the proposed model was validated to be effective and the relationship between the amplifier's design parameters and its characteristics was analyzed. At a given duty ratio, the design parameters with the highest efficiency and safe voltage stress are derived and the condition is called 'optimal subnominal condition.' The amplifier's efficiency can reach the highest of 99.3% at the 0.097 duty ratio. Furthermore, at the 0.5 duty ratio, the measured efficiency of the optimal subnominal condition can reach 90.8%, which is 15.2% higher than that of the nominal condition. Then, a WPT experiment with a receiving unit was carried out to validate the feasibility of the optimized amplifier. In general, the design parameters of class-E amplifier in a WPT system for biomedical implants can be determined with the proposed optimization method in this paper.

[Imaging center - optimization of the imaging process].

PubMed

Busch, H-P

2013-04-01

Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

R&D 100, 2016: Pyomo 4.0 – Python Optimization Modeling Objects

ScienceCinema

Hart, William; Laird, Carl; Siirola, John

2018-06-13

Pyomo provides a rich software environment for formulating and analyzing optimization applications. Pyomo supports the algebraic specification of complex sets of objectives and constraints, which enables optimization solvers to exploit problem structure to efficiently perform optimization.

Structural efficiency studies of corrugated compression panels with curved caps and beaded webs

NASA Technical Reports Server (NTRS)

Davis, R. C.; Mills, C. T.; Prabhakaran, R.; Jackson, L. R.

1984-01-01

Curved cross-sectional elements are employed in structural concepts for minimum-mass compression panels. Corrugated panel concepts with curved caps and beaded webs are optimized by using a nonlinear mathematical programming procedure and a rigorous buckling analysis. These panel geometries are shown to have superior structural efficiencies compared with known concepts published in the literature. Fabrication of these efficient corrugation concepts became possible by advances made in the art of superplastically forming of metals. Results of the mass optimization studies of the concepts are presented as structural efficiency charts for axial compression.

Overcoming the Fundamental Bottlenecks to a new world-record silicon solar cell. Final Technical Report

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

Rohatgi, Ajeet; Zimbardi, Francesco; Rounsaville, Brian

The objective of the work performed within this contract is to reveal the materials and device physics that currently limit the experimental world record efficiency to 25% for single junction Si (2013), and to demonstrate 26.5% efficiency. The starting efficiency for this project was 23.9% in 2013. Four strategies are being combined throughout the project to achieve 26.5% cell efficiency: (1) passivated contacts via tunnel dielectrics, (2) emitter optimization and passivation through dopant profile engineering, (3) enhanced light trapping through development of photonic crystals and (4) base optimization.

Theoretical and experimental investigations on the optimal match between compressor and cold finger of the Stirling-type pulse tube cryocooler

NASA Astrophysics Data System (ADS)

Dang, Haizheng; Tan, Jun; Zhang, Lei

2016-06-01

The match between the pulse tube cold finger (PTCF) and the linear compressor of the Stirling-type pulse tube cryocooler plays a vital role in optimizing the compressor efficiency and in improving the PTCF cooling performance as well. In this paper, the interaction of them has been analyzed in a detailed way to reveal the match mechanism, and systematic investigations on the two-way matching have been conducted. The design method of the PTCF to achieve the optimal matching for the given compressor and the counterpart design method of the compressor to achieve the optimal matching for the given PTCF are put forward. Specific experiments are then carried out to verify the conducted theoretical analyses and modeling. For a given linear compressor, a new in-line PTCF which seeks to achieve the optimal match is simulated, designed and tested. And for a given coaxial PTCF, a new dual-opposed moving-coil linear compressor is also developed to match with it. The simulated and experimental results are compared, and fairly good agreements are found between them in both cases. The matched in-line cooler with the newly-designed PTCF has capacities of 4-11.84 W at 80 K with higher than 17% of Carnot efficiency and the mean motor efficiency of 81.5%, and the matched coaxial cooler with the new-designed compressor can provide 2-5.5 W at 60 K with higher than 9.6% of Carnot efficiency and the mean motor efficiency of 83%, which verify the validity of the theoretical investigations on the optimal match and the proposed design methods.

Swarm size and iteration number effects to the performance of PSO algorithm in RFID tag coverage optimization

NASA Astrophysics Data System (ADS)

Prathabrao, M.; Nawawi, Azli; Sidek, Noor Azizah

2017-04-01

Radio Frequency Identification (RFID) system has multiple benefits which can improve the operational efficiency of the organization. The advantages are the ability to record data systematically and quickly, reducing human errors and system errors, update the database automatically and efficiently. It is often more readers (reader) is needed for the installation purposes in RFID system. Thus, it makes the system more complex. As a result, RFID network planning process is needed to ensure the RFID system works perfectly. The planning process is also considered as an optimization process and power adjustment because the coordinates of each RFID reader to be determined. Therefore, algorithms inspired by the environment (Algorithm Inspired by Nature) is often used. In the study, PSO algorithm is used because it has few number of parameters, the simulation time is fast, easy to use and also very practical. However, PSO parameters must be adjusted correctly, for robust and efficient usage of PSO. Failure to do so may result in disruption of performance and results of PSO optimization of the system will be less good. To ensure the efficiency of PSO, this study will examine the effects of two parameters on the performance of PSO Algorithm in RFID tag coverage optimization. The parameters to be studied are the swarm size and iteration number. In addition to that, the study will also recommend the most optimal adjustment for both parameters that is, 200 for the no. iterations and 800 for the no. of swarms. Finally, the results of this study will enable PSO to operate more efficiently in order to optimize RFID network planning system.

Exergy as a useful tool for the performance assessment of aircraft gas turbine engines: A key review

NASA Astrophysics Data System (ADS)

Şöhret, Yasin; Ekici, Selcuk; Altuntaş, Önder; Hepbasli, Arif; Karakoç, T. Hikmet

2016-05-01

It is known that aircraft gas turbine engines operate according to thermodynamic principles. Exergy is considered a very useful tool for assessing machines working on the basis of thermodynamics. In the current study, exergy-based assessment methodologies are initially explained in detail. A literature overview is then presented. According to the literature overview, turbofans may be described as the most investigated type of aircraft gas turbine engines. The combustion chamber is found to be the most irreversible component, and the gas turbine component needs less exergetic improvement compared to all other components of an aircraft gas turbine engine. Finally, the need for analyses of exergy, exergo-economic, exergo-environmental and exergo-sustainability for aircraft gas turbine engines is emphasized. A lack of agreement on exergy analysis paradigms and assumptions is noted by the authors. Exergy analyses of aircraft gas turbine engines, fed with conventional fuel as well as alternative fuel using advanced exergy analysis methodology to understand the interaction among components, are suggested to those interested in thermal engineering, aerospace engineering and environmental sciences.

Comparing kinetic curves in liquid chromatography

NASA Astrophysics Data System (ADS)

Kurganov, A. A.; Kanat'eva, A. Yu.; Yakubenko, E. E.; Popova, T. P.; Shiryaeva, V. E.

2017-01-01

Five equations for kinetic curves which connect the number of theoretical plates N and time of analysis t 0 for five different versions of optimization, depending on the parameters being varied (e.g., mobile phase flow rate, pressure drop, sorbent grain size), are obtained by means of mathematical modeling. It is found that a method based on the optimization of a sorbent grain size at fixed pressure is most suitable for the optimization of rapid separations. It is noted that the advantages of the method are limited by an area of relatively low efficiency, and the advantage of optimization is transferred to a method based on the optimization of both the sorbent grain size and the drop in pressure across a column in the area of high efficiency.

Design and Optimization of Composite Gyroscope Momentum Wheel Rings

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2007-01-01

Stress analysis and preliminary design/optimization procedures are presented for gyroscope momentum wheel rings composed of metallic, metal matrix composite, and polymer matrix composite materials. The design of these components involves simultaneously minimizing both true part volume and mass, while maximizing angular momentum. The stress analysis results are combined with an anisotropic failure criterion to formulate a new sizing procedure that provides considerable insight into the design of gyroscope momentum wheel ring components. Results compare the performance of two optimized metallic designs, an optimized SiC/Ti composite design, and an optimized graphite/epoxy composite design. The graphite/epoxy design appears to be far superior to the competitors considered unless a much greater premium is placed on volume efficiency compared to mass efficiency.

Multiobjective evolutionary optimization of water distribution systems: Exploiting diversity with infeasible solutions.

PubMed

Tanyimboh, Tiku T; Seyoum, Alemtsehay G

2016-12-01

This article investigates the computational efficiency of constraint handling in multi-objective evolutionary optimization algorithms for water distribution systems. The methodology investigated here encourages the co-existence and simultaneous development including crossbreeding of subpopulations of cost-effective feasible and infeasible solutions based on Pareto dominance. This yields a boundary search approach that also promotes diversity in the gene pool throughout the progress of the optimization by exploiting the full spectrum of non-dominated infeasible solutions. The relative effectiveness of small and moderate population sizes with respect to the number of decision variables is investigated also. The results reveal the optimization algorithm to be efficient, stable and robust. It found optimal and near-optimal solutions reliably and efficiently. The real-world system based optimization problem involved multiple variable head supply nodes, 29 fire-fighting flows, extended period simulation and multiple demand categories including water loss. The least cost solutions found satisfied the flow and pressure requirements consistently. The best solutions achieved indicative savings of 48.1% and 48.2% based on the cost of the pipes in the existing network, for populations of 200 and 1000, respectively. The population of 1000 achieved slightly better results overall. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

A transmission power optimization with a minimum node degree for energy-efficient wireless sensor networks with full-reachability.

PubMed

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-03-20

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

PubMed Central

Chen, Yi-Ting; Horng, Mong-Fong; Lo, Chih-Cheng; Chu, Shu-Chuan; Pan, Jeng-Shyang; Liao, Bin-Yih

2013-01-01

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments. PMID:23519351

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography.

PubMed

Prakash, Jaya; Yalavarthy, Phaneendra K

2013-03-01

Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time.

Optimizing the wireless power transfer over MIMO Channels

NASA Astrophysics Data System (ADS)

Wiedmann, Karsten; Weber, Tobias

2017-09-01

In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.

PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

PubMed Central

Chen, Shuangqing; Wei, Lixin; Guan, Bing

2018-01-01

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems. PMID:29675036

High-Efficiency Nonfullerene Polymer Solar Cell Enabling by Integration of Film-Morphology Optimization, Donor Selection, and Interfacial Engineering.

PubMed

Zhang, Xin; Li, Weiping; Yao, Jiannian; Zhan, Chuanlang

2016-06-22

Carrier mobility is a vital factor determining the electrical performance of organic solar cells. In this paper we report that a high-efficiency nonfullerene organic solar cell (NF-OSC) with a power conversion efficiency of 6.94 ± 0.27% was obtained by optimizing the hole and electron transportations via following judicious selection of polymer donor and engineering of film-morphology and cathode interlayers: (1) a combination of solvent annealing and solvent vapor annealing optimizes the film morphology and hence both hole and electron mobilities, leading to a trade-off of fill factor and short-circuit current density (Jsc); (2) the judicious selection of polymer donor affords a higher hole and electron mobility, giving a higher Jsc; and (3) engineering the cathode interlayer affords a higher electron mobility, which leads to a significant increase in electrical current generation and ultimately the power conversion efficiency (PCE).

Nanoethosomes mediated transdermal delivery of vinpocetine for management of Alzheimer's disease.

PubMed

Moghaddam, Atefeh Afshar; Aqil, Mohd; Ahmad, Farhan J; Ali, Mushir M; Sultana, Yasmin; Ali, Asgar

2015-12-01

To develop and statistically optimize nanoethosomal formulation for transdermal delivery of vinpocetine as an anti-Alzheimer's drug. Box-Behnken experimental design was applied for optimization of nanoethosomes. The independent variables were phospholipid (X 1 ), Tween 80 (X 2 ) and Ethanol (X 3 ) while entrapment efficiency (Y 1 ), particle sizes (Y 2 ), elasticity (Y 3 ) and flux (Y 4 ) were the dependent variables. Optimized nanoethosomal vinpocetine formulation with mean particle size 50.57 ± 26.11 nm showed 97.51 ± 0.86% entrapment efficiency, achieved mean transdermal flux 925.60 ± 39.80 µg/cm 2 /h and elasticity of 86.61 ± 2.88. Ex-vivo study of nanoethosomal formulation showed a significant increase flux and entrapment efficiency compared with control vinpocetine solution. Our results suggest that nanoethosome is an efficient carrier for transdermal delivery of vinpocetine as compared to its oral form.

Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-11-01

Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

Disorder-assisted quantum transport in suboptimal decoherence regimes

PubMed Central

Novo, Leonardo; Mohseni, Masoud; Omar, Yasser

2016-01-01

We investigate quantum transport in binary tree structures and in hypercubes for the disordered Frenkel-exciton Hamiltonian under pure dephasing noise. We compute the energy transport efficiency as a function of disorder and dephasing rates. We demonstrate that dephasing improves transport efficiency not only in the disordered case, but also in the ordered one. The maximal transport efficiency is obtained when the dephasing timescale matches the hopping timescale, which represent new examples of the Goldilocks principle at the quantum scale. Remarkably, we find that in weak dephasing regimes, away from optimal levels of environmental fluctuations, the average effect of increasing disorder is to improve the transport efficiency until an optimal value for disorder is reached. Our results suggest that rational design of the site energies statistical distributions could lead to better performances in transport systems at nanoscale when their natural environments are far from the optimal dephasing regime. PMID:26726133

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%.

Fluorination-enabled optimal morphology leads to over 11% efficiency for inverted small-molecule organic solar cells

PubMed Central

Deng, Dan; Zhang, Yajie; Zhang, Jianqi; Wang, Zaiyu; Zhu, Lingyun; Fang, Jin; Xia, Benzheng; Wang, Zhen; Lu, Kun; Ma, Wei; Wei, Zhixiang

2016-01-01

Solution-processable small molecules for organic solar cells have attracted intense attention for their advantages of definite molecular structures compared with their polymer counterparts. However, the device efficiencies based on small molecules are still lower than those of polymers, especially for inverted devices, the highest efficiency of which is <9%. Here we report three novel solution-processable small molecules, which contain π-bridges with gradient-decreased electron density and end acceptors substituted with various fluorine atoms (0F, 1F and 2F, respectively). Fluorination leads to an optimal active layer morphology, including an enhanced domain purity, the formation of hierarchical domain size and a directional vertical phase gradation. The optimal morphology balances charge separation and transfer, and facilitates charge collection. As a consequence, fluorinated molecules exhibit excellent inverted device performance, and an average power conversion efficiency of 11.08% is achieved for a two-fluorine atom substituted molecule. PMID:27991486

Stability of glassy hierarchical networks

NASA Astrophysics Data System (ADS)

Zamani, M.; Camargo-Forero, L.; Vicsek, T.

2018-02-01

The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

Nash equilibrium and multi criterion aerodynamic optimization

NASA Astrophysics Data System (ADS)

Tang, Zhili; Zhang, Lianhe

2016-06-01

Game theory and its particular Nash Equilibrium (NE) are gaining importance in solving Multi Criterion Optimization (MCO) in engineering problems over the past decade. The solution of a MCO problem can be viewed as a NE under the concept of competitive games. This paper surveyed/proposed four efficient algorithms for calculating a NE of a MCO problem. Existence and equivalence of the solution are analyzed and proved in the paper based on fixed point theorem. Specific virtual symmetric Nash game is also presented to set up an optimization strategy for single objective optimization problems. Two numerical examples are presented to verify proposed algorithms. One is mathematical functions' optimization to illustrate detailed numerical procedures of algorithms, the other is aerodynamic drag reduction of civil transport wing fuselage configuration by using virtual game. The successful application validates efficiency of algorithms in solving complex aerodynamic optimization problem.

Optimal slew path planning for the Sino-French Space-based multiband astronomical Variable Objects Monitor mission

NASA Astrophysics Data System (ADS)

She, Yuchen; Li, Shuang

2018-01-01

The planning algorithm to calculate a satellite's optimal slew trajectory with a given keep-out constraint is proposed. An energy-optimal formulation is proposed for the Space-based multiband astronomical Variable Objects Monitor Mission Analysis and Planning (MAP) system. The innovative point of the proposed planning algorithm lies in that the satellite structure and control limitation are not considered as optimization constraints but are formulated into the cost function. This modification is able to relieve the burden of the optimizer and increases the optimization efficiency, which is the major challenge for designing the MAP system. Mathematical analysis is given to prove that there is a proportional mapping between the formulation and the satellite controller output. Simulations with different scenarios are given to demonstrate the efficiency of the developed algorithm.

Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.

NASA Astrophysics Data System (ADS)

Velichkin, Vladimir A.; Zavyalov, Vladimir A.

2018-03-01

This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

An optimized proportional-derivative controller for the human upper extremity with gravity.

PubMed

Jagodnik, Kathleen M; Blana, Dimitra; van den Bogert, Antonie J; Kirsch, Robert F

2015-10-15

When Functional Electrical Stimulation (FES) is used to restore movement in subjects with spinal cord injury (SCI), muscle stimulation patterns should be selected to generate accurate and efficient movements. Ideally, the controller for such a neuroprosthesis will have the simplest architecture possible, to facilitate translation into a clinical setting. In this study, we used the simulated annealing algorithm to optimize two proportional-derivative (PD) feedback controller gain sets for a 3-dimensional arm model that includes musculoskeletal dynamics and has 5 degrees of freedom and 22 muscles, performing goal-oriented reaching movements. Controller gains were optimized by minimizing a weighted sum of position errors, orientation errors, and muscle activations. After optimization, gain performance was evaluated on the basis of accuracy and efficiency of reaching movements, along with three other benchmark gain sets not optimized for our system, on a large set of dynamic reaching movements for which the controllers had not been optimized, to test ability to generalize. Robustness in the presence of weakened muscles was also tested. The two optimized gain sets were found to have very similar performance to each other on all metrics, and to exhibit significantly better accuracy, compared with the three standard gain sets. All gain sets investigated used physiologically acceptable amounts of muscular activation. It was concluded that optimization can yield significant improvements in controller performance while still maintaining muscular efficiency, and that optimization should be considered as a strategy for future neuroprosthesis controller design. Published by Elsevier Ltd.

Application of rotatable central composite design in the preparation and optimization of poly(lactic-co-glycolic acid) nanoparticles for controlled delivery of paclitaxel.

PubMed

Kollipara, Sivacharan; Bende, Girish; Movva, Snehalatha; Saha, Ranendra

2010-11-01

Polymeric carrier systems of paclitaxel (PCT) offer advantages over only available formulation Taxol® in terms of enhancing therapeutic efficacy and eliminating adverse effects. The objective of the present study was to prepare poly (lactic-co-glycolic acid) nanoparticles containing PCT using emulsion solvent evaporation technique. Critical factors involved in the processing method were identified and optimized by scientific, efficient rotatable central composite design aiming at low mean particle size and high entrapment efficiency. Twenty different experiments were designed and each formulation was evaluated for mean particle size and entrapment efficiency. The optimized formulation was evaluated for in vitro drug release, and absorption characteristics were studied using in situ rat intestinal permeability study. Amount of polymer and duration of ultrasonication were found to have significant effect on mean particle size and entrapment efficiency. First-order interactions of amount of miglyol with amount of polymer were significant in case of mean particle size, whereas second-order interactions of polymer were significant in mean particle size and entrapment efficiency. The developed quadratic model showed high correlation (R(2) > 0.85) between predicted response and studied factors. The optimized formulation had low mean particle size (231.68 nm) and high entrapment efficiency (95.18%) with 4.88% drug content. The optimized formulation showed controlled release of PCT for more than 72 hours. In situ absorption study showed faster and enhanced extent of absorption of PCT from nanoparticles compared to pure drug. The poly (lactic-co-glycolic acid) nanoparticles containing PCT may be of clinical importance in enhancing its oral bioavailability.

Modeling stomatal conductance in the Earth system: linking leaf water-use efficiency and water transport along the soil-plant-atmosphere continuum

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Williams, M.; Fisher, R. A.; Oleson, K. W.

2014-05-01

The empirical Ball-Berry stomatal conductance model is commonly used in Earth system models to simulate biotic regulation of evapotranspiration. However, the dependence of stomatal conductance (gs) on vapor pressure deficit (Ds) and soil moisture must both be empirically parameterized. We evaluated the Ball-Berry model used in the Community Land Model version 4.5 (CLM4.5) and an alternative stomatal conductance model that links leaf gas exchange, plant hydraulic constraints, and the soil-plant-atmosphere continuum (SPA) to numerically optimize photosynthetic carbon gain per unit water loss while preventing leaf water potential dropping below a critical minimum level. We evaluated two alternative optimization algorithms: intrinsic water-use efficiency (Δ An/Δ gs, the marginal carbon gain of stomatal opening) and water-use efficiency (Δ An/Δ El, the marginal carbon gain of water loss). We implemented the stomatal models in a multi-layer plant canopy model, to resolve profiles of gas exchange, leaf water potential, and plant hydraulics within the canopy, and evaluated the simulations using: (1) leaf analyses; (2) canopy net radiation, sensible heat flux, latent heat flux, and gross primary production at six AmeriFlux sites spanning 51 site-years; and (3) parameter sensitivity analyses. Without soil moisture stress, the performance of the SPA stomatal conductance model was generally comparable to or somewhat better than the Ball-Berry model in flux tower simulations, but was significantly better than the Ball-Berry model when there was soil moisture stress. Functional dependence of gs on soil moisture emerged from the physiological theory linking leaf water-use efficiency and water flow to and from the leaf along the soil-to-leaf pathway rather than being imposed a priori, as in the Ball-Berry model. Similar functional dependence of gs on Ds emerged from the water-use efficiency optimization. Sensitivity analyses showed that two parameters (stomatal efficiency and root hydraulic conductivity) minimized errors with the SPA stomatal conductance model. The critical stomatal efficiency for optimization (ι) was estimated from leaf trait datasets and is related to the slope parameter (g1) of the Ball-Berry model. The optimized parameter value was consistent with this estimate. Optimized root hydraulic conductivity was consistent with estimates from literature surveys. The two central concepts embodied in the stomatal model, that plants account for both water-use efficiency and for hydraulic safety in regulating stomatal conductance, imply a notion of optimal plant strategies and provide testable model hypotheses, rather than empirical descriptions of plant behavior.

The admissible portfolio selection problem with transaction costs and an improved PSO algorithm

NASA Astrophysics Data System (ADS)

Chen, Wei; Zhang, Wei-Guo

2010-05-01

In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.

Design and Optimization Method of a Two-Disk Rotor System

NASA Astrophysics Data System (ADS)

Huang, Jingjing; Zheng, Longxi; Mei, Qing

2016-04-01

An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

An efficient hybrid approach for multiobjective optimization of water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2014-05-01

An efficient hybrid approach for the design of water distribution systems (WDSs) with multiple objectives is described in this paper. The objectives are the minimization of the network cost and maximization of the network resilience. A self-adaptive multiobjective differential evolution (SAMODE) algorithm has been developed, in which control parameters are automatically adapted by means of evolution instead of the presetting of fine-tuned parameter values. In the proposed method, a graph algorithm is first used to decompose a looped WDS into a shortest-distance tree (T) or forest, and chords (Ω). The original two-objective optimization problem is then approximated by a series of single-objective optimization problems of the T to be solved by nonlinear programming (NLP), thereby providing an approximate Pareto optimal front for the original whole network. Finally, the solutions at the approximate front are used to seed the SAMODE algorithm to find an improved front for the original entire network. The proposed approach is compared with two other conventional full-search optimization methods (the SAMODE algorithm and the NSGA-II) that seed the initial population with purely random solutions based on three case studies: a benchmark network and two real-world networks with multiple demand loading cases. Results show that (i) the proposed NLP-SAMODE method consistently generates better-quality Pareto fronts than the full-search methods with significantly improved efficiency; and (ii) the proposed SAMODE algorithm (no parameter tuning) exhibits better performance than the NSGA-II with calibrated parameter values in efficiently offering optimal fronts.

Near-optimal response of instantaneous transpiration efficiency to vapour pressure deficit, temperature and [CO2] in cotton (Gossypium hirsutum L.).

USDA-ARS?s Scientific Manuscript database

The instantaneous transpiration efficiency (ITE, the ratio of photosynthesis rate to transpiration) is an important variable for crops, because it ultimately affects dry mass production per unit of plant water lost to the atmosphere. The theory that stomata optimize carbon uptake per unit water used...

Aerodynamic design optimization of a fuel efficient high-performance, single-engine, business airplane

NASA Technical Reports Server (NTRS)

Holmes, B. J.

1980-01-01

A design study has been conducted to optimize a single-engine airplane for a high-performance cruise mission. The mission analyzed included a cruise speed of about 300 knots, a cruise range of about 1300 nautical miles, and a six-passenger payload (5340 N (1200 lb)). The purpose of the study is to investigate the combinations of wing design, engine, and operating altitude required for the mission. The results show that these mission performance characteristics can be achieved with fuel efficiencies competitive with present-day high-performance, single- and twin-engine, business airplanes. It is noted that relaxation of the present Federal Aviation Regulation, Part 23, stall-speed requirement for single-engine airplanes facilitates the optimization of the airplane for fuel efficiency.

Optimization of a Small Scale Linear Reluctance Accelerator

NASA Astrophysics Data System (ADS)

Barrera, Thor; Beard, Robby

2011-11-01

Reluctance accelerators are extremely promising future methods of transportation. Several problems still plague these devices, most prominently low efficiency. Variables to overcoming efficiency problems are many and difficult to correlate how they affect our accelerator. The study examined several differing variables that present potential challenges in optimizing the efficiency of reluctance accelerators. These include coil and projectile design, power supplies, switching, and the elusive gradient inductance problem. Extensive research in these areas has been performed from computational and theoretical to experimental. Findings show that these parameters share significant similarity to transformer design elements, thus general findings show current optimized parameters the research suggests as a baseline for further research and design. Demonstration of these current findings will be offered at the time of presentation.

Using Decision-Analytic Modeling to Isolate Interventions That Are Feasible, Efficient and Optimal: An Application from the Norwegian Cervical Cancer Screening Program.

