Optimization Model for Reducing Emissions of Greenhouse Gases from Automobiles (OMEGA)
The EPA Vehicle Greenhouse Gas (VGHG) model is used to apply various technologies to a defined set of vehicles in order to meet a specified GHG emission target, and to then calculate the costs and benefits of doing so.
Semileptonic Decays of Heavy Omega Baryons in a Quark Model
International Nuclear Information System (INIS)
Muslema Pervin; Winston Roberts; Simon Capstick
2006-01-01
The semileptonic decays of (Omega) c and (Omega) b are treated in the framework of a constituent quark model developed in a previous paper on the semileptonic decays of heavy Λ baryons. Analytic results for the form factors for the decays to ground states and a number of excited states are evaluated. For (Omega) b to (Omega) c the form factors obtained are shown to satisfy the relations predicted at leading order in the heavy-quark effective theory at the non-recoil point. A modified fit of nonrelativistic and semirelativistic Hamiltonians generates configuration-mixed baryon wave functions from the known masses and the measured Λ c + → Λe + ν rate, with wave functions expanded in both harmonic oscillator and Sturmian bases. Decay rates of (Omega) b to pairs of ground and excited (Omega) c states related by heavy-quark symmetry calculated using these configuration-mixed wave functions are in the ratios expected from heavy-quark effective theory, to a good approximation. Our predictions for the semileptonic elastic branching fraction of (Omega) Q vary minimally within the models we use. We obtain an average value of (84 ± 2%) for the fraction of (Omega) c → Ξ (*) decays to ground states, and 91% for the fraction of (Omega) c → (Omega) (*) decays to the ground state (Omega). The elastic fraction of (Omega) b → (Omega) c ranges from about 50% calculated with the two harmonic-oscillator models, to about 67% calculated with the two Sturmian models
Characteristics of Omega-Optimized Portfolios at Different Levels of Threshold Returns
Directory of Open Access Journals (Sweden)
Renaldas Vilkancas
2014-12-01
Full Text Available There is little literature considering effects that the loss-gain threshold used for dividing good and bad outcomes by all downside (upside risk measures has on portfolio optimization and performance. The purpose of this study is to assess the performance of portfolios optimized with respect to the Omega function developed by Keating and Shadwick at different levels of the threshold returns. The most common choices of the threshold values used in various Omega studies cover the risk-free rate and the average market return or simply a zero return, even though the inventors of this measure for risk warn that “using the values of the Omega function at particular points can be critically misleading” and that “only the entire Omega function contains information on distribution”. The obtained results demonstrate the importance of the selected values of the threshold return on portfolio performance – higher levels of the threshold lead to an increase in portfolio returns, albeit at the expense of a higher risk. In fact, within a certain threshold interval, Omega-optimized portfolios achieved the highest net return, compared with all other strategies for portfolio optimization using three different test datasets. However, beyond a certain limit, high threshold values will actually start hurting portfolio performance while meta-heuristic optimizers typically are able to produce a solution at any level of the threshold, and the obtained results would most likely be financially meaningless.
Earthquake Source Spectral Study beyond the Omega-Square Model
Uchide, T.; Imanishi, K.
2017-12-01
Earthquake source spectra have been used for characterizing earthquake source processes quantitatively and, at the same time, simply, so that we can analyze the source spectra for many earthquakes, especially for small earthquakes, at once and compare them each other. A standard model for the source spectra is the omega-square model, which has the flat spectrum and the falloff inversely proportional to the square of frequencies at low and high frequencies, respectively, which are bordered by a corner frequency. The corner frequency has often been converted to the stress drop under the assumption of circular crack models. However, recent studies claimed the existence of another corner frequency [Denolle and Shearer, 2016; Uchide and Imanishi, 2016] thanks to the recent development of seismic networks. We have found that many earthquakes in areas other than the area studied by Uchide and Imanishi [2016] also have source spectra deviating from the omega-square model. Another part of the earthquake spectra we now focus on is the falloff rate at high frequencies, which will affect the seismic energy estimation [e.g., Hirano and Yagi, 2017]. In June, 2016, we deployed seven velocity seismometers in the northern Ibaraki prefecture, where the shallow crustal seismicity mainly with normal-faulting events was activated by the 2011 Tohoku-oki earthquake. We have recorded seismograms at 1000 samples per second and at a short distance from the source, so that we can investigate the high-frequency components of the earthquake source spectra. Although we are still in the stage of discovery and confirmation of the deviation from the standard omega-square model, the update of the earthquake source spectrum model will help us systematically extract more information on the earthquake source process.
International Nuclear Information System (INIS)
Sikka, S.K.; Vohra, Y.K.; Chidambaram, R.
1982-01-01
The subject is reviewed under the headings: introduction; occurrence and some systematics of omega phase; crystallography; physical properties; kinetics of formation, synthesis and metastability of omega phase; electronic structure of omega phase; electronic basis for omega phase stability; omega phase formation under combined thermal and pressure treatment in alloys; transformation mechanisms and models for diffuse omega phase; conclusion. The following elements of nuclear interest (or their alloys) are included: Zr, Hf, Nb, V, Mo. (U.K.)
International Nuclear Information System (INIS)
Sikka, S.K.; Vohra, Y.K.; Chidambaram, R.
1982-01-01
The subject is covered in sections, entitled: introduction; occurrence and some systematics of omega phase (omega phase in Ti, Zr and Hf under high pressures; omega phase in Group IV transition metal alloys; omega in other systems; omega embryos at high temperatures); crystallography (omega structure; relationship of ω-structure to bcc (β) and hcp (α) structures); physical properties; kinetics of formation, synthesis and metastability of omega phase (kinetics of α-ω transformation under high pressures; kinetics of β-ω transformation; synthesis and metastability studies); electronic structure of omega phase (electronic structure models; band structure calculations; theoretical results and experimental studies); electronic basis for omega phase stability (unified phase diagram; stability of omega phase); omega phase formation under combined thermal and pressure treatment in alloys (Ti-V alloys under pressure - a prototype case study; P-X phase diagrams for alloys; transformation mechanisms and models for diffuse omega phase (is omega structure a charge density distortion of the bcc phase; nature of incommensurate ω-structure and models for diffuse scattering); conclusion. (U.K.)
Optimization modeling with spreadsheets
Baker, Kenneth R
2015-01-01
An accessible introduction to optimization analysis using spreadsheets Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft® Office Excel® Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software. The Third Edition includes many practical applications of optimization models as well as a systematic framework that il
Structure of the discrete Dirac vacuum in the sigma + omega model
International Nuclear Information System (INIS)
Miller, L.D.
1989-01-01
The sigma + omega model potentials imply that any moderate to large nucleus should have thousands of discrete negative-energy nucleon states. Theoretical predictions of structure in this discrete island of the nuclear Dirac sea are presented in this paper. This structure is related to the spectral functions that will emerge in high energy electron- and hardon-induced reactions on nuclei. These high-energy reaction studies should supplement our understanding of the saturation mechanism of the sigma + omega model. They could also identify the threshold for observable quantum chromo-dynamics (QCD) effects in nuclei
Directory of Open Access Journals (Sweden)
ALEXANDRA I. ZUGNO
2015-08-01
Full Text Available ABSTRACTNew studies suggest that polyunsaturated fatty acids, such as omega-3, may reduce the symptoms of schizophrenia. The present study evaluated the preventive effect of omega-3 on interleukines (IL and neurotrophin brain-derived neurotrophic factor (BDNF levels in the brains of young rats subjected to a model of schizophrenia. Treatment was performed over 21 days, starting on the 30th day of rat's life. After 14 days of treatment with omega-3 or vehicle, a concomitant treatment with saline or ketamine (25 mg/kg was started and maintained until the last day of the experiment. BDNF levels in the rat's prefrontal cortex were decreased at 1 h and 24 h after the last administration of ketamine, whereas the group administered with ketamine and omega-3 showed a decrease in BDNF levels only after 24 h. In contrast, both interventions induced similar responses in levels of IL-1β and IL6. These findings suggest that the similarity of IL-1β and IL6 levels in our experimental groups is due to the mechanism of action of ketamine on the immune system. More studies have to be carried out to explain this pathology. In conclusion, according to previous studies and considering the current study, we could suggest a prophylactic role of omega-3 against the outcome of symptoms associated with schizophrenia.
Approximate $w_\\phi\\sim\\Omega_\\phi$ Relations in Quintessence Models
Luo, Mingxing; Su, Qiping
2007-01-01
Quintessence field is a widely-studied candidate of dark energy. There is "tracker solution" in quintessence models, in which evolution of the field $\\phi$ at present times is not sensitive to its initial conditions. When the energy density of dark energy is neglectable ($\\Omega_\\phi\\ll1$), evolution of the tracker solution can be well analysed from "tracker equation". In this paper, we try to study evolution of the quintessence field from "full tracker equation", which is valid for all spans...
Kobyliak, Nazarii; Falalyeyeva, Tetyana; Bodnar, Petro; Beregova, Tetyana
2017-06-01
Today probiotics have been suggested as a treatment for the prevention of NAFLD. Omega-3 fatty acid supplementation may have beneficial effects in regulating hepatic lipid metabolism, adipose tissue function and inflammation. The present study was designed to determine whether probiotics plus omega-3 are superior to probiotics alone on the monosodium glutamate (MSG)-induced NAFLD model in rats. We included 60 rats divided into four groups, 15 animals in each. Rats of group I were intact. Newborn rats of groups II-IV were injected with MSG. The III (Symbiter) group received 2.5 ml/kg of multiprobiotic "Symbiter" containing concentrated biomass of 14 probiotic bacteria genera. The IV (Symbiter-Omega) groups received "Symbiter-Omega" combination of probiotic biomass supplemented with flax and wheat germ oil (250 mg of each, concentration of omega-3 fatty acids 1-5 %). In both interventional groups reduction in total NAS score was observed. Supplementation of alive probiotic mixture with omega-3 fatty acids lead to 20 % higher decrease in steatosis score (0.73 ± 0.11 vs 0.93 ± 0.22, p = 0.848) and reduction by 16.6 % of triglycerides content in liver as compared to probiotic alone. Our study demonstrated more pronounced reduction in hepatic steatosis and hepatic lipid accumulation after treatment with combination of alive probiotics and omega-3 as compared to probiotics alone.
Omega-3 Fatty Acids: Possible Neuroprotective Mechanisms in the Model of Global Ischemia in Rats
Nobre, Maria Elizabeth Pereira; Correia, Alyne Oliveira; Mendon?a, Francisco Nilson Maciel; Uchoa, Luiz Ricardo Ara?jo; Vasconcelos, Jessica Tamara Nunes; de Ara?jo, Carlos Ney Alencar; Brito, Gerly Anne de Castro; Siqueira, Rafaelly Maria Pinheiro; Cerqueira, Gilberto dos Santos; Neves, Kelly Rose Tavares; Arida, Ricardo M?rio; Viana, Glauce Socorro de Barros
2016-01-01
Background. Omega-3 (ω3) administration was shown to protect against hypoxic-ischemic injury. The objectives were to study the neuroprotective effects of ω3, in a model of global ischemia. Methods. Male Wistar rats were subjected to carotid occlusion (30 min), followed by reperfusion. The groups were SO, untreated ischemic and ischemic treated rats with ω3 (5 and 10 mg/kg, 7 days). The SO and untreated ischemic animals were orally treated with 1% cremophor and, 1 h after the last administrati...
Directory of Open Access Journals (Sweden)
Fivi Melva Diana
2012-09-01
Full Text Available Kejadian gizi kurang di Indonesia dari tahun ke tahun masihtinggi Penyebab tingginya angka kejadian gizi kurang di Indonesia salah satunya diduga karena kurangnya konsumsi makanan sumber omega 6, secara alami terdapat pada minyak biji-bijian, minyakjagung dan kacang kedelai. Omega 6 merupakan asam lemak tak jenuh ganda yang mempunyai banyak manfaat terutama untuk pertumbuhan dan perkembangan kecerdasan balita. Tulisan ini membahas tentang defenisi omega 6, sumber, klasifikasi, manfaat dan kerugian bila mengkonsumsi omega 6. Disarankan untuk melakukan penelitian lebih lanjut mengenai hubungan konsumsi omega 6 dengan tumbuh-kembang anak, selain itu bagi ibu-ibu disarankan untuk memperhatikan konsumsi makanan dari sumber omega 6 guna pengoptimalan tumbuh-kembang anak. Hal ini jika terlaksana dapat memberikan dukungan terhadap program pemerintah di bidang promosi kesehatan.
Optimization Modeling with Spreadsheets
Baker, Kenneth R
2011-01-01
This introductory book on optimization (mathematical programming) includes coverage on linear programming, nonlinear programming, integer programming and heuristic programming; as well as an emphasis on model building using Excel and Solver. The emphasis on model building (rather than algorithms) is one of the features that makes this book distinctive. Most books devote more space to algorithmic details than to formulation principles. These days, however, it is not necessary to know a great deal about algorithms in order to apply optimization tools, especially when relying on the sp
Omega-3 Fatty Acids Inhibit Tumor Growth in a Rat Model of Bladder Cancer
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Belmiro Parada
2013-01-01
Full Text Available Omega-3 (ω-3 fatty acids have been tested on prevention and treatment of several cancer types, but the efficacy on “in vivo” bladder cancer has not been analyzed yet. This study aimed at evaluating the chemopreventive efficacy of eicosapentaenoic acid (EPA and docosahexaenoic acid (DHA mixture in an animal model of bladder cancer. Forty-four male Wistar rats were divided into 4 groups during a 20-week protocol: control; carcinogen—N-butyl-N-(4-hydroxybutyl nitrosamine (BBN; ω-3 (DHA + EPA; and ω-3 + BBN. BBN and ω-3 were given during the initial 8 weeks. At week 20 blood and bladder were collected and checked for the presence of urothelium lesions and tumors, markers of inflammation, proliferation, and redox status. Incidence of bladder carcinoma was, control (0%, ω-3 (0%, BBN (65%, and ω-3 + BBN (62.5%. The ω-3 + BBN group had no infiltrative tumors or carcinoma in situ, and tumor volume was significantly reduced compared to the BBN (0.9 ± 0.1 mm3 versus 112.5 ± 6.4 mm3. Also, it showed a reduced MDA/TAS ratio and BBN-induced serum CRP, TGF-β1, and CD31 were prevented. In conclusion, omega-3 fatty acids inhibit the development of premalignant and malignant lesions in a rat model of bladder cancer, which might be due to anti-inflammatory, antioxidant, anti-proliferative, and anti-angiogenic properties.
Subthreshold SPICE Model Optimization
Lum, Gregory; Au, Henry; Neff, Joseph; Bozeman, Eric; Kamin, Nick; Shimabukuro, Randy
2011-04-01
The first step in integrated circuit design is the simulation of said design in software to verify proper functionally and design requirements. Properties of the process are provided by fabrication foundries in the form of SPICE models. These SPICE models contain the electrical data and physical properties of the basic circuit elements. A limitation of these models is that the data collected by the foundry only accurately model the saturation region. This is fine for most users, but when operating devices in the subthreshold region they are inadequate for accurate simulation results. This is why optimizing the current SPICE models to characterize the subthreshold region is so important. In order to accurately simulate this region of operation, MOSFETs of varying widths and lengths are fabricated and the electrical test data is collected. From the data collected the parameters of the model files are optimized through parameter extraction rather than curve fitting. With the completed optimized models the circuit designer is able to simulate circuit designs for the sub threshold region accurately.
Is the world supply of omega-3 fatty acids adequate for optimal human nutrition?
Salem, Norman; Eggersdorfer, Manfred
2015-03-01
To delineate the available sources of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) for human consumption and to determine if the available supply is capable of supplying the nutrient levels recommended by expert bodies. There are converging opinions among experts, professional organizations and health professionals that a recommendation for a daily individual consumption of 500 mg of EPA/DHA would provide health benefits, and this translates to an annual human consumption of 1.3 million metric tons. Current human consumption of EPA/DHA is estimated to be only a small fraction of this amount and many people may suffer from suboptimal health as a result of low intake. EPA and DHA originate in the phytoplankton and are made available in the human food chain mainly through fish and other seafood. The fish catch is not elastic and in fact has long since reached a plateau. Aquaculture has grown rapidly, but most of the fish oil produced is currently being used to support aquaculture feed and so this would appear to limit aquaculture growth - or at least the growth in availability of fish sources of EPA/DHA. Vegetable oil-derived alpha-linolenic acid, though relatively plentiful, is converted only at a trace level in humans to DHA and not very efficiently to EPA, and so cannot fill this gap. Microbial EPA/DHA production can in the future be increased, although this oil is likely to remain more expensive than fish oil. Plant sources of EPA and DHA have now been produced in the laboratory via transgenic means and will eventually clear regulatory hurdles for commercialization, but societal acceptance remains in question. The purpose of this review is to discuss the various sources of omega-3 fatty acids within the context of the potential world demand for these nutrients. In summary, it is concluded that fish and vegetable oil sources will not be adequate to meet future needs, but that algal oil and terrestrial plants modified genetically to produce EPA and DHA
Understanding Laser-Imprint Effects on Plastic-Target Implosions on OMEGA with New Physics Models
Hu, S. X.; Michel, D. T.; Davis, A. K.; Betti, R.; Radha, P. B.; Campbell, E. M.; Froula, D. H.; Stoeckl, C.
