A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data.

PubMed

Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke; Le, Tam; Takeuchi, Ichiro; Tateyama, Yoshitaka; Yamazaki, Hisatsugu

2018-01-01

Increasing attention has been paid to materials informatics approaches that promise efficient and fast discovery and optimization of functional inorganic materials. Technical breakthrough is urgently requested to advance this field and efforts have been made in the development of materials descriptors to encode or represent characteristics of crystalline solids, such as chemical composition, crystal structure, electronic structure, etc. We propose a general representation scheme for crystalline solids that lifts restrictions on atom ordering, cell periodicity, and system cell size based on structural descriptors of directly binned Voronoi-tessellation real feature values and atomic/chemical descriptors based on the electronegativity of elements in the crystal. Comparison was made vs. radial distribution function (RDF) feature vector, in terms of predictive accuracy on density functional theory (DFT) material properties: cohesive energy (CE), density ( d ), electronic band gap (BG), and decomposition energy (Ed). It was confirmed that the proposed feature vector from Voronoi real value binning generally outperforms the RDF-based one for the prediction of aforementioned properties. Together with electronegativity-based features, Voronoi-tessellation features from a given crystal structure that are derived from second-nearest neighbor information contribute significantly towards prediction.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov Websites

Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next -Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution Infrastructure This project develops innovative, real-time optimization and control methods for next-generation

Architecture For The Optimization Of A Machining Process In Real Time Through Rule-Based Expert System

NASA Astrophysics Data System (ADS)

Serrano, Rafael; González, Luis Carlos; Martín, Francisco Jesús

2009-11-01

Under the project SENSOR-IA which has had financial funding from the Order of Incentives to the Regional Technology Centers of the Counsil of Innovation, Science and Enterprise of Andalusia, an architecture for the optimization of a machining process in real time through rule-based expert system has been developed. The architecture consists of an acquisition system and sensor data processing engine (SATD) from an expert system (SE) rule-based which communicates with the SATD. The SE has been designed as an inference engine with an algorithm for effective action, using a modus ponens rule model of goal-oriented rules.The pilot test demonstrated that it is possible to govern in real time the machining process based on rules contained in a SE. The tests have been done with approximated rules. Future work includes an exhaustive collection of data with different tool materials and geometries in a database to extract more precise rules.

Microelectrical Impedance Spectroscopy for the Differentiation between Normal and Cancerous Human Urothelial Cell Lines: Real-Time Electrical Impedance Measurement at an Optimal Frequency

PubMed Central

Park, Yangkyu; Kim, Hyeon Woo; Yun, Joho; Seo, Seungwan; Park, Chang-Ju; Lee, Jeong Zoo; Lee, Jong-Hyun

2016-01-01

Purpose. To distinguish between normal (SV-HUC-1) and cancerous (TCCSUP) human urothelial cell lines using microelectrical impedance spectroscopy (μEIS). Materials and Methods. Two types of μEIS devices were designed and used in combination to measure the impedance of SV-HUC-1 and TCCSUP cells flowing through the channels of the devices. The first device (μEIS-OF) was designed to determine the optimal frequency at which the impedance of two cell lines is most distinguishable. The μEIS-OF trapped the flowing cells and measured their impedance at a frequency ranging from 5 kHz to 1 MHz. The second device (μEIS-RT) was designed for real-time impedance measurement of the cells at the optimal frequency. The impedance was measured instantaneously as the cells passed the sensing electrodes of μEIS-RT. Results. The optimal frequency, which maximized the average difference of the amplitude and phase angle between the two cell lines (p < 0.001), was determined to be 119 kHz. The real-time impedance of the cell lines was measured at 119 kHz; the two cell lines differed significantly in terms of amplitude and phase angle (p < 0.001). Conclusion. The μEIS-RT can discriminate SV-HUC-1 and TCCSUP cells by measuring the impedance at the optimal frequency determined by the μEIS-OF. PMID:26998490

1L Mark-IV Target Design Review

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

Koehler, Paul E.

This presentation includes General Design Considerations; Current (Mark-III) Lower Tier; Mark-III Upper Tier; Performance Metrics; General Improvements for Material Science; General Improvements for Nuclear Science; Improving FOM for Nuclear Science; General Design Considerations Summary; Design Optimization Studies; Expected Mark-IV Performance: Material Science; Expected Mark-IV Performance: Nuclear Science (Disk); Mark IV Enables Much Wider Range of Nuclear-Science FOM Gains than Mark III; Mark-IV Performance Summary; Rod or Disk? Center or Real FOV?; and Project Cost and Schedule.

Organic antireflective coatings for 193-nm lithography

NASA Astrophysics Data System (ADS)

Trefonas, Peter, III; Blacksmith, Robert F.; Szmanda, Charles R.; Kavanagh, Robert J.; Adams, Timothy G.; Taylor, Gary N.; Coley, Suzanne; Pohlers, Gerd

1999-06-01

Organic anti-reflective coatings (ARCs) continue to play an important role in semiconductor manufacturing. These materials provide a convenient means of greatly reducing the resist photospeed swing and reflective notching. In this paper, we describe a novel class of ARC materials optimized for lithographic applications using 193 nm exposure tools. These ARCs are based upon polymers containing hydroxyl-alkyl methacrylate monomers for crosslinkable sites, styrene for a chromophore at 193 nm, and additional alkyl-methacrylate monomers as property modifiers. A glycouril crosslinker and a thermally-activated acidic catalyst provide a route to forming an impervious crosslinked film activate data high bake temperatures. ARC compositions can be adjusted to optimize the film's real and imaginary refractive indices. Selection of optimal target indices for 193 nm lithographic processing through simulations is described. Potential chromophores for 193 nm were explored using ZNDO modeling. We show how these theoretical studies were combined with material selection criteria to yield a versatile organic anti-reflectant film, Shipley 193 G0 ARC. Lithographic process data indicates the materials is capable of supporting high resolution patterning, with the line features displaying a sharp resist/ARC interface with low line edge roughness. The resist Eo swing is successfully reduced from 43 percent to 6 percent.

Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model

NASA Astrophysics Data System (ADS)

Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr

2017-10-01

Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.

Entropy as a Gene-Like Performance Indicator Promoting Thermoelectric Materials.

PubMed

Liu, Ruiheng; Chen, Hongyi; Zhao, Kunpeng; Qin, Yuting; Jiang, Binbin; Zhang, Tiansong; Sha, Gang; Shi, Xun; Uher, Ctirad; Zhang, Wenqing; Chen, Lidong

2017-10-01

High-throughput explorations of novel thermoelectric materials based on the Materials Genome Initiative paradigm only focus on digging into the structure-property space using nonglobal indicators to design materials with tunable electrical and thermal transport properties. As the genomic units, following the biogene tradition, such indicators include localized crystal structural blocks in real space or band degeneracy at certain points in reciprocal space. However, this nonglobal approach does not consider how real materials differentiate from others. Here, this study successfully develops a strategy of using entropy as the global gene-like performance indicator that shows how multicomponent thermoelectric materials with high entropy can be designed via a high-throughput screening method. Optimizing entropy works as an effective guide to greatly improve the thermoelectric performance through either a significantly depressed lattice thermal conductivity down to its theoretical minimum value and/or via enhancing the crystal structure symmetry to yield large Seebeck coefficients. The entropy engineering using multicomponent crystal structures or other possible techniques provides a new avenue for an improvement of the thermoelectric performance beyond the current methods and approaches. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

REAL-TIME IDENTIFICATION AND CHARACTERIZATION OF ASBESTOS AND CONCRETE MATERIALS WITH RADIOACTIVE CONTAMINATION

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

XU, X. George; Zhang, X.C.

Concrete and asbestos-containing materials were widely used in DOE building construction in the 1940s and 1950s. Over the years, many of these porous materials have been contaminated with radioactive sources, on and below the surface. To improve current practice in identifying hazardous materials and in characterizing radioactive contamination, an interdisciplinary team from Rensselaer has conducted research in two aspects: (1) to develop terahertz time-domain spectroscopy and imaging system that can be used to analyze environmental samples such as asbestos in the field, and (2) to develop algorithms for characterizing the radioactive contamination depth profiles in real-time in the field usingmore » gamma spectroscopy. The basic research focused on the following: (1) mechanism of generating of broadband pulsed radiation in terahertz region, (2) optimal free-space electro-optic sampling for asbestos, (3) absorption and transmission mechanisms of asbestos in THz region, (4) the role of asbestos sample conditions on the temporal and spectral distributions, (5) real-time identification and mapping of asbestos using THz imaging, (7) Monte Carlo modeling of distributed contamination from diffusion of radioactive materials into porous concrete and asbestos materials, (8) development of unfolding algorithms for gamma spectroscopy, and (9) portable and integrated spectroscopy systems for field testing in DOE. Final results of the project show that the combination of these innovative approaches has the potential to bring significant improvement in future risk reduction and cost/time saving in DOE's D and D activities.« less

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging.

PubMed

Tremsin, Anton S; Perrodin, Didier; Losko, Adrian S; Vogel, Sven C; Bourke, Mark A M; Bizarri, Gregory A; Bourret, Edith D

2017-04-20

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes.

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

NASA Astrophysics Data System (ADS)

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; Vogel, Sven C.; Bourke, Mark A. M.; Bizarri, Gregory A.; Bourret, Edith D.

2017-04-01

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of “blind” processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes.

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

PubMed Central

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; Vogel, Sven C.; Bourke, Mark A.M.; Bizarri, Gregory A.; Bourret, Edith D.

2017-01-01

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of “blind” processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes. PMID:28425461

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

Veedu, Vinod; Hadmack, Michael; Pollock, Jacob

Nanite™ is a cementitious material that contains a proprietary formulation of functionalized nanomaterial additive to transform conventional cement into a smart material responsive to pressure (or stress), temperature, and any intrinsic changes in composition. This project has identified optimal sensing modalities of smart well cement and demonstrated how real-time sensing of Nanite™ can improve long-term wellbore integrity and zonal isolation in shale gas and applicable oil and gas operations. Oceanit has explored Nanite’s electrical sensing properties in depth and has advanced the technology from laboratory proof-of-concept to sub-scale testing in preparation for field trials.

The Tubular Penetration Depth and Adaption of Four Sealers: A Scanning Electron Microscopic Study

PubMed Central

Chen, Huan; Zhao, Xinyuan; Qiu, Yu; Xu, Dengyou

2017-01-01

Background. The tubular penetration and adaptation of the sealer are important factors for successful root canal filling. The aim of this study was to evaluate the tubular penetration depth of four different sealers in the coronal, middle, and apical third of root canals as well as the adaptation of these sealers to root canal walls. Materials and Methods. 50 single-rooted teeth were prepared in this study. Forty-eight of them were filled with different sealers (Cortisomol, iRoot SP, AH-Plus, and RealSeal SE) and respective core filling materials. Then the specimens were sectioned and scanning electron microscopy was employed to assess the tubular penetration and adaptation of the sealers. Results. Our results demonstrated that the maximum penetration was exhibited by RealSeal SE, followed by AH-Plus, iRoot SP, and Cortisomol. As regards the adaptation property to root canal walls, AH-Plus has best adaptation capacity followed by iRoot SP, RealSeal SE, and Cortisomol. Conclusion. The tubular penetration and adaptation vary with the different sealers investigated. RealSeal SE showed the most optimal tubular penetration, whereas AH-Plus presented the best adaptation to the root canal walls. PMID:29479539

Towards sensor array materials: can failure be delayed?

PubMed Central

Mekid, Samir; Saheb, Nouari; Khan, Shafique M A; Qureshi, Khurram K

2015-01-01

Further to prior development in enhancing structural health using smart materials, an innovative class of materials characterized by the ability to feel senses like humans, i.e. ‘nervous materials’, is discussed. Designed at all scales, these materials will enhance personnel and public safety, and secure greater reliability of products. Materials may fail suddenly, but any system wishes that failure is known in good time and delayed until safe conditions are reached. Nervous materials are expected to be the solution to this statement. This new class of materials is based on the novel concept of materials capable of feeling multiple structural and external stimuli, e.g. stress, force, pressure and temperature, while feeding information back to a controller for appropriate real-time action. The strain–stress state is developed in real time with the identified and characterized source of stimulus, with optimized time response to retrieve initial specified conditions, e.g. shape and strength. Sensors are volumetrically embedded and distributed, emulating the human nervous system. Immediate applications are in aircraft, cars, nuclear energy and robotics. Such materials will reduce maintenance costs, detect initial failures and delay them with self-healing. This article reviews the common aspects and challenges surrounding this new class of materials with types of sensors to be embedded seamlessly or inherently, including appropriate embedding manufacturing techniques with modeling and simulation methods. PMID:27877794

Towards sensor array materials: can failure be delayed?

NASA Astrophysics Data System (ADS)

Mekid, Samir; Saheb, Nouari; Khan, Shafique M. A.; Qureshi, Khurram K.

2015-06-01

Further to prior development in enhancing structural health using smart materials, an innovative class of materials characterized by the ability to feel senses like humans, i.e. ‘nervous materials’, is discussed. Designed at all scales, these materials will enhance personnel and public safety, and secure greater reliability of products. Materials may fail suddenly, but any system wishes that failure is known in good time and delayed until safe conditions are reached. Nervous materials are expected to be the solution to this statement. This new class of materials is based on the novel concept of materials capable of feeling multiple structural and external stimuli, e.g. stress, force, pressure and temperature, while feeding information back to a controller for appropriate real-time action. The strain-stress state is developed in real time with the identified and characterized source of stimulus, with optimized time response to retrieve initial specified conditions, e.g. shape and strength. Sensors are volumetrically embedded and distributed, emulating the human nervous system. Immediate applications are in aircraft, cars, nuclear energy and robotics. Such materials will reduce maintenance costs, detect initial failures and delay them with self-healing. This article reviews the common aspects and challenges surrounding this new class of materials with types of sensors to be embedded seamlessly or inherently, including appropriate embedding manufacturing techniques with modeling and simulation methods.

Characterizing dielectric tensors of anisotropic materials from a single measurement

NASA Astrophysics Data System (ADS)

Smith, Paula Kay

Ellipsometry techniques look at changes in polarization states to measure optical properties of thin film materials. A beam reflected from a substrate measures the real and imaginary parts of the index of the material represented as n and k, respectively. Measuring the substrate at several angles gives additional information that can be used to measure multilayer thin film stacks. However, the outstanding problem in standard ellipsometry is that it uses a limited number of incident polarization states (s and p). This limits the technique to isotropic materials. The technique discussed in this paper extends the standard process to measure anisotropic materials by using a larger set of incident polarization states. By using a polarimeter to generate several incident polarization states and measure the polarization properties of the sample, ellipsometry can be performed on biaxial materials. Use of an optimization algorithm in conjunction with biaxial ellipsometry can more accurately determine the dielectric tensor of individual layers in multilayer structures. Biaxial ellipsometry is a technique that measures the dielectric tensors of a biaxial substrate, single-layer thin film, or multi-layer structure. The dielectric tensor of a biaxial material consists of the real and imaginary parts of the three orthogonal principal indices (n x + ikx, ny +iky and nz + i kz) as well as three Euler angles (alpha, beta and gamma) to describe its orientation. The method utilized in this work measures an angle-of-incidence Mueller matrix from a Mueller matrix imaging polarimeter equipped with a pair of microscope objectives that have low polarization properties. To accurately determine the dielectric tensors for multilayer samples, the angle-of-incidence Mueller matrix images are collected for multiple wavelengths. This is done in either a transmission mode or a reflection mode, each incorporates an appropriate dispersion model. Given approximate a priori knowledge of the dielectric tensor and film thickness, a Jones reflectivity matrix is calculated by solving Maxwell's equations at each surface. Converting the Jones matrix into a Mueller matrix provides a starting point for optimization. An optimization algorithm then finds the best fit dielectric tensor based on the measured angle-of-incidence Mueller matrix image. This process can be applied to polarizing materials, birefringent crystals and the multilayer structures of liquid crystal displays. In particular, the need for such accuracy in liquid crystal displays is growing as their applications in industry evolve.

Performance of coincidence-based PSD on LiF/ZnS Detectors for Multiplicity Counting

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

Robinson, Sean M.; Stave, Sean C.; Lintereur, Azaree

Abstract: Mass accountancy measurement is a nuclear nonproliferation application which utilizes coincidence and multiplicity counters to verify special nuclear material declarations. With a well-designed and efficient detector system, several relevant parameters of the material can be verified simultaneously. 6LiF/ZnS scintillating sheets may be used for this purpose due to a combination of high efficiency and short die-away times in systems designed with this material, but involve choices of detector geometry and exact material composition (e.g., the addition of Ni-quenching in the material) that must be optimized for the application. Multiplicity counting for verification of declared nuclear fuel mass involves neutronmore » detection in conditions where several neutrons arrive in a short time window, with confounding gamma rays. This paper considers coincidence-based Pulse-Shape Discrimination (PSD) techniques developed to work under conditions of high pileup, and the performance of these algorithms with different detection materials. Simulated and real data from modern LiF/ZnS scintillator systems are evaluated with these techniques and the relationship between the performance under pileup and material characteristics (e.g., neutron peak width and total light collection efficiency) are determined, to allow for an optimal choice of detector and material.« less

A Comprehensive Optimization Strategy for Real-time Spatial Feature Sharing and Visual Analytics in Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Li, W.; Shao, H.

2017-12-01

For geospatial cyberinfrastructure enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for the vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: 1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance (ADT) to meet various visualization requirements, and at the same time speed up simplification efficiency; 2) a progressive attribute transmission method to reduce data size and therefore the service response time; 3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to widen the use of web service providing vector data to support real-time spatial feature sharing, visual analytics and decision-making.

Multi-parameter optimization of monolithic high-index contrast grating reflectors

NASA Astrophysics Data System (ADS)

Marciniak, Magdalena; Gebski, Marcin; Dems, Maciej; Wasiak, Michał; Czyszanowski, Tomasz

2016-03-01

Conventional High-index Contrast Gratings (HCG) consist of periodically distributed high refractive index stripes surrounded by low index media. Practically, such low/high index stack can be fabricated in several ways however low refractive index layers are electrical insulators of poor thermal conductivities. Monolithic High-index Contrast Gratings (MHCGs) overcome those limitations since they can be implemented in any material with a real refractive index larger than 1.75 without the need of the combination of low and high refractive index materials. The freedom of use of various materials allows to provide more efficient current injection and better heat flow through the mirror, in contrary to the conventional HCGs. MHCGs can simplify the construction of VCSELs, reducing their epitaxial design to monolithic wafer with carrier confinement and active region inside and etched stripes on both surfaces in post processing. We present numerical analysis of MHCGs using a three-dimensional, fully vectorial optical model. We investigate possible designs of MHCGs using multidimensional optimization of grating parameters for different refractive indices.

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

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

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production.more » This technique is widely applicable and is not limited to crystal growth processes.« less

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

DOE PAGES

Tremsin, Anton S.; Perrodin, Didier; Losko, Adrian S.; ...

2017-04-20

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production.more » This technique is widely applicable and is not limited to crystal growth processes.« less

The Application Research of Modern Intelligent Cold Chain Distribution System Based on Internet of Things Technology

NASA Astrophysics Data System (ADS)

Fan, Dehui; Gao, Shan

This paper implemented an intelligent cold chain distribution system based on the technology of Internet of things, and took the protoplasmic beer logistics transport system as example. It realized the remote real-time monitoring material status, recorded the distribution information, dynamically adjusted the distribution tasks and other functions. At the same time, the system combined the Internet of things technology with weighted filtering algorithm, realized the real-time query of condition curve, emergency alarming, distribution data retrieval, intelligent distribution task arrangement, etc. According to the actual test, it can realize the optimization of inventory structure, and improve the efficiency of cold chain distribution.

SymPS: BRDF Symmetry Guided Photometric Stereo for Shape and Light Source Estimation.

PubMed

Lu, Feng; Chen, Xiaowu; Sato, Imari; Sato, Yoichi

2018-01-01

We propose uncalibrated photometric stereo methods that address the problem due to unknown isotropic reflectance. At the core of our methods is the notion of "constrained half-vector symmetry" for general isotropic BRDFs. We show that such symmetry can be observed in various real-world materials, and it leads to new techniques for shape and light source estimation. Based on the 1D and 2D representations of the symmetry, we propose two methods for surface normal estimation; one focuses on accurate elevation angle recovery for surface normals when the light sources only cover the visible hemisphere, and the other for comprehensive surface normal optimization in the case that the light sources are also non-uniformly distributed. The proposed robust light source estimation method also plays an essential role to let our methods work in an uncalibrated manner with good accuracy. Quantitative evaluations are conducted with both synthetic and real-world scenes, which produce the state-of-the-art accuracy for all of the non-Lambertian materials in MERL database and the real-world datasets.

Temperature - Emissivity Separation Assessment in a Sub-Urban Scenario

NASA Astrophysics Data System (ADS)

Moscadelli, M.; Diani, M.; Corsini, G.

2017-10-01

In this paper, a methodology that aims at evaluating the effectiveness of different TES strategies is presented. The methodology takes into account the specific material of interest in the monitored scenario, sensor characteristics, and errors in the atmospheric compensation step. The methodology is proposed in order to predict and analyse algorithms performances during the planning of a remote sensing mission, aimed to discover specific materials of interest in the monitored scenario. As case study, the proposed methodology is applied to a real airborne data set of a suburban scenario. In order to perform the TES problem, three state-of-the-art algorithms, and a recently proposed one, are investigated: Temperature-Emissivity Separation '98 (TES-98) algorithm, Stepwise Refining TES (SRTES) algorithm, Linear piecewise TES (LTES) algorithm, and Optimized Smoothing TES (OSTES) algorithm. At the end, the accuracy obtained with real data, and the ones predicted by means of the proposed methodology are compared and discussed.

Microgravimetric Analysis Method for Activation-Energy Extraction from Trace-Amount Molecule Adsorption.

PubMed

Xu, Pengcheng; Yu, Haitao; Li, Xinxin

2016-05-03

Activation-energy (Ea) value for trace-amount adsorption of gas molecules on material is rapidly and inexpensively obtained, for the first time, from a microgravimetric analysis experiment. With the material loaded, a resonant microcantilever is used to record in real time the adsorption process at two temperatures. The kinetic parameter Ea is thereby extracted by solving the Arrhenius equation. As an example, two CO2 capture nanomaterials are examined by the Ea extracting method for evaluation/optimization and, thereby, demonstrating the applicability of the microgravimetric analysis method. The achievement helps to solve the absence in rapid quantitative characterization of sorption kinetics and opens a new route to investigate molecule adsorption processes and materials.

Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

PubMed Central

Liu, Xiaoli; Chen, Hong-Xin; Kim, Jinxie

2014-01-01

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline. PMID:25025089

Compact and portable digitally controlled device for testing footwear materials: technical note.

PubMed

Foto, James G

2008-01-01

Little or no practical decision-making data are available to the foot-care provider regarding the selection of orthotic materials used in therapeutic footwear. A device for simulating in-shoe forefoot conditions for the testing of orthosis materials is described. Materials are tested for their effectiveness by evaluating and comparing stress-strain and dynamic compression fatigue characteristics. The device, called the Cyclical Compression Tester (CCT), has been optimized for size, simplicity of construction, and cost. Application of the device ranges from the clinician deciding the useful life of single- and multidensity orthosis materials to the researcher characterizing materials for finite-element analysis modeling. This real-time CCT device and custom user interface combine to make an evaluation tool useful for testing how the pressure distribution of in-shoe materials changes over time in therapeutic footwear for those with peripheral neuropathy at risk for foot injury.

``Phantom'' Modes in Ab Initio Tunneling Calculations: Implications for Theoretical Materials Optimization, Tunneling, and Transport

NASA Astrophysics Data System (ADS)

Barabash, Sergey V.; Pramanik, Dipankar

2015-03-01

Development of low-leakage dielectrics for semiconductor industry, together with many other areas of academic and industrial research, increasingly rely upon ab initio tunneling and transport calculations. Complex band structure (CBS) is a powerful formalism to establish the nature of tunneling modes, providing both a deeper understanding and a guided optimization of materials, with practical applications ranging from screening candidate dielectrics for lowest ``ultimate leakage'' to identifying charge-neutrality levels and Fermi level pinning. We demonstrate that CBS is prone to a particular type of spurious ``phantom'' solution, previously deemed true but irrelevant because of a very fast decay. We demonstrate that (i) in complex materials, phantom modes may exhibit very slow decay (appearing as leading tunneling terms implying qualitative and huge quantitative errors), (ii) the phantom modes are spurious, (iii) unlike the pseudopotential ``ghost'' states, phantoms are an apparently unavoidable artifact of large numerical basis sets, (iv) a presumed increase in computational accuracy increases the number of phantoms, effectively corrupting the CBS results despite the higher accuracy achieved in resolving the true CBS modes and the real band structure, and (v) the phantom modes cannot be easily separated from the true CBS modes. We discuss implications for direct transport calculations. The strategy for dealing with the phantom states is discussed in the context of optimizing high-quality high- κ dielectric materials for decreased tunneling leakage.

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

NASA Astrophysics Data System (ADS)

Cai, Zhenhua; Chen, Tingyang; Zeng, Chunnian; Guo, Xueping; Lian, Huijuan; Zheng, You; Wei, Xiaoxu

2016-12-01

This paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). Owing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

Real-time focus controller for laser welding with fibre optic noninvasive capture of light

NASA Astrophysics Data System (ADS)

Cobo, Adolfo; Bardin, F.; Hand, Duncan P.; Jones, Julian D.; Collin, O.; Aubry, P.; Dubois, Thierry; Hoegstroem, M.; Nylen, P.; Jonsson, P.; Lopez-Higuera, Jose M.

2004-06-01

Laser welding is being introduced in the aerospace industry due to its many advantages over traditional techniques. However, welding of parts with complex shapes requires precise control of the focal point of the laser in order to achieve full penetration over the entire seam. In this paper, we present an improved control system for real-time adjustment of the correct focal position, which is based on the monitoring of the light emitted by the process in two different spectral bands. The reported system has been optimized for use in a real environment: it is robust, compact, easy to operate, able to adjust itself to different welding conditions, materials and laser setups, and includes a direct connection to an external PC. Results from recent field trials on complex aerospace structures are provided.

Using real-time electron microscopy to explore the effects of transition-metal composition on the local thermal stability in charged Li xNi yMn zCo 1-y-zO 2 cathode materials

DOE PAGES

Hwang, Sooyeon; Kim, Seung Min; Bak, Seong -Min; ...

2015-05-08

In this study, we use in-situ transmission electron microcopy (TEM) to investigate the thermal decomposition that occurs at the surface of charged Li xNi yMn zCo 1-y-zO 2 (NMC) cathode materials of different composition (with y, z=0.8, 0.1 and 0.6, 0.2 and 0.4, 0.3), after they have been charged to their practical upper limit voltage (4.3V). By heating these materials inside the TEM, we are able to directly characterize near surface changes in both their electronic structure (using electron energy loss spectroscopy) and crystal structure and morphology (using electron diffraction and bright-field imaging). The most Ni-rich material (y, z =more » 0.8, 0.1) is found to be thermally unstable at significantly lower temperatures than the other compositions – this is manifested by changes in both the electronic structure and the onset of phase transitions at temperatures as low as 100°C. Electron energy loss spectroscopy indicates that the thermally induced reduction of Ni ions drives these changes, and that this is exacerbated by the presence of an additional redox reaction that occurs at 4.2V in the y, z = 0.8, 0.1 material. Exploration of individual particles shows that there are substantial variations in the onset temperatures and overall extent of these changes. Of the compositions studied, the composition of y, z = 0.6, 0.2 has the optimal combination of high energy density and reasonable thermal stability. The observations herein demonstrate that real time electron microscopy provide direct insight into the changes that occur in cathode materials with temperature, allowing optimization of different alloy concentrations to maximize overall performance.« less

Optimization Testbed Cometboards Extended into Stochastic Domain

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.; Patnaik, Surya N.

2010-01-01

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

Expanding the Design Space: Forging the Transition from 3D Printing to Additive Manufacturing

NASA Astrophysics Data System (ADS)

Amend, Matthew

The synergy of Additive Manufacturing and Computational Geometry has the potential to radically expand the "design space" of solutions available to designers. Additive Manufacturing (AM) is capable of fabricating objects that are highly complex both in geometry and material properties. However, the introduction of any new technology can have a disruptive effect on established design practices and organizations. Before "Design for Additive Manufacturing" (DFAM) is a commonplace means of producing objects employed in "real world" products, appropriate design knowledge must be sufficiently integrated within industry. First, materials suited to additive manufacturing methods must be developed to satisfy existing industry standards and specifications, or new standards must be developed. Second, a new class of design representation (CAD) tools will need to be developed. Third, designers and design organizations will need to develop strategies for employing such tools. This thesis describes three DFAM exercises intended to demonstrate the potential for innovative design when using advanced additive materials, tools, and printers. These design exercises included 1) a light-weight composite layup mold developed with topology optimization, 2) a low-pressure fluid duct enhanced with an external lattice structure, and 3) an airline seat tray designed using a non-uniform lattice structure optimized with topology optimization.

A web-based Decision Support System for the optimal management of construction and demolition waste.

PubMed

Banias, G; Achillas, Ch; Vlachokostas, Ch; Moussiopoulos, N; Papaioannou, I

2011-12-01

Wastes from construction activities constitute nowadays the largest by quantity fraction of solid wastes in urban areas. In addition, it is widely accepted that the particular waste stream contains hazardous materials, such as insulating materials, plastic frames of doors, windows, etc. Their uncontrolled disposal result to long-term pollution costs, resource overuse and wasted energy. Within the framework of the DEWAM project, a web-based Decision Support System (DSS) application - namely DeconRCM - has been developed, aiming towards the identification of the optimal construction and demolition waste (CDW) management strategy that minimises end-of-life costs and maximises the recovery of salvaged building materials. This paper addresses both technical and functional structure of the developed web-based application. The web-based DSS provides an accurate estimation of the generated CDW quantities of twenty-one different waste streams (e.g. concrete, bricks, glass, etc.) for four different types of buildings (residential, office, commercial and industrial). With the use of mathematical programming, the DeconRCM provides also the user with the optimal end-of-life management alternative, taking into consideration both economic and environmental criteria. The DSS's capabilities are illustrated through a real world case study of a typical five floor apartment building in Thessaloniki, Greece. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reliability-Based Design Optimization of a Composite Airframe Component

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2009-01-01

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Probabilistic Cloning of Three Real States with Optimal Success Probabilities

NASA Astrophysics Data System (ADS)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.

Tunable dynamic response of magnetic gels: Impact of structural properties and magnetic fields

NASA Astrophysics Data System (ADS)

Tarama, Mitsusuke; Cremer, Peet; Borin, Dmitry Y.; Odenbach, Stefan; Löwen, Hartmut; Menzel, Andreas M.

2014-10-01

Ferrogels and magnetic elastomers feature mechanical properties that can be reversibly tuned from outside through magnetic fields. Here we concentrate on the question of how their dynamic response can be adjusted. The influence of three factors on the dynamic behavior is demonstrated using appropriate minimal models: first, the orientational memory imprinted into one class of the materials during their synthesis; second, the structural arrangement of the magnetic particles in the materials; and third, the strength of an external magnetic field. To illustrate the latter point, structural data are extracted from a real experimental sample and analyzed. Understanding how internal structural properties and external influences impact the dominant dynamical properties helps to design materials that optimize the requested behavior.

Real-time detection of mercury ions in water using a reduced graphene oxide/DNA field-effect transistor with assistance of a passivation layer

DOE PAGES

Chang, Jingbo; Zhou, Guihua; Gao, Xianfeng; ...

2015-08-01

Field-effect transistor (FET) sensors based on reduced graphene oxide (rGO) for detecting chemical species provide a number of distinct advantages, such as ultrasensitivity, label-free, and real-time response. However, without a passivation layer, channel materials directly exposed to an ionic solution could generate multiple signals from ionic conduction through the solution droplet, doping effect, and gating effect. Therefore, a method that provides a passivation layer on the surface of rGO without degrading device performance will significantly improve device sensitivity, in which the conductivity changes solely with the gating effect. In this work, we report rGO FET sensor devices with Hg 2+-dependentmore » DNA as a probe and the use of an Al 2O 3 layer to separate analytes from conducting channel materials. The device shows good electronic stability, excellent lower detection limit (1 nM), and high sensitivity for real-time detection of Hg 2+ in an underwater environment. Our work shows that optimization of an rGO FET structure can provide significant performance enhancement and profound fundamental understanding for the sensor mechanism.« less

Aggregation Pheromone System: A Real-parameter Optimization Algorithm using Aggregation Pheromones as the Base Metaphor

NASA Astrophysics Data System (ADS)

Tsutsui, Shigeyosi

This paper proposes an aggregation pheromone system (APS) for solving real-parameter optimization problems using the collective behavior of individuals which communicate using aggregation pheromones. APS was tested on several test functions used in evolutionary computation. The results showed APS could solve real-parameter optimization problems fairly well. The sensitivity analysis of control parameters of APS is also studied.

Experimental data showing the thermal behavior of a flat roof with phase change material.

PubMed

Tokuç, Ayça; Başaran, Tahsin; Yesügey, S Cengiz

2015-12-01

The selection and configuration of building materials for optimal energy efficiency in a building require some assumptions and models for the thermal behavior of the utilized materials. Although the models for many materials can be considered acceptable for simulation and calculation purposes, the work for modeling the real time behavior of phase change materials is still under development. The data given in this article shows the thermal behavior of a flat roof element with a phase change material (PCM) layer. The temperature and energy given to and taken from the building element are reported. In addition the solid-liquid behavior of the PCM is tracked through images. The resulting thermal behavior of the phase change material is discussed and simulated in [1] A. Tokuç, T. Başaran, S.C. Yesügey, An experimental and numerical investigation on the use of phase change materials in building elements: the case of a flat roof in Istanbul, Build. Energy, vol. 102, 2015, pp. 91-104.

Understanding non-radiative recombination processes of the optoelectronic materials from first principles

NASA Astrophysics Data System (ADS)

Shu, Yinan

The annual potential of the solar energy hit on the Earth is several times larger than the total energy consumption in the world. This huge amount of energy source makes it appealing as an alternative to conventional fuels. Due to the problems, for example, global warming, fossil fuel shortage, etc. arising from utilizing the conventional fuels, a tremendous amount of efforts have been applied toward the understanding and developing cost effective optoelectrical devices in the past decades. These efforts have pushed the efficiency of optoelectrical devices, say solar cells, increases from 0% to 46% as reported until 2015. All these facts indicate the significance of the optoelectrical devices not only regarding protecting our planet but also a large potential market. Empirical experience from experiment has played a key role in optimization of optoelectrical devices, however, a deeper understanding of the detailed electron-by-electron, atom-by-atom physical processes when material upon excitation is the key to gain a new sight into the field. It is also useful in developing the next generation of solar materials. Thanks to the advances in computer hardware, new algorithms, and methodologies developed in computational chemistry and physics in the past decades, we are now able to 1). model the real size materials, e.g. nanoparticles, to locate important geometries on the potential energy surfaces(PESs); 2). investigate excited state dynamics of the cluster models to mimic the real systems; 3). screen large amount of possible candidates to be optimized toward certain properties, so to help in the experiment design. In this thesis, I will discuss the efforts we have been doing during the past several years, especially in terms of understanding the non-radiative decay process of silicon nanoparticles with oxygen defects using ab initio nonadiabatic molecular dynamics as well as the accurate, efficient multireference electronic structure theories we have developed to fulfill our purpose. The new paradigm we have proposed in understanding the nonradiative recombination mechanisms is also applied to other systems, like water splitting catalyst. Besides in gaining a deeper understanding of the mechanism, we applied an evolutionary algorithm to optimize promising candidates towards specific properties, for example, organic light emitting diodes (OLED).

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

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

Zhang, Weizhao; Ren, Huaqing; Lu, Jie

This paper reports several characterization methods of the properties of the uncured woven prepreg during the preforming process. The uniaxial tension, bias-extension, and bending tests are conducted to measure the in-plane properties of the material. The friction tests utilized to reveal the prepreg-prepreg and prepreg-forming tool interactions. All these tests are performed within the temperature range of the real manufacturing process. The results serve as the inputs to the numerical simulation for the product prediction and preforming process parameter optimization.

Stent deployment protocol for optimized real-time visualization during endovascular neurosurgery.

PubMed

Silva, Michael A; See, Alfred P; Dasenbrock, Hormuzdiyar H; Ashour, Ramsey; Khandelwal, Priyank; Patel, Nirav J; Frerichs, Kai U; Aziz-Sultan, Mohammad A

2017-05-01

Successful application of endovascular neurosurgery depends on high-quality imaging to define the pathology and the devices as they are being deployed. This is especially challenging in the treatment of complex cases, particularly in proximity to the skull base or in patients who have undergone prior endovascular treatment. The authors sought to optimize real-time image guidance using a simple algorithm that can be applied to any existing fluoroscopy system. Exposure management (exposure level, pulse management) and image post-processing parameters (edge enhancement) were modified from traditional fluoroscopy to improve visualization of device position and material density during deployment. Examples include the deployment of coils in small aneurysms, coils in giant aneurysms, the Pipeline embolization device (PED), the Woven EndoBridge (WEB) device, and carotid artery stents. The authors report on the development of the protocol and their experience using representative cases. The stent deployment protocol is an image capture and post-processing algorithm that can be applied to existing fluoroscopy systems to improve real-time visualization of device deployment without hardware modifications. Improved image guidance facilitates aneurysm coil packing and proper positioning and deployment of carotid artery stents, flow diverters, and the WEB device, especially in the context of complex anatomy and an obscured field of view.

Improving Mid-Course Flight Through an Application of Real-Time Optimal Control

DTIC Science & Technology

2017-12-01

COURSE FLIGHT THROUGH AN APPLICATION OF REAL- TIME OPTIMAL CONTROL by Mark R. Roncoroni December 2017 Thesis Advisor: Ronald Proulx Co...collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources...AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE IMPROVING MID-COURSE FLIGHT THROUGH AN APPLICATION OF REAL- TIME OPTIMAL CONTROL 5. FUNDING

Closed-Loop Optimal Control Implementations for Space Applications

DTIC Science & Technology

2016-12-01

analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to feedback on the...through the analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering

Using real time traveler demand data to optimize commuter rail feeder systems.

DOT National Transportation Integrated Search

2012-08-01

"This report focuses on real time optimization of the Commuter Rail Circulator Route Network Design Problem (CRCNDP). The route configuration of the circulator system where to stop and the route among the stops is determined on a real-time ba...

On-the-fly data assessment for high-throughput x-ray diffraction measurements

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

Ren, Fang; Pandolfi, Ronald; Van Campen, Douglas

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributesmore » in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. Finally, with these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.« less

On-the-fly data assessment for high-throughput x-ray diffraction measurements

DOE PAGES

Ren, Fang; Pandolfi, Ronald; Van Campen, Douglas; ...

2017-05-02

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for the discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through the development of an approach that makes routine data assessment automatic and instantaneous. By extracting and visualizing customized attributesmore » in real time, data quality and coverage, as well as other scientifically relevant information contained in large data sets, is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize the usage of expensive characterization resources by prioritizing measurements of the highest scientific impact. We anticipate our approach will become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. Finally, with these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition.« less

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy.

PubMed

Sans, Victor; Porwol, Luzian; Dragone, Vincenza; Cronin, Leroy

2015-02-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19 F, 13 C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19 F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations.

A study of the application of singular perturbation theory. [development of a real time algorithm for optimal three dimensional aircraft maneuvers

NASA Technical Reports Server (NTRS)

Mehra, R. K.; Washburn, R. B.; Sajan, S.; Carroll, J. V.

1979-01-01

A hierarchical real time algorithm for optimal three dimensional control of aircraft is described. Systematic methods are developed for real time computation of nonlinear feedback controls by means of singular perturbation theory. The results are applied to a six state, three control variable, point mass model of an F-4 aircraft. Nonlinear feedback laws are presented for computing the optimal control of throttle, bank angle, and angle of attack. Real Time capability is assessed on a TI 9900 microcomputer. The breakdown of the singular perturbation approximation near the terminal point is examined Continuation methods are examined to obtain exact optimal trajectories starting from the singular perturbation solutions.

Design and optimization of membrane-type acoustic metamaterials

NASA Astrophysics Data System (ADS)

Blevins, Matthew Grant

One of the most common problems in noise control is the attenuation of low frequency noise. Typical solutions require barriers with high density and/or thickness. Membrane-type acoustic metamaterials are a novel type of engineered material capable of high low-frequency transmission loss despite their small thickness and light weight. These materials are ideally suited to applications with strict size and weight limitations such as aircraft, automobiles, and buildings. The transmission loss profile can be manipulated by changing the micro-level substructure, stacking multiple unit cells, or by creating multi-celled arrays. To date, analysis has focused primarily on experimental studies in plane-wave tubes and numerical modeling using finite element methods. These methods are inefficient when used for applications that require iterative changes to the structure of the material. To facilitate design and optimization of membrane-type acoustic metamaterials, computationally efficient dynamic models based on the impedance-mobility approach are proposed. Models of a single unit cell in a waveguide and in a baffle, a double layer of unit cells in a waveguide, and an array of unit cells in a baffle are studied. The accuracy of the models and the validity of assumptions used are verified using a finite element method. The remarkable computational efficiency of the impedance-mobility models compared to finite element methods enables implementation in design tools based on a graphical user interface and in optimization schemes. Genetic algorithms are used to optimize the unit cell design for a variety of noise reduction goals, including maximizing transmission loss for broadband, narrow-band, and tonal noise sources. The tools for design and optimization created in this work will enable rapid implementation of membrane-type acoustic metamaterials to solve real-world noise control problems.

Biological properties of solid free form designed ceramic scaffolds with BMP-2: in vitro and in vivo evaluation.

PubMed

Abarrategi, Ander; Moreno-Vicente, Carolina; Martínez-Vázquez, Francisco Javier; Civantos, Ana; Ramos, Viviana; Sanz-Casado, José Vicente; Martínez-Corriá, Ramón; Perera, Fidel Hugo; Mulero, Francisca; Miranda, Pedro; López-Lacomba, José Luís

2012-01-01

Porous ceramic scaffolds are widely studied in the tissue engineering field due to their potential in medical applications as bone substitutes or as bone-filling materials. Solid free form (SFF) fabrication methods allow fabrication of ceramic scaffolds with fully controlled pore architecture, which opens new perspectives in bone tissue regeneration materials. However, little experimentation has been performed about real biological properties and possible applications of SFF designed 3D ceramic scaffolds. Thus, here the biological properties of a specific SFF scaffold are evaluated first, both in vitro and in vivo, and later scaffolds are also implanted in pig maxillary defect, which is a model for a possible application in maxillofacial surgery. In vitro results show good biocompatibility of the scaffolds, promoting cell ingrowth. In vivo results indicate that material on its own conducts surrounding tissue and allow cell ingrowth, thanks to the designed pore size. Additional osteoinductive properties were obtained with BMP-2, which was loaded on scaffolds, and optimal bone formation was observed in pig implantation model. Collectively, data show that SFF scaffolds have real application possibilities for bone tissue engineering purposes, with the main advantage of being fully customizable 3D structures.

Biological Properties of Solid Free Form Designed Ceramic Scaffolds with BMP-2: In Vitro and In Vivo Evaluation

PubMed Central

Abarrategi, Ander; Moreno-Vicente, Carolina; Martínez-Vázquez, Francisco Javier; Civantos, Ana; Ramos, Viviana; Sanz-Casado, José Vicente; Martínez-Corriá, Ramón; Perera, Fidel Hugo; Mulero, Francisca; Miranda, Pedro; López-Lacomba, José Luís

2012-01-01

Porous ceramic scaffolds are widely studied in the tissue engineering field due to their potential in medical applications as bone substitutes or as bone-filling materials. Solid free form (SFF) fabrication methods allow fabrication of ceramic scaffolds with fully controlled pore architecture, which opens new perspectives in bone tissue regeneration materials. However, little experimentation has been performed about real biological properties and possible applications of SFF designed 3D ceramic scaffolds. Thus, here the biological properties of a specific SFF scaffold are evaluated first, both in vitro and in vivo, and later scaffolds are also implanted in pig maxillary defect, which is a model for a possible application in maxillofacial surgery. In vitro results show good biocompatibility of the scaffolds, promoting cell ingrowth. In vivo results indicate that material on its own conducts surrounding tissue and allow cell ingrowth, thanks to the designed pore size. Additional osteoinductive properties were obtained with BMP-2, which was loaded on scaffolds, and optimal bone formation was observed in pig implantation model. Collectively, data show that SFF scaffolds have real application possibilities for bone tissue engineering purposes, with the main advantage of being fully customizable 3D structures. PMID:22470527

Assessment of matrix effects on methyl benzoate, a potential biomarker for detection of outgassed semi-volatiles from mold in indoor building materials.

PubMed

Parkinson, Don-Roger; Churchill, Tonia J; Rolls, Wyn

2008-11-01

Methyl benzoate - as a biomarker for mold growth - was used as a specific target compound to indicate outgassed MVOC products from mold. Both real and surrogate samples were analyzed from a variety of matrices including: carpet, ceiling tiles, dried paint surfaces, wallboard and wallboard paper. Sampling parameters, including: desorption, extraction time, incubation temperature, pH, salt effects and spinning rate, were optimized. Results suggest that extraction and detection of methyl benzoate amongst other MVOCs can be accomplished cleanly by SPME-GC/MS methods. With detection limits (LOD = 1.5 ppb) and linearity (0.999) over a range of 100 ppm to 2 ppb, this work demonstrates that such a green technique can be contemplated for use in quick assessment or as part of an ongoing assessment strategy to detect mold growth in common indoor buildings and materials for both qualitative and quantitative determinations. Of importance, no matrix effects are observed under optimized extraction conditions.

A TV-constrained decomposition method for spectral CT

NASA Astrophysics Data System (ADS)

Guo, Xiaoyue; Zhang, Li; Xing, Yuxiang

2017-03-01

Spectral CT is attracting more and more attention in medicine, industrial nondestructive testing and security inspection field. Material decomposition is an important issue to a spectral CT to discriminate materials. Because of the spectrum overlap of energy channels, as well as the correlation of basis functions, it is well acknowledged that decomposition step in spectral CT imaging causes noise amplification and artifacts in component coefficient images. In this work, we propose materials decomposition via an optimization method to improve the quality of decomposed coefficient images. On the basis of general optimization problem, total variance minimization is constrained on coefficient images in our overall objective function with adjustable weights. We solve this constrained optimization problem under the framework of ADMM. Validation on both a numerical dental phantom in simulation and a real phantom of pig leg on a practical CT system using dual-energy imaging is executed. Both numerical and physical experiments give visually obvious better reconstructions than a general direct inverse method. SNR and SSIM are adopted to quantitatively evaluate the image quality of decomposed component coefficients. All results demonstrate that the TV-constrained decomposition method performs well in reducing noise without losing spatial resolution so that improving the image quality. The method can be easily incorporated into different types of spectral imaging modalities, as well as for cases with energy channels more than two.

Hybrid supply chain model for material requirement planning under financial constraints: A case study

NASA Astrophysics Data System (ADS)

Curci, Vita; Dassisti, Michele; Josefa, Mula Bru; Manuel, Díaz Madroñero

2014-10-01

Supply chain model (SCM) are potentially capable to integrate different aspects in supporting decision making for enterprise management tasks. The aim of the paper is to propose an hybrid mathematical programming model for optimization of production requirements resources planning. The preliminary model was conceived bottom-up from a real industrial case analysed oriented to maximize cash flow. Despite the intense computational effort required to converge to a solution, optimisation done brought good result in solving the objective function.

Evaluation of hybrid inverse planning and optimization (HIPO) algorithm for optimization in real-time, high-dose-rate (HDR) brachytherapy for prostate.

PubMed

Pokharel, Shyam; Rana, Suresh; Blikenstaff, Joseph; Sadeghi, Amir; Prestidge, Bradley

2013-07-08

The purpose of this study is to investigate the effectiveness of the HIPO planning and optimization algorithm for real-time prostate HDR brachytherapy. This study consists of 20 patients who underwent ultrasound-based real-time HDR brachytherapy of the prostate using the treatment planning system called Oncentra Prostate (SWIFT version 3.0). The treatment plans for all patients were optimized using inverse dose-volume histogram-based optimization followed by graphical optimization (GRO) in real time. The GRO is manual manipulation of isodose lines slice by slice. The quality of the plan heavily depends on planner expertise and experience. The data for all patients were retrieved later, and treatment plans were created and optimized using HIPO algorithm with the same set of dose constraints, number of catheters, and set of contours as in the real-time optimization algorithm. The HIPO algorithm is a hybrid because it combines both stochastic and deterministic algorithms. The stochastic algorithm, called simulated annealing, searches the optimal catheter distributions for a given set of dose objectives. The deterministic algorithm, called dose-volume histogram-based optimization (DVHO), optimizes three-dimensional dose distribution quickly by moving straight downhill once it is in the advantageous region of the search space given by the stochastic algorithm. The PTV receiving 100% of the prescription dose (V100) was 97.56% and 95.38% with GRO and HIPO, respectively. The mean dose (D(mean)) and minimum dose to 10% volume (D10) for the urethra, rectum, and bladder were all statistically lower with HIPO compared to GRO using the student pair t-test at 5% significance level. HIPO can provide treatment plans with comparable target coverage to that of GRO with a reduction in dose to the critical structures.

Topology optimization under stochastic stiffness

NASA Astrophysics Data System (ADS)

Asadpoure, Alireza

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

Simulation Model for Scenario Optimization of the Ready-Mix Concrete Delivery Problem

NASA Astrophysics Data System (ADS)

Galić, Mario; Kraus, Ivan

2016-12-01

This paper introduces a discrete simulation model for solving routing and network material flow problems in construction projects. Before the description of the model a detailed literature review is provided. The model is verified using a case study of solving the ready-mix concrete network flow and routing problem in metropolitan area in Croatia. Within this study real-time input parameters were taken into account. Simulation model is structured in Enterprise Dynamics simulation software and Microsoft Excel linked with Google Maps. The model is dynamic, easily managed and adjustable, but also provides good estimation for minimization of costs and realization time in solving discrete routing and material network flow problems.

A test of the optimality approach to modelling canopy properties and CO2 uptake by natural vegetation.

PubMed

Schymanski, Stanislaus J; Roderick, Michael L; Sivapalan, Murugesu; Hutley, Lindsay B; Beringer, Jason

2007-12-01

Photosynthesis provides plants with their main building material, carbohydrates, and with the energy necessary to thrive and prosper in their environment. We expect, therefore, that natural vegetation would evolve optimally to maximize its net carbon profit (NCP), the difference between carbon acquired by photosynthesis and carbon spent on maintenance of the organs involved in its uptake. We modelled N(CP) for an optimal vegetation for a site in the wet-dry tropics of north Australia based on this hypothesis and on an ecophysiological gas exchange and photosynthesis model, and compared the modelled CO2 fluxes and canopy properties with observations from the site. The comparison gives insights into theoretical and real controls on gas exchange and canopy structure, and supports the optimality approach for the modelling of gas exchange of natural vegetation. The main advantage of the optimality approach we adopt is that no assumptions about the particular vegetation of a site are required, making it a very powerful tool for predicting vegetation response to long-term climate or land use change.