PubMed

Pedersen, Kine; Sørbye, Sveinung Wergeland; Burger, Emily Annika; Lönnberg, Stefan; Kristiansen, Ivar Sønbø

2015-12-01

Decision makers often need to simultaneously consider multiple criteria or outcomes when deciding whether to adopt new health interventions. Using decision analysis within the context of cervical cancer screening in Norway, we aimed to aid decision makers in identifying a subset of relevant strategies that are simultaneously efficient, feasible, and optimal. We developed an age-stratified probabilistic decision tree model following a cohort of women attending primary screening through one screening round. We enumerated detected precancers (i.e., cervical intraepithelial neoplasia of grade 2 or more severe (CIN2+)), colposcopies performed, and monetary costs associated with 10 alternative triage algorithms for women with abnormal cytology results. As efficiency metrics, we calculated incremental cost-effectiveness, and harm-benefit, ratios, defined as the additional costs, or the additional number of colposcopies, per additional CIN2+ detected. We estimated capacity requirements and uncertainty surrounding which strategy is optimal according to the decision rule, involving willingness to pay (monetary or resources consumed per added benefit). For ages 25 to 33 years, we eliminated four strategies that did not fall on either efficiency frontier, while one strategy was efficient with respect to both efficiency metrics. Compared with current practice in Norway, two strategies detected more precancers at lower monetary costs, but some required more colposcopies. Similar results were found for women aged 34 to 69 years. Improving the effectiveness and efficiency of cervical cancer screening may necessitate additional resources. Although efficient and feasible, both society and individuals must specify their willingness to accept the additional resources and perceived harms required to increase effectiveness before a strategy can be considered optimal. Copyright © 2015. Published by Elsevier Inc.

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).

Energy Efficiency Optimization in Relay-Assisted MIMO Systems With Perfect and Statistical CSI

NASA Astrophysics Data System (ADS)

Zappone, Alessio; Cao, Pan; Jorswieck, Eduard A.

2014-01-01

A framework for energy-efficient resource allocation in a single-user, amplify-and-forward relay-assisted MIMO system is devised in this paper. Previous results in this area have focused on rate maximization or sum power minimization problems, whereas fewer results are available when bits/Joule energy efficiency (EE) optimization is the goal. The performance metric to optimize is the ratio between the system's achievable rate and the total consumed power. The optimization is carried out with respect to the source and relay precoding matrices, subject to QoS and power constraints. Such a challenging non-convex problem is tackled by means of fractional programming and and alternating maximization algorithms, for various CSI assumptions at the source and relay. In particular the scenarios of perfect CSI and those of statistical CSI for either the source-relay or the relay-destination channel are addressed. Moreover, sufficient conditions for beamforming optimality are derived, which is useful in simplifying the system design. Numerical results are provided to corroborate the validity of the theoretical findings.

Panorama parking assistant system with improved particle swarm optimization method

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Upper Limits for Power Yield in Thermal, Chemical, and Electrochemical Systems

NASA Astrophysics Data System (ADS)

Sieniutycz, Stanislaw

2010-03-01

We consider modeling and power optimization of energy converters, such as thermal, solar and chemical engines and fuel cells. Thermodynamic principles lead to expressions for converter's efficiency and generated power. Efficiency equations serve to solve the problems of upgrading or downgrading a resource. Power yield is a cumulative effect in a system consisting of a resource, engines, and an infinite bath. While optimization of steady state systems requires using the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. The primary result of static optimization is the upper limit of power, whereas that of dynamic optimization is a finite-rate counterpart of classical reversible work (exergy). The latter quantity depends on the end state coordinates and a dissipation index, h, which is the Hamiltonian of the problem of minimum entropy production. In reacting systems, an active part of chemical affinity constitutes a major component of the overall efficiency. The theory is also applied to fuel cells regarded as electrochemical flow engines. Enhanced bounds on power yield follow, which are stronger than those predicted by the reversible work potential.

Improving the Performance of PbS Quantum Dot Solar Cells by Optimizing ZnO Window Layer

NASA Astrophysics Data System (ADS)

Yang, Xiaokun; Hu, Long; Deng, Hui; Qiao, Keke; Hu, Chao; Liu, Zhiyong; Yuan, Shengjie; Khan, Jahangeer; Li, Dengbing; Tang, Jiang; Song, Haisheng; Cheng, Chun

2017-04-01

Comparing with hot researches in absorber layer, window layer has attracted less attention in PbS quantum dot solar cells (QD SCs). Actually, the window layer plays a key role in exciton separation, charge drifting, and so on. Herein, ZnO window layer was systematically investigated for its roles in QD SCs performance. The physical mechanism of improved performance was also explored. It was found that the optimized ZnO films with appropriate thickness and doping concentration can balance the optical and electrical properties, and its energy band align well with the absorber layer for efficient charge extraction. Further characterizations demonstrated that the window layer optimization can help to reduce the surface defects, improve the heterojunction quality, as well as extend the depletion width. Compared with the control devices, the optimized devices have obtained an efficiency of 6.7% with an enhanced V oc of 18%, J sc of 21%, FF of 10%, and power conversion efficiency of 58%. The present work suggests a useful strategy to improve the device performance by optimizing the window layer besides the absorber layer.

Inverse design of near unity efficiency perfectly vertical grating couplers

NASA Astrophysics Data System (ADS)

Michaels, Andrew; Yablonovitch, Eli

2018-02-01

Efficient coupling between integrated optical waveguides and optical fibers is essential to the success of integrated photonics. While many solutions exist, perfectly vertical grating couplers which scatter light out of a waveguide in the direction normal to the waveguide's top surface are an ideal candidate due to their potential to reduce packaging complexity. Designing such couplers with high efficiency, however, has proven difficult. In this paper, we use electromagnetic inverse design techniques to optimize a high efficiency two-layer perfectly vertical silicon grating coupler. Our base design achieves a chip-to-fiber coupling efficiency of over 99% (-0.04 dB) at 1550 nm. Using this base design, we apply subsequent constrained optimizations to achieve vertical couplers with over 96% efficiency which are fabricable using a 65 nm process.

Two-level optimization of composite wing structures based on panel genetic optimization

NASA Astrophysics Data System (ADS)

Liu, Boyang

The design of complex composite structures used in aerospace or automotive vehicles presents a major challenge in terms of computational cost. Discrete choices for ply thicknesses and ply angles leads to a combinatorial optimization problem that is too expensive to solve with presently available computational resources. We developed the following methodology for handling this problem for wing structural design: we used a two-level optimization approach with response-surface approximations to optimize panel failure loads for the upper-level wing optimization. We tailored efficient permutation genetic algorithms to the panel stacking sequence design on the lower level. We also developed approach for improving continuity of ply stacking sequences among adjacent panels. The decomposition approach led to a lower-level optimization of stacking sequence with a given number of plies in each orientation. An efficient permutation genetic algorithm (GA) was developed for handling this problem. We demonstrated through examples that the permutation GAs are more efficient for stacking sequence optimization than a standard GA. Repair strategies for standard GA and the permutation GAs for dealing with constraints were also developed. The repair strategies can significantly reduce computation costs for both standard GA and permutation GA. A two-level optimization procedure for composite wing design subject to strength and buckling constraints is presented. At wing-level design, continuous optimization of ply thicknesses with orientations of 0°, 90°, and +/-45° is performed to minimize weight. At the panel level, the number of plies of each orientation (rounded to integers) and inplane loads are specified, and a permutation genetic algorithm is used to optimize the stacking sequence. The process begins with many panel genetic optimizations for a range of loads and numbers of plies of each orientation. Next, a cubic polynomial response surface is fitted to the optimum buckling load. The resulting response surface is used for wing-level optimization. In general, complex composite structures consist of several laminates. A common problem in the design of such structures is that some plies in the adjacent laminates terminate in the boundary between the laminates. These discontinuities may cause stress concentrations and may increase manufacturing difficulty and cost. We developed measures of continuity of two adjacent laminates. We studied tradeoffs between weight and continuity through a simple composite wing design. Finally, we compared the two-level optimization to a single-level optimization based on flexural lamination parameters. The single-level optimization is efficient and feasible for a wing consisting of unstiffened panels.

Displacement based multilevel structural optimization

NASA Technical Reports Server (NTRS)

Striz, Alfred G.

1995-01-01

Multidisciplinary design optimization (MDO) is expected to play a major role in the competitive transportation industries of tomorrow, i.e., in the design of aircraft and spacecraft, of high speed trains, boats, and automobiles. All of these vehicles require maximum performance at minimum weight to keep fuel consumption low and conserve resources. Here, MDO can deliver mathematically based design tools to create systems with optimum performance subject to the constraints of disciplines such as structures, aerodynamics, controls, etc. Although some applications of MDO are beginning to surface, the key to a widespread use of this technology lies in the improvement of its efficiency. This aspect is investigated here for the MDO subset of structural optimization, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures (here, statically indeterminate trusses and beams for proof of concept) is performed. In the system level optimization, the design variables are the coefficients of assumed displacement functions, and the load unbalance resulting from the solution of the stiffness equations is minimized. Constraints are placed on the deflection amplitudes and the weight of the structure. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. This approach is expected to prove very efficient, especially for complex structures, since the design task is broken down into a large number of small and efficiently handled subtasks, each with only a small number of variables. This partitioning will also allow for the use of parallel computing, first, by sending the system and subsystems level computations to two different processors, ultimately, by performing all subsystems level optimizations in a massively parallel manner on separate processors. It is expected that the subsystems level optimizations can be further improved through the use of controlled growth, a method which reduces an optimization to a more efficient analysis with only a slight degradation in accuracy. The efficiency of all proposed techniques is being evaluated relative to the performance of the standard single level optimization approach where the complete structure is weight minimized under the action of all given constraints by one processor and to the performance of simultaneous analysis and design which combines analysis and optimization into a single step. It is expected that the present approach can be expanded to include additional structural constraints (buckling, free and forced vibration, etc.) or other disciplines (passive and active controls, aerodynamics, etc.) for true MDO.

A novel vortex tube-based N2-expander liquefaction process for enhancing the energy efficiency of natural gas liquefaction

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Wei, Feng; Hussain, Arif; Ali, Wahid; Sehee, Oh; Lee, Moonyong

2017-11-01

This research work unfolds a simple, safe, and environment-friendly energy efficient novel vortex tube-based natural gas liquefaction process (LNG). A vortex tube was introduced to the popular N2-expander liquefaction process to enhance the liquefaction efficiency. The process structure and condition were modified and optimized to take a potential advantage of the vortex tube on the natural gas liquefaction cycle. Two commercial simulators ANSYS® and Aspen HYSYS® were used to investigate the application of vortex tube in the refrigeration cycle of LNG process. The Computational fluid dynamics (CFD) model was used to simulate the vortex tube with nitrogen (N2) as a working fluid. Subsequently, the results of the CFD model were embedded in the Aspen HYSYS® to validate the proposed LNG liquefaction process. The proposed natural gas liquefaction process was optimized using the knowledge-based optimization (KBO) approach. The overall energy consumption was chosen as an objective function for optimization. The performance of the proposed liquefaction process was compared with the conventional N2-expander liquefaction process. The vortex tube-based LNG process showed a significant improvement of energy efficiency by 20% in comparison with the conventional N2-expander liquefaction process. This high energy efficiency was mainly due to the isentropic expansion of the vortex tube. It turned out that the high energy efficiency of vortex tube-based process is totally dependent on the refrigerant cold fraction, operating conditions as well as refrigerant cycle configurations.

Efficient Robust Optimization of Metal Forming Processes using a Sequential Metamodel Based Strategy

NASA Astrophysics Data System (ADS)

Wiebenga, J. H.; Klaseboer, G.; van den Boogaard, A. H.

2011-08-01

The coupling of Finite Element (FE) simulations to mathematical optimization techniques has contributed significantly to product improvements and cost reductions in the metal forming industries. The next challenge is to bridge the gap between deterministic optimization techniques and the industrial need for robustness. This paper introduces a new and generally applicable structured methodology for modeling and solving robust optimization problems. Stochastic design variables or noise variables are taken into account explicitly in the optimization procedure. The metamodel-based strategy is combined with a sequential improvement algorithm to efficiently increase the accuracy of the objective function prediction. This is only done at regions of interest containing the optimal robust design. Application of the methodology to an industrial V-bending process resulted in valuable process insights and an improved robust process design. Moreover, a significant improvement of the robustness (>2σ) was obtained by minimizing the deteriorating effects of several noise variables. The robust optimization results demonstrate the general applicability of the robust optimization strategy and underline the importance of including uncertainty and robustness explicitly in the numerical optimization procedure.

Optimal designs based on the maximum quasi-likelihood estimator

PubMed Central

Shen, Gang; Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We use optimal design theory and construct locally optimal designs based on the maximum quasi-likelihood estimator (MqLE), which is derived under less stringent conditions than those required for the MLE method. We show that the proposed locally optimal designs are asymptotically as efficient as those based on the MLE when the error distribution is from an exponential family, and they perform just as well or better than optimal designs based on any other asymptotically linear unbiased estimators such as the least square estimator (LSE). In addition, we show current algorithms for finding optimal designs can be directly used to find optimal designs based on the MqLE. As an illustrative application, we construct a variety of locally optimal designs based on the MqLE for the 4-parameter logistic (4PL) model and study their robustness properties to misspecifications in the model using asymptotic relative efficiency. The results suggest that optimal designs based on the MqLE can be easily generated and they are quite robust to mis-specification in the probability distribution of the responses. PMID:28163359

Optimal swimming of a sheet.

PubMed

Montenegro-Johnson, Thomas D; Lauga, Eric

2014-06-01

Propulsion at microscopic scales is often achieved through propagating traveling waves along hairlike organelles called flagella. Taylor's two-dimensional swimming sheet model is frequently used to provide insight into problems of flagellar propulsion. We derive numerically the large-amplitude wave form of the two-dimensional swimming sheet that yields optimum hydrodynamic efficiency: the ratio of the squared swimming speed to the rate-of-working of the sheet against the fluid. Using the boundary element method, we show that the optimal wave form is a front-back symmetric regularized cusp that is 25% more efficient than the optimal sine wave. This optimal two-dimensional shape is smooth, qualitatively different from the kinked form of Lighthill's optimal three-dimensional flagellum, not predicted by small-amplitude theory, and different from the smooth circular-arc-like shape of active elastic filaments.

Bandwidth reduction for video-on-demand broadcasting using secondary content insertion

NASA Astrophysics Data System (ADS)

Golynski, Alexander; Lopez-Ortiz, Alejandro; Poirier, Guillaume; Quimper, Claude-Guy

2005-01-01

An optimal broadcasting scheme under the presence of secondary content (i.e. advertisements) is proposed. The proposed scheme works both for movies encoded in a Constant Bit Rate (CBR) or a Variable Bit Rate (VBR) format. It is shown experimentally that secondary content in movies can make Video-on-Demand (VoD) broadcasting systems more efficient. An efficient algorithm is given to compute the optimal broadcasting schedule with secondary content, which in particular significantly improves over the best previously known algorithm for computing the optimal broadcasting schedule without secondary content.

Energy efficient LED layout optimization for near-uniform illumination

NASA Astrophysics Data System (ADS)

Ali, Ramy E.; Elgala, Hany

2016-09-01

In this paper, we consider the problem of designing energy efficient light emitting diodes (LEDs) layout while satisfying the illumination constraints. Towards this objective, we present a simple approach to the illumination design problem based on the concept of the virtual LED. We formulate a constrained optimization problem for minimizing the power consumption while maintaining a near-uniform illumination throughout the room. By solving the resulting constrained linear program, we obtain the number of required LEDs and the optimal output luminous intensities that achieve the desired illumination constraints.

Optimizing Ligand Efficiency of Selective Androgen Receptor Modulators (SARMs)

PubMed Central

2015-01-01

A series of selective androgen receptor modulators (SARMs) containing the 1-(trifluoromethyl)benzyl alcohol core have been optimized for androgen receptor (AR) potency and drug-like properties. We have taken advantage of the lipophilic ligand efficiency (LLE) parameter as a guide to interpret the effect of structural changes on AR activity. Over the course of optimization efforts the LLE increased over 3 log units leading to a SARM 43 with nanomolar potency, good aqueous kinetic solubility (>700 μM), and high oral bioavailability in rats (83%). PMID:26819671

Efficient Transition State Optimization of Periodic Structures through Automated Relaxed Potential Energy Surface Scans.

PubMed

Plessow, Philipp N

2018-02-13

This work explores how constrained linear combinations of bond lengths can be used to optimize transition states in periodic structures. Scanning of constrained coordinates is a standard approach for molecular codes with localized basis functions, where a full set of internal coordinates is used for optimization. Common plane wave-codes for periodic boundary conditions almost exlusively rely on Cartesian coordinates. An implementation of constrained linear combinations of bond lengths with Cartesian coordinates is described. Along with an optimization of the value of the constrained coordinate toward the transition states, this allows transition optimization within a single calculation. The approach is suitable for transition states that can be well described in terms of broken and formed bonds. In particular, the implementation is shown to be effective and efficient in the optimization of transition states in zeolite-catalyzed reactions, which have high relevance in industrial processes.

On optimal infinite impulse response edge detection filters

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1991-01-01

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

Towards high efficiency heliostat fields

NASA Astrophysics Data System (ADS)

Arbes, Florian; Wöhrbach, Markus; Gebreiter, Daniel; Weinrebe, Gerhard

2017-06-01

CSP power plants have great potential to substantially contribute to world energy supply. To set this free, cost reductions are required for future projects. Heliostat field layout optimization offers a great opportunity to improve field efficiency. Field efficiency primarily depends on the positions of the heliostats around the tower, commonly known as the heliostat field layout. Heliostat shape also influences efficiency. Improvements to optical efficiency results in electricity cost reduction without adding any extra technical complexity. Due to computational challenges heliostat fields are often arranged in patterns. The mathematical models of the radial staggered or spiral patterns are based on two parameters and thus lead to uniform patterns. Optical efficiencies of a heliostat field do not change uniformly with the distance to the tower, they even differ in the northern and southern field. A fixed pattern is not optimal in many parts of the heliostat field, especially when used as large scaled heliostat field. In this paper, two methods are described which allow to modify field density suitable to inconsistent field efficiencies. A new software for large scale heliostat field evaluation is presented, it allows for fast optimizations of several parameters for pattern modification routines. It was used to design a heliostat field with 23,000 heliostats, which is currently planned for a site in South Africa.

Holograms for power-efficient excitation of optical surface waves

NASA Astrophysics Data System (ADS)

Ignatov, Anton I.; Merzlikin, Alexander M.

2018-02-01

A method for effective excitation of optical surface waves based on holography principles has been proposed. For a particular example of excitation of a plasmonic wave in a dielectric layer on metal the efficiency of proposed volume holograms in the dielectric layer has been analyzed in comparison with optimized periodic gratings in the dielectric layer. Conditions when the holograms are considerably more efficient than the gratings have been found out. In addition, holograms recorded in two iterations have been proposed and studied. Such holograms are substantially more efficient than the optimized periodic gratings for all incidence angles of an exciting Gaussian beam. The proposed method is universal: it can be extended for efficient excitation of different types of optical surface waves and optical waveguide modes.

Flapping wing flight can save aerodynamic power compared to steady flight.

PubMed

Pesavento, Umberto; Wang, Z Jane

2009-09-11

Flapping flight is more maneuverable than steady flight. It is debated whether this advantage is necessarily accompanied by a trade-off in the flight efficiency. Here we ask if any flapping motion exists that is aerodynamically more efficient than the optimal steady motion. We solve the Navier-Stokes equation governing the fluid dynamics around a 2D flapping wing, and determine the minimal aerodynamic power needed to support a specified weight. While most flapping wing motions are more costly than the optimal steady wing motion, we find that optimized flapping wing motions can save up to 27% of the aerodynamic power required by the optimal steady flight. We explain the cause of this energetic advantage.

Multicriteria approaches for a private equity fund

NASA Astrophysics Data System (ADS)

Tammer, Christiane; Tannert, Johannes

2012-09-01

We develop a new model for a Private Equity Fund based on stochastic differential equations. In order to find efficient strategies for the fund manager we formulate a multicriteria optimization problem for a Private Equity Fund. Using the e-constraint method we solve this multicriteria optimization problem. Furthermore, a genetic algorithm is applied in order to get an approximation of the efficient frontier.

Study on key technologies of optimization of big data for thermal power plant performance

NASA Astrophysics Data System (ADS)

Mao, Mingyang; Xiao, Hong

2018-06-01

Thermal power generation accounts for 70% of China's power generation, the pollutants accounted for 40% of the same kind of emissions, thermal power efficiency optimization needs to monitor and understand the whole process of coal combustion and pollutant migration, power system performance data show explosive growth trend, The purpose is to study the integration of numerical simulation of big data technology, the development of thermal power plant efficiency data optimization platform and nitrogen oxide emission reduction system for the thermal power plant to improve efficiency, energy saving and emission reduction to provide reliable technical support. The method is big data technology represented by "multi-source heterogeneous data integration", "large data distributed storage" and "high-performance real-time and off-line computing", can greatly enhance the energy consumption capacity of thermal power plants and the level of intelligent decision-making, and then use the data mining algorithm to establish the boiler combustion mathematical model, mining power plant boiler efficiency data, combined with numerical simulation technology to find the boiler combustion and pollutant generation rules and combustion parameters of boiler combustion and pollutant generation Influence. The result is to optimize the boiler combustion parameters, which can achieve energy saving.

Optimizing luminescent solar concentrator design

DOE PAGES

Hernandez-Noyola, Hermilo; Potterveld, David H.; Holt, Roy J.; ...

2011-12-21

Luminescent Solar Concentrators (LSCs) use fluorescent materials and light guides to convert direct and diffuse sunlight into concentrated wavelength-shifted light that produces electrical power in small photovoltaic (PV) cells with the goal of significantly reducing the cost of solar energy utilization. In this paper we present an optimization analysis based on the implementation of a genetic algorithm (GA) subroutine to a numerical ray-tracing Monte Carlo model of an LSC, SIMSOLAR-P. The initial use of the GA implementation in SIMSOLAR-P is to find the optimal parameters of a hypothetical ‘‘perfect luminescent material’’ that obeys the Kennard Stepanov (K-S) thermodynamic relationship betweenmore » emission and absorption. The optimization balances the efficiency losses in the wavelength shift and PV conversion with the efficiency losses due to re-scattering of light out of the collector. The theoretical limits of efficiency are provided for one, two and three layer configurations; the results show that a single layer configuration is far from optimal and adding a second layer in the LSC with wavelength shifted material in the near infrared region significantly increases the power output, while the gain in power by adding a third layer is relatively small. Here, the results of this study provide a theoretical upper limit to the performance of an LSC and give guidance for the properties required for luminescent materials, such as quantum nanocrystals, to operate efficiently in planar LSC configurations« less

Optimization of storage tank locations in an urban stormwater drainage system using a two-stage approach.

PubMed

Wang, Mingming; Sun, Yuanxiang; Sweetapple, Chris

2017-12-15

Storage is important for flood mitigation and non-point source pollution control. However, to seek a cost-effective design scheme for storage tanks is very complex. This paper presents a two-stage optimization framework to find an optimal scheme for storage tanks using storm water management model (SWMM). The objectives are to minimize flooding, total suspended solids (TSS) load and storage cost. The framework includes two modules: (i) the analytical module, which evaluates and ranks the flooding nodes with the analytic hierarchy process (AHP) using two indicators (flood depth and flood duration), and then obtains the preliminary scheme by calculating two efficiency indicators (flood reduction efficiency and TSS reduction efficiency); (ii) the iteration module, which obtains an optimal scheme using a generalized pattern search (GPS) method based on the preliminary scheme generated by the analytical module. The proposed approach was applied to a catchment in CZ city, China, to test its capability in choosing design alternatives. Different rainfall scenarios are considered to test its robustness. The results demonstrate that the optimal framework is feasible, and the optimization is fast based on the preliminary scheme. The optimized scheme is better than the preliminary scheme for reducing runoff and pollutant loads under a given storage cost. The multi-objective optimization framework presented in this paper may be useful in finding the best scheme of storage tanks or low impact development (LID) controls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Processing technology for high efficiency silicon solar cells

NASA Technical Reports Server (NTRS)

Spitzer, M. B.; Keavney, C. J.

1985-01-01

Recent advances in silicon solar cell processing have led to attainment of conversion efficiency approaching 20%. The basic cell design is investigated and features of greatest importance to achievement of 20% efficiency are indicated. Experiments to separately optimize high efficiency design features in test structures are discussed. The integration of these features in a high efficiency cell is examined. Ion implantation has been used to achieve optimal concentrations of emitter dopant and junction depth. The optimization reflects the trade-off between high sheet conductivity, necessary for high fill factor, and heavy doping effects, which must be minimized for high open circuit voltage. A second important aspect of the design experiments is the development of a passivation process to minimize front surface recombination velocity. The manner in which a thin SiO2 layer may be used for this purpose is indicated without increasing reflection losses, if the antireflection coating is properly designed. Details are presented of processing intended to reduce recombination at the contact/Si interface. Data on cell performance (including CZ and ribbon) and analysis of loss mechanisms are also presented.

[Survival strategy of photosynthetic organisms. 1. Variability of the extent of light-harvesting pigment aggregation as a structural factor optimizing the function of oligomeric photosynthetic antenna. Model calculations].

PubMed

Fetisova, Z G

2004-01-01

In accordance with our concept of rigorous optimization of photosynthetic machinery by a functional criterion, this series of papers continues purposeful search in natural photosynthetic units (PSU) for the basic principles of their organization that we predicted theoretically for optimal model light-harvesting systems. This approach allowed us to determine the basic principles for the organization of a PSU of any fixed size. This series of papers deals with the problem of structural optimization of light-harvesting antenna of variable size controlled in vivo by the light intensity during the growth of organisms, which accentuates the problem of antenna structure optimization because optimization requirements become more stringent as the PSU increases in size. In this work, using mathematical modeling for the functioning of natural PSUs, we have shown that the aggregation of pigments of model light-harvesting antenna, being one of universal optimizing factors, furthermore allows controlling the antenna efficiency if the extent of pigment aggregation is a variable parameter. In this case, the efficiency of antenna increases with the size of the elementary antenna aggregate, thus ensuring the high efficiency of the PSU irrespective of its size; i.e., variation in the extent of pigment aggregation controlled by the size of light-harvesting antenna is biologically expedient.

Fast approximation for joint optimization of segmentation, shape, and location priors, and its application in gallbladder segmentation.

PubMed

Saito, Atsushi; Nawano, Shigeru; Shimizu, Akinobu

2017-05-01

This paper addresses joint optimization for segmentation and shape priors, including translation, to overcome inter-subject variability in the location of an organ. Because a simple extension of the previous exact optimization method is too computationally complex, we propose a fast approximation for optimization. The effectiveness of the proposed approximation is validated in the context of gallbladder segmentation from a non-contrast computed tomography (CT) volume. After spatial standardization and estimation of the posterior probability of the target organ, simultaneous optimization of the segmentation, shape, and location priors is performed using a branch-and-bound method. Fast approximation is achieved by combining sampling in the eigenshape space to reduce the number of shape priors and an efficient computational technique for evaluating the lower bound. Performance was evaluated using threefold cross-validation of 27 CT volumes. Optimization in terms of translation of the shape prior significantly improved segmentation performance. The proposed method achieved a result of 0.623 on the Jaccard index in gallbladder segmentation, which is comparable to that of state-of-the-art methods. The computational efficiency of the algorithm is confirmed to be good enough to allow execution on a personal computer. Joint optimization of the segmentation, shape, and location priors was proposed, and it proved to be effective in gallbladder segmentation with high computational efficiency.