2016-10-01
Using the state-of-the-art physics models (nonlocal thermal transport, cross-beam energy transfer, and first-principles equation of state) recently implemented in our two-dimensional hydrocode DRACO, we have performed a systematic study of laser-imprint effects on plastic-target implosions on OMEGA by both simulations and experiments. Through varying the laser picket intensity, the imploding shells were set at different adiabats ranging from α = 2 to α = 6 . As the shell adiabat α decreases, we observed: (1) the measured shell thickness at the hot spot emission becomes larger than the uniform prediction; (2) the hot-spot core emits and neutron burn starts earlier than the corresponding 1-D prediction; and (3) the measured neutron yields are significantly reduced from their 1-D designs. Most of these experimental observations are well reproduced by our DRACO simulations with laser imprints. These studies clearly identify that laser imprint is the major cause for target performance degradation of OMEGA implosions of α ignition attempts. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0001944.
Progress Toward Modeling Spectroscopic Signatures of Mix on Omega and NIF
Tregillis, I. L.; Schmitt, M. J.; Hsu, S. C.; Wysocki, F. J.; Cobble, J. A.; Murphy, T. J.
2011-10-01
Defect-induced mix processes may degrade the performance of ICF and ICF-like targets at Omega and NIF. An improved understanding of the relevant physics requires an experimental program built on a foundation of radiation-hydrodynamic simulations plus reliable synthetic diagnostic outputs. To that end, the Applications of Ignition (AoI) and Defect Implosion Experiment (DIME) efforts at LANL have focused on directly driven plastic capsules containing high-Z dopants and manufactured with an equatorial ``trench'' defect. One of the key diagnostic techniques for detecting and diagnosing the migration of dopant material into the hot core is Multi-Monochromatic X-ray Imaging (MMI). This talk will focus on recent efforts to model spectroscopic signatures of mix processes in AoI/DIME capsules via simulated MMI-type diagnostic instruments. It will also include data from recent Omega shots and calculations in support of Tier 1 experiments at NIF in FY2012. This work is supported by US DOE/NNSA, performed at LANL, operated by LANS LLC under contract DE-AC52-06NA25396.
FEM simulation of static loading test of the Omega beam
Bílý, Petr; Kohoutková, Alena; Jedlinský, Petr
2017-09-01
The paper deals with a FEM simulation of static loading test of the Omega beam. Omega beam is a precast prestressed high-performance concrete element with the shape of Greek letter omega. Omega beam was designed as a self-supporting permanent formwork member for construction of girder bridges. FEM program ATENA Science was exploited for simulation of load-bearing test of the beam. The numerical model was calibrated using the data from both static loading test and tests of material properties. Comparison of load-displacement diagrams obtained from the experiment and the model was conducted. Development of cracks and crack patterns were compared. Very good agreement of experimental data and the FEM model was reached. The calibrated model can be used for design of optimized Omega beams in the future without the need of expensive loading tests. The calibrated material model can be also exploited in other types of FEM analyses of bridges constructed with the use of Omega beams, such as limit state analysis, optimization of shear connectors, prediction of long-term deflections or prediction of crack development.
About spaces of $\\omega_1$-$\\omega_2$-ultradifferentiable functions
Schmets, Jean; Valdivia, Manuel
2008-01-01
Let $\\Omega_1$ and $\\Omega_2$ be non empty open subsets of $\\mathbb R^r$ and $\\mathbb R^s$ respectively and let $\\omega_1$ and $\\omega_2$ be weights. We introduce the spaces of ultradifferentiable functions $\\mathcal{E}_{(\\omega_1,\\omega_2)}(\\Omega_1 \\times \\Omega_2)$, $\\mathcal{D}_{(\\omega_1,\\omega_2)}(\\Omega_1 \\times \\Omega_2)$, $\\mathcal{E}_{\\{\\omega_1,\\omega_2\\}}(\\Omega_1 \\times \\Omega_2)$ and $\\mathcal{D}_{\\{\\omega_1,\\omega_2\\}}(\\Omega_1 \\times \\Omega_2)$, study their l...
Optimization of the carrot leaf dehydration aiming at the preservation of omega-3 fatty acids
Directory of Open Access Journals (Sweden)
Vanessa Vivian de Almeida
2009-01-01
Full Text Available The carrot leaf dehydration conditions in air circulation oven were optimized through response surface methodology (RSM for minimizing the degradation of polyunsaturated fatty acids, particularly alpha-linolenic (LNA, 18:3n-3. The optimized leaf drying time and temperature were 43 h and 70 ºC, respectively. The fatty acids (FA were investigated using gas chromatography equipped with a flame ionization detector and fused silica capillary column; FA were identified with standards and based on equivalent-chain-length. LNA and other FA were quantified against C21:0 internal standard. After dehydration, the amount of LNA, quantified in mg/100 g dry matter of dehydrated carrot leaves, were 984 mg.
The parameters used for passive soil moisture retrieval algorithms reported in the literature encompass a wide range, leading to a large uncertainty in the applicability of those values. This paper presents an evaluation of the proposed parameterizations of the tau-omega model from 1) SMAP ATBD for ...
Three-dimensional modeling of capsule implosions in OMEGA tetrahedral hohlraums
International Nuclear Information System (INIS)
Schnittman, J. D.; Craxton, R. S.
2000-01-01
Tetrahedral hohlraums have been proposed as a means for achieving the highly uniform implosions needed for ignition with inertial confinement fusion (ICF) [J. D. Schnittman and R. S. Craxton, Phys. Plasmas 3, 3786 (1996)]. Recent experiments on the OMEGA laser system have achieved good drive uniformity consistent with theoretical predictions [J. M. Wallace et al., Phys. Rev. Lett. 82, 3807 (1999)]. To better understand these experiments and future investigations of high-convergence ICF implosions, the three-dimensional (3-D) view-factor code BUTTERCUP has been expanded to model the time-dependent radiation transport in the hohlraum and the hydrodynamic implosion of the capsule. Additionally, a 3-D postprocessor has been written to simulate x-ray images of the imploded core. Despite BUTTERCUP's relative simplicity, its predictions for radiation drive temperatures, fusion yields, and core deformation show close agreement with experiment. (c) 2000 American Institute of Physics
Gowda, Avinash; Sharma, Vivek; Goyal, Ankit; Singh, A K; Arora, Sumit
2018-05-01
Microencapsulated flaxseed oil powder (MFOP) was supplemented for the fortification of α-linolenic acid (ALA, ω-3 fatty acid) in ice cream. Processing parameters were optimized in terms of the stage of homogenization of ice-cream mix, level of fortification (3, 4 and 5%) and flavors (vanilla, butter scotch and strawberry). Data revealed that free fatty acids increased significantly during first 15 days in all the samples and then remained constant. Peroxide value and thiobarbituric acid value first increased up to 30 and 45 days, respectively; and then decreased followed by a gradual increase up to 120 days. Fatty acids profile showed 18.74-21.38% decrease in ALA content in fortified ice creams after 120 days. A serving of 100 g of freshly prepared functional ice cream was able to meet ~ 45% of the RDA (1.4 g ALA/day), which reduced to 35.37-36.56% on the end of storage i.e. 120 days. Overall, it can be concluded that MFOP was oxidative stable in ice-cream throughout the storage, which could be fortified successfully at 4% (w/w) level.
Directory of Open Access Journals (Sweden)
Kensuke Tomio
Full Text Available Omega-3 polyunsaturated fatty acids (omega-3 PUFAs play a role in controlling pathological inflammatory reactions. Endometriosis is characterized by the presence of endometrial tissue on the peritoneum and an exaggerated inflammatory environment around ectopic tissues. Here peritoneal endometriosis was reproduced using a mouse model in which murine endometrial fragments were inoculated into the peritoneal cavity of mice. Fat-1 mice, in which omega-6 can be converted to omega-3 PUFAs, or wild type mice, in which it cannot, were used for the endometriosis model to address the actions of omega-3 PUFAs on the development of endometriotic lesions. The number and weight of cystic endometriotic lesions in fat-1 mice two weeks after inoculation were significantly less than half to those of controls. Mediator lipidomics revealed that cystic endometriotic lesions and peritoneal fluids were abundant in 12/15-hydroxyeicosapentaenoic acid (12/15-HEPE, derived from eicosapentaenoic acid (EPA, and their amount in fat-1 mice was significantly larger than that in controls. 12/15-Lipoxygenase (12/15-LOX-knockout (KO and control mice with or without EPA administration were assessed for the endometriosis model. EPA administration decreased the number of lesions in controls but not in 12/15-LOX-KO mice. The peritoneal fluids in EPA-fed 12/15-LOX-KO mice contained reduced levels of EPA metabolites such as 12/15-HEPE and EPA-derived resolvin E3 even after EPA administration. cDNA microarrays of endometriotic lesions revealed that Interleukin-6 (IL-6 expression in fat-1 mice was significantly lower than that in controls. These results suggest that both endogenous and exogenous EPA-derived PUFAs protect against the development of endometriosis through their anti-inflammatory effects and, in particular, the 12/15-LOX-pathway products of EPA may be key mediators to suppress endometriosis.
Tomio, Kensuke; Kawana, Kei; Taguchi, Ayumi; Isobe, Yosuke; Iwamoto, Ryo; Yamashita, Aki; Kojima, Satoko; Mori, Mayuyo; Nagamatsu, Takeshi; Arimoto, Takahide; Oda, Katsutoshi; Osuga, Yutaka; Taketani, Yuji; Kang, Jing X; Arai, Hiroyuki; Arita, Makoto; Kozuma, Shiro; Fujii, Tomoyuki
2013-01-01
Omega-3 polyunsaturated fatty acids (omega-3 PUFAs) play a role in controlling pathological inflammatory reactions. Endometriosis is characterized by the presence of endometrial tissue on the peritoneum and an exaggerated inflammatory environment around ectopic tissues. Here peritoneal endometriosis was reproduced using a mouse model in which murine endometrial fragments were inoculated into the peritoneal cavity of mice. Fat-1 mice, in which omega-6 can be converted to omega-3 PUFAs, or wild type mice, in which it cannot, were used for the endometriosis model to address the actions of omega-3 PUFAs on the development of endometriotic lesions. The number and weight of cystic endometriotic lesions in fat-1 mice two weeks after inoculation were significantly less than half to those of controls. Mediator lipidomics revealed that cystic endometriotic lesions and peritoneal fluids were abundant in 12/15-hydroxyeicosapentaenoic acid (12/15-HEPE), derived from eicosapentaenoic acid (EPA), and their amount in fat-1 mice was significantly larger than that in controls. 12/15-Lipoxygenase (12/15-LOX)-knockout (KO) and control mice with or without EPA administration were assessed for the endometriosis model. EPA administration decreased the number of lesions in controls but not in 12/15-LOX-KO mice. The peritoneal fluids in EPA-fed 12/15-LOX-KO mice contained reduced levels of EPA metabolites such as 12/15-HEPE and EPA-derived resolvin E3 even after EPA administration. cDNA microarrays of endometriotic lesions revealed that Interleukin-6 (IL-6) expression in fat-1 mice was significantly lower than that in controls. These results suggest that both endogenous and exogenous EPA-derived PUFAs protect against the development of endometriosis through their anti-inflammatory effects and, in particular, the 12/15-LOX-pathway products of EPA may be key mediators to suppress endometriosis.
Universal graphs at $\\aleph_{\\omega_1+1}$
Davis, Jacob
2016-01-01
Starting from a supercompact cardinal we build a model in which $2^{\\aleph_{\\omega_1}}=2^{\\aleph_{\\omega_1+1}}=\\aleph_{\\omega_1+3}$ but there is a jointly universal family of size $\\aleph_{\\omega_1+2}$ of graphs on $\\aleph_{\\omega_1+1}$. The same technique will work for any uncountable cardinal in place of $\\omega_1$.
Hadronic decay properties of newly observed $\\Omega_c$ baryons
Zhao, Ze; Ye, Dan-Dan; Zhang, Ailin
2017-01-01
Hadronic decay widths of the newly observed charmed strange baryons, $\\Omega_c(3000)^0$, $\\Omega_c(3050)^0$, $\\Omega_c(3066)^0$, $\\Omega_c(3090)^0$ and $\\Omega_c(3119)^0$ have been calculated in a $^3P_0$ model. Our results indicate that $\\Omega_c(3066)^0$ and $\\Omega_c(3090)^0$ can be interpreted as the $1P-$wave $\\Omega_{c2}(\\frac{3}{2}^-)$ or $\\Omega_{c2}(\\frac{5}{2}^-)$. Though the measured masses of $\\Omega_c(3000)^0$, $\\Omega_c(3050)^0$ and $\\Omega_c(3119)^0$ are lower than existed theo...
Pradelli, Lorenzo; Eandi, Mario; Povero, Massimiliano; Mayer, Konstantin; Muscaritoli, Maurizio; Heller, Axel R; Fries-Schaffner, Eva
2014-10-01
A recent meta-analysis showed that supplementation of omega-3 fatty acids in parenteral nutrition (PN) regimens is associated with a statistically and clinically significant reduction in infection rate, and length of hospital stay (LOS) in medical and surgical patients admitted to the ICU and in surgical patients not admitted to the ICU. The objective of this present study was to evaluate the cost-effectiveness of the addition of omega-3 fatty acids to standard PN regimens in four European countries (Italy, France, Germany and the UK) from the healthcare provider perspective. Using a discrete event simulation scheme, a patient-level simulation model was developed, based on outcomes from the Italian ICU patient population and published literature. Comparative efficacy data for PN regimens containing omega-3 fatty acids versus standard PN regimens was taken from the meta-analysis of published randomised clinical trials (n = 23 studies with a total of 1502 patients), and hospital LOS reduction was further processed in order to split the reduction in ICU stay from that in-ward stays for patients admitted to the ICU. Country-specific cost data was obtained for Italian, French, German and UK healthcare systems. Clinical outcomes included in the model were death rates, nosocomial infection rates, and ICU/hospital LOS. Probabilistic and deterministic sensitivity analyses were undertaken to test the reliability of results. PN regimens containing omega-3 fatty acids were more effective on average than standard PN both in ICU and in non-ICU patients in the four countries considered, reducing infection rates and overall LOS, and resulting in a lower total cost per patient. Overall costs for patients receiving PN regimens containing omega-3 fatty acids were between €14 144 to €19 825 per ICU patient and €5484 to €14 232 per non-ICU patient, translating into savings of between €3972 and €4897 per ICU patient and savings of between €561 and €1762 per non
Vulnerability to omega-3 deprivation in a mouse model of NMDA receptor hypofunction.
Islam, Rehnuma; Trépanier, Marc-Olivier; Milenkovic, Marija; Horsfall, Wendy; Salahpour, Ali; Bazinet, Richard P; Ramsey, Amy J
2017-01-01
Several studies have found decreased levels of ω-3 polyunsaturated fatty acids in the brain and blood of schizophrenia patients. Furthermore, dietary ω-3 supplements may improve schizophrenia symptoms and delay the onset of first-episode psychosis. We used an animal model of NMDA receptor hypofunction, NR1KD mice, to understand whether changes in glutamate neurotransmission could lead to changes in brain and serum fatty acids. We further asked whether dietary manipulations of ω-3, either depletion or supplementation, would affect schizophrenia-relevant behaviors of NR1KD mice. We discovered that NR1KD mice have elevated brain levels of ω-6 fatty acids regardless of their diet. While ω-3 supplementation did not improve any of the NR1KD behavioral abnormalities, ω-3 depletion exacerbated their deficits in executive function. Omega-3 depletion also caused extreme mortality among male mutant mice, with 75% mortality rate by 12 weeks of age. Our studies show that alterations in NMDAR function alter serum and brain lipid composition and make the brain more vulnerable to dietary ω-3 deprivation.
A model-based design and validation approach with OMEGA-UML and the IF toolset
Ben-hafaiedh, Imene; Constant, Olivier; Graf, Susanne; Robbana, Riadh
2009-03-01
Intelligent, embedded systems such as autonomous robots and other industrial systems are becoming increasingly more heterogeneous with respect to the platforms on which they are implemented, and thus the software architecture more complex to design and analyse. In this context, it is important to have well-defined design methodologies which should be supported by (1) high level design concepts allowing to master the design complexity, (2) concepts for the expression of non-functional requirements and (3) analysis tools allowing to verify or invalidate that the system under development will be able to conform to its requirements. We illustrate here such an approach for the design of complex embedded systems on hand of a small case study used as a running example for illustration purposes. We briefly present the important concepts of the OMEGA-RT UML profile, we show how we use this profile in a modelling approach, and explain how these concepts are used in the IFx verification toolbox to integrate validation into the design flow and make scalable verification possible.