Ideal heat transfer conditions for tubular solar receivers with different design constraints

NASA Astrophysics Data System (ADS)

Kim, Jin-Soo; Potter, Daniel; Gardner, Wilson; Too, Yen Chean Soo; Padilla, Ricardo Vasquez

2017-06-01

The optimum heat transfer condition for a tubular type solar receiver was investigated for various receiver pipe size, heat transfer fluid, and design requirement and constraint(s). Heat transfer of a single plain receiver pipe exposed to concentrated solar energy was modelled along the flow path of the heat transfer fluid. Three different working fluids, molten salt, sodium, and supercritical carbon dioxide (sCO2) were considered in the case studies with different design conditions. The optimized ideal heat transfer condition was identified through fast iterative heat transfer calculations solving for all relevant radiation, conduction and convection heat transfers throughout the entire discretized tubular receiver. The ideal condition giving the best performance was obtained by finding the highest acceptable solar energy flux optimally distributed to meet different constraint(s), such as maximum allowable material temperature of receiver, maximum allowable film temperature of heat transfer fluid, and maximum allowable stress of receiver pipe material. The level of fluid side turbulence (represented by pressure drop in this study) was also optimized to give the highest net power production. As the outcome of the study gives information on the most ideal heat transfer condition, it can be used as a useful guideline for optimal design of a real receiver and solar field in a combined manner. The ideal heat transfer condition is especially important for high temperature tubular receivers (e.g. for supplying heat to high efficiency Brayton cycle turbines) where the system design and performance is tightly constrained by the receiver pipe material strength.

A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

PubMed

Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

2013-05-30

Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

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

DOE PAGES

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

2016-01-01

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

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

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

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok

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

Multi-wavelength dual polarisation lidar for monitoring precipitation process in the cloud seeding technique

NASA Astrophysics Data System (ADS)

Sudhakar, P.; Sheela, K. Anitha; Ramakrishna Rao, D.; Malladi, Satyanarayana

2016-05-01

In recent years weather modification activities are being pursued in many countries through cloud seeding techniques to facilitate the increased and timely precipitation from the clouds. In order to induce and accelerate the precipitation process clouds are artificially seeded with suitable materials like silver iodide, sodium chloride or other hygroscopic materials. The success of cloud seeding can be predicted with confidence if the precipitation process involving aerosol, the ice water balance, water vapor content and size of the seeding material in relation to aerosol in the cloud is monitored in real time and optimized. A project on the enhancement of rain fall through cloud seeding is being implemented jointly with Kerala State Electricity Board Ltd. Trivandrum, Kerala, India at the catchment areas of the reservoir of one of the Hydro electric projects. The dual polarization lidar is being used to monitor and measure the microphysical properties, the extinction coefficient, size distribution and related parameters of the clouds. The lidar makes use of the Mie, Rayleigh and Raman scattering techniques for the various measurement proposed. The measurements with the dual polarization lidar as above are being carried out in real time to obtain the various parameters during cloud seeding operations. In this paper we present the details of the multi-wavelength dual polarization lidar being used and the methodology to monitor the various cloud parameters involved in the precipitation process. The necessary retrieval algorithms for deriving the microphysical properties of clouds, aerosols characteristics and water vapor profiles are incorporated as a software package working under Lab-view for online and off line analysis. Details on the simulation studies and the theoretical model developed in this regard for the optimization of various parameters are discussed.

Stochastic Optimization for an Analytical Model of Saltwater Intrusion in Coastal Aquifers

PubMed Central

Stratis, Paris N.; Karatzas, George P.; Papadopoulou, Elena P.; Zakynthinaki, Maria S.; Saridakis, Yiannis G.

2016-01-01

The present study implements a stochastic optimization technique to optimally manage freshwater pumping from coastal aquifers. Our simulations utilize the well-known sharp interface model for saltwater intrusion in coastal aquifers together with its known analytical solution. The objective is to maximize the total volume of freshwater pumped by the wells from the aquifer while, at the same time, protecting the aquifer from saltwater intrusion. In the direction of dealing with this problem in real time, the ALOPEX stochastic optimization method is used, to optimize the pumping rates of the wells, coupled with a penalty-based strategy that keeps the saltwater front at a safe distance from the wells. Several numerical optimization results, that simulate a known real aquifer case, are presented. The results explore the computational performance of the chosen stochastic optimization method as well as its abilities to manage freshwater pumping in real aquifer environments. PMID:27689362

Optimized deformation behavior of a dielectric elastomer generator

NASA Astrophysics Data System (ADS)

Foerster, Florentine; Schlaak, Helmut F.

2014-03-01

Dielectric elastomer generators (DEGs) produce electrical energy by converting mechanical into electrical energy. Efficient operation requires an optimal deformation of the DEG during the energy harvesting cycle. However, the deformation resulting from an external load has to be applied to the DEG. The deformation behavior of the DEG is dependent on the type of the mechanical interconnection between the elastic DEG and a stiff support area. The maximization of the capacitance of the DEG in the deformed state leads to the maximum absolute energy gain. Therefore several configurations of mechanical interconnections between a single DEG module as well as multiple stacked DEG modules and stiff supports are investigated in order to find the optimal mechanical interconnection. The investigation is done with numerical simulations using the FEM software ANSYS. A DEG module consists of 50 active dielectric layers with a single layer thickness of 50 μm. The elastomer material is silicone (PDMS) while the compliant electrodes are made of graphite powder. In the simulation the real material parameters of the PDMS and the graphite electrodes are included to compare simulation results to experimental investigations in the future. The numerical simulations of the several configurations are carried out as coupled electro-mechanical simulation for the first step in an energy harvesting cycle with constant external load strain. The simulation results are discussed and an optimal mechanical interconnection between DEG modules and stiff supports is derived.

Multi-Objective Flight Control for Drag Minimization and Load Alleviation of High-Aspect Ratio Flexible Wing Aircraft

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Ting, Eric; Chaparro, Daniel; Drew, Michael; Swei, Sean

2017-01-01

As aircraft wings become much more flexible due to the use of light-weight composites material, adverse aerodynamics at off-design performance can result from changes in wing shapes due to aeroelastic deflections. Increased drag, hence increased fuel burn, is a potential consequence. Without means for aeroelastic compensation, the benefit of weight reduction from the use of light-weight material could be offset by less optimal aerodynamic performance at off-design flight conditions. Performance Adaptive Aeroelastic Wing (PAAW) technology can potentially address these technical challenges for future flexible wing transports. PAAW technology leverages multi-disciplinary solutions to maximize the aerodynamic performance payoff of future adaptive wing design, while addressing simultaneously operational constraints that can prevent the optimal aerodynamic performance from being realized. These operational constraints include reduced flutter margins, increased airframe responses to gust and maneuver loads, pilot handling qualities, and ride qualities. All of these constraints while seeking the optimal aerodynamic performance present themselves as a multi-objective flight control problem. The paper presents a multi-objective flight control approach based on a drag-cognizant optimal control method. A concept of virtual control, which was previously introduced, is implemented to address the pair-wise flap motion constraints imposed by the elastomer material. This method is shown to be able to satisfy the constraints. Real-time drag minimization control is considered to be an important consideration for PAAW technology. Drag minimization control has many technical challenges such as sensing and control. An initial outline of a real-time drag minimization control has already been developed and will be further investigated in the future. A simulation study of a multi-objective flight control for a flight path angle command with aeroelastic mode suppression and drag minimization demonstrates the effectiveness of the proposed solution. In-flight structural loads are also an important consideration. As wing flexibility increases, maneuver load and gust load responses can be significant and therefore can pose safety and flight control concerns. In this paper, we will extend the multi-objective flight control framework to include load alleviation control. The study will focus initially on maneuver load minimization control, and then subsequently will address gust load alleviation control in future work.

The design of a PC-based real-time system for monitoring Methane and Oxygen concentration in biogas production

NASA Astrophysics Data System (ADS)

Yantidewi, M.; Muntini, M. S.; Deta, U. A.; Lestari, N. A.

2018-03-01

Limited fossil fuels nowadays trigger the development of alternative energy, one of which is biogas. Biogas is one type of bioenergy in the form of fermented gases of organic materials such as animal waste. The components of gases present in biogas and affect the biogas production are various, such as methane and oxygen. The biogas utilization will be more optimal if both gases concentration (in this case is methane and oxygen concentration) can be monitored. Therefore, this research focused on designing the monitoring system of methane and oxygen concentration in biogas production in real-time. The results showed that the instrument system was capable of monitoring and recording the data of gases (methane and oxygen) concentration in biogas production in every second.

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy† †Electronic supplementary information (ESI) available: Details about the methodology, LabView scripts, experimental set-ups, additional spectra and self-optimization can be found in the SI. See DOI: 10.1039/c4sc03075c Click here for additional data file.

PubMed Central

Sans, Victor; Porwol, Luzian; Dragone, Vincenza

2015-01-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19F, 13C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations. PMID:29560211

Comparison of real-time SYBR green dengue assay with real-time taqman RT-PCR dengue assay and the conventional nested PCR for diagnosis of primary and secondary dengue infection

PubMed Central

Paudel, Damodar; Jarman, Richard; Limkittikul, Kriengsak; Klungthong, Chonticha; Chamnanchanunt, Supat; Nisalak, Ananda; Gibbons, Robert; Chokejindachai, Watcharee

2011-01-01

Background: Dengue fever and dengue hemorrhagic fever are caused by dengue virus. Dengue infection remains a burning problem of many countries. To diagnose acute dengue in the early phase we improve the low cost, rapid SYBR green real time assay and compared the sensitivity and specificity with real time Taqman® assay and conventional nested PCR assay. Aims: To develop low cost, rapid and reliable real time SYBR green diagnostic dengue assay and compare with Taqman real-time assay and conventional nested PCR (modified Lanciotti). Materials and Methods: Eight cultured virus strains were diluted in tenth dilution down to undetectable level by the PCR to optimize the primer, temperature (annealing, and extension and to detect the limit of detection of the assay. Hundred and ninety three ELISA and PCR proved dengue clinical samples were tested with real time SYBR® Green assay, real time Taqman® assay to compare the sensitivity and specificity. Results: Sensitivity and specificity of real time SYBR® green dengue assay (84% and 66%, respectively) was almost comparable to those (81% and 74%) of Taqman real time PCR dengue assay. Real time SYBR® green RT-PCR was equally sensitive in primary and secondary infection while real time Taqman was less sensitive in the secondary infection. Sensitivity of real time Taqman on DENV3 (87%) was equal to SYBR green real time PCR dengue assay. Conclusion: We developed low cost rapid diagnostic SYBR green dengue assay. Further study is needed to make duplex primer assay for the serotyping of dengue virus. PMID:22363089

Intrinsic hierarchical structural imperfections in a natural ceramic of bivalve shell with distinctly graded properties

PubMed Central

Jiao, Da; Liu, Zengqian; Zhang, Zhenjun; Zhang, Zhefeng

2015-01-01

Despite the extensive investigation on the structure of natural biological materials, insufficient attention has been paid to the structural imperfections by which the mechanical properties of synthetic materials are dominated. In this study, the structure of bivalve Saxidomus purpuratus shell has been systematically characterized quantitatively on multiple length scales from millimeter to sub-nanometer. It is revealed that hierarchical imperfections are intrinsically involved in the crossed-lamellar structure of the shell despite its periodically packed platelets. In particular, various favorable characters which are always pursued in synthetic materials, e.g. nanotwins and low-angle misorientations, have been incorporated herein. The possible contributions of these imperfections to mechanical properties are further discussed. It is suggested that the imperfections may serve as structural adaptations, rather than detrimental defects in the real sense, to help improve the mechanical properties of natural biological materials. This study may aid in understanding the optimizing strategies of structure and properties designed by nature, and accordingly, provide inspiration for the design of synthetic materials. PMID:26198844

Intrinsic hierarchical structural imperfections in a natural ceramic of bivalve shell with distinctly graded properties.

PubMed

Jiao, Da; Liu, Zengqian; Zhang, Zhenjun; Zhang, Zhefeng

2015-07-22

Despite the extensive investigation on the structure of natural biological materials, insufficient attention has been paid to the structural imperfections by which the mechanical properties of synthetic materials are dominated. In this study, the structure of bivalve Saxidomus purpuratus shell has been systematically characterized quantitatively on multiple length scales from millimeter to sub-nanometer. It is revealed that hierarchical imperfections are intrinsically involved in the crossed-lamellar structure of the shell despite its periodically packed platelets. In particular, various favorable characters which are always pursued in synthetic materials, e.g. nanotwins and low-angle misorientations, have been incorporated herein. The possible contributions of these imperfections to mechanical properties are further discussed. It is suggested that the imperfections may serve as structural adaptations, rather than detrimental defects in the real sense, to help improve the mechanical properties of natural biological materials. This study may aid in understanding the optimizing strategies of structure and properties designed by nature, and accordingly, provide inspiration for the design of synthetic materials.

Phospholipid-templated silica nanocapsules as efficient polyenzymatic biocatalysts.

PubMed

Phuoc, Lai Truong; Laveille, Paco; Chamouleau, Françoise; Renard, Gilbert; Drone, Jullien; Coq, Bernard; Fajula, François; Galarneau, Anne

2010-09-28

Solid polyenzymatic biocatalysts have been designed by combining two immobilized enzymes, the first one allowing the in situ generation of H(2)O(2) from air and the second one performing an oxidation reaction. The in situ H(2)O(2) generation system is based on the reaction of glucose with air using a glucose oxidase (GOx). The optimization of the encapsulation of GOx into phospholipids-templated silica capsules (NPS) was performed. A bienzymatic system made of GOx and horseradish peroxidase (HRP) was studied. Optimal conditions for the activity of the GOx/HRP bienzymatic system have been determined for both homogeneous and heterogeneous conditions. The encapsulation in NPS materials increases the stability of both enzymes. The performance of the encapsulated bienzymatic GOx/HRP system in the model reaction of 4-aminoantipyridine with phenol is similar when the enzymes are immobilized separately in two NPS or coencapsulated in the same NPS. An excess of peroxidase compared to GOx ([HRP]/[GOx] = 5-10) is necessary to obtain the optimal activity. To show the potentiality of bienzymatic systems in real applications, HRP has been replaced by hemoglobin, which is known for its ability to oxidize polycyclic aromatic hydrocarbons (PAH) pollutants through a pseudoperoxidase pathway. A larger excess of Hb compared to GOx ([Hb]/[GOx] = 1000) was necessary to obtain the maximum PAH removal, as Hb is not a real peroxidase as HRP but a hemoprotein with some pseudoperoxidase activity. In opposite to real enzymes, the immobilization of Hb by adsorption in mesoporous silica is preferable as its encapsulation. Therefore, the bienzymatic system made of GOx encapsulated in NPS and Hb adsorbed in mesoporous silica has been used for the removal of 11 PAH from water. This heterogeneous bienzymatic system allows 64% of PAH removal from water using simple air as oxidant.

Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process

PubMed Central

Expósito-Rodríguez, Marino; Borges, Andrés A; Borges-Pérez, Andrés; Pérez, José A

2008-01-01

Background The elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR. Results In this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (CAC), SGN-U321250 (TIP41), SGN-U346908 ("Expressed") and SGN-U316474 (SAND) genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process. Conclusion This work constitutes the first effort for the selection of optimal endogenous controls for quantitative real-time RT-PCR studies of gene expression during tomato development process. From our study a tool-kit of control genes emerges that outperform the traditional genes in terms of expression stability. PMID:19102748

Comparison of Thermal Detector Arrays for Off-Axis THz Holography and Real-Time THz Imaging

PubMed Central

Hack, Erwin; Valzania, Lorenzo; Gäumann, Gregory; Shalaby, Mostafa; Hauri, Christoph P.; Zolliker, Peter

2016-01-01

In terahertz (THz) materials science, imaging by scanning prevails when low power THz sources are used. However, the application of array detectors operating with high power THz sources is increasingly reported. We compare the imaging properties of four different array detectors that are able to record THz radiation directly. Two micro-bolometer arrays are designed for infrared imaging in the 8–14 μm wavelength range, but are based on different absorber materials (i) vanadium oxide; (ii) amorphous silicon; (iii) a micro-bolometer array optimized for recording THz radiation based on silicon nitride; and (iv) a pyroelectric array detector for THz beam profile measurements. THz wavelengths of 96.5 μm, 118.8 μm, and 393.6 μm from a powerful far infrared laser were used to assess the technical performance in terms of signal to noise ratio, detector response and detectivity. The usefulness of the detectors for beam profiling and digital holography is assessed. Finally, the potential and limitation for real-time digital holography are discussed. PMID:26861341

Comparison of Thermal Detector Arrays for Off-Axis THz Holography and Real-Time THz Imaging.

PubMed

Hack, Erwin; Valzania, Lorenzo; Gäumann, Gregory; Shalaby, Mostafa; Hauri, Christoph P; Zolliker, Peter

2016-02-06

In terahertz (THz) materials science, imaging by scanning prevails when low power THz sources are used. However, the application of array detectors operating with high power THz sources is increasingly reported. We compare the imaging properties of four different array detectors that are able to record THz radiation directly. Two micro-bolometer arrays are designed for infrared imaging in the 8-14 μm wavelength range, but are based on different absorber materials (i) vanadium oxide; (ii) amorphous silicon; (iii) a micro-bolometer array optimized for recording THz radiation based on silicon nitride; and (iv) a pyroelectric array detector for THz beam profile measurements. THz wavelengths of 96.5 μm, 118.8 μm, and 393.6 μm from a powerful far infrared laser were used to assess the technical performance in terms of signal to noise ratio, detector response and detectivity. The usefulness of the detectors for beam profiling and digital holography is assessed. Finally, the potential and limitation for real-time digital holography are discussed.

Rapid quantification and sex determination of forensic evidence materials.

PubMed

Andréasson, Hanna; Allen, Marie

2003-11-01

DNA quantification of forensic evidence is very valuable for an optimal use of the available biological material. Moreover, sex determination is of great importance as additional information in criminal investigations as well as in identification of missing persons, no suspect cases, and ancient DNA studies. While routine forensic DNA analysis based on short tandem repeat markers includes a marker for sex determination, analysis of samples containing scarce amounts of DNA is often based on mitochondrial DNA, and sex determination is not performed. In order to allow quantification and simultaneous sex determination on minute amounts of DNA, an assay based on real-time PCR analysis of a marker within the human amelogenin gene has been developed. The sex determination is based on melting curve analysis, while an externally standardized kinetic analysis allows quantification of the nuclear DNA copy number in the sample. This real-time DNA quantification assay has proven to be highly sensitive, enabling quantification of single DNA copies. Although certain limitations were apparent, the system is a rapid, cost-effective, and flexible assay for analysis of forensic casework samples.

Designing optimal nanofocusing with a gradient hyperlens

NASA Astrophysics Data System (ADS)

Shen, Lian; Prokopeva, Ludmila J.; Chen, Hongsheng; Kildishev, Alexander V.

2017-11-01

We report the design of a high-throughput gradient hyperbolic lenslet built with real-life materials and capable of focusing a beam into a deep sub-wavelength spot of λ/23. This efficient design is achieved through high-order transformation optics and circular effective-medium theory (CEMT), which are used to engineer the radially varying anisotropic artificial material based on the thin alternating cylindrical metal and dielectric layers. The radial gradient of the effective anisotropic optical constants allows for matching the impedances at the input and output interfaces, drastically improving the throughput of the lenslet. However, it is the use of the zeroth-order CEMT that enables the practical realization of a gradient hyperlens with realistic materials. To illustrate the importance of using the CEMT versus the conventional planar effective-medium theory (PEMT) for cylindrical anisotropic systems, such as our hyperlens, both the CEMT and PEMT are adopted to design gradient hyperlenses with the same materials and order of elemental layers. The CEMT- and PEMT-based designs show similar performance if the number of metal-dielectric binary layers is sufficiently large (9+ pairs) and if the layers are sufficiently thin. However, for the manufacturable lenses with realistic numbers of layers (e.g. five pairs) and thicknesses, the performance of the CEMT design continues to be practical, whereas the PEMT-based design stops working altogether. The accurate design of transformation optics-based layered cylindrical devices enabled by CEMT allow for a new class of robustly manufacturable nanophotonic systems, even with relatively thick layers of real-life materials.

Real-Time Optimization for use in a Control Allocation System to Recover from Pilot Induced Oscillations

NASA Technical Reports Server (NTRS)

Leonard, Michael W.

2013-01-01

Integration of the Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) System into the control system of a Short Takeoff and Landing Mobility Concept Vehicle simulation presents a challenge because the CAPIO formulation requires that constrained optimization problems be solved at the controller operating frequency. We present a solution that utilizes a modified version of the well-known L-BFGS-B solver. Despite the iterative nature of the solver, the method is seen to converge in real time with sufficient reliability to support three weeks of piloted runs at the NASA Ames Vertical Motion Simulator (VMS) facility. The results of the optimization are seen to be excellent in the vast majority of real-time frames. Deficiencies in the quality of the results in some frames are shown to be improvable with simple termination criteria adjustments, though more real-time optimization iterations would be required.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

Sequence Optimized Real-Time RT-PCR Assay for Detection of Crimean-Congo Hemorrhagic Fever Virus

DTIC Science & Technology

2017-03-21

19-23]. Real-56 time reverse-transcription PCR remains the gold standard for quantitative , sensitive, and specific 57 detection of CCHFV; however...five-fold in two different series , and samples were run by real- time RT-PCR 116 in triplicate. The preliminary LOD was the lowest RNA dilution where...1 Sequence optimized real- time RT-PCR assay for detection of Crimean-Congo hemorrhagic fever 1 virus 2 3 JW Koehler1, KL Delp1, AT Hall1, SP

Sparse Covariance Matrix Estimation With Eigenvalue Constraints

PubMed Central

LIU, Han; WANG, Lie; ZHAO, Tuo

2014-01-01

We propose a new approach for estimating high-dimensional, positive-definite covariance matrices. Our method extends the generalized thresholding operator by adding an explicit eigenvalue constraint. The estimated covariance matrix simultaneously achieves sparsity and positive definiteness. The estimator is rate optimal in the minimax sense and we develop an efficient iterative soft-thresholding and projection algorithm based on the alternating direction method of multipliers. Empirically, we conduct thorough numerical experiments on simulated datasets as well as real data examples to illustrate the usefulness of our method. Supplementary materials for the article are available online. PMID:25620866

“Elegant Tool” Delivers Genome-Level Science for Electrolytes

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

Keith Arterburn

Now, a ‘disruptive, virtual scientific simulation tool’ delivers a new, genome-level investigation for electrolytes to develop better, more efficient batteries. Dr. Kevin Gering, an Idaho National Laboratory researcher, has developed the Advanced Electrolyte Model (AEM), a copyrighted molecular-based simulation tool that has been scientifically proven and validated using at least a dozen ‘real-world’ physical metrics. Nominated for the 2014 international R&D 100 Award, AEM revolutionizes electrolyte materials selection, optimizing combinations and key design elements to make battery design and experimentation quick, accurate and responsive to specific needs.

Development of the laboratory prototype "CavyPool" for assessing treatments and materials for swimming pools.

PubMed

Valeriani, F; Gianfranceschi, G; Vitali, M; Protano, C; Romano Spica, V

2017-01-01

Hygiene and surveillance in swimming pools are established by WHO Guidelines and national laws. Progress in water management and pool construction is revolutionizing the field, introducing new materials, systems, disinfection procedures or monitoring markers. Innovation advances challenge the upgrading of safety and quality in pools and the appropriate implementation of guidelines. In order to provide a device for laboratory test, a prototype was realized and applied to study and compare swimming pool materials and treatments. A pool scale-model was engineered and evaluated by computational fluid dynamics algorithms. An automated real time monitoring assured steady state. Critical control points along the water circuit were made accessible to allow the placing of different biocides or water sampling. Simulations were safely performed in a standard hood. Materials for pool surfaces and pipelines were evaluated for biofilm formation under different disinfection conditions. Adherent microorganisms were assayed by mfDNA analysis using real time PCR. The prototype reached the steady state within 5-25 hours under different conditions, showing chemical, physical and fluid-dynamic stability. A method was optimized for testing materials showing their different response to biofilm induction. Several innovative PVC samples displayed highest resistance to bacterial adhesion. A device and method was developed for testing swimming pool hygienic parameters in laboratory. It allowed to test materials for pools hygiene and maintenance, including biofilm formation. It can be applied to simulate contaminations under different water treatments or disinfection strategies. It may support technical decisions and help policymakers in acquiring evidences for comparing or validating innovative solutions.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

NASA Astrophysics Data System (ADS)

Zheng, Qiangang; Zhang, Haibo; Miao, Lizhen; Sun, Fengyong

2017-11-01

A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Optimization of coronary attenuation in coronary computed tomography angiography using diluted contrast material.

PubMed

Kawaguchi, Naoto; Kurata, Akira; Kido, Teruhito; Nishiyama, Yoshiko; Kido, Tomoyuki; Miyagawa, Masao; Ogimoto, Akiyoshi; Mochizuki, Teruhito

2014-01-01

The purpose of this study was to evaluate a personalized protocol with diluted contrast material (CM) for coronary computed tomography angiography (CTA). One hundred patients with suspected coronary artery disease underwent retrospective electrocardiogram-gated coronary CTA on a 256-slice multidetector-row CT scanner. In the diluted CM protocol (n=50), the optimal scan timing and CM dilution rate were determined by the timing bolus scan, with 20% CM dilution (5ml/s during 10s) being considered suitable to achieve the target arterial attenuation of 350 Hounsfield units (HU). In the body weight (BW)-adjusted protocol (n=50, 222mg iodine/kg), only the optimal scan timing was determined by the timing bolus scan. The injection rate and volume in the timing bolus scan and real scan were identical between the 2 protocols. We compared the means and variations in coronary attenuation between the 2 protocols. Coronary attenuation (mean±SD) in the diluted CM and BW-adjusted protocols was 346.1±23.9 HU and 298.8±45.2 HU, respectively. The diluted CM protocol provided significantly higher coronary attenuation and lower variance than did the BW-adjusted protocol (P<0.05, in each). The diluted CM protocol facilitates more uniform attenuation on coronary CTA in comparison with the BW-adjusted protocol.  

Self-consistent adjoint analysis for topology optimization of electromagnetic waves

NASA Astrophysics Data System (ADS)

Deng, Yongbo; Korvink, Jan G.

2018-05-01

In topology optimization of electromagnetic waves, the Gâteaux differentiability of the conjugate operator to the complex field variable results in the complexity of the adjoint sensitivity, which evolves the original real-valued design variable to be complex during the iterative solution procedure. Therefore, the self-inconsistency of the adjoint sensitivity is presented. To enforce the self-consistency, the real part operator has been used to extract the real part of the sensitivity to keep the real-value property of the design variable. However, this enforced self-consistency can cause the problem that the derived structural topology has unreasonable dependence on the phase of the incident wave. To solve this problem, this article focuses on the self-consistent adjoint analysis of the topology optimization problems for electromagnetic waves. This self-consistent adjoint analysis is implemented by splitting the complex variables of the wave equations into the corresponding real parts and imaginary parts, sequentially substituting the split complex variables into the wave equations with deriving the coupled equations equivalent to the original wave equations, where the infinite free space is truncated by the perfectly matched layers. Then, the topology optimization problems of electromagnetic waves are transformed into the forms defined on real functional spaces instead of complex functional spaces; the adjoint analysis of the topology optimization problems is implemented on real functional spaces with removing the variational of the conjugate operator; the self-consistent adjoint sensitivity is derived, and the phase-dependence problem is avoided for the derived structural topology. Several numerical examples are implemented to demonstrate the robustness of the derived self-consistent adjoint analysis.

Optimizing product life cycle processes in design phase

NASA Astrophysics Data System (ADS)

Faneye, Ola. B.; Anderl, Reiner

2002-02-01

Life cycle concepts do not only serve as basis in assisting product developers understand the dependencies between products and their life cycles, they also help in identifying potential opportunities for improvement in products. Common traditional concepts focus mainly on energy and material flow across life phases, necessitating the availability of metrics derived from a reference product. Knowledge of life cycle processes won from an existing product is directly reused in its redesign. Depending on sales volume nevertheless, the environmental impact before product optimization can be substantial. With modern information technologies today, computer-aided life cycle methodologies can be applied well before product use. On the basis of a virtual prototype, life cycle processes are analyzed and optimized, using simulation techniques. This preventive approach does not only help in minimizing (or even eliminating) environmental burdens caused by product, costs incurred due to changes in real product can also be avoided. The paper highlights the relationship between product and life cycle and presents a computer-based methodology for optimizing the product life cycle during design, as presented by SFB 392: Design for Environment - Methods and Tools at Technical University, Darmstadt.

[Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology].

PubMed

Wang, Hai-Xia; Suo, Tong-Chuan; Yu, He-Shui; Li, Zheng

2016-10-01

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes. Copyright© by the Chinese Pharmaceutical Association.

Reality check: the role of realism in stress reduction using media technology.

PubMed

de Kort, Y A W; Ijsselsteijn, W A

2006-04-01

There is a growing interest in the use of virtual and other mediated environments for therapeutic purposes. However, in the domain of restorative environments, virtual reality (VR) technology has hardly been used. Here the tendency has been to use mediated real environments, striving for maximum visual realism. This use of photographic material is mainly based on research in aesthetics judgments that has demonstrated the validity of this type of simulations as representations of real environments. Thus, restoration therapy is developing under the untested assumption that photorealistic images have the optimal level of realism, while in therapeutic applications 'experiential realism' seems to be the key rather than visual realism. The present paper discusses this contrast and briefly describes data of three studies aimed at exploring the importance and meaning of realism in the context of restorative environments.

Optimization of a superconducting linear levitation system using a soft ferromagnet

NASA Astrophysics Data System (ADS)

Agramunt-Puig, Sebastia; Del-Valle, Nuria; Navau, Carles; Sanchez, Alvaro

2013-04-01

The use of guideways that combine permanent magnets and soft ferromagnetic materials is a common practice in magnetic levitation transport systems (maglevs) with bulk high-temperature superconductors. Theoretical tools to simulate in a realistic way both the behavior of all elements (permanent magnets, soft ferromagnet and superconductor) and their mutual effects are helpful to optimize the designs of real systems. Here we present a systematic study of the levitation of a maglev with translational symmetry consisting of a superconducting bar and a guideway with two identic permanent magnets and a soft ferromagnetic material between them. The system is simulated with a numerical model based on the energy minimization method that allows to analyze the mutual interaction of the superconductor, assumed to be in the critical state, and a soft ferromagnet with infinite susceptibility. Results indicate that introducing a soft ferromagnet within the permanent magnets not only increases the levitation force but also improves the stability. Besides, an estimation of the relative sizes and shapes of the soft ferromagnet, permanent magnets and the superconductor in order to obtain large levitation force with full stability is provided.

Machine Learning to Discover and Optimize Materials

NASA Astrophysics Data System (ADS)

Rosenbrock, Conrad Waldhar

For centuries, scientists have dreamed of creating materials by design. Rather than discovery by accident, bespoke materials could be tailored to fulfill specific technological needs. Quantum theory and computational methods are essentially equal to the task, and computational power is the new bottleneck. Machine learning has the potential to solve that problem by approximating material behavior at multiple length scales. A full end-to-end solution must allow us to approximate the quantum mechanics, microstructure and engineering tasks well enough to be predictive in the real world. In this dissertation, I present algorithms and methodology to address some of these problems at various length scales. In the realm of enumeration, systems with many degrees of freedom such as high-entropy alloys may contain prohibitively many unique possibilities so that enumerating all of them would exhaust available compute memory. One possible way to address this problem is to know in advance how many possibilities there are so that the user can reduce their search space by restricting the occupation of certain lattice sites. Although tools to calculate this number were available, none performed well for very large systems and none could easily be integrated into low-level languages for use in existing scientific codes. I present an algorithm to solve these problems. Testing the robustness of machine-learned models is an essential component in any materials discovery or optimization application. While it is customary to perform a small number of system-specific tests to validate an approach, this may be insufficient in many cases. In particular, for Cluster Expansion models, the expansion may not converge quickly enough to be useful and reliable. Although the method has been used for decades, a rigorous investigation across many systems to determine when CE "breaks" was still lacking. This dissertation includes this investigation along with heuristics that use only a small training database to predict whether a model is worth pursuing in detail. To be useful, computational materials discovery must lead to experimental validation. However, experiments are difficult due to sample purity, environmental effects and a host of other considerations. In many cases, it is difficult to connect theory to experiment because computation is deterministic. By combining advanced group theory with machine learning, we created a new tool that bridges the gap between experiment and theory so that experimental and computed phase diagrams can be harmonized. Grain boundaries in real materials control many important material properties such as corrosion, thermal conductivity, and creep. Because of their high dimensionality, learning the underlying physics to optimizing grain boundaries is extremely complex. By leveraging a mathematically rigorous representation for local atomic environments, machine learning becomes a powerful tool to approximate properties for grain boundaries. But it also goes beyond predicting properties by highlighting those atomic environments that are most important for influencing the boundary properties. This provides an immense dimensionality reduction that empowers grain boundary scientists to know where to look for deeper physical insights.

Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms.

PubMed

Xu, Dongpo; Xia, Yili; Mandic, Danilo P

2016-02-01

The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks.

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Is optimism real?

PubMed

Simmons, Joseph P; Massey, Cade

2012-11-01

Is optimism real, or are optimistic forecasts just cheap talk? To help answer this question, we investigated whether optimistic predictions persist in the face of large incentives to be accurate. We asked National Football League football fans to predict the winner of a single game. Roughly half (the partisans) predicted a game involving their favorite team, and the other half (the neutrals) predicted a game involving 2 teams they were neutral about. Participants were promised either a small incentive ($5) or a large incentive ($50) for correctly predicting the game's winner. Optimism emerged even when incentives were large, as partisans were much more likely than neutrals to predict partisans' favorite teams to win. Strong optimism also emerged among participants whose responses to follow-up questions strongly suggested that they believed the predictions they made. This research supports the claim that optimism is real. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Venkateswara Rao, B.; Kumar, G. V. Nagesh; Chowdary, D. Deepak; Bharathi, M. Aruna; Patra, Stutee

2017-07-01

This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as objective function. Static VAR Compensator (SVC) is one of the best shunt connected device in the Flexible Alternating Current Transmission System (FACTS) family. It has capable of controlling the voltage magnitudes of buses by injecting the reactive power to system. In this paper SVC is integrated in CSA based Optimal Power Flow to optimize the real power generation cost. SVC is used to improve the voltage profile of the system. CSA gives better results as compared to genetic algorithm (GA) in both without and with SVC conditions.

Use of natural clays as sorbent materials for rare earth ions: Materials characterization and set up of the operative parameters.

PubMed

Iannicelli-Zubiani, Elena Maria; Cristiani, Cinzia; Dotelli, Giovanni; Gallo Stampino, Paola; Pelosato, Renato; Mesto, Ernesto; Schingaro, Emanuela; Lacalamita, Maria

2015-12-01

Two mineral clays of the montmorillonite group were tested as sorbents for the removal of Rare Earths (REs) from liquid solutions. Lanthanum and neodymium model solutions were used to perform uptake tests in order to: (a) verify the clays sorption capability, (b) investigate the sorption mechanisms and (c) optimize the experimental parameters, such as contact time and pH. The desorption was also studied, in order to evaluate the feasibility of REs recovery from waters. The adsorption-desorption procedure with the optimized parameters was also tested on a leaching solution obtained by dissolution of a dismantled NdFeB magnet of a hard-disk. The clays were fully characterized after REs adsorption and desorption by means of X-ray powder diffraction (XRPD) and X-ray photoelectron spectroscopy (XPS); the liquid phase was characterized via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) analyses. The experimental results show that both clays are able to capture and release La and Nd ions, with an ion exchange mechanism. The best total efficiency (capture ≈ 50%, release ≈ 70%) is obtained when the uptake and release processes are performed at pH=5 and pH=1 respectively; in real leached scrap solutions, the uptake is around 40% but release efficiency is strongly decreased passing from a mono-ion system to a real system (from 80% to 5%). Furthermore, a strong matrix effect is found, with the matrix largely affecting both the uptake and the release of neodymium. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

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

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

DOE PAGES

Liu, Guodong; Xu, Yan; Tomsovic, Kevin

2016-01-01

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total costmore » of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.« less

Real Time Optimal Control of Supercapacitor Operation for Frequency Response

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

Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish

2016-07-01

Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance tomore » the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.« less

Designing, programming, and optimizing a (small) quantum computer

NASA Astrophysics Data System (ADS)

Svore, Krysta

In 1982, Richard Feynman proposed to use a computer founded on the laws of quantum physics to simulate physical systems. In the more than thirty years since, quantum computers have shown promise to solve problems in number theory, chemistry, and materials science that would otherwise take longer than the lifetime of the universe to solve on an exascale classical machine. The practical realization of a quantum computer requires understanding and manipulating subtle quantum states while experimentally controlling quantum interference. It also requires an end-to-end software architecture for programming, optimizing, and implementing a quantum algorithm on the quantum device hardware. In this talk, we will introduce recent advances in connecting abstract theory to present-day real-world applications through software. We will highlight recent advancement of quantum algorithms and the challenges in ultimately performing a scalable solution on a quantum device.

MUSIC electromagnetic imaging with enhanced resolution for small inclusions

NASA Astrophysics Data System (ADS)

Chen, Xudong; Zhong, Yu

2009-01-01

This paper investigates the influence of the test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC does not apply.

A new MUSIC electromagnetic imaging method with enhanced resolution for small inclusions

NASA Astrophysics Data System (ADS)

Zhong, Yu; Chen, Xudong

2008-11-01

This paper investigates the influence of test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC doesn't apply.

Image analysis of multiple moving wood pieces in real time

NASA Astrophysics Data System (ADS)

Wang, Weixing

2006-02-01

This paper presents algorithms for image processing and image analysis of wood piece materials. The algorithms were designed for auto-detection of wood piece materials on a moving conveyor belt or a truck. When wood objects on moving, the hard task is to trace the contours of the objects in n optimal way. To make the algorithms work efficiently in the plant, a flexible online system was designed and developed, which mainly consists of image acquisition, image processing, object delineation and analysis. A number of newly-developed algorithms can delineate wood objects with high accuracy and high speed, and in the wood piece analysis part, each wood piece can be characterized by a number of visual parameters which can also be used for constructing experimental models directly in the system.

Rapid near-optimal aerospace plane trajectory generation and guidance

NASA Technical Reports Server (NTRS)

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

1991-01-01

Effort was directed toward the problems of the real time trajectory optimization and guidance law development for the National Aerospace Plane (NASP) applications. In particular, singular perturbation methods were used to develop guidance algorithms suitable for onboard, real time implementation. The progress made in this research effort is reported.

Is Optimism Real?

ERIC Educational Resources Information Center

Simmons, Joseph P.; Massey, Cade

2012-01-01

Is optimism real, or are optimistic forecasts just cheap talk? To help answer this question, we investigated whether optimistic predictions persist in the face of large incentives to be accurate. We asked National Football League football fans to predict the winner of a single game. Roughly half (the partisans) predicted a game involving their…

Combining density functional theory (DFT) and pair distribution function (PDF) analysis to solve the structure of metastable materials: the case of metakaolin.

PubMed

White, Claire E; Provis, John L; Proffen, Thomas; Riley, Daniel P; van Deventer, Jannie S J

2010-04-07

Understanding the atomic structure of complex metastable (including glassy) materials is of great importance in research and industry, however, such materials resist solution by most standard techniques. Here, a novel technique combining thermodynamics and local structure is presented to solve the structure of the metastable aluminosilicate material metakaolin (calcined kaolinite) without the use of chemical constraints. The structure is elucidated by iterating between least-squares real-space refinement using neutron pair distribution function data, and geometry optimisation using density functional modelling. The resulting structural representation is both energetically feasible and in excellent agreement with experimental data. This accurate structural representation of metakaolin provides new insight into the local environment of the aluminium atoms, with evidence of the existence of tri-coordinated aluminium. By the availability of this detailed chemically feasible atomic description, without the need to artificially impose constraints during the refinement process, there exists the opportunity to tailor chemical and mechanical processes involving metakaolin and other complex metastable materials at the atomic level to obtain optimal performance at the macro-scale.

Z2Pack: Numerical implementation of hybrid Wannier centers for identifying topological materials

NASA Astrophysics Data System (ADS)

Gresch, Dominik; Autès, Gabriel; Yazyev, Oleg V.; Troyer, Matthias; Vanderbilt, David; Bernevig, B. Andrei; Soluyanov, Alexey A.

2017-02-01

The intense theoretical and experimental interest in topological insulators and semimetals has established band structure topology as a fundamental material property. Consequently, identifying band topologies has become an important, but often challenging, problem, with no exhaustive solution at the present time. In this work we compile a series of techniques, some previously known, that allow for a solution to this problem for a large set of the possible band topologies. The method is based on tracking hybrid Wannier charge centers computed for relevant Bloch states, and it works at all levels of materials modeling: continuous k .p models, tight-binding models, and ab initio calculations. We apply the method to compute and identify Chern, Z2, and crystalline topological insulators, as well as topological semimetal phases, using real material examples. Moreover, we provide a numerical implementation of this technique (the Z2Pack software package) that is ideally suited for high-throughput screening of materials databases for compounds with nontrivial topologies. We expect that our work will allow researchers to (a) identify topological materials optimal for experimental probes, (b) classify existing compounds, and (c) reveal materials that host novel, not yet described, topological states.

Can Subjects be Guided to Optimal Decisions The Use of a Real-Time Training Intervention Model

DTIC Science & Technology

2016-06-01

execution of the task and may then be analyzed to determine if there is correlation between designated factors (scores, proportion of time in each...state with their decision performance in real time could allow training systems to be designed to tailor training to the individual decision maker...release; distribution is unlimited CAN SUBJECTS BE GUIDED TO OPTIMAL DECISIONS? THE USE OF A REAL- TIME TRAINING INTERVENTION MODEL by Travis D

A real-time and closed-loop control algorithm for cascaded multilevel inverter based on artificial neural network.

PubMed

Wang, Libing; Mao, Chengxiong; Wang, Dan; Lu, Jiming; Zhang, Junfeng; Chen, Xun

2014-01-01

In order to control the cascaded H-bridges (CHB) converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN) for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC) algorithm is employed to minimize the total harmonic distortion (THD) and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC) sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current's THD (<5%) when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

Development of a qualitative real-time PCR method to detect 19 targets for identification of genetically modified organisms.

PubMed

Peng, Cheng; Wang, Pengfei; Xu, Xiaoli; Wang, Xiaofu; Wei, Wei; Chen, Xiaoyun; Xu, Junfeng

2016-01-01

As the amount of commercially available genetically modified organisms (GMOs) grows recent years, the diversity of target sequences for molecular detection techniques are eagerly needed. Considered as the gold standard for GMO analysis, the real-time PCR technology was optimized to produce a high-throughput GMO screening method. With this method we can detect 19 transgenic targets. The specificity of the assays was demonstrated to be 100 % by the specific amplification of DNA derived from reference material from 20 genetically modified crops and 4 non modified crops. Furthermore, most assays showed a very sensitive detection, reaching the limit of ten copies. The 19 assays are the most frequently used genetic elements present in GM crops and theoretically enable the screening of the known GMO described in Chinese markets. Easy to use, fast and cost efficient, this method approach fits the purpose of GMO testing laboratories.

High Temperature Ultrasonic Transducer for Real-time Inspection

NASA Astrophysics Data System (ADS)

Amini, Mohammad Hossein; Sinclair, Anthony N.; Coyle, Thomas W.

A broadband ultrasonic transducer with a novel porous ceramic backing layer is introduced to operate at 700 °C. 36° Y-cut lithium niobate (LiNbO3) single crystal was selected for the piezoelectric element. By appropriate choice of constituent materials, porosity and pore size, the acoustic impedance and attenuation of a zirconia-based backing layer were optimized. An active brazing alloy with high temperature and chemical stability was selected to bond the transducer layers together. Prototype transducers have been tested at temperatures up to 700 °C. The experiments confirmed that transducer integrity was maintained.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE PAGES

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

2017-04-17

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

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

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

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

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

Treatment of real wastewater produced from Mobil car wash station using electrocoagulation technique.

PubMed

El-Ashtoukhy, E-S Z; Amin, N K; Fouad, Y O

2015-10-01

This paper deals with the electrocoagulation of real wastewater produced from a car wash station using a new cell design featuring a horizontal spiral anode placed above a horizontal disc cathode. The study dealt with the chemical oxygen demand (COD) reduction and turbidity removal using electrodes in a batch mode. Various operating parameters such as current density, initial pH, NaCl concentration, temperature, and electrode material were examined to optimize the performance of the process. Also, characterization of sludge formed during electrocoagulation was carried out. The results indicated that the COD reduction and turbidity removal increase with increasing the current density and NaCl concentration; pH from 7 to 8 was found to be optimum for treating the wastewater. Temperature was found to have an insignificant effect on the process. Aluminum was superior to iron as a sacrificial electrode material in treating car wash wastewater. Energy consumption based on COD reduction ranged from 2.32 to 15.1 kWh/kg COD removed depending on the operating conditions. Finally, the sludge produced during electrocoagulation using aluminum electrodes was characterized by scanning electron microscopy (SEM) and energy dispersive spectrometry (EDS) analysis.

Efficient Skin Temperature Sensor and Stable Gel-Less Sticky ECG Sensor for a Wearable Flexible Healthcare Patch.

PubMed

Yamamoto, Yuki; Yamamoto, Daisuke; Takada, Makoto; Naito, Hiroyoshi; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2017-09-01

Wearable, flexible healthcare devices, which can monitor health data to predict and diagnose disease in advance, benefit society. Toward this future, various flexible and stretchable sensors as well as other components are demonstrated by arranging materials, structures, and processes. Although there are many sensor demonstrations, the fundamental characteristics such as the dependence of a temperature sensor on film thickness and the impact of adhesive for an electrocardiogram (ECG) sensor are yet to be explored in detail. In this study, the effect of film thickness for skin temperature measurements, adhesive force, and reliability of gel-less ECG sensors as well as an integrated real-time demonstration is reported. Depending on the ambient conditions, film thickness strongly affects the precision of skin temperature measurements, resulting in a thin flexible film suitable for a temperature sensor in wearable device applications. Furthermore, by arranging the material composition, stable gel-less sticky ECG electrodes are realized. Finally, real-time simultaneous skin temperature and ECG signal recordings are demonstrated by attaching an optimized device onto a volunteer's chest. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Optimal colour quality of LED clusters based on memory colours.

PubMed

Smet, Kevin; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter

2011-03-28

The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.

A portable neutron spectroscope (NSPECT) for detection, imaging and identification of nuclear material

NASA Astrophysics Data System (ADS)

Ryan, James M.; Bancroft, Christopher; Bloser, Peter; Bravar, Ulisse; Fourguette, Dominique; Frost, Colin; Larocque, Liane; McConnell, Mark L.; Legere, Jason; Pavlich, Jane; Ritter, Greg; Wassick, Greg; Wood, Joshua; Woolf, Richard

2010-08-01

We have developed, fabricated and tested a prototype imaging neutron spectrometer designed for real-time neutron source location and identification. Real-time detection and identification is important for locating materials. These materials, specifically uranium and transuranics, emit neutrons via spontaneous or induced fission. Unlike other forms of radiation (e.g. gamma rays), penetrating neutron emission is very uncommon. The instrument detects these neutrons, constructs images of the emission pattern, and reports the neutron spectrum. The device will be useful for security and proliferation deterrence, as well as for nuclear waste characterization and monitoring. The instrument is optimized for imaging and spectroscopy in the 1-20 MeV range. The detection principle is based upon multiple elastic neutron-proton scatters in organic scintillator. Two detector panel layers are utilized. By measuring the recoil proton and scattered neutron locations and energies, the direction and energy spectrum of the incident neutrons can be determined and discrete and extended sources identified. Event reconstruction yields an image of the source and its location. The hardware is low power, low mass, and rugged. Its modular design allows the user to combine multiple units for increased sensitivity. We will report the results of laboratory testing of the instrument, including exposure to a calibrated Cf-252 source. Instrument parameters include energy and angular resolution, gamma rejection, minimum source identification distances and times, and projected effective area for a fully populated instrument.

Capabilities of Unconventional Processing of Multiphase AHSS Steels

NASA Astrophysics Data System (ADS)

Jirkova, H.; Masek, B.; Stadler, C.; Jenicek, S.

2016-03-01

Today, new types of materials and procedures are sought continuously in order to achieve lower manufacturing costs, reduced energy consumption, shorter production times and other savings. In terms of the materials, TRIP steels are an attractive choice, as they provide an excellent combination of strength and ductility. They also offer good energy absorption in crash scenarios. Their main use is in the production of automotive body parts. One can expect that well-chosen processing parameters and unconventional forming routes would enable a wider range of thin-walled products to be made of these steels. Those could include thin-walled hollow products with excellent mechanical properties imparted by effective manufacturing routes at relatively low costs. If these materials are to be employed in real-world forming processes, an appropriate forming route must be chosen, integrated into an appropriate production chain and then optimized in terms of its parameters. This article describes a study of a rotary spin extrusion process. In the first stage, the impact of strain magnitude on microstructural evolution was studied in CMnSi steel using physical modelling of thermomechanical treatment. Subsequently, trials of a real-life technology chain, which efficiently combined incremental forming and heat treatment, were carried out on low-alloy CMnSi and CMnSiNb steels. The resulting products were stepped hollow parts of various diameters. Their strength was close to 1000 MPa and their elongation level exceeded 20%.

An Optimization Framework for Dynamic, Distributed Real-Time Systems

NASA Technical Reports Server (NTRS)

Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara

2003-01-01

Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2001-01-01

A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.

Surgery scheduling optimization considering real life constraints and comprehensive operation cost of operating room.

PubMed

Xiang, Wei; Li, Chong

2015-01-01

Operating Room (OR) is the core sector in hospital expenditure, the operation management of which involves a complete three-stage surgery flow, multiple resources, prioritization of the various surgeries, and several real-life OR constraints. As such reasonable surgery scheduling is crucial to OR management. To optimize OR management and reduce operation cost, a short-term surgery scheduling problem is proposed and defined based on the survey of the OR operation in a typical hospital in China. The comprehensive operation cost is clearly defined considering both under-utilization and overutilization. A nested Ant Colony Optimization (nested-ACO) incorporated with several real-life OR constraints is proposed to solve such a combinatorial optimization problem. The 10-day manual surgery schedules from a hospital in China are compared with the optimized schedules solved by the nested-ACO. Comparison results show the advantage using the nested-ACO in several measurements: OR-related time, nurse-related time, variation in resources' working time, and the end time. The nested-ACO considering real-life operation constraints such as the difference between first and following case, surgeries priority, and fixed nurses in pre/post-operative stage is proposed to solve the surgery scheduling optimization problem. The results clearly show the benefit of using the nested-ACO in enhancing the OR management efficiency and minimizing the comprehensive overall operation cost.

Finite Element Simulation of Compression Molding of Woven Fabric Carbon Fiber/Epoxy Composites: Part I Material Model Development

DOE PAGES

Li, Yang; Zhao, Qiangsheng; Mirdamadi, Mansour; ...