Balanced Codon Usage Optimizes Eukaryotic Translational Efficiency

PubMed Central

Qian, Wenfeng; Yang, Jian-Rong; Pearson, Nathaniel M.; Maclean, Calum; Zhang, Jianzhi

2012-01-01

Cellular efficiency in protein translation is an important fitness determinant in rapidly growing organisms. It is widely believed that synonymous codons are translated with unequal speeds and that translational efficiency is maximized by the exclusive use of rapidly translated codons. Here we estimate the in vivo translational speeds of all sense codons from the budding yeast Saccharomyces cerevisiae. Surprisingly, preferentially used codons are not translated faster than unpreferred ones. We hypothesize that this phenomenon is a result of codon usage in proportion to cognate tRNA concentrations, the optimal strategy in enhancing translational efficiency under tRNA shortage. Our predicted codon–tRNA balance is indeed observed from all model eukaryotes examined, and its impact on translational efficiency is further validated experimentally. Our study reveals a previously unsuspected mechanism by which unequal codon usage increases translational efficiency, demonstrates widespread natural selection for translational efficiency, and offers new strategies to improve synthetic biology. PMID:22479199

Social networks in primates: smart and tolerant species have more efficient networks.

PubMed

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J J; Pelé, Marie; Bergstrom, Mackenzie L; Borgeaud, Christèle; Brosnan, Sarah F; Crofoot, Margaret C; Fedigan, Linda M; Fichtel, Claudia; Hopper, Lydia M; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-12-23

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.

Social networks in primates: smart and tolerant species have more efficient networks

PubMed Central

Pasquaretta, Cristian; Levé, Marine; Claidière, Nicolas; van de Waal, Erica; Whiten, Andrew; MacIntosh, Andrew J. J.; Pelé, Marie; Bergstrom, Mackenzie L.; Borgeaud, Christèle; Brosnan, Sarah F.; Crofoot, Margaret C.; Fedigan, Linda M.; Fichtel, Claudia; Hopper, Lydia M.; Mareno, Mary Catherine; Petit, Odile; Schnoell, Anna Viktoria; di Sorrentino, Eugenia Polizzi; Thierry, Bernard; Tiddi, Barbara; Sueur, Cédric

2014-01-01

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities. PMID:25534964

Optimal design study of high efficiency indium phosphide space solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

Recently indium phosphide solar cells have achieved beginning of life AMO efficiencies in excess of 19 pct. at 25 C. The high efficiency prospects along with superb radiation tolerance make indium phosphide a leading material for space power requirements. To achieve cost effectiveness, practical cell efficiencies have to be raised to near theoretical limits and thin film indium phosphide cells need to be developed. The optimal design study is described of high efficiency indium phosphide solar cells for space power applications using the PC-1D computer program. It is shown that cells with efficiencies over 22 pct. AMO at 25 C could be fabricated by achieving proper material and process parameters. It is observed that further improvements in cell material and process parameters could lead to experimental cell efficiencies near theoretical limits. The effect of various emitter and base parameters on cell performance was studied.

Multi-point optimization of recirculation flow type casing treatment in centrifugal compressors

NASA Astrophysics Data System (ADS)

Tun, Min Thaw; Sakaguchi, Daisaku

2016-06-01

High-pressure ratio and wide operating range are highly required for a turbocharger in diesel engines. A recirculation flow type casing treatment is effective for flow range enhancement of centrifugal compressors. Two ring grooves on a suction pipe and a shroud casing wall are connected by means of an annular passage and stable recirculation flow is formed at small flow rates from the downstream groove toward the upstream groove through the annular bypass. The shape of baseline recirculation flow type casing is modified and optimized by using a multi-point optimization code with a metamodel assisted evolutionary algorithm embedding a commercial CFD code CFX from ANSYS. The numerical optimization results give the optimized design of casing with improving adiabatic efficiency in wide operating flow rate range. Sensitivity analysis of design parameters as a function of efficiency has been performed. It is found that the optimized casing design provides optimized recirculation flow rate, in which an increment of entropy rise is minimized at grooves and passages of the rotating impeller.

An extended continuum model considering optimal velocity change with memory and numerical tests

NASA Astrophysics Data System (ADS)

Qingtao, Zhai; Hongxia, Ge; Rongjun, Cheng

2018-01-01

In this paper, an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory. The new model's stability condition and KdV-Burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis, respectively. Numerical simulation is carried out to study the extended continuum model, which explores how optimal velocity changes with memory affected velocity, density and energy consumption. Numerical results show that when considering the effects of optimal velocity changes with memory, the traffic jams can be suppressed efficiently. Both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently. Furthermore, numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information, which increases the stability of traffic flow on road, and so it improve the traffic flow stability and minimize cars' energy consumptions.

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.

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

NASA Technical Reports Server (NTRS)

2005-01-01

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation. motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

Continuum topology optimization considering uncertainties in load locations based on the cloud model

NASA Astrophysics Data System (ADS)

Liu, Jie; Wen, Guilin

2018-06-01

Few researchers have paid attention to designing structures in consideration of uncertainties in the loading locations, which may significantly influence the structural performance. In this work, cloud models are employed to depict the uncertainties in the loading locations. A robust algorithm is developed in the context of minimizing the expectation of the structural compliance, while conforming to a material volume constraint. To guarantee optimal solutions, sufficient cloud drops are used, which in turn leads to low efficiency. An innovative strategy is then implemented to enormously improve the computational efficiency. A modified soft-kill bi-directional evolutionary structural optimization method using derived sensitivity numbers is used to output the robust novel configurations. Several numerical examples are presented to demonstrate the effectiveness and efficiency of the proposed algorithm.

An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions

NASA Astrophysics Data System (ADS)

Najafi, Amir Abbas; Pourahmadi, Zahra

2016-04-01

Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.

Human motion planning based on recursive dynamics and optimal control techniques

NASA Technical Reports Server (NTRS)

Lo, Janzen; Huang, Gang; Metaxas, Dimitris

2002-01-01

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

Optimal laser wavelength for efficient laser power converter operation over temperature

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

Höhn, O., E-mail: oliver.hoehn@ise.fraunhofer.de; Walker, A. W.; Bett, A. W.

2016-06-13

A temperature dependent modeling study is conducted on a GaAs laser power converter to identify the optimal incident laser wavelength for optical power transmission. Furthermore, the respective temperature dependent maximal conversion efficiencies in the radiative limit as well as in a practically achievable limit are presented. The model is based on the transfer matrix method coupled to a two-diode model, and is calibrated to experimental data of a GaAs photovoltaic device over laser irradiance and temperature. Since the laser wavelength does not strongly influence the open circuit voltage of the laser power converter, the optimal laser wavelength is determined tomore » be in the range where the external quantum efficiency is maximal, but weighted by the photon flux of the laser.« less

Tool path strategy and cutting process monitoring in intelligent machining

NASA Astrophysics Data System (ADS)

Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

2018-06-01

Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

Mode conversion efficiency to Laguerre-Gaussian OAM modes using spiral phase optics.

PubMed

Longman, Andrew; Fedosejevs, Robert

2017-07-24

An analytical model for the conversion efficiency from a TEM 00 mode to an arbitrary Laguerre-Gaussian (LG) mode with null radial index spiral phase optics is presented. We extend this model to include the effects of stepped spiral phase optics, spiral phase optics of non-integer topological charge, and the reduction in conversion efficiency due to broad laser bandwidth. We find that through optimization, an optimal beam waist ratio of the input and output modes exists and is dependent upon the output azimuthal mode number.

Word lengths are optimized for efficient communication.

PubMed

Piantadosi, Steven T; Tily, Harry; Gibson, Edward

2011-03-01

We demonstrate a substantial improvement on one of the most celebrated empirical laws in the study of language, Zipf's 75-y-old theory that word length is primarily determined by frequency of use. In accord with rational theories of communication, we show across 10 languages that average information content is a much better predictor of word length than frequency. This indicates that human lexicons are efficiently structured for communication by taking into account interword statistical dependencies. Lexical systems result from an optimization of communicative pressures, coding meanings efficiently given the complex statistics of natural language use.

Use of nonlinear design optimization techniques in the comparison of battery discharger topologies for the space platform

NASA Technical Reports Server (NTRS)

Sable, Dan M.; Cho, Bo H.; Lee, Fred C.

1990-01-01

A detailed comparison of a boost converter, a voltage-fed, autotransformer converter, and a multimodule boost converter, designed specifically for the space platform battery discharger, is performed. Computer-based nonlinear optimization techniques are used to facilitate an objective comparison. The multimodule boost converter is shown to be the optimum topology at all efficiencies. The margin is greatest at 97 percent efficiency. The multimodule, multiphase boost converter combines the advantages of high efficiency, light weight, and ample margin on the component stresses, thus ensuring high reliability.

Optimization of the Controlled Evaluation of Closed Relational Queries

NASA Astrophysics Data System (ADS)

Biskup, Joachim; Lochner, Jan-Hendrik; Sonntag, Sebastian

For relational databases, controlled query evaluation is an effective inference control mechanism preserving confidentiality regarding a previously declared confidentiality policy. Implementations of controlled query evaluation usually lack efficiency due to costly theorem prover calls. Suitably constrained controlled query evaluation can be implemented efficiently, but is not flexible enough from the perspective of database users and security administrators. In this paper, we propose an optimized framework for controlled query evaluation in relational databases, being efficiently implementable on the one hand and relaxing the constraints of previous approaches on the other hand.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

18.4%-Efficient Heterojunction Si Solar Cells Using Optimized ITO/Top Electrode.

PubMed

Kim, Namwoo; Um, Han-Don; Choi, Inwoo; Kim, Ka-Hyun; Seo, Kwanyong

2016-05-11

We optimize the thickness of a transparent conducting oxide (TCO) layer, and apply a microscale mesh-pattern metal electrode for high-efficiency a-Si/c-Si heterojunction solar cells. A solar cell equipped with the proposed microgrid metal electrode demonstrates a high short-circuit current density (JSC) of 40.1 mA/cm(2), and achieves a high efficiency of 18.4% with an open-circuit voltage (VOC) of 618 mV and a fill factor (FF) of 74.1% as result of the shortened carrier path length and the decreased electrode area of the microgrid metal electrode. Furthermore, by optimizing the process sequence for electrode formation, we are able to effectively restore the reduction in VOC that occurs during the microgrid metal electrode formation process. This work is expected to become a fundamental study that can effectively improve current loss in a-Si/c-Si heterojunction solar cells through the optimization of transparent and metal electrodes.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

Efficient design of gain-flattened multi-pump Raman fiber amplifiers using least squares support vector regression

NASA Astrophysics Data System (ADS)

Chen, Jing; Qiu, Xiaojie; Yin, Cunyi; Jiang, Hao

2018-02-01

An efficient method to design the broadband gain-flattened Raman fiber amplifier with multiple pumps is proposed based on least squares support vector regression (LS-SVR). A multi-input multi-output LS-SVR model is introduced to replace the complicated solving process of the nonlinear coupled Raman amplification equation. The proposed approach contains two stages: offline training stage and online optimization stage. During the offline stage, the LS-SVR model is trained. Owing to the good generalization capability of LS-SVR, the net gain spectrum can be directly and accurately obtained when inputting any combination of the pump wavelength and power to the well-trained model. During the online stage, we incorporate the LS-SVR model into the particle swarm optimization algorithm to find the optimal pump configuration. The design results demonstrate that the proposed method greatly shortens the computation time and enhances the efficiency of the pump parameter optimization for Raman fiber amplifier design.

Testing and Optimizing a Stove-Powered Thermoelectric Generator with Fan Cooling.

PubMed

Zheng, Youqu; Hu, Jiangen; Li, Guoneng; Zhu, Lingyun; Guo, Wenwen

2018-06-07

In order to provide heat and electricity under emergency conditions in off-grid areas, a stove-powered thermoelectric generator (STEG) was designed and optimized. No battery was incorporated, ensuring it would work anytime, anywhere, as long as combustible materials were provided. The startup performance, power load feature and thermoelectric (TE) efficiency were investigated in detail. Furthermore, the heat-conducting plate thickness, cooling fan selection, heat sink dimension and TE module configuration were optimized. The heat flow method was employed to determine the TE efficiency, which was compared to the predicted data. Results showed that the STEG can supply clean-and-warm air (625 W) and electricity (8.25 W at 5 V) continuously at a temperature difference of 148 °C, and the corresponding TE efficiency was measured to be 2.31%. Optimization showed that the choice of heat-conducting plate thickness, heat sink dimensions and cooling fan were inter-dependent, and the TE module configuration affected both the startup process and the power output.

Dense Array Optimization of Cross-Flow Turbines

NASA Astrophysics Data System (ADS)

Scherl, Isabel; Strom, Benjamin; Brunton, Steven; Polagye, Brian

2017-11-01

Cross-flow turbines, where the axis of rotation is perpendicular to the freestream flow, can be used to convert the kinetic energy in wind or water currents to electrical power. By taking advantage of mean and time-resolved wake structures, the optimal density of an array of cross-flow turbines has the potential for higher power output per unit area of land or sea-floor than an equivalent array of axial-flow turbines. In addition, dense arrays in tidal or river channels may be able to further elevate efficiency by exploiting flow confinement and surface proximity. In this work, a two-turbine array is optimized experimentally in a recirculating water channel. The spacing between turbines, as well as individual and coordinated turbine control strategies are optimized. Array efficiency is found to exceed the maximum efficiency for a sparse array (i.e., no interaction between turbines) for stream-wise rotor spacing of less than two diameters. Results are discussed in the context of wake measurements made behind a single rotor.

Application of Box-Behnken design to prepare gentamicin-loaded calcium carbonate nanoparticles.

PubMed

Maleki Dizaj, Solmaz; Lotfipour, Farzaneh; Barzegar-Jalali, Mohammad; Zarrintan, Mohammad-Hossein; Adibkia, Khosro

2016-09-01

The aim of this research was to prepare and optimize calcium carbonate (CaCO3) nanoparticles as carriers for gentamicin sulfate. A chemical precipitation method was used to prepare the gentamicin sulfate-loaded CaCO3 nanoparticles. A 3-factor, 3-level Box-Behnken design was used for the optimization procedure, with the molar ratio of CaCl2: Na2CO3 (X1), the concentration of drug (X2), and the speed of homogenization (X3) as the independent variables. The particle size and entrapment efficiency were considered as response variables. Mathematical equations and response surface plots were used, along with the counter plots, to relate the dependent and independent variables. The results indicated that the speed of homogenization was the main variable contributing to particle size and entrapment efficiency. The combined effect of all three independent variables was also evaluated. Using the response optimization design, the optimized Xl-X3 levels were predicted. An optimized formulation was then prepared according to these levels, resulting in a particle size of 80.23 nm and an entrapment efficiency of 30.80%. It was concluded that the chemical precipitation technique, together with the Box-Behnken experimental design methodology, could be successfully used to optimize the formulation of drug-incorporated calcium carbonate nanoparticles.

An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist.

PubMed

Ishihara, Koji; Morimoto, Jun

2018-03-01

Humans use multiple muscles to generate such joint movements as an elbow motion. With multiple lightweight and compliant actuators, joint movements can also be efficiently generated. Similarly, robots can use multiple actuators to efficiently generate a one degree of freedom movement. For this movement, the desired joint torque must be properly distributed to each actuator. One approach to cope with this torque distribution problem is an optimal control method. However, solving the optimal control problem at each control time step has not been deemed a practical approach due to its large computational burden. In this paper, we propose a computationally efficient method to derive an optimal control strategy for a hybrid actuation system composed of multiple actuators, where each actuator has different dynamical properties. We investigated a singularly perturbed system of the hybrid actuator model that subdivided the original large-scale control problem into smaller subproblems so that the optimal control outputs for each actuator can be derived at each control time step and applied our proposed method to our pneumatic-electric hybrid actuator system. Our method derived a torque distribution strategy for the hybrid actuator by dealing with the difficulty of solving real-time optimal control problems. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Application of Box-Behnken design for preparation of levofloxacin-loaded stearic acid solid lipid nanoparticles for ocular delivery: Optimization, in vitro release, ocular tolerance, and antibacterial activity.

PubMed

Baig, Mirza Salman; Ahad, Abdul; Aslam, Mohammed; Imam, Syed Sarim; Aqil, Mohd; Ali, Asgar

2016-04-01

The aim of the present study was to develop and optimize levofloxacin loaded solid lipid nanoparticles for the treatment of conjunctivitis. Box-Behnken experimental design was applied for optimization of solid lipid nanoparticles. The independent variables were stearic acid as lipid (X1), Tween 80 as surfactant (X2) and sodium deoxycholate as co-surfactant (X3) while particle size (Y1) and entrapment efficiency (Y2) were the dependent variables. Further in vitro release and antibacterial activity in vitro were also performed. The optimized formulation of levofloxacin provides particle size of 237.82 nm and showed 78.71% entrapment efficiency and achieved flux 0.2,493 μg/cm(2)/h across excised goat cornea. In vitro release study showed prolonged drug release from the optimized formulation following Korsmeyer-Peppas model. Antimicrobial study revealed that the developed formulation possesses antibacterial activity against Staphylococcus aureus, and Escherichia coli equivalent to marketed eye drops. HET-CAM test demonstrated that optimized formulation was found to be non-irritant and safe for topical ophthalmic use. Our results concluded that solid lipid nanoparticles are an efficient carrier for ocular delivery of levofloxacin and other drugs. Copyright © 2015 Elsevier B.V. All rights reserved.

A novel rapid and reproducible flow cytometric method for optimization of transfection efficiency in cells

PubMed Central

Homann, Stefanie; Hofmann, Christian; Gorin, Aleksandr M.; Nguyen, Huy Cong Xuan; Huynh, Diana; Hamid, Phillip; Maithel, Neil; Yacoubian, Vahe; Mu, Wenli; Kossyvakis, Athanasios; Sen Roy, Shubhendu; Yang, Otto Orlean

2017-01-01

Transfection is one of the most frequently used techniques in molecular biology that is also applicable for gene therapy studies in humans. One of the biggest challenges to investigate the protein function and interaction in gene therapy studies is to have reliable monospecific detection reagents, particularly antibodies, for all human gene products. Thus, a reliable method that can optimize transfection efficiency based on not only expression of the target protein of interest but also the uptake of the nucleic acid plasmid, can be an important tool in molecular biology. Here, we present a simple, rapid and robust flow cytometric method that can be used as a tool to optimize transfection efficiency at the single cell level while overcoming limitations of prior established methods that quantify transfection efficiency. By using optimized ratios of transfection reagent and a nucleic acid (DNA or RNA) vector directly labeled with a fluorochrome, this method can be used as a tool to simultaneously quantify cellular toxicity of different transfection reagents, the amount of nucleic acid plasmid that cells have taken up during transfection as well as the amount of the encoded expressed protein. Finally, we demonstrate that this method is reproducible, can be standardized and can reliably and rapidly quantify transfection efficiency, reducing assay costs and increasing throughput while increasing data robustness. PMID:28863132

Structural optimization of large structural systems by optimality criteria methods

NASA Technical Reports Server (NTRS)

Berke, Laszlo

1992-01-01

The fundamental concepts of the optimality criteria method of structural optimization are presented. The effect of the separability properties of the objective and constraint functions on the optimality criteria expressions is emphasized. The single constraint case is treated first, followed by the multiple constraint case with a more complex evaluation of the Lagrange multipliers. Examples illustrate the efficiency of the method.

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.

Optimal pitching axis location of flapping wings for efficient hovering flight.

PubMed

Wang, Q; Goosen, J F L; van Keulen, F

2017-09-01

Flapping wings can pitch passively about their pitching axes due to their flexibility, inertia, and aerodynamic loads. A shift in the pitching axis location can dynamically alter the aerodynamic loads, which in turn changes the passive pitching motion and the flight efficiency. Therefore, it is of great interest to investigate the optimal pitching axis for flapping wings to maximize the power efficiency during hovering flight. In this study, flapping wings are modeled as rigid plates with non-uniform mass distribution. The wing flexibility is represented by a linearly torsional spring at the wing root. A predictive quasi-steady aerodynamic model is used to evaluate the lift generated by such wings. Two extreme power consumption scenarios are modeled for hovering flight, i.e. the power consumed by a drive system with and without the capacity of kinetic energy recovery. For wings with different shapes, the optimal pitching axis location is found such that the cycle-averaged power consumption during hovering flight is minimized. Optimization results show that the optimal pitching axis is located between the leading edge and the mid-chord line, which shows close resemblance to insect wings. An optimal pitching axis can save up to 33% of power during hovering flight when compared to traditional wings used by most of flapping wing micro air vehicles (FWMAVs). Traditional wings typically use the straight leading edge as the pitching axis. With the optimized pitching axis, flapping wings show higher pitching amplitudes and start the pitching reversals in advance of the sweeping reversals. These phenomena lead to higher lift-to-drag ratios and, thus, explain the lower power consumption. In addition, the optimized pitching axis provides the drive system higher potential to recycle energy during the deceleration phases as compared to their counterparts. This observation underlines the particular importance of the wing pitching axis location for energy-efficient FWMAVs when using kinetic energy recovery drive systems.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy.

PubMed

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-07

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A new approach to integrate GPU-based Monte Carlo simulation into inverse treatment plan optimization for proton therapy

NASA Astrophysics Data System (ADS)

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2017-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6  ±  15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.

A New Approach to Integrate GPU-based Monte Carlo Simulation into Inverse Treatment Plan Optimization for Proton Therapy

PubMed Central

Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2016-01-01

Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6±15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size. PMID:27991456

Regenerative Carbonate-Based Thermochemical Energy Storage System for Concentrating Solar Power

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

Gangwal, Santosh; Muto, Andrew

Southern Research has developed a thermochemical energy storage (TCES) technology that utilizes the endothermic-exothermic reversible carbonation of calcium oxide (lime) to store thermal energy at high-temperatures, such as those achieved by next generation concentrating solar power (CSP) facilities. The major challenges addressed in the development of this system include refining a high capacity, yet durable sorbent material and designing a low thermal resistance low-cost heat exchanger reactor system to move heat between the sorbent and a heat transfer fluid under conditions relevant for CSP operation (e.g., energy density, reaction kinetics, heat flow). The proprietary stabilized sorbent was developed by Precisionmore » Combustion, Inc. (PCI). A factorial matrix of sorbent compositions covering the design space was tested using accelerated high throughput screening in a thermo-gravimetric analyzer. Several promising formulations were selected for more thorough evaluation and one formulation with high capacity (0.38 g CO 2/g sorbent) and durability (>99.7% capacity retention over 100 cycles) was chosen as a basis for further development of the energy storage reactor system. In parallel with this effort, a full range of currently available commercial and developmental heat exchange reactor systems and sorbent loading methods were examined through literature research and contacts with commercial vendors. Process models were developed to examine if a heat exchange reactor system and balance of plant can meet required TCES performance and cost targets, optimizing tradeoffs between thermal performance, exergetic efficiency, and cost. Reactor types evaluated included many forms, from microchannel reactor, to diffusion bonded heat exchanger, to shell and tube heat exchangers. The most viable design for application to a supercritical CO 2 power cycle operating at 200-300 bar pressure and >700°C was determined to be a combination of a diffusion bonded heat exchanger with a shell and tube reactor. A bench scale reactor system was then designed and constructed to test sorbent performance under more commercially relevant conditions. This system utilizes a tube-in tube reactor design containing approximately 250 grams sorbent and is able to operate under a wide range of temperature, pressure and flow conditions as needed to explore system performance under a variety of operating conditions. A variety of sorbent loading methods may be tested using the reactor design. Initial bench test results over 25 cycles showed very high sorbent stability (>99%) and sufficient capacity (>0.28 g CO 2/g sorbent) for an economical commercial-scale system. Initial technoeconomic evaluation of the proposed storage system show that the sorbent cost should not have a significant impact on overall system cost, and that the largest cost impacts come from the heat exchanger reactor and balance of plant equipment, including compressors and gas storage, due to the high temperatures for sCO 2 cycles. Current estimated system costs are $47/kWhth based on current material and equipment cost estimates.« less

Optimization of composite tiltrotor wings with extensions and winglets

NASA Astrophysics Data System (ADS)

Kambampati, Sandilya

Tiltrotors suffer from an aeroelastic instability during forward flight called whirl flutter. Whirl flutter is caused by the whirling motion of the rotor, characterized by highly coupled wing-rotor-pylon modes of vibration. Whirl flutter is a major obstacle for tiltrotors in achieving high-speed flight. The conventional approach to assure adequate whirl flutter stability margins for tiltrotors is to design the wings with high torsional stiffness, typically using 23% thickness-to-chord ratio wings. However, the large aerodynamic drag associated with these high thickness-to-chord ratio wings decreases aerodynamic efficiency and increases fuel consumption. Wingtip devices such as wing extensions and winglets have the potential to increase the whirl flutter characteristics and the aerodynamic efficiency of a tiltrotor. However, wing-tip devices can add more weight to the aircraft. In this study, multi-objective parametric and optimization methodologies for tiltrotor aircraft with wing extensions and winglets are investigated. The objectives are to maximize aircraft aerodynamic efficiency while minimizing weight penalty due to extensions and winglets, subject to whirl flutter constraints. An aeroelastic model that predicts the whirl flutter speed and a wing structural model that computes strength and weight of a composite wing are developed. An existing aerodynamic model (that predicts the aerodynamic efficiency) is merged with the developed structural and aeroelastic models for the purpose of conducting parametric and optimization studies. The variables of interest are the wing thickness and structural properties, and extension and winglet planform variables. The Bell XV-15 tiltrotor aircraft the chosen as the parent aircraft for this study. Parametric studies reveal that a wing extension of span 25% of the inboard wing increases the whirl flutter speed by 10% and also increases the aircraft aerodynamic efficiency by 8%. Structurally tapering the wing of a tiltrotor equipped with an extension and a winglet can increase the whirl flutter speed by 15% while reducing the wing weight by 7.5%. The baseline design for the optimization is the optimized wing with no extension or winglet. The optimization studies reveal that the optimum design for a cruise speed of 250 knots has an increased aerodynamic efficiency of 7% over the baseline design for only a weight penalty of 3% - thus a better transport range of 5.5% more than the baseline. The optimal design for a cruise speed of 300 knots has an increased aerodynamic efficiency of 5%, a weight penalty of 2.5%, and a better transport range of 3.5% more than the baseline.