Omega-3 Fatty Acids: Possible Neuroprotective Mechanisms in the Model of Global Ischemia in Rats
Directory of Open Access Journals (Sweden)
Maria Elizabeth Pereira Nobre
2016-01-01
Full Text Available Background. Omega-3 (ω3 administration was shown to protect against hypoxic-ischemic injury. The objectives were to study the neuroprotective effects of ω3, in a model of global ischemia. Methods. Male Wistar rats were subjected to carotid occlusion (30 min, followed by reperfusion. The groups were SO, untreated ischemic and ischemic treated rats with ω3 (5 and 10 mg/kg, 7 days. The SO and untreated ischemic animals were orally treated with 1% cremophor and, 1 h after the last administration, they were behaviorally tested and euthanized for neurochemical (DA, DOPAC, and NE determinations, histological (Fluoro jade staining, and immunohistochemical (TNF-alpha, COX-2 and iNOS evaluations. The data were analyzed by ANOVA and Newman-Keuls as the post hoc test. Results. Ischemia increased the locomotor activity and rearing behavior that were partly reversed by ω3. Ischemia decreased striatal DA and DOPAC contents and increased NE contents, effects reversed by ω3. This drug protected hippocampal neuron degeneration, as observed by Fluoro-Jade staining, and the increased immunostainings for TNF-alpha, COX-2, and iNOS were partly or totally blocked by ω3. Conclusion. This study showed a neuroprotective effect of ω3, in great part due to its anti-inflammatory properties, stimulating translational studies focusing on its use in clinic for stroke managing.
International Nuclear Information System (INIS)
Shibuya, E.H.
1989-01-01
The OMEGA - Observation of Multiple particle production, Exotic Interactions and Gamma-ray Air Shower-project is presented. The project try to associate photosensitive detectors from experiences of hadronic interactions with electronic detectors used by experiences that investigate extensive atmospheric showers. (M.C.K.)
Gorski, Krzysztof M.; Silk, Joseph; Vittorio, Nicola
1992-01-01
A new technique is used to compute the correlation function for large-angle cosmic microwave background anisotropies resulting from both the space and time variations in the gravitational potential in flat, vacuum-dominated, cold dark matter cosmological models. Such models with Omega sub 0 of about 0.2, fit the excess power, relative to the standard cold dark matter model, observed in the large-scale galaxy distribution and allow a high value for the Hubble constant. The low order multipoles and quadrupole anisotropy that are potentially observable by COBE and other ongoing experiments should definitively test these models.
Risk modelling in portfolio optimization
Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi
2013-09-01
Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.
Model Risk in Portfolio Optimization
Directory of Open Access Journals (Sweden)
David Stefanovits
2014-08-01
Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.
MCNP and OMEGA criticality calculations
International Nuclear Information System (INIS)
Seifert, E.
1998-04-01
The reliability of OMEGA criticality calculations is shown by a comparison with calculations by the validated and widely used Monte Carlo code MCNP. The criticality of 16 assemblies with uranium as fissionable is calculated with the codes MCNP (Version 4A, ENDF/B-V cross sections), MCNP (Version 4B, ENDF/B-VI cross sections), and OMEGA. Identical calculation models are used for the three codes. The results are compared mutually and with the experimental criticality of the assemblies. (orig.)
Directory of Open Access Journals (Sweden)
Teti Estiasih1*
2009-12-01
Full Text Available Omega-3 fatty acids (-3 are proven to have health beneficial effects. Some effort had been done to obtained oil high in -3 fatty acids. Among the methods developed, urea crystallization was preferred because it is simple, economic, and result in high purity of fatty acids. A source that had not been widely explored for -3 fatty acids production is the by-product of tuna meal processing. This research studied the optimization condition for separation and purification of -3 fatty acids from the by-product of tuna meal processing by urea crystallization. Crystallization reaction conditions of urea inclusion were optimized using the response surface methodology, and the model was developed.Optimization result showed a quadratic polynomial regression equation of Y= 140,52677X1 + 8,38203X2 – 19,85850X12 – 0,12173X22 – 0,74000X1X2 – 240,33546 with X1=urea to fatty acid ratio and X2=crystallization time. Maximum response was obtained at urea to fatty acid ratio of 3,07:1,crystallization time of 25,10 hours, and predicted response was 80,60%. Analysis of variance showed that urea to fatty acid ratio and crystallization time affected response. Under optimal conditions, the product was 3.89 times concentrated and the purity of -3 fatty acids was 81,98%. Verification result revealed that the predicted value from this model was reasonably close to the experimentally observed value. Urea crystallization process changed quality parameters that were oxidation level (peroxide value, anisidin value, and totox value, Fe and Cu content, P content, and water content. The changes were caused by adsorption of primary and secondary oxidation products, part of metals, and phosphoric compound onto unsaponifiable matters or soluble into water.
Using Caenorhabditis elegans to Uncover Conserved Functions of Omega-3 and Omega-6 Fatty Acids
Watts, Jennifer L.
2016-01-01
The nematode Caenorhabditis elegans is a powerful model organism to study functions of polyunsaturated fatty acids. The ability to alter fatty acid composition with genetic manipulation and dietary supplementation permits the dissection of the roles of omega-3 and omega-6 fatty acids in many biological process including reproduction, aging and neurobiology. Studies in C. elegans to date have mostly identified overlapping functions of 20-carbon omega-6 and omega-3 fatty acids in reproduction and in neurons, however, specific roles for either omega-3 or omega-6 fatty acids are beginning to emerge. Recent findings with importance to human health include the identification of a conserved Cox-independent prostaglandin synthesis pathway, critical functions for cytochrome P450 derivatives of polyunsaturated fatty acids, the requirements for omega-6 and omega-3 fatty acids in sensory neurons, and the importance of fatty acid desaturation for long lifespan. Furthermore, the ability of C. elegans to interconvert omega-6 to omega-3 fatty acids using the FAT-1 omega-3 desaturase has been exploited in mammalian studies and biotechnology approaches to generate mammals capable of exogenous generation of omega-3 fatty acids. PMID:26848697
Pyomo optimization modeling in Python
Hart, William E; Watson, Jean-Paul; Woodruff, David L; Hackebeil, Gabriel A; Nicholson, Bethany L; Siirola, John D
2017-01-01
This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. Pyomo is an open source software package fo...
International Nuclear Information System (INIS)
Ilyasoglu, H.
2017-01-01
A structured lipid (SL) constituting omega fatty acids was synthesized by using linseed and grape seed oils as substrates via a lipase-catalyzed reaction. Lipozyme® TL IM was used as a biocatalyst. Good quadratic models predicting the incorporation of omega fatty acids were achieved via the Response surface methodology (RSM). The optimal conditions for targeted omega-6/omega-3 fatty acid ratio (2:1) were obtained at a substrate molar ratio 1.4, time 8.4 h, and enzyme amount 6.4%. The SL contained linoleic acid (43 g 100g-1), which was mainly located in the sn-2 position (40 g 100g-1). α-Linoleic acid, and α-linolenic acid at the sn-2 position were 22 g 100g-1, and 11 g 100g-1, respectively. The oxidative stability of the SL, and SL with antioxidants was also investigated. The produced SL may be proposed as a source of a balanced intake of omega fatty acids and an ingredient in functional food formulations. [es
Venturi scrubber modelling and optimization
Energy Technology Data Exchange (ETDEWEB)
Viswanathan, S [National Univ., La Jolla, CA (United States). School of Engineering and Technology; Ananthanarayanan, N.V. [National Univ. of Singapore (Singapore). Dept. of Chemical and Environmental Engineering; Azzopardi, B.J. [Nottingham Univ., Nottingham (United Kingdom). Dept. of Chemical Engineering
2005-04-01
This study presented a method to maintain the efficiency of venturi scrubbers in removing fine particulates during gas clean operations while minimizing pressure drop. Venturi scrubbers meet stringent emission standards. In order to choose the optimal method for predicting pressure drop, 4 established models were compared for their accuracy of prediction and simplicity in application. The enhanced algorithm optimizes Pease-Anthony type venturi scrubber performance by predicting the minimum pressure drop required to achieve the desired collection efficiency. This was accomplished by optimizing the key operating and design parameters such as liquid-to-gas ratio, throat gas velocity, number of nozzles, nozzle diameter and throat aspect ratio. Two of the 4 established models were expanded by providing an empirical algorithm to better predict pressure drop in the venturi throat. Model results were validated with experimental data. The optimization algorithm considers the non-uniformity in liquid distribution. It can be applied to cylindrical and rectangular Pease-Anthony type scrubbers. It offers an effective, systematic and accurate method to optimize the performance of new and existing scrubbers. 54 refs., 5 figs.
Three-dimensional modeling of direct-drive cryogenic implosions on OMEGA
International Nuclear Information System (INIS)
Igumenshchev, I. V.; Goncharov, V. N.; Marshall, F. J.; Knauer, J. P.; Campbell, E. M.
2016-01-01
The effects of large-scale (with Legendre modes ≲10) laser-imposed nonuniformities in direct-drive cryogenic implosions on the OMEGA laser system are investigated using three-dimension hydrodynamic simulations performed using a newly developed code ASTER. Sources of these nonuniformities include an illumination pattern produced by 60 OMEGA laser beams, capsule offsets (~10 to 20 μm), and imperfect pointing, energy balance, and timing of the beams (with typical σ rms ~10 μm, 10%, and 5 ps, respectively). Two implosion designs using 26-kJ triple-picket laser pulses were studied: a nominal design, in which a 880-μm-diameter capsule is illuminated by the same-diameter beams, and a “R75” design using a capsule of 900 μm in diameter and beams of 75% of this diameter. Simulations found that nonuniformities because of capsule offsets and beam imbalance have the largest effect on implosion performance. These nonuniformities lead to significant distortions of implosion cores resulting in an incomplete stagnation. The shape of distorted cores is well represented by neutron images, but loosely in x-rays. Simulated neutron spectra from perturbed implosions show large directional variations and up to ~ 2 keV variation of the hot spot temperature inferred from these spectra. The R75 design is more hydrodynamically efficient because of mitigation of crossed-beam energy transfer, but also suffers more from the nonuniformities. Furthermore, simulations predict a performance advantage of this design over the nominal design when the target offset and beam imbalance σ rms are reduced to less than 5 μm and 5%, respectively
Omega-Harmonic Functions and Inverse Conductivity Problems on Networks
National Research Council Canada - National Science Library
Berenstein, Carlos A; Chung, Soon-Yeong
2003-01-01
.... To do this, they introduce an elliptic operator DELTA omega and an omega-harmonic function on the graph, with its physical interpretation being the diffusion equation on the graph, which models an electric network...
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonia...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
Energy Technology Data Exchange (ETDEWEB)
Howerton, R.J.; Dye, R.E.; Giles, P.C.; Kimlinger, J.R.; Perkins, S.T.; Plechaty, E.F.
1983-08-01
OMEGA is a CRAY I computer program that controls nine codes used by LLNL Physical Data Group for: 1) updating the libraries of evaluated data maintained by the group (UPDATE); 2) calculating average values of energy deposited in secondary particles and residual nuclei (ENDEP); 3) checking the libraries for internal consistency, especially for energy conservation (GAMCHK); 4) producing listings, indexes and plots of the library data (UTILITY); 5) producing calculational constants such as group averaged cross sections and transfer matrices for diffusion and Sn transport codes (CLYDE); 6) producing and updating standard files of the calculational constants used by LLNL Sn and diffusion transport codes (NDFL); 7) producing calculational constants for Monte Carlo transport codes that use group-averaged cross sections and continuous energy for particles (CTART); 8) producing and updating standard files used by the LLNL Monte Carlo transport codes (TRTL); and 9) producing standard files used by the LANL pointwise Monte Carlo transport code MCNP (MCPOINT). The first four of these functions and codes deal with the libraries of evaluated data and the last five with various aspects of producing calculational constants for use by transport codes. In 1970 a series, called PD memos, of internal and informal memoranda was begun. These were intended to be circulated among the group for comment and then to provide documentation for later reference whenever questions arose about the subject matter of the memos. They have served this purpose and now will be drawn upon as source material for this more comprehensive report that deals with most of the matters covered in those memos.
International Nuclear Information System (INIS)
Howerton, R.J.; Dye, R.E.; Giles, P.C.; Kimlinger, J.R.; Perkins, S.T.; Plechaty, E.F.
1983-08-01
OMEGA is a CRAY I computer program that controls nine codes used by LLNL Physical Data Group for: 1) updating the libraries of evaluated data maintained by the group (UPDATE); 2) calculating average values of energy deposited in secondary particles and residual nuclei (ENDEP); 3) checking the libraries for internal consistency, especially for energy conservation (GAMCHK); 4) producing listings, indexes and plots of the library data (UTILITY); 5) producing calculational constants such as group averaged cross sections and transfer matrices for diffusion and Sn transport codes (CLYDE); 6) producing and updating standard files of the calculational constants used by LLNL Sn and diffusion transport codes (NDFL); 7) producing calculational constants for Monte Carlo transport codes that use group-averaged cross sections and continuous energy for particles (CTART); 8) producing and updating standard files used by the LLNL Monte Carlo transport codes (TRTL); and 9) producing standard files used by the LANL pointwise Monte Carlo transport code MCNP (MCPOINT). The first four of these functions and codes deal with the libraries of evaluated data and the last five with various aspects of producing calculational constants for use by transport codes. In 1970 a series, called PD memos, of internal and informal memoranda was begun. These were intended to be circulated among the group for comment and then to provide documentation for later reference whenever questions arose about the subject matter of the memos. They have served this purpose and now will be drawn upon as source material for this more comprehensive report that deals with most of the matters covered in those memos
Omega-6 fatty acids are types of fats. Some types are found in vegetable oils, including corn, evening primrose seed, safflower, and soybean oils. Other types of omega-6 fatty acids are found in black currant seed, borage seed, ...
MODELLING, SIMULATING AND OPTIMIZING BOILERS
DEFF Research Database (Denmark)
Sørensen, Kim; Condra, Thomas Joseph; Houbak, Niels
2004-01-01
In the present work a framework for optimizing the design of boilers for dynamic operation has been developed. A cost function to be minimized during the optimization has been formulated and for the present design variables related to the Boiler Volume and the Boiler load Gradient (i.e. ring rate...... on the boiler) have been dened. Furthermore a number of constraints related to: minimum and maximum boiler load gradient, minimum boiler size, Shrinking and Swelling and Steam Space Load have been dened. For dening the constraints related to the required boiler volume a dynamic model for simulating the boiler...... performance has been developed. Outputs from the simulations are shrinking and swelling of water level in the drum during for example a start-up of the boiler, these gures combined with the requirements with respect to allowable water level uctuations in the drum denes the requirements with respect to drum...
MODELLING, SIMULATING AND OPTIMIZING BOILERS
DEFF Research Database (Denmark)
Sørensen, K.; Condra, T.; Houbak, Niels
2003-01-01
, and the total stress level (i.e. stresses introduced due to internal pressure plus stresses introduced due to temperature gradients) must always be kept below the allowable stress level. In this way, the increased water-/steam space that should allow for better dynamic performance, in the end causes limited...... freedom with respect to dynamic operation of the plant. By means of an objective function including as well the price of the plant as a quantification of the value of dynamic operation of the plant an optimization is carried out. The dynamic model of the boiler plant is applied to define parts...
Clean coal technology optimization model
International Nuclear Information System (INIS)
Laseke, B.A.; Hance, S.B.
1992-01-01
Title IV of the Clean Air Act Amendments (CAAA) of 1990 contains provisions for the mitigation of acid rain precipitation through reductions in the annual emission of the acid rain precursors of sulfur dioxide (SO 2 ) and nitrogen oxide (NO x ). These provisions will affect primarily existing coal-fired power-generating plants by requiring nominal reductions of 5 millon and 10 million tons of SO 2 by the years 1995 and 2000, respectively, and 2 million tons of NO x by the year 2000 relative to the 1980 and 1985-87 reference period. The 1990 CAAA Title IV provisions are extremely complex in that they establish phased regulatory milestones, unit-level emission allowances and caps, a mechanism for inter-utility trading of emission allowances, and a system of emission allowance credits based on selection of control option and timing of its implementation. The net result of Title IV of the 1990 CAAA is that approximately 147 gigawatts (GW) of generating capacity is eligible to retrofit SO 2 controls by the year 2000. A number of options are available to bring affected boilers into compliance with Title IV. Market sharewill be influenced by technology performance and costs. These characteristics can be modeled through a bottom-up technology cost and performance optimization exercise to show their impact on the technology's potential market share. Such a model exists in the form of an integrated data base-model software system. This microcomputer (PC)-based software system consists of a unit (boiler)-level data base (ACIDBASE), a cost and performance engineering model (IAPCS), and a market forecast model (ICEMAN)
Omega-3 Index of Canadian adults.