2016-01-06

Woven fabric carbon fiber/epoxy composites made through compression molding are one of the promising choices of material for the vehicle light-weighting strategy. Previous studies have shown that the processing conditions can have substantial influence on the performance of this type of the material. Therefore the optimization of the compression molding process is of great importance to the manufacturing practice. An efficient way to achieve the optimized design of this process would be through conducting finite element (FE) simulations of compression molding for woven fabric carbon fiber/epoxy composites. However, performing such simulation remains a challenging task for FE as multiple typesmore » of physics are involved during the compression molding process, including the epoxy resin curing and the complex mechanical behavior of woven fabric structure. In the present study, the FE simulation of the compression molding process of resin based woven fabric composites at continuum level is conducted, which is enabled by the implementation of an integrated material modeling methodology in LS-Dyna. Specifically, the chemo-thermo-mechanical problem of compression molding is solved through the coupling of three material models, i.e., one thermal model for temperature history in the resin, one mechanical model to update the curing-dependent properties of the resin and another mechanical model to simulate the behavior of the woven fabric composites. Preliminary simulations of the carbon fiber/epoxy woven fabric composites in LS-Dyna are presented as a demonstration, while validations and models with real part geometry are planned in the future work.« less

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

Li, Yang; Zhao, Qiangsheng; Mirdamadi, Mansour

Woven fabric carbon fiber/epoxy composites made through compression molding are one of the promising choices of material for the vehicle light-weighting strategy. Previous studies have shown that the processing conditions can have substantial influence on the performance of this type of the material. Therefore the optimization of the compression molding process is of great importance to the manufacturing practice. An efficient way to achieve the optimized design of this process would be through conducting finite element (FE) simulations of compression molding for woven fabric carbon fiber/epoxy composites. However, performing such simulation remains a challenging task for FE as multiple typesmore » of physics are involved during the compression molding process, including the epoxy resin curing and the complex mechanical behavior of woven fabric structure. In the present study, the FE simulation of the compression molding process of resin based woven fabric composites at continuum level is conducted, which is enabled by the implementation of an integrated material modeling methodology in LS-Dyna. Specifically, the chemo-thermo-mechanical problem of compression molding is solved through the coupling of three material models, i.e., one thermal model for temperature history in the resin, one mechanical model to update the curing-dependent properties of the resin and another mechanical model to simulate the behavior of the woven fabric composites. Preliminary simulations of the carbon fiber/epoxy woven fabric composites in LS-Dyna are presented as a demonstration, while validations and models with real part geometry are planned in the future work.« less

Event Oriented Design and Adaptive Multiprocessing

DTIC Science & Technology

1991-08-31

System 5 2.3 The Classification 5 2.4 Real-Time Systems 7 2.5 Non Real-Time Systems 10 2.6 Common Characterizations of all Software Systems 10 2.7... Non -Optimal Guarantee Test Theorem 37 6.3.2 Chetto’s Optimal Guarantee Test Theorem 37 6.3.3 Multistate Case: An Extended Guarantee 39 Test Theorem...which subdivides all software systems according to the way in which they operate, such as interactive, non interactive, real-time, etc. Having defined

Online gaming for learning optimal team strategies in real time

NASA Astrophysics Data System (ADS)

Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

Development and Optimization of Voltammetric Methods for Real Time Analysis of Electrorefiner Salt with High Concentrations of Actinides and Fission Products

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

Simpson, Michael F.; Phongikaroon, Supathorn; Zhang, Jinsuo

This project addresses the problem of achieving accurate material control and accountability (MC&A) around pyroprocessing electrorefiner systems. Spent nuclear fuel pyroprocessing poses a unique challenge with respect to reprocessing technology in that the fuel is never fully dissolved in the process fluid. In this case, the process fluid is molten, anhydrous LiCl-KCl salt. Therefore, there is no traditional input accountability tank. However, electrorefiners (ER) accumulate very large quantities of fissile nuclear material (including plutonium) and should be well safeguarded in a commercial facility. Idaho National Laboratory (INL) currently operates a pyroprocessing facility for treatment of spent fuel from Experimental Breedermore » Reactor-II with two such ER systems. INL implements MC&A via a mass tracking model in combination with periodic sampling of the salt and other materials followed by destructive analysis. This approach is projected to be insufficient to meet international safeguards timeliness requirements. A real time or near real time monitoring method is, thus, direly needed to support commercialization of pyroprocessing. A variety of approaches to achieving real time monitoring for ER salt have been proposed and studied to date—including a potentiometric actinide sensor for concentration measurements, a double bubbler for salt depth and density measurements, and laser induced breakdown spectroscopy (LIBS) for concentration measurements. While each of these methods shows some promise, each also involves substantial technical complexity that may ultimately limit their implementation. Yet another alternative is voltammetry—a very simple method in theory that has previously been tested for this application to a limited extent. The equipment for a voltammetry system consists of off-the-shelf components (three electrodes and a potentiostat), which results in substantial benefits relative to cost and robustness. Based on prior knowledge of electrochemical reduction potentials for each of the species of interest, voltammetry can be used to quantify concentrations of a variety of elemental species—including uranium, plutonium, minor actinides, and rare earths. Various methods have been tested by other researchers to date—including cyclic voltammetry, square wave voltammetry, normal pulse voltammetry, etc. In most cases, it has been observed that there is a very limited concentration range for which the output can be readily correlated with concentration in the salt. Furthermore, testing to date has been limited to simple ternary salts with only a single element being quantified. While incomplete for application to MC&A for pyroprocessing, these results lead us to believe that voltammetry can be optimized based on salt properties and fundamental electrochemical rate processes to yield a highly accurate and robust method. This project is divided into four tasks jointly executed by three university research groups. This includes experimental measurement of key physical data on the systems of interest, development of a predictive voltammetry model, experimental validation of the voltammetry model, and design/verification of an optimized measurement method. This project supports the goals of the US-ROK Joint Fuel Cycle Study in addition to the NA-24 Office of the National Nuclear Security Agency and the International Atomic Energy Agency (IAEA).« less

Real-time sensing of fatigue crack damage for information-based decision and control

NASA Astrophysics Data System (ADS)

Keller, Eric Evans

Information-based decision and control for structures that are subject to failure by fatigue cracking is based on the following notion: Maintenance, usage scheduling, and control parameter tuning can be optimized through real time knowledge of the current state of fatigue crack damage. Additionally, if the material properties of a mechanical structure can be identified within a smaller range, then the remaining life prediction of that structure will be substantially more accurate. Information-based decision systems can rely one physical models, estimation of material properties, exact knowledge of usage history, and sensor data to synthesize an accurate snapshot of the current state of damage and the likely remaining life of a structure under given assumed loading. The work outlined in this thesis is structured to enhance the development of information-based decision and control systems. This is achieved by constructing a test facility for laboratory experiments on real-time damage sensing. This test facility makes use of a methodology that has been formulated for fatigue crack model parameter estimation and significantly improves the quality of predictions of remaining life. Specifically, the thesis focuses on development of an on-line fatigue crack damage sensing and life prediction system that is built upon the disciplines of Systems Sciences and Mechanics of Materials. A major part of the research effort has been expended to design and fabricate a test apparatus which allows: (i) measurement and recording of statistical data for fatigue crack growth in metallic materials via different sensing techniques; and (ii) identification of stochastic model parameters for prediction of fatigue crack damage. To this end, this thesis describes the test apparatus and the associated instrumentation based on four different sensing techniques, namely, traveling optical microscopy, ultrasonic flaw detection, Alternating Current Potential Drop (ACPD), and fiber-optic extensometry-based compliance, for crack length measurements.

Design optimization of a viscoelastic dynamic vibration absorber using a modified fixed-points theory.

PubMed

Wong, W O; Fan, R P; Cheng, F

2018-02-01

A viscoelastic dynamic vibration absorber (VDVA) is proposed for suppressing infrasonic vibrations of heavy structures because the traditional dynamic vibration absorber equipped with a viscous damper is not effective in suppressing low frequency vibrations. The proposed VDVA has an elastic spring and a viscoelastic damper with frequency dependent modulus and damping properties. The standard fixed-points theory cannot be applied to derive the optimum design parameters of the VDVA because both its stiffness and damping are frequency dependent. A modified fixed-points theory is therefore proposed to solve this problem. H ∞ design optimization of the proposed VDVA have been derived for the minimization of resonant vibration amplitude of a single degree-of-freedom system excited by harmonic forces or due to ground motions. The stiffness and damping of the proposed VDVA can be decoupled such that both of these two properties of the absorber can be tuned independently to their optimal values by following a specified procedure. The proposed VDVA with optimized design is tested numerically using two real commercial viscoelastic damping materials. It is found that the proposed viscoelastic absorber can provide much stronger vibration reduction effect than the conventional VDVA without the elastic spring.

Optimization of a 3.6-THz quantum cascade laser for real-time imaging with a microbolometer focal plane array

NASA Astrophysics Data System (ADS)

Behnken, Barry N.; Karunasiri, Gamani; Chamberlin, Danielle; Robrish, Peter; Faist, Jérôme

2008-02-01

Real-time imaging in the terahertz (THz) spectral range was achieved using a 3.6-THz quantum cascade laser (QCL) and an uncooled, 160×120 pixel microbolometer camera fitted with a picarin lens. Noise equivalent temperature difference of the camera in the 1-5 THz frequency range was calculated to be at least 3 K, confirming the need for external THz illumination when imaging in this frequency regime. After evaluating the effects of various operating parameters on laser performance, the QCL found to perform optimally at 1.9 A in pulsed mode with a 300 kHz repetition rate and 10-20% duty cycle; average output power was approximately 1 mW. Under this scheme, a series of metallic objects were imaged while wrapped in various obscurants. Single-frame and extended video recordings demonstrate strong contrast between metallic materials and those of plastic, cloth, and paper - supporting the viability of this imaging technology in security screening applications. Thermal effects arising from Joule heating of the laser were found to be the dominant issue affecting output power and image quality; these effects were mitigated by limiting laser pulse widths to 670 ns and operating the system under closed-cycle refrigeration at a temperature of 10 K.

Experimental investigation into biomechanical and biotribological properties of a real intestine and their significance for design of a spiral-type robotic capsule.

PubMed

Zhou, Hao; Alici, Gursel; Than, Trung D; Li, Weihua

2014-03-01

This article reports on the results and implications of our experimental investigation into the biomechanical and biotribological properties of a real intestine for the optimal design of a spiral-type robotic capsule. Dynamic shear experiments were conducted to evaluate how the storage and loss moduli and damping factor of the small intestine change with the speed or the angular frequency. The sliding friction between differently shaped test pieces, with a topology similar to that of the spirals, and the intestine sample was experimentally determined. Our findings demonstrate that the intestine's biomechanical and biotribological properties are coupled, suggesting that the sliding friction is strongly related to the internal friction of the intestinal tissue. The significant implication of this finding is that one can predict the reaction force between the capsule with a spiral-type traction topology and the intestine directly from the intestine's biomechanical measurements rather than employing complicated three-dimensional finite element analysis or an inaccurate analytical model. Sliding friction experiments were also conducted with bar-shaped solid samples to determine the sliding friction between the samples and the small intestine. This sliding friction data will be useful in determining spiral material for an optimally designed robotic capsule.

Development and validation of a SYBR Green I-based real-time polymerase chain reaction method for detection of haptoglobin gene deletion in clinical materials.

PubMed

Soejima, Mikiko; Tsuchiya, Yuji; Egashira, Kouichi; Kawano, Hiroyuki; Sagawa, Kimitaka; Koda, Yoshiro

2010-06-01

Anhaptoglobinemic patients run the risk of severe anaphylactic transfusion reaction because they produce serum haptoglobin (Hp) antibodies. Being homozygous for the Hp gene deletion (HP(del)) is the only known cause of congenital anhaptoglobinemia, and clinical diagnosis of HP(del) before transfusion is important to prevent anaphylactic shock. We recently developed a 5'-nuclease (TaqMan) real-time polymerase chain reaction (PCR) method. A SYBR Green I-based duplex real-time PCR assay using two forward primers and a common reverse primer followed by melting curve analysis was developed to determine HP(del) zygosity in a single tube. In addition, to obviate initial DNA extraction, we examined serially diluted blood samples as PCR templates. Allelic discrimination of HP(del) yielded optimal results at blood sample dilutions of 1:64 to 1:1024. The results from 2231 blood samples were fully concordant with those obtained by the TaqMan-based real-time PCR method. The detection rate of the HP(del) allele by the SYBR Green I-based method is comparable with that using the TaqMan-based method. This method is readily applicable due to its low initial cost and analyzability using economical real-time PCR machines and is suitable for high-throughput analysis as an alternative method for allelic discrimination of HP(del).

[Model and analysis of spectropolarimetric BRDF of painted target based on GA-LM method].

PubMed

Chen, Chao; Zhao, Yong-Qiang; Luo, Li; Pan, Quan; Cheng, Yong-Mei; Wang, Kai

2010-03-01

Models based on microfacet were used to describe spectropolarimetric BRDF (short for bidirectional reflectance distribution function) with experimental data. And the spectropolarimetric BRDF values of targets were measured with the comparison to the standard whiteboard, which was considered as Lambert and had a uniform reflectance rate up to 98% at arbitrary angle of view. And then the relationships between measured spectropolarimetric BRDF values and the angles of view, as well as wavelengths which were in a range of 400-720 nm were analyzed in details. The initial value needed to be input to the LM optimization method was difficult to get and greatly impacted the results. Therefore, optimization approach which combines genetic algorithm and Levenberg-Marquardt (LM) was utilized aiming to retrieve parameters of nonlinear models, and the initial values were obtained using GA approach. Simulated experiments were used to test the efficiency of the adopted optimization method. And the simulated experiment ensures the optimization method to have a good performance and be able to retrieve the parameters of nonlinear model efficiently. The correctness of the models was validated by real outdoor sampled data. The parameters of DoP model retrieved are the refraction index of measured targets. The refraction index of the same color painted target but with different materials was also obtained. Conclusion has been drawn that the refraction index from these two targets are very near and this slight difference could be understood by the difference in the conditions of paint targets' surface, not the material of the targets.

Instrumentation for optimizing an underground coal-gasification process

NASA Astrophysics Data System (ADS)

Seabaugh, W.; Zielinski, R. E.

1982-06-01

While the United States has a coal resource base of 6.4 trillion tons, only seven percent is presently recoverable by mining. The process of in-situ gasification can recover another twenty-eight percent of the vast resource, however, viable technology must be developed for effective in-situ recovery. The key to this technology is system that can optimize and control the process in real-time. An instrumentation system is described that optimizes the composition of the injection gas, controls the in-situ process and conditions the product gas for maximum utilization. The key elements of this system are Monsanto PRISM Systems, a real-time analytical system, and a real-time data acquisition and control system. This system provides from complete automation of the process but can easily be overridden by manual control. The use of this cost effective system can provide process optimization and is an effective element in developing a viable in-situ technology.

Quantitative Characterization of Nanostructured Materials

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

Dr. Frank

The two-and-a-half day symposium on the "Quantitative Characterization of Nanostructured Materials" will be the first comprehensive meeting on this topic held under the auspices of a major U.S. professional society. Spring MRS Meetings provide a natural venue for this symposium as they attract a broad audience of researchers that represents a cross-section of the state-of-the-art regarding synthesis, structure-property relations, and applications of nanostructured materials. Close interactions among the experts in local structure measurements and materials researchers will help both to identify measurement needs pertinent to real-world materials problems and to familiarize the materials research community with the state-of-the-art local structuremore » measurement techniques. We have chosen invited speakers that reflect the multidisciplinary and international nature of this topic and the need to continually nurture productive interfaces among university, government and industrial laboratories. The intent of the symposium is to provide an interdisciplinary forum for discussion and exchange of ideas on the recent progress in quantitative characterization of structural order in nanomaterials using different experimental techniques and theory. The symposium is expected to facilitate discussions on optimal approaches for determining atomic structure at the nanoscale using combined inputs from multiple measurement techniques.« less

Quantification of Nonproteolytic Clostridium botulinum Spore Loads in Food Materials.

PubMed

Barker, Gary C; Malakar, Pradeep K; Plowman, June; Peck, Michael W

2016-01-04

We have produced data and developed analysis to build representations for the concentration of spores of nonproteolytic Clostridium botulinum in materials that are used during the manufacture of minimally processed chilled foods in the United Kingdom. Food materials are categorized into homogenous groups which include meat, fish, shellfish, cereals, fresh plant material, dairy liquid, dairy nonliquid, mushroom and fungi, and dried herbs and spices. Models are constructed in a Bayesian framework and represent a combination of information from a literature survey of spore loads from positive-control experiments that establish a detection limit and from dedicated microbiological tests for real food materials. The detection of nonproteolytic C. botulinum employed an optimized protocol that combines selective enrichment culture with multiplex PCR, and the majority of tests on food materials were negative. Posterior beliefs about spore loads center on a concentration range of 1 to 10 spores kg(-1). Posterior beliefs for larger spore loads were most significant for dried herbs and spices and were most sensitive to the detailed results from control experiments. Probability distributions for spore loads are represented in a convenient form that can be used for numerical analysis and risk assessments. Copyright © 2016 Barker et al.

Quantification of Nonproteolytic Clostridium botulinum Spore Loads in Food Materials

PubMed Central

Barker, Gary C.; Malakar, Pradeep K.; Plowman, June

2016-01-01

We have produced data and developed analysis to build representations for the concentration of spores of nonproteolytic Clostridium botulinum in materials that are used during the manufacture of minimally processed chilled foods in the United Kingdom. Food materials are categorized into homogenous groups which include meat, fish, shellfish, cereals, fresh plant material, dairy liquid, dairy nonliquid, mushroom and fungi, and dried herbs and spices. Models are constructed in a Bayesian framework and represent a combination of information from a literature survey of spore loads from positive-control experiments that establish a detection limit and from dedicated microbiological tests for real food materials. The detection of nonproteolytic C. botulinum employed an optimized protocol that combines selective enrichment culture with multiplex PCR, and the majority of tests on food materials were negative. Posterior beliefs about spore loads center on a concentration range of 1 to 10 spores kg−1. Posterior beliefs for larger spore loads were most significant for dried herbs and spices and were most sensitive to the detailed results from control experiments. Probability distributions for spore loads are represented in a convenient form that can be used for numerical analysis and risk assessments. PMID:26729721

An Optimal Static Scheduling Algorithm for Hard Real-Time Systems Specified in a Prototyping Language

DTIC Science & Technology

1989-12-01

to construct because the mechanism is a dispatching procedure. Since all nonpreemptive schedules are contained in the set of all preemptive schedules...the optimal value of T’.. in the preemptive case is at least a lower bound on the optimal T., for the nonpreemptive schedules. This principle is the...adapt to changes in the enviro.nment. In hard real-time systems, tasks are also distinguished as preemptable and nonpreemptable . A task is preemptable

Concurrent design of quasi-random photonic nanostructures

PubMed Central

Lee, Won-Kyu; Yu, Shuangcheng; Engel, Clifford J.; Reese, Thaddeus; Rhee, Dongjoon; Chen, Wei

2017-01-01

Nanostructured surfaces with quasi-random geometries can manipulate light over broadband wavelengths and wide ranges of angles. Optimization and realization of stochastic patterns have typically relied on serial, direct-write fabrication methods combined with real-space design. However, this approach is not suitable for customizable features or scalable nanomanufacturing. Moreover, trial-and-error processing cannot guarantee fabrication feasibility because processing–structure relations are not included in conventional designs. Here, we report wrinkle lithography integrated with concurrent design to produce quasi-random nanostructures in amorphous silicon at wafer scales that achieved over 160% light absorption enhancement from 800 to 1,200 nm. The quasi-periodicity of patterns, materials filling ratio, and feature depths could be independently controlled. We statistically represented the quasi-random patterns by Fourier spectral density functions (SDFs) that could bridge the processing–structure and structure–performance relations. Iterative search of the optimal structure via the SDF representation enabled concurrent design of nanostructures and processing. PMID:28760975

Optimization design of toroidal core for magnetic energy harvesting near power line by considering saturation effect

NASA Astrophysics Data System (ADS)

Park, Bumjin; Kim, Dongwook; Park, Jaehyoung; Kim, Kibeom; Koo, Jay; Park, HyunHo; Ahn, Seungyoung

2018-05-01

Recently, magnetic energy harvesting technologies have been studied actively for self-sustainable operation of applications around power line. However, magnetic energy harvesting around power lines has the problem of magnetic saturation, which can cause power performance degradation of the harvester. In this paper, optimal design of a toroidal core for magnetic energy harvesters has been proposed with consideration of magnetic saturation near power lines. Using Permeability-H curve and Ampere's circuital law, the optimum dimensional parameters needed to generate induced voltage were analyzed via calculation and simulation. To reflect a real environment, we consider the nonlinear characteristic of the magnetic core material and supply current through a 3-phase distribution panel used in the industry. The effectiveness of the proposed design methodology is verified by experiments in a power distribution panel and takes 60.9 V from power line current of 60 A at 60 Hz.

Comprehensive transcriptome analysis and flavonoid profiling of Ginkgo leaves reveals flavonoid content alterations in day-night cycles.

PubMed

Ni, Jun; Dong, Lixiang; Jiang, Zhifang; Yang, Xiuli; Chen, Ziying; Wu, Yuhuan; Xu, Maojun

2018-01-01

Ginkgo leaves are raw materials for flavonoid extraction. Thus, the timing of their harvest is important to optimize the extraction efficiency, which benefits the pharmaceutical industry. In this research, we compared the transcriptomes of Ginkgo leaves harvested at midday and midnight. The differentially expressed genes with the highest probabilities in each step of flavonoid biosynthesis were down-regulated at midnight. Furthermore, real-time PCR corroborated the transcriptome results, indicating the decrease in flavonoid biosynthesis at midnight. The flavonoid profiles of Ginkgo leaves harvested at midday and midnight were compared, and the total flavonoid content decreased at midnight. A detailed analysis of individual flavonoids showed that most of their contents were decreased by various degrees. Our results indicated that circadian rhythms affected the flavonoid contents in Ginkgo leaves, which provides valuable information for optimizing their harvesting times to benefit the pharmaceutical industry.

Study on the performance of eosin-doped poly(vinyl alcohol)/acrylamide photopolymer films for holographic recording using 488-nm wavelength

NASA Astrophysics Data System (ADS)

Rajesh, Chelakkal Sukumaran; Sreeroop, Sasidharan Savithrydevi; Pramitha, Vayalamkuzhi; Joseph, Rani; Sreekumar, Krishnapillai; Kartha, Cheranellore Sudha

2011-12-01

This article reports a study done on eosin-doped poly(vinyl alcohol)/acrylamide films for holographic recording using 488 nm Ar+ laser. Films were fabricated using gravity settling method at room temperature and were stored under normal laboratory conditions. Ar+ laser (488 nm) was used for fringe recording. Characterization was done by real time transmittance measurement, optical absorption studies, and diffraction efficiency measurements. Various holographic parameters such as exposure energy, recording power, spatial frequency, etc., were optimized so as to ensure maximum performance. More than 85% diffraction efficiency was obtained at an exposure energy of 50 mJ/cm2 in the optimized film. Efforts were taken to study the environmental stability of this self-developing polymeric material by looking at its shelf life and storage life. Compatibility for recording transmission hologram was also checked.

Novel ion imprinted magnetic mesoporous silica for selective magnetic solid phase extraction of trace Cd followed by graphite furnace atomic absorption spectrometry detection

NASA Astrophysics Data System (ADS)

Zhao, Bingshan; He, Man; Chen, Beibei; Hu, Bin

2015-05-01

Determination of trace Cd in environmental, biological and food samples is of great significance to toxicological research and environmental pollution monitoring. While the direct determination of Cd in real-world samples is difficult due to its low concentration and the complex matrix. Herein, a novel Cd(II)-ion imprinted magnetic mesoporous silica (Cd(II)-II-MMS) was prepared and was employed as a selective magnetic solid-phase extraction (MSPE) material for extraction of trace Cd in real-world samples followed by graphite furnace atomic absorption spectrometry (GFAAS) detection. Under the optimized conditions, the detection limit of the proposed method was 6.1 ng L- 1 for Cd with the relative standard deviation (RSD) of 4.0% (c = 50 ng L- 1, n = 7), and the enrichment factor was 50-fold. To validate the proposed method, Certified Reference Materials of GSBZ 50009-88 environmental water, ZK018-1 lyophilized human urine and NIES10-b rice flour were analyzed and the determined values were in a good agreement with the certified values. The proposed method exhibited a robust anti-interference ability due to the good selectivity of Cd(II)-II-MMS toward Cd(II). It was successfully employed for the determination of trace Cd(II) in environmental water, human urine and rice samples with recoveries of 89.3-116%, demonstrating that the proposed method has good application potential in real world samples with complex matrix.

Printing Fabrication of Bulk Heterojunction Solar Cells and In Situ Morphology Characterization.

PubMed

Liu, Feng; Ferdous, Sunzida; Wan, Xianjian; Zhu, Chenhui; Schaible, Eric; Hexemer, Alexander; Wang, Cheng; Russell, Thomas P

2017-01-29

Polymer-based materials hold promise as low-cost, flexible efficient photovoltaic devices. Most laboratory efforts to achieve high performance devices have used devices prepared by spin coating, a process that is not amenable to large-scale fabrication. This mismatch in device fabrication makes it difficult to translate quantitative results obtained in the laboratory to the commercial level, making optimization difficult. Using a mini-slot die coater, this mismatch can be resolved by translating the commercial process to the laboratory and characterizing the structure formation in the active layer of the device in real time and in situ as films are coated onto a substrate. The evolution of the morphology was characterized under different conditions, allowing us to propose a mechanism by which the structures form and grow. This mini-slot die coater offers a simple, convenient, material efficient route by which the morphology in the active layer can be optimized under industrially relevant conditions. The goal of this protocol is to show experimental details of how a solar cell device is fabricated using a mini-slot die coater and technical details of running in situ structure characterization using the mini-slot die coater.

Modeling and optimal design of an optical MEMS tactile sensor for use in robotically assisted surgery

NASA Astrophysics Data System (ADS)

Ahmadi, Roozbeh; Kalantari, Masoud; Packirisamy, Muthukumaran; Dargahi, Javad

2010-06-01

Currently, Minimally Invasive Surgery (MIS) performs through keyhole incisions using commercially available robotic surgery systems. One of the most famous examples of these robotic surgery systems is the da Vinci surgical system. In the current robotic surgery systems like the da Vinci, surgeons are faced with problems such as lack of tactile feedback during the surgery. Therefore, providing a real-time tactile feedback from interaction between surgical instruments and tissue can help the surgeons to perform MIS more reliably. The present paper proposes an optical tactile sensor to measure the contact force between the bio-tissue and the surgical instrument. A model is proposed for simulating the interaction between a flexible membrane and bio-tissue based on the finite element methods. The tissue is considered as a hyperelastic material with the material properties similar to the heart tissue. The flexible membrane is assumed as a thin layer of silicon which can be microfabricated using the technology of Micro Electro Mechanical Systems (MEMS). The simulation results are used to optimize the geometric design parameters of a proposed MEMS tactile sensor for use in robotic surgical systems to perform MIS.

Soft tissue deformation for surgical simulation: a position-based dynamics approach.

PubMed

Camara, Mafalda; Mayer, Erik; Darzi, Ara; Pratt, Philip

2016-06-01

To assist the rehearsal and planning of robot-assisted partial nephrectomy, a real-time simulation platform is presented that allows surgeons to visualise and interact with rapidly constructed patient-specific biomechanical models of the anatomical regions of interest. Coupled to a framework for volumetric deformation, the platform furthermore simulates intracorporeal 2D ultrasound image acquisition, using preoperative imaging as the data source. This not only facilitates the planning of optimal transducer trajectories and viewpoints, but can also act as a validation context for manually operated freehand 3D acquisitions and reconstructions. The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. In order to validate the model and determine material properties and other simulation parameter values, a porcine kidney with embedded fiducial beads was CT-scanned and segmented. Acquisitions for the rest position and three different levels of probe-induced deformation were collected. Optimal values of the cluster stiffness coefficients were determined for a range of different particle radii, where the objective function comprised the mean distance error between real and simulated fiducial positions over the sequence of deformations. The mean fiducial error at each deformation stage was found to be compatible with the level of ultrasound probe calibration error typically observed in clinical practice. Furthermore, the simulation exhibited unconditional stability on account of its use of clustered shape-matching constraints. A novel position-based dynamics implementation of soft tissue deformation has been shown to facilitate several desirable simulation characteristics: real-time performance, unconditional stability, rapid model construction enabling patient-specific behaviour and accuracy with respect to reference CT images.

Terahertz thickness measurements for real industrial applications: from automotive paints to aerospace industry (Conference Presentation)

NASA Astrophysics Data System (ADS)

Krimi, Soufiene; Beigang, René

2017-02-01

In this contribution, we present a highly accurate approach for real-time thickness measurements of multilayered coatings using terahertz time domain spectroscopy in reflection geometry. The proposed approach combines the benefits of a model-based material parameters extraction method to calibrate the specimen under test, a generalized modeling method to simulate the terahertz radiation behavior within arbitrary thin films, and the robustness of a powerful evolutionary optimization algorithm to increase the sensitivity and the precision of the minimum thickness measurement limit. Furthermore, a novel self-calibration model is introduced, which takes into consideration the real industrial challenges such as the effect of wet-on-wet spray in the car painting process and the influence of the spraying conditions and the sintering process on ceramic thermal barrier coatings (TBCs) in aircraft industry. In addition, the developed approach enables for some applications the simultaneous determination of the complex refractive index and the coating thickness. Hence, a pre-calibration of the specimen under test is not required for such cases. Due to the high robustness of the self-calibration method and the genetic optimization algorithms, the approach has been successfully applied to resolve individual layer thicknesses within multi-layered coated samples down to less than 10 µm. The regression method can be applied in time-domain, frequency-domain or in both the time and frequency-domain simultaneously. The data evaluation uses general-purpose computing on graphics processing units and thanks to the developed highly parallelized algorithm lasts less than 300 ms. Thus, industrial requirements for fast thickness measurements with an "every-second-cycle" can be fulfilled.

Overview of the ARPA/WL Smart Structures and Materials Development-Smart Wing contract

NASA Astrophysics Data System (ADS)

Kudva, Jayanth N.; Jardine, A. Peter; Martin, Christopher A.; Appa, Kari

1996-05-01

While the concept of an adaptive aircraft wing, i.e., a wing whose shape parameters such as camber, wing twist, and thickness can be varied to optimize the wing shape for various flight conditions, has been extensively studied, the complexity and weight penalty of the actuation mechanisms have precluded their practical implementation. Recent development of sensors and actuators using smart materials could potentially alleviate the shortcomings of prior designs, paving the way for a practical, `smart' adaptive wing which responds to changes in flight and environmental conditions by modifying its shape to provide optimal performance. This paper presents a summary of recent work done on adaptive wing designs under an on-going ARPA/WL contract entitled `Smart Structures and Materials Development--Smart Wing.' Specifically, the design, development and planned wind tunnel testing of a 16% model representative of a fighter aircraft wing and incorporating the following features, are discussed: (1) a composite wing torque box whose span-wise twist can be varied by activating built-in shape memory alloy (SMA) torque tubes to provide increased lift and enhanced maneuverability at multiple flight conditions, (2) trailing edge control surfaces deployed using composite SMA actuators to provide smooth, hingeless aerodynamic surfaces, and (3) a suite of fiber optic sensors integrated into the wing skin which provide real-time strain and pressure data to a feedback control system.

WE-AB-303-06: Combining DAO with MV + KV Optimization to Improve Skin Dose Sparing with Real-Time Fluoroscopy

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

Grelewicz, Z; Wiersma, R

Purpose: Real-time fluoroscopy may allow for improved patient positioning and tumor tracking, particularly in the treatment of lung tumors. In order to mitigate the effects of the imaging dose, previous studies have demonstrated the effect of including both imaging dose and imaging constraints into the inverse treatment planning object function. That method of combined MV+kV optimization may Result in plans with treatment beams chosen to allow for more gentle imaging beam-on times. Direct-aperture optimization (DAO) is also known to produce treatment plans with fluence maps more conducive to lower beam-on times. Therefore, in this work we demonstrate the feasibility ofmore » a combination of DAO and MV+kV optimization for further optimized real-time kV imaging. Methods: Therapeutic and imaging beams were modeled in the EGSnrc Monte Carlo environment, and applied to a patient model for a previously treated lung patient to provide dose influence matrices from DOSXYZnrc. An MV + kV IMRT DAO treatment planning system was developed to compare DAO treatment plans with and without MV+kV optimization. The objective function was optimized using simulated annealing. In order to allow for comparisons between different cases of the stochastically optimized plans, the optimization was repeated twenty times. Results: Across twenty optimizations, combined MV+kV IMRT resulted in an average of 12.8% reduction in peak skin dose. Both non-optimized and MV+kV optimized imaging beams delivered, on average, mean dose of approximately 1 cGy per fraction to the target, with peak doses to target of approximately 6 cGy per fraction. Conclusion: When using DAO, MV+kV optimization is shown to Result in improvements to plan quality in terms of skin dose, when compared to the case of MV optimization with non-optimized kV imaging. The combination of DAO and MV+kV optimization may allow for real-time imaging without excessive imaging dose. Financial support for the work has been provided in part by NIH Grant T32 EB002103, ACS RSG-13-313-01-CCE, and NIH S10 RR021039 and P30 CA14599 grants. The contents of this submission do not necessarily represent the official views of any of the supporting organizations.« less

The optimal structure-conductivity relation in epoxy-phthalocyanine nanocomposites.

PubMed

Huijbregts, L J; Brom, H B; Brokken-Zijp, J C M; Kemerink, M; Chen, Z; Goeje, M P de; Yuan, M; Michels, M A J

2006-11-23

Phthalcon-11 (aquocyanophthalocyaninatocobalt (III)) forms semiconducting nanocrystals that can be dispersed in epoxy coatings to obtain a semiconducting material with a low percolation threshold. We investigated the structure-conductivity relation in this composite and the deviation from its optimal realization by combining two techniques. The real parts of the electrical conductivity of a Phthalcon-11/epoxy coating and of Phthalcon-11 powder were measured by dielectric spectroscopy as a function of frequency and temperature. Conducting atomic force microscopy (C-AFM) was applied to quantify the conductivity through the coating locally along the surface. This combination gives an excellent tool to visualize the particle network. We found that a large fraction of the crystals is organized in conducting channels of fractal building blocks. In this picture, a low percolation threshold automatically leads to a conductivity that is much lower than that of the filler. Since the structure-conductivity relation for the found network is almost optimal, a drastic increase in the conductivity of the coating cannot be achieved by changing the particle network, but only by using a filler with a higher conductivity level.

Parametric estimation for reinforced concrete relief shelter for Aceh cases

NASA Astrophysics Data System (ADS)

Atthaillah; Saputra, Eri; Iqbal, Muhammad

2018-05-01

This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

Optimization of the resources management in fighting wildfires.

PubMed

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

The Linear Quadratic Gaussian Multistage Game with Nonclassical Information Pattern Using a Direct Solution Method

NASA Astrophysics Data System (ADS)

Clemens, Joshua William

Game theory has application across multiple fields, spanning from economic strategy to optimal control of an aircraft and missile on an intercept trajectory. The idea of game theory is fascinating in that we can actually mathematically model real-world scenarios and determine optimal decision making. It may not always be easy to mathematically model certain real-world scenarios, nonetheless, game theory gives us an appreciation for the complexity involved in decision making. This complexity is especially apparent when the players involved have access to different information upon which to base their decision making (a nonclassical information pattern). Here we will focus on the class of adversarial two-player games (sometimes referred to as pursuit-evasion games) with nonclassical information pattern. We present a two-sided (simultaneous) optimization solution method for the two-player linear quadratic Gaussian (LQG) multistage game. This direct solution method allows for further interpretation of each player's decision making (strategy) as compared to previously used formal solution methods. In addition to the optimal control strategies, we present a saddle point proof and we derive an expression for the optimal performance index value. We provide some numerical results in order to further interpret the optimal control strategies and to highlight real-world application of this game-theoretic optimal solution.

"Real-time" disintegration analysis and D-optimal experimental design for the optimization of diclofenac sodium fast-dissolving films.

PubMed

El-Malah, Yasser; Nazzal, Sami

2013-01-01

The objective of this work was to study the dissolution and mechanical properties of fast-dissolving films prepared from a tertiary mixture of pullulan, polyvinylpyrrolidone and hypromellose. Disintegration studies were performed in real-time by probe spectroscopy to detect the onset of film disintegration. Tensile strength and elastic modulus of the films were measured by texture analysis. Disintegration time of the films ranged from 21 to 105 seconds whereas their mechanical properties ranged from approximately 2 to 49 MPa for tensile strength and 1 to 21 MPa% for young's modulus. After generating polynomial models correlating the variables using a D-Optimal mixture design, an optimal formulation with desired responses was proposed by the statistical package. For validation, a new film formulation loaded with diclofenac sodium based on the optimized composition was prepared and tested for dissolution and tensile strength. Dissolution of the optimized film was found to commence almost immediately with 50% of the drug released within one minute. Tensile strength and young's modulus of the film were 11.21 MPa and 6, 78 MPa%, respectively. Real-time spectroscopy in conjunction with statistical design were shown to be very efficient for the optimization and development of non-conventional intraoral delivery system such as fast dissolving films.

Optimization of Vacuum Impregnation with Calcium Lactate of Minimally Processed Melon and Shelf-Life Study in Real Storage Conditions.

PubMed

Tappi, Silvia; Tylewicz, Urszula; Romani, Santina; Siroli, Lorenzo; Patrignani, Francesca; Dalla Rosa, Marco; Rocculi, Pietro

2016-10-05

Vacuum impregnation (VI) is a processing operation that permits the impregnation of fruit and vegetable porous tissues with a fast and more homogeneous penetration of active compounds compared to the classical diffusion processes. The objective of this research was to investigate the impact on VI treatment with the addition of calcium lactate on qualitative parameters of minimally processed melon during storage. For this aim, this work was divided in 2 parts. Initially, the optimization of process parameters was carried out in order to choose the optimal VI conditions for improving texture characteristics of minimally processed melon that were then used to impregnate melons for a shelf-life study in real storage conditions. On the basis of a 2 3 factorial design, the effect of Calcium lactate (CaLac) concentration between 0% and 5% and of minimum pressure (P) between 20 and 60 MPa were evaluated on color and texture. Processing parameters corresponding to 5% CaLac concentration and 60 MPa of minimum pressure were chosen for the storage study, during which the modifications of main qualitative parameters were evaluated. Despite of the high variability of the raw material, results showed that VI allowed a better maintenance of texture during storage. Nevertheless, other quality traits were negatively affected by the application of vacuum. Impregnated products showed a darker and more translucent appearance on the account of the alteration of the structural properties. Moreover microbial shelf-life was reduced to 4 d compared to the 7 obtained for control and dipped samples. © 2016 Institute of Food Technologists®.

Real-time CT-video registration for continuous endoscopic guidance

NASA Astrophysics Data System (ADS)

Merritt, Scott A.; Rai, Lav; Higgins, William E.

2006-03-01

Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.

Optimization of the gypsum-based materials by the sequential simplex method

NASA Astrophysics Data System (ADS)

Doleželová, Magdalena; Vimmrová, Alena

2017-11-01

The application of the sequential simplex optimization method for the design of gypsum based materials is described. The principles of simplex method are explained and several examples of the method usage for the optimization of lightweight gypsum and ternary gypsum based materials are given. By this method lightweight gypsum based materials with desired properties and ternary gypsum based material with higher strength (16 MPa) were successfully developed. Simplex method is a useful tool for optimizing of gypsum based materials, but the objective of the optimization has to be formulated appropriately.

Optimal Reservoir Operation using Stochastic Model Predictive Control

NASA Astrophysics Data System (ADS)

Sahu, R.; McLaughlin, D.

2016-12-01

Hydropower operations are typically designed to fulfill contracts negotiated with consumers who need reliable energy supplies, despite uncertainties in reservoir inflows. In addition to providing reliable power the reservoir operator needs to take into account environmental factors such as downstream flooding or compliance with minimum flow requirements. From a dynamical systems perspective, the reservoir operating strategy must cope with conflicting objectives in the presence of random disturbances. In order to achieve optimal performance, the reservoir system needs to continually adapt to disturbances in real time. Model Predictive Control (MPC) is a real-time control technique that adapts by deriving the reservoir release at each decision time from the current state of the system. Here an ensemble-based version of MPC (SMPC) is applied to a generic reservoir to determine both the optimal power contract, considering future inflow uncertainty, and a real-time operating strategy that attempts to satisfy the contract. Contract selection and real-time operation are coupled in an optimization framework that also defines a Pareto trade off between the revenue generated from energy production and the environmental damage resulting from uncontrolled reservoir spills. Further insight is provided by a sensitivity analysis of key parameters specified in the SMPC technique. The results demonstrate that SMPC is suitable for multi-objective planning and associated real-time operation of a wide range of hydropower reservoir systems.

Mask etcher data strategy for 45nm and beyond

NASA Astrophysics Data System (ADS)

Lewington, Richard; Ibrahim, Ibrahim M.; Panayil, Sheeba; Kumar, Ajay; Yamartino, John

2006-05-01

Mask Etching for the 45nm technology node and beyond requires a system-level data and diagnostics strategy. This necessity stems from the need to control the performance of the mask etcher to increasingly stringent and diverse requirements of the mask production environment. Increasing mask costs and the capability to acquire and consolidate a wealth of data within the mask etch platform are primary motivators towards harnessing data mines for feedback into the mask etching optimization. There are offline and real-time possibilities and scenarios. Here, we discuss the data architecture, acquisition, and strategies of the Applied Materials Tetra II TM Mask Etch System.

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

Rational positive real approximations for LQG optimal compensators arising in active stabilization of flexible structures

NASA Technical Reports Server (NTRS)

Desantis, A.

1994-01-01

In this paper the approximation problem for a class of optimal compensators for flexible structures is considered. The particular case of a simply supported truss with an offset antenna is dealt with. The nonrational positive real optimal compensator transfer function is determined, and it is proposed that an approximation scheme based on a continued fraction expansion method be used. Comparison with the more popular modal expansion technique is performed in terms of stability margin and parameters sensitivity of the relative approximated closed loop transfer functions.

A heterogeneous artificial stock market model can benefit people against another financial crisis

PubMed Central

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

A heterogeneous artificial stock market model can benefit people against another financial crisis.

PubMed

Yang, Haijun; Chen, Shuheng

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

Optimized positioning of autonomous surgical lamps

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

Kang, Keeryun

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

Self-Assembled Carbon-Polyoxometalate Composites for Electrochemical Capacitors

NASA Astrophysics Data System (ADS)

Genovese, Matthew

The development of high performance yet cost effective energy storage devices is critical for enabling the growth of important emerging sectors from the internet of things to grid integration of renewable energy. Material costs are by far the largest contributor to the overall cost of energy storage devices and thus research into cost effective energy storage materials will play an important role in developing technology to meet real world storage demands. In this thesis, low cost high performance composite electrode materials for supercapacitors (SCs) have been developed through the surface modification of electrochemically double layer capacitive (EDLC) carbon substrates with pseudocapacitive Polyoxometalates (POMs). Significant fundamental contributions have been made to the understanding of all components of the composite electrode including the POM active layer, cation linker, and carbon substrate. The interaction of different POM chemistries in solution has been studied to elucidate the novel ways in which these molecules combine and the mechanism underlying this combination. A more thorough understanding regarding the cation linker's role in electrode fabrication has been developed through examining the linker properties which most strongly affect electrode performance. The development of porosity in biomass derived carbon materials has also been examined leading to important insights regarding the effect of substrate porosity on POM modification and electrochemical properties. These fundamental contributions enabled the design and performance optimization of POM-carbon composite SC electrodes. Understanding how POMs combine in solution, allowed for the development of mixed POM molecular coatings with tunable electrochemical properties. These molecular coatings were used to modify low cost biomass derived carbon substrates that had been structurally optimized to accommodate POM molecules. The resulting electrode composites utilizing low cost materials fabricated through simple scalable techniques demonstrated (i) high capacitance (361 F g-1), (ii) close to ideal pseudocapacitive behavior, (iii) stable cycling, and (iv) good rate performance.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Diamine-Functionalization of a Metal-Organic Framework Adsorbent for Superb Carbon Dioxide Adsorption and Desorption Properties.

PubMed

Lee, Woo Ram; Kim, Jeong Eun; Lee, Sung Jin; Kang, Minjung; Kang, Dong Won; Lee, Hwa Young; Hiremath, Vishwanath; Seo, Jeong Gil; Jin, Hailian; Moon, Dohyun; Cho, Moses; Jung, Yousung; Hong, Chang Seop

2018-05-25

For real-world postcombustion applications in the mitigation of CO 2 emissions using dry sorbents, adsorption and desorption behaviors should be controlled to design and fabricate prospective materials with optimal CO 2 performances. Herein, we prepared diamine-functionalized Mg 2 (dobpdc) (H 4 dobpdc=4,4'-dihydroxy-(1,1'-biphenyl)-3,3'-dicarboxylic acid). (1-diamine) with ethylenediamine (en), primary-secondary (N-ethylethylenediamine-een and N-isopropylethylenediamine-ipen), primary-tertiary, and secondary-secondary diamines. A slight alteration of the number of alkyl substituents on the diamines and their alkyl chain length dictates the desorption temperature (T des ) at 100 % CO 2 , desorption characteristics, and ΔT systematically to result in the tuning of the working capacity. The existence of bulky substituents on the diamines improves the framework stability upon exposure to O 2 , SO 2 , and water vapor, relevant to real flue-gas conditions. Bulky substituents are also responsible for an interesting two-step behavior observed for the ipen case, as revealed by DFT calculations. Among the diamine-appended metal-organic frameworks, 1-een, which has the required adsorption and desorption properties, is a promising material for sorbent-based CO 2 capture processes. Hence, CO 2 performance and framework durability can be tailored by the judicial selection of the diamine structure, which enables property design at will and facilitates the development of desirable CO 2 -capture materials. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real Estate Site Selection: An Application of Artificial Intelligence for Military Retail Facilities

DTIC Science & Technology

2006-09-01

Information and Spatial Analysis (SCGISA), University of Sheffield. Kotler , P. (1984). Marketing Management: Analysis, Planning, and Control...Spatial Distribution of Retail Sales. Journal of Real Estate Finance and Economics, Vol. 31 Iss. 1, 53. Lilien, G., & Kotler , P. (1983). Marketing ...commissaries). The current business model for military retail facilities may not be optimized based upon current trends market data. Optimizing

Dynamic Analysis of the Temperature and the Concentration Profiles of an Industrial Rotary Kiln Used in Clinker Production.

PubMed

Rodrigues, Diulia C Q; Soares, Atílio P; Costa, Esly F; Costa, Andréa O S

2017-01-01

Cement is one of the most used building materials in the world. The process of cement production involves numerous and complex reactions that occur under different temperatures. Thus, there is great interest in the optimization of cement manufacturing. Clinker production is one of the main steps of cement production and it occurs inside the kiln. In this paper, the dry process of clinker production is analysed in a rotary kiln that operates in counter flow. The main phenomena involved in clinker production is as follows: free residual water evaporation of raw material, decomposition of magnesium carbonate, decarbonation, formation of C3A and C4AF, formation of dicalcium silicate, and formation of tricalcium silicate. The main objective of this study was to propose a mathematical model that realistically describes the temperature profile and the concentration of clinker components in a real rotary kiln. In addition, the influence of different speeds of inlet gas and solids in the system was analysed. The mathematical model is composed of partial differential equations. The model was implemented in Mathcad (available at CCA/UFES) and solved using industrial input data. The proposal model is satisfactory to describe the temperature and concentration profiles of a real rotary kiln.

Tabu Search enhances network robustness under targeted attacks

NASA Astrophysics Data System (ADS)

Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi

2016-03-01

We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.

Validation of a Projection-domain Insertion of Liver Lesions into CT Images

PubMed Central

Chen, Baiyu; Ma, Chi; Leng, Shuai; Fidler, Jeff L.; Sheedy, Shannon P.; McCollough, Cynthia H.; Fletcher, Joel G.; Yu, Lifeng

2016-01-01

Rationale and Objectives The aim of this study was to validate a projection-domain lesion-insertion method with observer studies. Materials and Methods A total of 51 proven liver lesions were segmented from computed tomography images, forward projected, and inserted into patient projection data. The images containing inserted and real lesions were then reconstructed and examined in consensus by two radiologists. First, 102 lesions (51 original, 51 inserted) were viewed in a randomized, blinded fashion and scored from 1 (absolutely inserted) to 10 (absolutely real). Statistical tests were performed to compare the scores for inserted and real lesions. Subsequently, a two-alternative-forced-choice test was conducted, with lesions viewed in pairs (real vs. inserted) in a blinded fashion. The radiologists selected the inserted lesion and provided a confidence level of 1 (no confidence) to 5 (completely certain). The number of lesion pairs that were incorrectly classified was calculated. Results The scores for inserted and proven lesions had the same median (8) and similar interquartile ranges (inserted, 5.5–8; real, 6.5–8). The means scores were not significantly different between real and inserted lesions (P value = 0.17). The receiver operating characteristic curve was nearly diagonal, with an area under the curve of 0.58 ± 0.06. For the two-alternative-forced-choice study, the inserted lesions were incorrectly identified in 49% (25 out of 51) of pairs; radiologists were incorrect in 38% (3 out of 8) of pairs even when they felt very confident in identifying the inserted lesion (confidence level ≥4). Conclusions Radiologists could not distinguish between inserted and real lesions, thereby validating the lesion-insertion technique, which may be useful for conducting virtual clinical trials to optimize image quality and radiation dose. PMID:27432267

Cognitive state monitoring and the design of adaptive instruction in digital environments: lessons learned from cognitive workload assessment using a passive brain-computer interface approach

PubMed Central

Gerjets, Peter; Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Zander, Thorsten O.

2014-01-01

According to Cognitive Load Theory (CLT), one of the crucial factors for successful learning is the type and amount of working-memory load (WML) learners experience while studying instructional materials. Optimal learning conditions are characterized by providing challenges for learners without inducing cognitive over- or underload. Thus, presenting instruction in a way that WML is constantly held within an optimal range with regard to learners' working-memory capacity might be a good method to provide these optimal conditions. The current paper elaborates how digital learning environments, which achieve this goal can be developed by combining approaches from Cognitive Psychology, Neuroscience, and Computer Science. One of the biggest obstacles that needs to be overcome is the lack of an unobtrusive method of continuously assessing learners' WML in real-time. We propose to solve this problem by applying passive Brain-Computer Interface (BCI) approaches to realistic learning scenarios in digital environments. In this paper we discuss the methodological and theoretical prospects and pitfalls of this approach based on results from the literature and from our own research. We present a strategy on how several inherent challenges of applying BCIs to WML and learning can be met by refining the psychological constructs behind WML, by exploring their neural signatures, by using these insights for sophisticated task designs, and by optimizing algorithms for analyzing electroencephalography (EEG) data. Based on this strategy we applied machine-learning algorithms for cross-task classifications of different levels of WML to tasks that involve studying realistic instructional materials. We obtained very promising results that yield several recommendations for future work. PMID:25538544

Design of experiments for amino acid extraction from tobacco leaves and their subsequent determination by capillary zone electrophoresis.

PubMed

Hodek, Ondřej; Křížek, Tomáš; Coufal, Pavel; Ryšlavá, Helena

2017-03-01

In this study, we optimized a method for the determination of free amino acids in Nicotiana tabacum leaves. Capillary electrophoresis with contactless conductivity detector was used for the separation of 20 proteinogenic amino acids in acidic background electrolyte. Subsequently, the conditions of extraction with HCl were optimized for the highest extraction yield of the amino acids because sample treatment of plant materials brings some specific challenges. Central composite face-centered design with fractional factorial design was used in order to evaluate the significance of selected factors (HCl volume, HCl concentration, sonication, shaking) on the extraction process. In addition, the composite design helped us to find the optimal values for each factor using the response surface method. The limits of detection and limits of quantification for the 20 proteinogenic amino acids were found to be in the order of 10 -5 and 10 -4  mol l -1 , respectively. Addition of acetonitrile to the sample was tested as a method commonly used to decrease limits of detection. Ambiguous results of this experiment pointed out some features of plant extract samples, which often required specific approaches. Suitability of the method for metabolomic studies was tested by analysis of a real sample, in which all amino acids, except for L-methionine and L-cysteine, were successfully detected. The optimized extraction process together with the capillary electrophoresis method can be used for the determination of proteinogenic amino acids in plant materials. The resulting inexpensive, simple, and robust method is well suited for various metabolomic studies in plants. As such, the method represents a valuable tool for research and practical application in the fields of biology, biochemistry, and agriculture.