Multi-Objective Aerodynamic Optimization of the Streamlined Shape of High-Speed Trains Based on the Kriging Model.

PubMed

Xu, Gang; Liang, Xifeng; Yao, Shuanbao; Chen, Dawei; Li, Zhiwei

2017-01-01

Minimizing the aerodynamic drag and the lift of the train coach remains a key issue for high-speed trains. With the development of computing technology and computational fluid dynamics (CFD) in the engineering field, CFD has been successfully applied to the design process of high-speed trains. However, developing a new streamlined shape for high-speed trains with excellent aerodynamic performance requires huge computational costs. Furthermore, relationships between multiple design variables and the aerodynamic loads are seldom obtained. In the present study, the Kriging surrogate model is used to perform a multi-objective optimization of the streamlined shape of high-speed trains, where the drag and the lift of the train coach are the optimization objectives. To improve the prediction accuracy of the Kriging model, the cross-validation method is used to construct the optimal Kriging model. The optimization results show that the two objectives are efficiently optimized, indicating that the optimization strategy used in the present study can greatly improve the optimization efficiency and meet the engineering requirements.

Decoupled CFD-based optimization of efficiency and cavitation performance of a double-suction pump

NASA Astrophysics Data System (ADS)

Škerlavaj, A.; Morgut, M.; Jošt, D.; Nobile, E.

2017-04-01

In this study the impeller geometry of a double-suction pump ensuring the best performances in terms of hydraulic efficiency and reluctance of cavitation is determined using an optimization strategy, which was driven by means of the modeFRONTIER optimization platform. The different impeller shapes (designs) are modified according to the optimization parameters and tested with a computational fluid dynamics (CFD) software, namely ANSYS CFX. The simulations are performed using a decoupled approach, where only the impeller domain region is numerically investigated for computational convenience. The flow losses in the volute are estimated on the base of the velocity distribution at the impeller outlet. The best designs are then validated considering the computationally more expensive full geometry CFD model. The overall results show that the proposed approach is suitable for quick impeller shape optimization.

Gain and power optimization of the wireless optical system with multilevel modulation.

PubMed

Liu, Xian

2008-06-01

When used in an outdoor environment to expedite networking access, the performance of wireless optical communication systems is affected by transmitter sway. In the design of such systems, much attention has been paid to developing power-efficient schemes. However, the bandwidth efficiency is also an important issue. One of the most natural approaches to promote bandwidth efficiency is to use multilevel modulation. This leads to multilevel pulse amplitude modulation in the context of intensity modulation and direct detection. We develop a model based on the four-level pulse amplitude modulation. We show that the model can be formulated as an optimization problem in terms of the transmitter power, bit error probability, transmitter gain, and receiver gain. The technical challenges raised by modeling and solving the problem include the analytical and numerical treatments for the improper integrals of the Gaussian functions coupled with the erfc function. The results demonstrate that, at the optimal points, the power penalty paid to the doubled bandwidth efficiency is around 3 dB.

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

PubMed Central

Penumalli, Chakradhar; Palanichamy, Yogesh

2015-01-01

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627

Technique Developed for Optimizing Traveling-Wave Tubes

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.

1999-01-01

A traveling-wave tube (TWT) is an electron beam device that is used to amplify electromagnetic communication waves at radio and microwave frequencies. TWT s are critical components in deep-space probes, geosynchronous communication satellites, and high-power radar systems. Power efficiency is of paramount importance for TWT s employed in deep-space probes and communications satellites. Consequently, increasing the power efficiency of TWT s has been the primary goal of the TWT group at the NASA Lewis Research Center over the last 25 years. An in-house effort produced a technique (ref. 1) to design TWT's for optimized power efficiency. This technique is based on simulated annealing, which has an advantage over conventional optimization techniques in that it enables the best possible solution to be obtained (ref. 2). A simulated annealing algorithm was created and integrated into the NASA TWT computer model (ref. 3). The new technique almost doubled the computed conversion power efficiency of a TWT from 7.1 to 13.5 percent (ref. 1).

Numerical investigation of optimized CZTSSe based solar cell in Wx-Amps environment

NASA Astrophysics Data System (ADS)

Mohanty, Soumya Priyadarshini; Padhy, Srinibasa; Chowdhury, Joy; Sing, Udai P.

2018-05-01

The CZTSSe is the modified version of CZTS with selenium infusion. It shows maximum efficiency in the band gap from 1 to 1.4 eV. In our present work CZTSSe based solar cell is investigated using Wx-Amps tool. The Mo layer, absorber layer, CdS layer, i-ZnO [4]and Al-ZnO layers with their electrical, optical and material parameters are fitted in the tool. The vital parameters such as carrier density, thickness of the CZTSSe absorber layer, operating temperature, CdS buffer layer thickness and its carrier density on the cell interpretation are calculated. From[4] the simulation results it is apparent that the optimal absorber layer varies from 2.9 µm to 3.7 µm. The temperature variation has a strong influence on the efficiency of the cell. An optimal efficiency of 22% (With Jsc=33 mA/cm2, Voc=0.98 V, and fill factor= 68%) are attained. These results will give some insight for makeing higher efficiency CZTSSe based solar cell.

Optimization of active cell area on the dye-sensitized solar cell efficiency

NASA Astrophysics Data System (ADS)

Putri, A. W.; Nurosyid, F.; Supriyanto, Agus

2017-11-01

This study is aimed to obtain optimal active area producing high efficiency of DSSC module. The DSSC structure is constructed of TiO2 as working electrode, dye as photosensitizer, platinum as counter electrode, and electrolyte as electron transfer media. TiO2 paste was deposited on Fluorine-doped Tin Oxide (FTO) by screen printing method. Meanwhile, platinum was also coated on FTO via brush painting method. Keithley I-V meter was performed to characterize DSSC electrical property. The active area of each cell was varied of 4.5 cm2, 9 cm2, and 13.5 cm2. Each cell was assembled into a module using an external series connection of Z type. The module was consisted of 12 cells, 6 cells, and 4 cells with module active area of 54 cm2. The optimal active area of DSSC cell is 4.5 cm2 resulting 0.4149% efficiency. In addition, the highest efficiency of DSSC module is 0.2234% acquired by 6 cells assembling.

Efficient logistic regression designs under an imperfect population identifier.

PubMed

Albert, Paul S; Liu, Aiyi; Nansel, Tonja

2014-03-01

Motivated by actual study designs, this article considers efficient logistic regression designs where the population is identified with a binary test that is subject to diagnostic error. We consider the case where the imperfect test is obtained on all participants, while the gold standard test is measured on a small chosen subsample. Under maximum-likelihood estimation, we evaluate the optimal design in terms of sample selection as well as verification. We show that there may be substantial efficiency gains by choosing a small percentage of individuals who test negative on the imperfect test for inclusion in the sample (e.g., verifying 90% test-positive cases). We also show that a two-stage design may be a good practical alternative to a fixed design in some situations. Under optimal and nearly optimal designs, we compare maximum-likelihood and semi-parametric efficient estimators under correct and misspecified models with simulations. The methodology is illustrated with an analysis from a diabetes behavioral intervention trial. © 2013, The International Biometric Society.

Monte Carlo treatment of resonance-radiation imprisonment in fluorescent lamps—revisited

NASA Astrophysics Data System (ADS)

Anderson, James B.

2016-12-01

We reported in 1985 a Monte Carlo treatment of the imprisonment of the 253.7 nm resonance radiation from mercury in the mercury-argon discharge of fluorescent lamps. The calculated spectra of the emitted radiation were found in good agreement with measured spectra. The addition of the isotope mercury-196 to natural mercury was found, also in agreement with experiments, to increase lamp efficiency. In this paper we report the extension of the earlier work with increased accuracy, analysis of photon exit-time distributions, recycling of energy released in quenching, analysis of dynamic similarity for different lamp sizes, variation of Mrozowski transfer rates, prediction and analysis of the hyperfine ultra-violet spectra, and optimization of tailored mercury isotope mixtures for increased lamp efficiency. The spectra were found insensitive to the extent of quenching and recycling. The optimized mixtures were found to increase efficiencies by as much as 5% for several lamp configurations. Optimization without increasing the mercury-196 fraction was found to increase efficiencies by nearly 1% for several configurations.

Energy-Efficient Cognitive Radio Sensor Networks: Parametric and Convex Transformations

PubMed Central

Naeem, Muhammad; Illanko, Kandasamy; Karmokar, Ashok; Anpalagan, Alagan; Jaseemuddin, Muhammad

2013-01-01

Designing energy-efficient cognitive radio sensor networks is important to intelligently use battery energy and to maximize the sensor network life. In this paper, the problem of determining the power allocation that maximizes the energy-efficiency of cognitive radio-based wireless sensor networks is formed as a constrained optimization problem, where the objective function is the ratio of network throughput and the network power. The proposed constrained optimization problem belongs to a class of nonlinear fractional programming problems. Charnes-Cooper Transformation is used to transform the nonlinear fractional problem into an equivalent concave optimization problem. The structure of the power allocation policy for the transformed concave problem is found to be of a water-filling type. The problem is also transformed into a parametric form for which a ε-optimal iterative solution exists. The convergence of the iterative algorithms is proven, and numerical solutions are presented. The iterative solutions are compared with the optimal solution obtained from the transformed concave problem, and the effects of different system parameters (interference threshold level, the number of primary users and secondary sensor nodes) on the performance of the proposed algorithms are investigated. PMID:23966194

An efficient identification approach for stable and unstable nonlinear systems using Colliding Bodies Optimization algorithm.

PubMed

Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P

2015-11-01

This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

High efficiency yellow organic light-emitting diodes with optimized barrier layers

NASA Astrophysics Data System (ADS)

Mu, Ye; Zhang, Shiming; Yue, Shouzhen; Wu, Qingyang; Zhao, Yi

2015-12-01

High efficiency Iridium (III) bis (4-phenylthieno [3,2-c] pyridinato-N,C2‧) acetylacetonate (PO-01) based yellow organic light-emitting devices are fabricated by employing multiple emission layers. The efficiency of the device using 4,4‧,4″-tris(N-carbazolyl) triphenylamine (TCTA) as potential barrier layer (PBL) outperforms those devices based on other PBLs and detailed analysis is carried out to reveal the mechanisms. A forward-viewing current efficiency (CE) of 65.21 cd/A, which corresponds to a maximum total CE of 110.85 cd/A is achieved at 335.8 cd/m2 in the optimized device without any outcoupling enhancement structures.

Batch technique to evaluate the efficiency of different natural adsorbents for defluoridation from groundwater

NASA Astrophysics Data System (ADS)

Kumar, Pankaj; Saraswat, Chitresh; Mishra, Binaya Kumar; Avtar, Ram; Patel, Hiral; Patel, Asha; Sharma, Tejal; Patel, Roshni

2017-09-01

Fluoride pollution (with concentration >1.0 mg/L) in groundwater has become a global threat in the recent past due to the lesser availability of potable groundwater resource. In between several defluoridation techniques discovered so far, the adsorption process proved to be most economic and efficient. This study is an effort to evaluate defluoridation efficiency of powdered rice husk, fine chopped rice husk and sawdust by the batch adsorption process. Optimum defluoridation capacity is achieved by optimizing various parameters, viz. dose of adsorbent, pH, contact time and initial concentration. It was found that all three materials can be employed for the defluoridation technique, but powdered rice husk is the best adsorbent in the midst of all three. Powdered rice husk showed fluoride removal efficiency ranging between 85 and 90 % in the contact period of 7 h only in conditions of all optimized parameter. Following this parameter optimization, adsorption efficiency was also evaluated at natural pH of groundwater to minimize the cost of defluoridation. No significant difference was found between fluoride adsorption at optimized pH (pH = 4) and natural one (pH = 7), which concludes that powdered rice husk can be efficiently used for the defluoridation technique at field scale. The adsorption isotherm using this adsorbent perfectly followed Langmuir isotherms. The value of calculated separation factor also suggests the favourable adsorption of fluoride onto this adsorbent under the conditions used for the experiments. The field application for defluoridation of groundwater using this adsorbent (based on pH of natural groundwater there and seasonal variation of temperature) showed the high success rate.

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.

Progress towards an Optimization Methodology for Combustion-Driven Portable Thermoelectric Power Generation Systems

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

Krishnan, Shankar; Karri, Naveen K.; Gogna, Pawan K.

2012-03-13

Enormous military and commercial interests exist in developing quiet, lightweight, and compact thermoelectric (TE) power generation systems. This paper investigates design integration and analysis of an advanced TE power generation system implementing JP-8 fueled combustion and thermal recuperation. Design and development of a portable TE power system using a JP-8 combustor as a high temperature heat source and optimal process flows depend on efficient heat generation, transfer, and recovery within the system are explored. Design optimization of the system required considering the combustion system efficiency and TE conversion efficiency simultaneously. The combustor performance and TE sub-system performance were coupled directlymore » through exhaust temperatures, fuel and air mass flow rates, heat exchanger performance, subsequent hot-side temperatures, and cold-side cooling techniques and temperatures. Systematic investigation of this system relied on accurate thermodynamic modeling of complex, high-temperature combustion processes concomitantly with detailed thermoelectric converter thermal/mechanical modeling. To this end, this work reports on design integration of systemlevel process flow simulations using commercial software CHEMCADTM with in-house thermoelectric converter and module optimization, and heat exchanger analyses using COMSOLTM software. High-performance, high-temperature TE materials and segmented TE element designs are incorporated in coupled design analyses to achieve predicted TE subsystem level conversion efficiencies exceeding 10%. These TE advances are integrated with a high performance microtechnology combustion reactor based on recent advances at the Pacific Northwest National Laboratory (PNNL). Predictions from this coupled simulation established a basis for optimal selection of fuel and air flow rates, thermoelectric module design and operating conditions, and microtechnology heat-exchanger design criteria. This paper will discuss this simulation process that leads directly to system efficiency power maps defining potentially available optimal system operating conditions and regimes. This coupled simulation approach enables pathways for integrated use of high-performance combustor components, high performance TE devices, and microtechnologies to produce a compact, lightweight, combustion driven TE power system prototype that operates on common fuels.« less

A Pareto frontier intersection-based approach for efficient multiobjective optimization of competing concept alternatives

NASA Astrophysics Data System (ADS)

Rousis, Damon A.

The expected growth of civil aviation over the next twenty years places significant emphasis on revolutionary technology development aimed at mitigating the environmental impact of commercial aircraft. As the number of technology alternatives grows along with model complexity, current methods for Pareto finding and multiobjective optimization quickly become computationally infeasible. Coupled with the large uncertainty in the early stages of design, optimal designs are sought while avoiding the computational burden of excessive function calls when a single design change or technology assumption could alter the results. This motivates the need for a robust and efficient evaluation methodology for quantitative assessment of competing concepts. This research presents a novel approach that combines Bayesian adaptive sampling with surrogate-based optimization to efficiently place designs near Pareto frontier intersections of competing concepts. Efficiency is increased over sequential multiobjective optimization by focusing computational resources specifically on the location in the design space where optimality shifts between concepts. At the intersection of Pareto frontiers, the selection decisions are most sensitive to preferences place on the objectives, and small perturbations can lead to vastly different final designs. These concepts are incorporated into an evaluation methodology that ultimately reduces the number of failed cases, infeasible designs, and Pareto dominated solutions across all concepts. A set of algebraic samples along with a truss design problem are presented as canonical examples for the proposed approach. The methodology is applied to the design of ultra-high bypass ratio turbofans to guide NASA's technology development efforts for future aircraft. Geared-drive and variable geometry bypass nozzle concepts are explored as enablers for increased bypass ratio and potential alternatives over traditional configurations. The method is shown to improve sampling efficiency and provide clusters of feasible designs that motivate a shift towards revolutionary technologies that reduce fuel burn, emissions, and noise on future aircraft.

Optimization through satisficing with prospects

NASA Astrophysics Data System (ADS)

Oyo, Kuratomo; Takahashi, Tatsuji

2017-07-01

As the broadening scope of reinforcement learning calls for a rational and more efficient heuristics, we test a satisficing strategy named RS, based on the theory of bounded rationality that considers the limited resources in agents. In K-armed bandit problems, despite its simpler form than the previous formalization of satisficing, RS shows better-than-optimal performances when the optimal aspiration level is given. We also show that RS shows a scalability for the number of actions, K, and an adaptability in the face of an infinite number of actions. It may be an efficient means for online learning in a complex or real environments.

4-channels coherent perfect absorption (CPA)-type demultiplexer using plasmonic nano spheres

NASA Astrophysics Data System (ADS)

Soltani, Mohamadreza; Keshavarzi, Rasul

2017-10-01

The current research represents a nanoscale and compact 4-channels plasmonic demultiplexer. It includes eight coherent perfect absorption (CPA) - type filters. The operation principle is based on the absorbable formation of a conductive path in the dielectric layer of a plasmonic nano-spheres waveguide. Since the CPA efficiency depends strongly on the number of plasmonic nano-spheres and the nano spheres location, an efficient binary optimization method based on the Particle Swarm Optimization algorithm is used to design an optimized array of the plasmonic nano-sphere in order to achieve the maximum absorption coefficient in the 'off' state.

The technological raw material heating furnaces operation efficiency improving issue

NASA Astrophysics Data System (ADS)

Paramonov, A. M.

2017-08-01

The issue of fuel oil applying efficiency improving in the technological raw material heating furnaces by means of its combustion intensification is considered in the paper. The technical and economic optimization problem of the fuel oil heating before combustion is solved. The fuel oil heating optimal temperature defining method and algorithm analytically considering the correlation of thermal, operating parameters and discounted costs for the heating furnace were developed. The obtained optimization functionality provides the heating furnace appropriate thermal indices achievement at minimum discounted costs. The carried out research results prove the expediency of the proposed solutions using.

Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

DOE PAGES

Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; ...

2013-07-18

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

Optimizing the function of upstanding activities in adult patients with acquired lesions of the central nervous system by using the Bobath concept approach - A case report.

PubMed

Jelica, Stjepan; Seper, Vesna; Davidović, Erna; Bujisić, Gordana

2011-01-01

Nonspecific medical gymnastic therapy may help patients after stroke achieve certain results in terms of efficiency but not in terms of quality of movement. The goal of treatment by Bobath concept is development of movement (effectiveness) and optimization of movement (efficiency). This article presents the case of a 62-year old patient who had experienced a stroke and has difficulties with standing up activities. It underscores the importance of not only recovery of function but also optimization of the function in such patients.

A modified form of conjugate gradient method for unconstrained optimization problems

NASA Astrophysics Data System (ADS)

Ghani, Nur Hamizah Abdul; Rivaie, Mohd.; Mamat, Mustafa

2016-06-01

Conjugate gradient (CG) methods have been recognized as an interesting technique to solve optimization problems, due to the numerical efficiency, simplicity and low memory requirements. In this paper, we propose a new CG method based on the study of Rivaie et al. [7] (Comparative study of conjugate gradient coefficient for unconstrained Optimization, Aus. J. Bas. Appl. Sci. 5(2011) 947-951). Then, we show that our method satisfies sufficient descent condition and converges globally with exact line search. Numerical results show that our proposed method is efficient for given standard test problems, compare to other existing CG methods.

Multi-parameter optimization of piezoelectric actuators for multi-mode active vibration control of cylindrical shells

NASA Astrophysics Data System (ADS)

Hu, K. M.; Li, Hua

2018-07-01

A novel technique for the multi-parameter optimization of distributed piezoelectric actuators is presented in this paper. The proposed method is designed to improve the performance of multi-mode vibration control in cylindrical shells. The optimization parameters of actuator patch configuration include position, size, and tilt angle. The modal control force of tilted orthotropic piezoelectric actuators is derived and the multi-parameter cylindrical shell optimization model is established. The linear quadratic energy index is employed as the optimization criterion. A geometric constraint is proposed to prevent overlap between tilted actuators, which is plugged into a genetic algorithm to search the optimal configuration parameters. A simply-supported closed cylindrical shell with two actuators serves as a case study. The vibration control efficiencies of various parameter sets are evaluated via frequency response and transient response simulations. The results show that the linear quadratic energy indexes of position and size optimization decreased by 14.0% compared to position optimization; those of position and tilt angle optimization decreased by 16.8%; and those of position, size, and tilt angle optimization decreased by 25.9%. It indicates that, adding configuration optimization parameters is an efficient approach to improving the vibration control performance of piezoelectric actuators on shells.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mardechay

1992-01-01

The purpose of the research project was to continue the development of new methods for efficient aeroservoelastic analysis and optimization. The main targets were as follows: to complete the development of analytical tools for the investigation of flutter with large stiffness changes; to continue the work on efficient continuous gust response and sensitivity derivatives; and to advance the techniques of calculating dynamic loads with control and unsteady aerodynamic effects. An efficient and highly accurate mathematical model for time-domain analysis of flutter during which large structural changes occur was developed in cooperation with Carol D. Wieseman of NASA LaRC. The model was based on the second-year work 'Modal Coordinates for Aeroelastic Analysis with Large Local Structural Variations'. The work on continuous gust response was completed. An abstract of the paper 'Continuous Gust Response and Sensitivity Derivatives Using State-Space Models' was submitted for presentation in the 33rd Israel Annual Conference on Aviation and Astronautics, Feb. 1993. The abstract is given in Appendix A. The work extends the optimization model to deal with continuous gust objectives in a way that facilitates their inclusion in the efficient multi-disciplinary optimization scheme. Currently under development is a work designed to extend the analysis and optimization capabilities to loads and stress considerations. The work is on aircraft dynamic loads in response to impulsive and non-impulsive excitation. The work extends the formulations of the mode-displacement and summation-of-forces methods to include modes with significant local distortions, and load modes. An abstract of the paper,'Structural Dynamic Loads in Response to Impulsive Excitation' is given in appendix B. Another work performed this year under the Grant was 'Size-Reduction Techniques for the Determination of Efficient Aeroservoelastic Models' given in Appendix C.

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

Beltran, C; Kamal, H

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatmentmore » planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.« less

Efficient Optimization of Low-Thrust Spacecraft Trajectories

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Fink, Wolfgang; Russell, Ryan; Terrile, Richard; Petropoulos, Anastassios; vonAllmen, Paul

2007-01-01

A paper describes a computationally efficient method of optimizing trajectories of spacecraft driven by propulsion systems that generate low thrusts and, hence, must be operated for long times. A common goal in trajectory-optimization problems is to find minimum-time, minimum-fuel, or Pareto-optimal trajectories (here, Pareto-optimality signifies that no other solutions are superior with respect to both flight time and fuel consumption). The present method utilizes genetic and simulated-annealing algorithms to search for globally Pareto-optimal solutions. These algorithms are implemented in parallel form to reduce computation time. These algorithms are coupled with either of two traditional trajectory- design approaches called "direct" and "indirect." In the direct approach, thrust control is discretized in either arc time or arc length, and the resulting discrete thrust vectors are optimized. The indirect approach involves the primer-vector theory (introduced in 1963), in which the thrust control problem is transformed into a co-state control problem and the initial values of the co-state vector are optimized. In application to two example orbit-transfer problems, this method was found to generate solutions comparable to those of other state-of-the-art trajectory-optimization methods while requiring much less computation time.

Influential factors on thermoacoustic efficiency of multilayered graphene film loudspeakers for optimal design

NASA Astrophysics Data System (ADS)

Xing, Qianhe; Li, Shuang; Fan, Xueliang; Bian, Anhua; Cao, Shi-Jie; Li, Cheng

2017-09-01

Graphene thermoacoustic loudspeakers, composed of a graphene film on a substrate, generate sound with heat. Improving thermoacoustic efficiency of graphene speakers is a goal for optimal design. In this work, we first modified the existing TA model with respect to small thermal wavelengths, and then built an acoustic platform for model validation. Additionally, sensitivity analyses for influential factors on thermoacoustic efficiency were performed, including the thickness of multilayered graphene films, the thermal effusivity of substrates, and the characteristics of inserted gases. The higher sensitivity coefficients result in the stronger effects on thermoacoustic efficiency. We find that the thickness (5 nm-15 nm) of graphene films plays a trivial role in efficiency, resulting in the sensitivity coefficient less than 0.02. The substrate thermal effusivity, however, has significant effects on efficiency, with the sensitivity coefficient around 1.7. Moreover, substrates with a lower thermal effusivity show better acoustic performances. For influences of ambient gases, the sensitivity coefficients of density ρg, thermal conductivity κg, and specific heat cp,g are 2.7, 0.98, and 0.8, respectively. Furthermore, large magnitudes of both ρg and κg lead to a higher efficiency and the sound pressure level generated by graphene films is approximately proportional to the inverse of cp,g. These findings can refer to the optimal design for graphene thermoacoustic speakers.

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Chopped random-basis quantum optimization

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

Caneva, Tommaso; Calarco, Tommaso; Montangero, Simone

2011-08-15

In this work, we describe in detail the chopped random basis (CRAB) optimal control technique recently introduced to optimize time-dependent density matrix renormalization group simulations [P. Doria, T. Calarco, and S. Montangero, Phys. Rev. Lett. 106, 190501 (2011)]. Here, we study the efficiency of this control technique in optimizing different quantum processes and we show that in the considered cases we obtain results equivalent to those obtained via different optimal control methods while using less resources. We propose the CRAB optimization as a general and versatile optimal control technique.

Basic aspects and contributions to the optimization of energy systems exploitation of a super tanker ship

NASA Astrophysics Data System (ADS)

Faitar, C.; Novac, I.

2017-08-01

Today, the concept of energy efficiency or energy optimization in ships has become one of the main problems of engineers in the whole world. To increase the fiability of a crude oil super tanker ship it means, among other things, to improve the energy performance and optimize the fuel consumption of ship through the development of engines and propulsion system or using alternative energies. Also, the importance of having an effective and reliable Power Management System (PMS) in a vessel operating system means to reduce operational costs and maintain power system of machine parts working in minimum stress in all operating conditions. Studying the Energy Efficiency Design Index and Energy Efficiency Operational Indicator for a crude oil super tanker ship, it allows us to study the reconfiguration of ship power system introducing new generation systems.

Optimizing cost-efficiency in mean exposure assessment - cost functions reconsidered

PubMed Central

2011-01-01

Background Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios. Methods Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components. Results Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods. For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set. Conclusions The analysis procedures developed in the present study can be used for informed design of exposure assessment strategies, provided that data are available on exposure variability and the costs of collecting and processing data. The present shortage of empirical evidence on costs and appropriate cost functions however impedes general conclusions on optimal exposure measurement strategies in different epidemiologic scenarios. PMID:21600023

Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.