Langlois, Kellie; Ratnayake, Walisundera M N
2015-11-01
Cardioprotective properties have been associated with two fatty acids-eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The Omega-3 Index indicates the percentage of EPA+DHA in red blood cell fatty acids. Omega-3 Index levels of the Canadian population have not been directly measured. Data for respondents aged 20 to 79 from cycle 3 (2012/2013) of the Canadian Health Measures Survey were used to calculate means and the prevalence of Omega-3 Index coronary heart disease (CHD) risk cut-offs-high (4% or less), moderate (more than 4% to less than 8%), and low (8% or more)-by sociodemographic and lifestyle characteristics, including fish consumption and use of omega-3 supplements. Associations between the Omega-3 Index and CHD-related factors including biomarkers, risk factors, and previous CHD events, were examined in multivariate regression models. The mean Omega-3 Index level of Canadians aged 20 to 79 was 4.5%. Levels were higher for women, older adults, Asians and other non-white Canadians, omega-3 supplement users, and fish consumers; levels were lower for smokers and people who were obese. Fewer than 3% of adults had levels associated with low CHD risk; 43% had levels associated with high risk. No CHD-related factor was associated with the Omega-3 Index when control variables were taken into account. Omega-3 Index levels among Canadian adults were strongly related to age, race, supplement use, fish consumption, smoking status and obesity. Fewer than 3% of adults had Omega-3 Index levels associated with low risk for CHD.
Omega-3 fatty acids are a form of polyunsaturated fat that the body derives from food. Omega-3s (and omega-6s) are known as essential fatty acids (EFAs) because they are important for good health. ...
Surrogate Modeling for Geometry Optimization
DEFF Research Database (Denmark)
Rojas Larrazabal, Marielba de la Caridad; Abraham, Yonas; Holzwarth, Natalie
2009-01-01
A new approach for optimizing the nuclear geometry of an atomic system is described. Instead of the original expensive objective function (energy functional), a small number of simpler surrogates is used.......A new approach for optimizing the nuclear geometry of an atomic system is described. Instead of the original expensive objective function (energy functional), a small number of simpler surrogates is used....
Georgiou, Tassos; Wen, Yao-Tseng; Chang, Chung-Hsing; Kolovos, Panagiotis; Kalogerou, Maria; Prokopiou, Ekatherine; Neokleous, Anastasia; Huang, Chin-Te; Tsai, Rong-Kung
2017-03-01
The purpose of this study was to investigate the therapeutic effect of omega-3 polyunsaturated fatty acid (ω-3 PUFA) administration in a rat model of anterior ischemic optic neuropathy (rAION). The level of blood arachidonic acid/eicosapentaenoic acid (AA/EPA) was measured to determine the suggested dosage. The rAION-induced rats were administered fish oil (1 g/day EPA) or phosphate-buffered saline (PBS) by daily gavage for 10 consecutive days to evaluate the neuroprotective effects. Blood fatty acid analysis showed that the AA/EPA ratio was reduced from 17.6 to ≤1.5 after 10 days of fish oil treatment. The retinal ganglion cell (RGC) densities and the P1-N2 amplitude of flash visual-evoked potentials (FVEP) were significantly higher in the ω-3 PUFA-treated group, compared with the PBS-treated group (P optic nerve (ON) by 3.17-fold in the rAION model. The M2 macrophage markers, which decrease inflammation, were induced in the ω-3 PUFA-treated group in contrast to the PBS-treated group. In addition, the mRNA levels of tumor necrosis factor-alpha, interleukin-1 beta, and inducible nitric oxide synthase were significantly reduced in the ω-3 PUFA-treated group. The administration of ω-3 PUFAs has neuroprotective effects in rAION, possibly through dual actions of the antiapoptosis of RGCs and anti-inflammation via decreasing inflammatory cell infiltration, as well as the regulation of macrophage polarization to decrease the cytokine-induced injury of the ON.
Following an Optimal Batch Bioreactor Operations Model
DEFF Research Database (Denmark)
Ibarra-Junquera, V.; Jørgensen, Sten Bay; Virgen-Ortíz, J.J.
2012-01-01
The problem of following an optimal batch operation model for a bioreactor in the presence of uncertainties is studied. The optimal batch bioreactor operation model (OBBOM) refers to the bioreactor trajectory for nominal cultivation to be optimal. A multiple-variable dynamic optimization of fed...... as the master system which includes the optimal cultivation trajectory for the feed flow rate and the substrate concentration. The “real” bioreactor, the one with unknown dynamics and perturbations, is considered as the slave system. Finally, the controller is designed such that the real bioreactor...
Intelligent structural optimization: Concept, Model and Methods
International Nuclear Information System (INIS)
Lu, Dagang; Wang, Guangyuan; Peng, Zhang
2002-01-01
Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented
Near-wall extension of a non-equilibrium, omega-based Reynolds stress model
International Nuclear Information System (INIS)
Nguyen, Tue; Behr, Marek; Reinartz, Birgit
2011-01-01
In this paper, the development of a new ω-based Reynolds stress model that is consistent with asymptotic analysis in the near wall region and with rapid distortion theory in homogeneous turbulence is reported. The model is based on the SSG/LRR-ω model developed by Eisfeld (2006) with three main modifications. Firstly, the near wall behaviors of the redistribution, dissipation and diffusion terms are modified according to the asymptotic analysis and a new blending function based on low Reynolds number is proposed. Secondly, an anisotropic dissipation tensor based on the Reynolds stress inhomogeneity (Jakirlic et al., 2007) is used instead of the original isotropic model. Lastly, the SSG redistribution term, which is activated far from the wall, is replaced by Speziale's non-equilibrium model (Speziale, 1998).
Omega-3 fatty acids are used together with lifestyle changes (diet, weight-loss, exercise) to reduce the amount of triglycerides (a fat- ... in people with very high triglycerides. Omega-3 fatty acids are in a class of medications called antilipemic ...
Optimization in engineering models and algorithms
Sioshansi, Ramteen
2017-01-01
This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering ...
Optimal Hedging with the Vector Autoregressive Model
L. Gatarek (Lukasz); S.G. Johansen (Soren)
2014-01-01
markdownabstract__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be
Energy Technology Data Exchange (ETDEWEB)
Johns, H. M., E-mail: hjohns@lanl.gov; Lanier, N. E.; Kline, J. L.; Fontes, C. J.; Perry, T. S.; Fryer, C. L.; Sherrill, M. E. [Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, New Mexico 87544 (United States); Brown, C. R. D.; Morton, J. W. [AWE Aldermaston, Berkshire, Reading RG7 4PR (United Kingdom); Hager, J. D. [Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, New Mexico 87544 (United States); Lockheed-Martin, 497 Electronics Parkway, Syracuse, New York 13221 (United States)
2016-11-15
We present synthetic transmission spectra generated with PrismSPECT utilizing both the ATBASE model and the Los Alamos opacity library (OPLIB) to evaluate whether an alternative choice in atomic data will impact modeling of experimental data from radiation transport experiments using Sc-doped aerogel foams (ScSi{sub 6}O{sub 12} at 75 mg/cm{sup 3} density). We have determined that in the 50-200 eV T{sub e} range there is a significant difference in the 1s-3p spectra, especially below 100 eV, and for T{sub e} = 200 eV above 5000 eV in photon energy. Examining synthetic spectra generated using OPLIB with 300 resolving power reveals spectral sensitivity to T{sub e} changes of ∼3 eV.
Energy Technology Data Exchange (ETDEWEB)
Ilyasoglu, H.
2017-07-01
A structured lipid (SL) constituting omega fatty acids was synthesized by using linseed and grape seed oils as substrates via a lipase-catalyzed reaction. Lipozyme® TL IM was used as a biocatalyst. Good quadratic models predicting the incorporation of omega fatty acids were achieved via the Response surface methodology (RSM). The optimal conditions for targeted omega-6/omega-3 fatty acid ratio (2:1) were obtained at a substrate molar ratio 1.4, time 8.4 h, and enzyme amount 6.4%. The SL contained linoleic acid (43 g 100g-1), which was mainly located in the sn-2 position (40 g 100g-1). α-Linoleic acid, and α-linolenic acid at the sn-2 position were 22 g 100g-1, and 11 g 100g-1, respectively. The oxidative stability of the SL, and SL with antioxidants was also investigated. The produced SL may be proposed as a source of a balanced intake of omega fatty acids and an ingredient in functional food formulations. [Spanish] Se sintetizaron lípidos estructurados (SL), formados por ácidos grasos omega, utilizando aceites de linaza y semillas de uva como sustratos a través de una reacción catalizada por lipasa. Se utilizó Lipozyme® TL IM como biocatalizador. Los buenos modelos cuadráticos que predecían la incorporación de los ácidos grasos omega se lograron a través de la metodología de superficie de respuesta (RSM). Se obtuvieron las condiciones óptimas para una proporción de ácidos grasos omega-6/omega-3 (2:1) con una relación molar de sustrato 1:4, tiempo de 8,4 h, y cantidad de enzima 6,4%. El SL contenía ácido linoleico (43 g·100 g-1), que se localizaba principalmente en la posición sn-2 (40 g·100 g-1). El ácido α-linoleico y el ácido α-linolénico en la posición sn-2 fueron de 22 g·100 g-1y 11 g·100 g-1, respectivamente. También se investigó la estabilidad oxidativa del SL y SL con antioxidantes. El SL producido puede ser propuesto como una fuente para una ingesta equilibrada de ácidos grasos omega y un ingrediente en las formulaciones
Rethinking exchange market models as optimization algorithms
Luquini, Evandro; Omar, Nizam
2018-02-01
The exchange market model has mainly been used to study the inequality problem. Although the human society inequality problem is very important, the exchange market models dynamics until stationary state and its capability of ranking individuals is interesting in itself. This study considers the hypothesis that the exchange market model could be understood as an optimization procedure. We present herein the implications for algorithmic optimization and also the possibility of a new family of exchange market models
Directory of Open Access Journals (Sweden)
Rossi, P.
2014-12-01
Full Text Available The concentration of omega-3 compounds obtained for the esterification of squid oil by molecular distillation was carried out in two stages. This operation can process these thermolabile and high molecular weight components at very low temperatures. Given the mathematical complexity of the theoretical model, artificial neural networks (ANN have provided an alternative to a classical computing analysis. The objective of this study was to create a predictive model using artificial neural network techniques to represent the concentration process of omega-3 compounds obtained from squid oil using molecular distillation. Another objective of this study was to analyze the performance of two different alternatives of ANN modeling; one of them is a model that represents all variables in the process and the other is a global model that simulates only the input and output variables of the process. The alternative of the ANN global model showed the best fit to the experimental data.La concentración de compuestos omega-3, obtenidos de la esterificación de aceite de calamar, por destilación molecular fue llevada a cabo en dos etapas. Esta operación permite procesar componentes termolábiles y de alto peso molecular a muy bajas temperaturas. Dada la alta complejidad de los modelos teóricos, las redes neuronales artificiales (RNA conforman una alternativa al análisis computacional clásico. El objetivo de este estudio fue crear un modelo predictivo usando modelos de redes neuronales artificiales para representar el proceso de concentración de compuestos omega-3 obtenidos del aceite de calamar por destilación molecular. Otro objetivo de este estudio fue analizar el desenvolvimiento de dos alternativas de modelos RNA; uno de ellos es un modelo que representa todas las variables en el proceso y otro es un modelo global que simula solo las variables de entrada y de salida del proceso. La alternativa de un modelo RNA global mostró el mejor ajuste de los
DEFF Research Database (Denmark)
Ghiglino, Christian; Tvede, Mich
for generations, through fiscal policy, i.e. monetary transfers and taxes. Both situations with and without time discounting are considered. It is shown that if the discount factor is suffciently close to one then the optimal policy stabilizes the economy, i.e. the equilibrium path has the turnpike property...
DEFF Research Database (Denmark)
Ghiglino, Christian; Tvede, Mich
2000-01-01
for generations, through fiscal policy, i.e., monetary transfers and taxes. Situations both with and without time discounting are considered. It is shown that if the discount factor is sufficiently close to one then the optimal policy stabilizes the economy, i.e. the equilibrium path has the turnpike property...
Handbook on modelling for discrete optimization
Pitsoulis, Leonidas; Williams, H
2006-01-01
The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...
Portfolio optimization with mean-variance model
Hoe, Lam Weng; Siew, Lam Weng
2016-06-01
Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.
Modeling investor optimism with fuzzy connectives
Lovric, M.; Almeida, R.J.; Kaymak, U.; Spronk, J.; Carvalho, J.P.; Dubois, D.; Kaymak, U.; Sousa, J.M.C.
2009-01-01
Optimism or pessimism of investors is one of the important characteristics that determine the investment behavior in financial markets. In this paper, we propose a model of investor optimism based on a fuzzy connective. The advantage of the proposed approach is that the influence of different levels
The omega-6/omega-3 fatty acid ratio: health implications
Directory of Open Access Journals (Sweden)
Simopoulos Artemis P.
2010-09-01
Full Text Available Today, Western diets are characterized by a higher omega-6 and a lower omega-3 fatty acid intake, whereas during the Paleolithic period when human’s genetic profile was established, there was a balance between omega-6 and omega-3 fatty acids. Their balance is an important determinant for brain development and in decreasing the risk for coronary heart disease (CHD, hypertension, cancer, diabetes, arthritis, and other autoimmune and possibly neurodegenerative diseases. Both omega-6 and omega-3 fatty acids influence gene expression. Because of single nucleotide polymorphisms (SNPs in their metabolic pathways, blood levels of omega-6 and omega-3 fatty acids are determined by both endogenous metabolism and dietary intake making the need of balanced dietary intake essential for health and disease prevention. Whether an omega-6/omega-3 ratio of 3:1 to 4:1 could prevent the pathogenesis of many diseases induced by today’s Western diets (AFSSA, 2010, a target of 1:1 to 2:1 appears to be consistent with studies on evolutionary aspects of diet, neurodevelopment, and genetics. A target of omega-6/omega-3 fatty acid ratio of 1:1 to 2:1 appears to be consistent with studies on evolutionary aspects of diet, neurodevelopment and genetics. A balanced ratio of omega-6/omega-3 fatty acids is important for health and in the prevention of CHD and possibly other chronic diseases.
Directory of Open Access Journals (Sweden)
K. O. Zolotarova
2016-12-01
Full Text Available The article presents the results of the study of the comparative efficacy of the protocol for angina pectoris medication and combined therapy with the use of ω-3 PUFA and magnetotherapy on the dynamics of the frequency of anginal attacks of patients with stable angina. It was found that the use of ώ-3 PUFA and MT in therapy allows a significantly higher and further reduction in the frequency of attacks compared with standard therapy, and this effect is largely due to the influence of MT and to a lesser extent - the effect of omega-3 polyunsaturated fatty acids.
Modeling and optimization of laser cutting operations
Directory of Open Access Journals (Sweden)
Gadallah Mohamed Hassan
2015-01-01
Full Text Available Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta, surface roughness (Ra and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.
Mathematical modeling and optimization of complex structures
Repin, Sergey; Tuovinen, Tero
2016-01-01
This volume contains selected papers in three closely related areas: mathematical modeling in mechanics, numerical analysis, and optimization methods. The papers are based upon talks presented on the International Conference for Mathematical Modeling and Optimization in Mechanics, held in Jyväskylä, Finland, March 6-7, 2014 dedicated to Prof. N. Banichuk on the occasion of his 70th birthday. The articles are written by well-known scientists working in computational mechanics and in optimization of complicated technical models. Also, the volume contains papers discussing the historical development, the state of the art, new ideas, and open problems arising in modern continuum mechanics and applied optimization problems. Several papers are concerned with mathematical problems in numerical analysis, which are also closely related to important mechanical models. The main topics treated include: * Computer simulation methods in mechanics, physics, and biology; * Variational problems and methods; minimiz...
Maintenance Optimization of High Voltage Substation Model
Directory of Open Access Journals (Sweden)
Radim Bris
2008-01-01
Full Text Available The real system from practice is selected for optimization purpose in this paper. We describe the real scheme of a high voltage (HV substation in different work states. Model scheme of the HV substation 22 kV is demonstrated within the paper. The scheme serves as input model scheme for the maintenance optimization. The input reliability and cost parameters of all components are given: the preventive and corrective maintenance costs, the actual maintenance period (being optimized, the failure rate and mean time to repair - MTTR.
A useful framework for optimal replacement models
International Nuclear Information System (INIS)
Aven, Terje; Dekker, Rommert
1997-01-01
In this note we present a general framework for optimization of replacement times. It covers a number of models, including various age and block replacement models, and allows a uniform analysis for all these models. A relation to the marginal cost concept is described
Multiobjective optimization of an extremal evolution model
International Nuclear Information System (INIS)
Elettreby, M.F.