Standoff detection: distinction of bacteria by hyperspectral laser induced fluorescence

NASA Astrophysics Data System (ADS)

Walter, Arne; Duschek, Frank; Fellner, Lea; Grünewald, Karin M.; Hausmann, Anita; Julich, Sandra; Pargmann, Carsten; Tomaso, Herbert; Handke, Jürgen

2016-05-01

Sensitive detection and rapid identification of hazardous bioorganic material with high sensitivity and specificity are essential topics for defense and security. A single method can hardly cover these requirements. While point sensors allow a highly specific identification, they only provide localized information and are comparatively slow. Laser based standoff systems allow almost real-time detection and classification of potentially hazardous material in a wide area and can provide information on how the aerosol may spread. The coupling of both methods may be a promising solution to optimize the acquisition and identification of hazardous substances. The capability of the outdoor LIF system at DLR Lampoldshausen test facility as an online classification tool has already been demonstrated. Here, we present promising data for further differentiation among bacteria. Bacteria species can express unique fluorescence spectra after excitation at 280 nm and 355 nm. Upon deactivation, the spectral features change depending on the deactivation method.

Programmable and reversible plasmon mode engineering.

PubMed

Yang, Ankun; Hryn, Alexander J; Bourgeois, Marc R; Lee, Won-Kyu; Hu, Jingtian; Schatz, George C; Odom, Teri W

2016-12-13

Plasmonic nanostructures with enhanced localized optical fields as well as narrow linewidths have driven advances in numerous applications. However, the active engineering of ultranarrow resonances across the visible regime-and within a single system-has not yet been demonstrated. This paper describes how aluminum nanoparticle arrays embedded in an elastomeric slab may exhibit high-quality resonances with linewidths as narrow as 3 nm at wavelengths not accessible by conventional plasmonic materials. We exploited stretching to improve and tune simultaneously the optical response of as-fabricated nanoparticle arrays by shifting the diffraction mode relative to single-particle dipolar or quadrupolar resonances. This dynamic modulation of particle-particle spacing enabled either dipolar or quadrupolar lattice modes to be selectively accessed and individually optimized. Programmable plasmon modes offer a robust way to achieve real-time tunable materials for plasmon-enhanced molecular sensing and plasmonic nanolasers and opens new possibilities for integrating with flexible electronics.

Contact material optimization and contact physics in metal-contact microelectromechanical systems (MEMS) switches

NASA Astrophysics Data System (ADS)

Yang, Zhenyin

Metal-contact MEMS switches hold great promise for implementing agile radio frequency (RF) systems because of their small size, low fabrication cost, low power consumption, wide operational band, excellent isolation and exceptionally low signal insertion loss. Gold is often utilized as a contact material for metal-contact MEMS switches due to its excellent electrical conductivity and corrosion resistance. However contact wear and stiction are the two major failure modes for these switches due to its material softness and high surface adhesion energy. To strengthen the contact material, pure gold was alloyed with other metal elements. We designed and constructed a new micro-contacting test facility that closely mimic the typical MEMS operation and utilized this facility to efficiently evaluate optimized contact materials. Au-Ni binary alloy system as the candidate contact material for MEMS switches was systematically investigated. A correlation between contact material properties (etc. microstructure, micro-hardness, electrical resistivity, topology, surface structures and composition) and micro-contacting performance was established. It was demonstrated nano-scale graded two-phase Au-Ni film could possibly yield an improved device performance. Gold micro-contact degradation mechanisms were also systematically investigated by running the MEMS switching tests under a wide range of test conditions. According to our quantitative failure analysis, field evaporation could be the dominant failure mode for highfield (> critical threshold field) hot switching; transient thermal-assisted wear could be the dominant failure mode for low-field hot switching; on the other hand, pure mechanical wear and steady current heating (1 mA) caused much less contact degradation in cold switching tests. Results from low-force (50 muN/micro-contact), low current (0.1 mA) tests on real MEMS switches indicated that continuous adsorbed films from ambient air could degrade the switch contact resistance. Our work also contributes to the field of general nano-science and technology by resolving the transfer directionality of field evaporation of gold in atomic force microscope (AFM)/scanning tunneling microscope (STM).

Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

1999-01-01

A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy

PubMed Central

Fu, Qinyi; Martin, Benjamin L.; Matus, David Q.; Gao, Liang

2016-01-01

Despite the progress made in selective plane illumination microscopy, high-resolution 3D live imaging of multicellular specimens remains challenging. Tiling light-sheet selective plane illumination microscopy (TLS-SPIM) with real-time light-sheet optimization was developed to respond to the challenge. It improves the 3D imaging ability of SPIM in resolving complex structures and optimizes SPIM live imaging performance by using a real-time adjustable tiling light sheet and creating a flexible compromise between spatial and temporal resolution. We demonstrate the 3D live imaging ability of TLS-SPIM by imaging cellular and subcellular behaviours in live C. elegans and zebrafish embryos, and show how TLS-SPIM can facilitate cell biology research in multicellular specimens by studying left-right symmetry breaking behaviour of C. elegans embryos. PMID:27004937

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Feedback Controlled Colloidal Assembly at Fluid Interfaces

NASA Astrophysics Data System (ADS)

Bevan, Michael

The autonomous and reversible assembly of colloidal nano- and micro- scale components into ordered configurations is often suggested as a scalable process capable of manufacturing meta-materials with exotic electromagnetic properties. As a result, there is strong interest in understanding how thermal motion, particle interactions, patterned surfaces, and external fields can be optimally coupled to robustly control the assembly of colloidal components into hierarchically structured functional meta-materials. We approach this problem by directly relating equilibrium and dynamic colloidal microstructures to kT-scale energy landscapes mediated by colloidal forces, physically and chemically patterned surfaces, multiphase fluid interfaces, and electromagnetic fields. 3D colloidal trajectories are measured in real-space and real-time with nanometer resolution using an integrated suite of evanescent wave, video, and confocal microscopy methods. Equilibrium structures are connected to energy landscapes via statistical mechanical models. The dynamic evolution of initially disordered colloidal fluid configurations into colloidal crystals in the presence of tunable interactions (electromagnetic field mediated interactions, particle-interface interactions) is modeled using a novel approach based on fitting the Fokker-Planck equation to experimental microscopy and computer simulated assembly trajectories. This approach is based on the use of reaction coordinates that capture important microstructural features of crystallization processes and quantify both statistical mechanical (free energy) and fluid mechanical (hydrodynamic) contributions. Ultimately, we demonstrate real-time control of assembly, disassembly, and repair of colloidal crystals using both open loop and closed loop control to produce perfectly ordered colloidal microstructures. This approach is demonstrated for close packed colloidal crystals of spherical particles at fluid-solid interfaces and is being extended to anisotropic particles and multiphase fluid interfaces.

Optimization and Verification of Droplet Digital PCR Even-Specific Methods for the Quantification of GM Maize DAS1507 and NK603.

PubMed

Grelewska-Nowotko, Katarzyna; Żurawska-Zajfert, Magdalena; Żmijewska, Ewelina; Sowa, Sławomir

2018-05-01

In recent years, digital polymerase chain reaction (dPCR), a new molecular biology technique, has been gaining in popularity. Among many other applications, this technique can also be used for the detection and quantification of genetically modified organisms (GMOs) in food and feed. It might replace the currently widely used real-time PCR method (qPCR), by overcoming problems related to the PCR inhibition and the requirement of certified reference materials to be used as a calibrant. In theory, validated qPCR methods can be easily transferred to the dPCR platform. However, optimization of the PCR conditions might be necessary. In this study, we report the transfer of two validated qPCR methods for quantification of maize DAS1507 and NK603 events to the droplet dPCR (ddPCR) platform. After some optimization, both methods have been verified according to the guidance of the European Network of GMO Laboratories (ENGL) on analytical method verification (ENGL working group on "Method Verification." (2011) Verification of Analytical Methods for GMO Testing When Implementing Interlaboratory Validated Methods). Digital PCR methods performed equally or better than the qPCR methods. Optimized ddPCR methods confirm their suitability for GMO determination in food and feed.

Control and materials characterization System for 6T Superconducting Cryogen Free Magnet Facility at IUAC, New Delhi

NASA Astrophysics Data System (ADS)

Dutt, R. N.; Meena, D. K.; Kar, S.; Soni, V.; Nadaf, A.; Das, A.; Singh, F.; Datta, T. S.

2017-02-01

A system for carrying out automatic experimental measurements of various electrical transport characteristics and their relation to magnetic fields for samples mounted on the sample holder on a Variable Temperature Insert (VTI) of the Cryogen Free Superconducting Magnet System (CFMS) has been developed. The control and characterization system is capable of monitoring, online plotting and history logging in real-time of cryogenic temperatures with the Silicon (Si) Diode and Zirconium Oxy-Nitride sensors installed inside the magnet facility. Electrical transport property measurements have been automated with implementation of current reversal resistance measurements and automatic temperature set-point ramping with the parameters of interest available in real-time as well as for later analysis. The Graphical User Interface (GUI) based system is user friendly to facilitate operations. An ingenious electronics for reading Zirconium Oxy-Nitride temperature sensors has been used. Price to performance ratio has been optimized by using in house developed measurement techniques mixed with specialized commercial cryogenic measurement / control equipment.

Distributed behavior model orchestration in cognitive internet of things solution

NASA Astrophysics Data System (ADS)

Li, Chung-Sheng; Darema, Frederica; Chang, Victor

2018-04-01

The introduction of pervasive and ubiquitous instrumentation within Internet of Things (IoT) leads to unprecedented real-time visibility (instrumentation), optimization and fault-tolerance of the power grid, traffic, transportation, water, oil & gas, to give some examples. Interconnecting those distinct physical, people, and business worlds through ubiquitous instrumentation, even though still in its embryonic stage, has the potential to create intelligent IoT solutions that are much greener, more efficient, comfortable, and safer. An essential new direction to materialize this potential is to develop comprehensive models of such systems dynamically interacting with the instrumentation in a feed-back control loop. We describe here opportunities in applying cognitive computing on interconnected and instrumented worlds (Cognitive Internet of Things-CIoT) and call out the system-of-systems trend among distinct but interdependent worlds, and Dynamic Data-Driven Application System (DDDAS)-based methods for advanced understanding, analysis, and real-time decision support capabilities with the accuracy of full-scale models.

Development of magnetic graphene @hydrophilic polydopamine for the enrichment and analysis of phthalates in environmental water samples.

PubMed

Wang, Xianying; Song, Guoxin; Deng, Chunhui

2015-01-01

Magnetic graphene @hydrophilic polydopamine composites were successfully fabricated via a simple solvothermal reaction and self-polymerization of dopamine. Benefit from the excellent characteristics of strong magnetic responsivity, super-hydrophilicity and abundant π-electron system, the prepared material showed great potential as a magnetic solid phase extraction (MSPE) sorbent. In this work, six kinds of phthalates (PAEs) were selected as the target analytes to evaluate the extraction ability of the adsorbents combined with MSPE-GC-MS. And various extraction parameters were optimized by selecting the pH value of samples, the amount of sorbents, adsorption and desorption time, the type and volume of eluting solution. Meanwhile, the whole extraction process could be finished in 30 min. Under the optimized conditions, validations of the method were evaluated as well. And the results presented excellent linearity with a wide range of 50-20,000 μg/L (R(2)>0.9991). The detection of limits were in the range from 0.05-5 μg/L (S/N=3). Therefore, the novel magnetic graphene@polydopamine composites were successfully used as the sorbents for the enrichment and analysis of PAEs in real water samples. This proposed method provided a simple, efficient and sensitive approach for the determination of aromatic compounds in real environmental samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Road map to adaptive optimal control. [jet engine control

NASA Technical Reports Server (NTRS)

Boyer, R.

1980-01-01

A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

Optical realization of optimal symmetric real state quantum cloning machine

NASA Astrophysics Data System (ADS)

Hu, Gui-Yu; Zhang, Wen-Hai; Ye, Liu

2010-01-01

We present an experimentally uniform linear optical scheme to implement the optimal 1→2 symmetric and optimal 1→3 symmetric economical real state quantum cloning machine of the polarization state of the single photon. This scheme requires single-photon sources and two-photon polarization entangled state as input states. It also involves linear optical elements and three-photon coincidence. Then we consider the realistic realization of the scheme by using the parametric down-conversion as photon resources. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Real-Time Optimization in Complex Stochastic Environment

DTIC Science & Technology

2015-06-24

simpler ones, thus addressing scalability and the limited resources of networked wireless devices. This, however, comes at the expense of increased...Maximization of Wireless Sensor Networks with Non-ideal Batteries”, IEEE Trans. on Control of Network Systems, Vol. 1, 1, pp. 86-98, 2014. [27...C.G., “Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks ”, subm. to IEEE Trans. on Control of Network Systems

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.

A new real-time guidance strategy for aerodynamic ascent flight

NASA Astrophysics Data System (ADS)

Yamamoto, Takayuki; Kawaguchi, Jun'ichiro

2007-12-01

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

Evaluating the effects of real power losses in optimal power flow based storage integration

DOE PAGES

Castillo, Anya; Gayme, Dennice

2017-03-27

This study proposes a DC optimal power flow (DCOPF) with losses formulation (the `-DCOPF+S problem) and uses it to investigate the role of real power losses in OPF based grid-scale storage integration. We derive the `- DCOPF+S problem by augmenting a standard DCOPF with storage (DCOPF+S) problem to include quadratic real power loss approximations. This procedure leads to a multi-period nonconvex quadratically constrained quadratic program, which we prove can be solved to optimality using either a semidefinite or second order cone relaxation. Our approach has some important benefits over existing models. It is more computationally tractable than ACOPF with storagemore » (ACOPF+S) formulations and the provably exact convex relaxations guarantee that an optimal solution can be attained for a feasible problem. Adding loss approximations to a DCOPF+S model leads to a more accurate representation of locational marginal prices, which have been shown to be critical to determining optimal storage dispatch and siting in prior ACOPF+S based studies. Case studies demonstrate the improved accuracy of the `-DCOPF+S model over a DCOPF+S model and the computational advantages over an ACOPF+S formulation.« less

OPTIMIZED REAL-TIME CONTROL OF COMBINED SEWERAGE SYSTEMS: TWO CASE STUDIES

EPA Science Inventory

The paper presents results of two case studies of Real-Time Control (RTC) alternatives evaluations that were conducted on portions of sewerage systems near Paris, France and in Quebec City, Canada, respectively. The studies were performed at real-scale demonstration sites. RTC ...

Ordinal optimization and its application to complex deterministic problems

NASA Astrophysics Data System (ADS)

Yang, Mike Shang-Yu

1998-10-01

We present in this thesis a new perspective to approach a general class of optimization problems characterized by large deterministic complexities. Many problems of real-world concerns today lack analyzable structures and almost always involve high level of difficulties and complexities in the evaluation process. Advances in computer technology allow us to build computer models to simulate the evaluation process through numerical means, but the burden of high complexities remains to tax the simulation with an exorbitant computing cost for each evaluation. Such a resource requirement makes local fine-tuning of a known design difficult under most circumstances, let alone global optimization. Kolmogorov equivalence of complexity and randomness in computation theory is introduced to resolve this difficulty by converting the complex deterministic model to a stochastic pseudo-model composed of a simple deterministic component and a white-noise like stochastic term. The resulting randomness is then dealt with by a noise-robust approach called Ordinal Optimization. Ordinal Optimization utilizes Goal Softening and Ordinal Comparison to achieve an efficient and quantifiable selection of designs in the initial search process. The approach is substantiated by a case study in the turbine blade manufacturing process. The problem involves the optimization of the manufacturing process of the integrally bladed rotor in the turbine engines of U.S. Air Force fighter jets. The intertwining interactions among the material, thermomechanical, and geometrical changes makes the current FEM approach prohibitively uneconomical in the optimization process. The generalized OO approach to complex deterministic problems is applied here with great success. Empirical results indicate a saving of nearly 95% in the computing cost.

Reporter nanoparticle that monitors its anticancer efficacy in real time

PubMed Central

Kulkarni, Ashish; Rao, Poornima; Natarajan, Siva; Goldman, Aaron; Sabbisetti, Venkata S.; Khater, Yashika; Korimerla, Navya; Chandrasekar, Vineethkrishna; Mashelkar, Raghunath A.; Sengupta, Shiladitya

2016-01-01

The ability to monitor the efficacy of an anticancer treatment in real time can have a critical effect on the outcome. Currently, clinical readouts of efficacy rely on indirect or anatomic measurements, which occur over prolonged time scales postchemotherapy or postimmunotherapy and may not be concordant with the actual effect. Here we describe the biology-inspired engineering of a simple 2-in-1 reporter nanoparticle that not only delivers a cytotoxic or an immunotherapy payload to the tumor but also reports back on the efficacy in real time. The reporter nanoparticles are engineered from a novel two-staged stimuli-responsive polymeric material with an optimal ratio of an enzyme-cleavable drug or immunotherapy (effector elements) and a drug function-activatable reporter element. The spatiotemporally constrained delivery of the effector and the reporter elements in a single nanoparticle produces maximum signal enhancement due to the availability of the reporter element in the same cell as the drug, thereby effectively capturing the temporal apoptosis process. Using chemotherapy-sensitive and chemotherapy-resistant tumors in vivo, we show that the reporter nanoparticles can provide a real-time noninvasive readout of tumor response to chemotherapy. The reporter nanoparticle can also monitor the efficacy of immune checkpoint inhibition in melanoma. The self-reporting capability, for the first time to our knowledge, captures an anticancer nanoparticle in action in vivo. PMID:27036008

3D finite element modelling of sheet metal blanking process

NASA Astrophysics Data System (ADS)

Bohdal, Lukasz; Kukielka, Leon; Chodor, Jaroslaw; Kulakowska, Agnieszka; Patyk, Radoslaw; Kaldunski, Pawel

2018-05-01

The shearing process such as the blanking of sheet metals has been used often to prepare workpieces for subsequent forming operations. The use of FEM simulation is increasing for investigation and optimizing the blanking process. In the current literature a blanking FEM simulations for the limited capability and large computational cost of the three dimensional (3D) analysis has been largely limited to two dimensional (2D) plane axis-symmetry problems. However, a significant progress in modelling which takes into account the influence of real material (e.g. microstructure of the material), physical and technological conditions can be obtained by using 3D numerical analysis methods in this area. The objective of this paper is to present 3D finite element analysis of the ductile fracture, strain distribution and stress in blanking process with the assumption geometrical and physical nonlinearities. The physical, mathematical and computer model of the process are elaborated. Dynamic effects, mechanical coupling, constitutive damage law and contact friction are taken into account. The application in ANSYS/LS-DYNA program is elaborated. The effect of the main process parameter a blanking clearance on the deformation of 1018 steel and quality of the blank's sheared edge is analyzed. The results of computer simulations can be used to forecasting quality of the final parts optimization.

The maximum work principle regarded as a consequence of an optimization problem based on mechanical virtual power principle and application of constructal theory

NASA Astrophysics Data System (ADS)

Gavrus, Adinel

2017-10-01

This scientific paper proposes to prove that the maximum work principle used by theory of continuum media plasticity can be regarded as a consequence of an optimization problem based on constructal theory (prof. Adrian BEJAN). It is known that the thermodynamics define the conservation of energy and the irreversibility of natural systems evolution. From mechanical point of view the first one permits to define the momentum balance equation, respectively the virtual power principle while the second one explains the tendency of all currents to flow from high to low values. According to the constructal law all finite-size system searches to evolve in such configurations that flow more and more easily over time distributing the imperfections in order to maximize entropy and to minimize the losses or dissipations. During a material forming process the application of constructal theory principles leads to the conclusion that under external loads the material flow is that which all dissipated mechanical power (deformation and friction) become minimal. On a mechanical point of view it is then possible to formulate the real state of all mechanical variables (stress, strain, strain rate) as those that minimize the total dissipated power. So between all other virtual non-equilibrium states, the real state minimizes the total dissipated power. It can be then obtained a variational minimization problem and this paper proof in a mathematical sense that starting from this formulation can be finding in a more general form the maximum work principle together with an equivalent form for the friction term. An application in the case of a plane compression of a plastic material shows the feasibility of the proposed minimization problem formulation to find analytical solution for both cases: one without friction influence and a second which take into account Tresca friction law. To valid the proposed formulation, a comparison with a classical analytical analysis based on slices, upper/lower bound methods and numerical Finite Element simulation is also presented.

Evaluation of traffic signal timing optimization methods using a stochastic and microscopic simulation program.

DOT National Transportation Integrated Search

2003-01-01

This study evaluated existing traffic signal optimization programs including Synchro,TRANSYT-7F, and genetic algorithm optimization using real-world data collected in Virginia. As a first step, a microscopic simulation model, VISSIM, was extensively ...

RTDS implementation of an improved sliding mode based inverter controller for PV system.

PubMed

Islam, Gazi; Muyeen, S M; Al-Durra, Ahmed; Hasanien, Hany M

2016-05-01

This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

From atoms to layers: in situ gold cluster growth kinetics during sputter deposition

NASA Astrophysics Data System (ADS)

Schwartzkopf, Matthias; Buffet, Adeline; Körstgens, Volker; Metwalli, Ezzeldin; Schlage, Kai; Benecke, Gunthard; Perlich, Jan; Rawolle, Monika; Rothkirch, André; Heidmann, Berit; Herzog, Gerd; Müller-Buschbaum, Peter; Röhlsberger, Ralf; Gehrke, Rainer; Stribeck, Norbert; Roth, Stephan V.

2013-05-01

The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources.The adjustment of size-dependent catalytic, electrical and optical properties of gold cluster assemblies is a very significant issue in modern applied nanotechnology. We present a real-time investigation of the growth kinetics of gold nanostructures from small nuclei to a complete gold layer during magnetron sputter deposition with high time resolution by means of in situ microbeam grazing incidence small-angle X-ray scattering (μGISAXS). We specify the four-stage growth including their thresholds with sub-monolayer resolution and identify phase transitions monitored in Yoneda intensity as a material-specific characteristic. An innovative and flexible geometrical model enables the extraction of morphological real space parameters, such as cluster size and shape, correlation distance, layer porosity and surface coverage, directly from reciprocal space scattering data. This approach enables a large variety of future investigations of the influence of different process parameters on the thin metal film morphology. Furthermore, our study allows for deducing the wetting behavior of gold cluster films on solid substrates and provides a better understanding of the growth kinetics in general, which is essential for optimization of manufacturing parameters, saving energy and resources. Electronic supplementary information (ESI) available: The full GISAXS image sequence of the experiment, the model-based IsGISAXS-simulation sequence as movie files for comparison and detailed information about sample cleaning, XRR, FESEM, IsGISAXS, comparison μGIWAXS/μGISAXS, and sampling statistics. See DOI: 10.1039/c3nr34216f

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

PubMed

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

2017-03-01

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

Tire-road friction estimation and traction control strategy for motorized electric vehicle.

PubMed

Jin, Li-Qiang; Ling, Mingze; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS).

Tire-road friction estimation and traction control strategy for motorized electric vehicle

PubMed Central

Jin, Li-Qiang; Yue, Weiqiang

2017-01-01

In this paper, an optimal longitudinal slip ratio system for real-time identification of electric vehicle (EV) with motored wheels is proposed based on the adhesion between tire and road surface. First and foremost, the optimal longitudinal slip rate torque control can be identified in real time by calculating the derivative and slip rate of the adhesion coefficient. Secondly, the vehicle speed estimation method is also brought. Thirdly, an ideal vehicle simulation model is proposed to verify the algorithm with simulation, and we find that the slip ratio corresponds to the detection of the adhesion limit in real time. Finally, the proposed strategy is applied to traction control system (TCS). The results showed that the method can effectively identify the state of wheel and calculate the optimal slip ratio without wheel speed sensor; in the meantime, it can improve the accelerated stability of electric vehicle with traction control system (TCS). PMID:28662053

Application of ant colony optimization to optimal foragaing theory: comparison of simulation and field results

USDA-ARS?s Scientific Manuscript database

Ant Colony Optimization (ACO) refers to the family of algorithms inspired by the behavior of real ants and used to solve combinatorial problems such as the Traveling Salesman Problem (TSP).Optimal Foraging Theory (OFT) is an evolutionary principle wherein foraging organisms or insect parasites seek ...

Vortex pinning properties in Fe-chalcogenides

NASA Astrophysics Data System (ADS)

Leo, A.; Grimaldi, G.; Guarino, A.; Avitabile, F.; Nigro, A.; Galluzzi, A.; Mancusi, D.; Polichetti, M.; Pace, S.; Buchkov, K.; Nazarova, E.; Kawale, S.; Bellingeri, E.; Ferdeghini, C.

2015-12-01

Among the families of iron-based superconductors, the 11-family is one of the most attractive for high field applications at low temperatures. Optimization of the fabrication processes for bulk, crystalline and/or thin film samples is the first step in producing wires and/or tapes for practical high power conductors. Here we present the results of a comparative study of pinning properties in iron-chalcogenides, investigating the flux pinning mechanisms in optimized Fe(Se{}1-xTe x ) and FeSe samples by current-voltage characterization, magneto-resistance and magnetization measurements. In particular, from Arrhenius plots in magnetic fields up to 9 T, the activation energy is derived as a function of the magnetic field, {U}0(H), whereas the activation energy as a function of temperature, U(T), is derived from relaxation magnetization curves. The high pinning energies, high upper critical field versus temperature slopes near critical temperatures, and highly isotropic pinning properties make iron-chalcogenide superconductors a technological material which could be a real competitor to cuprate high temperature superconductors for high field applications.

Mechanical characterization of atherosclerotic arteries using finite-element modeling: feasibility study on mock arteries.

PubMed

Pazos, Valérie; Mongrain, Rosaire; Tardif, Jean-Claude

2010-06-01

Clinical studies on lipid-lowering therapy have shown that changing the composition of lipid pools reduced significantly the risk of cardiac events associated with plaque rupture. It has been shown also that changing the composition of the lipid pool affects its mechanical properties. However, knowledge about the mechanical properties of human atherosclerotic lesions remains limited due to the difficulty of the experiments. This paper aims to assess the feasibility of characterizing a lipid pool embedded in the wall of a pressurized vessel using finite-element simulations and an optimization algorithm. Finite-element simulations of inflation experiments were used together with nonlinear least squares algorithm to estimate the material model parameters of the wall and of the inclusion. An optimal fit of the simulated experiment and the real experiment was sought with the parameter estimation algorithm. The method was first tested on a single-layer polyvinyl alcohol (PVA) cryogel stenotic vessel, and then, applied on a double-layered PVA cryogel stenotic vessel with a lipid inclusion.

Optimization and Validation of Thermal Desorption Gas Chromatography-Mass Spectrometry for the Determination of Polycyclic Aromatic Hydrocarbons in Ambient Air

PubMed Central

Durana, Nieves; García, José Antonio; Gómez, María Carmen; Alonso, Lucio

2018-01-01

Thermal desorption (TD) coupled with gas chromatography/mass spectrometry (TD-GC/MS) is a simple alternative that overcomes the main drawbacks of the solvent extraction-based method: long extraction times, high sample manipulation, and large amounts of solvent waste. This work describes the optimization of TD-GC/MS for the measurement of airborne polycyclic aromatic hydrocarbons (PAHs) in particulate phase. The performance of the method was tested by Standard Reference Material (SRM) 1649b urban dust and compared with the conventional method (Soxhlet extraction-GC/MS), showing a better recovery (mean of 97%), precision (mean of 12%), and accuracy (±25%) for the determination of 14 EPA PAHs. Furthermore, other 15 nonpriority PAHs were identified and quantified using their relative response factors (RRFs). Finally, the proposed method was successfully applied for the quantification of PAHs in real 8 h-samples (PM10), demonstrating its capability for determination of these compounds in short-term monitoring. PMID:29854561

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport

PubMed Central

Pan, Wei; Guo, Ying; Jin, Lei; Liao, ShuJie

2017-01-01

With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport. PMID:28931007

Medical resource inventory model for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport.

PubMed

Pan, Wei; Guo, Ying; Jin, Lei; Liao, ShuJie

2017-01-01

With the high accident rate of civil aviation, medical resource inventory becomes more important for emergency management at the airport. Meanwhile, medical products usually are time-sensitive and short lifetime. Moreover, we find that the optimal medical resource inventory depends on multiple factors such as different risk preferences, the material shelf life and so on. Thus, it becomes very complex in a real-life environment. According to this situation, we construct medical resource inventory decision model for emergency preparation at the airport. Our model is formulated in such a way as to simultaneously consider uncertain demand, stochastic occurrence time and different risk preferences. For solving this problem, a new programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the optimal medical resource inventory for emergency preparation with uncertain demand and stochastic occurrence time under considering different risk preferences at the airport.

Highly accurate thickness measurement of multi-layered automotive paints using terahertz technology

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

Krimi, Soufiene; Beigang, René; Klier, Jens

2016-07-11

In this contribution, we present a highly accurate approach for thickness measurements of multi-layered automotive paints using terahertz time domain spectroscopy in reflection geometry. The proposed method combines the benefits of a model-based material parameters extraction method to calibrate the paint coatings, a generalized Rouard's method to simulate the terahertz radiation behavior within arbitrary thin films, and the robustness of a powerful evolutionary optimization algorithm to increase the sensitivity of the minimum thickness measurement limit. Within the framework of this work, a self-calibration model is introduced, which takes into consideration the real industrial challenges such as the effect of wet-on-wetmore » spray in the painting process.« less

Adaptive convex combination approach for the identification of improper quaternion processes.

PubMed

Ujang, Bukhari Che; Jahanchahi, Cyrus; Took, Clive Cheong; Mandic, Danilo P

2014-01-01

Data-adaptive optimal modeling and identification of real-world vector sensor data is provided by combining the fractional tap-length (FT) approach with model order selection in the quaternion domain. To account rigorously for the generality of such processes, both second-order circular (proper) and noncircular (improper), the proposed approach in this paper combines the FT length optimization with both the strictly linear quaternion least mean square (QLMS) and widely linear QLMS (WL-QLMS). A collaborative approach based on QLMS and WL-QLMS is shown to both identify the type of processes (proper or improper) and to track their optimal parameters in real time. Analysis shows that monitoring the evolution of the convex mixing parameter within the collaborative approach allows us to track the improperness in real time. Further insight into the properties of those algorithms is provided by establishing a relationship between the steady-state error and optimal model order. The approach is supported by simulations on model order selection and identification of both strictly linear and widely linear quaternion-valued systems, such as those routinely used in renewable energy (wind) and human-centered computing (biomechanics).

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Slotting optimization of automated storage and retrieval system (AS/RS) for efficient delivery of parts in an assembly shop using genetic algorithm: A case Study

NASA Astrophysics Data System (ADS)

Yue, L.; Guan, Z.; He, C.; Luo, D.; Saif, U.

2017-06-01

In recent years, the competitive pressure on manufacturing companies shifted them from mass production to mass customization to produce large variety of products. It is a great challenge for companies nowadays to produce customized mixed flow mode of production to meet customized demand on time. Due to large variety of products, the storage system to deliver variety of products to production lines influences on the timely production of variety of products, as investigated from by simulation study of an inefficient storage system of a real Company, in the current research. Therefore, current research proposed a slotting optimization model with mixed model sequence to assemble in consideration of the final flow lines to optimize whole automated storage and retrieval system (AS/RS) and distribution system in the case company. Current research is aimed to minimize vertical height of centre of gravity of AS/RS and total time spent for taking the materials out from the AS/RS simultaneously. Genetic algorithm is adopted to solve the proposed problem and computational result shows significant improvement in stability and efficiency of AS/RS as compared to the existing method used in the case company.

Progress Toward an Integration of Process-Structure-Property-Performance Models for "Three-Dimensional (3-D) Printing" of Titanium Alloys

NASA Astrophysics Data System (ADS)

Collins, P. C.; Haden, C. V.; Ghamarian, I.; Hayes, B. J.; Ales, T.; Penso, G.; Dixit, V.; Harlow, G.

2014-07-01

Electron beam direct manufacturing, synonymously known as electron beam additive manufacturing, along with other additive "3-D printing" manufacturing processes, are receiving widespread attention as a means of producing net-shape (or near-net-shape) components, owing to potential manufacturing benefits. Yet, materials scientists know that differences in manufacturing processes often significantly influence the microstructure of even widely accepted materials and, thus, impact the properties and performance of a material in service. It is important to accelerate the understanding of the processing-structure-property relationship of materials being produced via these novel approaches in a framework that considers the performance in a statistically rigorous way. This article describes the development of a process model, the assessment of key microstructural features to be incorporated into a microstructure simulation model, a novel approach to extract a constitutive equation to predict tensile properties in Ti-6Al-4V (Ti-64), and a probabilistic approach to measure the fidelity of the property model against real data. This integrated approach will provide designers a tool to vary process parameters and understand the influence on performance, enabling design and optimization for these highly visible manufacturing approaches.

Optimized Real-Time Control of Combined Sewerage Systems: Two Case Studies (Proceedings Paper)

EPA Science Inventory

The paper presents results of two case studies of Real-Time Control (RTC) alternatives evaluations that were conducted on portions of sewerage systems near Paris, France and in Quebec City, Canada, respectively. The studies were performed at real-scale demonstration sites. RTC al...

Techniques for optimizing human-machine information transfer related to real-time interactive display systems

NASA Technical Reports Server (NTRS)

Granaas, Michael M.; Rhea, Donald C.

1989-01-01

The requirements for the development of real-time displays are reviewed. Of particular interest are the psychological aspects of design such as the layout, color selection, real-time response rate, and the interactivity of displays. Some existing Western Aeronautical Test Range displays are analyzed.

Optimization of Profile and Material of Abrasive Water Jet Nozzle

NASA Astrophysics Data System (ADS)

Anand Bala Selwin, K. P.; Ramachandran, S.

2017-05-01

The objective of this work is to study the behaviour of the abrasive water jet nozzle with different profiles and materials. Taguchi-Grey relational analysis optimization technique is used to optimize the value with different material and different profiles. Initially the 3D models of the nozzle are modelled with different profiles by changing the tapered inlet angle of the nozzle. The different profile models are analysed with different materials and the results are optimized. The optimized results would give the better result taking wear and machining behaviour of the nozzle.

Computational optimization and biological evolution.

PubMed

Goryanin, Igor

2010-10-01

Modelling and optimization principles become a key concept in many biological areas, especially in biochemistry. Definitions of objective function, fitness and co-evolution, although they differ between biology and mathematics, are similar in a general sense. Although successful in fitting models to experimental data, and some biochemical predictions, optimization and evolutionary computations should be developed further to make more accurate real-life predictions, and deal not only with one organism in isolation, but also with communities of symbiotic and competing organisms. One of the future goals will be to explain and predict evolution not only for organisms in shake flasks or fermenters, but for real competitive multispecies environments.

Advanced Characterization Techniques for Sodium-Ion Battery Studies

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

Shadike, Zulipiya; Zhao, Enyue; Zhou, Yong-Ning

Sodium (Na)-ion batteries (NIBs) are considered promising alternative candidates to the well-commercialized lithium-ion batteries, especially for applications in large-scale energy storage systems. The electrochemical performance of NIBs such as the cyclability, rate capability, and voltage profiles are strongly dependent on the structural and morphological evolution, phase transformation, sodium-ion diffusion, and electrode/electrolyte interface reconstruction during charge–discharge cycling. Therefore, in-depth understanding of the structure and kinetics of electrode materials and the electrode/electrolyte interfaces is essential for optimizing current NIB systems and exploring new materials for NIBs. Recently, rapid progress and development in spectroscopic, microscopic, and scattering techniques have provided extensive insight intomore » the nature of structural evolution, morphological changes of electrode materials, and electrode/electrolyte interface in NIBs. Here in this review, a comprehensive overview of both static (ex situ) and real-time (in situ or in operando) techniques for studying the NIBs is provided. Lastly, special focus is placed on how these techniques are applied to the fundamental investigation of NIB systems and what important results are obtained.« less

Querying clinical data in HL7 RIM based relational model with morph-RDB.

PubMed

Priyatna, Freddy; Alonso-Calvo, Raul; Paraiso-Medina, Sergio; Corcho, Oscar

2017-10-05

Semantic interoperability is essential when carrying out post-genomic clinical trials where several institutions collaborate, since researchers and developers need to have an integrated view and access to heterogeneous data sources. One possible approach to accommodate this need is to use RDB2RDF systems that provide RDF datasets as the unified view. These RDF datasets may be materialized and stored in a triple store, or transformed into RDF in real time, as virtual RDF data sources. Our previous efforts involved materialized RDF datasets, hence losing data freshness. In this paper we present a solution that uses an ontology based on the HL7 v3 Reference Information Model and a set of R2RML mappings that relate this ontology to an underlying relational database implementation, and where morph-RDB is used to expose a virtual, non-materialized SPARQL endpoint over the data. By applying a set of optimization techniques on the SPARQL-to-SQL query translation algorithm, we can now issue SPARQL queries to the underlying relational data with generally acceptable performance.

The Evaluations of Hydrogen Permeation and Life Cycle Assessment on Nanocrystallined TiN-BCY Hydrogen Membrane.

PubMed

Lee, Soo-Sun; Hong, Tae-Whan

2016-02-01

Recently, Membrane technologies are used for the separation of mixtures in various industries. The promising method to reduce the CO2 emission and production of H2 from the coal based power plants is membrane separation with polymer, metal, ceramic and cermet materials. In this study, TiN ceramic material was selected, that is much less expensive than Pd. Also it has resistance to acids and chemically steady. Yttrium doped barium cerate (BCY) is a proton conductor. This perovskite exhibit both high proton conductivity and thermodynamic stability. But its chemical stability is very low under real operating environments. Thus, TiN-BCY may provide'a new membrane material for application. Life cycle assessment (LCA) based on fabrication of membrane and it was carried out to evaluate the energy demand and environmental impact. The analysis is performed according to the recommendations of ISO norms 14040 and obtained using the Gabi 6 software. This LCA will contribute to optimizing the eco-design, reducing the energy consumption and pollutant emissions during the eco-profiles of the TiN-BCY membrane.

Advanced Characterization Techniques for Sodium-Ion Battery Studies

DOE PAGES

Shadike, Zulipiya; Zhao, Enyue; Zhou, Yong-Ning; ...

2018-02-19

Sodium (Na)-ion batteries (NIBs) are considered promising alternative candidates to the well-commercialized lithium-ion batteries, especially for applications in large-scale energy storage systems. The electrochemical performance of NIBs such as the cyclability, rate capability, and voltage profiles are strongly dependent on the structural and morphological evolution, phase transformation, sodium-ion diffusion, and electrode/electrolyte interface reconstruction during charge–discharge cycling. Therefore, in-depth understanding of the structure and kinetics of electrode materials and the electrode/electrolyte interfaces is essential for optimizing current NIB systems and exploring new materials for NIBs. Recently, rapid progress and development in spectroscopic, microscopic, and scattering techniques have provided extensive insight intomore » the nature of structural evolution, morphological changes of electrode materials, and electrode/electrolyte interface in NIBs. Here in this review, a comprehensive overview of both static (ex situ) and real-time (in situ or in operando) techniques for studying the NIBs is provided. Lastly, special focus is placed on how these techniques are applied to the fundamental investigation of NIB systems and what important results are obtained.« less

Maximal near-field radiative heat transfer between two plates

NASA Astrophysics Data System (ADS)

Nefzaoui, Elyes; Ezzahri, Younès; Drévillon, Jérémie; Joulain, Karl

2013-09-01

Near-field radiative transfer is a promising way to significantly and simultaneously enhance both thermo-photovoltaic (TPV) devices power densities and efficiencies. A parametric study of Drude and Lorentz models performances in maximizing near-field radiative heat transfer between two semi-infinite planes separated by nanometric distances at room temperature is presented in this paper. Optimal parameters of these models that provide optical properties maximizing the radiative heat flux are reported and compared to real materials usually considered in similar studies, silicon carbide and heavily doped silicon in this case. Results are obtained by exact and approximate (in the extreme near-field regime and the electrostatic limit hypothesis) calculations. The two methods are compared in terms of accuracy and CPU resources consumption. Their differences are explained according to a mesoscopic description of nearfield radiative heat transfer. Finally, the frequently assumed hypothesis which states a maximal radiative heat transfer when the two semi-infinite planes are of identical materials is numerically confirmed. Its subsequent practical constraints are then discussed. Presented results enlighten relevant paths to follow in order to choose or design materials maximizing nano-TPV devices performances.

Implementing a quantum cloning machine in separate cavities via the optical coherent pulse as a quantum communication bus

NASA Astrophysics Data System (ADS)

Zhu, Meng-Zheng; Ye, Liu

2015-04-01

An efficient scheme is proposed to implement a quantum cloning machine in separate cavities based on a hybrid interaction between electron-spin systems placed in the cavities and an optical coherent pulse. The coefficient of the output state for the present cloning machine is just the direct product of two trigonometric functions, which ensures that different types of quantum cloning machine can be achieved readily in the same framework by appropriately adjusting the rotated angles. The present scheme can implement optimal one-to-two symmetric (asymmetric) universal quantum cloning, optimal symmetric (asymmetric) phase-covariant cloning, optimal symmetric (asymmetric) real-state cloning, optimal one-to-three symmetric economical real-state cloning, and optimal symmetric cloning of qubits given by an arbitrary axisymmetric distribution. In addition, photon loss of the qubus beams during the transmission and decoherence effects caused by such a photon loss are investigated.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

Optimal design and management of chlorination in drinking water networks: a multi-objective approach using Genetic Algorithms and the Pareto optimality concept

NASA Astrophysics Data System (ADS)

Nouiri, Issam

2017-11-01

This paper presents the development of multi-objective Genetic Algorithms to optimize chlorination design and management in drinking water networks (DWN). Three objectives have been considered: the improvement of the chlorination uniformity (healthy objective), the minimization of chlorine booster stations number, and the injected chlorine mass (economic objectives). The problem has been dissociated in medium and short terms ones. The proposed methodology was tested on hypothetical and real DWN. Results proved the ability of the developed optimization tool to identify relationships between the healthy and economic objectives as Pareto fronts. The proposed approach was efficient in computing solutions ensuring better chlorination uniformity while requiring the weakest injected chlorine mass when compared to other approaches. For the real DWN studied, chlorination optimization has been crowned by great improvement of free-chlorine-dosing uniformity and by a meaningful chlorine mass reduction, in comparison with the conventional chlorination.

Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

NASA Astrophysics Data System (ADS)

Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

2017-03-01

In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

Speedup of lexicographic optimization by superiorization and its applications to cancer radiotherapy treatment

NASA Astrophysics Data System (ADS)

Bonacker, Esther; Gibali, Aviv; Küfer, Karl-Heinz; Süss, Philipp

2017-04-01

Multicriteria optimization problems occur in many real life applications, for example in cancer radiotherapy treatment and in particular in intensity modulated radiation therapy (IMRT). In this work we focus on optimization problems with multiple objectives that are ranked according to their importance. We solve these problems numerically by combining lexicographic optimization with our recently proposed level set scheme, which yields a sequence of auxiliary convex feasibility problems; solved here via projection methods. The projection enables us to combine the newly introduced superiorization methodology with multicriteria optimization methods to speed up computation while guaranteeing convergence of the optimization. We demonstrate our scheme with a simple 2D academic example (used in the literature) and also present results from calculations on four real head neck cases in IMRT (Radiation Oncology of the Ludwig-Maximilians University, Munich, Germany) for two different choices of superiorization parameter sets suited to yield fast convergence for each case individually or robust behavior for all four cases.

The benefits of adaptive parametrization in multi-objective Tabu Search optimization

NASA Astrophysics Data System (ADS)

Ghisu, Tiziano; Parks, Geoffrey T.; Jaeggi, Daniel M.; Jarrett, Jerome P.; Clarkson, P. John

2010-10-01

In real-world optimization problems, large design spaces and conflicting objectives are often combined with a large number of constraints, resulting in a highly multi-modal, challenging, fragmented landscape. The local search at the heart of Tabu Search, while being one of its strengths in highly constrained optimization problems, requires a large number of evaluations per optimization step. In this work, a modification of the pattern search algorithm is proposed: this modification, based on a Principal Components' Analysis of the approximation set, allows both a re-alignment of the search directions, thereby creating a more effective parametrization, and also an informed reduction of the size of the design space itself. These changes make the optimization process more computationally efficient and more effective - higher quality solutions are identified in fewer iterations. These advantages are demonstrated on a number of standard analytical test functions (from the ZDT and DTLZ families) and on a real-world problem (the optimization of an axial compressor preliminary design).

Near-Optimal Guidance Method for Maximizing the Reachable Domain of Gliding Aircraft

NASA Astrophysics Data System (ADS)

Tsuchiya, Takeshi

This paper proposes a guidance method for gliding aircraft by using onboard computers to calculate a near-optimal trajectory in real-time, and thereby expanding the reachable domain. The results are applicable to advanced aircraft and future space transportation systems that require high safety. The calculation load of the optimal control problem that is used to maximize the reachable domain is too large for current computers to calculate in real-time. Thus the optimal control problem is divided into two problems: a gliding distance maximization problem in which the aircraft motion is limited to a vertical plane, and an optimal turning flight problem in a horizontal direction. First, the former problem is solved using a shooting method. It can be solved easily because its scale is smaller than that of the original problem, and because some of the features of the optimal solution are obtained in the first part of this paper. Next, in the latter problem, the optimal bank angle is computed from the solution of the former; this is an analytical computation, rather than an iterative computation. Finally, the reachable domain obtained from the proposed near-optimal guidance method is compared with that obtained from the original optimal control problem.

Enabling Next-Generation Multicore Platforms in Embedded Applications

DTIC Science & Technology

2014-04-01

mapping to sets 129 − 256 ) to the second page in memory, color 2 (sets 257 − 384) to the third page, and so on. Then, after the 32nd page, all 212 sets...the Real-Time Nested Locking Protocol (RNLP) [56], a recently developed multiprocessor real-time locking protocol that optimally supports the...RELEASE; DISTRIBUTION UNLIMITED 15 In general, the problems of optimally assigning tasks to processors and colors to tasks are both NP-hard in the

Canonical Duality Theory and Algorithms for Solving Some Challenging Problems in Global Optimization and Decision Science

DTIC Science & Technology

2015-09-24

algorithms for solving real- world problems. Within the past five years, 2 books, 5 journal special issues, and about 60 papers have been published...Four international conferences have been organized, including the 3rd World Congress of Global Optimization. A unified methodology and algorithm have...been developed with real- world applications. This grant has been used to support and co-support three post-doctors, three PhD students, one part

Acute stent recoil and optimal balloon inflation strategy: an experimental study using real-time optical coherence tomography.

PubMed

Kitahara, Hideki; Waseda, Katsuhisa; Yamada, Ryotaro; Otagiri, Kyuhachi; Tanaka, Shigemitsu; Kobayashi, Yuhei; Okada, Kozo; Kume, Teruyoshi; Nakagawa, Kaori; Teramoto, Tomohiko; Ikeno, Fumiaki; Yock, Paul G; Fitzgerald, Peter J; Honda, Yasuhiro

2016-06-12

Our aim was to evaluate stent expansion and acute recoil at deployment and post-dilatation, and the impact of post-dilatation strategies on final stent dimensions. Optical coherence tomography (OCT) was performed on eight bare metal platforms of drug-eluting stents (3.0 mm diameter, n=6 for each) during and after balloon inflation in a silicone mock vessel. After nominal-pressure deployment, a single long (30 sec) vs. multiple short (10 sec x3) post-dilatations were performed using a non-compliant balloon (3.25 mm, 20 atm). Stent areas during deployment with original delivery systems were smaller in stainless steel stents than in cobalt-chromium and platinum-chromium stents (p<0.001), whereas subsequent acute recoil was comparable among the three materials. At post-dilatation, acute recoil was greater in cobalt-chromium and platinum-chromium stents than in stainless steel stents (p<0.001), resulting in smaller final stent areas in cobalt-chromium and platinum-chromium stents than in stainless steel stents (p<0.001). In comparison between conventional and latest-generation cobalt-chromium stents, stent areas were not significantly different after both deployment and post-dilatation. With multiple short post-dilatations, acute recoil was significantly improved from first to third short inflation (p<0.001), achieving larger final area than a single long inflation, despite stent materials/designs (p<0.001). Real-time OCT revealed significant acute recoil in all stent types. Both stent materials/designs and post-dilatation strategies showed a significant impact on final stent expansion.

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

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

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

Suboptimal LQR-based spacecraft full motion control: Theory and experimentation

NASA Astrophysics Data System (ADS)

Guarnaccia, Leone; Bevilacqua, Riccardo; Pastorelli, Stefano P.

2016-05-01

This work introduces a real time suboptimal control algorithm for six-degree-of-freedom spacecraft maneuvering based on a State-Dependent-Algebraic-Riccati-Equation (SDARE) approach and real-time linearization of the equations of motion. The control strategy is sub-optimal since the gains of the linear quadratic regulator (LQR) are re-computed at each sample time. The cost function of the proposed controller has been compared with the one obtained via a general purpose optimal control software, showing, on average, an increase in control effort of approximately 15%, compensated by real-time implementability. Lastly, the paper presents experimental tests on a hardware-in-the-loop six-degree-of-freedom spacecraft simulator, designed for testing new guidance, navigation, and control algorithms for nano-satellites in a one-g laboratory environment. The tests show the real-time feasibility of the proposed approach.

A new ChainMail approach for real-time soft tissue simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2016-07-03

This paper presents a new ChainMail method for real-time soft tissue simulation. This method enables the use of different material properties for chain elements to accommodate various materials. Based on the ChainMail bounding region, a new time-saving scheme is developed to improve computational efficiency for isotropic materials. The proposed method also conserves volume and strain energy. Experimental results demonstrate that the proposed ChainMail method can not only accommodate isotropic, anisotropic and heterogeneous materials but also model incompressibility and relaxation behaviors of soft tissues. Further, the proposed method can achieve real-time computational performance.

Real-time powder diffraction studies of energy materials under non-equilibrium conditions

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

Peterson, Vanessa K.; Auckett, Josie E.; Pang, Wei-Kong

Energy materials form the central part of energy devices. An essential part of their function is the ability to reversibly host charge or energy carriers, and analysis of their phase composition and structure in real time under non-equilibrium conditions is mandatory for a full understanding of their atomic-scale functional mechanism. Real-time powder diffraction is increasingly being applied for this purpose, forming a critical step in the strategic chemical engineering of materials with improved behaviour. This topical review gives examples of real-time analysis using powder diffraction of rechargeable battery electrodes and porous sorbent materials used for the separation and storage ofmore » energy-relevant gases to demonstrate advances in the insights which can be gained into their atomic-scale function.« less

Real-time powder diffraction studies of energy materials under non-equilibrium conditions

PubMed Central

Peterson, Vanessa K.; Auckett, Josie E.; Pang, Wei-Kong

2017-01-01

Energy materials form the central part of energy devices. An essential part of their function is the ability to reversibly host charge or energy carriers, and analysis of their phase composition and structure in real time under non-equilibrium conditions is mandatory for a full understanding of their atomic-scale functional mechanism. Real-time powder diffraction is increasingly being applied for this purpose, forming a critical step in the strategic chemical engineering of materials with improved behaviour. This topical review gives examples of real-time analysis using powder diffraction of rechargeable battery electrodes and porous sorbent materials used for the separation and storage of energy-relevant gases to demonstrate advances in the insights which can be gained into their atomic-scale function. PMID:28989711

Experimental Optimization of Exposure Index and Quality of Service in Wlan Networks.