PubMed

Mathiassen, Svend Erik; Bolin, Kristian

2011-05-21

Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios. Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components. Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods.For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set. The analysis procedures developed in the present study can be used for informed design of exposure assessment strategies, provided that data are available on exposure variability and the costs of collecting and processing data. The present shortage of empirical evidence on costs and appropriate cost functions however impedes general conclusions on optimal exposure measurement strategies in different epidemiologic scenarios.

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

NASA Technical Reports Server (NTRS)

Jardin, Matthew R.

2004-01-01

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

PubMed

Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

Optimization of chiral lattice based metastructures for broadband vibration suppression using genetic algorithms

NASA Astrophysics Data System (ADS)

Abdeljaber, Osama; Avci, Onur; Inman, Daniel J.

2016-05-01

One of the major challenges in civil, mechanical, and aerospace engineering is to develop vibration suppression systems with high efficiency and low cost. Recent studies have shown that high damping performance at broadband frequencies can be achieved by incorporating periodic inserts with tunable dynamic properties as internal resonators in structural systems. Structures featuring these kinds of inserts are referred to as metamaterials inspired structures or metastructures. Chiral lattice inserts exhibit unique characteristics such as frequency bandgaps which can be tuned by varying the parameters that define the lattice topology. Recent analytical and experimental investigations have shown that broadband vibration attenuation can be achieved by including chiral lattices as internal resonators in beam-like structures. However, these studies have suggested that the performance of chiral lattice inserts can be maximized by utilizing an efficient optimization technique to obtain the optimal topology of the inserted lattice. In this study, an automated optimization procedure based on a genetic algorithm is applied to obtain the optimal set of parameters that will result in chiral lattice inserts tuned properly to reduce the global vibration levels of a finite-sized beam. Genetic algorithms are considered in this study due to their capability of dealing with complex and insufficiently understood optimization problems. In the optimization process, the basic parameters that govern the geometry of periodic chiral lattices including the number of circular nodes, the thickness of the ligaments, and the characteristic angle are considered. Additionally, a new set of parameters is introduced to enable the optimization process to explore non-periodic chiral designs. Numerical simulations are carried out to demonstrate the efficiency of the optimization process.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants

PubMed Central

Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996–2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated. PMID:27010658

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals

NASA Astrophysics Data System (ADS)

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals.

PubMed

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Performance analysis and optimization of power plants with gas turbines

NASA Astrophysics Data System (ADS)

Besharati-Givi, Maryam

The gas turbine is one of the most important applications for power generation. The purpose of this research is performance analysis and optimization of power plants by using different design systems at different operation conditions. In this research, accurate efficiency calculation and finding optimum values of efficiency for design of chiller inlet cooling and blade cooled gas turbine are investigated. This research shows how it is possible to find the optimum design for different operation conditions, like ambient temperature, relative humidity, turbine inlet temperature, and compressor pressure ratio. The simulated designs include the chiller, with varied COP and fogging cooling for a compressor. In addition, the overall thermal efficiency is improved by adding some design systems like reheat and regenerative heating. The other goal of this research focuses on the blade-cooled gas turbine for higher turbine inlet temperature, and consequently, higher efficiency. New film cooling equations, along with changing film cooling effectiveness for optimum cooling air requirement at the first-stage blades, and an internal and trailing edge cooling for the second stage, are innovated for optimal efficiency calculation. This research sets the groundwork for using the optimum value of efficiency calculation, while using inlet cooling and blade cooling designs. In the final step, the designed systems in the gas cycles are combined with a steam cycle for performance improvement.

Design of a portable artificial heart drive system based on efficiency analysis.

PubMed

Kitamura, T

1986-11-01

This paper discusses a computer simulation of a pneumatic portable piston-type artificial heart drive system with a linear d-c-motor. The purpose of the design is to obtain an artificial heart drive system with high efficiency and small dimensions to enhance portability. The design employs two factors contributing the total efficiency of the drive system. First, the dimensions of the pneumatic actuator were optimized under a cost function of the total efficiency. Second, the motor performance was studied in terms of efficiency. More than 50 percent of the input energy of the actuator with practical loads is consumed in the armature circuit in all linear d-c-motors with brushes. An optimal design is: the piston cross-sectional area of 10.5 cm2 cylinder longitudinal length of 10 cm. The total efficiency could be up to 25 percent by improving the gasket to reduce the frictional force.

Methods for understanding super-efficient data envelopment analysis results with an application to hospital inpatient surgery.

PubMed

O'Neill, Liam; Dexter, Franklin

2005-11-01

We compare two techniques for increasing the transparency and face validity of Data Envelopment Analysis (DEA) results for managers at a single decision-making unit: multifactor efficiency (MFE) and non-radial super-efficiency (NRSE). Both methods incorporate the slack values from the super-efficient DEA model to provide a more robust performance measure than radial super-efficiency scores. MFE and NRSE are equivalent for unique optimal solutions and a single output. MFE incorporates the slack values from multiple output variables, whereas NRSE does not. MFE can be more transparent to managers since it involves no additional optimization steps beyond the DEA, whereas NRSE requires several. We compare results for operating room managers at an Iowa hospital evaluating its growth potential for multiple surgical specialties. In addition, we address the problem of upward bias of the slack values of the super-efficient DEA model.

Open space preservation, property value, and optimal spatial configuration

Treesearch

Yong Jiang; Stephen K. Swallow

2007-01-01

The public has increasingly demonstrated a strong support for open space preservation. How to finance the socially efficient level of open space with the optimal spatial structure is of high policy relevance to local governments. In this study, we developed a spatially explicit open space model to help identify the socially optimal amount and optimal spatial...

Optimization of White-Matter-Nulled Magnetization Prepared Rapid Gradient Echo (MP-RAGE) Imaging

PubMed Central

Saranathan, Manojkumar; Tourdias, Thomas; Bayram, Ersin; Ghanouni, Pejman; Rutt, Brian K.

2014-01-01

Purpose To optimize the white-matter-nulled (WMn) Magnetization Prepared Rapid Gradient Echo (MP-RAGE) sequence at 7T, with comparisons to 3T. Methods Optimal parameters for maximising SNR efficiency were derived. The effect of flip angle and TR on image blurring was modeled using simulations and validated in vivo. A novel 2D-centric radial fan beam (RFB) k-space segmentation scheme was used to shorten scan times and improve parallel imaging. Healthy subjects as well as patients with multiple sclerosis and tremor were scanned using the optimized protocols. Results Inversion repetition times (TS) of 4.5s and 6s were found to yield the highest SNR efficiency for WMn MP-RAGE at 3T and 7T, respectively. Blurring was more sensitive to flip in WMn than in CSFn MP-RAGE and relatively insensitive to TR for both regimes. The 2D RFB scheme had 19% and 47% higher thalamic SNR and SNR efficiency than the 1D centric scheme for WMn MP-RAGE. Compared to 3T, SNR and SNR efficiency were higher for the 7T WMn regime by 56% and 41% respectively. MS lesions in the cortex and thalamus as well as thalamic subnuclei in tremor patients were clearly delineated using WMn MP-RAGE. Conclusion Optimization and new view ordering enabled MP-RAGE imaging with 0.8–1 mm3 isotropic spatial resolution in scan times of 5 minutes with whole brain coverage. PMID:24889754

General method for simultaneous optimization of light trapping and carrier collection in an ultra-thin film organic photovoltaic cell

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

Tsai, Cheng-Chia, E-mail: ct2443@columbia.edu; Grote, Richard R.; Beck, Jonathan H.

2014-07-14

We describe a general method for maximizing the short-circuit current in thin planar organic photovoltaic (OPV) heterojunction cells by simultaneous optimization of light absorption and carrier collection. Based on the experimentally obtained complex refractive indices of the OPV materials and the thickness-dependence of the internal quantum efficiency of the OPV active layer, we analyze the potential benefits of light trapping strategies for maximizing the overall power conversion efficiency of the cell. This approach provides a general strategy for optimizing the power conversion efficiency of a wide range of OPV structures. In particular, as an experimental trial system, the approach ismore » applied here to a ultra-thin film solar cell with a SubPc/C{sub 60} photovoltaic structure. Using a patterned indium tin oxide (ITO) top contact, the numerically optimized designs achieve short-circuit currents of 0.790 and 0.980 mA/cm{sup 2} for 30 nm and 45 nm SubPc/C{sub 60} heterojunction layer thicknesses, respectively. These values correspond to a power conversion efficiency enhancement of 78% for the 30 nm thick cell, but only of 32% for a 45 nm thick cell, for which the overall photocurrent is actually higher. Applied to other material systems, the general optimization method can elucidate if light trapping strategies can improve a given cell architecture.« less

An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.

2017-01-01

Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.

Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing.

PubMed

Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo

2018-04-18

Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

Optimization and experimental validation of stiff porous phononic plates for widest complete bandgap of mixed fundamental guided wave modes

NASA Astrophysics Data System (ADS)

Hedayatrasa, Saeid; Kersemans, Mathias; Abhary, Kazem; Uddin, Mohammad; Van Paepegem, Wim

2018-01-01

Phononic crystal plates (PhPs) have promising application in manipulation of guided waves for design of low-loss acoustic devices and built-in acoustic metamaterial lenses in plate structures. The prominent feature of phononic crystals is the existence of frequency bandgaps over which the waves are stopped, or are resonated and guided within appropriate defects. Therefore, maximized bandgaps of PhPs are desirable to enhance their phononic controllability. Porous PhPs produced through perforation of a uniform background plate, in which the porous interfaces act as strong reflectors of wave energy, are relatively easy to produce. However, the research in optimization of porous PhPs and experimental validation of achieved topologies has been very limited and particularly focused on bandgaps of flexural (asymmetric) wave modes. In this paper, porous PhPs are optimized through an efficient multiobjective genetic algorithm for widest complete bandgap of mixed fundamental guided wave modes (symmetric and asymmetric) and maximized stiffness. The Pareto front of optimization is analyzed and variation of bandgap efficiency with respect to stiffness is presented for various optimized topologies. Selected optimized topologies from the stiff and compliant regimes of Pareto front are manufactured by water-jetting an aluminum plate and their promising bandgap efficiency is experimentally observed. An optimized Pareto topology is also chosen and manufactured by laser cutting a Plexiglas (PMMA) plate, and its performance in self-collimation and focusing of guided waves is verified as compared to calculated dispersion properties.

[Workflow management in the operating room. Analysis of potentials for optimizing efficiency at a university hospital].

PubMed

Welker, A; Wolcke, B; Schleppers, A; Schmeck, S B; Focke, U; Gervais, H W; Schmeck, J

2010-10-01

The introduction of the diagnosis-related groups reimbursement system has increased cost pressures. Due to the interaction of many different professional groups, analysis and optimization of internal coordination and scheduling in the operating room (OR) is mandatory. The aim of this study was to analyze the processes at a university hospital in order to optimize strategies by identifying potential weak points. Over a period 6 weeks before and 4 weeks after intervention processes time intervals in the OR of a tertiary care hospital (university hospital) were documented in a structured data collection sheet. The main reason for lack of efficiency of labor was underused OR utilization. Multifactorial reasons, particularly in the management of perioperative interfaces, led to vacant ORs. A significant deficit was in the use of OR capacity at the end of the daily OR schedule. After harmonization of working hours of different staff groups and implementation of several other changes an increase in efficiency could be verified. These results indicate that optimization of perioperative processes considerably contribute to the success of OR organization. Additionally, the implementation of standard operating procedures and a generally accepted OR statute are mandatory. In this way an efficient OR management can contribute to the economic success of a hospital.

Acoustic reverse-time migration using GPU card and POSIX thread based on the adaptive optimal finite-difference scheme and the hybrid absorbing boundary condition

NASA Astrophysics Data System (ADS)

Cai, Xiaohui; Liu, Yang; Ren, Zhiming

2018-06-01

Reverse-time migration (RTM) is a powerful tool for imaging geologically complex structures such as steep-dip and subsalt. However, its implementation is quite computationally expensive. Recently, as a low-cost solution, the graphic processing unit (GPU) was introduced to improve the efficiency of RTM. In the paper, we develop three ameliorative strategies to implement RTM on GPU card. First, given the high accuracy and efficiency of the adaptive optimal finite-difference (FD) method based on least squares (LS) on central processing unit (CPU), we study the optimal LS-based FD method on GPU. Second, we develop the CPU-based hybrid absorbing boundary condition (ABC) to the GPU-based one by addressing two issues of the former when introduced to GPU card: time-consuming and chaotic threads. Third, for large-scale data, the combinatorial strategy for optimal checkpointing and efficient boundary storage is introduced for the trade-off between memory and recomputation. To save the time of communication between host and disk, the portable operating system interface (POSIX) thread is utilized to create the other CPU core at the checkpoints. Applications of the three strategies on GPU with the compute unified device architecture (CUDA) programming language in RTM demonstrate their efficiency and validity.

Light distribution in diffractive multifocal optics and its optimization.

PubMed

Portney, Valdemar

2011-11-01

To expand a geometrical model of diffraction efficiency and its interpretation to the multifocal optic and to introduce formulas for analysis of far and near light distribution and their application to multifocal intraocular lenses (IOLs) and to diffraction efficiency optimization. Medical device consulting firm, Newport Coast, California, USA. Experimental study. Application of a geometrical model to the kinoform (single focus diffractive optical element) was expanded to a multifocal optic to produce analytical definitions of light split between far and near images and light loss to other diffraction orders. The geometrical model gave a simple interpretation of light split in a diffractive multifocal IOL. An analytical definition of light split between far, near, and light loss was introduced as curve fitting formulas. Several examples of application to common multifocal diffractive IOLs were developed; for example, to light-split change with wavelength. The analytical definition of diffraction efficiency may assist in optimization of multifocal diffractive optics that minimize light loss. Formulas for analysis of light split between different foci of multifocal diffractive IOLs are useful in interpreting diffraction efficiency dependence on physical characteristics, such as blaze heights of the diffractive grooves and wavelength of light, as well as for optimizing multifocal diffractive optics. Disclosure is found in the footnotes. Copyright © 2011 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Fuzzy control based engine sizing optimization for a fuel cell/battery hybrid mini-bus

NASA Astrophysics Data System (ADS)

Kim, Minjin; Sohn, Young-Jun; Lee, Won-Yong; Kim, Chang-Soo

The fuel cell/battery hybrid vehicle has been focused for the alternative engine of the existing internal-combustion engine due to the following advantages of the fuel cell and the battery. Firstly, the fuel cell is highly efficient and eco-friendly. Secondly, the battery has the fast response for the changeable power demand. However, the competitive efficiency of the hybrid fuel cell vehicle is necessary to successfully alternate the conventional vehicles with the fuel cell hybrid vehicle. The most relevant factor which affects the overall efficiency of the hybrid fuel cell vehicle is the relative engine sizing between the fuel cell and the battery. Therefore the design method to optimize the engine sizing of the fuel cell hybrid vehicle has been proposed. The target system is the fuel cell/battery hybrid mini-bus and its power distribution is controlled based on the fuzzy logic. The optimal engine sizes are determined based on the simulator developed in this paper. The simulator includes the several models for the fuel cell, the battery, and the major balance of plants. After the engine sizing, the system efficiency and the stability of the power distribution are verified based on the well-known driving schedule. Consequently, the optimally designed mini-bus shows good performance.

Research of grasping algorithm based on scara industrial robot

NASA Astrophysics Data System (ADS)

Peng, Tao; Zuo, Ping; Yang, Hai

2018-04-01

As the tobacco industry grows, facing the challenge of the international tobacco giant, efficient logistics service is one of the key factors. How to complete the tobacco sorting task of efficient economy is the goal of tobacco sorting and optimization research. Now the cigarette distribution system uses a single line to carry out the single brand sorting task, this article adopts a single line to realize the cigarette sorting task of different brands. Using scara robot special algorithm for sorting and packaging, the optimization scheme significantly enhances the indicators of smoke sorting system. Saving labor productivity, obviously improve production efficiency.

Experiences in autotuning matrix multiplication for energy minimization on GPUs

DOE PAGES

Anzt, Hartwig; Haugen, Blake; Kurzak, Jakub; ...

2015-05-20

In this study, we report extensive results and analysis of autotuning the computationally intensive graphics processing units kernel for dense matrix–matrix multiplication in double precision. In contrast to traditional autotuning and/or optimization for runtime performance only, we also take the energy efficiency into account. For kernels achieving equal performance, we show significant differences in their energy balance. We also identify the memory throughput as the most influential metric that trades off performance and energy efficiency. Finally, as a result, the performance optimal case ends up not being the most efficient kernel in overall resource use.

Scott Horowitz | NREL

Science.gov Websites

area, which includes work on whole building energy modeling, cost-based optimization, model accuracy optimization tool used to provide support for the Building America program's teams and energy efficiency goals Colorado graduate student exploring enhancements to building optimization in terms of robustness and speed

Queue and stack sorting algorithm optimization and performance analysis

NASA Astrophysics Data System (ADS)

Qian, Mingzhu; Wang, Xiaobao

2018-04-01

Sorting algorithm is one of the basic operation of a variety of software development, in data structures course specializes in all kinds of sort algorithm. The performance of the sorting algorithm is directly related to the efficiency of the software. A lot of excellent scientific research queue is constantly optimizing algorithm, algorithm efficiency better as far as possible, the author here further research queue combined with stacks of sorting algorithms, the algorithm is mainly used for alternating operation queue and stack storage properties, Thus avoiding the need for a large number of exchange or mobile operations in the traditional sort. Before the existing basis to continue research, improvement and optimization, the focus on the optimization of the time complexity of the proposed optimization and improvement, The experimental results show that the improved effectively, at the same time and the time complexity and space complexity of the algorithm, the stability study corresponding research. The improvement and optimization algorithm, improves the practicability.

Optimization of composite sandwich cover panels subjected to compressive loadings

NASA Technical Reports Server (NTRS)

Cruz, Juan R.

1991-01-01

An analysis and design method is presented for the design of composite sandwich cover panels that includes transverse shear effects and damage tolerance considerations. This method is incorporated into an optimization program called SANDOP (SANDwich OPtimization). SANDOP is used in the present study to design optimized composite sandwich cover panels for transport aircraft wing applications as a demonstration of its capabilities. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to identical constraints. Results indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and plus or minus 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

PubMed Central

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Optimized zein nanospheres for improved oral bioavailability of atorvastatin

PubMed Central

Hashem, Fahima M; Al-Sawahli, Majid M; Nasr, Mohamed; Ahmed, Osama AA

2015-01-01

Background This work focuses on the development of atorvastatin utilizing zein, a natural, safe, and biocompatible polymer, as a nanosized formulation in order to overcome the poor oral bioavailability (12%) of the drug. Methods Twelve experimental runs of atorvastatin–zein nanosphere formula were formulated by a liquid–liquid phase separation method according to custom fractional factorial design to optimize the formulation variables. The factors studied were: weight % of zein to atorvastatin (X1), pH (X2), and stirring time (X3). Levels for each formulation variable were designed. The selected dependent variables were: mean particle size (Y1), zeta potential (Y2), drug loading efficiency (Y3), drug encapsulation efficiency (Y4), and yield (Y5). The optimized formulation was assayed for compatibility using an X-ray diffraction assay. In vitro diffusion of the optimized formulation was carried out. A pharmacokinetic study was also done to compare the plasma profile of the atorvastatin–zein nanosphere formulation versus atorvastatin oral suspension and the commercially available tablet. Results The optimized atorvastatin–zein formulation had a mean particle size of 183 nm, a loading efficiency of 14.86%, and an encapsulation efficiency of 29.71%. The in vitro dissolution assay displayed an initial burst effect, with a cumulative amount of atorvastatin released of 41.76% and 82.3% after 12 and 48 hours, respectively. In Wistar albino rats, the bioavailability of atorvastatin from the optimized atorvastatin–zein formulation was 3-fold greater than that from the atorvastatin suspension and the commercially available tablet. Conclusion The atorvastatin–zein nanosphere formulation improved the oral delivery and pharmacokinetic profile of atorvastatin by enhancing its oral bioavailability. PMID:26150716

Diffusion Monte Carlo approach versus adiabatic computation for local Hamiltonians

NASA Astrophysics Data System (ADS)

Bringewatt, Jacob; Dorland, William; Jordan, Stephen P.; Mink, Alan

2018-02-01

Most research regarding quantum adiabatic optimization has focused on stoquastic Hamiltonians, whose ground states can be expressed with only real non-negative amplitudes and thus for whom destructive interference is not manifest. This raises the question of whether classical Monte Carlo algorithms can efficiently simulate quantum adiabatic optimization with stoquastic Hamiltonians. Recent results have given counterexamples in which path-integral and diffusion Monte Carlo fail to do so. However, most adiabatic optimization algorithms, such as for solving MAX-k -SAT problems, use k -local Hamiltonians, whereas our previous counterexample for diffusion Monte Carlo involved n -body interactions. Here we present a 6-local counterexample which demonstrates that even for these local Hamiltonians there are cases where diffusion Monte Carlo cannot efficiently simulate quantum adiabatic optimization. Furthermore, we perform empirical testing of diffusion Monte Carlo on a standard well-studied class of permutation-symmetric tunneling problems and similarly find large advantages for quantum optimization over diffusion Monte Carlo.

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

A framework for parallelized efficient global optimization with application to vehicle crashworthiness optimization

NASA Astrophysics Data System (ADS)

Hamza, Karim; Shalaby, Mohamed

2014-09-01

This article presents a framework for simulation-based design optimization of computationally expensive problems, where economizing the generation of sample designs is highly desirable. One popular approach for such problems is efficient global optimization (EGO), where an initial set of design samples is used to construct a kriging model, which is then used to generate new 'infill' sample designs at regions of the search space where there is high expectancy of improvement. This article attempts to address one of the limitations of EGO, where generation of infill samples can become a difficult optimization problem in its own right, as well as allow the generation of multiple samples at a time in order to take advantage of parallel computing in the evaluation of the new samples. The proposed approach is tested on analytical functions, and then applied to the vehicle crashworthiness design of a full Geo Metro model undergoing frontal crash conditions.

Data on cost-optimal Nearly Zero Energy Buildings (NZEBs) across Europe.

PubMed

D'Agostino, Delia; Parker, Danny

2018-04-01

This data article refers to the research paper A model for the cost-optimal design of Nearly Zero Energy Buildings (NZEBs) in representative climates across Europe [1]. The reported data deal with the design optimization of a residential building prototype located in representative European locations. The study focus on the research of cost-optimal choices and efficiency measures in new buildings depending on the climate. The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data allow to visualize energy consumption before and after the optimization, selected efficiency measures, costs and renewable production. The reduction of electricity and natural gas consumption towards the NZEB target can be visualized together with incremental and cumulative costs in each location. Further data is available about building geometry, costs, CO 2 emissions, envelope, materials, lighting, appliances and systems.

Optimization-based additive decomposition of weakly coercive problems with applications

DOE PAGES

Bochev, Pavel B.; Ridzal, Denis

2016-01-27

In this study, we present an abstract mathematical framework for an optimization-based additive decomposition of a large class of variational problems into a collection of concurrent subproblems. The framework replaces a given monolithic problem by an equivalent constrained optimization formulation in which the subproblems define the optimization constraints and the objective is to minimize the mismatch between their solutions. The significance of this reformulation stems from the fact that one can solve the resulting optimality system by an iterative process involving only solutions of the subproblems. Consequently, assuming that stable numerical methods and efficient solvers are available for every subproblem,more » our reformulation leads to robust and efficient numerical algorithms for a given monolithic problem by breaking it into subproblems that can be handled more easily. An application of the framework to the Oseen equations illustrates its potential.« less

Dependence of optimal initial density on laser parameters for multi-keV x-ray radiators generated by nanosecond laser-produced underdense plasma

NASA Astrophysics Data System (ADS)

Tu, Shao-yong; Yuan, Yong-teng; Hu, Guang-yue; Miao, Wen-yong; Zhao, Bin; Zheng, Jian; Jiang, Shao-en; Ding, Yong-kun

2016-01-01

Efficient multi-keV x-ray sources can be produced using nanosecond laser pulse-heated middle-Z underdense plasmas generated using gas or foam. Previous experimental results show that an optimal initial target density exists for efficient multi-keV x-ray emission at which the laser ionization wave is supersonic. Here we explore the influence of the laser intensity and the pulse duration on this optimal initial target density via a one-dimensional radiation hydrodynamic simulation. The simulation shows that the optimal initial density is sensitive to both the laser intensity and the pulse duration. However, the speed of the supersonic ionization wave at the end of the laser irradiation is always maintained at 1.5 to 1.7 times that of the ion acoustic wave under the optimal initial density conditions.

Tunable, Flexible and Efficient Optimization of Control Pulses for Superconducting Qubits, part II - Applications

NASA Astrophysics Data System (ADS)

AsséMat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank

In part I, we presented the theoretic foundations of the GOAT algorithm for the optimal control of quantum systems. Here in part II, we focus on several applications of GOAT to superconducting qubits architecture. First, we consider a control-Z gate on Xmons qubits with an Erf parametrization of the optimal pulse. We show that a fast and accurate gate can be obtained with only 16 parameters, as compared to hundreds of parameters required in other algorithms. We present numerical evidences that such parametrization should allow an efficient in-situ calibration of the pulse. Next, we consider the flux-tunable coupler by IBM. We show optimization can be carried out in a more realistic model of the system than was employed in the original study, which is expected to further simplify the calibration process. Moreover, GOAT reduced the complexity of the optimal pulse to only 6 Fourier components, composed with analytic wrappers.

Tree crickets optimize the acoustics of baffles to exaggerate their mate-attraction signal.

PubMed

Mhatre, Natasha; Malkin, Robert; Deb, Rittik; Balakrishnan, Rohini; Robert, Daniel

2017-12-11

Object manufacture in insects is typically inherited, and believed to be highly stereotyped. Optimization, the ability to select the functionally best material and modify it appropriately for a specific function, implies flexibility and is usually thought to be incompatible with inherited behaviour. Here, we show that tree-crickets optimize acoustic baffles, objects that are used to increase the effective loudness of mate-attraction calls. We quantified the acoustic efficiency of all baffles within the naturally feasible design space using finite-element modelling and found that design affects efficiency significantly. We tested the baffle-making behaviour of tree crickets in a series of experimental contexts. We found that given the opportunity, tree crickets optimised baffle acoustics; they selected the best sized object and modified it appropriately to make a near optimal baffle. Surprisingly, optimization could be achieved in a single attempt, and is likely to be achieved through an inherited yet highly accurate behavioural heuristic.

Aerodynamic design and optimization in one shot

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo; Kuruvila, G.; Salas, M. D.