2004-09-01
We propose a two-dimensional model for a co-evolving ecosystem that generalizes the extremal coupled map lattice model. The model takes into account the concept of multiobjective optimization. We find that the system self-organizes into a critical state. The distributions of the distances between subsequent mutations as well as the distribution of avalanches sizes follow power law. (author)
Modeling and optimization of HVAC energy consumption
Energy Technology Data Exchange (ETDEWEB)
Kusiak, Andrew; Li, Mingyang; Tang, Fan [Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242 - 1527 (United States)
2010-10-15
A data-driven approach for minimization of the energy to air condition a typical office-type facility is presented. Eight data-mining algorithms are applied to model the nonlinear relationship among energy consumption, control settings (supply air temperature and supply air static pressure), and a set of uncontrollable parameters. The multiple-linear perceptron (MLP) ensemble outperforms other models tested in this research, and therefore it is selected to model a chiller, a pump, a fan, and a reheat device. These four models are integrated into an energy optimization model with two decision variables, the setpoint of the supply air temperature and the static pressure in the air handling unit. The model is solved with a particle swarm optimization algorithm. The optimization results have demonstrated the total energy consumed by the heating, ventilation, and air-conditioning system is reduced by over 7%. (author)
Optimization Models for Petroleum Field Exploitation
Energy Technology Data Exchange (ETDEWEB)
Jonsbraaten, Tore Wiig
1998-12-31
This thesis presents and discusses various models for optimal development of a petroleum field. The objective of these optimization models is to maximize, under many uncertain parameters, the project`s expected net present value. First, an overview of petroleum field optimization is given from the point of view of operations research. Reservoir equations for a simple reservoir system are derived and discretized and included in optimization models. Linear programming models for optimizing production decisions are discussed and extended to mixed integer programming models where decisions concerning platform, wells and production strategy are optimized. Then, optimal development decisions under uncertain oil prices are discussed. The uncertain oil price is estimated by a finite set of price scenarios with associated probabilities. The problem is one of stochastic mixed integer programming, and the solution approach is to use a scenario and policy aggregation technique developed by Rockafellar and Wets although this technique was developed for continuous variables. Stochastic optimization problems with focus on problems with decision dependent information discoveries are also discussed. A class of ``manageable`` problems is identified and an implicit enumeration algorithm for finding optimal decision policy is proposed. Problems involving uncertain reservoir properties but with a known initial probability distribution over possible reservoir realizations are discussed. Finally, a section on Nash-equilibrium and bargaining in an oil reservoir management game discusses the pool problem arising when two lease owners have access to the same underlying oil reservoir. Because the oil tends to migrate, both lease owners have incentive to drain oil from the competitors part of the reservoir. The discussion is based on a numerical example. 107 refs., 31 figs., 14 tabs.
Enhanced index tracking modelling in portfolio optimization
Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin
2013-09-01
Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.
micrOMEGAs 2.0.7: a program to calculate the relic density of dark matter in a generic model
Bélanger, G.; Boudjema, F.; Pukhov, A.; Semenov, A.
2007-12-01
micrOMEGAs2.0.7 is a code which calculates the relic density of a stable massive particle in an arbitrary model. The underlying assumption is that there is a conservation law like R-parity in supersymmetry which guarantees the stability of the lightest odd particle. The new physics model must be incorporated in the notation of CalcHEP, a package for the automatic generation of squared matrix elements. Once this is done, all annihilation and coannihilation channels are included automatically in any model. Cross-sections at v=0, relevant for indirect detection of dark matter, are also computed automatically. The package includes three sample models: the minimal supersymmetric standard model (MSSM), the MSSM with complex phases and the NMSSM. Extension to other models, including non supersymmetric models, is described. Program summaryTitle of program:micrOMEGAs2.0.7 Catalogue identifier:ADQR_v2_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADQR_v2_1.html Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.:216 529 No. of bytes in distributed program, including test data, etc.:1 848 816 Distribution format:tar.gz Programming language used:C and Fortran Computer:PC, Alpha, Mac, Sun Operating system:UNIX (Linux, OSF1, SunOS, Darwin, Cygwin) RAM:17 MB depending on the number of processes required Classification:1.9, 11.6 Catalogue identifier of previous version:ADQR_v2_0 Journal version of previous version:Comput. Phys. Comm. 176 (2007) 367 Does the new version supersede the previous version?:Yes Nature of problem:Calculation of the relic density of the lightest stable particle in a generic new model of particle physics. Solution method:In numerically solving the evolution equation for the density of dark matter, relativistic formulae for the thermal average are used. All tree
Energy Technology Data Exchange (ETDEWEB)
Herwig, Falk; VandenBerg, Don A.; Navarro, Julio F. [Department of Physics and Astronomy, University of Victoria, P.O. Box 3055, Victoria, BC V8W 3P6 (Canada); Ferguson, Jason [Department of Physics, Wichita State University Wichita, KS 67260 (United States); Paxton, Bill, E-mail: fherwig@uvic.ca, E-mail: vandenbe@uvic.ca, E-mail: jason.ferguson@wichita.edu, E-mail: paxton@kitp.ucsb.edu [KITP/UC Santa Barbara, Santa Barbara, CA 93106 (United States)
2012-10-01
We have investigated the color-magnitude diagram of {omega} Centauri and find that the blue main sequence (bMS) can be reproduced only by models that have a helium abundance in the range Y = 0.35-0.40. To explain the faint subgiant branch of the reddest stars ('MS-a/RG-a' sequence), isochrones for the observed metallicity ([Fe/H] Almost-Equal-To -0.7) appear to require both a high age ({approx}13 Gyr) and enhanced CNO abundances ([CNO/Fe] Almost-Equal-To 0.9). Y Almost-Equal-To 0.35 must also be assumed in order to counteract the effects of high CNO on turnoff colors and thereby to obtain a good fit to the relatively blue turnoff of this stellar population. This suggests a short chemical evolution period of time (<1 Gyr) for {omega} Cen. Our intermediate-mass (super-)asymptotic giant branch (AGB) models are able to reproduce the high helium abundances, along with [N/Fe] {approx}2 and substantial O depletions if uncertainties in the treatment of convection are fully taken into account. These abundance features distinguish the bMS stars from the dominant [Fe/H] Almost-Equal-To -1.7 population. The most massive super-AGB stellar models (M{sub ZAMS} {>=} 6.8 M{sub Sun }, M{sub He,core} {>=} 1.245 M{sub Sun }) predict too large N enhancements, which limit their role in contributing to the extreme populations. In order to address the observed central concentration of stars with He-rich abundance, we show here quantitatively that highly He- and N-enriched AGB ejecta have particularly efficient cooling properties. Based on these results and on the reconstruction of the orbit of {omega} Cen with respect to the Milky Way, we propose the Galactic plane passage gas purging scenario for the chemical evolution of this cluster. The bMS population formed shortly after the purging of most of the cluster gas as a result of the passage of {omega} Cen through the Galactic disk (which occurs today every {approx}40 Myr for {omega} Cen) when the initial mass function of the
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
OMEGA Upgrade preliminary design
International Nuclear Information System (INIS)
Craxton, R.S.
1989-10-01
The OMEGA laser system at the Laboratory for Laser Energetics of the University of Rochester is the only major facility in the United States capable of conducting fully diagnosed, direct-drive, spherical implosion experiments. As such, it serves as the national Laser Users Facility, benefiting scientists throughout the country. The University's participation in the National Inertial Confinement Fusion (ICF) program underwent review by a group of experts under the auspices of the National Academy of Sciences (the Happer Committee) in 1985. The Happer Committee recommended that the OMEGA laser be upgraded in energy to 30 kJ. To this end, Congress appropriated $4,000,000 for the preliminary design of the OMEGA Upgrade, spread across FY88 and FY89. This document describes the preliminary design of the OMEGA Upgrade. The proposed enhancements to the existing OMEGA facility will result in a 30-kHJ, 351-nm, 60-beam direct-drive system, with a versatile pulse-shaping facility and a 1%--2% uniformity of target drive. The Upgrade will allow scientists to explore the ignition-scaling regime, and to study target behavior that is hydrodynamically equivalent to that of targets appropriate for a laboratory microfusion facility (LMF). In addition, it will be possible to perform critical interaction experiments with large-scale-length uniformly irradiated plasmas
Splitting families and the Noetherian type of $\\beta\\omega-\\omega$
Milovich, David
2007-01-01
Extending some results of Malykhin, we prove several independence results about base properties of $\\beta\\omega-\\omega$ and its powers, especially the Noetherian type $Nt(\\beta\\omega-\\omega)$, the least $\\kappa$ for which $\\beta\\omega-\\omega$ has a base that is $\\kappa$-like with respect to containment. For example, $Nt(\\beta\\omega-\\omega)$ is never less than the splitting number, but can consistently be that $\\omega_1$, $2^\\omega$, $(2^\\omega)^+$, or strictly between $\\omega_1$ and $2^\\omega...
Mathematical model of highways network optimization
Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.
2017-12-01
The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.
Statistical models for optimizing mineral exploration
International Nuclear Information System (INIS)
Wignall, T.K.; DeGeoffroy, J.
1987-01-01
The primary purpose of mineral exploration is to discover ore deposits. The emphasis of this volume is on the mathematical and computational aspects of optimizing mineral exploration. The seven chapters that make up the main body of the book are devoted to the description and application of various types of computerized geomathematical models. These chapters include: (1) the optimal selection of ore deposit types and regions of search, as well as prospecting selected areas, (2) designing airborne and ground field programs for the optimal coverage of prospecting areas, and (3) delineating and evaluating exploration targets within prospecting areas by means of statistical modeling. Many of these statistical programs are innovative and are designed to be useful for mineral exploration modeling. Examples of geomathematical models are applied to exploring for six main types of base and precious metal deposits, as well as other mineral resources (such as bauxite and uranium)
Dynamic optimization deterministic and stochastic models
Hinderer, Karl; Stieglitz, Michael
2016-01-01
This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Modeling and optimization of LCD optical performance
Yakovlev, Dmitry A; Kwok, Hoi-Sing
2015-01-01
The aim of this book is to present the theoretical foundations of modeling the optical characteristics of liquid crystal displays, critically reviewing modern modeling methods and examining areas of applicability. The modern matrix formalisms of optics of anisotropic stratified media, most convenient for solving problems of numerical modeling and optimization of LCD, will be considered in detail. The benefits of combined use of the matrix methods will be shown, which generally provides the best compromise between physical adequacy and accuracy with computational efficiency and optimization fac
Modelling and Optimizing Mathematics Learning in Children
Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus
2013-01-01
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…
Omega test series - an overview
International Nuclear Information System (INIS)
Knowles, C.P.
2001-01-01
The United States Defense Threat Reduction Agency (DTRA) has supported a series of high explosive calibration experiments that were conducted in the Degelen Mountain area of the Semipalatinsk Test Site (STS) in the Republic of Kazakhstan (ROK). This paper will provide an overview of the second and third tests of this series which have been designated Omega-2 and Omega-3. Omega-2 was conducted on Saturday, September 25, 1999 and Omega-3 on Saturday, July 29, 2000. (author)
Modeling, simulation and optimization of bipedal walking
Berns, Karsten
2013-01-01
The model-based investigation of motions of anthropomorphic systems is an important interdisciplinary research topic involving specialists from many fields such as Robotics, Biomechanics, Physiology, Orthopedics, Psychology, Neurosciences, Sports, Computer Graphics and Applied Mathematics. This book presents a study of basic locomotion forms such as walking and running is of particular interest due to the high demand on dynamic coordination, actuator efficiency and balance control. Mathematical models and numerical simulation and optimization techniques are explained, in combination with experimental data, which can help to better understand the basic underlying mechanisms of these motions and to improve them. Example topics treated in this book are Modeling techniques for anthropomorphic bipedal walking systems Optimized walking motions for different objective functions Identification of objective functions from measurements Simulation and optimization approaches for humanoid robots Biologically inspired con...
International Nuclear Information System (INIS)
Kelly, J.H.; Shoup, M.J.; Smith, D.L.
1989-01-01
The authors discuss how they are designing an upgrade to its 24-beam OMEGA laser system, OMEGA is a frequency tripled, all-rod system capable of producing 2 kJ at 0.8 ns on target. Important direct-drive-target-ignition physics could be investigated with an upgraded system capable of producing a shaped pulse consisting of a long (5ns) low-intensity, foot, smoothly transitioning into a short (0.5 ns), intense, compression pulse. The total pulse energy is 30 kJ, which, from target-irradiation uniformity considerations, must be distributed over 60 beams
Modeling and Optimization : Theory and Applications Conference
Terlaky, Tamás
2017-01-01
This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 17-19, 2016. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.
Modeling and Optimization : Theory and Applications Conference
Terlaky, Tamás
2015-01-01
This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 13-15, 2014. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, healthcare, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.
A model of optimal voluntary muscular control.
FitzHugh, R
1977-07-19
In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.
Optimal time points sampling in pathway modelling.
Hu, Shiyan
2004-01-01
Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.
Simplified ejector model for control and optimization
International Nuclear Information System (INIS)
Zhu Yinhai; Cai Wenjian; Wen Changyun; Li Yanzhong
2008-01-01
In this paper, a simple yet effective ejector model for a real time control and optimization of an ejector system is proposed. Firstly, a fundamental model for calculation of ejector entrainment ratio at critical working conditions is derived by one-dimensional analysis and the shock circle model. Then, based on thermodynamic principles and the lumped parameter method, the fundamental ejector model is simplified to result in a hybrid ejector model. The model is very simple, which only requires two or three parameters and measurement of two variables to determine the ejector performance. Furthermore, the procedures for on line identification of the model parameters using linear and non-linear least squares methods are also presented. Compared with existing ejector models, the solution of the proposed model is much easier without coupled equations and iterative computations. Finally, the effectiveness of the proposed model is validated by published experimental data. Results show that the model is accurate and robust and gives a better match to the real performances of ejectors over the entire operating range than the existing models. This model is expected to have wide applications in real time control and optimization of ejector systems
Measurements of $\\jpsi$ decays into $\\omega\\pio$, $\\omega\\eta$, and $\\omega\\etap$
Ablikim, M.
2005-01-01
Based on $5.8 \\times 10^7 \\jpsi$ events collected with BESII at the Beijing Electron-Positron Collider (BEPC), the decay branching fractions of $\\jpsi\\to\\omega\\pio$, $\\omega\\eta$, and $\\omega\\etap$ are measured using different $\\eta$ and $\\etap$ decay modes. The results are higher than previous measurements. The $\\omega\\pio$ electromagnetic form factor is also obtained.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Optimal inventory management and order book modeling
Baradel, Nicolas
2018-02-16
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
1972-01-01
The Omega spectrometer which came into action during the year. An array of optical spark chambers can be seen withdrawn from the magnet aperture. In the 'igloo' above the magnet is located the Plumbicon camera system which collects information from the spark chambers.
Applied probability models with optimization applications
Ross, Sheldon M
1992-01-01
Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.
Extracting the Omega- electric quadrupole moment from lattice QCD data
Energy Technology Data Exchange (ETDEWEB)
G. Ramalho, M.T. Pena
2011-03-01
The Omega- has an extremely long lifetime, and is the most stable of the baryons with spin 3/2. Therefore the Omega- magnetic moment is very accurately known. Nevertheless, its electric quadrupole moment was never measured, although estimates exist in different formalisms. In principle, lattice QCD simulations provide at present the most appropriate way to estimate the Omega- form factors, as function of the square of the transferred four-momentum, Q2, since it describes baryon systems at the physical mass for the strange quark. However, lattice QCD form factors, and in particular GE2, are determined at finite Q2 only, and the extraction of the electric quadrupole moment, Q_Omega= GE2(0) e/(2 M_Omega), involves an extrapolation of the numerical lattice results. In this work we reproduce the lattice QCD data with a covariant spectator quark model for Omega- which includes a mixture of S and two D states for the relative quark-diquark motion. Once the model is calibrated, it is used to determine Q_Omega. Our prediction is Q_Omega= (0.96 +/- 0.02)*10^(-2) efm2 [GE2(0)=0.680 +/- 0.012].
Marsman, H. A.; de Graaf, W.; Heger, M.; van Golen, R. F.; ten Kate, F. J. W.; Bennink, R.; van Gulik, T. M.
2013-01-01
Omega-3 fatty acids (FAs) have been shown to reduce experimental hepatic steatosis and protect the liver from ischaemia-reperfusion injury. The aim of this study was to examine the effects of omega-3 FAs on regeneration of steatotic liver. Steatosis was induced in rats by a 3-week
Model averaging, optimal inference and habit formation
Directory of Open Access Journals (Sweden)
Thomas H B FitzGerald
2014-06-01
Full Text Available Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function – the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an additional challenge – that of determining which model or models of their environment are the best for guiding behaviour. Bayesian model averaging – which says that an agent should weight the predictions of different models according to their evidence – provides a principled way to solve this problem. Importantly, because model evidence is determined by both the accuracy and complexity of the model, optimal inference requires that these be traded off against one another. This means an agent’s behaviour should show an equivalent balance. We hypothesise that Bayesian model averaging plays an important role in cognition, given that it is both optimal and realisable within a plausible neuronal architecture. We outline model averaging and how it might be implemented, and then explore a number of implications for brain and behaviour. In particular, we propose that model averaging can explain a number of apparently suboptimal phenomena within the framework of approximate (bounded Bayesian inference, focussing particularly upon the relationship between goal-directed and habitual behaviour.
Procedural Optimization Models for Multiobjective Flexible JSSP
Directory of Open Access Journals (Sweden)
Elena Simona NICOARA
2013-01-01
Full Text Available The most challenging issues related to manufacturing efficiency occur if the jobs to be sched-uled are structurally different, if these jobs allow flexible routings on the equipments and mul-tiple objectives are required. This framework, called Multi-objective Flexible Job Shop Scheduling Problems (MOFJSSP, applicable to many real processes, has been less reported in the literature than the JSSP framework, which has been extensively formalized, modeled and analyzed from many perspectives. The MOFJSSP lie, as many other NP-hard problems, in a tedious place where the vast optimization theory meets the real world context. The paper brings to discussion the most optimization models suited to MOFJSSP and analyzes in detail the genetic algorithms and agent-based models as the most appropriate procedural models.