PubMed

Plets, David; Vermeeren, Günter; Poorter, Eli De; Moerman, Ingrid; Goudos, Sotirios K; Luc, Martens; Wout, Joseph

2017-07-01

This paper presents the first real-life optimization of the Exposure Index (EI). A genetic optimization algorithm is developed and applied to three real-life Wireless Local Area Network scenarios in an experimental testbed. The optimization accounts for downlink, uplink and uplink of other users, for realistic duty cycles, and ensures a sufficient Quality of Service to all users. EI reductions up to 97.5% compared to a reference configuration can be achieved in a downlink-only scenario, in combination with an improved Quality of Service. Due to the dominance of uplink exposure and the lack of WiFi power control, no optimizations are possible in scenarios that also consider uplink traffic. However, future deployments that do implement WiFi power control can be successfully optimized, with EI reductions up to 86% compared to a reference configuration and an EI that is 278 times lower than optimized configurations under the absence of power control. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Model Specification Searches Using Ant Colony Optimization Algorithms

ERIC Educational Resources Information Center

Marcoulides, George A.; Drezner, Zvi

2003-01-01

Ant colony optimization is a recently proposed heuristic procedure inspired by the behavior of real ants. This article applies the procedure to model specification searches in structural equation modeling and reports the results. The results demonstrate the capabilities of ant colony optimization algorithms for conducting automated searches.

Application of Odor Sensors to Ore Sorting and Mill Feed Control

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

Michael G. Nelson

2005-08-01

Control of the feed provided to mineral processing facilities is a continuing challenge. Much effort is currently being devoted to overcoming these problems. These projects are usually described under the general headings of Mine-to-Mill Integration or Mine-Mill Optimization. It should be possible to combine the knowledge of ore type, mineralogy, and other characteristics (located in the mine modeling system), with the advanced capabilities of state-of-the-art mill control systems, to achieve an improved level of control in mineral processing that will allow optimization of the mill processes on an almost real-time basis. This is not happening because mill feed it ismore » often treated as a uniform material, when in reality it varies in composition and characteristics. An investigation was conducted to assess the suitability of odor sensors for maintaining traceability in ore production and processing. Commercially available sensors are now used in food processing, environmental monitoring, and other applications and can detect the presence of very small amounts (0.1-500 ppm) of some molecules. An assortment of such molecules could be used to ''tag'' blocks of ore as they are mined, according to their respective characteristics. Then, as the ore came into the mill, an array of ''electronic noses'' could be used to assess its characteristics in real time. It was found that the Cyranose 320{trademark}, a commercially available odor sensor, can easily distinguish among samples of rock marked with almond, cinnamon, citronella, lemon, and orange oils. Further, the sensor could detect mixtures of rocks marked with various combinations of these oils. Treatment of mixtures of galena and silica with odorant compounds showed no detrimental effects on flotation response in laboratory tests. Additional work is recommended to determine how this concept can be extended to the marking of large volumes of materials.« less

Detection of Nonvolatile Inorganic Oxidizer-Based Explosives from Wipe Collections by Infrared Thermal Desorption-Direct Analysis in Real Time Mass Spectrometry.

PubMed

Forbes, Thomas P; Sisco, Edward; Staymates, Matthew

2018-05-07

Infrared thermal desorption (IRTD) was coupled with direct analysis in real time mass spectrometry (DART-MS) for the detection of both inorganic and organic explosives from wipe collected samples. This platform generated discrete and rapid heating rates that allowed volatile and semivolatile organic explosives to thermally desorb at relatively lower temperatures, while still achieving elevated temperatures required to desorb nonvolatile inorganic oxidizer-based explosives. IRTD-DART-MS demonstrated the thermal desorption and detection of refractory potassium chlorate and potassium perchlorate oxidizers, compounds difficult to desorb with traditional moderate-temperature resistance-based thermal desorbers. Nanogram to sub-nanogram sensitivities were established for analysis of a range of organic and inorganic oxidizer-based explosive compounds, with further enhancement limited by the thermal properties of the most common commercial wipe materials. Detailed investigations and high-speed visualization revealed conduction from the heated glass-mica base plate as the dominant process for heating of the wipe and analyte materials, resulting in thermal desorption through boiling, aerosolization, and vaporization of samples. The thermal desorption and ionization characteristics of the IRTD-DART technique resulted in optimal sensitivity for the formation of nitrate adducts with both organic and inorganic species. The IRTD-DART-MS coupling and IRTD in general offer promising explosive detection capabilities to the defense, security, and law enforcement arenas.

A Real-Time Brain-Machine Interface Combining Motor Target and Trajectory Intent Using an Optimal Feedback Control Design

PubMed Central

Shanechi, Maryam M.; Williams, Ziv M.; Wornell, Gregory W.; Hu, Rollin C.; Powers, Marissa; Brown, Emery N.

2013-01-01

Real-time brain-machine interfaces (BMI) have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move the prosthetic device towards a desired target while receiving real-time sensory feedback of the state of the movement. We develop a novel real-time BMI using an optimal feedback control design that jointly estimates the movement target and trajectory of monkeys in two stages. First, the target is decoded from neural spiking activity before movement initiation. Second, the trajectory is decoded by combining the decoded target with the peri-movement spiking activity using an optimal feedback control design. This design exploits a recursive Bayesian decoder that uses an optimal feedback control model of the sensorimotor system to take into account the intended target location and the sensory feedback in its trajectory estimation from spiking activity. The real-time BMI processes the spiking activity directly using point process modeling. We implement the BMI in experiments consisting of an instructed-delay center-out task in which monkeys are presented with a target location on the screen during a delay period and then have to move a cursor to it without touching the incorrect targets. We show that the two-stage BMI performs more accurately than either stage alone. Correct target prediction can compensate for inaccurate trajectory estimation and vice versa. The optimal feedback control design also results in trajectories that are smoother and have lower estimation error. The two-stage decoder also performs better than linear regression approaches in offline cross-validation analyses. Our results demonstrate the advantage of a BMI design that jointly estimates the target and trajectory of movement and more closely mimics the sensorimotor control system. PMID:23593130

Design and Characterization of an Acoustically and Structurally Matched 3-D-Printed Model for Transcranial Ultrasound Imaging.

PubMed

Bai, Chen; Ji, Meiling; Bouakaz, Ayache; Zong, Yujin; Wan, Mingxi

2018-05-01

For investigating human transcranial ultrasound imaging (TUI) through the temporal bone, an intact human skull is needed. Since it is complex and expensive to obtain one, it requires that experiments are performed without excision or abrasion of the skull. Besides, to mimic blood circulation for the vessel target, cellulose tubes generally fit the vessel simulation with straight linear features. These issues, which limit experimental studies, can be overcome by designing a 3-D-printed skull model with acoustic and dimensional properties that match a real skull and a vessel model with curve and bifurcation. First, the optimal printing material which matched a real skull in terms of the acoustic attenuation coefficient and sound propagation velocity was identified at 2-MHz frequency, i.e., 7.06 dB/mm and 2168.71 m/s for the skull while 6.98 dB/mm and 2114.72 m/s for the printed material, respectively. After modeling, the average thickness of the temporal bone in the printed skull was about 1.8 mm, while it was to 1.7 mm in the real skull. Then, a vascular phantom was designed with 3-D-printed vessels of low acoustic attenuation (0.6 dB/mm). It was covered with a porcine brain tissue contained within a transparent polyacrylamide gel. After characterizing the acoustic consistency, based on the designed skull model and vascular phantom, vessels with inner diameters of 1 and 0.7 mm were distinguished by resolution enhanced imaging with low frequency. Measurements and imaging results proved that the model and phantom are authentic and viable alternatives, and will be of interest for TUI, high intensity focused ultrasound, or other therapy studies.

Real-time Quaking-induced Conversion Assay for Detection of CWD Prions in Fecal Material.

PubMed

Cheng, Yo Ching; Hannaoui, Samia; John, Theodore Ralph; Dudas, Sandor; Czub, Stefanie; Gilch, Sabine

2017-09-29

The RT-QuIC technique is a sensitive in vitro cell-free prion amplification assay based mainly on the seeded misfolding and aggregation of recombinant prion protein (PrP) substrate using prion seeds as a template for the conversion. RT-QuIC is a novel high-throughput technique which is analogous to real-time polymerase chain reaction (PCR). Detection of amyloid fibril growth is based on the dye Thioflavin T, which fluoresces upon specific interaction with ᵦ-sheet rich proteins. Thus, amyloid formation can be detected in real time. We attempted to develop a reliable non-invasive screening test to detect chronic wasting disease (CWD) prions in fecal extract. Here, we have specifically adapted the RT-QuIC technique to reveal PrP Sc seeding activity in feces of CWD infected cervids. Initially, the seeding activity of the fecal extracts we prepared was relatively low in RT-QuIC, possibly due to potential assay inhibitors in the fecal material. To improve seeding activity of feces extracts and remove potential assay inhibitors, we homogenized the fecal samples in a buffer containing detergents and protease inhibitors. We also submitted the samples to different methodologies to concentrate PrP Sc on the basis of protein precipitation using sodium phosphotungstic acid, and centrifugal force. Finally, the feces extracts were tested by optimized RT-QuIC which included substrate replacement in the protocol to improve the sensitivity of detection. Thus, we established a protocol for sensitive detection of CWD prion seeding activity in feces of pre-clinical and clinical cervids by RT-QuIC, which can be a practical tool for non-invasive CWD diagnosis.

Simultaneous detection of ricin and abrin DNA by real-time PCR (qPCR).

PubMed

Felder, Eva; Mossbrugger, Ilona; Lange, Mirko; Wölfel, Roman

2012-09-01

Ricin and abrin are two of the most potent plant toxins known and may be easily obtained in high yield from the seeds using rather simple technology. As a result, both toxins are potent and available toxins for criminal or terrorist acts. However, as the production of highly purified ricin or abrin requires sophisticated equipment and knowledge, it may be more likely that crude extracts would be used by non-governmental perpetrators. Remaining plant-specific nucleic acids in these extracts allow the application of a real-time PCR (qPCR) assay for the detection and identification of abrin or ricin genomic material. Therefore, we have developed a duplex real-time PCR assays for simultaneous detection of ricin and abrin DNA based on the OmniMix HS bead PCR reagent mixture. Novel primers and hybridization probes were designed for detection on a SmartCycler instrument by using 5'-nuclease technology. The assay was thoroughly optimized and validated in terms of analytical sensitivity. Evaluation of the assay sensitivity by probit analysis demonstrated a 95% probability of detection at 3 genomes per reaction for ricin DNA and 1.2 genomes per reaction for abrin DNA. The suitability of the assays was exemplified by detection of ricin and abrin contaminations in a food matrix.

High-sensitivity, real-time, ratiometric imaging of surface-enhanced Raman scattering nanoparticles with a clinically translatable Raman endoscope device.

PubMed

Garai, Ellis; Sensarn, Steven; Zavaleta, Cristina L; Van de Sompel, Dominique; Loewke, Nathan O; Mandella, Michael J; Gambhir, Sanjiv S; Contag, Christopher H

2013-09-01

Topical application and quantification of targeted, surface-enhanced Raman scattering (SERS) nanoparticles offer a new technique that has the potential for early detection of epithelial cancers of hollow organs. Although less toxic than intravenous delivery, the additional washing required to remove unbound nanoparticles cannot necessarily eliminate nonspecific pooling. Therefore, we developed a real-time, ratiometric imaging technique to determine the relative concentrations of at least two spectrally unique nanoparticle types, where one serves as a nontargeted control. This approach improves the specific detection of bound, targeted nanoparticles by adjusting for working distance and for any nonspecific accumulation following washing. We engineered hardware and software to acquire SERS signals and ratios in real time and display them via a graphical user interface. We report quantitative, ratiometric imaging with nanoparticles at pM and sub-pM concentrations and at varying working distances, up to 50 mm. Additionally, we discuss optimization of a Raman endoscope by evaluating the effects of lens material and fiber coating on background noise, and theoretically modeling and simulating collection efficiency at various working distances. This work will enable the development of a clinically translatable, noncontact Raman endoscope capable of rapidly scanning large, topographically complex tissue surfaces for small and otherwise hard to detect lesions.

Optimal lattice-structured materials

DOE PAGES

Messner, Mark C.

2016-07-09

This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less

Application of tabu search to deterministic and stochastic optimization problems

NASA Astrophysics Data System (ADS)

Gurtuna, Ozgur

During the past two decades, advances in computer science and operations research have resulted in many new optimization methods for tackling complex decision-making problems. One such method, tabu search, forms the basis of this thesis. Tabu search is a very versatile optimization heuristic that can be used for solving many different types of optimization problems. Another research area, real options, has also gained considerable momentum during the last two decades. Real options analysis is emerging as a robust and powerful method for tackling decision-making problems under uncertainty. Although the theoretical foundations of real options are well-established and significant progress has been made in the theory side, applications are lagging behind. A strong emphasis on practical applications and a multidisciplinary approach form the basic rationale of this thesis. The fundamental concepts and ideas behind tabu search and real options are investigated in order to provide a concise overview of the theory supporting both of these two fields. This theoretical overview feeds into the design and development of algorithms that are used to solve three different problems. The first problem examined is a deterministic one: finding the optimal servicing tours that minimize energy and/or duration of missions for servicing satellites around Earth's orbit. Due to the nature of the space environment, this problem is modeled as a time-dependent, moving-target optimization problem. Two solution methods are developed: an exhaustive method for smaller problem instances, and a method based on tabu search for larger ones. The second and third problems are related to decision-making under uncertainty. In the second problem, tabu search and real options are investigated together within the context of a stochastic optimization problem: option valuation. By merging tabu search and Monte Carlo simulation, a new method for studying options, Tabu Search Monte Carlo (TSMC) method, is developed. The theoretical underpinnings of the TSMC method and the flow of the algorithm are explained. Its performance is compared to other existing methods for financial option valuation. In the third, and final, problem, TSMC method is used to determine the conditions of feasibility for hybrid electric vehicles and fuel cell vehicles. There are many uncertainties related to the technologies and markets associated with new generation passenger vehicles. These uncertainties are analyzed in order to determine the conditions in which new generation vehicles can compete with established technologies.

OPAD-EDIFIS Real-Time Processing

NASA Technical Reports Server (NTRS)

Katsinis, Constantine

1997-01-01

The Optical Plume Anomaly Detection (OPAD) detects engine hardware degradation of flight vehicles through identification and quantification of elemental species found in the plume by analyzing the plume emission spectra in a real-time mode. Real-time performance of OPAD relies on extensive software which must report metal amounts in the plume faster than once every 0.5 sec. OPAD software previously written by NASA scientists performed most necessary functions at speeds which were far below what is needed for real-time operation. The research presented in this report improved the execution speed of the software by optimizing the code without changing the algorithms and converting it into a parallelized form which is executed in a shared-memory multiprocessor system. The resulting code was subjected to extensive timing analysis. The report also provides suggestions for further performance improvement by (1) identifying areas of algorithm optimization, (2) recommending commercially available multiprocessor architectures and operating systems to support real-time execution and (3) presenting an initial study of fault-tolerance requirements.

A study of optimization techniques in HDR brachytherapy for the prostate

NASA Astrophysics Data System (ADS)

Pokharel, Ghana Shyam

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

Model-Data Fusion and Adaptive Sensing for Large Scale Systems: Applications to Atmospheric Release Incidents

NASA Astrophysics Data System (ADS)

Madankan, Reza

All across the world, toxic material clouds are emitted from sources, such as industrial plants, vehicular traffic, and volcanic eruptions can contain chemical, biological or radiological material. With the growing fear of natural, accidental or deliberate release of toxic agents, there is tremendous interest in precise source characterization and generating accurate hazard maps of toxic material dispersion for appropriate disaster management. In this dissertation, an end-to-end framework has been developed for probabilistic source characterization and forecasting of atmospheric release incidents. The proposed methodology consists of three major components which are combined together to perform the task of source characterization and forecasting. These components include Uncertainty Quantification, Optimal Information Collection, and Data Assimilation. Precise approximation of prior statistics is crucial to ensure performance of the source characterization process. In this work, an efficient quadrature based method has been utilized for quantification of uncertainty in plume dispersion models that are subject to uncertain source parameters. In addition, a fast and accurate approach is utilized for the approximation of probabilistic hazard maps, based on combination of polynomial chaos theory and the method of quadrature points. Besides precise quantification of uncertainty, having useful measurement data is also highly important to warranty accurate source parameter estimation. The performance of source characterization is highly affected by applied sensor orientation for data observation. Hence, a general framework has been developed for the optimal allocation of data observation sensors, to improve performance of the source characterization process. The key goal of this framework is to optimally locate a set of mobile sensors such that measurement of textit{better} data is guaranteed. This is achieved by maximizing the mutual information between model predictions and observed data, given a set of kinetic constraints on mobile sensors. Dynamic Programming method has been utilized to solve the resulting optimal control problem. To complete the loop of source characterization process, two different estimation techniques, minimum variance estimation framework and Bayesian Inference method has been developed to fuse model forecast with measurement data. Incomplete information regarding the distribution of associated noise signal in measurement data, is another major challenge in the source characterization of plume dispersion incidents. This frequently happens in data assimilation of atmospheric data by using the satellite imagery. This occurs due to the fact that satellite imagery data can be polluted with noise, depending on weather conditions, clouds, humidity, etc. Unfortunately, there is no accurate procedure to quantify the error in recorded satellite data. Hence, using classical data assimilation methods in this situation is not straight forward. In this dissertation, the basic idea of a novel approach has been proposed to tackle these types of real world problems with more accuracy and robustness. A simple example demonstrating the real-world scenario is presented to validate the developed methodology.

Optimal structural design of the midship of a VLCC based on the strategy integrating SVM and GA

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2012-03-01

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine (SVM) and genetic algorithm (GA), was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier (VLCC) ship was carried out according to the direct strength assessment method in common structural rules (CSR), which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.

Time-Frequency Distribution Analyses of Ku-Band Radar Doppler Echo Signals

NASA Astrophysics Data System (ADS)

Bujaković, Dimitrije; Andrić, Milenko; Bondžulić, Boban; Mitrović, Srđan; Simić, Slobodan

2015-03-01

Real radar echo signals of a pedestrian, vehicle and group of helicopters are analyzed in order to maximize signal energy around central Doppler frequency in time-frequency plane. An optimization, preserving this concentration, is suggested based on three well-known concentration measures. Various window functions and time-frequency distributions were optimization inputs. Conducted experiments on an analytic and three real signals have shown that energy concentration significantly depends on used time-frequency distribution and window function, for all three used criteria.

Thermal bistability-based method for real-time optimization of ultralow-threshold whispering gallery mode microlasers.

PubMed

Lin, Guoping; Candela, Y; Tillement, O; Cai, Zhiping; Lefèvre-Seguin, V; Hare, J

2012-12-15

A method based on thermal bistability for ultralow-threshold microlaser optimization is demonstrated. When sweeping the pump laser frequency across a pump resonance, the dynamic thermal bistability slows down the power variation. The resulting line shape modification enables a real-time monitoring of the laser characteristic. We demonstrate this method for a functionalized microsphere exhibiting a submicrowatt laser threshold. This approach is confirmed by comparing the results with a step-by-step recording in quasi-static thermal conditions.

Particle swarm optimization with recombination and dynamic linkage discovery.

PubMed

Chen, Ying-Ping; Peng, Wen-Chih; Jian, Ming-Chung

2007-12-01

In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 Institute of Electrical and Electronics Engineers Congress on Evolutionary Computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.

Real-time optimizations for integrated smart network camera

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Lienard, Bruno; Meessen, Jerome; Delaigle, Jean-Francois

2005-02-01

We present an integrated real-time smart network camera. This system is composed of an image sensor, an embedded PC based electronic card for image processing and some network capabilities. The application detects events of interest in visual scenes, highlights alarms and computes statistics. The system also produces meta-data information that could be shared between other cameras in a network. We describe the requirements of such a system and then show how the design of the system is optimized to process and compress video in real-time. Indeed, typical video-surveillance algorithms as background differencing, tracking and event detection should be highly optimized and simplified to be used in this hardware. To have a good adequation between hardware and software in this light embedded system, the software management is written on top of the java based middle-ware specification established by the OSGi alliance. We can integrate easily software and hardware in complex environments thanks to the Java Real-Time specification for the virtual machine and some network and service oriented java specifications (like RMI and Jini). Finally, we will report some outcomes and typical case studies of such a camera like counter-flow detection.

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

Locational Marginal Pricing in the Campus Power System at the Power Distribution Level

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

Hao, Jun; Gu, Yi; Zhang, Yingchen

2016-11-14

In the development of smart grid at distribution level, the realization of real-time nodal pricing is one of the key challenges. The research work in this paper implements and studies the methodology of locational marginal pricing at distribution level based on a real-world distribution power system. The pricing mechanism utilizes optimal power flow to calculate the corresponding distributional nodal prices. Both Direct Current Optimal Power Flow and Alternate Current Optimal Power Flow are utilized to calculate and analyze the nodal prices. The University of Denver campus power grid is used as the power distribution system test bed to demonstrate themore » pricing methodology.« less

Real-World Application of Robust Design Optimization Assisted by Response Surface Approximation and Visual Data-Mining

NASA Astrophysics Data System (ADS)

Shimoyama, Koji; Jeong, Shinkyu; Obayashi, Shigeru

A new approach for multi-objective robust design optimization was proposed and applied to a real-world design problem with a large number of objective functions. The present approach is assisted by response surface approximation and visual data-mining, and resulted in two major gains regarding computational time and data interpretation. The Kriging model for response surface approximation can markedly reduce the computational time for predictions of robustness. In addition, the use of self-organizing maps as a data-mining technique allows visualization of complicated design information between optimality and robustness in a comprehensible two-dimensional form. Therefore, the extraction and interpretation of trade-off relations between optimality and robustness of design, and also the location of sweet spots in the design space, can be performed in a comprehensive manner.

Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation

PubMed Central

Pizzolato, Claudio; Lloyd, David G.; Barrett, Rod S.; Cook, Jill L.; Zheng, Ming H.; Besier, Thor F.; Saxby, David J.

2017-01-01

Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading. PMID:29093676

Real-time optimal guidance for orbital maneuvering.

NASA Technical Reports Server (NTRS)

Cohen, A. O.; Brown, K. R.

1973-01-01

A new formulation for soft-constraint trajectory optimization is presented as a real-time optimal feedback guidance method for multiburn orbital maneuvers. Control is always chosen to minimize burn time plus a quadratic penalty for end condition errors, weighted so that early in the mission (when controllability is greatest) terminal errors are held negligible. Eventually, as controllability diminishes, the method partially relaxes but effectively still compensates perturbations in whatever subspace remains controllable. Although the soft-constraint concept is well-known in optimal control, the present formulation is novel in addressing the loss of controllability inherent in multiple burn orbital maneuvers. Moreover the necessary conditions usually obtained from a Bolza formulation are modified in this case so that the fully hard constraint formulation is a numerically well behaved subcase. As a result convergence properties have been greatly improved.

Development of polymerase chain reaction-based diagnostic tests for detection of Malsoor virus & adenovirus isolated from Rousettus species of bats in Maharashtra, India.

PubMed

Shete, Anita M; Yadav, Pragya; Kumar, Vimal; Nikam, Tushar; Mehershahi, Kurosh; Kokate, Prasad; Patil, Deepak; Mourya, Devendra T

2017-01-01

Bats are recognized as important reservoirs for emerging infectious disease and some unknown viral diseases. Two novel viruses, Malsoor virus (family Bunyaviridae, genus, Phlebovirus) and a novel adenovirus (AdV) (family, Adenoviridae genus, Mastadenovirus), were identified from Rousettus bats in the Maharashtra State of India. This study was done to develop and optimize real time reverse transcription - polymerase chain reaction (RT-PCR) assays for Malsoor virus and real time and nested PCR for adenovirus from Rousettus bats. For rapid and accurate screening of Malsoor virus and adenovirus a nested polymerase chain reaction and TaqMan-based real-time PCR were developed. Highly conserved region of nucleoprotein gene of phleboviruses and polymerase gene sequence from the Indian bat AdV isolate polyprotein gene were selected respectively for diagnostic assay development of Malsoor virus and AdV. Sensitivity and specificity of assays were calculated and optimized assays were used to screen bat samples. Molecular diagnostic assays were developed for screening of Malsoor virus and AdV and those were found to be specific. Based on the experiments performed with different parameters, nested PCR was found to be more sensitive than real-time PCR; however, for rapid screening, real-time PCR can be used and further nested PCR can be used for final confirmation or in those laboratories where real-time facility/expertise is not existing. This study reports the development and optimization of nested RT-PCR and a TaqMan-based real-time PCR for Malsoor virus and AdV. The diagnostic assays can be used for rapid detection of these novel viruses to understand their prevalence among bat population.

Individual differences in face-looking behavior generalize from the lab to the world.

PubMed

Peterson, Matthew F; Lin, Jing; Zaun, Ian; Kanwisher, Nancy

2016-05-01

Recent laboratory studies have found large, stable individual differences in the location people first fixate when identifying faces, ranging from the brows to the mouth. Importantly, this variation is strongly associated with differences in fixation-specific identification performance such that individuals' recognition ability is maximized when looking at their preferred location (Mehoudar, Arizpe, Baker, & Yovel, 2014; Peterson & Eckstein, 2013). This finding suggests that face representations are retinotopic and individuals enact gaze strategies that optimize identification, yet the extent to which this behavior reflects real-world gaze behavior is unknown. Here, we used mobile eye trackers to test whether individual differences in face gaze generalize from lab to real-world vision. In-lab fixations were measured with a speeded face identification task, while real-world behavior was measured as subjects freely walked around the Massachusetts Institute of Technology campus. We found a strong correlation between the patterns of individual differences in face gaze in the lab and real-world settings. Our findings support the hypothesis that individuals optimize real-world face identification by consistently fixating the same location and thus strongly constraining the space of retinotopic input. The methods developed for this study entailed collecting a large set of high-definition, wide field-of-view natural videos from head-mounted cameras and the viewer's fixation position, allowing us to characterize subjects' actually experienced real-world retinotopic images. These images enable us to ask how vision is optimized not just for the statistics of the "natural images" found in web databases, but of the truly natural, retinotopic images that have landed on actual human retinae during real-world experience.

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

PubMed

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Iterative optimizing quantization method for reconstructing three-dimensional images from a limited number of views

DOEpatents

Lee, Heung-Rae

1997-01-01

A three-dimensional image reconstruction method comprises treating the object of interest as a group of elements with a size that is determined by the resolution of the projection data, e.g., as determined by the size of each pixel. One of the projections is used as a reference projection. A fictitious object is arbitrarily defined that is constrained by such reference projection. The method modifies the known structure of the fictitious object by comparing and optimizing its four projections to those of the unknown structure of the real object and continues to iterate until the optimization is limited by the residual sum of background noise. The method is composed of several sub-processes that acquire four projections from the real data and the fictitious object: generate an arbitrary distribution to define the fictitious object, optimize the four projections, generate a new distribution for the fictitious object, and enhance the reconstructed image. The sub-process for the acquisition of the four projections from the input real data is simply the function of acquiring the four projections from the data of the transmitted intensity. The transmitted intensity represents the density distribution, that is, the distribution of absorption coefficients through the object.

Relations between information, time, and value of water

NASA Astrophysics Data System (ADS)

Weijs, S. V.; Galindo, L. C.

2015-12-01

This research uses with stochastic dynamic programming (SDP) as a tool to reveal economic information about managed water resources. An application to the operation of an example hydropower reservoir is presented. SDP explicitly balances the marginal value of water for immediate use and its expected opportunity cost of not having more water available for future use. The result of an SDP analysis is a steady state policy, which gives the optimal decision as a function of the state. A commonly applied form gives the optimal release as a function of the month, current reservoir level and current inflow to the reservoir. The steady state policy can be complemented with a real-time management strategy, that can depend on more real-time information. An information-theoretical perspective is given on how this information influences the value of water, and how to deal with that influence in hydropower reservoir optimization. This results in some conjectures about how the information gain from real-time operation could affect the optimal long term policy. Another issue is the sharing of increased benefits that result from this information gain in a multi-objective setting. It is argued that this should be accounted for in negotiations about an operation policy.

Optimizing Industrial Consumer Demand Response Through Disaggregation, Hour-Ahead Pricing, and Momentary Autonomous Control

NASA Astrophysics Data System (ADS)

Abdulaal, Ahmed

The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.

Dependence of behavioral performance on material category in an object grasping task with monkeys.

PubMed

Yokoi, Isao; Tachibana, Atsumichi; Minamimoto, Takafumi; Goda, Naokazu; Komatsu, Hidehiko

2018-05-02

Material perception is an essential part of our cognitive function that enables us to properly interact with our complex daily environment. One important aspect of material perception is its multimodal nature. When we see an object, we generally recognize its haptic properties as well as its visual properties. Consequently, one must examine behavior using real objects that are perceived both visually and haptically to fully understand the characteristics of material perception. As a first step, we examined whether there is any difference in the behavioral responses to different materials in monkeys trained to perform an object grasping task in which they saw and grasped rod-shaped real objects made of various materials. We found that the monkeys' behavior in the grasping task, measured based on the success rate and the pulling force, differed depending on the material category. Monkeys easily and correctly grasped objects of some materials, such as metal and glass, but failed to grasp objects of other materials. In particular, monkeys avoided grasping fur-covered objects. The differences in the behavioral responses to the material categories cannot be explained solely based on the degree of familiarity with the different materials. These results shed light on the organization of multimodal representation of materials, where their biological significance is an important factor. In addition, a monkey that avoided touching real fur-covered objects readily touched images of the same objects presented on a CRT display. This suggests employing real objects is important when studying behaviors related to material perception.

PAVENET OS: A Compact Hard Real-Time Operating System for Precise Sampling in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Saruwatari, Shunsuke; Suzuki, Makoto; Morikawa, Hiroyuki

The paper shows a compact hard real-time operating system for wireless sensor nodes called PAVENET OS. PAVENET OS provides hybrid multithreading: preemptive multithreading and cooperative multithreading. Both of the multithreading are optimized for two kinds of tasks on wireless sensor networks, and those are real-time tasks and best-effort ones. PAVENET OS can efficiently perform hard real-time tasks that cannot be performed by TinyOS. The paper demonstrates the hybrid multithreading realizes compactness and low overheads, which are comparable to those of TinyOS, through quantitative evaluation. The evaluation results show PAVENET OS performs 100 Hz sensor sampling with 0.01% jitter while performing wireless communication tasks, whereas optimized TinyOS has 0.62% jitter. In addition, PAVENET OS has a small footprint and low overheads (minimum RAM size: 29 bytes, minimum ROM size: 490 bytes, minimum task switch time: 23 cycles).

Mining hidden value through strategic real estate plans.

PubMed

Hayes, D

1998-11-01

Healthcare providers can get the most from their real estate investments if they manage them strategically rather than view them as a cost of doing business. Organizations that develop strategic real estate plans can optimize the cost-effectiveness of their assets, reduce operating costs, and create cash through disposition strategies. The cost-effectiveness of assets can be optimized by using off-balance-sheet financing structures, such as outright sale, sale-lease-back arrangements, synthetic leases, and beneficial occupancy agreements. Opportunities for cost reduction can be found by conducting operations, administrative, and maintenance reviews and cost-segregation studies. Cost-reduction efforts also should focus on ensuring space is used in the most productive manner possible and that the organization pays no more than the minimum required property tax. Disposition strategies should begin with inventorying real estate assets to identify surplus assets. Such assets then can be moved off the balance sheet or converted into commercial or public uses.

A Neuro-Musculo-Skeletal Model for Insects With Data-driven Optimization.

PubMed

Guo, Shihui; Lin, Juncong; Wöhrl, Toni; Liao, Minghong

2018-02-01

Simulating the locomotion of insects is beneficial to many areas such as experimental biology, computer animation and robotics. This work proposes a neuro-musculo-skeletal model, which integrates the biological inspirations from real insects and reproduces the gait pattern on virtual insects. The neural system is a network of spiking neurons, whose spiking patterns are controlled by the input currents. The spiking pattern provides a uniform representation of sensory information, high-level commands and control strategy. The muscle models are designed following the characteristic Hill-type muscle with customized force-length and force-velocity relationships. The model parameters, including both the neural and muscular components, are optimized via an approach of evolutionary optimization, with the data captured from real insects. The results show that the simulated gait pattern, including joint trajectories, matches the experimental data collected from real ants walking in the free mode. The simulated character is capable of moving at different directions and traversing uneven terrains.

Development, optimization, and single laboratory validation of an event-specific real-time PCR method for the detection and quantification of Golden Rice 2 using a novel taxon-specific assay.

PubMed

Jacchia, Sara; Nardini, Elena; Savini, Christian; Petrillo, Mauro; Angers-Loustau, Alexandre; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

2015-02-18

In this study, we developed, optimized, and in-house validated a real-time PCR method for the event-specific detection and quantification of Golden Rice 2, a genetically modified rice with provitamin A in the grain. We optimized and evaluated the performance of the taxon (targeting rice Phospholipase D α2 gene)- and event (targeting the 3' insert-to-plant DNA junction)-specific assays that compose the method as independent modules, using haploid genome equivalents as unit of measurement. We verified the specificity of the two real-time PCR assays and determined their dynamic range, limit of quantification, limit of detection, and robustness. We also confirmed that the taxon-specific DNA sequence is present in single copy in the rice genome and verified its stability of amplification across 132 rice varieties. A relative quantification experiment evidenced the correct performance of the two assays when used in combination.

Pruning-Based, Energy-Optimal, Deterministic I/O Device Scheduling for Hard Real-Time Systems

DTIC Science & Technology

2005-02-01

However, DPM via I/O device scheduling for hard real - time systems has received relatively little attention. In this paper,we present an offline I/O...polynomial time. We present experimental results to show that EDS and MDO reduce the energy consumption of I/O devices significantly for hard real - time systems .

The virtues of virtual reality in exposure therapy.

PubMed

Gega, Lina

2017-04-01

Virtual reality can be more effective and less burdensome than real-life exposure. Optimal virtual reality delivery should incorporate in situ direct dialogues with a therapist, discourage safety behaviours, allow for a mismatch between virtual and real exposure tasks, and encourage self-directed real-life practice between and beyond virtual reality sessions. © The Royal College of Psychiatrists 2017.

Real-time X-ray Diffraction: Applications to Materials Characterization

NASA Technical Reports Server (NTRS)

Rosemeier, R. G.

1984-01-01

With the high speed growth of materials it becomes necessary to develop measuring systems which also have the capabilities of characterizing these materials at high speeds. One of the conventional techniques of characterizing materials was X-ray diffraction. Film, which is the oldest method of recording the X-ray diffraction phenomenon, is not quite adequate in most circumstances to record fast changing events. Even though conventional proportional counters and scintillation counters can provide the speed necessary to record these changing events, they lack the ability to provide image information which may be important in some types of experiment or production arrangements. A selected number of novel applications of using X-ray diffraction to characterize materials in real-time are discussed. Also, device characteristics of some X-ray intensifiers useful in instantaneous X-ray diffraction applications briefly presented. Real-time X-ray diffraction experiments with the incorporation of image X-ray intensification add a new dimension in the characterization of materials. The uses of real-time image intensification in laboratory and production arrangements are quite unlimited and their application depends more upon the ingenuity of the scientist or engineer.

Soil tillage conservation and its effect on erosion control, water management and carbon sequestration

NASA Astrophysics Data System (ADS)

Rusu, Dr.; Gus, Dr.; Bogdan, Dr.; Moraru, Dr.; Pop, Dr.; Clapa, Dr.; Pop, Drd.

2009-04-01

The energetic function of the soil expressed through the potential energy accumulated through humus, the biogeochemical function (the circuit of the nutrient elements) are significantly influenced by its hydrophysical function and especially by the state of the bedding- consolidation, soil capacity of retaining an optimal quantity of water, and then its gradual disponibility for plant consumption. The understanding of soil functions and management including nutrient production, stocking, filtering and transforming minerals, water , organic matter , gas circuit and furnishing breeding material, all make the basis of human activity, Earth's past, present and especially future. The minimum tillage soil systems - paraplow, chisel or rotary grape - are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. By continuously applying for 10 years the minimum tillage system in a crop rotation: corn - soy-bean - wheat - potato / rape, an improvement in physical, hydro-physical and biological properties of soil was observed, together with the rebuilt of structure and increase of water permeability of soil. The minimum tillage systems ensure an adequate aerial-hydrical regime for the biological activity intensity and for the nutrients solubility equilibrium. The vegetal material remaining at the soil surface or superficially incorporated has its contribution to intensifying the biological activity, being an important resource of organic matter. The minimum tillage systems rebuild the soil structure, improving the global drainage of soil which allows a rapid infiltration of water in soil. The result is a more productive soil, better protected against wind and water erosion and needing less fuel for preparing the germination bed. Presently it is necessary a change concerning the concept of conservation practices and a new approach regarding the control of erosion. The real conservation of soil must be expanded beyond the traditional understanding of soil erosion. The real soil conservation is represented by carbon management. We need to focus to another level concerning conservation by focusing on of soil quality. Carbon management is necessary for a complex of matters including soil, water management, field productivity, biological fuel and climatic change. Profound research is necessary in order to establish the carbon sequestration practices and their implementation impact.

Soil tillage conservation and its effect on erosion control, water management and carbon sequestration

NASA Astrophysics Data System (ADS)

Rusu, T.; Gus, P.; Bogdan, I.; Moraru, P.; Pop, A.; Clapa, D.; Pop, L.

2009-04-01

The energetic function of the soil expressed through the potential energy accumulated through humus, the biogeochemical function (the circuit of the nutrient elements) are significantly influenced by its hydrophysical function and especially by the state of the bedding- consolidation, soil capacity of retaining an optimal quantity of water, and then its gradual disponibility for plant consumption. The understanding of soil functions and management including nutrient production, stocking, filtering and transforming minerals, water , organic matter, gas circuit and furnishing breeding material, all make the basis of human activity, Earth's past, present and especially future. The minimum tillage soil systems - paraplow, chisel or rotary grape - are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. By continuously applying for 10 years the minimum tillage system in a crop rotation: corn - soy-bean - wheat - potato / rape, an improvement in physical, hydro-physical and biological properties of soil was observed, together with the rebuilt of structure and increase of water permeability of soil. The minimum tillage systems ensure an adequate aerial-hydrical regime for the biological activity intensity and for the nutrients solubility equilibrium. The vegetal material remaining at the soil surface or superficially incorporated has its contribution to intensifying the biological activity, being an important resource of organic matter. The minimum tillage systems rebuild the soil structure, improving the global drainage of soil which allows a rapid infiltration of water in soil. The result is a more productive soil, better protected against wind and water erosion and needing less fuel for preparing the germination bed. Presently it is necessary a change concerning the concept of conservation practices and a new approach regarding the control of erosion. The real conservation of soil must be expanded beyond the traditional understanding of soil erosion. The real soil conservation is represented by carbon management. We need to focus to another level concerning conservation by focusing on of soil quality. Carbon management is necessary for a complex of matters including soil, water management, field productivity, biological fuel and climatic change.

Progress Towards Highly Efficient Windows for Zero—Energy Buildings

NASA Astrophysics Data System (ADS)

Selkowitz, Stephen

2008-09-01

Energy efficient windows could save 4 quads/year, with an additional 1 quad/year gain from daylighting in commercial buildings. This corresponds to 13% of energy used by US buildings and 5% of all energy used by the US. The technical potential is thus very large and the economic potential is slowly becoming a reality. This paper describes the progress in energy efficient windows that employ low-emissivity glazing, electrochromic switchable coatings and other novel materials. Dynamic systems are being developed that use sensors and controls to modulate daylighting and shading contributions in response to occupancy, comfort and energy needs. Improving the energy performance of windows involves physics in a variety of application: optics, heat transfer, materials science and applied engineering. Technical solutions must also be compatible with national policy, codes and standards, economics, business practice and investment, real and perceived risks, comfort, health, safety, productivity, amenities, and occupant preference and values. The challenge is to optimize energy performance by understanding and reinforcing the synergetic coupling between these many issues.

Determination of steroid sex hormones in wastewater by stir bar sorptive extraction based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material and liquid chromatographic analysis.

PubMed

Huang, Xiaojia; Lin, Jianbin; Yuan, Dongxing; Hu, Rongzong

2009-04-17

In this study, a simple and rapid method was developed for the determination of seven steroid hormones in wastewater. Sample preparation and analysis were performed by stir bar sorptive extraction (SBSE) based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material (SBSEM) combined with high-performance liquid chromatography with diode array detection. To achieve the optimum extraction performance, several main parameters, including extraction and desorption time, pH value and contents of inorganic salt in the sample matrix, were investigated. Under the optimized experimental conditions, the method showed good linearity and repeatability, as well as advantages such as sensitivity, simplicity, low cost and high feasibility. The extraction performance of SBSEM to the target compounds also compared with commercial SBSE which used polydimethylsiloxane as coating. Finally, the proposed method was successfully applied to the determination of the target compounds in wastewater samples. The recoveries of spiked target compounds in real samples ranged from 48.2% to 110%.

Electrochemical concentration measurements for multianalyte mixtures in simulated electrorefiner salt

NASA Astrophysics Data System (ADS)

Rappleye, Devin Spencer

The development of electroanalytical techniques in multianalyte molten salt mixtures, such as those found in used nuclear fuel electrorefiners, would enable in situ, real-time concentration measurements. Such measurements are beneficial for process monitoring, optimization and control, as well as for international safeguards and nuclear material accountancy. Electroanalytical work in molten salts has been limited to single-analyte mixtures with a few exceptions. This work builds upon the knowledge of molten salt electrochemistry by performing electrochemical measurements on molten eutectic LiCl-KCl salt mixture containing two analytes, developing techniques for quantitatively analyzing the measured signals even with an additional signal from another analyte, correlating signals to concentration and identifying improvements in experimental and analytical methodologies. (Abstract shortened by ProQuest.).

Research on a new fiber-optic axial pressure sensor of transformer winding based on fiber Bragg grating

NASA Astrophysics Data System (ADS)

Liu, Yuan; Li, Lianqing; Zhao, Lin; Wang, Jiqiang; Liu, Tongyu

2017-12-01

Based on the principle of the fiber Bragg grating, a new type of fiber-optic pressure sensor for axial force measurement of transformer winding is designed, which is designed with the structure of bending plate beam, the optimization of the packaging process, and material of the sensor. Through the calibration experiment to calibrate the sensor, the field test results of the Taikai transformer factory show that the sensitivity of the sensor is 0.133 pm/kPa and the repeatability error is 2.7% FS. The data of the fiber-optic pressure sensor in different positions maintain consistent and repeatable, which can meet the requirement of the real-time monitoring of the axial force of transformer winding.

Absorption and Emission of Light in Optoelectronic Nanomaterials: The Role of the Local Optical Environment.

PubMed

Jiménez-Solano, Alberto; Galisteo-López, Juan F; Míguez, Hernán

2018-04-19

Tailoring the interaction of electromagnetic radiation with matter is central to the development of optoelectronic devices. This becomes particularly relevant for a new generation of devices offering the possibility of solution processing with competitive efficiencies as well as new functionalities. These devices, containing novel materials such as inorganic colloidal quantum dots or hybrid organic-inorganic lead halide perovskites, commonly demand thin (tens of nanometers) active layers in order to perform optimally and thus maximizing the way electromagnetic radiation interacts with these layers is essential. In this Perspective, we discuss the relevance of tailoring the optical environment of the active layer in an optoelectronic device and illustrate it with two real-world systems comprising photovoltaic cells and light emitting devices.

Dimensionless Model of a Thermoelectric Cooling Device Operating at Real Heat Transfer Conditions: Maximum Cooling Capacity Mode

NASA Astrophysics Data System (ADS)

Melnikov, A. A.; Kostishin, V. G.; Alenkov, V. V.

2017-05-01

Real operating conditions of a thermoelectric cooling device are in the presence of thermal resistances between thermoelectric material and a heat medium or cooling object. They limit performance of a device and should be considered when modeling. Here we propose a dimensionless mathematical steady state model, which takes them into account. Analytical equations for dimensionless cooling capacity, voltage, and coefficient of performance (COP) depending on dimensionless current are given. For improved accuracy a device can be modeled with use of numerical or combined analytical-numerical methods. The results of modeling are in acceptable accordance with experimental results. The case of zero temperature difference between hot and cold heat mediums at which the maximum cooling capacity mode appears is considered in detail. Optimal device parameters for maximal cooling capacity, such as fraction of thermal conductance on the cold side y, fraction of current relative to maximal j' are estimated in range of 0.38-0.44 and 0.48-0.95, respectively, for dimensionless conductance K' = 5-100. Also, a method for determination of thermal resistances of a thermoelectric cooling system is proposed.

New generation of magnetic and luminescent nanoparticles for in vivo real-time imaging

PubMed Central

Lacroix, Lise-Marie; Delpech, Fabien; Nayral, Céline; Lachaize, Sébastien; Chaudret, Bruno

2013-01-01

A new generation of optimized contrast agents is emerging, based on metallic nanoparticles (NPs) and semiconductor nanocrystals for, respectively, magnetic resonance imaging (MRI) and near-infrared (NIR) fluorescent imaging techniques. Compared with established contrast agents, such as iron oxide NPs or organic dyes, these NPs benefit from several advantages: their magnetic and optical properties can be tuned through size, shape and composition engineering, their efficiency can exceed by several orders of magnitude that of contrast agents clinically used, their surface can be modified to incorporate specific targeting agents and antifolding polymers to increase blood circulation time and tumour recognition, and they can possibly be integrated in complex architecture to yield multi-modal imaging agents. In this review, we will report the materials of choice based on the understanding of the basic physics of NIR and MRI techniques and their corresponding syntheses as NPs. Surface engineering, water transfer and specific targeting will be highlighted prior to their first use for in vivo real-time imaging. Highly efficient NPs that are safer and target specific are likely to enter clinical application in a near future. PMID:24427542

Common Bolted Joint Analysis Tool

NASA Technical Reports Server (NTRS)

Imtiaz, Kauser

2011-01-01

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

General rules for incorporating noble metal nanoparticles in organic solar cells

NASA Astrophysics Data System (ADS)

Ciesielski, A.; Switlik, D.; Szoplik, T.

2017-05-01

Over the recent years, the influence of the addition of noble metal nanoparticles (Au, Ag, Al, Cu) into the bulk heterojunction (BHJ) solar cells on their efficiency of visible sunlight absorption has been excessively studied. However, several detailed studies were focused on compounds with similar chemical structure, and thus similar optical and electric properties. Such approach provides little help when it comes to admixing metallic nanoparticles into new compound families with different properties. Moreover, theoretical approaches frequently tend to neglect the fact, that nanoparticles have different dispersion relation than bulk material, which may lead to false conclusions. In this work, we consider additional dispersion modes in the metal permittivity due to finite size of the nanoparticles. We use Maxwell-Garnet effective medium approach (EMA), combined with the transfer matrix method, as well as finite-difference time-domain (FDTD) simulations, to create a set of general rules for incorporating noble metal nanoparticles into the active layer. These principles, based on assumed basic properties of the active layer (e.g. real and imaginary part of refractive index, thickness) provide optimal material, size spectrum and fill factor of nanoparticle inclusions in order to ensure the best absorption enhancement. Our results show, that the optimal concentrations for silver nanoparticles are about 50% greater than those determined without taking into account additional components in the permittivity of the metal.

High throughput workflow for coacervate formation and characterization in shampoo systems.

PubMed

Kalantar, T H; Tucker, C J; Zalusky, A S; Boomgaard, T A; Wilson, B E; Ladika, M; Jordan, S L; Li, W K; Zhang, X; Goh, C G

2007-01-01

Cationic cellulosic polymers find wide utility as benefit agents in shampoo. Deposition of these polymers onto hair has been shown to mend split-ends, improve appearance and wet combing, as well as provide controlled delivery of insoluble actives. The deposition is thought to be enhanced by the formation of a polymer/surfactant complex that phase-separates from the bulk solution upon dilution. A standard characterization method has been developed to characterize the coacervate formation upon dilution, but the test is time and material prohibitive. We have developed a semi-automated high throughput workflow to characterize the coacervate-forming behavior of different shampoo formulations. A procedure that allows testing of real use shampoo dilutions without first formulating a complete shampoo was identified. This procedure was adapted to a Tecan liquid handler by optimizing the parameters for liquid dispensing as well as for mixing. The high throughput workflow enabled preparation and testing of hundreds of formulations with different types and levels of cationic cellulosic polymers and surfactants, and for each formulation a haze diagram was constructed. Optimal formulations and their dilutions that give substantial coacervate formation (determined by haze measurements) were identified. Results from this high throughput workflow were shown to reproduce standard haze and bench-top turbidity measurements, and this workflow has the advantages of using less material and allowing more variables to be tested with significant time savings.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

PubMed Central

Tian, Le; Latré, Steven

2017-01-01

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

PubMed

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

Real time method and computer system for identifying radioactive materials from HPGe gamma-ray spectroscopy

DOEpatents

Rowland, Mark S.; Howard, Douglas E.; Wong, James L.; Jessup, James L.; Bianchini, Greg M.; Miller, Wayne O.

2007-10-23

A real-time method and computer system for identifying radioactive materials which collects gamma count rates from a HPGe gamma-radiation detector to produce a high-resolution gamma-ray energy spectrum. A library of nuclear material definitions ("library definitions") is provided, with each uniquely associated with a nuclide or isotope material and each comprising at least one logic condition associated with a spectral parameter of a gamma-ray energy spectrum. The method determines whether the spectral parameters of said high-resolution gamma-ray energy spectrum satisfy all the logic conditions of any one of the library definitions, and subsequently uniquely identifies the material type as that nuclide or isotope material associated with the satisfied library definition. The method is iteratively repeated to update the spectrum and identification in real time.

Real-time PCR probe optimization using design of experiments approach.

PubMed

Wadle, S; Lehnert, M; Rubenwolf, S; Zengerle, R; von Stetten, F

2016-03-01

Primer and probe sequence designs are among the most critical input factors in real-time polymerase chain reaction (PCR) assay optimization. In this study, we present the use of statistical design of experiments (DOE) approach as a general guideline for probe optimization and more specifically focus on design optimization of label-free hydrolysis probes that are designated as mediator probes (MPs), which are used in reverse transcription MP PCR (RT-MP PCR). The effect of three input factors on assay performance was investigated: distance between primer and mediator probe cleavage site; dimer stability of MP and target sequence (influenza B virus); and dimer stability of the mediator and universal reporter (UR). The results indicated that the latter dimer stability had the greatest influence on assay performance, with RT-MP PCR efficiency increased by up to 10% with changes to this input factor. With an optimal design configuration, a detection limit of 3-14 target copies/10 μl reaction could be achieved. This improved detection limit was confirmed for another UR design and for a second target sequence, human metapneumovirus, with 7-11 copies/10 μl reaction detected in an optimum case. The DOE approach for improving oligonucleotide designs for real-time PCR not only produces excellent results but may also reduce the number of experiments that need to be performed, thus reducing costs and experimental times.

Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

NASA Astrophysics Data System (ADS)

Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

2014-01-01

We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

Applications for the environment : real-time information synthesis (AERIS). Eco-lanes : operational concept.