1992-01-01

This paper describes an efficient numerical approach for the design and optimization of aerodynamic bodies. As in classical optimal control methods, the present approach introduces a cost function and a costate variable (Lagrange multiplier) in order to achieve a minimum. High efficiency is achieved by using a multigrid technique to solve for all the unknowns simultaneously, but restricting work on a design variable only to grids on which their changes produce nonsmooth perturbations. Thus, the effort required to evaluate design variables that have nonlocal effects on the solution is confined to the coarse grids. However, if a variable has a nonsmooth local effect on the solution in some neighborhood, it is relaxed in that neighborhood on finer grids. The cost of solving the optimal control problem is shown to be approximately two to three times the cost of the equivalent analysis problem. Examples are presented to illustrate the application of the method to aerodynamic design and constraint optimization.

Research on design method of the full form ship with minimum thrust deduction factor

NASA Astrophysics Data System (ADS)

Zhang, Bao-ji; Miao, Ai-qin; Zhang, Zhu-xin

2015-04-01

In the preliminary design stage of the full form ships, in order to obtain a hull form with low resistance and maximum propulsion efficiency, an optimization design program for a full form ship with the minimum thrust deduction factor has been developed, which combined the potential flow theory and boundary layer theory with the optimization technique. In the optimization process, the Sequential Unconstrained Minimization Technique (SUMT) interior point method of Nonlinear Programming (NLP) was proposed with the minimum thrust deduction factor as the objective function. An appropriate displacement is a basic constraint condition, and the boundary layer separation is an additional one. The parameters of the hull form modification function are used as design variables. At last, the numerical optimization example for lines of after-body of 50000 DWT product oil tanker was provided, which indicated that the propulsion efficiency was improved distinctly by this optimal design method.

TU-EF-304-07: Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Proton Therapy

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

Li, Y; UT Southwestern Medical Center, Dallas, TX; Tian, Z

2015-06-15

Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC intomore » IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical usages.« less

Optimization of a gene electrotransfer procedure for efficient intradermal immunization with an hTERT-based DNA vaccine in mice

PubMed Central

Calvet, Christophe Y; Thalmensi, Jessie; Liard, Christelle; Pliquet, Elodie; Bestetti, Thomas; Huet, Thierry; Langlade-Demoyen, Pierre; Mir, Lluis M

2014-01-01

DNA vaccination consists in administering an antigen-encoding plasmid in order to trigger a specific immune response. This specific vaccine strategy is of particular interest to fight against various infectious diseases and cancer. Gene electrotransfer is the most efficient and safest non-viral gene transfer procedure and specific electrical parameters have been developed for several target tissues. Here, a gene electrotransfer protocol into the skin has been optimized in mice for efficient intradermal immunization against the well-known telomerase tumor antigen. First, the luciferase reporter gene was used to evaluate gene electrotransfer efficiency into the skin as a function of the electrical parameters and electrodes, either non-invasive or invasive. In a second time, these parameters were tested for their potency to generate specific cellular CD8 immune responses against telomerase epitopes. These CD8 T-cells were fully functional as they secreted IFNγ and were endowed with specific cytotoxic activity towards target cells. This simple and optimized procedure for efficient gene electrotransfer into the skin using the telomerase antigen is to be used in cancer patients for the phase 1 clinical evaluation of a therapeutic cancer DNA vaccine called INVAC-1. PMID:26015983

Optimization of intrinsic layer thickness, dopant layer thickness and concentration for a-SiC/a-SiGe multilayer solar cell efficiency performance using Silvaco software

NASA Astrophysics Data System (ADS)

Yuan, Wong Wei; Natashah Norizan, Mohd; Salwani Mohamad, Ili; Jamalullail, Nurnaeimah; Hidayah Saad, Nor

2017-11-01

Solar cell is expanding as green renewable alternative to conventional fossil fuel electricity generation, but compared to other land-used electrical generators, it is a comparative beginner. Many applications covered by solar cells starting from low power mobile devices, terrestrial, satellites and many more. To date, the highest efficiency solar cell is given by GaAs based multilayer solar cell. However, this material is very expensive in fabrication and material costs compared to silicon which is cheaper due to the abundance of supply. Thus, this research is devoted to develop multilayer solar cell by combining two different layers of P-I-N structures with silicon carbide and silicon germanium. This research focused on optimising the intrinsic layer thickness, p-doped layer thickness and concentration, n-doped layer thickness and concentration in achieving the highest efficiency. As a result, both single layer a-SiC and a-SiGe showed positive efficiency improvement with the record of 27.19% and 9.07% respectively via parametric optimization. The optimized parameters is then applied on both SiC and SiGe P-I-N layers and resulted the convincing efficiency of 33.80%.

Numerical study on the influence of boss cap fins on efficiency of controllable-pitch propeller

NASA Astrophysics Data System (ADS)

Xiong, Ying; Wang, Zhanzhi; Qi, Wanjiang

2013-03-01

Numerical simulation is investigated to disclose how propeller boss cap fins (PBCF) operate utilizing Reynolds-averaged Navier-Stokes (RANS) method. In addition, exploration of the influencing mechanism of PBCF on the open water efficiency of one controllable-pitch propeller is analyzed through the open water characteristic curves, blade surface pressure distribution and hub streamline distribution. On this basis, the influence of parameters including airfoil profile, diameter, axial position of installation and circumferential installation angle on the open water efficiency of the controllable-pitch propeller is investigated. Numerical results show: for the controllable-pitch propeller, the thrust generated is at the optimum when the radius of boss cap fins is 1.5 times of propeller hub with an optimal installation position in the axial direction, and its optimal circumferential installation position is the midpoint of the extension line of the front and back ends of two adjacent propeller roots in the front of fin root. Under these optimal parameters, the gain of open water efficiency of the controllable-pitch propeller with different advance velocity coefficients is greater than 0.01, which accounts for approximately an increase of 1%-5% of open water efficiency.

Optimization of the transductional efficiency of lentiviral vectors: effect of sera and polycations

PubMed Central

Denning, Warren; Das, Suvendu; Guo, Siqi; Xu, Jun; Kappes, John C.; Hel, Zdenek

2012-01-01

Lentiviral vectors are widely used as effective gene-delivery vehicles. Optimization of the conditions for efficient lentiviral transduction is of a high importance for a variety of research applications. Presence of positively-charged polycations reduces the electrostatic repulsion forces between a negatively-charged cell and an approaching enveloped lentiviral particle resulting in an increase in the transduction efficiency. Although a variety of polycations are commonly used to enhance the transduction with retroviruses, the relative effect of various types of polycations on the efficiency of transduction and on the potential bias in the determination of titer of lentiviral vectors is not fully understood. Here we present data suggesting that DEAE-dextran provides superior results in enhancing lentiviral transduction of most tested cell lines and primary cell cultures. Specific type and source of serum affects the efficiency of transduction of target cell populations. Non-specific binding of enhanced green fluorescent protein (EGFP)-containing membrane aggregates in the presence of DEAE-dextran does not significantly affect the determination of the titer of EGFP-expressing lentiviral vectors. In conclusion, various polycations and types of sera should be tested when optimizing lentiviral transduction of target cell populations. PMID:22407723

Optimization of the transductional efficiency of lentiviral vectors: effect of sera and polycations.

PubMed

Denning, Warren; Das, Suvendu; Guo, Siqi; Xu, Jun; Kappes, John C; Hel, Zdenek

2013-03-01

Lentiviral vectors are widely used as effective gene-delivery vehicles. Optimization of the conditions for efficient lentiviral transduction is of a high importance for a variety of research applications. Presence of positively charged polycations reduces the electrostatic repulsion forces between a negatively charged cell and an approaching enveloped lentiviral particle resulting in an increase in the transduction efficiency. Although a variety of polycations are commonly used to enhance the transduction with retroviruses, the relative effect of various types of polycations on the efficiency of transduction and on the potential bias in the determination of titer of lentiviral vectors is not fully understood. Here, we present data suggesting that DEAE-dextran provides superior results in enhancing lentiviral transduction of most tested cell lines and primary cell cultures. Specific type and source of serum affects the efficiency of transduction of target cell populations. Non-specific binding of enhanced green fluorescent protein (EGFP)-containing membrane aggregates in the presence of DEAE-dextran does not significantly affect the determination of the titer of EGFP-expressing lentiviral vectors. In conclusion, various polycations and types of sera should be tested when optimizing lentiviral transduction of target cell populations.

Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation.

PubMed

Aguilar, I; Misztal, I; Legarra, A; Tsuruta, S

2011-12-01

Genomic evaluations can be calculated using a unified procedure that combines phenotypic, pedigree and genomic information. Implementation of such a procedure requires the inverse of the relationship matrix based on pedigree and genomic relationships. The objective of this study was to investigate efficient computing options to create relationship matrices based on genomic markers and pedigree information as well as their inverses. SNP maker information was simulated for a panel of 40 K SNPs, with the number of genotyped animals up to 30 000. Matrix multiplication in the computation of the genomic relationship was by a simple 'do' loop, by two optimized versions of the loop, and by a specific matrix multiplication subroutine. Inversion was by a generalized inverse algorithm and by a LAPACK subroutine. With the most efficient choices and parallel processing, creation of matrices for 30 000 animals would take a few hours. Matrices required to implement a unified approach can be computed efficiently. Optimizations can be either by modifications of existing code or by the use of efficient automatic optimizations provided by open source or third-party libraries. © 2011 Blackwell Verlag GmbH.

Efficiency improvement of GaN-on-silicon thin-film light-emitting diodes with optimized via-like n-electrodes

NASA Astrophysics Data System (ADS)

Feng, Bo; Deng, Biao; Fu, Yi; Liu, Le Gong; Li, Zeng Cheng; Feng, Mei Xin; Zhao, Han Min; Sun, Qian

2017-07-01

This work reports a significant improvement in efficiency by optimizing the via-like n-electrode architecture design of a GaN-based thin-film LED grown on a 6-inch silicon substrate. The external quantum efficiency of the as-fabricated 1.1 mm × 1.1 mm via-thin-film LED chip at 350 mA was increased by 11.3% compared to that of a vertical thin-film LED chip with a conventional finger-like n-electrode. Detailed analysis of encapsulation gain and false color emission patterns illustrated that the significantly improved LED performance was due to enhanced light extraction efficiency and more uniform current spreading, both of which can be attributed to the optimized via-thin-film chip structure. Minimizing the light loss at the periphery of the Ag mirror was demonstrated to be a critical factor for improving light extraction, rather than simply replacing the finger-like n-electrodes with via-like ones. After encapsulation, the median blue lamp power and the wall-plug efficiency of the via-thin-film LED at 350 mA reached 659 mW and 63.7%, respectively.

Optimization of operation conditions and configurations for solid-propellant ducted rocket combustors

NASA Astrophysics Data System (ADS)

Onn, Shing-Chung; Chiang, Hau-Jei; Hwang, Hang-Che; Wei, Jen-Ko; Cherng, Dao-Lien

1993-06-01

The dynamic behavior of a 2D turbulent mixing and combustion process has been studied numerically in the main combustion chamber of a solid-propellant ducted rocket (SDR). The mathematical model is based on the Favre-averaged conservation equations developed by Cherng (1990). Combustion efficiency, rather than specific impulse from earlier studies, is applied successfully to optimize the effects of two parameters by a multiple linear regression model. Specifically, the fuel-air equivalence ratio of the operating conditions and the air inlet location of configurations for the SDR combustor have been studied. For a equivalence ratio near the stoichiometric condition, the use of specific impulse or combustion efficiency will show similar trend in characterizing the reacting flow field in the combustor. For the overall fuel lean operating conditions, the change of combustion efficiency is much more sensitive to that of air inlet location than specific impulse does, suggesting combustion efficiency a better property than specific impulse in representing the condition toward flammability limits. In addition, the air inlet for maximum efficiency, in general, appears to be located at downstream of that for highest specific impulse. The optimal case for the effects of two parameters occurs at fuel lean condition, which shows a larger recirculation zone in front, deeper penetration of ram air into the combustor and much larger high temperature zone near the centerline of the combustor exit than those shown in the optimal case for overall equivalence ratio close to stoichiometric.

Design, simulation, and optimization of an RGB polarization independent transmission volume hologram

NASA Astrophysics Data System (ADS)

Mahamat, Adoum Hassan

Volume phase holographic (VPH) gratings have been designed for use in many areas of science and technology such as optical communication, medical imaging, spectroscopy and astronomy. The goal of this dissertation is to design a volume phase holographic grating that provides diffraction efficiencies of at least 70% for the entire visible wavelengths and higher than 90% for red, green, and blue light when the incident light is unpolarized. First, the complete design, simulation and optimization of the volume hologram are presented. The optimization is done using a Monte Carlo analysis to solve for the index modulation needed to provide higher diffraction efficiencies. The solutions are determined by solving the diffraction efficiency equations determined by Kogelnik's two wave coupled-wave theory. The hologram is further optimized using the rigorous coupled-wave analysis to correct for effects of absorption omitted by Kogelnik's method. Second, the fabrication or recording process of the volume hologram is described in detail. The active region of the volume hologram is created by interference of two coherent beams within the thin film. Third, the experimental set up and measurement of some properties including the diffraction efficiencies of the volume hologram, and the thickness of the active region are conducted. Fourth, the polarimetric response of the volume hologram is investigated. The polarization study is developed to provide insight into the effect of the refractive index modulation onto the polarization state and diffraction efficiency of incident light.

Optimal layout design of obstacles for panic evacuation using differential evolution

NASA Astrophysics Data System (ADS)

Zhao, Yongxiang; Li, Meifang; Lu, Xin; Tian, Lijun; Yu, Zhiyong; Huang, Kai; Wang, Yana; Li, Ting

2017-01-01

To improve the pedestrian outflow in panic situations by suitably placing an obstacle in front of the exit, it is vital to understand the physical mechanism behind the evacuation efficiency enhancement. In this paper, a robust differential evolution is firstly employed to optimize the geometrical parameters of different shaped obstacles in order to achieve an optimal evacuation efficiency. Moreover, it is found that all the geometrical parameters of obstacles could markedly influence the evacuation efficiency of pedestrians, and the best way for achieving an optimal pedestrian outflow is to slightly shift the obstacle from the center of the exit which is consistent with findings of extant literature. Most importantly, by analyzing the profiles of density, velocity and specific flow, as well as the spatial distribution of crowd pressure, we have proven that placing an obstacle in panic situations does not reduce or absorb the pressure in the region of exit, on the contrary, promotes the pressure to a much higher level, hence the physical mechanism behind the evacuation efficiency enhancement is not a pressure decrease in the region of exit, but a significant reduction of high density region by effective separation in space which finally causes the increasing of escape speed and evacuation outflow. Finally, it is clearly demonstrated that the panel-like obstacle is considerably more robust and stable than the pillar-like obstacle to guarantee the enhancement of evacuation efficiency under different initial pedestrian distributions, different initial crowd densities as well as different desired velocities.

Axioms of adaptivity

PubMed Central

Carstensen, C.; Feischl, M.; Page, M.; Praetorius, D.

2014-01-01

This paper aims first at a simultaneous axiomatic presentation of the proof of optimal convergence rates for adaptive finite element methods and second at some refinements of particular questions like the avoidance of (discrete) lower bounds, inexact solvers, inhomogeneous boundary data, or the use of equivalent error estimators. Solely four axioms guarantee the optimality in terms of the error estimators. Compared to the state of the art in the temporary literature, the improvements of this article can be summarized as follows: First, a general framework is presented which covers the existing literature on optimality of adaptive schemes. The abstract analysis covers linear as well as nonlinear problems and is independent of the underlying finite element or boundary element method. Second, efficiency of the error estimator is neither needed to prove convergence nor quasi-optimal convergence behavior of the error estimator. In this paper, efficiency exclusively characterizes the approximation classes involved in terms of the best-approximation error and data resolution and so the upper bound on the optimal marking parameters does not depend on the efficiency constant. Third, some general quasi-Galerkin orthogonality is not only sufficient, but also necessary for the R-linear convergence of the error estimator, which is a fundamental ingredient in the current quasi-optimality analysis due to Stevenson 2007. Finally, the general analysis allows for equivalent error estimators and inexact solvers as well as different non-homogeneous and mixed boundary conditions. PMID:25983390

Ultra-high enhancement of light focusing through disordered media controlled by mega-pixel modes (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yu, Hyeonseung; Lee, KyeoReh; Park, YongKeun

2017-02-01

Developing an efficient strategy for light focusing through scattering media is an important topic in the study of multiple light scattering. The enhancement factor of the light focusing, defined as the ratio between the optimized intensity and the background intensity is proportional to the number of controlling modes in a spatial light modulator (SLM). The demonstrated enhancement factors in previous studies are typically less than 1,000 due to several limiting factors, such as the slow refresh rate of a LCoS SLM, long optimization time, and lack of an efficient algorithm for high controlling modes. A digital micro-mirror device is an amplitude modulator, which is recently widely used for fast optimization through dynamic biological tissues. The fast frame rate of the DMD up to 16 kHz can also be exploited for increasing the number of controlling modes. However, the manipulation of large pattern data and efficient calculation of the optimized pattern remained as an issue. In this work, we demonstrate the enhancement factor more than 100,000 in focusing through scattering media by using 1 Mega controlling modes of a DMD. Through careful synchronization between a DMD, a photo-detector and an additional computer for parallel optimization, we achieved the unprecedented enhancement factor with 75 mins of the optimization time. We discuss the design principles of the system and the possible applications of the enhanced light focusing.

Optimization of controlled release nanoparticle formulation of verapamil hydrochloride using artificial neural networks with genetic algorithm and response surface methodology.

PubMed

Li, Yongqiang; Abbaspour, Mohammadreza R; Grootendorst, Paul V; Rauth, Andrew M; Wu, Xiao Yu

2015-08-01

This study was performed to optimize the formulation of polymer-lipid hybrid nanoparticles (PLN) for the delivery of an ionic water-soluble drug, verapamil hydrochloride (VRP) and to investigate the roles of formulation factors. Modeling and optimization were conducted based on a spherical central composite design. Three formulation factors, i.e., weight ratio of drug to lipid (X1), and concentrations of Tween 80 (X2) and Pluronic F68 (X3), were chosen as independent variables. Drug loading efficiency (Y1) and mean particle size (Y2) of PLN were selected as dependent variables. The predictive performance of artificial neural networks (ANN) and the response surface methodology (RSM) were compared. As ANN was found to exhibit better recognition and generalization capability over RSM, multi-objective optimization of PLN was then conducted based upon the validated ANN models and continuous genetic algorithms (GA). The optimal PLN possess a high drug loading efficiency (92.4%, w/w) and a small mean particle size (∼100nm). The predicted response variables matched well with the observed results. The three formulation factors exhibited different effects on the properties of PLN. ANN in coordination with continuous GA represent an effective and efficient approach to optimize the PLN formulation of VRP with desired properties. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization and evaluation of gastroretentive ranitidine HCl microspheres by using design expert software.

PubMed

Hooda, Aashima; Nanda, Arun; Jain, Manish; Kumar, Vikash; Rathee, Permender

2012-12-01

The current study involves the development and optimization of their drug entrapment and ex vivo bioadhesion of multiunit chitosan based floating system containing Ranitidine HCl by ionotropic gelation method for gastroretentive delivery. Chitosan being cationic, non-toxic, biocompatible, biodegradable and bioadhesive is frequently used as a material for drug delivery systems and used to transport a drug to an acidic environment where it enhances the transport of polar drugs across epithelial surfaces. The effect of various process variables like drug polymer ratio, concentration of sodium tripolyphosphate and stirring speed on various physiochemical properties like drug entrapment efficiency, particle size and bioadhesion was optimized using central composite design and analyzed using response surface methodology. The observed responses were coincided well with the predicted values given by the optimization technique. The optimized microspheres showed drug entrapment efficiency of 74.73%, particle size 707.26 μm and bioadhesion 71.68% in simulated gastric fluid (pH 1.2) after 8 h with floating lag time 40s. The average size of all the dried microspheres ranged from 608.24 to 720.80 μm. The drug entrapment efficiency of microspheres ranged from 41.67% to 87.58% and bioadhesion ranged from 62% to 86%. Accelerated stability study was performed on optimized formulation as per ICH guidelines and no significant change was found in drug content on storage. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimized efficient liver T1ρ mapping using limited spin lock times

NASA Astrophysics Data System (ADS)

Yuan, Jing; Zhao, Feng; Griffith, James F.; Chan, Queenie; Wang, Yi-Xiang J.

2012-03-01

T1ρ relaxation has recently been found to be sensitive to liver fibrosis and has potential to be used for early detection of liver fibrosis and grading. Liver T1ρ imaging and accurate mapping are challenging because of the long scan time, respiration motion and high specific absorption rate. Reduction and optimization of spin lock times (TSLs) are an efficient way to reduce scan time and radiofrequency energy deposition of T1ρ imaging, but maintain the near-optimal precision of T1ρ mapping. This work analyzes the precision in T1ρ estimation with limited, in particular two, spin lock times, and explores the feasibility of using two specific operator-selected TSLs for efficient and accurate liver T1ρ mapping. Two optimized TSLs were derived by theoretical analysis and numerical simulations first, and tested experimentally by in vivo rat liver T1ρ imaging at 3 T. The simulation showed that the TSLs of 1 and 50 ms gave optimal T1ρ estimation in a range of 10-100 ms. In the experiment, no significant statistical difference was found between the T1ρ maps generated using the optimized two-TSL combination and the maps generated using the six TSLs of [1, 10, 20, 30, 40, 50] ms according to one-way ANOVA analysis (p = 0.1364 for liver and p = 0.8708 for muscle).

V-Assembly Dual-Head Efficient Resonator (VADER) for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Coyle, D. Barry; Kay, Richard B.; Stysley, Paul R.; Clark, Greg; Poulios, Demetrios; Frederickson, Robert; Blalock, Gordon; Arnold, Ed; Cory, Ken

2011-01-01

The V-Assembly Dual-head Efficient Resonator (VADER) is a diode pumped, Nd:YAG, Q-switched, positive branch unstable resonator that employs a split laser gain module designed for optimal efficiency and thermal lensing compensation.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

PubMed

Dai, Cai; Wang, Yuping; Ye, Miao; Xue, Xingsi; Liu, Hailin

2016-12-01

Research on multiobjective optimization problems becomes one of the hottest topics of intelligent computation. In order to improve the search efficiency of an evolutionary algorithm and maintain the diversity of solutions, in this paper, the learning automata (LA) is first used for quantization orthogonal crossover (QOX), and a new fitness function based on decomposition is proposed to achieve these two purposes. Based on these, an orthogonal evolutionary algorithm with LA for complex multiobjective optimization problems with continuous variables is proposed. The experimental results show that in continuous states, the proposed algorithm is able to achieve accurate Pareto-optimal sets and wide Pareto-optimal fronts efficiently. Moreover, the comparison with the several existing well-known algorithms: nondominated sorting genetic algorithm II, decomposition-based multiobjective evolutionary algorithm, decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes, multiobjective optimization by LA, and multiobjective immune algorithm with nondominated neighbor-based selection, on 15 multiobjective benchmark problems, shows that the proposed algorithm is able to find more accurate and evenly distributed Pareto-optimal fronts than the compared ones.

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

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

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

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

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

Singh, Punit; Nestmann, Franz

2009-09-15

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

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Highly efficient organic electroluminescent diodes realized by efficient charge balance with optimized electron and hole transport layers

NASA Astrophysics Data System (ADS)

Khan, M. A.; Xu, Wei; Wei, Fuxiang; Bai, Yu; Jiang, X. Y.; Zhang, Z. L.; Zhu, W. Q.

2007-11-01

Highly efficient organic electroluminescent devices (OLEDs) were developed based on 4,7-diphenyl-1, 10-phenanthroline (BPhen) as the electron transport layer (ETL), tris-(8-hydroxyquinoline) aluminum (Alq 3) as the emission layer (EML) and N,Ń-bis-[1-naphthy(-N,Ńdiphenyl-1,1'-biphenyl-4,4'-diamine)] (NPB) as the hole transport layer (HTL). The typical device structure was glass substrate/ ITO/ NPB/ Alq 3/ BPhen/ LiF/ Al. Since BPhen possesses a considerable high electron mobility of 5×10 -4 cm 2 V -1 s -1, devices with BPhen as ETL can realize an extremely high luminous efficiency. By optimizing the thickness of both HTL and ETL, we obtained a highly efficient OLED with a current efficiency of 6.80 cd/A and luminance of 1361 cd/m 2 at a current density of 20 mA/cm 2. This dramatic improvement in the current efficiency has been explained on the principle of charge balance.

Inverse design of near unity efficiency perfectly vertical grating couplers.

PubMed

Michaels, Andrew; Yablonovitch, Eli

2018-02-19

Efficient coupling between integrated optical waveguides and optical fibers is essential to the success of silicon photonics. While many solutions exist, perfectly vertical grating couplers that scatter light out of a waveguide in the direction normal to the waveguide's top surface are an ideal candidate due to their potential to reduce packaging complexity. Designing such couplers with high efficiencies, however, has proven difficult. In this paper, we use inverse electromagnetic design techniques to optimize a high efficiency two-layer perfectly vertical silicon grating coupler. Our base design achieves a chip-to-fiber coupling efficiency of 99.2% (-0.035 dB) at 1550 nm. Using this base design as a starting point, we run subsequent constrained optimizations to realize vertical couplers with coupling efficiencies over 96% and back reflections of less than -40 dB which can be fabricated using 65 nm-resolution lithography. These results demonstrate a new path forward for designing fabrication-tolerant ultra high efficiency grating couplers.

General Methodology Combining Engineering Optimization of Primary HVAC and R Plants with Decision Analysis Methods--Part II: Uncertainty and Decision Analysis

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

Jiang, Wei; Reddy, T. A.; Gurian, Patrick

2007-01-31

A companion paper to Jiang and Reddy that presents a general and computationally efficient methodology for dyanmic scheduling and optimal control of complex primary HVAC&R plants using a deterministic engineering optimization approach.

High-Fidelity Aerostructural Design Optimization of Transport Aircraft with Continuous Morphing Trailing Edge Technology

NASA Astrophysics Data System (ADS)

Burdette, David A., Jr.