Computer models for optimizing radiation therapy
International Nuclear Information System (INIS)
Duechting, W.
1998-01-01
The aim of this contribution is to outline how methods of system analysis, control therapy and modelling can be applied to simulate normal and malignant cell growth and to optimize cancer treatment as for instance radiation therapy. Based on biological observations and cell kinetic data, several types of models have been developed describing the growth of tumor spheroids and the cell renewal of normal tissue. The irradiation model is represented by the so-called linear-quadratic model describing the survival fraction as a function of the dose. Based thereon, numerous simulation runs for different treatment schemes can be performed. Thus, it is possible to study the radiation effect on tumor and normal tissue separately. Finally, this method enables a computer-assisted recommendation for an optimal patient-specific treatment schedule prior to clinical therapy. (orig.) [de
An optimization model for metabolic pathways.
Planes, F J; Beasley, J E
2009-10-15
Different mathematical methods have emerged in the post-genomic era to determine metabolic pathways. These methods can be divided into stoichiometric methods and path finding methods. In this paper we detail a novel optimization model, based upon integer linear programming, to determine metabolic pathways. Our model links reaction stoichiometry with path finding in a single approach. We test the ability of our model to determine 40 annotated Escherichia coli metabolic pathways. We show that our model is able to determine 36 of these 40 pathways in a computationally effective manner.
Optimization and mathematical modeling in computer architecture
Sankaralingam, Karu; Nowatzki, Tony
2013-01-01
In this book we give an overview of modeling techniques used to describe computer systems to mathematical optimization tools. We give a brief introduction to various classes of mathematical optimization frameworks with special focus on mixed integer linear programming which provides a good balance between solver time and expressiveness. We present four detailed case studies -- instruction set customization, data center resource management, spatial architecture scheduling, and resource allocation in tiled architectures -- showing how MILP can be used and quantifying by how much it outperforms t
Optimizing refiner operation with statistical modelling
Energy Technology Data Exchange (ETDEWEB)
Broderick, G [Noranda Research Centre, Pointe Claire, PQ (Canada)
1997-02-01
The impact of refining conditions on the energy efficiency of the process and on the handsheet quality of a chemi-mechanical pulp was studied as part of a series of pilot scale refining trials. Statistical models of refiner performance were constructed from these results and non-linear optimization of process conditions were conducted. Optimization results indicated that increasing the ratio of specific energy applied in the first stage led to a reduction of some 15 per cent in the total energy requirement. The strategy can also be used to obtain significant increases in pulp quality for a given energy input. 20 refs., 6 tabs.
A study on an optimal movement model
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [COGS, Sussex University, Brighton BN1 9QH, UK (United Kingdom); Zhang, Kewei [SMS, Sussex University, Brighton BN1 9QH (United Kingdom); Luo Yousong [Department of Mathematics and Statistics, RMIT University, GOP Box 2476V, Melbourne, Vic 3001 (Australia)
2003-07-11
We present an analytical and rigorous study on a TOPS (task optimization in the presence of signal-dependent noise) model with a hold-on or an end-point control. Optimal control signals are rigorously obtained, which enables us to investigate various issues about the model including its trajectories, velocities, control signals, variances and the dependence of these quantities on various model parameters. With the hold-on control, we find that the optimal control can be implemented with an almost 'nil' hold-on period. The optimal control signal is a linear combination of two sub-control signals. One of the sub-control signals is positive and the other is negative. With the end-point control, the end-point variance is dramatically reduced, in comparison with the hold-on control. However, the velocity is not symmetric (bell shape). Finally, we point out that the velocity with a hold-on control takes the bell shape only within a limited parameter region.
Aerodynamic modelling and optimization of axial fans
Energy Technology Data Exchange (ETDEWEB)
Noertoft Soerensen, Dan
1998-01-01
A numerically efficient mathematical model for the aerodynamics of low speed axial fans of the arbitrary vortex flow type has been developed. The model is based on a blade-element principle, whereby the rotor is divided into a number of annular stream tubes. For each of these stream tubes relations for velocity, pressure and radial position are derived from the conservation laws for mass, tangential momentum and energy. The equations are solved using the Newton-Raphson methods, and solutions converged to machine accuracy are found at small computing costs. The model has been validated against published measurements on various fan configurations, comprising two rotor-only fan stages, a counter-rotating fan unit and a stator-rotor stator stage. Comparisons of local and integrated properties show that the computed results agree well with the measurements. Optimizations have been performed to maximize the mean value of fan efficiency in a design interval of flow rates, thus designing a fan which operates well over a range of different flow conditions. The optimization scheme was used to investigate the dependence of maximum efficiency on 1: the number of blades, 2: the width of the design interval and 3: the hub radius. The degree of freedom in the choice of design variable and constraints, combined with the design interval concept, provides a valuable design-tool for axial fans. To further investigate the use of design optimization, a model for the vortex shedding noise from the trailing edge of the blades has been incorporated into the optimization scheme. The noise emission from the blades was minimized in a flow rate design point. Optimizations were performed to investigate the dependence of the noise on 1: the number of blades, 2: a constraint imposed on efficiency and 3: the hub radius. The investigations showed, that a significant reduction of noise could be achieved, at the expense of a small reduction in fan efficiency. (EG) 66 refs.
MARKOV CHAIN PORTFOLIO LIQUIDITY OPTIMIZATION MODEL
Directory of Open Access Journals (Sweden)
Eder Oliveira Abensur
2014-05-01
Full Text Available The international financial crisis of September 2008 and May 2010 showed the importance of liquidity as an attribute to be considered in portfolio decisions. This study proposes an optimization model based on available public data, using Markov chain and Genetic Algorithms concepts as it considers the classic duality of risk versus return and incorporating liquidity costs. The work intends to propose a multi-criterion non-linear optimization model using liquidity based on a Markov chain. The non-linear model was tested using Genetic Algorithms with twenty five Brazilian stocks from 2007 to 2009. The results suggest that this is an innovative development methodology and useful for developing an efficient and realistic financial portfolio, as it considers many attributes such as risk, return and liquidity.
Efficient Iris Localization via Optimization Model
Directory of Open Access Journals (Sweden)
Qi Wang
2017-01-01
Full Text Available Iris localization is one of the most important processes in iris recognition. Because of different kinds of noises in iris image, the localization result may be wrong. Besides this, localization process is time-consuming. To solve these problems, this paper develops an efficient iris localization algorithm via optimization model. Firstly, the localization problem is modeled by an optimization model. Then SIFT feature is selected to represent the characteristic information of iris outer boundary and eyelid for localization. And SDM (Supervised Descent Method algorithm is employed to solve the final points of outer boundary and eyelids. Finally, IRLS (Iterative Reweighted Least-Square is used to obtain the parameters of outer boundary and upper and lower eyelids. Experimental result indicates that the proposed algorithm is efficient and effective.
Global Optimization Ensemble Model for Classification Methods
Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab
2014-01-01
Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382
Global Optimization Ensemble Model for Classification Methods
Directory of Open Access Journals (Sweden)
Hina Anwar
2014-01-01
Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.
Identifying optimal models to represent biochemical systems.
Directory of Open Access Journals (Sweden)
Mochamad Apri
Full Text Available Biochemical systems involving a high number of components with intricate interactions often lead to complex models containing a large number of parameters. Although a large model could describe in detail the mechanisms that underlie the system, its very large size may hinder us in understanding the key elements of the system. Also in terms of parameter identification, large models are often problematic. Therefore, a reduced model may be preferred to represent the system. Yet, in order to efficaciously replace the large model, the reduced model should have the same ability as the large model to produce reliable predictions for a broad set of testable experimental conditions. We present a novel method to extract an "optimal" reduced model from a large model to represent biochemical systems by combining a reduction method and a model discrimination method. The former assures that the reduced model contains only those components that are important to produce the dynamics observed in given experiments, whereas the latter ensures that the reduced model gives a good prediction for any feasible experimental conditions that are relevant to answer questions at hand. These two techniques are applied iteratively. The method reveals the biological core of a model mathematically, indicating the processes that are likely to be responsible for certain behavior. We demonstrate the algorithm on two realistic model examples. We show that in both cases the core is substantially smaller than the full model.
Modeling and optimization of potable water network
Energy Technology Data Exchange (ETDEWEB)
Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)
2000-07-01
Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.
Computer modeling for optimal placement of gloveboxes
Energy Technology Data Exchange (ETDEWEB)
Hench, K.W.; Olivas, J.D. [Los Alamos National Lab., NM (United States); Finch, P.R. [New Mexico State Univ., Las Cruces, NM (United States)
1997-08-01
Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components (pits) in an environment of intense regulation and shrinking budgets. Historically, the location of gloveboxes in a processing area has been determined without benefit of industrial engineering studies to ascertain the optimal arrangement. The opportunity exists for substantial cost savings and increased process efficiency through careful study and optimization of the proposed layout by constructing a computer model of the fabrication process. This paper presents an integrative two- stage approach to modeling the casting operation for pit fabrication. The first stage uses a mathematical technique for the formulation of the facility layout problem; the solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a computer simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.
Computer modeling for optimal placement of gloveboxes
International Nuclear Information System (INIS)
Hench, K.W.; Olivas, J.D.; Finch, P.R.
1997-08-01
Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components (pits) in an environment of intense regulation and shrinking budgets. Historically, the location of gloveboxes in a processing area has been determined without benefit of industrial engineering studies to ascertain the optimal arrangement. The opportunity exists for substantial cost savings and increased process efficiency through careful study and optimization of the proposed layout by constructing a computer model of the fabrication process. This paper presents an integrative two- stage approach to modeling the casting operation for pit fabrication. The first stage uses a mathematical technique for the formulation of the facility layout problem; the solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a computer simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units
Directory of Open Access Journals (Sweden)
Al-Okbi, S. Y.
2015-12-01
Full Text Available In the present study, the hepato and reno-protective effect of Nigella sativa crude oil and its binary blend with omega-3 fatty acid-rich oils (fish and flaxseed oils was studied in a modified hepatorenal syndrome model (MHRS in rats. MHRS was induced through feeding a high fructose diet followed by an intraperitoneal injection of galactosamine hydrochloride. Nigella oil and its different blends were given as a daily oral dose to MHRS rats. Two control groups of MHRS and normal healthy rats were run. Different biochemical and nutritional parameters were assessed. The induction of MHRS produced liver and kidney dysfunction, and elevated oxidative stress, an inflammatory biomarker, endothelin 1, and plasma cholesterol. Reduced plasma high density lipoprotein cholesterol, albumin and Ca and elevated urinary N-acetyl-β-D-Glucosaminidase and liver fats were noticed. The administration of Nigella crude oil that originally had 0.2% total omega-3 fatty acids or its blend with fish oil (17.9% omega-3 or flaxseed oil (42.1% omega-3 significantly improved all biochemical parameters of MHRS. There was no significant difference in the biochemical parameters among the different oil treated groups regardless of the omega-3 fatty acid content. This may point out to the potential profound effect of the volatile oil fraction of Nigella crude oil which may compensates for its low omega-3 content.En el presente estudio, el efecto hepato- y reno-protector de aceites crudos de Nigella sativa y su mezcla binaria con aceites ricos en ácidos grasos omega-3 (pescado y aceites de linaza fue estudiado en un modelo modificado de síndrome hepatorenal (MHRS en ratas. MHRS fue inducido a través de la alimentación de una dieta alta en fructosa seguido de la inyección intraperitoneal de clorhidrato de galactosamina. Diferentes aceites fueron suministrados como dosis oral diaria a ratas con MHRS. Se realizaron dos grupos de control de MHRS y ratas sanas normales. Se
Behavioral optimization models for multicriteria portfolio selection
Directory of Open Access Journals (Sweden)
Mehlawat Mukesh Kumar
2013-01-01
Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.
International Nuclear Information System (INIS)
1984-01-01
The Adam Smith Institute's Omega Project was conceived to fill a significant gap in the field of public policy research. Administrations entering office in democratic societies are often aware of the problems which they face, but lack a well-developed range of policy options. The Omega Project was designed to create and develop new policy initiatives, to research and analyze these new ideas, and to bring them forward for public discussion in ways which overcame the conventional shortcomings. The organization of the Project is described. The results are presented in sections entitled: energy supplies and policy; the gas industry; North Sea oil; the coal industry; the electricity industry; nuclear energy; renewable and alternative fuel sources; energy conservation. (U.K.)
DEFF Research Database (Denmark)
Lunde, Anita; Sørensen, Jan
2009-01-01
Rapport afgrænser sig til evidensbaserede helbredsmæssige gevinster ved et øget indtag af langkædede omega-3, som opnås ved en kost rig på fisk eller som et tilskud af fiskeolier. Der gennemføres en systematisk litteraturgennemgang, som baserer sig på et evidensniveau svarende til styrke A. Det...... betyder, at gennemgangen inkluderer metaanalyser/oversigtsartikler af enten eksperimentelle studier eller observationsstudier, endvidere indgår udvalgte større RCT, som er refereret i meta-analyserne. Sammenfattende findes på baggrund af litteraturgennemgang, at tilskud af omega-3 har effekt på...... hjertesygdom ved at nedsætte mortaliteten. Effekten er mest evident ved personer i særlig risiko for at udvikle hjerte-karsygdom, eller som sekundær/tertiær profylakse. Tilsvarende findes også ved tilskud af omega-3 en forebyggende effekt i forhold til iskæmisk apopleksi. Af mulige virkningsmekanismer viser...
Sýkora, Michal; Jedlinský, Petr; Komanec, Jan
2017-09-01
In the design and construction of precast bridge structures, a general goal is to achieve the maximum possible span length. Often, the weight of individual beams makes them difficult to handle, which may be a limiting factor in achieving the desired span. The design of the OMEGA beam aims to solve a part of these problems. It is a thin-walled shell made of prestressed high-performance concrete (HPC) in the shape of inverted Ω character. The concrete shell with prestressed strands is fitted with a non-stressed tendon already in the casting yard and is more easily transported and installed on the site. The shells are subsequently completed with mild steel reinforcement and cores are cast in situ together with the deck. The OMEGA beams can also be used as an alternative to steel - concrete composite bridges. Due to the higher production complexity, OMEGA beam can hardly substitute conventional prestressed beams like T or PETRA completely, but it can be a useful alternative for specific construction needs.
Optimal transportation networks models and theory
Bernot, Marc; Morel, Jean-Michel
2009-01-01
The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.
Image-Optimized Coronal Magnetic Field Models
Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M.
2017-01-01
We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work we presented early tests of the method which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane, and the effect on the outcome of the optimization of errors in localization of constraints. We find that substantial improvement in the model field can be achieved with this type of constraints, even when magnetic features in the images are located outside of the image plane.
Image-optimized Coronal Magnetic Field Models
Energy Technology Data Exchange (ETDEWEB)
Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M., E-mail: shaela.i.jones-mecholsky@nasa.gov, E-mail: shaela.i.jonesmecholsky@nasa.gov [NASA Goddard Space Flight Center, Code 670, Greenbelt, MD 20771 (United States)
2017-08-01
We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work, we presented early tests of the method, which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper, we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane and the effect on the outcome of the optimization of errors in the localization of constraints. We find that substantial improvement in the model field can be achieved with these types of constraints, even when magnetic features in the images are located outside of the image plane.
PROPERTIES OF THE $omega$ MESON
Energy Technology Data Exchange (ETDEWEB)
Shafer, J. B.; Murray, J. J.; Ferro-Luzzi, M.; Huwe, D. O.
1963-06-15
Properties of the omega meson were studied from the reaction K/sup -/ + p yields LAMBDA + omega in a 72-in. hydrogen bubble chamber. The momentum of the K/sup -/ mesons was 1.2 to 1.75 Bev/c. The mass of the omega meson is found to be 782 Mev with a width, predominated by three-meson( pi ) decay mode, estimated to be less than 4 Mev. Branching ratios for omega -meson decay into pi /sup +/ pi /sup -/ pi /sup o/, pi /sup o/ gamma , pi /sup +/ i/ sup -/, and e/sup +/e/sup -o/ were determined. (R.E.U.)
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Optimization of hybrid model on hajj travel
Cahyandari, R.; Ariany, R. L.; Sukono
2018-03-01
Hajj travel insurance is an insurance product offered by the insurance company in preparing funds to perform the pilgrimage. This insurance product helps would-be pilgrims to set aside a fund of saving hajj with regularly, but also provides funds of profit sharing (mudharabah) and insurance protection. Scheme of insurance product fund management is largely using the hybrid model, which is the fund from would-be pilgrims will be divided into three account management, that is personal account, tabarru’, and ujrah. Scheme of hybrid model on hajj travel insurance was already discussed at the earlier paper with titled “The Hybrid Model Algorithm on Sharia Insurance”, taking the example case of Mitra Mabrur Plus product from Bumiputera company. On these advanced paper, will be made the previous optimization model design, with partition of benefit the tabarru’ account. Benefits such as compensation for 40 critical illness which initially only for participants of insurance only, on optimization is intended for participants of the insurance and his heir, also to benefit the hospital bills. Meanwhile, the benefits of death benefit is given if the participant is fixed die.