DOT National Transportation Integrated Search

2013-10-01

This document serves as an Operational Concept for the Applications for the Environment: Real-Time Information Synthesis (AERIS) Eco-Lanes Transformative Concept. The Eco-Lanes Transformative Concept features dedicated lanes on freeways optimized for...

Topology Optimization - Engineering Contribution to Architectural Design

NASA Astrophysics Data System (ADS)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one-material problems.

Real-time parameter optimization based on neural network for smart injection molding

NASA Astrophysics Data System (ADS)

Lee, H.; Liau, Y.; Ryu, K.

2018-03-01

The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. Injection molding process has a short cycle time and high productivity. This features have been making it suitable for mass production. In addition, this process is used to produce precise parts in various industry fields such as automobiles, optics and medical devices. Injection molding process has a mixture of discrete and continuous variables. In order to optimized the quality, variables that is generated in the injection molding process must be considered. Furthermore, Optimal parameter setting is time-consuming work to predict the optimum quality of the product. Since the process parameter cannot be easily corrected during the process execution. In this research, we propose a neural network based real-time process parameter optimization methodology that sets optimal process parameters by using mold data, molding machine data, and response data. This paper is expected to have academic contribution as a novel study of parameter optimization during production compare with pre - production parameter optimization in typical studies.

Modelling energy costs for different operational strategies of a large water resource recovery facility.

PubMed

Póvoa, P; Oehmen, A; Inocêncio, P; Matos, J S; Frazão, A

2017-05-01

The main objective of this paper is to demonstrate the importance of applying dynamic modelling and real energy prices on a full scale water resource recovery facility (WRRF) for the evaluation of control strategies in terms of energy costs with aeration. The Activated Sludge Model No. 1 (ASM1) was coupled with real energy pricing and a power consumption model and applied as a dynamic simulation case study. The model calibration is based on the STOWA protocol. The case study investigates the importance of providing real energy pricing comparing (i) real energy pricing, (ii) weighted arithmetic mean energy pricing and (iii) arithmetic mean energy pricing. The operational strategies evaluated were (i) old versus new air diffusers, (ii) different DO set-points and (iii) implementation of a carbon removal controller based on nitrate sensor readings. The application in a full scale WRRF of the ASM1 model coupled with real energy costs was successful. Dynamic modelling with real energy pricing instead of constant energy pricing enables the wastewater utility to optimize energy consumption according to the real energy price structure. Specific energy cost allows the identification of time periods with potential for linking WRRF with the electric grid to optimize the treatment costs, satisfying operational goals.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Solving Energy-Aware Real-Time Tasks Scheduling Problem with Shuffled Frog Leaping Algorithm on Heterogeneous Platforms

PubMed Central

Zhang, Weizhe; Bai, Enci; He, Hui; Cheng, Albert M.K.

2015-01-01

Reducing energy consumption is becoming very important in order to keep battery life and lower overall operational costs for heterogeneous real-time multiprocessor systems. In this paper, we first formulate this as a combinatorial optimization problem. Then, a successful meta-heuristic, called Shuffled Frog Leaping Algorithm (SFLA) is proposed to reduce the energy consumption. Precocity remission and local optimal avoidance techniques are proposed to avoid the precocity and improve the solution quality. Convergence acceleration significantly reduces the search time. Experimental results show that the SFLA-based energy-aware meta-heuristic uses 30% less energy than the Ant Colony Optimization (ACO) algorithm, and 60% less energy than the Genetic Algorithm (GA) algorithm. Remarkably, the running time of the SFLA-based meta-heuristic is 20 and 200 times less than ACO and GA, respectively, for finding the optimal solution. PMID:26110406

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing.

PubMed

Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao

2017-04-01

Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.

Optimized resolved rate control of seven-degree-of-freedom Laboratory Telerobotic Manipulator (LTM) with application to three-dimensional graphics simulation

NASA Technical Reports Server (NTRS)

Barker, L. Keith; Mckinney, William S., Jr.

1989-01-01

The Laboratory Telerobotic Manipulator (LTM) is a seven-degree-of-freedom robot arm. Two of the arms were delivered to Langley Research Center for ground-based research to assess the use of redundant degree-of-freedom robot arms in space operations. Resolved-rate control equations for the LTM are derived. The equations are based on a scheme developed at the Oak Ridge National Laboratory for computing optimized joint angle rates in real time. The optimized joint angle rates actually represent a trade-off, as the hand moves, between small rates (least-squares solution) and those rates which work toward satisfying a specified performance criterion of joint angles. In singularities where the optimization scheme cannot be applied, alternate control equations are devised. The equations developed were evaluated using a real-time computer simulation to control a 3-D graphics model of the LTM.

Dynamic ADMM for Real-Time Optimal Power Flow

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

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

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of noncontrollable resources. Optimality and convergence of the proposed algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

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

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

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

PubMed

Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

2016-08-01

This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability. PMID:26880881

Linear quadratic optimization for positive LTI system

NASA Astrophysics Data System (ADS)

Muhafzan, Yenti, Syafrida Wirma; Zulakmal

2017-05-01

Nowaday the linear quadratic optimization subject to positive linear time invariant (LTI) system constitute an interesting study considering it can become a mathematical model of variety of real problem whose variables have to nonnegative and trajectories generated by these variables must be nonnegative. In this paper we propose a method to generate an optimal control of linear quadratic optimization subject to positive linear time invariant (LTI) system. A sufficient condition that guarantee the existence of such optimal control is discussed.

Comparing performances of a CdTe X-ray spectroscopic detector and an X-ray dual-energy sandwich detector

NASA Astrophysics Data System (ADS)

Gorecki, A.; Brambilla, A.; Moulin, V.; Gaborieau, E.; Radisson, P.; Verger, L.

2013-11-01

Multi-energy (ME) detectors are becoming a serious alternative to classical dual-energy sandwich (DE-S) detectors for X-ray applications such as medical imaging or explosive detection. They can use the full X-ray spectrum of irradiated materials, rather than disposing only of low and high energy measurements, which may be mixed. In this article, we intend to compare both simulated and real industrial detection systems, operating at a high count rate, independently of the dimensions of the measurements and independently of any signal processing methods. Simulations or prototypes of similar detectors have already been compared (see [1] for instance), but never independently of estimation methods and never with real detectors. We have simulated both an ME detector made of CdTe - based on the characteristics of the MultiX ME100 and - a DE-S detector - based on the characteristics of the Detection Technology's X-Card 1.5-64DE model. These detectors were compared to a perfect spectroscopic detector and an optimal DE-S detector. For comparison purposes, two approaches were investigated. The first approach addresses how to distinguise signals, while the second relates to identifying materials. Performance criteria were defined and comparisons were made over a range of material thicknesses and with different photon statistics. Experimental measurements in a specific configuration were acquired to checks simulations. Results showed good agreement between the ME simulation and the ME100 detector. Both criteria seem to be equivalent, and the ME detector performs 3.5 times better than the DE-S detector with same photon statistics based on simulations and experimental measurements. Regardless of the photon statistics ME detectors appeared more efficient than DE-S detectors for all material thicknesses between 1 and 9 cm when measuring plastics with an attenuation signature close that of explosive materials. This translates into an improved false detection rate (FDR): DE-S detectors have an FDR 2.87±0.03-fold higher than ME detectors for 4 cm of POM with 20 000 incident photons, when identifications are screened against a two-material base.

Robust portfolio selection based on asymmetric measures of variability of stock returns

NASA Astrophysics Data System (ADS)

Chen, Wei; Tan, Shaohua

2009-10-01

This paper addresses a new uncertainty set--interval random uncertainty set for robust optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming to robust mean-variance portfolio selection under interval random uncertainty sets in the elements of mean vector and covariance matrix. Numerical experiments with real market data indicate that our approach results in better portfolio performance.

DG Planning with Amalgamation of Operational and Reliability Considerations

NASA Astrophysics Data System (ADS)

Battu, Neelakanteshwar Rao; Abhyankar, A. R.; Senroy, Nilanjan

2016-04-01

Distributed Generation has been playing a vital role in dealing issues related to distribution systems. This paper presents an approach which provides policy maker with a set of solutions for DG placement to optimize reliability and real power loss of the system. Optimal location of a Distributed Generator is evaluated based on performance indices derived for reliability index and real power loss. The proposed approach is applied on a 15-bus radial distribution system and a 18-bus radial distribution system with conventional and wind distributed generators individually.

Real-time edge-enhanced optical correlator

NASA Technical Reports Server (NTRS)

Liu, Tsuen-Hsi (Inventor); Cheng, Li-Jen (Inventor)

1992-01-01

Edge enhancement of an input image by four-wave mixing a first write beam with a second write beam in a photorefractive crystal, GaAs, was achieved for VanderLugt optical correlation with an edge enhanced reference image by optimizing the power ratio of a second write beam to the first write beam (70:1) and optimizing the power ratio of a read beam, which carries the reference image to the first write beam (100:701). Liquid crystal TV panels are employed as spatial light modulators to change the input and reference images in real time.

Crowd evacuation model based on bacterial foraging algorithm

NASA Astrophysics Data System (ADS)

Shibiao, Mu; Zhijun, Chen

To understand crowd evacuation, a model based on a bacterial foraging algorithm (BFA) is proposed in this paper. Considering dynamic and static factors, the probability of pedestrian movement is established using cellular automata. In addition, given walking and queue times, a target optimization function is built. At the same time, a BFA is used to optimize the objective function. Finally, through real and simulation experiments, the relationship between the parameters of evacuation time, exit width, pedestrian density, and average evacuation speed is analyzed. The results show that the model can effectively describe a real evacuation.

SNM detection with an optimized water Cherenkov neutron detector

NASA Astrophysics Data System (ADS)

Dazeley, S.; Sweany, M.; Bernstein, A.

2012-11-01

Special Nuclear Material (SNM) can either spontaneously fission or be induced to do so: either case results in neutron emission. For this reason, neutron detection performs a crucial role in the functionality of Radiation Portal Monitoring (RPM) devices. Since neutrons are highly penetrating and difficult to shield, they could potentially be detected escaping even a well-shielded cargo container. If the shielding were sophisticated, detecting escaping neutrons would require a highly efficient detector with close to full solid angle coverage. In 2008, we reported the successful detection of neutrons with a 250 liter (l) gadolinium doped water Cherenkov prototype [1]—a technology that could potentially be employed cost effectively with full solid angle coverage. More recently we have built and tested both 1-kl and 3.5-kl versions [2], demonstrating that very large, cost effective, non-flammable and environmentally benign neutron detectors can be operated efficiently without being overwhelmed by background. In this paper, we present a new design for a modular system of water-based neutron detectors that could be deployed as a real RPM. The modules contain a number of optimizations that have not previously been combined within a single system. We present simulations of the new system, based on the performance of our previous detectors. Our simulations indicate that an optimized system such as is presented here could achieve SNM sensitivity competitive with a large 3He-based system. Moreover, the realization of large, cost effective neutron detectors could, for the first time, enable the detection of multiple neutrons per fission from within a large object such as a cargo container. Such a signal would provide a robust indication of the presence of fissioning material, reducing the frequency of false alarms while increasing sensitivity.

SNM Detection with an Optimized Water Cherenkov Neutron Detector

DOE PAGES

Dazeley, S.; Sweany, M.; Bernstein, A.

2012-07-23

Special Nuclear Material (SNM) can either spontaneously fission or be induced to do so: either case results in neutron emission. For this reason, neutron detection performs a crucial role in the functionality of Radiation Portal Monitoring (RPM) devices. Since neutrons are highly penetrating and difficult to shield, they could potentially be detected escaping even a well-shielded cargo container. If the shielding were sophisticated, detecting escaping neutrons would require a highly efficient detector with close to full solid angle coverage. In 2008, we reported the successful detection of neutrons with a 250 liter (l) gadolinium doped water Cherenkov prototype—a technology thatmore » could potentially be employed cost effectively with full solid angle coverage. More recently we have built and tested both 1-kl and 3.5-kl versions, demonstrating that very large, cost effective, non-flammable and environmentally benign neutron detectors can be operated efficiently without being overwhelmed by background. In our paper, we present a new design for a modular system of water-based neutron detectors that could be deployed as a real RPM. The modules contain a number of optimizations that have not previously been combined within a single system. We present simulations of the new system, based on the performance of our previous detectors. These simulations indicate that an optimized system such as is presented here could achieve SNM sensitivity competitive with a large 3He-based system. Moreover, the realization of large, cost effective neutron detectors could, for the first time, enable the detection of multiple neutrons per fission from within a large object such as a cargo container. Such a signal would provide a robust indication of the presence of fissioning material, reducing the frequency of false alarms while increasing sensitivity.« less

Laser tissue welding in genitourinary reconstructive surgery: assessment of optimal suture materials.

PubMed

Poppas, D P; Klioze, S D; Uzzo, R G; Schlossberg, S M

1995-02-01

Laser tissue welding in genitourinary reconstructive surgery has been shown in animal models to decrease operative time, improve healing, and decrease postoperative fistula formation when compared with conventional suture controls. Although the absence of suture material is the ultimate goal, this has not been shown to be practical with current technology for larger repairs. Therefore, suture-assisted laser tissue welding will likely be performed. This study sought to determine the optimal suture to be used during laser welding. The integrity of various organic and synthetic sutures exposed to laser irradiation were analyzed. Sutures studied included gut, clear Vicryl, clear polydioxanone suture (PDS), and violet PDS. Sutures were irradiated with a potassium titanyl phosphate (KTP)-532 laser or an 808-nm diode laser with and without the addition of a light-absorbing chromophore (fluorescein or indocyanine green, respectively). A remote temperature-sensing device obtained real-time surface temperatures during lasing. The average temperature, time, and total energy at break point were recorded. Overall, gut suture achieved significantly higher temperatures and withstood higher average energy delivery at break point with both the KTP-532 and the 808-nm diode lasers compared with all other groups (P < 0.05). Both chromophore-treated groups had higher average temperatures at break point combined with lower average energy. The break-point temperature for all groups other than gut occurred at 91 degrees C or less. The optimal temperature range for tissue welding appears to be between 60 degrees and 80 degrees C. Gut suture offers the greatest margin of error for KTP and 808-nm diode laser welding with or without the use of a chromophore.

Temperature Mapping of 3D Printed Polymer Plates: Experimental and Numerical Study

PubMed Central

Kousiatza, Charoula; Chatzidai, Nikoleta; Karalekas, Dimitris

2017-01-01

In Fused Deposition Modeling (FDM), which is a common thermoplastic Additive Manufacturing (AM) method, the polymer model material that is in the form of a flexible filament is heated above its glass transition temperature (Tg) to a semi-molten state in the head’s liquefier. The heated material is extruded in a rastering configuration onto the building platform where it rapidly cools and solidifies with the adjoining material. The heating and rapid cooling cycles of the work materials exhibited during the FDM process provoke non-uniform thermal gradients and cause stress build-up that consequently result in part distortions, dimensional inaccuracy and even possible part fabrication failure. Within the purpose of optimizing the FDM technique by eliminating the presence of such undesirable effects, real-time monitoring is essential for the evaluation and control of the final parts’ quality. The present work investigates the temperature distributions developed during the FDM building process of multilayered thin plates and on this basis a numerical study is also presented. The recordings of temperature changes were achieved by embedding temperature measuring sensors at various locations into the middle-plane of the printed structures. The experimental results, mapping the temperature variations within the samples, were compared to the corresponding ones obtained by finite element modeling, exhibiting good correlation. PMID:28245557

SU-D-218-05: Material Quantification in Spectral X-Ray Imaging: Optimization and Validation.

PubMed

Nik, S J; Thing, R S; Watts, R; Meyer, J

2012-06-01

To develop and validate a multivariate statistical method to optimize scanning parameters for material quantification in spectral x-rayimaging. An optimization metric was constructed by extensively sampling the thickness space for the expected number of counts for m (two or three) materials. This resulted in an m-dimensional confidence region ofmaterial quantities, e.g. thicknesses. Minimization of the ellipsoidal confidence region leads to the optimization of energy bins. For the given spectrum, the minimum counts required for effective material separation can be determined by predicting the signal-to-noise ratio (SNR) of the quantification. A Monte Carlo (MC) simulation framework using BEAM was developed to validate the metric. Projection data of the m-materials was generated and material decomposition was performed for combinations of iodine, calcium and water by minimizing the z-score between the expected spectrum and binned measurements. The mean square error (MSE) and variance were calculated to measure the accuracy and precision of this approach, respectively. The minimum MSE corresponds to the optimal energy bins in the BEAM simulations. In the optimization metric, this is equivalent to the smallest confidence region. The SNR of the simulated images was also compared to the predictions from the metric. TheMSE was dominated by the variance for the given material combinations,which demonstrates accurate material quantifications. The BEAMsimulations revealed that the optimization of energy bins was accurate to within 1keV. The SNRs predicted by the optimization metric yielded satisfactory agreement but were expectedly higher for the BEAM simulations due to the inclusion of scattered radiation. The validation showed that the multivariate statistical method provides accurate material quantification, correct location of optimal energy bins and adequateprediction of image SNR. The BEAM code system is suitable for generating spectral x- ray imaging simulations. © 2012 American Association of Physicists in Medicine.

A method to optimize the shield compact and lightweight combining the structure with components together by genetic algorithm and MCNP code.

PubMed

Cai, Yao; Hu, Huasi; Pan, Ziheng; Hu, Guang; Zhang, Tao

2018-05-17

To optimize the shield for neutrons and gamma rays compact and lightweight, a method combining the structure and components together was established employing genetic algorithms and MCNP code. As a typical case, the fission energy spectrum of 235 U which mixed neutrons and gamma rays was adopted in this study. Six types of materials were presented and optimized by the method. Spherical geometry was adopted in the optimization after checking the geometry effect. Simulations have made to verify the reliability of the optimization method and the efficiency of the optimized materials. To compare the materials visually and conveniently, the volume and weight needed to build a shield are employed. The results showed that, the composite multilayer material has the best performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Proposed suitable electron reflector layer materials for thin-film CuIn1-xGaxSe2 solar cells

NASA Astrophysics Data System (ADS)

Sharbati, Samaneh; Gharibshahian, Iman; Orouji, Ali A.

2018-01-01

This paper investigates the electrical properties of electron reflector layer to survey materials as an electron reflector (ER) for chalcopyrite CuInGaSe solar cells. The purpose is optimizing the conduction-band and valence-band offsets at ER layer/CIGS junction that can effectively reduce the electron recombination near the back contact. In this work, an initial device model based on an experimental solar cell is established, then the properties of a solar cell with electron reflector layer are physically analyzed. The electron reflector layer numerically applied to baseline model of thin-film CIGS cell fabricated by ZSW (efficiency = 20.3%). The improvement of efficiency is achievable by electron reflector layer materials with Eg > 1.3 eV and -0.3 < Δχ < 0.7, depends on bandgap. Our simulations examine various electron reflector layer materials and conclude the most suitable electron reflector layer for this real CIGS solar cells. ZnSnP2, CdSiAs2, GaAs, CdTe, Cu2ZnSnS4, InP, CuO, Pb10Ag3Sb11S28, CuIn5S8, SnS, PbCuSbS3, Cu3AsS4 as well as CuIn1-xGaxSe (x > 0.5) are efficient electron reflector layer materials, so the potential improvement in efficiency obtained relative gain of 5%.

Design of materials with prescribed nonlinear properties

NASA Astrophysics Data System (ADS)

Wang, F.; Sigmund, O.; Jensen, J. S.

2014-09-01

We systematically design materials using topology optimization to achieve prescribed nonlinear properties under finite deformation. Instead of a formal homogenization procedure, a numerical experiment is proposed to evaluate the material performance in longitudinal and transverse tensile tests under finite deformation, i.e. stress-strain relations and Poissons ratio. By minimizing errors between actual and prescribed properties, materials are tailored to achieve the target. Both two dimensional (2D) truss-based and continuum materials are designed with various prescribed nonlinear properties. The numerical examples illustrate optimized materials with rubber-like behavior and also optimized materials with extreme strain-independent Poissons ratio for axial strain intervals of εi∈[0.00, 0.30].

Real-time PCR method combined with immunomagnetic separation for detecting healthy and heat-injured Salmonella Typhimurium on raw duck wings.

PubMed

Zheng, Qianwang; Mikš-Krajnik, Marta; Yang, Yishan; Xu, Wang; Yuk, Hyun-Gyun

2014-09-01

Conventional culture detection methods are time consuming and labor-intensive. For this reason, an alternative rapid method combining real-time PCR and immunomagnetic separation (IMS) was investigated in this study to detect both healthy and heat-injured Salmonella Typhimurium on raw duck wings. Firstly, the IMS method was optimized by determining the capture efficiency of Dynabeads(®) on Salmonella cells on raw duck wings with different bead incubation (10, 30 and 60 min) and magnetic separation (3, 10 and 30 min) times. Secondly, three Taqman primer sets, Sal, invA and ttr, were evaluated to optimize the real-time PCR protocol by comparing five parameters: inclusivity, exclusivity, PCR efficiency, detection probability and limit of detection (LOD). Thirdly, the optimized real-time PCR, in combination with IMS (PCR-IMS) assay, was compared with a standard ISO and a real-time PCR (PCR) method by analyzing artificially inoculated raw duck wings with healthy and heat-injured Salmonella cells at 10(1) and 10(0) CFU/25 g. Finally, the optimized PCR-IMS assay was validated for Salmonella detection in naturally contaminated raw duck wing samples. Under optimal IMS conditions (30 min bead incubation and 3 min magnetic separation times), approximately 85 and 64% of S. Typhimurium cells were captured by Dynabeads® from pure culture and inoculated raw duck wings, respectively. Although Sal and ttr primers exhibited 100% inclusivity and exclusivity for 16 Salmonella spp. and 36 non-Salmonella strains, the Sal primer showed lower LOD (10(3) CFU/ml) and higher PCR efficiency (94.1%) than the invA and ttr primers. Moreover, for Sal and invA primers, 100% detection probability on raw duck wings suspension was observed at 10(3) and 10(4) CFU/ml with and without IMS, respectively. Thus, the Sal primer was chosen for further experiments. The optimized PCR-IMS method was significantly (P=0.0011) better at detecting healthy Salmonella cells after 7-h enrichment than traditional PCR method. However there was no significant difference between the two methods with longer enrichment time (14 h). The diagnostic accuracy of PCR-IMS was shown to be 98.3% through the validation study. These results indicate that the optimized PCR-IMS method in this study could provide a sensitive, specific and rapid detection method for Salmonella on raw duck wings, enabling 10-h detection. However, a longer enrichment time could be needed for resuscitation and reliable detection of heat-injured cells. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimal Design of Gradient Materials and Bi-Level Optimization of Topology Using Targets (BOTT)

NASA Astrophysics Data System (ADS)

Garland, Anthony

The objective of this research is to understand the fundamental relationships necessary to develop a method to optimize both the topology and the internal gradient material distribution of a single object while meeting constraints and conflicting objectives. Functionally gradient material (FGM) objects possess continuous varying material properties throughout the object, and they allow an engineer to tailor individual regions of an object to have specific mechanical properties by locally modifying the internal material composition. A variety of techniques exists for topology optimization, and several methods exist for FGM optimization, but combining the two together is difficult. Understanding the relationship between topology and material gradient optimization enables the selection of an appropriate model and the development of algorithms, which allow engineers to design high-performance parts that better meet design objectives than optimized homogeneous material objects. For this research effort, topology optimization means finding the optimal connected structure with an optimal shape. FGM optimization means finding the optimal macroscopic material properties within an object. Tailoring the material constitutive matrix as a function of position results in gradient properties. Once, the target macroscopic properties are known, a mesostructure or a particular material nanostructure can be found which gives the target material properties at each macroscopic point. This research demonstrates that topology and gradient materials can both be optimized together for a single part. The algorithms use a discretized model of the domain and gradient based optimization algorithms. In addition, when considering two conflicting objectives the algorithms in this research generate clear 'features' within a single part. This tailoring of material properties within different areas of a single part (automated design of 'features') using computational design tools is a novel benefit of gradient material designs. A macroscopic gradient can be achieved by varying the microstructure or the mesostructures of an object. The mesostructure interpretation allows for more design freedom since the mesostructures can be tuned to have non-isotropic material properties. A new algorithm called Bi-level Optimization of Topology using Targets (BOTT) seeks to find the best distribution of mesostructure designs throughout a single object in order to minimize an objective value. On the macro level, the BOTT algorithm optimizes the macro topology and gradient material properties within the object. The BOTT algorithm optimizes the material gradient by finding the best constitutive matrix at each location with the object. In order to enhance the likelihood that a mesostructure can be generated with the same equivalent constitutive matrix, the variability of the constitutive matrix is constrained to be an orthotropic material. The stiffness in the X and Y directions (of the base coordinate system) can change in addition to rotating the orthotropic material to align with the loading at each region. Second, the BOTT algorithm designs mesostructures with macroscopic properties equal to the target properties found in step one while at the same time the algorithm seeks to minimize material usage in each mesostructure. The mesostructure algorithm maximizes the strain energy of the mesostructures unit cell when a pseudo strain is applied to the cell. A set of experiments reveals the fundamental relationship between target cell density and the strain (or pseudo strain) applied to a unit cell and the output effective properties of the mesostructure. At low density, a few mesostructure unit cell design are possible, while at higher density the mesostructure unit cell designs have many possibilities. Therefore, at low densities the effective properties of the mesostructure are a step function of the applied pseudo strain. At high densities, the effective properties of the mesostructure are continuous function of the applied pseudo strain. Finally, the macro and mesostructure designs are coordinated so that the macro and meso levels agree on the material properties at each macro region. In addition, a coordination effort seeks to coordinate the boundaries of adjacent mesostructure designs so that the macro load path is transmitted from one mesostructure design to its neighbors. The BOTT algorithm has several advantages over existing algorithms within the literature. First, the BOTT algorithm significantly reduces the computational power required to run the algorithm. Second, the BOTT algorithm indirectly enforces a minimum mesostructure density constraint which increases the manufacturability of the final design. Third, the BOTT algorithm seeks to transfer the load from one mesostructure to its neighbors by coordinating the boundaries of adjacent mesostructure designs. However, the BOTT algorithm can still be improved since it may have difficulty converging due to the step function nature of the mesostructure design problem at low density.

Structural optimization of structured carbon-based energy-storing composite materials used in space vehicles.

PubMed

Yu, Jia; Yu, Zhichao; Tang, Chenlong

2016-07-04

The hot work environment of electronic components in the instrument cabin of spacecraft was researched, and a new thermal protection structure, namely graphite carbon foam, which is an impregnated phase-transition material, was adopted to implement the thermal control on the electronic components. We used the optimized parameters obtained from ANSYS to conduct 2D optimization, 3-D modeling and simulation, as well as the strength check. Finally, the optimization results were verified by experiments. The results showed that after optimization, the structured carbon-based energy-storing composite material could reduce the mass and realize the thermal control over electronic components. This phase-transition composite material still possesses excellent temperature control performance after its repeated melting and solidifying.

[Purifying process of gynostemma pentaphyllum saponins based on "adjoint marker" online control technology and identification of their compositions by UPLC-QTOF-MS].

PubMed

Fan, Dong-Dong; Kuang, Yan-Hui; Dong, Li-Hua; Ye, Xiao; Chen, Liang-Mian; Zhang, Dong; Ma, Zhen-Shan; Wang, Jin-Yu; Zhu, Jing-Jing; Wang, Zhi-Min; Wang, De-Qin; Li, Chu-Yuan

2017-04-01

To optimize the purification process of gynostemma pentaphyllum saponins (GPS) based on "adjoint marker" online control technology with GPS as the testing index. UPLC-QTOF-MS technology was used for qualitative analysis. "Adjoint marker" online control results showed that the end point of load sample was that the UV absorbance of effluent liquid was equal to half of that of load sample solution, and the absorbance was basically stable when the end point was stable. In UPLC-QTOF-MS qualitative analysis, 16 saponins were identified from GPS, including 13 known gynostemma saponins and 3 new saponins. This optimized method was proved to be simple, scientific, reasonable, easy for online determination, real-time record, and can be better applied to the mass production and automation of production. The results of qualitative analysis indicated that the "adjoint marker" online control technology can well retain main efficacy components of medicinal materials, and provide analysis tools for the process control and quality traceability. Copyright© by the Chinese Pharmaceutical Association.

Ultrathin-shell boron nitride hollow spheres as sorbent for dispersive solid-phase extraction of polychlorinated biphenyls from environmental water samples.

PubMed

Fu, Meizhen; Xing, Hanzhu; Chen, Xiangfeng; Chen, Fan; Wu, Chi-Man Lawrence; Zhao, Rusong; Cheng, Chuange

2014-11-21

Boron nitride hollow spheres with ultrathin-shells were synthesized and used as sorbents for dispersive solid-phase extraction of aromatic pollutants at trace levels from environmental water samples. Polychlorinated biphenyls (PCBs) were selected as target compounds. Sample quantification and detection were performed by gas chromatography-tandem mass spectrometry. Extraction parameters influencing the extraction efficiency were optimized through response surface methodology using the Box-Behnken design. The proposed method achieved good linearity within the concentration range of 0.15-250 ng L(-1) PCBs, low limits of detection (0.04-0.09 ng L(-1), S/N=3:1), good repeatability of the extractions (relative standard deviation, <12%, n=6), and satisfactory recoveries between 84.9% and 101.0% under optimal conditions. Real environmental samples collected from rivers, local lakes, rain and spring waters were analyzed using the developed method. Results demonstrated that the hexagonal boron nitride-based material has significant potential as a sorbent for organic pollutant extraction from environmental water samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Electronic Structure of Semiconductor Interfaces.

DTIC Science & Technology

1984-11-01

Workshop on Effective One-Electron Potentials In Real Materials, Ossining , New York, Mar. 21-22, 1980 Member, Organizing Committee, Annual Conferences on...Workshop on Effective One-Electron Potentials in Real Materials, Ossining , New York, Mar. 21-22, 1980 (Invited Paper) Electronic Structure of

A preliminary study to metaheuristic approach in multilayer radiation shielding optimization

NASA Astrophysics Data System (ADS)

Arif Sazali, Muhammad; Rashid, Nahrul Khair Alang Md; Hamzah, Khaidzir

2018-01-01

Metaheuristics are high-level algorithmic concepts that can be used to develop heuristic optimization algorithms. One of their applications is to find optimal or near optimal solutions to combinatorial optimization problems (COPs) such as scheduling, vehicle routing, and timetabling. Combinatorial optimization deals with finding optimal combinations or permutations in a given set of problem components when exhaustive search is not feasible. A radiation shield made of several layers of different materials can be regarded as a COP. The time taken to optimize the shield may be too high when several parameters are involved such as the number of materials, the thickness of layers, and the arrangement of materials. Metaheuristics can be applied to reduce the optimization time, trading guaranteed optimal solutions for near-optimal solutions in comparably short amount of time. The application of metaheuristics for radiation shield optimization is lacking. In this paper, we present a review on the suitability of using metaheuristics in multilayer shielding design, specifically the genetic algorithm and ant colony optimization algorithm (ACO). We would also like to propose an optimization model based on the ACO method.

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.

PubMed

Jiang, Hao; Ching, Wai-Ki; Qiu, Yushan; Cheng, Xiao-Qing

2017-12-14

Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applications do not produce positive semi-definite kernels. We propose projection method by constructing projection matrix on indefinite kernels. As a generalization of the spectrum method (denoising method and flipping method), the projection method shows better or comparable performance comparing to the corresponding indefinite kernel methods on a number of real world data sets. Under the Bregman matrix divergence theory, we can find suggested optimal λ in projection method using unconstrained optimization in kernel learning. In this paper we focus on optimal λ determination, in the pursuit of precise optimal λ determination method in unconstrained optimization framework. We developed a perturbed von-Neumann divergence to measure kernel relationships. We compared optimal λ determination with Logdet Divergence and perturbed von-Neumann Divergence, aiming at finding better λ in projection method. Results on a number of real world data sets show that projection method with optimal λ by Logdet divergence demonstrate near optimal performance. And the perturbed von-Neumann Divergence can help determine a relatively better optimal projection method. Projection method ia easy to use for dealing with indefinite kernels. And the parameter embedded in the method can be determined through unconstrained optimization under Bregman matrix divergence theory. This may provide a new way in kernel SVMs for varied objectives.

Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation

NASA Technical Reports Server (NTRS)

Clifton, C.; Homaifax, A.; Bikdash, M.

1997-01-01

This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

NASA Technical Reports Server (NTRS)

Baskaran, Subbiah; Noever, D.

1999-01-01

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

Detection of caffeine in tea, instant coffee, green tea beverage, and soft drink by direct analysis in real time (DART) source coupled to single-quadrupole mass spectrometry.

PubMed

Wang, Lei; Zhao, Pengyue; Zhang, Fengzu; Bai, Aijuan; Pan, Canping

2013-01-01

Ambient ionization direct analysis in real time (DART) coupled to single-quadrupole MS (DART-MS) was evaluated for rapid detection of caffeine in commercial samples without chromatographic separation or sample preparation. Four commercial samples were examined: tea, instant coffee, green tea beverage, and soft drink. The response-related parameters were optimized for the DART temperature and MS fragmentor. Under optimal conditions, the molecular ion (M+H)+ was the major ion for identification of caffeine. The results showed that DART-MS is a promising tool for the quick analysis of important marker molecules in commercial samples. Furthermore, this system has demonstrated significant potential for high sample throughput and real-time analysis.

Singular perturbation techniques for real time aircraft trajectory optimization and control

NASA Technical Reports Server (NTRS)

Calise, A. J.; Moerder, D. D.

1982-01-01

The usefulness of singular perturbation methods for developing real time computer algorithms to control and optimize aircraft flight trajectories is examined. A minimum time intercept problem using F-8 aerodynamic and propulsion data is used as a baseline. This provides a framework within which issues relating to problem formulation, solution methodology and real time implementation are examined. Theoretical questions relating to separability of dynamics are addressed. With respect to implementation, situations leading to numerical singularities are identified, and procedures for dealing with them are outlined. Also, particular attention is given to identifying quantities that can be precomputed and stored, thus greatly reducing the on-board computational load. Numerical results are given to illustrate the minimum time algorithm, and the resulting flight paths. An estimate is given for execution time and storage requirements.

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric

2016-01-01

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

PubMed

Foo, Brian; van der Schaar, Mihaela

2010-11-01

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

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

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Iterative optimizing quantization method for reconstructing three-dimensional images from a limited number of views

DOEpatents

Lee, H.R.

1997-11-18

A three-dimensional image reconstruction method comprises treating the object of interest as a group of elements with a size that is determined by the resolution of the projection data, e.g., as determined by the size of each pixel. One of the projections is used as a reference projection. A fictitious object is arbitrarily defined that is constrained by such reference projection. The method modifies the known structure of the fictitious object by comparing and optimizing its four projections to those of the unknown structure of the real object and continues to iterate until the optimization is limited by the residual sum of background noise. The method is composed of several sub-processes that acquire four projections from the real data and the fictitious object: generate an arbitrary distribution to define the fictitious object, optimize the four projections, generate a new distribution for the fictitious object, and enhance the reconstructed image. The sub-process for the acquisition of the four projections from the input real data is simply the function of acquiring the four projections from the data of the transmitted intensity. The transmitted intensity represents the density distribution, that is, the distribution of absorption coefficients through the object. 5 figs.

Optimized adhesives for strong, lightweight, damage-resistant, nanocomposite materials: new insights from natural materials

NASA Astrophysics Data System (ADS)

Hansma, P. K.; Turner, P. J.; Ruoff, R. S.

2007-01-01

From our investigations of natural composite materials such as abalone shell and bone we have learned the following. (1) Nature is frugal with resources: it uses just a few per cent glue, by weight, to glue together composite materials. (2) Nature does not avoid voids. (3) Nature makes optimized glues with sacrificial bonds and hidden length. We discuss how optimized adhesives combined with high specific stiffness/strength structures such as carbon nanotubes or graphene sheets could yield remarkably strong, lightweight, and damage-resistant materials.

Design and implementation of real-time wireless projection system based on ARM embedded system

NASA Astrophysics Data System (ADS)

Long, Zhaohua; Tang, Hao; Huang, Junhua

2018-04-01

Aiming at the shortage of existing real-time screen sharing system, a real-time wireless projection system is proposed in this paper. Based on the proposed system, a weight-based frame deletion strategy combined sampling time period and data variation is proposed. By implementing the system on the hardware platform, the results show that the system can achieve good results. The weight-based strategy can improve the service quality, reduce the delay and optimize the real-time customer service system [1].

A method for rapid sampling and characterization of smokeless powder using sorbent-coated wire mesh and direct analysis in real time - mass spectrometry (DART-MS).

PubMed

Li, Frederick; Tice, Joseph; Musselman, Brian D; Hall, Adam B

2016-09-01

Improvised explosive devices (IEDs) are often used by terrorists and criminals to create public panic and destruction, necessitating rapid investigative information. However, backlogs in many forensic laboratories resulting in part from time-consuming GC-MS and LC-MS techniques prevent prompt analytical information. Direct analysis in real time - mass spectrometry (DART-MS) is a promising analytical technique that can address this challenge in the forensic science community by permitting rapid trace analysis of energetic materials. Therefore, we have designed a qualitative analytical approach that utilizes novel sorbent-coated wire mesh and dynamic headspace concentration to permit the generation of information rich chemical attribute signatures (CAS) for trace energetic materials in smokeless powder with DART-MS. Sorbent-coated wire mesh improves the overall efficiency of capturing trace energetic materials in comparison to swabbing or vacuuming. Hodgdon Lil' Gun smokeless powder was used to optimize the dynamic headspace parameters. This method was compared to traditional GC-MS methods and validated using the NIST RM 8107 smokeless powder reference standard. Additives and energetic materials, notably nitroglycerin, were rapidly and efficiently captured by the Carbopack X wire mesh, followed by detection and identification using DART-MS. This approach has demonstrated the capability of generating comparable results with significantly reduced analysis time in comparison to GC-MS. All targeted components that can be detected by GC-MS were detected by DART-MS in less than a minute. Furthermore, DART-MS offers the advantage of detecting targeted analytes that are not amenable to GC-MS. The speed and efficiency associated with both the sample collection technique and DART-MS demonstrate an attractive and viable potential alternative to conventional techniques. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Fracture of Carbon Nanotube - Amorphous Carbon Composites: Molecular Modeling

NASA Technical Reports Server (NTRS)

Jensen, Benjamin D.; Wise, Kristopher E.; Odegard, Gregory M.

2015-01-01

Carbon nanotubes (CNTs) are promising candidates for use as reinforcements in next generation structural composite materials because of their extremely high specific stiffness and strength. They cannot, however, be viewed as simple replacements for carbon fibers because there are key differences between these materials in areas such as handling, processing, and matrix design. It is impossible to know for certain that CNT composites will represent a significant advance over carbon fiber composites before these various factors have been optimized, which is an extremely costly and time intensive process. This work attempts to place an upper bound on CNT composite mechanical properties by performing molecular dynamics simulations on idealized model systems with a reactive forcefield that permits modeling of both elastic deformations and fracture. Amorphous carbon (AC) was chosen for the matrix material in this work because of its structural simplicity and physical compatibility with the CNT fillers. It is also much stiffer and stronger than typical engineering polymer matrices. Three different arrangements of CNTs in the simulation cell have been investigated: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. The SWNT and MWNT array systems are clearly idealizations, but the SWNT bundle system is a step closer to real systems in which individual tubes aggregate into large assemblies. The effect of chemical crosslinking on composite properties is modeled by adding bonds between the CNTs and AC. The balance between weakening the CNTs and improving fiber-matrix load transfer is explored by systematically varying the extent of crosslinking. It is, of course, impossible to capture the full range of deformation and fracture processes that occur in real materials with even the largest atomistic molecular dynamics simulations. With this limitation in mind, the simulation results reported here provide a plausible upper limit on achievable CNT composite properties and yield some insight on the influence of processing conditions on the mechanical properties of CNT composites.

Topology optimization of hyperelastic structures using a level set method

NASA Astrophysics Data System (ADS)

Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.

2017-12-01

Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.

Systematic design of 3D auxetic lattice materials with programmable Poisson's ratio for finite strains

NASA Astrophysics Data System (ADS)

Wang, Fengwen

2018-05-01

This paper presents a systematic approach for designing 3D auxetic lattice materials, which exhibit constant negative Poisson's ratios over large strain intervals. A unit cell model mimicking tensile tests is established and based on the proposed model, the secant Poisson's ratio is defined as the negative ratio between the lateral and the longitudinal engineering strains. The optimization problem for designing a material unit cell with a target Poisson's ratio is formulated to minimize the average lateral engineering stresses under the prescribed deformations. Numerical results demonstrate that 3D auxetic lattice materials with constant Poisson's ratios can be achieved by the proposed optimization formulation and that two sets of material architectures are obtained by imposing different symmetry on the unit cell. Moreover, inspired by the topology-optimized material architecture, a subsequent shape optimization is proposed by parametrizing material architectures using super-ellipsoids. By designing two geometrical parameters, simple optimized material microstructures with different target Poisson's ratios are obtained. By interpolating these two parameters as polynomial functions of Poisson's ratios, material architectures for any Poisson's ratio in the interval of ν ∈ [ - 0.78 , 0.00 ] are explicitly presented. Numerical evaluations show that interpolated auxetic lattice materials exhibit constant Poisson's ratios in the target strain interval of [0.00, 0.20] and that 3D auxetic lattice material architectures with programmable Poisson's ratio are achievable.

Trace analysis of energetic materials via direct analyte-probed nanoextraction coupled to direct analysis in real time mass spectrometry.

PubMed

Clemons, Kristina; Dake, Jeffrey; Sisco, Edward; Verbeck, Guido F

2013-09-10

Direct analysis in real time mass spectrometry (DART-MS) has proven to be a useful forensic tool for the trace analysis of energetic materials. While other techniques for detecting trace amounts of explosives involve extraction, derivatization, solvent exchange, or sample clean-up, DART-MS requires none of these. Typical DART-MS analyses directly from a solid sample or from a swab have been quite successful; however, these methods may not always be an optimal sampling technique in a forensic setting. For example, if the sample were only located in an area which included a latent fingerprint of interest, direct DART-MS analysis or the use of a swab would almost certainly destroy the print. To avoid ruining such potentially invaluable evidence, another method has been developed which will leave the fingerprint virtually untouched. Direct analyte-probed nanoextraction coupled to nanospray ionization-mass spectrometry (DAPNe-NSI-MS) has demonstrated excellent sensitivity and repeatability in forensic analyses of trace amounts of illicit drugs from various types of surfaces. This technique employs a nanomanipulator in conjunction with bright-field microscopy to extract single particles from a surface of interest and has provided a limit of detection of 300 attograms for caffeine. Combining DAPNe with DART-MS provides another level of flexibility in forensic analysis, and has proven to be a sufficient detection method for trinitrotoluene (TNT), RDX, and 1-methylaminoanthraquinone (MAAQ). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A multi-material topology optimization approach for wrinkle-free design of cable-suspended membrane structures

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-06-01

In order to eliminate stress-related wrinkles in cable-suspended membrane structures and to provide simple and reliable deployment, this study presents a multi-material topology optimization model and an effective solution procedure for generating optimal connected layouts for membranes and cables. On the basis of the principal stress criterion of membrane wrinkling behavior and the density-based interpolation of multi-phase materials, the optimization objective is to maximize the total structural stiffness while satisfying principal stress constraints and specified material volume requirements. By adopting the cosine-type relaxation scheme to avoid the stress singularity phenomenon, the optimization model is successfully solved through a standard gradient-based algorithm. Four-corner tensioned membrane structures with different loading cases were investigated to demonstrate the effectiveness of the proposed method in automatically finding the optimal design composed of curved boundary cables and wrinkle-free membranes.

Medical real estate in an age of reform.

PubMed

Hammond, Laca Wong; Camp, Philip J

2011-04-01

The following are four ways healthcare organizations are fulfilling their medical real estate needs in an era of change: Real estate monetization. Renovation of existing facilities. A careful focus on containing materials costs. Joint ventures with real estate organizations.

Development and Long-Term Stability of a Novel Microbial Fuel Cell BOD Sensor with MnO2 Catalyst

PubMed Central

Kharkwal, Shailesh; Tan, Yi Chao; Lu, Min; Ng, How Yong

2017-01-01

A novel microbial fuel cell (MFC)-based biosensor was designed for continuous monitoring of biochemical oxygen demand (BOD) in real wastewater. To lower the material cost, manganese dioxide (MnO2) was tested as an innovative cathode catalyst for oxygen reduction in a single chamber air-cathode MFC, and two different crystalline structures obtained during synthesis of MnO2 (namely β- and γ-MnO2) were compared. The BOD sensor was studied in a comprehensive way, using both sodium acetate solution and real domestic wastewater (DWW). The optimal performance of the sensor was obtained with a β-MnO2 catalyst, with R2 values of 0.99 and 0.98 using sodium acetate solution and DWW, respectively. The BOD values predicted by the β-MnO2 biosensor for DWW were in agreement with the BOD5 values, determined according to standard methods, with slight variations in the range from 3% to 12%. Finally, the long-term stability of the BOD biosensor was evaluated over 1.5 years. To the best of our knowledge, this is the first report of an MFC BOD sensor using an MnO2 catalyst at the cathode; the feasibility of using a low-cost catalyst in an MFC for online measurement of BOD in real wastewater broadens the scope of applications for such devices. PMID:28134838

3D highway alignment optimization for Brookeville Bypass : final report.

DOT National Transportation Integrated Search

2005-06-01

This study applies the previously developed Highway Alignment Optimization (HAO) : model to the MD 97 Bypass project in Brookeville, Maryland. The objective of this study is to : demonstrate the applicability of the HAO model to a real highway projec...

Optimizing a reconfigurable material via evolutionary computation

NASA Astrophysics Data System (ADS)

Wilken, Sam; Miskin, Marc Z.; Jaeger, Heinrich M.

2015-08-01

Rapid prototyping by combining evolutionary computation with simulations is becoming a powerful tool for solving complex design problems in materials science. This method of optimization operates in a virtual design space that simulates potential material behaviors and after completion needs to be validated by experiment. However, in principle an evolutionary optimizer can also operate on an actual physical structure or laboratory experiment directly, provided the relevant material parameters can be accessed by the optimizer and information about the material's performance can be updated by direct measurements. Here we provide a proof of concept of such direct, physical optimization by showing how a reconfigurable, highly nonlinear material can be tuned to respond to impact. We report on an entirely computer controlled laboratory experiment in which a 6 ×6 grid of electromagnets creates a magnetic field pattern that tunes the local rigidity of a concentrated suspension of ferrofluid and iron filings. A genetic algorithm is implemented and tasked to find field patterns that minimize the force transmitted through the suspension. Searching within a space of roughly 1010 possible configurations, after testing only 1500 independent trials the algorithm identifies an optimized configuration of layered rigid and compliant regions.

A Real-Time Greedy-Index Dispatching Policy for using PEVs to Provide Frequency Regulation Service

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

Ke, Xinda; Wu, Di; Lu, Ning

This article presents a real-time greedy-index dispatching policy (GIDP) for using plug-in electric vehicles (PEVs) to provide frequency regulation services. A new service cost allocation mechanism is proposed to award PEVs based on the amount of service they provided, while considering compensations for delayed-charging and reduction of battery lifetime due to participation of the service. The GIDP transforms the optimal dispatch problem from a high-dimensional space into a one-dimensional space while preserving the solution optimality. When solving the transformed problem in real-time, the global optimality of the GIDP solution can be guaranteed by mathematically proved “indexability”. Because the GIDP indexmore » can be calculated upon the PEV’s arrival and used for the entire decision making process till its departure, the computational burden is minimized and the complexity of the aggregator dispatch process is significantly reduced. Finally, simulation results are used to evaluate the proposed GIDP, and to demonstrate the potential profitability from providing frequency regulation service by using PEVs.« less

Error field optimization in DIII-D using extremum seeking control

NASA Astrophysics Data System (ADS)

Lanctot, M. J.; Olofsson, K. E. J.; Capella, M.; Humphreys, D. A.; Eidietis, N.; Hanson, J. M.; Paz-Soldan, C.; Strait, E. J.; Walker, M. L.

2016-07-01

DIII-D experiments have demonstrated a new real-time approach to tokamak error field control based on maximizing the toroidal angular momentum. This approach uses extremum seeking control theory to optimize the error field in real time without inducing instabilities. Slowly-rotating n  =  1 fields (the dither), generated by external coils, are used to perturb the angular momentum, monitored in real-time using a charge-exchange spectroscopy diagnostic. Simple signal processing of the rotation measurements extracts information about the rotation gradient with respect to the control coil currents. This information is used to converge the control coil currents to a point that maximizes the toroidal angular momentum. The technique is well-suited for multi-coil, multi-harmonic error field optimizations in disruption sensitive devices as it does not require triggering locked tearing modes or plasma current disruptions. Control simulations highlight the importance of the initial search direction on the rate of the convergence, and identify future algorithm upgrades that may allow more rapid convergence that projects to convergence times in ITER on the order of tens of seconds.

A Real-Time Greedy-Index Dispatching Policy for using PEVs to Provide Frequency Regulation Service

DOE PAGES

Ke, Xinda; Wu, Di; Lu, Ning

2017-09-18

This article presents a real-time greedy-index dispatching policy (GIDP) for using plug-in electric vehicles (PEVs) to provide frequency regulation services. A new service cost allocation mechanism is proposed to award PEVs based on the amount of service they provided, while considering compensations for delayed-charging and reduction of battery lifetime due to participation of the service. The GIDP transforms the optimal dispatch problem from a high-dimensional space into a one-dimensional space while preserving the solution optimality. When solving the transformed problem in real-time, the global optimality of the GIDP solution can be guaranteed by mathematically proved “indexability”. Because the GIDP indexmore » can be calculated upon the PEV’s arrival and used for the entire decision making process till its departure, the computational burden is minimized and the complexity of the aggregator dispatch process is significantly reduced. Finally, simulation results are used to evaluate the proposed GIDP, and to demonstrate the potential profitability from providing frequency regulation service by using PEVs.« less

Optimal Sparse Upstream Sensor Placement for Hydrokinetic Turbines

NASA Astrophysics Data System (ADS)

Cavagnaro, Robert; Strom, Benjamin; Ross, Hannah; Hill, Craig; Polagye, Brian

2016-11-01

Accurate measurement of the flow field incident upon a hydrokinetic turbine is critical for performance evaluation during testing and setting boundary conditions in simulation. Additionally, turbine controllers may leverage real-time flow measurements. Particle image velocimetry (PIV) is capable of rendering a flow field over a wide spatial domain in a controlled, laboratory environment. However, PIV's lack of suitability for natural marine environments, high cost, and intensive post-processing diminish its potential for control applications. Conversely, sensors such as acoustic Doppler velocimeters (ADVs), are designed for field deployment and real-time measurement, but over a small spatial domain. Sparsity-promoting regression analysis such as LASSO is utilized to improve the efficacy of point measurements for real-time applications by determining optimal spatial placement for a small number of ADVs using a training set of PIV velocity fields and turbine data. The study is conducted in a flume (0.8 m2 cross-sectional area, 1 m/s flow) with laboratory-scale axial and cross-flow turbines. Predicted turbine performance utilizing the optimal sparse sensor network and associated regression model is compared to actual performance with corresponding PIV measurements.

TLBO based Voltage Stable Environment Friendly Economic Dispatch Considering Real and Reactive Power Constraints

NASA Astrophysics Data System (ADS)

Verma, H. K.; Mafidar, P.