Adaptive morphing trailing edge technology offers the potential to decrease the fuel burn of transonic commercial transport aircraft by allowing wings to dynamically adjust to changing flight conditions. Current configurations allow flap and aileron droop; however, this approach provides limited degrees of freedom and increased drag produced by gaps in the wing's surface. Leading members in the aeronautics community including NASA, AFRL, Boeing, and a number of academic institutions have extensively researched morphing technology for its potential to improve aircraft efficiency. With modern computational tools it is possible to accurately and efficiently model aircraft configurations in order to quantify the efficiency improvements offered by mor- phing technology. Coupled high-fidelity aerodynamic and structural solvers provide the capability to model and thoroughly understand the nuanced trade-offs involved in aircraft design. This capability is important for a detailed study of the capabilities of morphing trailing edge technology. Gradient-based multidisciplinary design opti- mization provides the ability to efficiently traverse design spaces and optimize the trade-offs associated with the design. This thesis presents a number of optimization studies comparing optimized config- urations with and without morphing trailing edge devices. The baseline configuration used throughout this work is the NASA Common Research Model. The first opti- mization comparison considers the optimal fuel burn predicted by the Breguet range equation at a single cruise point. This initial singlepoint optimization comparison demonstrated a limited fuel burn savings of less than 1%. Given the effectiveness of the passive aeroelastic tailoring in the optimized non-morphing wing, the singlepoint optimization offered limited potential for morphing technology to provide any bene- fit. To provide a more appropriate comparison, a number of multipoint optimizations were performed. With a 3-point stencil, the morphing wing burned 2.53% less fuel than its optimized non-morphing counterpart. Expanding further to a 7-point stencil, the morphing wing used 5.04% less fuel. Additional studies demonstrate that the size of the morphing device can be reduced without sizable performance reductions, and that as aircraft wings' aspect ratios increase, the effectiveness of morphing trailing edge devices increases. The final set of studies in this thesis consider mission analy- sis, including climb, multi-altitude cruise, and descent. These mission analyses were performed with a number of surrogate models, trained with O(100) optimizations. These optimizations demonstrated fuel burn reductions as large as 5% at off-design conditions. The fuel burn predicted by the mission analysis was up to 2.7% lower for the morphing wing compared to the conventional configuration.

Optimal Cooling of High Purity Germanium Spectrometers for Missions to Planets and Moons

NASA Astrophysics Data System (ADS)

Chernenko, A.; Kostenko, V.; Konev, S.; Rybkin, B.; Paschin, A.; Prokopenko, I.

2004-04-01

Gamma-ray spectrometers based on high purity germanium (HPGe) detectors are ultimately sensitive instruments for composition studies of surfaces of planets and moons. However, they require deep cooling well below 120K for the entire duration of space mission, and this challenges the feasibility of such instruments in the era of small and cost-efficient missions. In this paper we summarise our experience in the field of the theoretical and experimental studies of optimal cryogenic cooling of gamma-ray spectrometers based on HPGe detectors in order to find out how efficient, light and compact these instruments could be, provided such technologies like cryogenic heat pipe diodes (HPDs), efficient thermal insulation and efficient miniature cryocoolers are used.

Optimization design of hydroturbine rotors according to the efficiency-strength criteria

NASA Astrophysics Data System (ADS)

Bannikov, D. V.; Yesipov, D. V.; Cherny, S. G.; Chirkov, D. V.

2010-12-01

The hydroturbine runner designing [1] is optimized by efficient methods for calculation of head loss in entire flow-through part of the turbine and deformation state of the blade. Energy losses are found at modelling of the spatial turbulent flow and engineering semi-empirical formulae. State of deformation is determined from the solution of the linear problem of elasticity for the isolated blade at hydrodynamic pressure with the method of boundary elements. With the use of the proposed system, the problem of the turbine runner design with the capacity of 640 MW providing the preset dependence of efficiency on the turbine work mode (efficiency criterion) is solved. The arising stresses do not exceed the critical value (strength criterion).

Cost-efficiency trade-off and the design of thermoelectric power generators.

PubMed

Yazawa, Kazuaki; Shakouri, Ali

2011-09-01

The energy conversion efficiency of today's thermoelectric generators is significantly lower than that of conventional mechanical engines. Almost all of the existing research is focused on materials to improve the conversion efficiency. Here we propose a general framework to study the cost-efficiency trade-off for thermoelectric power generation. A key factor is the optimization of thermoelectric modules together with their heat source and heat sinks. Full electrical and thermal co-optimization yield a simple analytical expression for optimum design. Based on this model, power output per unit mass can be maximized. We show that the fractional area coverage of thermoelectric elements in a module could play a significant role in reducing the cost of power generation systems.

[Research on the photoelectric conversion efficiency of grating antireflective layer solar cells].

PubMed

Zhong, Hui; Gao, Yong-Yi; Zhou, Ren-Long; Zhou, Bing-ju; Tang, Li-qiang; Wu, Ling-xi; Li, Hong-jian

2011-07-01

A numerical investigation of the effect of grating antireflective layer structure on the photoelectric conversion efficiency of solar cells was carried out by the finite-difference time-domain method. The influence of grating shape, height and the metal film thickness coated on grating surface on energy storage was analyzed in detail. It was found that the comparison between unoptimized and optimized surface grating structure on solar cells shows that the optimization of surface by grating significantly increases the energy storage capability and greatly improves the efficiency, especially of the photoelectric conversion efficiency and energy storage of the triangle grating. As the film thickness increases, energy storage effect increases, while as the film thickness is too thick, energy storage effect becomes lower and lower.

A Swarm Optimization approach for clinical knowledge mining.

PubMed

Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

2015-10-01

Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

PubMed

Shamsan Saleh, Ahmed M; Ali, Borhanuddin Mohd; Rasid, Mohd Fadlee A; Ismail, Alyani

2012-01-01

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

Numerical investigation on layout optimization of obstacles in a three-dimensional passive micromixer.

PubMed

Chen, Xueye; Zhao, Zhongyi

2017-04-29

This paper aims at layout optimization design of obstacles in a three-dimensional T-type micromixer. Numerical analysis shows that the direction of flow velocity change constantly due to the obstacles blocking, which produces the chaotic convection and increases species mixing effectively. The orthogonal experiment method was applied for determining the effects of some key parameters on mixing efficiency. The weights in the order are: height of obstacles > geometric shape > symmetry = number of obstacles. Based on the optimized results, a multi-units obstacle micromixer was designed. Compared with T-type micromixer, the multi-units obstacle micromixer is more efficient, and more than 90% mixing efficiency were obtained for a wide range of peclet numbers. It can be demonstrated that the presented optimal design method of obstacles layout in three-dimensional microchannels is a simple and effective technology to improve species mixing in microfluidic devices. The obstacles layout methodology has the potential for applications in chemical engineering and bioengineering. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimizing the method for generation of integration-free induced pluripotent stem cells from human peripheral blood.

PubMed

Gu, Haihui; Huang, Xia; Xu, Jing; Song, Lili; Liu, Shuping; Zhang, Xiao-Bing; Yuan, Weiping; Li, Yanxin

2018-06-15

Generation of induced pluripotent stem cells (iPSCs) from human peripheral blood provides a convenient and low-invasive way to obtain patient-specific iPSCs. The episomal vector is one of the best approaches for reprogramming somatic cells to pluripotent status because of its simplicity and affordability. However, the efficiency of episomal vector reprogramming of adult peripheral blood cells is relatively low compared with cord blood and bone marrow cells. In the present study, integration-free human iPSCs derived from peripheral blood were established via episomal technology. We optimized mononuclear cell isolation and cultivation, episomal vector promoters, and a combination of transcriptional factors to improve reprogramming efficiency. Here, we improved the generation efficiency of integration-free iPSCs from human peripheral blood mononuclear cells by optimizing the method of isolating mononuclear cells from peripheral blood, by modifying the integration of culture medium, and by adjusting the duration of culture time and the combination of different episomal vectors. With this optimized protocol, a valuable asset for banking patient-specific iPSCs has been established.

Distributed Bees Algorithm Parameters Optimization for a Cost Efficient Target Allocation in Swarms of Robots

PubMed Central

Jevtić, Aleksandar; Gutiérrez, Álvaro

2011-01-01

Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA), previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce. PMID:22346677

Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks.

PubMed

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-12-13

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm.

Very Large Scale Optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)

2002-01-01

The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.

Optimization strategy for and structural properties of traffic efficiency under bounded information accessibility

NASA Astrophysics Data System (ADS)

Sanghyun, Ahn; Seungwoong, Ha; Kim, Soo Yong

2016-06-01

A vital challenge for many socioeconomic systems is determining the optimum use of limited information. Traffic systems, wherein the range of resources is limited, are a particularly good example of this challenge. Based on bounded information accessibility in terms of, for example, high costs or technical limitations, we develop a new optimization strategy to improve the efficiency of a traffic system with signals and intersections. Numerous studies, including the study by Chowdery and Schadschneider (whose method we denote by ChSch), have attempted to achieve the maximum vehicle speed or the minimum wait time for a given traffic condition. In this paper, we introduce a modified version of ChSch with an independently functioning, decentralized control system. With the new model, we determine the optimization strategy under bounded information accessibility, which proves the existence of an optimal point for phase transitions in the system. The paper also provides insight that can be applied by traffic engineers to create more efficient traffic systems by analyzing the area and symmetry of local sites. We support our results with a statistical analysis using empirical traffic data from Seoul, Korea.

Photonic crystal enhanced silicon cell based thermophotovoltaic systems

DOE PAGES

Yeng, Yi Xiang; Chan, Walker R.; Rinnerbauer, Veronika; ...

2015-01-30

We report the design, optimization, and experimental results of large area commercial silicon solar cell based thermophotovoltaic (TPV) energy conversion systems. Using global non-linear optimization tools, we demonstrate theoretically a maximum radiative heat-to-electricity efficiency of 6.4% and a corresponding output electrical power density of 0.39 W cm⁻² at temperature T = 1660 K when implementing both the optimized two-dimensional (2D) tantalum photonic crystal (PhC) selective emitter, and the optimized 1D tantalum pentoxide – silicon dioxide PhC cold-side selective filter. In addition, we have developed an experimental large area TPV test setup that enables accurate measurement of radiative heat-to-electricity efficiency formore » any emitter-filter-TPV cell combination of interest. In fact, the experimental results match extremely well with predictions of our numerical models. Our experimental setup achieved a maximum output electrical power density of 0.10W cm⁻² and radiative heat-to-electricity efficiency of 1.18% at T = 1380 K using commercial wafer size back-contacted silicon solar cells.« less

Towards a Hybrid Energy Efficient Multi-Tree-Based Optimized Routing Protocol for Wireless Networks

PubMed Central

Mitton, Nathalie; Razafindralambo, Tahiry; Simplot-Ryl, David; Stojmenovic, Ivan

2012-01-01

This paper considers the problem of designing power efficient routing with guaranteed delivery for sensor networks with unknown geographic locations. We propose HECTOR, a hybrid energy efficient tree-based optimized routing protocol, based on two sets of virtual coordinates. One set is based on rooted tree coordinates, and the other is based on hop distances toward several landmarks. In HECTOR, the node currently holding the packet forwards it to its neighbor that optimizes ratio of power cost over distance progress with landmark coordinates, among nodes that reduce landmark coordinates and do not increase distance in tree coordinates. If such a node does not exist, then forwarding is made to the neighbor that reduces tree-based distance only and optimizes power cost over tree distance progress ratio. We theoretically prove the packet delivery and propose an extension based on the use of multiple trees. Our simulations show the superiority of our algorithm over existing alternatives while guaranteeing delivery, and only up to 30% additional power compared to centralized shortest weighted path algorithm. PMID:23443398

Optimal Design of Magnetic ComponentsinPlasma Cutting Power Supply

NASA Astrophysics Data System (ADS)

Jiang, J. F.; Zhu, B. R.; Zhao, W. N.; Yang, X. J.; Tang, H. J.

2017-10-01

Phase-shifted transformer and DC reactor are usually needed in chopper plasma cutting power supply. Because of high power rate, the loss of magnetic components may reach to several kilowatts, which seriously affects the conversion efficiency. Therefore, it is necessary to research and design low loss magnetic components by means of efficient magnetic materials and optimal design methods. The main task in this paper is to compare the core loss of different magnetic material, to analyze the influence of transformer structure, winding arrangement and wire structure on the characteristics of magnetic component. Then another task is to select suitable magnetic material, structure and wire in order to reduce the loss and volume of magnetic components. Based on the above outcome, the optimization design process of transformer and dc reactor are proposed in chopper plasma cutting power supply with a lot of solutions. These solutions are analyzed and compared before the determination of the optimal solution in order to reduce the volume and power loss of the two magnetic components and improve the conversion efficiency of plasma cutting power supply.

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.

Role of intermediate metallic sub-layers in improving the efficiency of kesterite solar cells: concept and optimization

NASA Astrophysics Data System (ADS)

Ferhati, H.; Djeffal, F.

2018-03-01

In this work, versatile CdS/Cu 2 ZnSnS 4 (CZTS) solar cell designs based on intermediate metallic sub-layers (Au, Ti, and Ag) engineering are proposed for enhancing light-scattering behavior and reducing recombination losses. The idea behind this work is to generate optical confinement regions in the CZTS absorber layer to achieve an improved absorption and appropriate antireflection effects. Moreover, the ultra-thin metal at the CZTS/Mo interface can be helpful for reducing the series resistance, where it behaves like a blocking layer for the Sulfur diffusion. We further combine the proposed designs with Particle Swarm Optimization (PSO)-based approach to achieve broadband absorption and boost the conversion efficiency. It is found that the optimized design with Ti sub-layer improves the CZTS solar cell properties, where it yields 31% improvement in short-circuit current and 60% in the power efficiency over the conventional one. Therefore, the optimized designs provide the opportunity for bridging the gap between improving the optical behavior and reducing the recombination losses.

Design and optimization of a volume-phase holographic grating for simultaneous use with red, green, and blue light using unpolarized light.

PubMed

Mahamat, Adoum H; Narducci, Frank A; Schwiegerling, James

2016-03-01

Volume-phase holographic (VPH) gratings have been designed for use in many areas of science and technology, such as optical communication, optical imaging, and astronomy. In this paper, the design of a volume-phase holographic grating, simultaneously optimized to operate in the red, green, and blue wavelengths, is presented along with a study of its fabrication tolerances. The grating is optimized to produce 98% efficiency at λ=532  nm and at least 75% efficiency in the region between 400 and 700 nm, when the incident light is unpolarized. The optimization is done for recording in dichromated gelatin with a thickness of 12 μm, an average refractive index of 1.5, and a refractive index modulation of 0.022.

Design Optimization of a Centrifugal Fan with Splitter Blades

NASA Astrophysics Data System (ADS)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

Optimal power and efficiency of quantum Stirling heat engines

NASA Astrophysics Data System (ADS)

Yin, Yong; Chen, Lingen; Wu, Feng

2017-01-01

A quantum Stirling heat engine model is established in this paper in which imperfect regeneration and heat leakage are considered. A single particle which contained in a one-dimensional infinite potential well is studied, and the system consists of countless replicas. Each particle is confined in its own potential well, whose occupation probabilities can be expressed by the thermal equilibrium Gibbs distributions. Based on the Schrödinger equation, the expressions of power output and efficiency for the engine are obtained. Effects of imperfect regeneration and heat leakage on the optimal performance are discussed. The optimal performance region and the optimal values of important parameters of the engine cycle are obtained. The results obtained can provide some guidelines for the design of a quantum Stirling heat engine.

Design optimization of a prescribed vibration system using conjoint value analysis

NASA Astrophysics Data System (ADS)

Malinga, Bongani; Buckner, Gregory D.

2016-12-01

This article details a novel design optimization strategy for a prescribed vibration system (PVS) used to mechanically filter solids from fluids in oil and gas drilling operations. A dynamic model of the PVS is developed, and the effects of disturbance torques are detailed. This model is used to predict the effects of design parameters on system performance and efficiency, as quantified by system attributes. Conjoint value analysis, a statistical technique commonly used in marketing science, is utilized to incorporate designer preferences. This approach effectively quantifies and optimizes preference-based trade-offs in the design process. The effects of designer preferences on system performance and efficiency are simulated. This novel optimization strategy yields improvements in all system attributes across all simulated vibration profiles, and is applicable to other industrial electromechanical systems.

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

Optimizing Irregular Applications for Energy and Performance on the Tilera Many-core Architecture

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

Chavarría-Miranda, Daniel; Panyala, Ajay R.; Halappanavar, Mahantesh

Optimizing applications simultaneously for energy and performance is a complex problem. High performance, parallel, irregular applications are notoriously hard to optimize due to their data-dependent memory accesses, lack of structured locality and complex data structures and code patterns. Irregular kernels are growing in importance in applications such as machine learning, graph analytics and combinatorial scientific computing. Performance- and energy-efficient implementation of these kernels on modern, energy efficient, multicore and many-core platforms is therefore an important and challenging problem. We present results from optimizing two irregular applications { the Louvain method for community detection (Grappolo), and high-performance conjugate gradient (HPCCG) {more » on the Tilera many-core system. We have significantly extended MIT's OpenTuner auto-tuning framework to conduct a detailed study of platform-independent and platform-specific optimizations to improve performance as well as reduce total energy consumption. We explore the optimization design space along three dimensions: memory layout schemes, compiler-based code transformations, and optimization of parallel loop schedules. Using auto-tuning, we demonstrate whole node energy savings of up to 41% relative to a baseline instantiation, and up to 31% relative to manually optimized variants.« less

Optimization of 3D Field Design

NASA Astrophysics Data System (ADS)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. Using the IPEC dominant mode as a target spectrum, the Finding Optimized Coils Using Space-curves (FOCUS) code optimizes the currents and 3D geometry of multiple coils to maximize the total set's resonant coupling. The optimized coils are individually distorted in space, creating toroidal ``arrays'' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. The generalized perturbed equilibrium code (GPEC) is used to determine optimally efficient spectra for driving total, core, and edge neoclassical toroidal viscosity (NTV) torque and these too provide targets for the optimization of 3D coil designs. These conceptual designs represent a fundamentally new approach to 3D coil design for tokamaks targeting desired plasma physics phenomena. Optimized coil sets based on plasma response theory will be relevant to designs for future reactors or on any active machine. External coils, in particular, must be optimized for reliable and efficient fusion reactor designs. Work supported by the US Department of Energy under DE-AC02-09CH11466.

Optimization design of multiphase pump impeller based on combined genetic algorithm and boundary vortex flux diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Jin-ya; Cai, Shu-jie; Li, Yong-jiang; Li, Yong-jiang; Zhang, Yong-xue

2017-12-01

A novel optimization design method for the multiphase pump impeller is proposed through combining the quasi-3D hydraulic design (Q3DHD), the boundary vortex flux (BVF) diagnosis, and the genetic algorithm (GA). The BVF diagnosis based on the Q3DHD is used to evaluate the objection function. Numerical simulations and hydraulic performance tests are carried out to compare the impeller designed only by the Q3DHD method and that optimized by the presented method. The comparisons of both the flow fields simulated under the same condition show that (1) the pressure distribution in the optimized impeller is more reasonable and the gas-liquid separation is more efficiently inhibited, (2) the scales of the gas pocket and the vortex decrease remarkably for the optimized impeller, (3) the unevenness of the BVF distributions near the shroud of the original impeller is effectively eliminated in the optimized impeller. The experimental results show that the differential pressure and the maximum efficiency of the optimized impeller are increased by 4% and 2.5%, respectively. Overall, the study indicates that the optimization design method proposed in this paper is feasible.

Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm.

PubMed

Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar

2018-01-01

Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Optimization Design Algorithm for High-Frequency TWTs

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.; Chevalier, Christine T.

2010-01-01

Traveling-wave tubes (TWTs), such as the Ka-band (26-GHz) model recently developed for the Lunar Reconnaissance Orbiter, are essential as communication amplifiers in spacecraft for virtually all near- and deep-space missions. This innovation is a computational design algorithm that, for the first time, optimizes the efficiency and output power of a TWT while taking into account the effects of dimensional tolerance variations. Because they are primary power consumers and power generation is very expensive in space, much effort has been exerted over the last 30 years to increase the power efficiency of TWTs. However, at frequencies higher than about 60 GHz, efficiencies of TWTs are still quite low. A major reason is that at higher frequencies, dimensional tolerance variations from conventional micromachining techniques become relatively large with respect to the circuit dimensions. When this is the case, conventional design- optimization procedures, which ignore dimensional variations, provide inaccurate designs for which the actual amplifier performance substantially under-performs that of the design. Thus, this new, robust TWT optimization design algorithm was created to take account of and ameliorate the deleterious effects of dimensional variations and to increase efficiency, power, and yield of high-frequency TWTs. This design algorithm can help extend the use of TWTs into the terahertz frequency regime of 300-3000 GHz. Currently, these frequencies are under-utilized because of the lack of efficient amplifiers, thus this regime is known as the "terahertz gap." The development of an efficient terahertz TWT amplifier could enable breakthrough applications in space science molecular spectroscopy, remote sensing, nondestructive testing, high-resolution "through-the-wall" imaging, biomedical imaging, and detection of explosives and toxic biochemical agents.

Efficiency optimization of a closed indirectly fired gas turbine cycle working under two variable-temperature heat reservoirs

NASA Astrophysics Data System (ADS)

Ma, Zheshu; Wu, Jieer

2011-08-01

Indirectly or externally fired gas turbines (IFGT or EFGT) are interesting technologies under development for small and medium scale combined heat and power (CHP) supplies in combination with micro gas turbine technologies. The emphasis is primarily on the utilization of the waste heat from the turbine in a recuperative process and the possibility of burning biomass even "dirty" fuel by employing a high temperature heat exchanger (HTHE) to avoid the combustion gases passing through the turbine. In this paper, finite time thermodynamics is employed in the performance analysis of a class of irreversible closed IFGT cycles coupled to variable temperature heat reservoirs. Based on the derived analytical formulae for the dimensionless power output and efficiency, the efficiency optimization is performed in two aspects. The first is to search the optimum heat conductance distribution corresponding to the efficiency optimization among the hot- and cold-side of the heat reservoirs and the high temperature heat exchangers for a fixed total heat exchanger inventory. The second is to search the optimum thermal capacitance rate matching corresponding to the maximum efficiency between the working fluid and the high-temperature heat reservoir for a fixed ratio of the thermal capacitance rates of the two heat reservoirs. The influences of some design parameters on the optimum heat conductance distribution, the optimum thermal capacitance rate matching and the maximum power output, which include the inlet temperature ratio of the two heat reservoirs, the efficiencies of the compressor and the gas turbine, and the total pressure recovery coefficient, are provided by numerical examples. The power plant configuration under optimized operation condition leads to a smaller size, including the compressor, turbine, two heat reservoirs and the HTHE.

An Optimization System with Parallel Processing for Reducing Common-Mode Current on Electronic Control Unit

NASA Astrophysics Data System (ADS)

Okazaki, Yuji; Uno, Takanori; Asai, Hideki

In this paper, we propose an optimization system with parallel processing for reducing electromagnetic interference (EMI) on electronic control unit (ECU). We adopt simulated annealing (SA), genetic algorithm (GA) and taboo search (TS) to seek optimal solutions, and a Spice-like circuit simulator to analyze common-mode current. Therefore, the proposed system can determine the adequate combinations of the parasitic inductance and capacitance values on printed circuit board (PCB) efficiently and practically, to reduce EMI caused by the common-mode current. Finally, we apply the proposed system to an example circuit to verify the validity and efficiency of the system.

Fuzzy efficiency optimization of AC induction motors

NASA Technical Reports Server (NTRS)

Jani, Yashvant; Sousa, Gilberto; Turner, Wayne; Spiegel, Ron; Chappell, Jeff

1993-01-01

This paper describes the early states of work to implement a fuzzy logic controller to optimize the efficiency of AC induction motor/adjustable speed drive (ASD) systems running at less than optimal speed and torque conditions. In this paper, the process by which the membership functions of the controller were tuned is discussed and a controller which operates on frequency as well as voltage is proposed. The membership functions for this dual-variable controller are sketched. Additional topics include an approach for fuzzy logic to motor current control which can be used with vector-controlled drives. Incorporation of a fuzzy controller as an application-specific integrated circuit (ASIC) microchip is planned.

Design of spoke type motor and magnetizer for improving efficiency based rare-earth-free permanent-magnet motor

NASA Astrophysics Data System (ADS)

Kim, Young Hyun; Cheon, Byung Chul; Lee, Jung Ho

2018-05-01

This study proposes criteria for both optimal-shape and magnetizer-system designs to be used for a high-output spoke-type motor. The study also examines methods of reducing high-cogging torque and torque ripple, to prevent noise and vibration. The optimal design of the stator and rotor can be enhanced using both a response surface method and finite element method. In addition, a magnetizer system is optimally designed for the magnetization of permanent magnets for use in the motor. Finally, this study verifies that the proposed motor can efficiently replace interior permanent magnet synchronous motor in many industries.

Optimizing piezoelectric receivers for acoustic power transfer applications

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2018-07-01

In this paper, we aim to optimize piezoelectric plate receivers for acoustic power transfer applications by analyzing the influence of the losses and of the acoustic boundary conditions. We derive the analytic expressions of the efficiency of the receiver with the optimal electric loads attached, and analyze the maximum efficiency value and its frequency with different loss and acoustic boundary conditions. To validate the analytical expressions that we have derived, we perform experiments in water with composite transducers of different filling fractions, and see that a lower acoustic impedance mismatch can compensate the influence of large dielectric and acoustic losses to achieve a good performance. Finally, we briefly compare the advantages and drawbacks of composite transducers and pure PZT (lead zirconate titanate) plates as acoustic power receivers, and conclude that 1–3 composites can achieve similar efficiency values in low power applications due to their adjustable acoustic impedance.

[Identification and Nitrogen Removal Characteristics of a Heterotrophic Nitrification-Aerobic Denitrification Strain Isolated from Marine Environment].

PubMed

Sun, Qing-hua; Yu, De-shuang; Zhang, Pei-yu; Lin, Xue-zheng; Li, Jin

2016-02-15

A heterotrophic nitrification-aerobic denitrification strain named y5 was isolated from marine environment by traditional microbial isolation method using seawater as medium. It was identified as Klebsiella sp. based on the morphological, physiological and 16S rRNA sequence analysis. The experiment results showed that the optimal carbon resource was sodium citrate; the optimal pH was 7.0; and the optimal C/N was 17. The strain could use NH4Cl, NaNO2 and KNO3 as sole nitrogen source, and the removal efficiencies were77.07%, 64.14% and 100% after 36 hours, respectively. The removal efficiency reached 100% after 36 hours in the coexistence of NH4Cl, NaNO2 and KNO3. The results showed that the strain y5 had independent and efficient heterotrophic nitrification and aerobic denitrification activities in high salt wastewater.