Utama, D. N.; Ani, N.; Iqbal, M. M.
2018-03-01
Optimization is a process for finding parameter (parameters) that is (are) able to deliver an optimal value for an objective function. Seeking an optimal generic model for optimizing is a computer science study that has been being practically conducted by numerous researchers. Generic model is a model that can be technically operated to solve any varieties of optimization problem. By using an object-oriented method, the generic model for optimizing was constructed. Moreover, two types of optimization method, simulated-annealing and hill-climbing, were functioned in constructing the model and compared to find the most optimal one then. The result said that both methods gave the same result for a value of objective function and the hill-climbing based model consumed the shortest running time.
Business model optimization of Prego Gourmet
Salema, José Frederico Bettencourt
2013-01-01
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics Prego Gourmet is a fast food restaurant which sells refined versions of a traditional Portuguese dish inside shopping centers in the area of Lisbon. The company is at the beginning of its expansion strategy. This work project is a prospective analysis on what the company should do to in order to optimize its business model and grow in Portug...
CERN PhotoLab
1974-01-01
The huge superconducting magnet (3 m inside coil diameter, 2 m gap, 18 kGauss) contains a large number of optical spark chambers partly surrounding a hydrogen target which is hit by the beam entering from behind. The half cylindrical aluminium hut houses eight television cameras viewing the spark chambers from the top. The big gas Cerenkov counter in front of the picture (6 m x 4 m x 3 m) which identifies fast forward particles was constructed at Saclay as a contribution of one of the Omega.
Smit, EN; Martini, IA; Woltil, HA; Boersma, ER; Muskiet, FAJ
2002-01-01
Background. Early suspicion of essential fatty acid deficiency (EFAD) or omega3-deficiency may rather focus on polyunsaturated fatty acid (PUFA) or long-chain PUFA (LCP) analyses than clinical symptoms. We determined cut-off values for biochemical EFAD, omega3-and omega3/22:6omega3 [docosahexaenoic
Smit, EN; Martini, IA; Woltil, HA; Boersma, ER; Muskiet, FAJ
Background. Early suspicion of essential fatty acid deficiency (EFAD) or omega3-deficiency may rather focus on polyunsaturated fatty acid (PUFA) or long-chain PUFA (LCP) analyses than clinical symptoms. We determined cut-off values for biochemical EFAD, omega3-and omega3/22:6omega3 [docosahexaenoic
Optimal evolution models for quantum tomography
International Nuclear Information System (INIS)
Czerwiński, Artur
2016-01-01
The research presented in this article concerns the stroboscopic approach to quantum tomography, which is an area of science where quantum physics and linear algebra overlap. In this article we introduce the algebraic structure of the parametric-dependent quantum channels for 2-level and 3-level systems such that the generator of evolution corresponding with the Kraus operators has no degenerate eigenvalues. In such cases the index of cyclicity of the generator is equal to 1, which physically means that there exists one observable the measurement of which performed a sufficient number of times at distinct instants provides enough data to reconstruct the initial density matrix and, consequently, the trajectory of the state. The necessary conditions for the parameters and relations between them are introduced. The results presented in this paper seem to have considerable potential applications in experiments due to the fact that one can perform quantum tomography by conducting only one kind of measurement. Therefore, the analyzed evolution models can be considered optimal in the context of quantum tomography. Finally, we introduce some remarks concerning optimal evolution models in the case of n-dimensional Hilbert space. (paper)
Energy Technology Data Exchange (ETDEWEB)
Kristofova, Kristina; Daniska, Vladimir; Ondra, Frantisek; Rehak, Ivan; Vasko, Marek [DECOM SLOVAKIA spol. s.r.o., Trnava (Slovakia)
2004-12-01
The presented study is focused on model decommissioning cost calculations for primary circuit of A-1 nuclear power plant in Jaslovske Bohunice. In addition, the survey of advanced decommissioning costing is included together with impact analyses of contamination on particular decommissioning parameters. OMEGA code decommissioning cost calculations for primary circuit of A-1 NPP presented in the study are performed and evaluated under the following conditions: different contamination level of inner and outer surfaces; different waste management scenarios; application and non-application of pre-dismantling decontamination; different start of decommissioning: 2004, 2010, 2020, 2030, 2040; radionuclide composition of primary circuit contamination in A-1 NPP with occurrence of alpha radionuclides and fission products as a consequence of operational accident with damaged fuel cladding; radionuclide composition of primary circuit contamination in V-2 NPP in Jaslovske Bohunice as a representative NPP with an operation without accidents and therefore neither non-alpha contaminants nor fission products are included. The results of all the above mentioned conditions impacts on calculated costs, manpower, exposure and distribution of materials arisen from decommissioning are evaluated in detail within the calculation sensitivity analysis.
International Nuclear Information System (INIS)
Kristofova, Kristina; Daniska, Vladimir; Ondra, Frantisek; Rehak, Ivan; Vasko, Marek
2004-12-01
The presented study is focused on model decommissioning cost calculations for primary circuit of A-1 nuclear power plant in Jaslovske Bohunice. In addition, the survey of advanced decommissioning costing is included together with impact analyses of contamination on particular decommissioning parameters. OMEGA code decommissioning cost calculations for primary circuit of A-1 NPP presented in the study are performed and evaluated under the following conditions: different contamination level of inner and outer surfaces; different waste management scenarios; application and non-application of pre-dismantling decontamination; different start of decommissioning: 2004, 2010, 2020, 2030, 2040; radionuclide composition of primary circuit contamination in A-1 NPP with occurrence of alpha radionuclides and fission products as a consequence of operational accident with damaged fuel cladding; radionuclide composition of primary circuit contamination in V-2 NPP in Jaslovske Bohunice as a representative NPP with an operation without accidents and therefore neither non-alpha contaminants nor fission products are included. The results of all the above mentioned conditions impacts on calculated costs, manpower, exposure and distribution of materials arisen from decommissioning are evaluated in detail within the calculation sensitivity analysis
International Nuclear Information System (INIS)
Umezawa, Hirokazu
1989-01-01
Attention has been paid to the research and development on the group partition and annihilation disposal technology which separates long life radioactive nuclides, rare stable nuclides and so on in high level radioactive wastes and utilizes those for respective suitable uses, or which searches for the possibility of promoting the nuclear disintegration of long life radioactive nuclides, as the basic research aiming at the further development of atomic energy. It was named 'OMEGA project' and its promotion has been carried out. The outline of the project and the international circumstances surrounding it are described. In the high level radioactive wastes generated from the reprocessing of spent nuclear fuel, the alpha and beta-gamma radionuclides having long life are contained. Consequently, it is necessary to isolate them from human environment for very long period, and the basic method is the glass solidification and the disposal in deep strata, therefore the technical development has been advanced. The OMEGA project was decided in October, 1988, and the course of the research carried out so far, the international cooperation and the subjects of research and development are reported. (K.I.)
Process optimization of friction stir welding based on thermal models
DEFF Research Database (Denmark)
Larsen, Anders Astrup
2010-01-01
This thesis investigates how to apply optimization methods to numerical models of a friction stir welding process. The work is intended as a proof-of-concept using different methods that are applicable to models of high complexity, possibly with high computational cost, and without the possibility...... information of the high-fidelity model. The optimization schemes are applied to stationary thermal models of differing complexity of the friction stir welding process. The optimization problems considered are based on optimizing the temperature field in the workpiece by finding optimal translational speed....... Also an optimization problem based on a microstructure model is solved, allowing the hardness distribution in the plate to be optimized. The use of purely thermal models represents a simplification of the real process; nonetheless, it shows the applicability of the optimization methods considered...
Modeling, Analysis, and Optimization Issues for Large Space Structures
Pinson, L. D. (Compiler); Amos, A. K. (Compiler); Venkayya, V. B. (Compiler)
1983-01-01
Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design.
Dynamical coupled channel approach to omega meson production
Energy Technology Data Exchange (ETDEWEB)
Mark Paris
2007-09-10
The dynamical coupled channel approach of Matsuyama, Sato, and Lee is used to study the $\\omega$--meson production induced by pions and photons scattering from the proton. The parameters of the model are fixed in a two-channel (\\omega N,\\pi N) calculation for the non-resonant and resonant contributions to the $T$ matrix by fitting the available unpolarized differential cross section data. The polarized photon beam asymmetry is predicted and compared to existing data.
da Rocha, Camilla M M; Kac, Gilberto
2012-01-01
Observational studies suggest association between low concentrations of omega-3 family fatty acids and greater risk for post-partum depression (PPD). The objective was to investigate the effect of unbalanced dietary intake of omega-6/omega-3 ratio >9:1 in the prevalence for PPD. The study comprises a prospective cohort with four waves of follow-up during pregnancy and one following delivery. PPD was evaluated according to the Edinburgh Post-partum Depression Scale (PPD ≥ 11) in 106 puerperae between 2005 and 2007, in Rio de Janeiro, Brazil. Independent variables included socio-demographic, obstetric, pre-pregnancy body mass index (BMI) and dietary intake data, which were obtained by means of a food frequency questionnaire in the first trimester of pregnancy. Statistical analysis involved calculation of PPD prevalence and multivariate Poisson regression with robust variance. PPD prevalence amounted to 26.4% [n = 28; confidence interval (CI) 95%: 18.0-34.8], and higher prevalences of PPD were observed in women who consumed an omega-6/omega-3 ratio >9:1 (60.0%) and in those with pre-pregnancy BMI <18.5 kg/m(2) (66.7%). These variables held as factors associated to PPD in the multivariate model, elevating the chances of occurrence of the outcome in 2.50 (CI 95%: 1.21-5.14) and 4.01 times (CI 95%: 1.96-8.20), respectively. Analyses were adjusted for age, schooling, pre-pregnancy BMI, lipids consumption and time elapsed since delivery. It verified an association between omega-6/omega-3 ratio above 9:1, the levels recommended by the Institute of Medicine, and the prevalence of PPD. These results add to the evidence regarding the importance of omega-6 and omega-3 fatty acids in the regulation of mental health mechanisms. © 2010 Blackwell Publishing Ltd.
Modeling and optimization of planar microcoils
International Nuclear Information System (INIS)
Beyzavi, Ali; Nguyen, Nam-Trung
2008-01-01
Magnetic actuation has emerged as a useful tool for manipulating particles, droplets and biological samples in microfluidics. A planar coil is one of the suitable candidates for magnetic actuation and has the potential to be integrated in digital microfluidic devices. A simple model of microcoils is needed to optimize their use in actuation applications. This paper first develops an analytical model for calculating the magnetic field of a planar microcoil. The model was validated by experimental data from microcoils fabricated on printed circuit boards (PCB). The model was used for calculating the field strength and the force acting on a magnetic object. Finally, the effect of different coil parameters such as the magnitude of the electric current, the gap between the wires and the number of wire segments is discussed. Both analytical and experimental results show that a smaller gap size between wire segments, more wire segments and a higher electric current can increase both the magnitude and the gradient of the magnetic field, and consequently cause a higher actuating force. The planar coil analyzed in the paper is suitable for applications in magnetic droplet-based microfluidics
Multiobjective Optimization Model for Wind Power Allocation
Directory of Open Access Journals (Sweden)
Juan Alemany
2017-01-01
Full Text Available There is an increasing need for the injection to the grid of renewable energy; therefore, to evaluate the optimal location of new renewable generation is an important task. The primary purpose of this work is to develop a multiobjective optimization model that permits finding multiple trade-off solutions for the location of new wind power resources. It is based on the augmented ε-constrained methodology. Two competitive objectives are considered: maximization of preexisting energy injection and maximization of new wind energy injection, both embedded, in the maximization of load supply. The results show that the location of new renewable generation units affects considerably the transmission network flows, the load supply, and the preexisting energy injection. Moreover, there are diverse opportunities to benefit the preexisting generation, contrarily to the expected effect where renewable generation displaces conventional power. The proposed methodology produces a diverse range of equivalent solutions, expanding and enriching the horizon of options and giving flexibility to the decision-making process.
Code Differentiation for Hydrodynamic Model Optimization
Energy Technology Data Exchange (ETDEWEB)
Henninger, R.J.; Maudlin, P.J.
1999-06-27
Use of a hydrodynamics code for experimental data fitting purposes (an optimization problem) requires information about how a computed result changes when the model parameters change. These so-called sensitivities provide the gradient that determines the search direction for modifying the parameters to find an optimal result. Here, the authors apply code-based automatic differentiation (AD) techniques applied in the forward and adjoint modes to two problems with 12 parameters to obtain these gradients and compare the computational efficiency and accuracy of the various methods. They fit the pressure trace from a one-dimensional flyer-plate experiment and examine the accuracy for a two-dimensional jet-formation problem. For the flyer-plate experiment, the adjoint mode requires similar or less computer time than the forward methods. Additional parameters will not change the adjoint mode run time appreciably, which is a distinct advantage for this method. Obtaining ''accurate'' sensitivities for the j et problem parameters remains problematic.
Kanban simulation model for production process optimization
Directory of Open Access Journals (Sweden)
Golchev Riste
2015-01-01
Full Text Available A long time has passed since the KANBAN system has been established as an efficient method for coping with the excessive inventory. Still, the possibilities for its improvement through its integration with other different approaches should be investigated further. The basic research challenge of this paper is to present benefits of KANBAN implementation supported with Discrete Event Simulation (DES. In that direction, at the beginning, the basics of KANBAN system are presented with emphasis on the information and material flow, together with a methodology for implementation of KANBAN system. Certain analysis on combining the simulation with this methodology is presented. The paper is concluded with a practical example which shows that through understanding the philosophy of the implementation methodology of KANBAN system and the simulation methodology, a simulation model can be created which can serve as a basis for a variety of experiments that can be conducted within a short period of time, resulting with production process optimization.
Balancing omega-6 and omega-3 fatty acids in ready-to-use therapeutic foods (RUTF)
DEFF Research Database (Denmark)
Brenna, J Thomas; Akomo, Peter; Bahwere, Paluku
2015-01-01
with altered PUFA content and looked at the effects on circulating omega-3 docosahexaenoic acid (DHA) status as a measure of overall omega-3 status. Supplemental oral administration of omega-3 DHA or reduction of RUTF omega-6 linoleic acid using high oleic peanuts improved DHA status, whereas increasing omega...
Modeling and Optimizing Antennas for Rotational Spectroscopy Applications
Directory of Open Access Journals (Sweden)
Z. Raida
2006-12-01
Full Text Available In the paper, dielectric and metallic lenses are modeled and optimized in order to enhance the gain of a horn antenna in the frequency range from 60 GHz to 100 GHz. Properties of designed lenses are compared and discussed. The structures are modeled in CST Microwave Studio and optimized by Particle Swarm Optimization (PSO in order to get required antenna parameters.
Modeling and optimization of wet sizing process
International Nuclear Information System (INIS)
Thai Ba Cau; Vu Thanh Quang and Nguyen Ba Tien
2004-01-01
Mathematical simulation on basis of Stock law has been done for wet sizing process on cylinder equipment of laboratory and semi-industrial scale. The model consists of mathematical equations describing relations between variables, such as: - Resident time distribution function of emulsion particles in the separating zone of the equipment depending on flow-rate, height, diameter and structure of the equipment. - Size-distribution function in the fine and coarse parts depending on resident time distribution function of emulsion particles, characteristics of the material being processed, such as specific density, shapes, and characteristics of the environment of classification, such as specific density, viscosity. - Experimental model was developed on data collected from an experimental cylindrical equipment with diameter x height of sedimentation chamber equal to 50 x 40 cm for an emulsion of zirconium silicate in water. - Using this experimental model allows to determine optimal flow-rate in order to obtain product with desired grain size in term of average size or size distribution function. (author)
Teo, Lynn; Crawford, Cindy; Yehuda, Rachel; Jaghab, Danny; Bingham, John J; Chittum, Holly K; Gallon, Matthew D; O'Connell, Meghan L; Arzola, Sonya M; Berry, Kevin
2017-06-01
There has been interest in identifying whether nutrients might help optimize cognitive performance, especially for the military tasked with ensuring mission-readiness. This systematic review assesses the quality of the evidence for n-3 polyunsaturated fatty acids (PUFAs) across various outcomes related to cognitive function in healthy adult populations in order to develop research recommendations concerning n-3 PUFAs for mission-readiness. PubMed, CINAHL, Embase, PsycInfo, and the Cochrane Library were searched. Peer-reviewed randomized controlled trials published in the English language were eligible. Thirteen included trials were assessed for methodological quality, and descriptive data were extracted. Of the acceptable-quality (n = 8) and high-quality (n = 1) studies, 2 produced no statistically significant results, 5 produced mixed results, and 2 did not report between-group results. Results indicate that ingestion of n-3 PUFAs does not significantly alter cognitive performance in cognitively healthy persons. Studies exposing subjects to adverse circumstances that would be most relevant for drawing conclusions specifically for the military population are lacking. Several research recommendations are offered to enhance understanding of the role of fatty acids on cognitive functioning. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Tetrahedral hohlraums at omega
International Nuclear Information System (INIS)
Kyrala, G.A.; Goldman, S.R.; Batha, S.H.; Wallace, J.M.; Klare, K.A.; Schappert, G.T.; Oertel, J.; Turner, R.E.