2013-09-01

In view of growing concern towards environment, power system engineers are forced to generate quality green energy. Hence the economic dispatch (ED) aims at the power generation to meet the load demand at minimum fuel cost with environmental and voltage constraints along with essential constraints on real and reactive power. The emission control which reduces the negative impact on environment is achieved by including the additional constraints in ED problem. Presently, the power system mostly operates near its stability limits, therefore with increased demand the system faces voltage problem. The bus voltages are brought within limit in the present work by placement of static var compensator (SVC) at weak bus which is identified from bus participation factor. The optimal size of SVC is determined by univariate search method. This paper presents the use of Teaching Learning based Optimization (TLBO) algorithm for voltage stable environment friendly ED problem with real and reactive power constraints. The computational effectiveness of TLBO is established through test results over particle swarm optimization (PSO) and Big Bang-Big Crunch (BB-BC) algorithms for the ED problem.

Improved Strategies and Optimization of Calibration Models for Real-time PCR Absolute Quantification

EPA Science Inventory

Real-time PCR absolute quantification applications rely on the use of standard curves to make estimates of DNA target concentrations in unknown samples. Traditional absolute quantification approaches dictate that a standard curve must accompany each experimental run. However, t...

Real-time range generation for ladar hardware-in-the-loop testing

NASA Astrophysics Data System (ADS)

Olson, Eric M.; Coker, Charles F.

1996-05-01

Real-time closed loop simulation of LADAR seekers in a hardware-in-the-loop facility can reduce program risk and cost. This paper discusses an implementation of real-time range imagery generated in a synthetic environment at the Kinetic Kill Vehicle Hardware-in-the Loop facility at Eglin AFB, for the stimulation of LADAR seekers and algorithms. The computer hardware platform used was a Silicon Graphics Incorporated Onyx Reality Engine. This computer contains graphics hardware, and is optimized for generating visible or infrared imagery in real-time. A by-produce of the rendering process, in the form of a depth buffer, is generated from all objects in view during its rendering process. The depth buffer is an array of integer values that contributes to the proper rendering of overlapping objects and can be converted to range values using a mathematical formula. This paper presents an optimized software approach to the generation of the scenes, calculation of the range values, and outputting the range data for a LADAR seeker.

Research on the optimization of quota design in real estate

NASA Astrophysics Data System (ADS)

Sun, Chunling; Ma, Susu; Zhong, Weichao

2017-11-01

Quota design is one of the effective methods of cost control in real estate development project and widely used in the current real estate development project to control the engineering construction cost, but quota design have many deficiencies in design process. For this purpose, this paper put forward a method to achieve investment control of real estate development project, which combine quota design and value engineering(VE) at the stage of design. Specifically, it’s an optimizing for the structure of quota design. At first, determine the design limits by investment estimate value, then using VE to carry on initial allocation of design limits and gain the functional target cost, finally, consider the whole life cycle cost (LCC) and operational problem in practical application to finish complex correction for the functional target cost. The improved process can control the project cost more effectively. It not only can control investment in a certain range, but also make the project realize maximum value within investment.

Microwave corrosion detection using open ended rectangular waveguide sensors

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

Qaddoumi, N.; Handjojo, L.; Bigelow, T.

The use of microwave and millimeter wave nondestructive testing methods utilizing open ended rectangular waveguide sensors has shown great potential for detecting minute thickness variations in laminate structures, in particular those backed by a conducting plate. Slight variations in the dielectric properties of materials may also be detected using a set of optimal parameters which include the standoff distance and the frequency of operation. In a recent investigation, on detecting rust under paint, the dielectric properties of rust were assumed to be similar to those of Fe{sub 2}O{sub 3} powder. These values were used in an electromagnetic model that simulatesmore » the interaction of fields radiated by a rectangular waveguide aperture with layered structures to obtain optimal parameters. The dielectric properties of Fe{sub 2}O{sub 3} were measured to be very similar to the properties of paint. Nevertheless, the presence of a simulated Fe{sub 2}O{sub 3} layer under a paint layer was detected. In this paper the dielectric properties of several different rust samples from different environments are measured. The measurements indicate that the nature of real rust is quite diverse and is different from Fe{sub 2}O{sub 3} and paint, indicating that the presence of rust under paint can be easily detected. The same electromagnetic model is also used (with the newly measured dielectric properties of real rust) to obtain an optimal standoff distance at a frequency of 24 GHz. The results indicate that variations in the magnitude as well as the phase of the reflection coefficient can be used to obtain information about the presence of rust. An experimental investigation on detecting the presence of very thin rust layers (2.5--5 x 10{sup {minus}2} mm [09--2.0 x 10{sup {minus}3} in.]) using an open ended rectangular waveguide probe is also conducted. Microwave images of rusted specimens, obtained at 24 GHz, are also presented.« less

Evaluation of 5 different labeled polymer immunohistochemical detection systems.

PubMed

Skaland, Ivar; Nordhus, Marit; Gudlaugsson, Einar; Klos, Jan; Kjellevold, Kjell H; Janssen, Emiel A M; Baak, Jan P A

2010-01-01

Immunohistochemical staining is important for diagnosis and therapeutic decision making but the results may vary when different detection systems are used. To analyze this, 5 different labeled polymer immunohistochemical detection systems, REAL EnVision, EnVision Flex, EnVision Flex+ (Dako, Glostrup, Denmark), NovoLink (Novocastra Laboratories Ltd, Newcastle Upon Tyne, UK) and UltraVision ONE (Thermo Fisher Scientific, Fremont, CA) were tested using 12 different, widely used mouse and rabbit primary antibodies, detecting nuclear, cytoplasmic, and membrane antigens. Serial sections of multitissue blocks containing 4% formaldehyde fixed paraffin embedded material were selected for their weak, moderate, and strong staining for each antibody. Specificity and sensitivity were evaluated by subjective scoring and digital image analysis. At optimal primary antibody dilution, digital image analysis showed that EnVision Flex+ was the most sensitive system (P < 0.005), with means of 8.3, 13.4, 20.2, and 41.8 gray scale values stronger staining than REAL EnVision, EnVision Flex, NovoLink, and UltraVision ONE, respectively. NovoLink was the second most sensitive system for mouse antibodies, but showed low sensitivity for rabbit antibodies. Due to low sensitivity, 2 cases with UltraVision ONE and 1 case with NovoLink stained false negatively. None of the detection systems showed any distinct false positivity, but UltraVision ONE and NovoLink consistently showed weak background staining both in negative controls and at optimal primary antibody dilution. We conclude that there are significant differences in sensitivity, specificity, costs, and total assay time in the immunohistochemical detection systems currently in use.

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

DOE PAGES

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik; ...

2017-07-25

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

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

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

Optimizing the Anti-VEGF Treatment Strategy for Neovascular Age-Related Macular Degeneration: From Clinical Trials to Real-Life Requirements.

PubMed

Mantel, Irmela

2015-06-01

This Perspective discusses the pertinence of variable dosing regimens with anti-vascular endothelial growth factor (VEGF) for neovascular age-related macular degeneration (nAMD) with regard to real-life requirements. After the initial pivotal trials of anti-VEGF therapy, the variable dosing regimens pro re nata (PRN), Treat-and-Extend, and Observe-and-Plan, a recently introduced regimen, aimed to optimize the anti-VEGF treatment strategy for nAMD. The PRN regimen showed good visual results but requires monthly monitoring visits and can therefore be difficult to implement. Moreover, application of the PRN regimen revealed inferior results in real-life circumstances due to problems with resource allocation. The Treat-and-Extend regimen uses an interval based approach and has become widely accepted for its ease of preplanning and the reduced number of office visits required. The parallel development of the Observe-and-Plan regimen demonstrated that the future need for retreatment (interval) could be reliably predicted. Studies investigating the observe-and-plan regimen also showed that this could be used in individualized fixed treatment plans, allowing for dramatically reduced clinical burden and good outcomes, thus meeting the real life requirements. This progressive development of variable dosing regimens is a response to the real-life circumstances of limited human, technical, and financial resources. This includes an individualized treatment approach, optimization of the number of retreatments, a minimal number of monitoring visits, and ease of planning ahead. The Observe-and-Plan regimen achieves this goal with good functional results. Translational Relevance: This perspective reviews the process from the pivotal clinical trials to the development of treatment regimens which are adjusted to real life requirements. The article discusses this translational process which- although not the classical interpretation of translation from fundamental to clinical research, but a subsequent process after the pivotal clinical trials - represents an important translational step from the clinical proof of efficacy to optimization in terms of patients' and clinics' needs. The related scientific procedure includes the exploration of the concept, evaluation of security, and finally proof of efficacy.

Real-time and accelerated outdoor endurance testing of solar cells

NASA Technical Reports Server (NTRS)

Forestieri, A. F.; Anagnostou, E.

1978-01-01

Materials for solar-cell module construction have been studied on the basis of limited real-time outdoor exposure evaluations. The materials tested included transmission samples, sub-modules, and actual solar cells. The results suggest that glass, fluorinated ethylene propylene, and perfluoroalkoxy are good materials for the covering or encapsulation of solar-cell modules. In all cases, dirt accumulation and cleanability are important factors.

Autonomous In-Situ Resources Prospector

NASA Technical Reports Server (NTRS)

Dissly, R. W.; Buehler, M. G.; Schaap, M. G.; Nicks, D.; Taylor, G. J.; Castano, R.; Suarez, D.

2004-01-01

This presentation will describe the concept of an autonomous, intelligent, rover-based rapid surveying system to identify and map several key lunar resources to optimize their ISRU (In Situ Resource Utilization) extraction potential. Prior to an extraction phase for any target resource, ground-based surveys are needed to provide confirmation of remote observation, to quantify and map their 3-D distribution, and to locate optimal extraction sites (e.g. ore bodies) with precision to maximize their economic benefit. The system will search for and quantify optimal minerals for oxygen production feedstock, water ice, and high glass-content regolith that can be used for building materials. These are targeted because of their utility and because they are, or are likely to be, variable in quantity over spatial scales accessible to a rover (i.e., few km). Oxygen has benefits for life support systems and as an oxidizer for propellants. Water is a key resource for sustainable exploration, with utility for life support, propellants, and other industrial processes. High glass-content regolith has utility as a feedstock for building materials as it readily sinters upon heating into a cohesive matrix more readily than other regolith materials or crystalline basalts. Lunar glasses are also a potential feedstock for oxygen production, as many are rich in iron and titanium oxides that are optimal for oxygen extraction. To accomplish this task, a system of sensors and decision-making algorithms for an autonomous prospecting rover is described. One set of sensors will be located in the wheel tread of the robotic search vehicle providing contact sensor data on regolith composition. Another set of instruments will be housed on the platform of the rover, including VIS-NIR imagers and spectrometers, both for far-field context and near-field characterization of the regolith in the immediate vicinity of the rover. Also included in the sensor suite are a neutron spectrometer, ground-penetrating radar, and an instrumented cone penetrometer for subsurface assessment. Output from these sensors will be evaluated autonomously in real-time by decision-making software to evaluate if any of the targeted resources has been detected, and if so, to quantify their abundance. Algorithms for optimizing the mapping strategy based on target resource abundance and distribution are also included in the autonomous software. This approach emphasizes on-the-fly survey measurements to enable efficient and rapid prospecting of large areas, which will improve the economics of ISRU system approaches. The mature technology will enable autonomous rovers to create in-situ resource maps of lunar or other planetary surfaces, which will facilitate human and robotic exploration.

Development of devices for self-injection: using tribological analysis to optimize injection force

PubMed Central

Lange, Jakob; Urbanek, Leos; Burren, Stefan

2016-01-01

This article describes the use of analytical models and physical measurements to characterize and optimize the tribological behavior of pen injectors for self-administration of biopharmaceuticals. One of the main performance attributes of this kind of device is its efficiency in transmitting the external force applied by the user on to the cartridge inside the pen in order to effectuate an injection. This injection force characteristic is heavily influenced by the frictional properties of the polymeric materials employed in the mechanism. Standard friction tests are available for characterizing candidate materials, but they use geometries and conditions far removed from the actual situation inside a pen injector and thus do not always generate relevant data. A new test procedure, allowing the direct measurement of the coefficient of friction between two key parts of a pen injector mechanism using real parts under simulated use conditions, is presented. In addition to the absolute level of friction, the test method provides information on expected evolution of friction over lifetime as well as on expected consistency between individual devices. Paired with an analytical model of the pen mechanism, the frictional data allow the expected overall injection system force efficiency to be estimated. The test method and analytical model are applied to a range of polymer combinations with different kinds of lubrication. It is found that material combinations used without lubrication generally have unsatisfactory performance, that the use of silicone-based internal lubricating additives improves performance, and that the best results can be achieved with external silicone-based lubricants. Polytetrafluoroethylene-based internal lubrication and external lubrication are also evaluated but found to provide only limited benefits unless used in combination with silicone. PMID:27274319

Dynamics of Biofilm Regrowth in Drinking Water Distribution Systems.

PubMed

Douterelo, I; Husband, S; Loza, V; Boxall, J

2016-07-15

The majority of biomass within water distribution systems is in the form of attached biofilm. This is known to be central to drinking water quality degradation following treatment, yet little understanding of the dynamics of these highly heterogeneous communities exists. This paper presents original information on such dynamics, with findings demonstrating patterns of material accumulation, seasonality, and influential factors. Rigorous flushing operations repeated over a 1-year period on an operational chlorinated system in the United Kingdom are presented here. Intensive monitoring and sampling were undertaken, including time-series turbidity and detailed microbial analysis using 16S rRNA Illumina MiSeq sequencing. The results show that bacterial dynamics were influenced by differences in the supplied water and by the material remaining attached to the pipe wall following flushing. Turbidity, metals, and phosphate were the main factors correlated with the distribution of bacteria in the samples. Coupled with the lack of inhibition of biofilm development due to residual chlorine, this suggests that limiting inorganic nutrients, rather than organic carbon, might be a viable component in treatment strategies to manage biofilms. The research also showed that repeat flushing exerted beneficial selective pressure, giving another reason for flushing being a viable advantageous biofilm management option. This work advances our understanding of microbiological processes in drinking water distribution systems and helps inform strategies to optimize asset performance. This research provides novel information regarding the dynamics of biofilm formation in real drinking water distribution systems made of different materials. This new knowledge on microbiological process in water supply systems can be used to optimize the performance of the distribution network and to guarantee safe and good-quality drinking water to consumers. Copyright © 2016 Douterelo et al.

Dynamics of Biofilm Regrowth in Drinking Water Distribution Systems

PubMed Central

Husband, S.; Loza, V.; Boxall, J.

2016-01-01

ABSTRACT The majority of biomass within water distribution systems is in the form of attached biofilm. This is known to be central to drinking water quality degradation following treatment, yet little understanding of the dynamics of these highly heterogeneous communities exists. This paper presents original information on such dynamics, with findings demonstrating patterns of material accumulation, seasonality, and influential factors. Rigorous flushing operations repeated over a 1-year period on an operational chlorinated system in the United Kingdom are presented here. Intensive monitoring and sampling were undertaken, including time-series turbidity and detailed microbial analysis using 16S rRNA Illumina MiSeq sequencing. The results show that bacterial dynamics were influenced by differences in the supplied water and by the material remaining attached to the pipe wall following flushing. Turbidity, metals, and phosphate were the main factors correlated with the distribution of bacteria in the samples. Coupled with the lack of inhibition of biofilm development due to residual chlorine, this suggests that limiting inorganic nutrients, rather than organic carbon, might be a viable component in treatment strategies to manage biofilms. The research also showed that repeat flushing exerted beneficial selective pressure, giving another reason for flushing being a viable advantageous biofilm management option. This work advances our understanding of microbiological processes in drinking water distribution systems and helps inform strategies to optimize asset performance. IMPORTANCE This research provides novel information regarding the dynamics of biofilm formation in real drinking water distribution systems made of different materials. This new knowledge on microbiological process in water supply systems can be used to optimize the performance of the distribution network and to guarantee safe and good-quality drinking water to consumers. PMID:27208119

A new magnetic nanodiamond/graphene oxide hybrid (Fe3O4@ND@GO) material for pre-concentration and sensitive determination of sildenafil in alleged herbal aphrodisiacs by HPLC-DAD system.

PubMed

Yilmaz, Erkan; Ulusoy, Halil İbrahim; Demir, Özge; Soylak, Mustafa

2018-05-01

A sensitive analytical methodology was investigated to concentrate and determine of sildenafil citrate (SLC) present at trace level in herbal supplementary products. The proposed method is based on simple and sensitive pre-concentration of SLC by using magnetic solid phase extraction with new developed magnetic nanodiamond/graphene oxide hybrid (Fe 3 O 4 @ND@GO) material as a sorbent. Experimental variables affecting the extraction efficiency of SLC like; pH, sample volume, eluent type and volume, extraction time and amount of adsorbent were studied and optimized in detail. Determination of sildenafil citrate after magnetic solid phase extraction (MSPE) was carried out by HPLC-DAD system. The morphology, composition, and properties of the synthesized hybrid material was characterized by Fourier transform infrared spectrometry (FT-IR), Raman spectrometry (Raman), X-ray diffraction spectrometry (XRD), scanning electron microscopy (SEM), mapping photographs, zeta potential analyzer, and BET surface area analysis. Under optimized conditions, linear range was ranged from 5.00 to 250.00 ng mL -1 with R 2 of 0.9952. The limit of detection (LOD) was 1.49 ng mL -1 and the recoveries at two spiked levels were ranged from 94.0 to 104.1% with the relative standard deviation (RSD) < 7.1% (n = 5). The enhancement factor (EF) was 86.9. The results show that the combination MSPE with HPLC-DAD is a suitable and sensitive method for the determination of SLC in real samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Actinobacteria consortium as an efficient biotechnological tool for mixed polluted soil reclamation: Experimental factorial design for bioremediation process optimization.

PubMed

Aparicio, Juan Daniel; Raimondo, Enzo Emanuel; Gil, Raúl Andrés; Benimeli, Claudia Susana; Polti, Marta Alejandra

2018-01-15

The objective of the present work was to establish optimal biological and physicochemical parameters in order to remove simultaneously lindane and Cr(VI) at high and/or low pollutants concentrations from the soil by an actinobacteria consortium formed by Streptomyces sp. M7, MC1, A5, and Amycolatopsis tucumanensis AB0. Also, the final aim was to treat real soils contaminated with Cr(VI) and/or lindane from the Northwest of Argentina employing the optimal biological and physicochemical conditions. In this sense, after determining the optimal inoculum concentration (2gkg -1 ), an experimental design model with four factors (temperature, moisture, initial concentration of Cr(VI) and lindane) was employed for predicting the system behavior during bioremediation process. According to response optimizer, the optimal moisture level was 30% for all bioremediation processes. However, the optimal temperature was different for each situation: for low initial concentrations of both pollutants, the optimal temperature was 25°C; for low initial concentrations of Cr(VI) and high initial concentrations of lindane, the optimal temperature was 30°C; and for high initial concentrations of Cr(VI), the optimal temperature was 35°C. In order to confirm the model adequacy and the validity of the optimization procedure, experiments were performed in six real contaminated soils samples. The defined actinobacteria consortium reduced the contaminants concentrations in five of the six samples, by working at laboratory scale and employing the optimal conditions obtained through the factorial design. Copyright © 2017 Elsevier B.V. All rights reserved.

Tangible display systems: bringing virtual surfaces into the real world

NASA Astrophysics Data System (ADS)

Ferwerda, James A.

2012-03-01

We are developing tangible display systems that enable natural interaction with virtual surfaces. Tangible display systems are based on modern mobile devices that incorporate electronic image displays, graphics hardware, tracking systems, and digital cameras. Custom software allows the orientation of a device and the position of the observer to be tracked in real-time. Using this information, realistic images of surfaces with complex textures and material properties illuminated by environment-mapped lighting, can be rendered to the screen at interactive rates. Tilting or moving in front of the device produces realistic changes in surface lighting and material appearance. In this way, tangible displays allow virtual surfaces to be observed and manipulated as naturally as real ones, with the added benefit that surface geometry and material properties can be modified in real-time. We demonstrate the utility of tangible display systems in four application areas: material appearance research; computer-aided appearance design; enhanced access to digital library and museum collections; and new tools for digital artists.

Micro-chromatin Immunoprecipation (μChIP) Protocol for Real-time PCR Analysis of a Limited Amount of Cells.

PubMed

Gillotin, Sébastien; Guillemot, François

2016-06-20

Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is an important strategy to study gene regulation. When availability of cells is limited, however, it can be useful to focus on specific genes to investigate in depth the role of transcription factors or histone marks. Unfortunately, performing ChIP experiments to study transcription factors' binding to DNA can be difficult when biological material is restricted. This protocol describes a robust method to perform μChIP for over-expressed or endogenous transcription factors using ~100,000 cells per ChIP experiment (Masserdotti et al ., 2015). We also describe optimization steps, which we think are critical for this protocol to work and which can be used to further reduce the number of cells.

Signal-to-noise ratio application to seismic marker analysis and fracture detection

NASA Astrophysics Data System (ADS)

Xu, Hui-Qun; Gui, Zhi-Xian

2014-03-01

Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoir exploration. To obtain high SNR seismic data, significant effort is required to achieve noise attenuation in seismic data processing, which is costly in materials, and human and financial resources. We introduce a method for improving the SNR of seismic data. The SNR is calculated by using the frequency domain method. Furthermore, we optimize and discuss the critical parameters and calculation procedure. We applied the proposed method on real data and found that the SNR is high in the seismic marker and low in the fracture zone. Consequently, this can be used to extract detailed information about fracture zones that are inferred by structural analysis but not observed in conventional seismic data.

Electroporating Fields Target Oxidatively Damaged Areas in the Cell Membrane

PubMed Central

Vernier, P. Thomas; Levine, Zachary A.; Wu, Yu-Hsuan; Joubert, Vanessa; Ziegler, Matthew J.; Mir, Lluis M.; Tieleman, D. Peter

2009-01-01

Reversible electropermeabilization (electroporation) is widely used to facilitate the introduction of genetic material and pharmaceutical agents into living cells. Although considerable knowledge has been gained from the study of real and simulated model membranes in electric fields, efforts to optimize electroporation protocols are limited by a lack of detailed understanding of the molecular basis for the electropermeabilization of the complex biomolecular assembly that forms the plasma membrane. We show here, with results from both molecular dynamics simulations and experiments with living cells, that the oxidation of membrane components enhances the susceptibility of the membrane to electropermeabilization. Manipulation of the level of oxidative stress in cell suspensions and in tissues may lead to more efficient permeabilization procedures in the laboratory and in clinical applications such as electrochemotherapy and electrotransfection-mediated gene therapy. PMID:19956595

Feasibility study of current pulse induced 2-bit/4-state multilevel programming in phase-change memory

NASA Astrophysics Data System (ADS)

Liu, Yan; Fan, Xi; Chen, Houpeng; Wang, Yueqing; Liu, Bo; Song, Zhitang; Feng, Songlin

2017-08-01

In this brief, multilevel data storage for phase-change memory (PCM) has attracted more attention in the memory market to implement high capacity memory system and reduce cost-per-bit. In this work, we present a universal programing method of SET stair-case current pulse in PCM cells, which can exploit the optimum programing scheme to achieve 2-bit/ 4state resistance-level with equal logarithm interval. SET stair-case waveform can be optimized by TCAD real time simulation to realize multilevel data storage efficiently in an arbitrary phase change material. Experimental results from 1 k-bit PCM test-chip have validated the proposed multilevel programing scheme. This multilevel programming scheme has improved the information storage density, robustness of resistance-level, energy efficient and avoiding process complexity.

Advanced analytical electron microscopy for alkali-ion batteries

DOE PAGES

Qian, Danna; Ma, Cheng; Meng, Ying Shirley; ...

2015-06-26

Lithium-ion batteries are a leading candidate for electric vehicle and smart grid applications. However, further optimizations of the energy/power density, coulombic efficiency and cycle life are still needed, and this requires a thorough understanding of the dynamic evolution of each component and their synergistic behaviors during battery operation. With the capability of resolving the structure and chemistry at an atomic resolution, advanced analytical transmission electron microscopy (AEM) is an ideal technique for this task. The present review paper focuses on recent contributions of this important technique to the fundamental understanding of the electrochemical processes of battery materials. A detailed reviewmore » of both static (ex situ) and real-time (in situ) studies will be given, and issues that still need to be addressed will be discussed.« less

Extinction spectra of suspensions of microspheres: determination of the spectral refractive index and particle size distribution with nanometer accuracy.

PubMed

Gienger, Jonas; Bär, Markus; Neukammer, Jörg

2018-01-10

A method is presented to infer simultaneously the wavelength-dependent real refractive index (RI) of the material of microspheres and their size distribution from extinction measurements of particle suspensions. To derive the averaged spectral optical extinction cross section of the microspheres from such ensemble measurements, we determined the particle concentration by flow cytometry to an accuracy of typically 2% and adjusted the particle concentration to ensure that perturbations due to multiple scattering are negligible. For analysis of the extinction spectra, we employ Mie theory, a series-expansion representation of the refractive index and nonlinear numerical optimization. In contrast to other approaches, our method offers the advantage to simultaneously determine size, size distribution, and spectral refractive index of ensembles of microparticles including uncertainty estimation.

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

DOE PAGES

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

2018-04-02

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

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

Barlow, Andrew; Klima, Matej; Shashkov, Mikhail

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of amore » realistic shaped charge calculation in the presence of voids and solids.« less

Real time optimal guidance of low-thrust spacecraft: an application of nonlinear model predictive control.

PubMed

Arrieta-Camacho, Juan José; Biegler, Lorenz T

2005-12-01

Real time optimal guidance is considered for a class of low thrust spacecraft. In particular, nonlinear model predictive control (NMPC) is utilized for computing the optimal control actions required to transfer a spacecraft from a low Earth orbit to a mission orbit. The NMPC methodology presented is able to cope with unmodeled disturbances. The dynamics of the transfer are modeled using a set of modified equinoctial elements because they do not exhibit singularities for zero inclination and zero eccentricity. The idea behind NMPC is the repeated solution of optimal control problems; at each time step, a new control action is computed. The optimal control problem is solved using a direct method-fully discretizing the equations of motion. The large scale nonlinear program resulting from the discretization procedure is solved using IPOPT--a primal-dual interior point algorithm. Stability and robustness characteristics of the NMPC algorithm are reviewed. A numerical example is presented that encourages further development of the proposed methodology: the transfer from low-Earth orbit to a molniya orbit.

Digi Island: A Serious Game for Teaching and Learning Digital Circuit Optimization

NASA Technical Reports Server (NTRS)

Harper, Michael; Miller, Joseph; Shen, Yuzhong

2011-01-01

Karnaugh maps, also known as K-maps, are a tool used to optimize or simplify digital logic circuits. A K-map is a graphical display of a logic circuit. K-map optimization is essentially the process of finding a minimum number of maximal aggregations of K-map cells. with values of 1 according to a set of rules. The Digi Island is a serious game designed for aiding students to learn K-map optimization. The game takes place on an exotic island (called Digi Island) in the Pacific Ocean . The player is an adventurer to the Digi Island and will transform it into a tourist attraction by developing real estates, such as amusement parks.and hotels. The Digi Island game elegantly converts boring 1s and Os in digital circuits into usable and unusable spaces on a beautiful island and transforms K-map optimization into real estate development, an activity with which many students are familiar and also interested in. This paper discusses the design, development, and some preliminary results of the Digi Island game.

Solving NP-Hard Problems with Physarum-Based Ant Colony System.

PubMed

Liu, Yuxin; Gao, Chao; Zhang, Zili; Lu, Yuxiao; Chen, Shi; Liang, Mingxin; Tao, Li

2017-01-01

NP-hard problems exist in many real world applications. Ant colony optimization (ACO) algorithms can provide approximate solutions for those NP-hard problems, but the performance of ACO algorithms is significantly reduced due to premature convergence and weak robustness, etc. With these observations in mind, this paper proposes a Physarum-based pheromone matrix optimization strategy in ant colony system (ACS) for solving NP-hard problems such as traveling salesman problem (TSP) and 0/1 knapsack problem (0/1 KP). In the Physarum-inspired mathematical model, one of the unique characteristics is that critical tubes can be reserved in the process of network evolution. The optimized updating strategy employs the unique feature and accelerates the positive feedback process in ACS, which contributes to the quick convergence of the optimal solution. Some experiments were conducted using both benchmark and real datasets. The experimental results show that the optimized ACS outperforms other meta-heuristic algorithms in accuracy and robustness for solving TSPs. Meanwhile, the convergence rate and robustness for solving 0/1 KPs are better than those of classical ACS.

Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Benavides-Piccione, Ruth; DeFelipe, Javier; Larrañaga, Pedro

2016-10-01

The way in which a neuronal tree expands plays an important role in its functional and computational characteristics. We aimed to study the existence of an optimal neuronal design for different types of cortical GABAergic neurons. To do this, we hypothesized that both the axonal and dendritic trees of individual neurons optimize brain connectivity in terms of wiring length. We took the branching points of real three-dimensional neuronal reconstructions of the axonal and dendritic trees of different types of cortical interneurons and searched for the minimal wiring arborization structure that respects the branching points. We compared the minimal wiring arborization with real axonal and dendritic trees. We tested this optimization problem using a new approach based on graph theory and evolutionary computation techniques. We concluded that neuronal wiring is near-optimal in most of the tested neurons, although the wiring length of dendritic trees is generally nearer to the optimum. Therefore, wiring economy is related to the way in which neuronal arborizations grow irrespective of the marked differences in the morphology of the examined interneurons.

Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

PubMed

Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

2009-01-01

This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control.

Instrument for Real-Time Digital Nucleic Acid Amplification on Custom Microfluidic Devices

PubMed Central

Selck, David A.

2016-01-01

Nucleic acid amplification tests that are coupled with a digital readout enable the absolute quantification of single molecules, even at ultralow concentrations. Digital methods are robust, versatile and compatible with many amplification chemistries including isothermal amplification, making them particularly invaluable to assays that require sensitive detection, such as the quantification of viral load in occult infections or detection of sparse amounts of DNA from forensic samples. A number of microfluidic platforms are being developed for carrying out digital amplification. However, the mechanistic investigation and optimization of digital assays has been limited by the lack of real-time kinetic information about which factors affect the digital efficiency and analytical sensitivity of a reaction. Commercially available instruments that are capable of tracking digital reactions in real-time are restricted to only a small number of device types and sample-preparation strategies. Thus, most researchers who wish to develop, study, or optimize digital assays rely on the rate of the amplification reaction when performed in a bulk experiment, which is now recognized as an unreliable predictor of digital efficiency. To expand our ability to study how digital reactions proceed in real-time and enable us to optimize both the digital efficiency and analytical sensitivity of digital assays, we built a custom large-format digital real-time amplification instrument that can accommodate a wide variety of devices, amplification chemistries and sample-handling conditions. Herein, we validate this instrument, we provide detailed schematics that will enable others to build their own custom instruments, and we include a complete custom software suite to collect and analyze the data retrieved from the instrument. We believe assay optimizations enabled by this instrument will improve the current limits of nucleic acid detection and quantification, improving our fundamental understanding of single-molecule reactions and providing advancements in practical applications such as medical diagnostics, forensics and environmental sampling. PMID:27760148

Individualized treatment with transcranial direct current stimulation in patients with chronic non-fluent aphasia due to stroke

PubMed Central

Shah-Basak, Priyanka P.; Norise, Catherine; Garcia, Gabriella; Torres, Jose; Faseyitan, Olufunsho; Hamilton, Roy H.

2015-01-01

While evidence suggests that transcranial direct current stimulation (tDCS) may facilitate language recovery in chronic post-stroke aphasia, individual variability in patient response to different patterns of stimulation remains largely unexplored. We sought to characterize this variability among chronic aphasic individuals, and to explore whether repeated stimulation with an individualized optimal montage could lead to persistent reduction of aphasia severity. In a two-phase study, we first stimulated patients with four active montages (left hemispheric anode or cathode; right hemispheric anode or cathode) and one sham montage (Phase 1). We examined changes in picture naming ability to address (1) variability in response to different montages among our patients, and (2) whether individual patients responded optimally to at least one montage. During Phase 2, subjects who responded in Phase 1 were randomized to receive either real-tDCS or to receive sham stimulation (10 days); patients who were randomized to receive sham stimulation first were then crossed over to receive real-tDCS (10 days). In both phases, 2 mA tDCS was administered for 20 min per real-tDCS sessions and patients performed a picture naming task during stimulation. Patients' language ability was re-tested after 2-weeks and 2-months following real and sham tDCS in Phase 2. In Phase 1, despite considerable individual variability, the greatest average improvement was observed after left-cathodal stimulation. Seven out of 12 subjects responded optimally to at least one montage as demonstrated by transient improvement in picture-naming. In Phase 2, aphasia severity improved at 2-weeks and 2-months following real-tDCS but not sham. Despite individual variability with respect to optimal tDCS approach, certain montages result in consistent transient improvement in persons with chronic post-stroke aphasia. This preliminary study supports the notion that individualized tDCS treatment may enhance aphasia recovery in a persistent manner. PMID:25954178

Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems

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

Dall'Anese, Emiliano; Dhople, Sairaj V.; Johnson, Brian B.

Summary form only given. Decentralized methods for computing optimal real and reactive power setpoints for residential photovoltaic (PV) inverters are developed in this paper. It is known that conventional PV inverter controllers, which are designed to extract maximum power at unity power factor, cannot address secondary performance objectives such as voltage regulation and network loss minimization. Optimal power flow techniques can be utilized to select which inverters will provide ancillary services, and to compute their optimal real and reactive power setpoints according to well-defined performance criteria and economic objectives. Leveraging advances in sparsity-promoting regularization techniques and semidefinite relaxation, this papermore » shows how such problems can be solved with reduced computational burden and optimality guarantees. To enable large-scale implementation, a novel algorithmic framework is introduced - based on the so-called alternating direction method of multipliers - by which optimal power flow-type problems in this setting can be systematically decomposed into sub-problems that can be solved in a decentralized fashion by the utility and customer-owned PV systems with limited exchanges of information. Since the computational burden is shared among multiple devices and the requirement of all-to-all communication can be circumvented, the proposed optimization approach scales favorably to large distribution networks.« less

The trade-off between morphology and control in the co-optimized design of robots.

PubMed

Rosendo, Andre; von Atzigen, Marco; Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques.

Sequential quantum cloning under real-life conditions

NASA Astrophysics Data System (ADS)

Saberi, Hamed; Mardoukhi, Yousof

2012-05-01

We consider a sequential implementation of the optimal quantum cloning machine of Gisin and Massar and propose optimization protocols for experimental realization of such a quantum cloner subject to the real-life restrictions. We demonstrate how exploiting the matrix-product state (MPS) formalism and the ensuing variational optimization techniques reveals the intriguing algebraic structure of the Gisin-Massar output of the cloning procedure and brings about significant improvements to the optimality of the sequential cloning prescription of Delgado [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.98.150502 98, 150502 (2007)]. Our numerical results show that the orthodox paradigm of optimal quantum cloning can in practice be realized in a much more economical manner by utilizing a considerably lesser amount of informational and numerical resources than hitherto estimated. Instead of the previously predicted linear scaling of the required ancilla dimension D with the number of qubits n, our recipe allows a realization of such a sequential cloning setup with an experimentally manageable ancilla of dimension at most D=3 up to n=15 qubits. We also address satisfactorily the possibility of providing an optimal range of sequential ancilla-qubit interactions for optimal cloning of arbitrary states under realistic experimental circumstances when only a restricted class of such bipartite interactions can be engineered in practice.

The trade-off between morphology and control in the co-optimized design of robots

PubMed Central

Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques. PMID:29023482

Smart Water: Energy-Water Optimization in Drinking Water Systems

EPA Science Inventory

This project aims to develop and commercialize a Smart Water Platform – Sensor-based Data-driven Energy-Water Optimization technology in drinking water systems. The key technological advances rely on cross-platform data acquisition and management system, model-based real-time sys...

μ-'Diving suit' for liquid-phase high-Q resonant detection.

PubMed

Yu, Haitao; Chen, Ying; Xu, Pengcheng; Xu, Tiegang; Bao, Yuyang; Li, Xinxin

2016-03-07

A resonant cantilever sensor is, for the first time, dressed in a water-proof 'diving suit' for real-time bio/chemical detection in liquid. The μ-'diving suit' technology can effectively avoid not only unsustainable resonance due to heavy liquid-damping, but also inevitable nonspecific adsorption on the cantilever body. Such a novel technology ensures long-time high-Q resonance of the cantilever in solution environment for real-time trace-concentration bio/chemical detection and analysis. After the formation of the integrated resonant micro-cantilever, a patterned photoresist and hydrophobic parylene thin-film are sequentially formed on top of the cantilever as sacrificial layer and water-proof coat, respectively. After sacrificial-layer release, an air gap is formed between the parylene coat and the cantilever to protect the resonant cantilever from heavy liquid damping effect. Only a small sensing-pool area, located at the cantilever free-end and locally coated with specific sensing-material, is exposed to the liquid analyte for gravimetric detection. The specifically adsorbed analyte mass can be real-time detected by recording the frequency-shift signal. In order to secure vibration movement of the cantilever and, simultaneously, reject liquid leakage from the sensing-pool region, a hydrophobic parylene made narrow slit structure is designed surrounding the sensing-pool. The anti-leakage effect of the narrow slit and damping limited resonance Q-factor are modelled and optimally designed. Integrated with electro-thermal resonance excitation and piezoresistive frequency readout, the cantilever is embedded in a micro-fluidic chip to form a lab-chip micro-system for liquid-phase bio/chemical detection. Experimental results show the Q-factor of 23 in water and longer than 20 hours liquid-phase continuous working time. Loaded with two kinds of sensing-materials at the sensing-pools, two types of sensing chips successfully show real-time liquid-phase detection to ppb-level organophosphorous pesticide of acephate and E.coli DH5α in PBS, respectively. The proposed method fundamentally solves the long-standing problem of being unable to operate a resonant micro-sensor in liquid well.

Adaptive Origami for Efficiently Folded Structures

DTIC Science & Technology

2016-02-01

design optimization to find optimal origami patterns for in-plane compression. 3. Self-folding and programmable material systems were developed for...2014, 1st place in the Midwest and 2nd place in the National 2014 SAMPE student research symposium). • Design of self-folding and programmable ... material systems: Nafion SMP Programming: To integrate active materials into origami, mechanical analysis and optimization tools where applied to the

Parameter Study for Optimizing the Mass of a Space Nuclear Power System Radiation Shield

DTIC Science & Technology

2002-03-01

long been selected as the best choice for neutron shielding of a SNPS [ 3 :24-30]. The low atomic number of both lithium and hydrogen allows...Integer :: missed(1:nBatches) Real(dp), Dimension(1: 3 ) :: r1, r2, omegaHat Real(dp) :: Radius1, Radius2, z1, z2, xi, omega , rFrac Real(dp) :: pAvg... 3 Motivation

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

NASA Astrophysics Data System (ADS)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this application of the proposed algorithm, TSEA, with several state-of-the-art multiobjective optimization algorithms reveals that TSEA outperforms these algorithms by providing retrofit solutions with greater reliability for the same costs (i.e., closer to the Pareto-optimal front) after the algorithms are executed for the same number of generations. This research also demonstrates that TSEA competes with and, in some situations, outperforms state-of-the-art multiobjective optimization algorithms such as NSGA II and SPEA 2 when applied to classic bicriteria test problems in the technical literature and other complex, sizable real-world applications. The successful implementation of TSEA contributes to the safety of aeronautical structures by providing a systematic way to guide aircraft structural retrofitting efforts, as well as a potentially useful algorithm for a wide range of multiobjective optimization problems in engineering and other fields.

Building Spoken Language in the First Plane

ERIC Educational Resources Information Center

Bettmann, Joen

2016-01-01

Through a strong Montessori orientation to the parameters of spoken language, Joen Bettmann makes the case for "materializing" spoken knowledge using the stimulation of real objects and real situations that promote mature discussion around the sensorial aspect of the prepared environment. She lists specific materials in the classroom…

Additive manufacturing: Toward holistic design

DOE PAGES

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.; ...

2017-03-18

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

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

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.

Interlaced photoacoustic and ultrasound imaging system with real-time coregistration for ovarian tissue characterization

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Li, Hai; Yuan, Guangqian; Kumavor, Patrick; Zanganeh, Saeid; Zhu, Quing

2014-07-01

Coregistered ultrasound (US) and photoacoustic imaging are emerging techniques for mapping the echogenic anatomical structure of tissue and its corresponding optical absorption. We report a 128-channel imaging system with real-time coregistration of the two modalities, which provides up to 15 coregistered frames per second limited by the laser pulse repetition rate. In addition, the system integrates a compact transvaginal imaging probe with a custom-designed fiber optic assembly for in vivo detection and characterization of human ovarian tissue. We present the coregistered US and photoacoustic imaging system structure, the optimal design of the PC interfacing software, and the reconfigurable field programmable gate array operation and optimization. Phantom experiments of system lateral resolution and axial sensitivity evaluation, examples of the real-time scanning of a tumor-bearing mouse, and ex vivo human ovaries studies are demonstrated.

Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

NASA Astrophysics Data System (ADS)

Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

2018-01-01

This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

Optimized growth and reorientation of anisotropic material based on evolution equations

NASA Astrophysics Data System (ADS)

Jantos, Dustin R.; Junker, Philipp; Hackl, Klaus

2018-07-01

Modern high-performance materials have inherent anisotropic elastic properties. The local material orientation can thus be considered to be an additional design variable for the topology optimization of structures containing such materials. In our previous work, we introduced a variational growth approach to topology optimization for isotropic, linear-elastic materials. We solved the optimization problem purely by application of Hamilton's principle. In this way, we were able to determine an evolution equation for the spatial distribution of density mass, which can be evaluated in an iterative process within a solitary finite element environment. We now add the local material orientation described by a set of three Euler angles as additional design variables into the three-dimensional model. This leads to three additional evolution equations that can be separately evaluated for each (material) point. Thus, no additional field unknown within the finite element approach is needed, and the evolution of the spatial distribution of density mass and the evolution of the Euler angles can be evaluated simultaneously.

Combinatorial materials synthesis and high-throughput screening: an integrated materials chip approach to mapping phase diagrams and discovery and optimization of functional materials.

PubMed

Xiang, X D

Combinatorial materials synthesis methods and high-throughput evaluation techniques have been developed to accelerate the process of materials discovery and optimization and phase-diagram mapping. Analogous to integrated circuit chips, integrated materials chips containing thousands of discrete different compositions or continuous phase diagrams, often in the form of high-quality epitaxial thin films, can be fabricated and screened for interesting properties. Microspot x-ray method, various optical measurement techniques, and a novel evanescent microwave microscope have been used to characterize the structural, optical, magnetic, and electrical properties of samples on the materials chips. These techniques are routinely used to discover/optimize and map phase diagrams of ferroelectric, dielectric, optical, magnetic, and superconducting materials.

Real time optimization algorithm for wavefront sensorless adaptive optics OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Verstraete, Hans R. G. W.; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel J.; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Sarunic, Marinko V.; Verhaegen, Michel; Jian, Yifan

2017-02-01

Optical Coherence Tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. A limitation of the performance and utilization of the OCT systems has been the lateral resolution. Through the combination of wavefront sensorless adaptive optics with dual variable optical elements, we present a compact lens based OCT system that is capable of imaging the photoreceptor mosaic. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient eyes, and a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators for aberration correction to obtain near diffraction limited imaging at the retina. A parallel processing computational platform permitted real-time image acquisition and display. The Data-based Online Nonlinear Extremum seeker (DONE) algorithm was used for real time optimization of the wavefront sensorless adaptive optics OCT, and the performance was compared with a coordinate search algorithm. Cross sectional images of the retinal layers and en face images of the cone photoreceptor mosaic acquired in vivo from research volunteers before and after WSAO optimization are presented. Applying the DONE algorithm in vivo for wavefront sensorless AO-OCT demonstrates that the DONE algorithm succeeds in drastically improving the signal while achieving a computational time of 1 ms per iteration, making it applicable for high speed real time applications.

A hyperspectral image optimizing method based on sub-pixel MTF analysis

NASA Astrophysics Data System (ADS)

Wang, Yun; Li, Kai; Wang, Jinqiang; Zhu, Yajie

2015-04-01

Hyperspectral imaging is used to collect tens or hundreds of images continuously divided across electromagnetic spectrum so that the details under different wavelengths could be represented. A popular hyperspectral imaging methods uses a tunable optical band-pass filter settled in front of the focal plane to acquire images of different wavelengths. In order to alleviate the influence of chromatic aberration in some segments in a hyperspectral series, in this paper, a hyperspectral optimizing method uses sub-pixel MTF to evaluate image blurring quality was provided. This method acquired the edge feature in the target window by means of the line spread function (LSF) to calculate the reliable position of the edge feature, then the evaluation grid in each line was interpolated by the real pixel value based on its relative position to the optimal edge and the sub-pixel MTF was used to analyze the image in frequency domain, by which MTF calculation dimension was increased. The sub-pixel MTF evaluation was reliable, since no image rotation and pixel value estimation was needed, and no artificial information was introduced. With theoretical analysis, the method proposed in this paper is reliable and efficient when evaluation the common images with edges of small tilt angle in real scene. It also provided a direction for the following hyperspectral image blurring evaluation and the real-time focal plane adjustment in real time in related imaging system.

The Model Optimization, Uncertainty, and SEnsitivity analysis (MOUSE) toolbox: overview and application

USDA-ARS?s Scientific Manuscript database

For several decades, optimization and sensitivity/uncertainty analysis of environmental models has been the subject of extensive research. Although much progress has been made and sophisticated methods developed, the growing complexity of environmental models to represent real-world systems makes it...

Removal of methylene blue from aqueous solution by wood millet carbon optimization using response surface methodology

NASA Astrophysics Data System (ADS)

Ghaedi, Mehrorang; Kokhdan, Syamak Nasiri

2015-02-01

The use of cheep, non-toxic, safe and easily available adsorbent are efficient and recommended material and alternative to the current expensive substance for pollutant removal from wastewater. The activated carbon prepared from wood waste of local tree (millet) extensively was applied for quantitative removal of methylene blue (MB), while simply. It was used to re-used after heating and washing with alkaline solution of ethanol. This new adsorbent was characterized by using BET surface area measurement, FT-IR, pH determination at zero point of charge (pHZPC) and Boehm titration method. Response surface methodology (RSM) by at least the number of experiments main and interaction of experimental conditions such as pH of solution, contact time, initial dye concentration and adsorbent dosage was optimized and set as pH 7, contact time 18 min, initial dye concentration 20 ppm and 0.2 g of adsorbent. It was found that variable such as pH and amount of adsorbent as solely or combination effects seriously affect the removal percentage. The fitting experimental data with conventional models reveal the applicability of isotherm models Langmuir model for their well presentation and description and Kinetic real rate of adsorption at most conditions efficiently can be represented pseudo-second order, and intra-particle diffusion. It novel material is good candidate for removal of huge amount of MB (20 ppm) in short time (18 min) by consumption of small amount (0.2 g).

New solutions and technologies for uncooled infrared imaging

NASA Astrophysics Data System (ADS)

Rollin, Joël.; Diaz, Frédéric; Fontaine, Christophe; Loiseaux, Brigitte; Lee, Mane-Si Laure; Clienti, Christophe; Lemonnier, Fabrice; Zhang, Xianghua; Calvez, Laurent

2013-06-01

The military uncooled infrared market is driven by the continued cost reduction of the focal plane arrays whilst maintaining high standards of sensitivity and steering towards smaller pixel sizes. As a consequence, new optical solutions are called for. Two approaches can come into play: the bottom up option consists in allocating improvements to each contributor and the top down process rather relies on an overall optimization of the complete image channel. The University of Rennes I with Thales Angénieux alongside has been working over the past decade through French MOD funding's, on low cost alternatives of infrared materials based upon chalcogenide glasses. A special care has been laid on the enhancement of their mechanical properties and their ability to be moulded according to complex shapes. New manufacturing means developments capable of better yields for the raw materials will be addressed, too. Beyond the mere lenses budget cuts, a wave front coding process can ease a global optimization. This technic gives a way of relaxing optical constraints or upgrading thermal device performances through an increase of the focus depths and desensitization against temperature drifts: it combines image processing and the use of smart optical components. Thales achievements in such topics will be enlightened and the trade-off between image quality correction levels and low consumption/ real time processing, as might be required in hand-free night vision devices, will be emphasized. It is worth mentioning that both approaches are deeply leaning on each other.

Validated numerical simulation model of a dielectric elastomer generator

NASA Astrophysics Data System (ADS)

Foerster, Florentine; Moessinger, Holger; Schlaak, Helmut F.

2013-04-01

Dielectric elastomer generators (DEG) produce electrical energy by converting mechanical into electrical energy. Efficient operation requires homogeneous deformation of each single layer. However, by different internal and external influences like supports or the shape of a DEG the deformation will be inhomogeneous and hence negatively affect the amount of the generated electrical energy. Optimization of the deformation behavior leads to improved efficiency of the DEG and consequently to higher energy gain. In this work a numerical simulation model of a multilayer dielectric elastomer generator is developed using the FEM software ANSYS. The analyzed multilayer DEG consists of 49 active dielectric layers with layer thicknesses of 50 μm. The elastomer is silicone (PDMS) while the compliant electrodes are made of graphite powder. In the simulation the real material parameters of the PDMS and the graphite electrodes need to be included. Therefore, the mechanical and electrical material parameters of the PDMS are determined by experimental investigations of test samples while the electrode parameters are determined by numerical simulations of test samples. The numerical simulation of the DEG is carried out as coupled electro-mechanical simulation for the constant voltage energy harvesting cycle. Finally, the derived numerical simulation model is validated by comparison with analytical calculations and further simulated DEG configurations. The comparison of the determined results show good accordance with regard to the deformation of the DEG. Based on the validated model it is now possible to optimize the DEG layout for improved deformation behavior with further simulations.

Automatic optimization high-speed high-resolution OCT retinal imaging at 1μm

NASA Astrophysics Data System (ADS)

Cua, Michelle; Liu, Xiyun; Miao, Dongkai; Lee, Sujin; Lee, Sieun; Bonora, Stefano; Zawadzki, Robert J.; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2015-03-01

High-resolution OCT retinal imaging is important in providing visualization of various retinal structures to aid researchers in better understanding the pathogenesis of vision-robbing diseases. However, conventional optical coherence tomography (OCT) systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking optical coherence tomography (OCT) system with automatic optimization for high-resolution, extended-focal-range clinical retinal imaging. A variable-focus liquid lens was added to correct for de-focus in real-time. A GPU-accelerated segmentation and optimization was used to provide real-time layer-specific enface visualization as well as depth-specific focus adjustment. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the ONH, from which we extracted clinically-relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Stochastic Optimization for Unit Commitment-A Review

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

Zheng, Qipeng P.; Wang, Jianhui; Liu, Andrew L.