A global optimization method synthesizing heat transfer and thermodynamics for the power generation system with Brayton cycle

NASA Astrophysics Data System (ADS)

Fu, Rong-Huan; Zhang, Xing

2016-09-01

Supercritical carbon dioxide operated in a Brayton cycle offers a numerous of potential advantages for a power generation system, and a lot of thermodynamics analyses have been conducted to increase its efficiency. Because there are a lot of heat-absorbing and heat-lossing subprocesses in a practical thermodynamic cycle and they are implemented by heat exchangers, it will increase the gross efficiency of the whole power generation system to optimize the system combining thermodynamics and heat transfer theory. This paper analyzes the influence of the performance of heat exchangers on the actual efficiency of an ideal Brayton cycle with a simple configuration, and proposes a new method to optimize the power generation system, which aims at the minimum energy consumption. Although the method is operated only for the ideal working fluid in this paper, its merits compared to that only with thermodynamic analysis are fully shown.

Analysis, Design and Optimization of Non-Cylindrical Fuselage for Blended-Wing-Body (BWB) Vehicle

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Sobieszczanski-Sobieski, J.; Kosaka, I.; Quinn, G.; Charpentier, C.

2002-01-01

Initial results of an investigation towards finding an efficient non-cylindrical fuselage configuration for a conceptual blended-wing-body flight vehicle were presented. A simplified 2-D beam column analysis and optimization was performed first. Then a set of detailed finite element models of deep sandwich panel and ribbed shell construction concepts were analyzed and optimized. Generally these concepts with flat surfaces were found to be structurally inefficient to withstand internal pressure and resultant compressive loads simultaneously. Alternatively, a set of multi-bubble fuselage configuration concepts were developed for balancing internal cabin pressure load efficiently, through membrane stress in inner-stiffened shell and inter-cabin walls. An outer-ribbed shell was designed to prevent buckling due to external resultant compressive loads. Initial results from finite element analysis appear to be promising. These concepts should be developed further to exploit their inherent structurally efficiency.

Control of nitromethane photoionization efficiency with shaped femtosecond pulses.

PubMed

Roslund, Jonathan; Shir, Ofer M; Dogariu, Arthur; Miles, Richard; Rabitz, Herschel

2011-04-21

The applicability of adaptive femtosecond pulse shaping is studied for achieving selectivity in the photoionization of low-density polyatomic targets. In particular, optimal dynamic discrimination (ODD) techniques exploit intermediate molecular electronic resonances that allow a significant increase in the photoionization efficiency of nitromethane with shaped near-infrared femtosecond pulses. The intensity bias typical of high-photon number, nonresonant ionization is accounted for by reference to a strictly intensity-dependent process. Closed-loop adaptive learning is then able to discover a pulse form that increases the ionization efficiency of nitromethane by ∼150%. The optimally induced molecular dynamics result from entry into a region of parameter space inaccessible with intensity-only control. Finally, the discovered pulse shape is demonstrated to interact with the molecular system in a coherent fashion as assessed from the asymmetry between the response to the optimal field and its time-reversed counterpart.

Thermal design of a Mars oxygen production plant

NASA Technical Reports Server (NTRS)

Sridhar, K. R.; Iyer, Venkatesh A.

1991-01-01

The optimal design of the thermal components of a system that uses carbon dioxide from the Martian atmosphere to produce oxygen for spacecraft propulsion and/or life support is discussed. The gases are pressurized, heated and passed through an electrochemical cell. Carbon dioxide is reduced to carbon monoxide and oxygen due to thermal dissociation and electrocatalysis. The oxygen thus formed is separated from the gas mixture by the electrochemical cell. The objective of the design is to optimize both the overall mass and the power consumption of the system. The analysis shows that at electrochemical cell efficiencies of about 50 percent and lower, the optimal system would require unspent carbon dioxide in the exhaust gases to be separated and recycled. Various methods of efficiently compressing the intake gases to system pressures of 0.1 MPa are investigated. The total power requirement for oxygen production rates of 1, 5, and 10 kg/day at various cell efficiencies are presented.

Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks

NASA Astrophysics Data System (ADS)

Liao, Wei-Cheng; Hong, Mingyi; Liu, Ya-Feng; Luo, Zhi-Quan

2014-08-01

In a densely deployed heterogeneous network (HetNet), the number of pico/micro base stations (BS) can be comparable with the number of the users. To reduce the operational overhead of the HetNet, proper identification of the set of serving BSs becomes an important design issue. In this work, we show that by jointly optimizing the transceivers and determining the active set of BSs, high system resource utilization can be achieved with only a small number of BSs. In particular, we provide formulations and efficient algorithms for such joint optimization problem, under the following two common design criteria: i) minimization of the total power consumption at the BSs, and ii) maximization of the system spectrum efficiency. In both cases, we introduce a nonsmooth regularizer to facilitate the activation of the most appropriate BSs. We illustrate the efficiency and the efficacy of the proposed algorithms via extensive numerical simulations.

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.

Quantum optimal control with automatic differentiation using graphics processors

NASA Astrophysics Data System (ADS)

Leung, Nelson; Abdelhafez, Mohamed; Chakram, Srivatsan; Naik, Ravi; Groszkowski, Peter; Koch, Jens; Schuster, David

We implement quantum optimal control based on automatic differentiation and harness the acceleration afforded by graphics processing units (GPUs). Automatic differentiation allows us to specify advanced optimization criteria and incorporate them into the optimization process with ease. We will describe efficient techniques to optimally control weakly anharmonic systems that are commonly encountered in circuit QED, including coupled superconducting transmon qubits and multi-cavity circuit QED systems. These systems allow for a rich variety of control schemes that quantum optimal control is well suited to explore.

Operation Results of the Kstar Helium Refrigeration System

NASA Astrophysics Data System (ADS)

Chang, H.-S.; Fauve, E.; Park, D.-S.; Joo, J.-J.; Moon, K.-M.; Cho, K.-W.; Na, H. K.; Kwon, M.; Yang, S.-H.; Gistau-Baguer, G.

2010-04-01

The "first plasma" (100 kA of controllable plasma current for 100 ms) of KSTAR has been successfully generated in July 2008. The major outstanding feature of KSTAR compared to most other Tokamaks is that all the magnet coils are superconducting (SC), which enables higher plasma current values for a longer time duration when the nominal operation status has been reached. However, to establish the operating condition for the SC coils, other cold components, such as thermal shields, coil-supporting structures, SC buslines, and current leads also must be maintained at proper cryogenic temperature levels. A helium refrigeration system (HRS) with an exergetic equivalent cooling power of 9 kW at 4.5 K has been installed for such purposes and successfully commissioned. In this proceeding, we will report on the operation results of the HRS during the first plasma campaign of KSTAR. Using the HRS, the 300-ton cold mass of KSTAR was cooled down from ambient to the operating temperature levels of each cold component. Stable and steady cryogenic conditions, proper for the generation of the "first plasma" have been maintained for three months, after which, all of the cold mass was warmed up again to ambient temperature.

Assay optimization: a statistical design of experiments approach.

PubMed

Altekar, Maneesha; Homon, Carol A; Kashem, Mohammed A; Mason, Steven W; Nelson, Richard M; Patnaude, Lori A; Yingling, Jeffrey; Taylor, Paul B

2007-03-01

With the transition from manual to robotic HTS in the last several years, assay optimization has become a significant bottleneck. Recent advances in robotic liquid handling have made it feasible to reduce assay optimization timelines with the application of statistically designed experiments. When implemented, they can efficiently optimize assays by rapidly identifying significant factors, complex interactions, and nonlinear responses. This article focuses on the use of statistically designed experiments in assay optimization.

Development of High Efficiency Four-Terminal Perovskite-Silicon Tandems

NASA Astrophysics Data System (ADS)

Duong, The Duc

This thesis is concerned with the development of high efficiency four-terminal perovskite-silicon tandem solar cells with the potential to reduce the cost of solar energy. The work focuses on perovskite top cells and can be divided into three main parts: developing low parasitic absorption and efficient semi-transparent perovskite cells, doping perovskite materials with rubidium, and optimizing perovskite material's bandgap with quadruple-cation and mixed-halide. A further section investigates the light stability of optimized bandgap perovskite cells. In a four-terminal mechanically stacked tandem, the perovskite top cell requires two transparent contacts at both the front and rear sides. Through detailed optical and electrical power loss analysis of the tandem efficiency due to non-ideal properties of the two transparent contacts, optimal contact parameters in term of sheet resistance and transparency are identified. Indium doped tin oxide by sputtering is used for both two transparent contacts and their deposition parameters are optimized separately. The semi-transparent perovskite cell using MAPbI3 has an efficiency of more than 12% with less than 12% parasitic absorption and up to 80% transparency in the long wavelength region. Using a textured foil as anti-reflection coating, an outstanding average transparency of 84% in the long wavelength is obtained. The low parasitic absorption allows an opaque version of the semi-transparent perovskite cell to operate efficiently in a filterless spectrum splitting perovskite-silicon tandem configuration. To further enhance the performance of perovskite cells, it is essential to improve the quality of perovskite films. This can be achieved with mixed-perovskite FAPbI3/MAPbBr3. However, mixed-perovskite films normally contain small a small amount of a non-perovskite phase, which is detrimental for the cell performance. Rb-doping is found to eliminate the formation of the non-perovskite phase and enhance the crystallinity of the films. Rb-doping is studied under different excess PbI2 concentrations and the optimal condition is found to be 5% Rb-doping and 15% excess PbI2 concentration. The addition of more than 10% Rb results in the formation of an unwanted Rb-rich phase due to the significant lattice mismatch between Rb and FA/MA cations. An efficiency of 18.8% is achieved for the champion cell as compared to 16% with control cells. Importantly, Rb-doping improves the light, moisture and thermal stability of perovskite cells. The optimal bandgap of the perovskite top cell in perovskite-silicon tandems is between 1.7 eV and 1.8 eV. A quadruple-cation Rb/Cs/FA/MA mixed-halide I/Br perovskite composition is explored to obtain high quality perovskite films with a bandgap of 1.73 eV. The ratio between Cs/FA/MA cations is critical to the morphology, crystal orientation and electronic properties of perovskite films. Furthermore, 5% Rb-doping enhances the crystallinity and suppresses defect migration in the films. Semi-transparent cells with efficiencies up to 16% and negligible hysteresis are achieved using this material. With excellent transparency and optimal bandgap of the semi-transparent perovskite cell, a record four-terminal mechanically stacked perovskite-silicon tandem efficiency of 26.4% is achieved.

Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

Treesearch

Bistra Dilkina; Rachel Houtman; Carla P. Gomes; Claire A. Montgomery; Kevin S. McKelvey; Katherine Kendall; Tabitha A. Graves; Richard Bernstein; Michael K. Schwartz

2016-01-01

Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a...

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Innovative model-based flow rate optimization for vanadium redox flow batteries

NASA Astrophysics Data System (ADS)

König, S.; Suriyah, M. R.; Leibfried, T.

2016-11-01

In this paper, an innovative approach is presented to optimize the flow rate of a 6-kW vanadium redox flow battery with realistic stack dimensions. Efficiency is derived using a multi-physics battery model and a newly proposed instantaneous efficiency determination technique. An optimization algorithm is applied to identify optimal flow rates for operation points defined by state-of-charge (SoC) and current. The proposed method is evaluated against the conventional approach of applying Faraday's first law of electrolysis, scaled to the so-called flow factor. To make a fair comparison, the flow factor is also optimized by simulating cycles with different charging/discharging currents. It is shown through the obtained results that the efficiency is increased by up to 1.2% points; in addition, discharge capacity is also increased by up to 1.0 kWh or 5.4%. Detailed loss analysis is carried out for the cycles with maximum and minimum charging/discharging currents. It is shown that the proposed method minimizes the sum of losses caused by concentration over-potential, pumping and diffusion. Furthermore, for the deployed Nafion 115 membrane, it is observed that diffusion losses increase with stack SoC. Therefore, to decrease stack SoC and lower diffusion losses, a higher flow rate during charging than during discharging is reasonable.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Enhancement of dissolution and oral bioavailability of lacidipine via pluronic P123/F127 mixed polymeric micelles: formulation, optimization using central composite design and in vivo bioavailability study.

PubMed

Fares, Ahmed R; ElMeshad, Aliaa N; Kassem, Mohamed A A

2018-11-01

This study aims at preparing and optimizing lacidipine (LCDP) polymeric micelles using thin film hydration technique in order to overcome LCDP solubility-limited oral bioavailability. A two-factor three-level central composite face-centered design (CCFD) was employed to optimize the formulation variables to obtain LCDP polymeric micelles of high entrapment efficiency and small and uniform particle size (PS). Formulation variables were: Pluronic to drug ratio (A) and Pluronic P123 percentage (B). LCDP polymeric micelles were assessed for entrapment efficiency (EE%), PS and polydispersity index (PDI). The formula with the highest desirability (0.959) was chosen as the optimized formula. The values of the formulation variables (A and B) in the optimized polymeric micelles formula were 45% and 80%, respectively. Optimum LCDP polymeric micelles had entrapment efficiency of 99.23%, PS of 21.08 nm and PDI of 0.11. Optimum LCDP polymeric micelles formula was physically characterized using transmission electron microscopy. LCDP polymeric micelles showed saturation solubility approximately 450 times that of raw LCDP in addition to significantly enhanced dissolution rate. Bioavailability study of optimum LCDP polymeric micelles formula in rabbits revealed a 6.85-fold increase in LCDP bioavailability compared to LCDP oral suspension.

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

NASA Astrophysics Data System (ADS)

Sanaye, Sepehr; Katebi, Arash

2014-02-01

Energy, exergy, economic and environmental (4E) analysis and optimization of a hybrid solid oxide fuel cell and micro gas turbine (SOFC-MGT) system for use as combined generation of heat and power (CHP) is investigated in this paper. The hybrid system is modeled and performance related results are validated using available data in literature. Then a multi-objective optimization approach based on genetic algorithm is incorporated. Eight system design parameters are selected for the optimization procedure. System exergy efficiency and total cost rate (including capital or investment cost, operational cost and penalty cost of environmental emissions) are the two objectives. The effects of fuel unit cost, capital investment and system power output on optimum design parameters are also investigated. It is observed that the most sensitive and important design parameter in the hybrid system is fuel cell current density which has a significant effect on the balance between system cost and efficiency. The selected design point from the Pareto distribution of optimization results indicates a total system exergy efficiency of 60.7%, with estimated electrical energy cost 0.057 kW-1 h-1, and payback period of about 6.3 years for the investment.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

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

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Model-based optimizations of packaged rooftop air conditioners using low global warming potential refrigerants

DOE PAGES

Shen, Bo; Abdelaziz, Omar; Shrestha, Som; ...

2017-10-31

Based on laboratory investigations for R-22 and R-410A alternative low GWP refrigerants in two baseline rooftop air conditioners (RTU), the DOE/ORNL Heat Pump Design Model was used to model the two RTUs and the models were calibrated against the experimental data. We compared the compressor efficiencies and heat exchanger performances. An efficiency-based compressor mapping method was developed. Extensive model-based optimizations were conducted to provide a fair comparison between all the low GWP candidates by selecting optimal configurations. The results illustrate that all the R-22 low GWP refrigerants will lead to slightly lower COPs. ARM-20B appears to be the best R-22more » replacement at normal conditions. At higher ambient temperatures, ARM-20A exhibits better performance. All R-410A low GWP candidates will result in similar or better efficiencies than R-410A. R-32 has the best COP while requiring the smallest compressor. Finally, R-452B uses the closest compressor displacement volume and achieves the same efficiency as R-410A.« less

Model-based optimizations of packaged rooftop air conditioners using low global warming potential refrigerants

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

Shen, Bo; Abdelaziz, Omar; Shrestha, Som

Based on laboratory investigations for R-22 and R-410A alternative low GWP refrigerants in two baseline rooftop air conditioners (RTU), the DOE/ORNL Heat Pump Design Model was used to model the two RTUs and the models were calibrated against the experimental data. We compared the compressor efficiencies and heat exchanger performances. An efficiency-based compressor mapping method was developed. Extensive model-based optimizations were conducted to provide a fair comparison between all the low GWP candidates by selecting optimal configurations. The results illustrate that all the R-22 low GWP refrigerants will lead to slightly lower COPs. ARM-20B appears to be the best R-22more » replacement at normal conditions. At higher ambient temperatures, ARM-20A exhibits better performance. All R-410A low GWP candidates will result in similar or better efficiencies than R-410A. R-32 has the best COP while requiring the smallest compressor. Finally, R-452B uses the closest compressor displacement volume and achieves the same efficiency as R-410A.« less

Promoting Charge Separation and Injection by Optimizing the Interfaces of GaN:ZnO Photoanode for Efficient Solar Water Oxidation.

PubMed

Wang, Zhiliang; Zong, Xu; Gao, Yuying; Han, Jingfeng; Xu, Zhiqiang; Li, Zheng; Ding, Chunmei; Wang, Shengyang; Li, Can

2017-09-13

Photoelectrochemical water splitting provides an attractive way to store solar energy in molecular hydrogen as a kind of sustainable fuel. To achieve high solar conversion efficiency, the most stringent criteria are effective charge separation and injection in electrodes. Herein, efficient photoelectrochemical water oxidation is realized by optimizing charge separation and surface charge transfer of GaN:ZnO photoanode. The charge separation can be greatly improved through modified moisture-assisted nitridation and HCl acid treatment, by which the interfaces in GaN:ZnO solid solution particles are optimized and recombination centers existing at the interfaces are depressed in GaN:ZnO photoanode. Moreover, a multimetal phosphide of NiCoFeP was employed as water oxidation cocatalyst to improve the charge injection at the photoanode/electrolyte interface. Consequently, it significantly decreases the overpotential and brings the photocurrent to a benchmark of 3.9 mA cm -2 at 1.23 V vs RHE and a solar conversion efficiency over 1% was obtained.

Light collection optimization for composite photoanode in dye-sensitized solar cells: Towards higher efficiency

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

Guo, X. Z.; Shen, W. Z., E-mail: wzshen@sjtu.edu.cn; Laboratory of Condensed Matter Spectroscopy and Opto-Electronic Physics, and Key Laboratory of Artificial Structures and Quantum Control

2015-06-14

Composite photoanode comprising nanoparticles and one-dimensional (1D) nanostructure is a promising alternative to conventional photoanode for dye-sensitized solar cells (DSCs). Besides fast electron transport channels, the 1D nanostructure also plays as light scattering centers. Here, we theoretically investigate the light scattering properties of capsule-shaped 1D nanostructure and their influence on the light collection of DSCs. It is found that the far-field light scattering of a single capsule depends on its volume, shape, and orientation: capsules with bigger equivalent spherical diameter, smaller aspect ratio, and horizontal orientation demonstrate stronger light scattering especially at large scattering angle. Using Monte Carlo approach, wemore » simulated and optimized the light harvesting efficiency of the cell. Two multilayer composite photoanodes containing orderly or randomly oriented capsules are proposed. DSCs composed of these two photoanodes are promising for higher efficiencies because of their efficient light collection and superior electron collection. These results will provide practical guidance to the design and optimization of the photoanodes for DSCs.« less

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.

Coupling between a multi-physics workflow engine and an optimization framework

NASA Astrophysics Data System (ADS)

Di Gallo, L.; Reux, C.; Imbeaux, F.; Artaud, J.-F.; Owsiak, M.; Saoutic, B.; Aiello, G.; Bernardi, P.; Ciraolo, G.; Bucalossi, J.; Duchateau, J.-L.; Fausser, C.; Galassi, D.; Hertout, P.; Jaboulay, J.-C.; Li-Puma, A.; Zani, L.

2016-03-01

A generic coupling method between a multi-physics workflow engine and an optimization framework is presented in this paper. The coupling architecture has been developed in order to preserve the integrity of the two frameworks. The objective is to provide the possibility to replace a framework, a workflow or an optimizer by another one without changing the whole coupling procedure or modifying the main content in each framework. The coupling is achieved by using a socket-based communication library for exchanging data between the two frameworks. Among a number of algorithms provided by optimization frameworks, Genetic Algorithms (GAs) have demonstrated their efficiency on single and multiple criteria optimization. Additionally to their robustness, GAs can handle non-valid data which may appear during the optimization. Consequently GAs work on most general cases. A parallelized framework has been developed to reduce the time spent for optimizations and evaluation of large samples. A test has shown a good scaling efficiency of this parallelized framework. This coupling method has been applied to the case of SYCOMORE (SYstem COde for MOdeling tokamak REactor) which is a system code developed in form of a modular workflow for designing magnetic fusion reactors. The coupling of SYCOMORE with the optimization platform URANIE enables design optimization along various figures of merit and constraints.

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.

Theoretical analysis of improved efficiency of silicon-wafer solar cells with textured nanotriangular grating structure

NASA Astrophysics Data System (ADS)

Zhang, Yaoju; Zheng, Jun; Zhao, Xuesong; Ruan, Xiukai; Cui, Guihua; Zhu, Haiyong; Dai, Yuxing

2018-03-01

A practical model of crystalline silicon-wafer solar cells is proposed in order to enhance the light absorption and improve the conversion efficiency of silicon solar cells. In the model, the front surface of the silicon photovoltaic film is designed to be a textured-triangular-grating (TTG) structure, and the ITO contact film and the antireflection coating (ARC) of glass are coated on the TTG surface of silicon solar cells. The optical absorption spectrum of solar cells are simulated by applying the finite difference time domain method. Electrical parameters of the solar cells are calculated using two models with and without carrier loss. The effect of structure parameters on the performance of the TTG cell is discussed in detail. It is found that the thickness (tg) of the ARC, period (p) of grating, and base angle (θ) of triangle have a crucial influence on the conversion efficiency. The optimal structure of the TTG cell is designed. The TTG solar cell can produce higher efficiency in a wide range of solar incident angle and the average efficiency of the optimal TTG cell over 7:30-16:30 time of day is 8% higher than that of the optimal plane solar cell. In addition, the study shows that the bulk recombination of carriers has an influence on the conversion efficiency of the cell, the conversion efficiency of the actual solar cell with carrier recombination is reduced by 20.0% of the ideal cell without carrier recombination.

No Cost – Low Cost Compressed Air System Optimization in Industry

NASA Astrophysics Data System (ADS)

Dharma, A.; Budiarsa, N.; Watiniasih, N.; Antara, N. G.

2018-04-01

Energy conservation is a systematic, integrated of effort, in order to preserve energy sources and improve energy utilization efficiency. Utilization of energy in efficient manner without reducing the energy usage it must. Energy conservation efforts are applied at all stages of utilization, from utilization of energy resources to final, using efficient technology, and cultivating an energy-efficient lifestyle. The most common way is to promote energy efficiency in the industry on end use and overcome barriers to achieve such efficiency by using system energy optimization programs. The facts show that energy saving efforts in the process usually only focus on replacing tools and not an overall system improvement effort. In this research, a framework of sustainable energy reduction work in companies that have or have not implemented energy management system (EnMS) will be conducted a systematic technical approach in evaluating accurately a compressed-air system and potential optimization through observation, measurement and verification environmental conditions and processes, then processing the physical quantities of systems such as air flow, pressure and electrical power energy at any given time measured using comparative analysis methods in this industry, to provide the potential savings of energy saving is greater than the component approach, with no cost to the lowest cost (no cost - low cost). The process of evaluating energy utilization and energy saving opportunities will provide recommendations for increasing efficiency in the industry and reducing CO2 emissions and improving environmental quality.

Performance Analysis and Optimization of Concentrating Solar Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Lamba, Ravita; Manikandan, S.; Kaushik, S. C.

2018-06-01

A thermodynamic model for a concentrating solar thermoelectric generator considering the Thomson effect combined with Fourier heat conduction, Peltier, and Joule heating has been developed and optimized in MATLAB environment. The temperatures at the hot and cold junctions of the thermoelectric generator were evaluated by solving the energy balance equations at both junctions. The effects of the solar concentration ratio, input electrical current, number of thermocouples, and electrical load resistance ratio on the power output and energy and exergy efficiencies of the system were studied. Optimization studies were carried out for the STEG system, and the optimum number of thermocouples, concentration ratio, and resistance ratio determined. The results showed that the optimum values of these parameters are different for conditions of maximum power output and maximum energy and exergy efficiency. The optimum values of the concentration ratio and load resistance ratio for maximum energy efficiency of 5.85% and maximum exergy efficiency of 6.29% were found to be 180 and 1.3, respectively, with corresponding power output of 4.213 W. Furthermore, at higher concentration ratio (C = 600), the optimum number of thermocouples was found to be 101 for maximum power output of 13.75 W, maximum energy efficiency of 5.73%, and maximum exergy efficiency of 6.16%. Moreover, the optimum number of thermocouple was the same for conditions of maximum power output and energy and exergy efficiency. The results of this study may provide insight for design of actual concentrated solar thermoelectric generator systems.

Protein functionalized tramadol-loaded PLGA nanoparticles: preparation, optimization, stability and pharmacodynamic studies.

PubMed

Lalani, Jigar; Rathi, Mohan; Lalan, Manisha; Misra, Ambikanandan

2013-06-01

Poly (d,l-lactide-co-glycolide acid) (PLGA) Nanoparticles (NPs) with sustained drug release and enhanced circulation time presents widely explored non-invasive approach for drug delivery to brain. However, blood-brain barrier (BBB) limits the drug delivery to brain. This can be overcome by anchoring endogenous ligand like Transferrin (Tf) and Lactoferrin (Lf) on the surface of NPs, allowing efficient brain delivery via receptor-mediated endocytosis. The aim of the present investigation was preparation, optimization, characterization and comparative evaluation of targeting efficiency of Tf- vs. Lf-conjugated NPs. Tramadol-loaded PLGA NPs were prepared by nanoprecipitation techniques and optimized using 3(3) factorial design. The effect of polymer concentration, stabilizer concentration and organic:aqueous phase ratio were evaluated on particle size (PS) and entrapment efficiency (EE). The formulation was optimized based on desirability for lower PS (<150 nm) and higher EE (>70%). Optimized PLGA NPs were conjugated with Tf and Lf, characterized and evaluated for stability study. Pharmacodynamic study was performed in rat after intravenous administration. The optimized formulation had 100 mg of PLGA, 1% polyvinyl alcohol (PVA) and 1:2 acetone:water ratio. The Lf and Tf conjugation to PLGA NPs was estimated to 186 Tf and 185 Lf molecules per NPs. Lyophilization was optimized at 1:2 ratio of NPs:trehalose. The NPs were found stable for 6 months at refrigerated condition. Pharmacodynamic study demonstrated enhanced efficacy of ligand-conjugated NPs against unconjugated NPs. Conjugated NPs demonstrated significantly higher pharmacological effect over a period of 24 h. Furthermore Lf functionalized NPs exhibited better antinociceptive effect as compared to Tf functionalized NPs.