2015-07-01

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave ismore » focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications.« less

SVM-Based Synthetic Fingerprint Discrimination Algorithm and Quantitative Optimization Strategy

PubMed Central

Chen, Suhang; Chang, Sheng; Huang, Qijun; He, Jin; Wang, Hao; Huang, Qiangui

2014-01-01

Synthetic fingerprints are a potential threat to automatic fingerprint identification systems (AFISs). In this paper, we propose an algorithm to discriminate synthetic fingerprints from real ones. First, four typical characteristic factors—the ridge distance features, global gray features, frequency feature and Harris Corner feature—are extracted. Then, a support vector machine (SVM) is used to distinguish synthetic fingerprints from real fingerprints. The experiments demonstrate that this method can achieve a recognition accuracy rate of over 98% for two discrete synthetic fingerprint databases as well as a mixed database. Furthermore, a performance factor that can evaluate the SVM's accuracy and efficiency is presented, and a quantitative optimization strategy is established for the first time. After the optimization of our synthetic fingerprint discrimination task, the polynomial kernel with a training sample proportion of 5% is the optimized value when the minimum accuracy requirement is 95%. The radial basis function (RBF) kernel with a training sample proportion of 15% is a more suitable choice when the minimum accuracy requirement is 98%. PMID:25347063

Real-time management of an urban groundwater well field threatened by pollution.

PubMed

Bauser, Gero; Franssen, Harrie-Jan Hendricks; Kaiser, Hans-Peter; Kuhlmann, Ulrich; Stauffer, Fritz; Kinzelbach, Wolfgang

2010-09-01

We present an optimal real-time control approach for the management of drinking water well fields. The methodology is applied to the Hardhof field in the city of Zurich, Switzerland, which is threatened by diffuse pollution. The risk of attracting pollutants is higher if the pumping rate is increased and can be reduced by increasing artificial recharge (AR) or by adaptive allocation of the AR. The method was first tested in offline simulations with a three-dimensional finite element variably saturated subsurface flow model for the period January 2004-August 2005. The simulations revealed that (1) optimal control results were more effective than the historical control results and (2) the spatial distribution of AR should be different from the historical one. Next, the methodology was extended to a real-time control method based on the Ensemble Kalman Filter method, using 87 online groundwater head measurements, and tested at the site. The real-time control of the well field resulted in a decrease of the electrical conductivity of the water at critical measurement points which indicates a reduced inflow of water originating from contaminated sites. It can be concluded that the simulation and the application confirm the feasibility of the real-time control concept.

Optimizing the real-time automatic location of the events produced in Romania using an advanced processing system

NASA Astrophysics Data System (ADS)

Neagoe, Cristian; Grecu, Bogdan; Manea, Liviu

2016-04-01

National Institute for Earth Physics (NIEP) operates a real time seismic network which is designed to monitor the seismic activity on the Romanian territory, which is dominated by the intermediate earthquakes (60-200 km) from Vrancea area. The ability to reduce the impact of earthquakes on society depends on the existence of a large number of high-quality observational data. The development of the network in recent years and an advanced seismic acquisition are crucial to achieving this objective. The software package used to perform the automatic real-time locations is Seiscomp3. An accurate choice of the Seiscomp3 setting parameters is necessary to ensure the best performance of the real-time system i.e., the most accurate location for the earthquakes and avoiding any false events. The aim of this study is to optimize the algorithms of the real-time system that detect and locate the earthquakes in the monitored area. This goal is pursued by testing different parameters (e.g., STA/LTA, filters applied to the waveforms) on a data set of representative earthquakes of the local seismicity. The results are compared with the locations from the Romanian Catalogue ROMPLUS.

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery

PubMed Central

Qi, Baogui; Zhuang, Yin; Chen, He; Chen, Liang

2018-01-01

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited. PMID:29693585

On-Board, Real-Time Preprocessing System for Optical Remote-Sensing Imagery.

PubMed

Qi, Baogui; Shi, Hao; Zhuang, Yin; Chen, He; Chen, Liang

2018-04-25

With the development of remote-sensing technology, optical remote-sensing imagery processing has played an important role in many application fields, such as geological exploration and natural disaster prevention. However, relative radiation correction and geometric correction are key steps in preprocessing because raw image data without preprocessing will cause poor performance during application. Traditionally, remote-sensing data are downlinked to the ground station, preprocessed, and distributed to users. This process generates long delays, which is a major bottleneck in real-time applications for remote-sensing data. Therefore, on-board, real-time image preprocessing is greatly desired. In this paper, a real-time processing architecture for on-board imagery preprocessing is proposed. First, a hierarchical optimization and mapping method is proposed to realize the preprocessing algorithm in a hardware structure, which can effectively reduce the computation burden of on-board processing. Second, a co-processing system using a field-programmable gate array (FPGA) and a digital signal processor (DSP; altogether, FPGA-DSP) based on optimization is designed to realize real-time preprocessing. The experimental results demonstrate the potential application of our system to an on-board processor, for which resources and power consumption are limited.

A Modified Particle Swarm Optimization Technique for Finding Optimal Designs for Mixture Models

PubMed Central

Wong, Weng Kee; Chen, Ray-Bing; Huang, Chien-Chih; Wang, Weichung

2015-01-01

Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and without constraints on the components, and also for related models, like the log contrast models. We also compare the modified PSO performance with Fedorov's algorithm, a popular algorithm used to generate optimal designs, Cocktail algorithm, and the recent algorithm proposed by [1]. PMID:26091237

Robust control of systems with real parameter uncertainty and unmodelled dynamics

NASA Technical Reports Server (NTRS)

Chang, Bor-Chin; Fischl, Robert

1991-01-01

During this research period we have made significant progress in the four proposed areas: (1) design of robust controllers via H infinity optimization; (2) design of robust controllers via mixed H2/H infinity optimization; (3) M-delta structure and robust stability analysis for structured uncertainties; and (4) a study on controllability and observability of perturbed plant. It is well known now that the two-Riccati-equation solution to the H infinity control problem can be used to characterize all possible stabilizing optimal or suboptimal H infinity controllers if the optimal H infinity norm or gamma, an upper bound of a suboptimal H infinity norm, is given. In this research, we discovered some useful properties of these H infinity Riccati solutions. Among them, the most prominent one is that the spectral radius of the product of these two Riccati solutions is a continuous, nonincreasing, convex function of gamma in the domain of interest. Based on these properties, quadratically convergent algorithms are developed to compute the optimal H infinity norm. We also set up a detailed procedure for applying the H infinity theory to robust control systems design. The desire to design controllers with H infinity robustness but H(exp 2) performance has recently resulted in mixed H(exp 2) and H infinity control problem formulation. The mixed H(exp 2)/H infinity problem have drawn the attention of many investigators. However, solution is only available for special cases of this problem. We formulated a relatively realistic control problem with H(exp 2) performance index and H infinity robustness constraint into a more general mixed H(exp 2)/H infinity problem. No optimal solution yet is available for this more general mixed H(exp 2)/H infinity problem. Although the optimal solution for this mixed H(exp 2)/H infinity control has not yet been found, we proposed a design approach which can be used through proper choice of the available design parameters to influence both robustness and performance. For a large class of linear time-invariant systems with real parametric perturbations, the coefficient vector of the characteristic polynomial is a multilinear function of the real parameter vector. Based on this multilinear mapping relationship together with the recent developments for polytopic polynomials and parameter domain partition technique, we proposed an iterative algorithm for coupling the real structured singular value.

RHODES-ITMS Tempe field test project : implementation and field testing of RHODES, a real-time traffic adaptive control system

DOT National Transportation Integrated Search

2001-09-01

RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchang...

The Development of the Real Number System.

ERIC Educational Resources Information Center

Kaplan, Jerome D.

These materials were designed to provide a logical development of the number systems from the natural numbers through the real number system. The course attempts to develop pedagogical strategies which will enable naive mathematics students to cope with its content. Revised versions of these materials will be used with prospective elementary…

20 CFR 404.1082 - Rentals from real estate; material participation.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., SURVIVORS AND DISABILITY INSURANCE (1950- ) Employment, Wages, Self-Employment, and Self-Employment Income Self-Employment Income § 404.1082 Rentals from real estate; material participation. (a) In general... earnings from self-employment, unless you receive the rentals in the course of a trade or business as a...

20 CFR 404.1082 - Rentals from real estate; material participation.

Code of Federal Regulations, 2011 CFR

2011-04-01

..., SURVIVORS AND DISABILITY INSURANCE (1950- ) Employment, Wages, Self-Employment, and Self-Employment Income Self-Employment Income § 404.1082 Rentals from real estate; material participation. (a) In general... earnings from self-employment, unless you receive the rentals in the course of a trade or business as a...

20 CFR 404.1082 - Rentals from real estate; material participation.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., SURVIVORS AND DISABILITY INSURANCE (1950- ) Employment, Wages, Self-Employment, and Self-Employment Income Self-Employment Income § 404.1082 Rentals from real estate; material participation. (a) In general... earnings from self-employment, unless you receive the rentals in the course of a trade or business as a...

20 CFR 404.1082 - Rentals from real estate; material participation.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., SURVIVORS AND DISABILITY INSURANCE (1950- ) Employment, Wages, Self-Employment, and Self-Employment Income Self-Employment Income § 404.1082 Rentals from real estate; material participation. (a) In general... earnings from self-employment, unless you receive the rentals in the course of a trade or business as a...

20 CFR 404.1082 - Rentals from real estate; material participation.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., SURVIVORS AND DISABILITY INSURANCE (1950- ) Employment, Wages, Self-Employment, and Self-Employment Income Self-Employment Income § 404.1082 Rentals from real estate; material participation. (a) In general... earnings from self-employment, unless you receive the rentals in the course of a trade or business as a...

SPOT-A SENSOR PLACEMENT OPTIMIZATION TOOL FOR ...

EPA Pesticide Factsheets

journal article This paper presents SPOT, a Sensor Placement Optimization Tool. SPOT provides a toolkit that facilitates research in sensor placement optimization and enables the practical application of sensor placement solvers to real-world CWS design applications. This paper provides an overview of SPOT’s key features, and then illustrates how this tool can be flexibly applied to solve a variety of different types of sensor placement problems.

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.

A new proof of the generalized Hamiltonian–Real calculus

PubMed Central

Gao, Hua; Mandic, Danilo P.

2016-01-01

The recently introduced generalized Hamiltonian–Real (GHR) calculus comprises, for the first time, the product and chain rules that makes it a powerful tool for quaternion-based optimization and adaptive signal processing. In this paper, we introduce novel dual relationships between the GHR calculus and multivariate real calculus, in order to provide a new, simpler proof of the GHR derivative rules. This further reinforces the theoretical foundation of the GHR calculus and provides a convenient methodology for generic extensions of real- and complex-valued learning algorithms to the quaternion domain.

Parallel algorithms for islanded microgrid with photovoltaic and energy storage systems planning optimization problem: Material selection and quantity demand optimization

NASA Astrophysics Data System (ADS)

Cao, Yang; Liu, Chun; Huang, Yuehui; Wang, Tieqiang; Sun, Chenjun; Yuan, Yue; Zhang, Xinsong; Wu, Shuyun

2017-02-01

With the development of roof photovoltaic power (PV) generation technology and the increasingly urgent need to improve supply reliability levels in remote areas, islanded microgrid with photovoltaic and energy storage systems (IMPE) is developing rapidly. The high costs of photovoltaic panel material and energy storage battery material have become the primary factors that hinder the development of IMPE. The advantages and disadvantages of different types of photovoltaic panel materials and energy storage battery materials are analyzed in this paper, and guidance is provided on material selection for IMPE planners. The time sequential simulation method is applied to optimize material demands of the IMPE. The model is solved by parallel algorithms that are provided by a commercial solver named CPLEX. Finally, to verify the model, an actual IMPE is selected as a case system. Simulation results on the case system indicate that the optimization model and corresponding algorithm is feasible. Guidance for material selection and quantity demand for IMPEs in remote areas is provided by this method.

A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

An Optimized Trajectory Planning for Welding Robot

NASA Astrophysics Data System (ADS)

Chen, Zhilong; Wang, Jun; Li, Shuting; Ren, Jun; Wang, Quan; Cheng, Qunchao; Li, Wentao

2018-03-01

In order to improve the welding efficiency and quality, this paper studies the combined planning between welding parameters and space trajectory for welding robot and proposes a trajectory planning method with high real-time performance, strong controllability and small welding error. By adding the virtual joint at the end-effector, the appropriate virtual joint model is established and the welding process parameters are represented by the virtual joint variables. The trajectory planning is carried out in the robot joint space, which makes the control of the welding process parameters more intuitive and convenient. By using the virtual joint model combined with the B-spline curve affine invariant, the welding process parameters are indirectly controlled by controlling the motion curve of the real joint. To solve the optimal time solution as the goal, the welding process parameters and joint space trajectory joint planning are optimized.

Photovoltaic Inverter Controllers Seeking AC Optimal Power Flow Solutions

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

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

This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual ..epsilon..-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules formore » cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time.« less

Processor tradeoffs in distributed real-time systems

NASA Technical Reports Server (NTRS)

Krishna, C. M.; Shin, Kang G.; Bhandari, Inderpal S.

1987-01-01

The problem of the optimization of the design of real-time distributed systems is examined with reference to a class of computer architectures similar to the continuously reconfigurable multiprocessor flight control system structure, CM2FCS. Particular attention is given to the impact of processor replacement and the burn-in time on the probability of dynamic failure and mean cost. The solution is obtained numerically and interpreted in the context of real-time applications.

VAXELN Experimentation: Programming a Real-Time Periodic Task Dispatcher Using VAXELN Ada 1.1

DTIC Science & Technology

1987-11-01

synchronization to the SQM and VAXELN semaphores. Based on real-time scheduling theory, the optimal rate-monotonic scheduling algorithm [Lui 73...schedulability test based on the rate-monotonic algorithm , namely task-lumping [Sha 871, was necessary to cal- culate the theoretically expected schedulability...8217 Guide Digital Equipment Corporation, Maynard, MA, 1986. [Lui 73] Liu, C.L., Layland, J.W. Scheduling Algorithms for Multi-programming in a Hard-Real-Time

A 'smart' tube holder enables real-time sample monitoring in a standard lab centrifuge.

PubMed

Hoang, Tony; Moskwa, Nicholas; Halvorsen, Ken

2018-01-01

The centrifuge is among the oldest and most widely used pieces of laboratory equipment, with significant applications that include clinical diagnostics and biomedical research. A major limitation of laboratory centrifuges is their "black box" nature, limiting sample observation to before and after centrifugation. Thus, optimized protocols require significant trial and error, while unoptimized protocols waste time by centrifuging longer than necessary or material due to incomplete sedimentation. Here, we developed an instrumented centrifuge tube receptacle compatible with several commercial benchtop centrifuges that can provide real-time sample analysis during centrifugation. We demonstrated the system by monitoring cell separations during centrifugation for different spin speeds, concentrations, buffers, cell types, and temperatures. We show that the collected data are valuable for analytical purposes (e.g. quality control), or as feedback to the user or the instrument. For the latter, we verified an adaptation where complete sedimentation turned off the centrifuge and notified the user by a text message. Our system adds new functionality to existing laboratory centrifuges, saving users time and providing useful feedback. This add-on potentially enables new analytical applications for an instrument that has remained largely unchanged for decades.

A ‘smart’ tube holder enables real-time sample monitoring in a standard lab centrifuge

PubMed Central

Hoang, Tony; Moskwa, Nicholas

2018-01-01

The centrifuge is among the oldest and most widely used pieces of laboratory equipment, with significant applications that include clinical diagnostics and biomedical research. A major limitation of laboratory centrifuges is their “black box” nature, limiting sample observation to before and after centrifugation. Thus, optimized protocols require significant trial and error, while unoptimized protocols waste time by centrifuging longer than necessary or material due to incomplete sedimentation. Here, we developed an instrumented centrifuge tube receptacle compatible with several commercial benchtop centrifuges that can provide real-time sample analysis during centrifugation. We demonstrated the system by monitoring cell separations during centrifugation for different spin speeds, concentrations, buffers, cell types, and temperatures. We show that the collected data are valuable for analytical purposes (e.g. quality control), or as feedback to the user or the instrument. For the latter, we verified an adaptation where complete sedimentation turned off the centrifuge and notified the user by a text message. Our system adds new functionality to existing laboratory centrifuges, saving users time and providing useful feedback. This add-on potentially enables new analytical applications for an instrument that has remained largely unchanged for decades. PMID:29659624

Real-Time Seismic Data from the Bottom Sea

PubMed Central

Roset, Xavier; Trullols, Enric; Artero-Delgado, Carola; Prat, Joana; Massana, Immaculada; Carbonell, Montserrat; Barco de la Torre, Jaime; Toma, Daniel Mihai

2018-01-01

An anchored marine seismometer, acquiring real-time seismic data, has been built and tested. The system consists of an underwater seismometer, a surface buoy, and a mooring line that connects them. Inductive communication through the mooring line provides an inexpensive, reliable, and flexible solution. Prior to the deployment the dynamics of the system have been simulated numerically in order to find optimal materials, cables, buoys, and connections under critical marine conditions. The seismometer used is a high sensitivity triaxial broadband geophone able to measure low vibrational signals produced by the underwater seismic events. The power to operate the surface buoy is provided by solar panels. Additional batteries are needed for the underwater unit. In this paper we also present the first results and an earthquake detection of a prototype system that demonstrates the feasibility of this concept. The seismometer transmits continuous data at a rate of 1000 bps to a controller equipped with a radio link in the surface buoy. A GPS receiver on the surface buoy has been configured to perform accurate timestamps on the seismic data, which makes it possible to integrate the seismic data from these marine seismometers into the existing seismic network. PMID:29642479

Real-time measurements of crystallization processes in viscoelastic polymeric photonic crystals

NASA Astrophysics Data System (ADS)

Snoswell, David R. E.; Finlayson, Chris E.; Zhao, Qibin; Baumberg, Jeremy J.

2015-11-01

We present a study of the dynamic shear ordering of viscoelastic photonic crystals, based on core-shell polymeric composite particles. Using an adapted shear-cell arrangement, the crystalline ordering of the material under conditions of oscillatory shear is interrogated in real time, through both video imaging and from the optical transmission spectra of the cell. In order to gain a deeper understanding of the macroscopic influences of shear on the crystallization process in this solvent-free system, the development of bulk ordering is studied as a function of the key parameters including duty cycle and shear-strain magnitude. In particular, optimal ordering is observed from a prerandomized sample at shear strains of around 160%, for 1-Hz oscillations. This ordering reaches completion over time scales of order 10 s. These observations suggest significant local strains are needed to drive nanoparticles through energy barriers, and that local creep is needed to break temporal symmetry in such high-viscosity nanoassemblies. Crystal shear-melting effects are also characterized under conditions of constant shear rate. These quantitative experiments aim to stimulate the development of theoretical models which can deal with the strong local particle interactions in this system.

Local flaps: a real-time finite element based solution to the plastic surgery defect puzzle.

PubMed

Sifakis, Eftychios; Hellrung, Jeffrey; Teran, Joseph; Oliker, Aaron; Cutting, Court

2009-01-01

One of the most fundamental challenges in plastic surgery is the alteration of the geometry and topology of the skin. The specific decisions made by the surgeon concerning the size and shape of the tissue to be removed and the subsequent closure of the resulting wound may have a dramatic affect on the quality of life for the patient after the procedure is completed. The plastic surgeon must look at the defect created as an organic puzzle, designing the optimal pattern to close the hole aesthetically and efficiently. In the past, such skills were the distillation of years of hands-on practice on live patients, while relevant reference material was limited to two-dimensional illustrations. Practicing this procedure on a personal computer [1] has been largely impractical to date, but recent technological advances may come to challenge this limitation. We present a comprehensive real-time virtual surgical environment, based on finite element modeling and simulation of tissue cutting and manipulation. Our system demonstrates the fundamental building blocks of plastic surgery procedures on a localized tissue flap, and provides a proof of concept for larger simulation systems usable in the authoring of complex procedures on elaborate subject geometry.

Assessing direct analysis in real-time-mass spectrometry (DART-MS) for the rapid identification of additives in food packaging.

PubMed

Ackerman, L K; Noonan, G O; Begley, T H

2009-12-01

The ambient ionization technique direct analysis in real time (DART) was characterized and evaluated for the screening of food packaging for the presence of packaging additives using a benchtop mass spectrometer (MS). Approximate optimum conditions were determined for 13 common food-packaging additives, including plasticizers, anti-oxidants, colorants, grease-proofers, and ultraviolet light stabilizers. Method sensitivity and linearity were evaluated using solutions and characterized polymer samples. Additionally, the response of a model additive (di-ethyl-hexyl-phthalate) was examined across a range of sample positions, DART, and MS conditions (temperature, voltage and helium flow). Under optimal conditions, molecular ion (M+H+) was the major ion for most additives. Additive responses were highly sensitive to sample and DART source orientation, as well as to DART flow rates, temperatures, and MS inlet voltages, respectively. DART-MS response was neither consistently linear nor quantitative in this setting, and sensitivity varied by additive. All additives studied were rapidly identified in multiple food-packaging materials by DART-MS/MS, suggesting this technique can be used to screen food packaging rapidly. However, method sensitivity and quantitation requires further study and improvement.

Real-Time Seismic Data from the Bottom Sea.

PubMed

Roset, Xavier; Trullols, Enric; Artero-Delgado, Carola; Prat, Joana; Del Río, Joaquin; Massana, Immaculada; Carbonell, Montserrat; Barco de la Torre, Jaime; Toma, Daniel Mihai

2018-04-08

An anchored marine seismometer, acquiring real-time seismic data, has been built and tested. The system consists of an underwater seismometer, a surface buoy, and a mooring line that connects them. Inductive communication through the mooring line provides an inexpensive, reliable, and flexible solution. Prior to the deployment the dynamics of the system have been simulated numerically in order to find optimal materials, cables, buoys, and connections under critical marine conditions. The seismometer used is a high sensitivity triaxial broadband geophone able to measure low vibrational signals produced by the underwater seismic events. The power to operate the surface buoy is provided by solar panels. Additional batteries are needed for the underwater unit. In this paper we also present the first results and an earthquake detection of a prototype system that demonstrates the feasibility of this concept. The seismometer transmits continuous data at a rate of 1000 bps to a controller equipped with a radio link in the surface buoy. A GPS receiver on the surface buoy has been configured to perform accurate timestamps on the seismic data, which makes it possible to integrate the seismic data from these marine seismometers into the existing seismic network.

On the use of PGD for optimal control applied to automated fibre placement

NASA Astrophysics Data System (ADS)

Bur, N.; Joyot, P.

2017-10-01

Automated Fibre Placement (AFP) is an incipient manufacturing process for composite structures. Despite its concep-tual simplicity it involves many complexities related to the necessity of melting the thermoplastic at the interface tape-substrate, ensuring the consolidation that needs the diffusion of molecules and control the residual stresses installation responsible of the residual deformations of the formed parts. The optimisation of the process and the determination of the process window cannot be achieved in a traditional way since it requires a plethora of trials/errors or numerical simulations, because there are many parameters involved in the characterisation of the material and the process. Using reduced order modelling such as the so called Proper Generalised Decomposition method, allows the construction of multi-parametric solution taking into account many parameters. This leads to virtual charts that can be explored on-line in real time in order to perform process optimisation or on-line simulation-based control. Thus, for a given set of parameters, determining the power leading to an optimal temperature becomes easy. However, instead of controlling the power knowing the temperature field by particularizing an abacus, we propose here an approach based on optimal control: we solve by PGD a dual problem from heat equation and optimality criteria. To circumvent numerical issue due to ill-conditioned system, we propose an algorithm based on Uzawa's method. That way, we are able to solve the dual problem, setting the desired state as an extra-coordinate in the PGD framework. In a single computation, we get both the temperature field and the required heat flux to reach a parametric optimal temperature on a given zone.

A near-real-time full-parallax holographic display for remote operations

NASA Technical Reports Server (NTRS)

Iavecchia, Helene P.; Huff, Lloyd; Marzwell, Neville I.

1991-01-01

A near real-time, full parallax holographic display system was developed that has the potential to provide a 3-D display for remote handling operations in hazardous environments. The major components of the system consist of a stack of three spatial light modulators which serves as the object source of the hologram; a near real-time holographic recording material (such as thermoplastic and photopolymer); and an optical system for relaying SLM images to the holographic recording material and to the observer for viewing.

Using a water-food-energy nexus approach for optimal irrigation management during drought events in Nebraska

NASA Astrophysics Data System (ADS)

Campana, P. E.; Zhang, J.; Yao, T.; Melton, F. S.; Yan, J.

2017-12-01

Climate change and drought have severe impacts on the agricultural sector affecting crop yields, water availability, and energy consumption for irrigation. Monitoring, assessing and mitigating the effects of climate change and drought on the agricultural and energy sectors are fundamental challenges that require investigation for water, food, and energy security issues. Using an integrated water-food-energy nexus approach, this study is developing a comprehensive drought management system through integration of real-time drought monitoring with real-time irrigation management. The spatially explicit model developed, GIS-OptiCE, can be used for simulation, multi-criteria optimization and generation of forecasts to support irrigation management. To demonstrate the value of the approach, the model has been applied to one major corn region in Nebraska to study the effects of the 2012 drought on crop yield and irrigation water/energy requirements as compared to a wet year such as 2009. The water-food-energy interrelationships evaluated show that significant water volumes and energy are required to halt the negative effects of drought on the crop yield. The multi-criteria optimization problem applied in this study indicates that the optimal solutions of irrigation do not necessarily correspond to those that would produce the maximum crop yields, depending on both water and economic constraints. In particular, crop pricing forecasts are extremely important to define the optimal irrigation management strategy. The model developed shows great potential in precision agriculture by providing near real-time data products including information on evapotranspiration, irrigation volumes, energy requirements, predicted crop growth, and nutrient requirements.

Real-time adaptive ramp metering : phase I, MILOS proof of concept (multi-objective, integrated, large-scale, optimized system).

DOT National Transportation Integrated Search

2006-12-01

Over the last several years, researchers at the University of Arizonas ATLAS Center have developed an adaptive ramp : metering system referred to as MILOS (Multi-Objective, Integrated, Large-Scale, Optimized System). The goal of this project : is ...

Overview and application of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) toolbox

USDA-ARS?s Scientific Manuscript database

For several decades, optimization and sensitivity/uncertainty analysis of environmental models has been the subject of extensive research. Although much progress has been made and sophisticated methods developed, the growing complexity of environmental models to represent real-world systems makes it...

TH-AB-202-09: Direct-Aperture Optimization for Combined MV+kV Dose Planning in Fluoroscopic Real-Time Tumor-Tracking Radiation Therapy

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

Liu, X; Belcher, AH; Grelewicz, Z

Purpose: Real-time kV fluoroscopic tumor tracking has the benefit of direct tumor position monitoring. However, there is clinical concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work addresses this specific issue by proposing a combined MV+kV direct-aperture optimization (DAO) approach to integrate the kV imaging beam into a treatment planning such that the kV radiation is considered as a contributor to the overall dose delivery. Methods: The combined MV+kV DAO approach includes three algorithms. First, a projected Quasi-Newton algorithm (L-BFGS) is used to find optimized fluence with MV+kV dose formore » the best possible dose distribution. Then, Engel’s algorithm is applied to optimize the total number of monitor units and heuristically optimize the number of apertures. Finally, an aperture shape optimization (ASO) algorithm is applied to locally optimize the leaf positions of MLC. Results: Compared to conventional DAO MV plans with continuous kV fluoroscopic tracking, combined MV+kV DAO plan leads to a reduction in the total number of MV monitor units due to inclusion of kV dose as part of the PTV, and was also found to reduce the mean and maximum doses on the organs at risk (OAR). Compared to conventional DAO MV plan without kV tracking, the OAR dose in the combined MV+kV DAO plan was only slightly higher. DVH curves show that combined MV+kV DAO plan provided about the same PTV coverage as that in the conventional DAO plans without kV imaging. Conclusion: We report a combined MV+kV DAO approach that allows real time kV imager tumor tracking with only a trivial increasing on the OAR doses while providing the same coverage to PTV. The approach is suitable for clinic implementation.« less

Nowcast model for hazardous material spill prevention and response, San Francisco Bay, California

USGS Publications Warehouse

Cheng, Ralph T.; Wilmot, Wayne L.; Galt, Jerry A.

1997-01-01

The National Oceanic and Atmospheric Administration (NOAA) installed the Physical Oceanographic Real-time System (PORTS) in San Francisco Bay, California, to provide real-time observations of tides, tidal currents, and meteorological conditions to, among other purposes, guide hazardous material spill prevention and response. Integrated with nowcast modeling techniques and dissemination of real-time data and the nowcasting results through the Internet on the World Wide Web, emerging technologies used in PORTS for real-time data collection forms a nowcast modeling system. Users can download tides and tidal current distribution in San Francisco Bay for their specific applications and/or for further analysis.

Railroad Regulation: Changes in Freight Railroad Rates from 1997 through 2000

DTIC Science & Technology

2002-06-01

Routes, 1990–2000 19 Figure 5: Real Rail Rates for Plastic Materials or Synthetic Fibers, Resins, or Rubbers, Selected Short-Distance Routes, 1990–2000...Compounds, Selected Short-, Medium-, and Long-Distance Routes, 1990–2000 39 Figure 14: Real Rail Rates for Plastic Materials or Synthetic Fibers, Resins...Transportation Board to determine rates for coal, grain (wheat and corn), chemicals (potassium and sodium compounds and plastic materials or synthetic

Nanotechnology Applications in Functional Foods; Opportunities and Challenges.

PubMed

Singh, Harjinder

2016-03-01

Increasing knowledge on the link between diet and human health has generated a lot of interest in the development of functional foods. However, several challenges, including discovering of beneficial compounds, establishing optimal intake levels, and developing adequate food delivering matrix and product formulations, need to be addressed. A number of new processes and materials derived from nanotechnology have the potential to provide new solutions in many of these fronts. Nanotechnology is concerned with the manipulation of materials at the atomic and molecular scales to create structures that are less than 100 nm in size in one dimension. By carefully choosing the molecular components, it seems possible to design particles with different surface properties. Several food-based nanodelivery vehicles, such as protein-polysaccharide coacervates, multiple emulsions, liposomes and cochleates have been developed on a laboratory scale, but there have been very limited applications in real food systems. There are also public concerns about potential negative effects of nanotechnology-based delivery systems on human health. This paper provides an overview of the new opportunities and challenges for nanotechnology-based systems in future functional food development.

Counter-ion and dopant effects on charge carriers in intrinsically conductive polymer

NASA Astrophysics Data System (ADS)

Ogle, Jonathan; Yehulie, Mandefro; Boehme, Christoph; Whittaker-Brooks, Luisa

Recently, a significant amount of attention has been devoted to the optimization and applications of organic electronics. In particular, intrinsically conductive polymers have seen a strong continued interest for their use in thermoelectric and photovoltaic devices. With conductivities ranging from 10-8 to 103 S cm-1, the conductive polymer poly(3,4-ethylenedioxythiophene) -PEDOT is one of the most studied solution-processable polymer material due to its unique optical and electronic properties. While charge carriers at lower conductivities have been identified as polarons, an understanding of the electronic structure of PEDOT as its conductivity increases is not well understood. We have investigated the effect that counter-ion exchange and doping has on the polaron concentration of PEDOT via electron paramagnetic resonance, ultraviolet photoelectron spectroscopy, and X-ray absorption fine structure spectroscopy studies. Such studies have allowed us to correlate charge carriers concentrations and the real and virtual electronic states in PEDOT as a function of various dopants. As discussed in our talk, we believe our findings could be extended to the understanding of other polymeric materials.

Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

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

Plechac, Petr; Vlachos, Dionisios G.

We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems,more » etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.« less

Rapid Analysis of Trace Drugs and Metabolites Using a Thermal Desorption DART-MS Configuration.

PubMed

Sisco, Edward; Forbes, Thomas P; Staymates, Matthew E; Gillen, Greg

2016-01-01

The need to analyze trace narcotic samples rapidly for screening or confirmatory purposes is of increasing interest to the forensic, homeland security, and criminal justice sectors. This work presents a novel method for the detection and quantification of trace drugs and metabolites off of a swipe material using a thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS) configuration. A variation on traditional DART, this configuration allows for desorption of the sample into a confined tube, completely independent of the DART source, allowing for more efficient and thermally precise analysis of material present on a swipe. Over thirty trace samples of narcotics, metabolites, and cutting agents deposited onto swipes were rapidly differentiated using this methodology. The non-optimized method led to sensitivities ranging from single nanograms to hundreds of picograms. Direct comparison to traditional DART with a subset of the samples highlighted an improvement in sensitivity by a factor of twenty to thirty and an increase in reproducibility sample to sample from approximately 45 % RSD to less than 15 % RSD. Rapid extraction-less quantification was also possible.

Validation of Reference Genes for Relative Quantitative Gene Expression Studies in Cassava (Manihot esculenta Crantz) by Using Quantitative Real-Time PCR

PubMed Central

Hu, Meizhen; Hu, Wenbin; Xia, Zhiqiang; Zhou, Xincheng; Wang, Wenquan

2016-01-01

Reverse transcription quantitative real-time polymerase chain reaction (real-time PCR, also referred to as quantitative RT-PCR or RT-qPCR) is a highly sensitive and high-throughput method used to study gene expression. Despite the numerous advantages of RT-qPCR, its accuracy is strongly influenced by the stability of internal reference genes used for normalizations. To date, few studies on the identification of reference genes have been performed on cassava (Manihot esculenta Crantz). Therefore, we selected 26 candidate reference genes mainly via the three following channels: reference genes used in previous studies on cassava, the orthologs of the most stable Arabidopsis genes, and the sequences obtained from 32 cassava transcriptome sequence data. Then, we employed ABI 7900 HT and SYBR Green PCR mix to assess the expression of these genes in 21 materials obtained from various cassava samples under different developmental and environmental conditions. The stability of gene expression was analyzed using two statistical algorithms, namely geNorm and NormFinder. geNorm software suggests the combination of cassava4.1_017977 and cassava4.1_006391 as sufficient reference genes for major cassava samples, the union of cassava4.1_014335 and cassava4.1_006884 as best choice for drought stressed samples, and the association of cassava4.1_012496 and cassava4.1_006391 as optimal choice for normally grown samples. NormFinder software recommends cassava4.1_006884 or cassava4.1_006776 as superior reference for qPCR analysis of different materials and organs of drought stressed or normally grown cassava, respectively. Results provide an important resource for cassava reference genes under specific conditions. The limitations of these findings were also discussed. Furthermore, we suggested some strategies that may be used to select candidate reference genes. PMID:27242878

Impact of ultrasound on solid-liquid extraction of phenolic compounds from maritime pine sawdust waste. Kinetics, optimization and large scale experiments.

PubMed

Meullemiestre, A; Petitcolas, E; Maache-Rezzoug, Z; Chemat, F; Rezzoug, S A

2016-01-01

Maritime pine sawdust, a by-product from industry of wood transformation, has been investigated as a potential source of polyphenols which were extracted by ultrasound-assisted maceration (UAM). UAM was optimized for enhancing extraction efficiency of polyphenols and reducing time-consuming. In a first time, a preliminary study was carried out to optimize the solid/liquid ratio (6g of dry material per mL) and the particle size (0.26 cm(2)) by conventional maceration (CVM). Under these conditions, the optimum conditions for polyphenols extraction by UAM, obtained by response surface methodology, were 0.67 W/cm(2) for the ultrasonic intensity (UI), 40°C for the processing temperature (T) and 43 min for the sonication time (t). UAM was compared with CVM, the results showed that the quantity of polyphenols was improved by 40% (342.4 and 233.5mg of catechin equivalent per 100g of dry basis, respectively for UAM and CVM). A multistage cross-current extraction procedure allowed evaluating the real impact of UAM on the solid-liquid extraction enhancement. The potential industrialization of this procedure was implemented through a transition from a lab sonicated reactor (3 L) to a large scale one with 30 L volume. Copyright © 2015 Elsevier B.V. All rights reserved.

Construction of bionic tissue engineering cartilage scaffold based on three-dimensional printing and oriented frozen technology.

PubMed

Xu, Yuanyuan; Guo, Xiao; Yang, Shuaitao; Li, Long; Zhang, Peng; Sun, Wei; Liu, Changyong; Mi, Shengli

2018-06-01

Articular cartilage (AC) has gradient features in both mechanics and histology as well as a poor regeneration ability. The repair of AC poses difficulties in both research and the clinic. In this paper, a gradient scaffold based on poly(lactic-co-glycolic acid) (PLGA)-extracellular matrix was proposed. Cartilage scaffolds with a three-layer gradient structure were fabricated by PLGA through three-dimensional printing, and the microstructure orientation and pore fabrication were made by decellularized extracellular matrix injection and directional freezing. The manufactured scaffold has a mechanical strength close to that of real cartilage. A quantitative optimization of the Young's modulus and shear modulus was achieved by material mechanics formulas, which achieved a more accurate mechanical bionic and a more stable interface performance because of the one-time molding process. At the same time, the scaffolds have a bionic and gradient microstructure orientation and pore size, and the stratification ratio can be quantitatively optimized by design of the freeze box and temperature simulation. In general, this paper provides a method to optimize AC scaffolds by both mechanics and histology as well as a bionic multimaterial scaffold. This paper is of significance for cell culture and clinical transplantation experiments. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 1664-1676, 2018. © 2018 Wiley Periodicals, Inc.

Protonated graphitic carbon nitride coated metal-organic frameworks with enhanced visible-light photocatalytic activity for contaminants degradation

NASA Astrophysics Data System (ADS)

Huang, Jie; Zhang, Xibiao; Song, Haiyan; Chen, Chunxia; Han, Fuqin; Wen, Congcong

2018-05-01

Most of the reported composites of g-C3N4/metal-organic frameworks (MOFs) were obtained via exfoliation of g-C3N4 and wrapping the nanosheets on MOFs with weak interaction. In this work, chemical protonation of g-C3N4 and dip-coating was adopted as a feasible pathway to achieve the real combination of g-C3N4 derivatives with a familiar MOF material MIL-100(Fe). Structural, chemical and photophysical properties of the novel hybrid photocatalysts were characterized and compared to those of the parent materials. It was verified that the protonated g-C3N4 species of appropriate content were uniformly coated along the frameworks of MIL-100(Fe) with strong interaction. The optimal materials maintained the intact framework structure, surface property and porosity of MIL-100(Fe), as well as the inherent structural units and physicochemical properties of C3N4. In comparison to the parent materials, the protonated g-C3N4 coated MIL-100(Fe) materials exhibited enhanced photocatalytic activity in degradation of rhodamine B or methylene blue dye, as well as in oxidative denitrogenation for pyridine by molecular oxygen under visible light. Introduction of protonated g-C3N4 on MOFs improved the adsorption ability for contaminant molecules. Furthermore, coating effect provided a platform for rapid photoexcited electrons transfer and superior separation of photogenerated electron-hole pairs. Photocatalytic conversion of the three contaminants followed different mechanisms.

High resolution micro-CT of low attenuating organic materials using large area photon-counting detector

NASA Astrophysics Data System (ADS)

Kumpová, I.; Vavřík, D.; Fíla, T.; Koudelka, P.; Jandejsek, I.; Jakůbek, J.; Kytýř, D.; Zlámal, P.; Vopálenský, M.; Gantar, A.

2016-02-01

To overcome certain limitations of contemporary materials used for bone tissue engineering, such as inflammatory response after implantation, a whole new class of materials based on polysaccharide compounds is being developed. Here, nanoparticulate bioactive glass reinforced gelan-gum (GG-BAG) has recently been proposed for the production of bone scaffolds. This material offers promising biocompatibility properties, including bioactivity and biodegradability, with the possibility of producing scaffolds with directly controlled microgeometry. However, to utilize such a scaffold with application-optimized properties, large sets of complex numerical simulations using the real microgeometry of the material have to be carried out during the development process. Because the GG-BAG is a material with intrinsically very low attenuation to X-rays, its radiographical imaging, including tomographical scanning and reconstructions, with resolution required by numerical simulations might be a very challenging task. In this paper, we present a study on X-ray imaging of GG-BAG samples. High-resolution volumetric images of investigated specimens were generated on the basis of micro-CT measurements using a large area flat-panel detector and a large area photon-counting detector. The photon-counting detector was composed of a 010× 1 matrix of Timepix edgeless silicon pixelated detectors with tiling based on overlaying rows (i.e. assembled so that no gap is present between individual rows of detectors). We compare the results from both detectors with the scanning electron microscopy on selected slices in transversal plane. It has been shown that the photon counting detector can provide approx. 3× better resolution of the details in low-attenuating materials than the integrating flat panel detectors. We demonstrate that employment of a large area photon counting detector is a good choice for imaging of low attenuating materials with the resolution sufficient for numerical simulations.

Optimal Mortgage Refinancing: A Closed Form Solution.

PubMed

Agarwal, Sumit; Driscoll, John C; Laibson, David I

2013-06-01

We derive the first closed-form optimal refinancing rule: Refinance when the current mortgage interest rate falls below the original rate by at least [Formula: see text] In this formula W (.) is the Lambert W -function, [Formula: see text] ρ is the real discount rate, λ is the expected real rate of exogenous mortgage repayment, σ is the standard deviation of the mortgage rate, κ/M is the ratio of the tax-adjusted refinancing cost and the remaining mortgage value, and τ is the marginal tax rate. This expression is derived by solving a tractable class of refinancing problems. Our quantitative results closely match those reported by researchers using numerical methods.

Projectile motion in real-life situation: Kinematics of basketball shooting

NASA Astrophysics Data System (ADS)

Changjan, A.; Mueanploy, W.

2015-06-01

Basketball shooting is a basic practice for players. The path of the ball from the players to the hoop is projectile motion. For undergraduate introductory physics courses student must be taught about projectile motion. Basketball shooting can be used as a case study for learning projectile motion from real-life situation. In this research, we discuss the relationship between optimal angle, minimum initial velocity and the height of the ball before the player shoots the ball for basketball shooting problem analytically. We found that the value of optimal angle and minimum initial velocity decreases with increasing the height of the ball before the player shoots the ball.

Synthesis of Optimal Constant-Gain Positive-Real Controllers for Passive Systems

NASA Technical Reports Server (NTRS)

Mao, Y.; Kelkar, A. G.; Joshi, S. M.

1999-01-01

This paper presents synthesis methods for the design of constant-gain positive real controllers for passive systems. The results presented in this paper, in conjunction with the previous work by the authors on passification of non-passive systems, offer a useful synthesis tool for the design of passivity-based robust controllers for non-passive systems as well. Two synthesis approaches are given for minimizing an LQ-type performance index, resulting in optimal controller gains. Two separate algorithms, one for each of these approaches, are given. The synthesis techniques are demonstrated using two numerical examples: control of a flexible structure and longitudinal control of a fighter aircraft.

Grain Propellant Optimization Using Real Code Genetic Algorithm (RCGA)

NASA Astrophysics Data System (ADS)

Farizi, Muhammad Farraz Al; Oktovianus Bura, Romie; Fajar Junjunan, Soleh; Jihad, Bagus H.

2018-04-01

Grain propellant design is important in rocket motor design. The total impulse and ISP of the rocket motor is influenced by the grain propellant design. One way to get a grain propellant shape that generates the maximum total impulse value is to use the Real Code Genetic Algorithm (RCGA) method. In this paper RCGA is applied to star grain Rx-450. To find burn area of propellant used analytical method. While the combustion chamber pressures are sought with zero-dimensional equations. The optimization result can reach the desired target and increase the total impulse value by 3.3% from the initial design of Rx-450.

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

Firestone, Ryan; Marnay, Chris

The on-site generation of electricity can offer buildingowners and occupiers financial benefits as well as social benefits suchas reduced grid congestion, improved energy efficiency, and reducedgreenhouse gas emissions. Combined heat and power (CHP), or cogeneration,systems make use of the waste heat from the generator for site heatingneeds. Real-time optimal dispatch of CHP systems is difficult todetermine because of complicated electricity tariffs and uncertainty inCHP equipment availability, energy prices, and system loads. Typically,CHP systems use simple heuristic control strategies. This paper describesa method of determining optimal control in real-time and applies it to alight industrial site in San Diego, California, tomore » examine: 1) the addedbenefit of optimal over heuristic controls, 2) the price elasticity ofthe system, and 3) the site-attributable greenhouse gas emissions, allunder three different tariff structures. Results suggest that heuristiccontrols are adequate under the current tariff structure and relativelyhigh electricity prices, capturing 97 percent of the value of thedistributed generation system. Even more value could be captured bysimply not running the CHP system during times of unusually high naturalgas prices. Under hypothetical real-time pricing of electricity,heuristic controls would capture only 70 percent of the value ofdistributed generation.« less

Real-Time Control of an Ensemble of Heterogeneous Resources

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

Bernstein, Andrey; Bouman, Niek J.; Le Boudec, Jean-Yves

This paper focuses on the problem of controlling an ensemble of heterogeneous resources connected to an electrical grid at the same point of common coupling (PCC). The controller receives an aggregate power setpoint for the ensemble in real time and tracks this setpoint by issuing individual optimal setpoints to the resources. The resources can have continuous or discrete nature (e.g., heating systems consisting of a finite number of heaters that each can be either switched on or off) and/or can be highly uncertain (e.g., photovoltaic (PV) systems or residential loads). A naive approach would lead to a stochastic mixed-integer optimizationmore » problem to be solved at the controller at each time step, which might be infeasible in real time. Instead, we allow the controller to solve a continuous convex optimization problem and compensate for the errors at the resource level by using a variant of the well-known error diffusion algorithm. We give conditions guaranteeing that our algorithm tracks the power setpoint at the PCC on average while issuing optimal setpoints to individual resources. We illustrate the approach numerically by controlling a collection of batteries, PV systems, and discrete loads.« less

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning

NASA Astrophysics Data System (ADS)

Guthier, C.; Aschenbrenner, K. P.; Buergy, D.; Ehmann, M.; Wenz, F.; Hesser, J. W.

2015-03-01

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning.

PubMed

Guthier, C; Aschenbrenner, K P; Buergy, D; Ehmann, M; Wenz, F; Hesser, J W

2015-03-21

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

Oil shocks in New Keynesian models: Positive and normative implications

NASA Astrophysics Data System (ADS)

Chang, Jian

Chapter 1 investigates optimal monetary policy response towards oil shocks in a New Keynesian model. We find that optimal policy, in general, becomes contractionary in response to an adverse oil shock. However, the optimal policy rule and the inflation-output trade-off depend on the specific structure of the model. The benchmark economy consists of a flexible-price energy sector and a sticky-price manufacturing sector where energy is used as an intermediate input. We show that optimal policy is to stabilize the sticky (core) price level. We then show that after incorporating a less oil-dependent sticky-price service sector, the model exhibits a trade-off in stabilizing prices and output gaps in the different sticky-price sectors. It predicts that central bank should not try to stabilize the core price level, and the economy will experience higher inflation and rising output gaps, even if central banks respond optimally. Chapter 2 addresses the observed volatility and persistence of real exchange rates and the terms of trade. It contributes to the literature with a quantitative study on the U.S. and Canada. A two-country New Keynesian model consisting of traded, non-traded, and oil production sectors is proposed to examine the time series properties of the real exchange rate, the terms of trade and the real oil price. We find that after incorporating several realistic features (namely oil price shocks, sector specific labor, non-traded goods, asymmetric pricing decisions of exporters and asymmetric consumer preferences over tradables), the benchmark model broadly matches the volatilities of the relative prices and some business cycle correlations. The model matches the data more closely after adding real demand shocks, suggesting their importance in explaining the relative price movements between the US and Canada. Chapter 3 explores several sources and transmission channels of international relative price movements. In particular, we elaborate on the role of imperfect labor mobility, pricing decisions of exporting firms, oil price shocks and asymmetric consumer preferences over tradables. Our results suggest that: Incorporating both producer currency pricing and local currency pricing assumptions produces more reasonable relative price movements. A model with imperfect labor mobility generates larger relative price volatility. Oil price shocks only contribute to terms of trade variability when oil is modeled as part of the traded basket. And asymmetric consumer preferences contribute to the volatility of the real exchange rate.

Microscopic 3D measurement of dynamic scene using optimized pulse-width-modulation binary fringe

NASA Astrophysics Data System (ADS)

Hu, Yan; Chen, Qian; Feng, Shijie; Tao, Tianyang; Li, Hui; Zuo, Chao

2017-10-01

Microscopic 3-D shape measurement can supply accurate metrology of the delicacy and complexity of MEMS components of the final devices to ensure their proper performance. Fringe projection profilometry (FPP) has the advantages of noncontactness and high accuracy, making it widely used in 3-D measurement. Recently, tremendous advance of electronics development promotes 3-D measurements to be more accurate and faster. However, research about real-time microscopic 3-D measurement is still rarely reported. In this work, we effectively combine optimized binary structured pattern with number-theoretical phase unwrapping algorithm to realize real-time 3-D shape measurement. A slight defocusing of our proposed binary patterns can considerably alleviate the measurement error based on phase-shifting FPP, making the binary patterns have the comparable performance with ideal sinusoidal patterns. Real-time 3-D measurement about 120 frames per second (FPS) is achieved, and experimental result of a vibrating earphone is presented.

Autonomous health management for PMSM rail vehicles through demagnetization monitoring and prognosis control.

PubMed

Niu, Gang; Jiang, Junjie; Youn, Byeng D; Pecht, Michael

2018-01-01

Autonomous vehicles are playing an increasingly importance in support of a wide variety of critical events. This paper presents a novel autonomous health management scheme on rail vehicles driven by permanent magnet synchronous motors (PMSMs). Firstly, the PMSMs are modeled based on first principle to deduce the initial profile of pneumatic braking (p-braking) force, then which is utilized for real-time demagnetization monitoring and degradation prognosis through similarity-based theory and generate prognosis-enhanced p-braking force strategy for final optimal control. A case study is conducted to demonstrate the feasibility and benefit of using the real-time prognostics and health management (PHM) information in vehicle 'drive-brake' control automatically. The results show that accurate demagnetization monitoring, degradation prognosis, and real-time capability for control optimization can be obtained, which can effectively relieve brake shoe wear. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Improving Free-Piston Stirling Engine Specific Power

NASA Technical Reports Server (NTRS)

Briggs, Maxwell Henry

2014-01-01

This work uses analytical methods to demonstrate the potential benefits of optimizing piston and/or displacer motion in a Stirling Engine. Isothermal analysis was used to show the potential benefits of ideal motion in ideal Stirling engines. Nodal analysis is used to show that ideal piston and displacer waveforms are not optimal in real Stirling engines. Constrained optimization was used to identify piston and displacer waveforms that increase Stirling engine specific power.

Improving Free-Piston Stirling Engine Specific Power

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.

2015-01-01

This work uses analytical methods to demonstrate the potential benefits of optimizing piston and/or displacer motion in a Stirling engine. Isothermal analysis was used to show the potential benefits of ideal motion in ideal Stirling engines. Nodal analysis is used to show that ideal piston and displacer waveforms are not optimal in real Stirling engines. Constrained optimization was used to identify piston and displacer waveforms that increase Stirling engine specific power.

Recent Experiences in Multidisciplinary Analysis and Optimization, part 2

NASA Technical Reports Server (NTRS)

Sobieski, J. (Compiler)

1984-01-01

The papers presented at the NASA Symposium on Recent Experiences in Multidisciplinary Analysis and Optimization held at NASA Langley Research Center, Hampton, Virginia, April 24 to 26, 1984 are given. The purposes of the symposium were to exchange information about the status of the application of optimization and the associated analyses in industry or research laboratories to real life problems and to examine the directions of future developments.

Polyhedral Interpolation for Optimal Reaction Control System Jet Selection

NASA Technical Reports Server (NTRS)

Gefert, Leon P.; Wright, Theodore

2014-01-01

An efficient algorithm is described for interpolating optimal values for spacecraft Reaction Control System jet firing duty cycles. The algorithm uses the symmetrical geometry of the optimal solution to reduce the number of calculations and data storage requirements to a level that enables implementation on the small real time flight control systems used in spacecraft. The process minimizes acceleration direction errors, maximizes control authority, and minimizes fuel consumption.