2000-01-01
We have initiated a study of the usefulness of tetrahedrally illuminated spherical hohlraums, using the Omega laser beams, to drive planar shocks in packages that require indirect drive. A first suite of experiments used spherical hohlraums with a 2-μm thick gold wall surrounded by a 100-μm thick epoxy layer and had an internal diameter of 2.8 mm. Four laser entrance holes each of diameter 700 μm, located on the tips of a regular tetrahedron were used. The shock velocities and the shock uniformities were measured using optical shock break out techniques. The hohlraum x-ray radiation spectrum was also measured using a 10-channel x-ray detector. Tentatively, peak temperatures approaching 195 eV were achieved and shock speeds of 60 μm/ns were measured, when the hohlraum was driven by 22 kJ of 3 ω radiation. (authors)
Ground Vehicle System Integration (GVSI) and Design Optimization Model
National Research Council Canada - National Science Library
Horton, William
1996-01-01
This report documents the Ground Vehicle System Integration (GVSI) and Design Optimization Model GVSI is a top-level analysis tool designed to support engineering tradeoff studies and vehicle design optimization efforts...
Directory of Open Access Journals (Sweden)
Dervola Kine S
2012-12-01
Full Text Available Abstract Background Previous reports suggest that omega-3 (n-3 polyunsaturated fatty acids (PUFA supplements may reduce ADHD-like behaviour. Our aim was to investigate potential effects of n-3 PUFA supplementation in an animal model of ADHD. Methods We used spontaneously hypertensive rats (SHR. SHR dams were given n-3 PUFA (EPA and DHA-enriched feed (n-6/n-3 of 1:2.7 during pregnancy, with their offspring continuing on this diet until sacrificed. The SHR controls and Wistar Kyoto (WKY control rats were given control-feed (n-6/n-3 of 7:1. During postnatal days (PND 25–50, offspring were tested for reinforcement-dependent attention, impulsivity and hyperactivity as well as spontaneous locomotion. The animals were then sacrificed at PND 55–60 and their neostriata were analysed for monoamine and amino acid neurotransmitters with high performance liquid chromatography. Results n-3 PUFA supplementation significantly enhanced reinforcement-controlled attention and reduced lever-directed hyperactivity and impulsiveness in SHR males whereas the opposite or no effects were observed in females. Analysis of neostriata from the same animals showed significantly enhanced dopamine and serotonin turnover ratios in the male SHRs, whereas female SHRs showed no change, except for an intermediate increase in serotonin catabolism. In contrast, both male and female SHRs showed n-3 PUFA-induced reduction in non-reinforced spontaneous locomotion, and sex-independent changes in glycine levels and glutamate turnover. Conclusions Feeding n-3 PUFAs to the ADHD model rats induced sex-specific changes in reinforcement-motivated behaviour and a sex-independent change in non-reinforcement-associated behaviour, which correlated with changes in presynaptic striatal monoamine and amino acid signalling, respectively. Thus, dietary n-3 PUFAs may partly ameliorate ADHD-like behaviour by reinforcement-induced mechanisms in males and partly via reinforcement-insensitive mechanisms
Measurement of the Omega0(c) lifetime
International Nuclear Information System (INIS)
Iori, M.
2007-01-01
The authors report a precise measurement of the (Omega) c 0 lifetime. The data were taken by the SELEX (E781) experiment using 600 GeV/c Σ - , π - and p beams. The measurement has been made using 83 ± 19 reconstructed (Omega) c 0 in the (Omega) - π - π + π + and (Omega) - π + decay modes. The lifetime of the (Omega) c 0 is measured to be 65 ± 13(stat) ± 9(sys) fs
Omega-3 fatty acids upregulate adult neurogenesis
Beltz, Barbara S.; Tlusty, Michael F.; Benton, Jeannie L.; Sandeman, David C.
2007-01-01
Omega-3 fatty acids play crucial roles in the development and function of the central nervous system. These components, which must be obtained from dietary sources, have been implicated in a variety of neurodevelopmental and psychiatric disorders. Furthermore, the presence of omega-6 fatty acids may interfere with omega-3 fatty acid metabolism. The present study investigated whether changes in dietary ratios of omega-3:omega-6 fatty acids influence neurogenesis in the lobster (Homarus america...
An optimization model for improving highway safety
Directory of Open Access Journals (Sweden)
Promothes Saha
2016-12-01
Full Text Available This paper developed a traffic safety management system (TSMS for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors (CRFs associated with safety improvement countermeasures, and average daily traffics (ADTs. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.
Directory of Open Access Journals (Sweden)
Zhang De-Sheng
2015-01-01
Full Text Available The prediction accuracies of partially-averaged Navier-Stokes model and improved shear stress transport k-ω turbulence model for simulating the unsteady cavitating flow around the hydrofoil were discussed in this paper. Numerical results show that the two turbulence models can effectively reproduce the cavitation evolution process. The numerical prediction for the cycle time of cavitation inception, development, detachment, and collapse agrees well with the experimental data. It is found that the vortex pair induced by the interaction between the re-entrant jet and mainstream is responsible for the instability of the cavitation shedding flow.
International Nuclear Information System (INIS)
Carlberg, R.G.
1990-01-01
The redshift dependence of the fraction of galaxies which are merging or strongly interacting is a steep function of Omega and depends on the ratio of the cutoff velocity for interactions to the pairwise velocity dispersion. For typical galaxies the merger rate is shown to vary as (1 + z)exp m, where m is about 4.51 (Omega)exp 0.42, for Omega near 1 and a CDM-like cosmology. The index m has a relatively weak dependence on the maximum merger velocity, the mass of the galaxy, and the background cosmology, for small variations around a cosmology with a low redshift, z of about 2, of galaxy formation. Estimates of m from optical and IRAS galaxies have found that m is about 3-4, but with very large uncertainties. If quasar evolution follows the evolution of galaxy merging and m for quasars is greater than 4, then Omega is greater than 0.8. 21 refs
Cancelier, Kizzy; Gomes, Lara M; Carvalho-Silva, Milena; Teixeira, Letícia J; Rebelo, Joyce; Mota, Isabella T; Arent, Camila O; Mariot, Edemilson; Kist, Luiza W; Bogo, Maurício R; Quevedo, João; Scaini, Giselli; Streck, Emilio L
2017-08-01
Studies have shown that changes in energy metabolism are involved in the pathophysiology of bipolar disorder (BD). It was suggested that omega-3 (ω3) fatty acids have beneficial properties in the central nervous system and that this fatty acid plays an important role in energy metabolism. Therefore, the study aimed to evaluate the effect of ω3 fatty acids alone and in combination with lithium (Li) or valproate (VPA) on behaviour and parameters of energy metabolism in an animal model of mania induced by fenproporex. Our results showed that co-administration of ω3 fatty acids and Li was able to prevent and reverse the increase in locomotor and exploratory activity induced by fenproporex. The combination of ω3 fatty acids with VPA was only able to prevent the fenproporex-induced hyperactivity. For the energy metabolism parameters, our results showed that the administration of Fen for the reversal or prevention protocol inhibited the activities of succinate dehydrogenase, complex II and complex IV in the hippocampus. However, hippocampal creatine kinase (CK) activity was decreased only for the reversal protocol. The ω3 fatty acids, alone and in combination with VPA or Li, prevented and reversed the decrease in complex II, IV and succinate dehydrogenase activity, whereas the decrease in CK activity was only reversed after the co-administration of ω3 fatty acids and VPA. In conclusion, our results showed that the ω3 fatty acids combined with VPA or Li were able to prevent and reverse manic-like hyperactivity and the inhibition of energy metabolism in the hippocampus, suggesting that ω3 fatty acids may play an important role in the modulation of behavioural parameters and energy metabolism.
Patrick, Rhonda P; Ames, Bruce N
2015-06-01
Serotonin regulates a wide variety of brain functions and behaviors. Here, we synthesize previous findings that serotonin regulates executive function, sensory gating, and social behavior and that attention deficit hyperactivity disorder, bipolar disorder, schizophrenia, and impulsive behavior all share in common defects in these functions. It has remained unclear why supplementation with omega-3 fatty acids and vitamin D improve cognitive function and behavior in these brain disorders. Here, we propose mechanisms by which serotonin synthesis, release, and function in the brain are modulated by vitamin D and the 2 marine omega-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Brain serotonin is synthesized from tryptophan by tryptophan hydroxylase 2, which is transcriptionally activated by vitamin D hormone. Inadequate levels of vitamin D (∼70% of the population) and omega-3 fatty acids are common, suggesting that brain serotonin synthesis is not optimal. We propose mechanisms by which EPA increases serotonin release from presynaptic neurons by reducing E2 series prostaglandins and DHA influences serotonin receptor action by increasing cell membrane fluidity in postsynaptic neurons. We propose a model whereby insufficient levels of vitamin D, EPA, or DHA, in combination with genetic factors and at key periods during development, would lead to dysfunctional serotonin activation and function and may be one underlying mechanism that contributes to neuropsychiatric disorders and depression. This model suggests that optimizing vitamin D and marine omega-3 fatty acid intake may help prevent and modulate the severity of brain dysfunction. © FASEB.
Omega-3 Fatty Acids and Skeletal Muscle Health
Directory of Open Access Journals (Sweden)
Stewart Jeromson
2015-11-01
Full Text Available Skeletal muscle is a plastic tissue capable of adapting and mal-adapting to physical activity and diet. The response of skeletal muscle to adaptive stimuli, such as exercise, can be modified by the prior nutritional status of the muscle. The influence of nutrition on skeletal muscle has the potential to substantially impact physical function and whole body metabolism. Animal and cell based models show that omega-3 fatty acids, in particular those of marine origin, can influence skeletal muscle metabolism. Furthermore, recent human studies demonstrate that omega-3 fatty acids of marine origin can influence the exercise and nutritional response of skeletal muscle. These studies show that the prior omega-3 status influences not only the metabolic response of muscle to nutrition, but also the functional response to a period of exercise training. Omega-3 fatty acids of marine origin therefore have the potential to alter the trajectory of a number of human diseases including the physical decline associated with aging. We explore the potential molecular mechanisms by which omega-3 fatty acids may act in skeletal muscle, considering the n-3/n-6 ratio, inflammation and lipidomic remodelling as possible mechanisms of action. Finally, we suggest some avenues for further research to clarify how omega-3 fatty acids may be exerting their biological action in skeletal muscle.
Optimization Models and Methods Developed at the Energy Systems Institute
N.I. Voropai; V.I. Zorkaltsev
2013-01-01
The paper presents shortly some optimization models of energy system operation and expansion that have been created at the Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences. Consideration is given to the optimization models of energy development in Russia, a software package intended for analysis of power system reliability, and model of flow distribution in hydraulic systems. A general idea of the optimization methods developed at the Energy Systems Institute...
Optimality models in the age of experimental evolution and genomics
Bull, J. J.; Wang, I.-N.
2010-01-01
Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimen...
Observation of an Excited Charm Baryon OmegaC* Decaying to OmegaC0 Gamma
The BABAR Collaboration; Aubert, B.
2006-01-01
We report the first observation of an excited singly-charm baryon OmegaC* (css) in the radiative decay OmegaC0 Gamma, where the OmegaC0 baryon is reconstructed in the decays to the final states Omega-pi+, Omega-pi+pi0, Omega-pi+pi-pi+, and Cascade-K-pi+pi+. This analysis is performed using a dataset of 230.7 fb$-1} collected by the BABAR detector at the PEP-II asymmetric-energy B Factory at the Stanford Linear Accelerator Center. The mass difference between the OmegaC* and the OmegaC0 baryons...
Models and Methods for Free Material Optimization
DEFF Research Database (Denmark)
Weldeyesus, Alemseged Gebrehiwot
Free Material Optimization (FMO) is a powerful approach for structural optimization in which the design parametrization allows the entire elastic stiffness tensor to vary freely at each point of the design domain. The only requirement imposed on the stiffness tensor lies on its mild necessary...
Hairy AdS black holes with a toroidal horizon in 4D Einstein-nonlinear omega-model system
Czech Academy of Sciences Publication Activity Database
Astorino, M.; Canfora, F.; Giacomini, A.; Ortaggio, Marcello
2018-01-01
Roč. 776, 10 January (2018), s. 236-241 ISSN 0370-2693 R&D Projects: GA ČR GB14-37086G Institutional support: RVO:67985840 Keywords : AdS black holes * nonlinear sigma model Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 4.807, year: 2016 http://www.sciencedirect.com/science/article/pii/S0370269317309437
Hairy AdS black holes with a toroidal horizon in 4D Einstein-nonlinear omega-model system
Czech Academy of Sciences Publication Activity Database
Astorino, M.; Canfora, F.; Giacomini, A.; Ortaggio, Marcello
2018-01-01
Roč. 776, 10 January (2018), s. 236-241 ISSN 0370-2693 R&D Projects: GA ČR GB14-37086G Institutional support: RVO:67985840 Keywords : AdS black holes * nonlinear sigma model Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 4.807, year: 2016 http://www.sciencedirect.com/science/ article /pii/S0370269317309437
Sheppard, Kelly W; Cheatham, Carol L
2018-03-09
Omega-6 and omega-3 fatty acids (FAs) and their ratio have been shown to affect cognitive function in children and older adults. With these analyses, we aimed to describe omega-6 and omega-3 FA intake among children and older adults in light of FA intake recommendations and with consideration of overall diet. Data were merged from two cross-sectional studies with 219 children 7 to 12 years old and one longitudinal study with 133 adults 65 to 79 years old. Demographic data, anthropometric data, and Healthy Eating Index scores were used to study relations among the omega-6 to omega-3 FA ratio and age, education, body mass index, and diet quality. FA intake, demographic, and anthropometric data were examined using partial correlations, t-tests, and analysis of variance. Most children and adults consumed at least the recommended amount of alpha-linolenic acid (LNA; omega-3) for their age and gender without consuming high amounts of linoleic acid (LA; omega-6), but did not consume sufficient eicosapentaenoic acid (EPA; omega-) and docosahexaenoic acid (DHA; omega-3). The average omega-6 to omega-3 ratios in both groups were lower than previously reported. Eating lower ratios was associated with healthier diets and consuming adequate amounts of several other nutrients. No demographic or anthropometric variables were related to FA intake in children. Adults with a college degree had significantly lower ratios than those without a college degree. American children and older adults are able to consume more balanced omega-6 to omega-3 ratios than has been indicated by commodity data. However, very few American children met even the lowest recommendations for EPA and DHA intake. Research is needed to clarify recommendations for the optimal ratio across development, which may aid in increasing EPA and DHA intake and improving health outcomes in the United States. ClinicalTrials.gov NCT02199808 13 July 2014, NCT01823419 (retrospectively registered) 20 March 2013, and NCT
Visual prosthesis wireless energy transfer system optimal modeling.
Li, Xueping; Yang, Yuan; Gao, Yong
2014-01-16
Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.
Optimal velocity difference model for a car-following theory
International Nuclear Information System (INIS)
Peng, G.H.; Cai, X.H.; Liu, C.Q.; Cao, B.F.; Tuo, M.X.
2011-01-01
In this Letter, we present a new optimal velocity difference model for a car-following theory based on the full velocity difference model. The linear stability condition of the new model is obtained by using the linear stability theory. The unrealistically high deceleration does not appear in OVDM. Numerical simulation of traffic dynamics shows that the new model can avoid the disadvantage of negative velocity occurred at small sensitivity coefficient λ in full velocity difference model by adjusting the coefficient of the optimal velocity difference, which shows that collision can disappear in the improved model. -- Highlights: → A new optimal velocity difference car-following model is proposed. → The effects of the optimal velocity difference on the stability of traffic flow have been explored. → The starting and braking process were carried out through simulation. → The effects of the optimal velocity difference can avoid the disadvantage of negative velocity.
Hydrodynamic simulations of integrated experiments planned for OMEGA/OMEGA EP laser systems
International Nuclear Information System (INIS)
Delettrez, J. A.; Myatt, J.; Radha, P. B.; Stoeckl, C.; Meyerhofer, D. D.
2005-01-01
Integrated fast-ignition experiments for the combined OMEGA/OMEGA EP laser systems have been simulated with the multidimensional hydrodynamic code DRACO. In the simplified electron transport model included in DRACO, the electrons are introduced at the pole of a 2-D simulation and transported in a straight line toward the target core, depositing their energy according to a recently published slowing-down formula.1 Simulations, including alpha transport, of an OMEGA cryogenic target designed to reach a 1-D fuel R of 500 mg/cm2 have been carried out for 1-D (clean) and, more realistic, 2-D (with nonuniformities) implosions to assess the sensitivity to energy, timing, and irradiance of the Gaussian fast-ignitor beam. The OMEGA laser system provides up to 30 kJ of compression energy, and OMEGA EP will provide two short pulse beams, each with energies up to 2.6 kJ. For the 1-D case, the neutron yield is predicted to be in excess of 1015 (compared to 1014 for no ignitor beam) over a timing range of about 80 ps. This talk will present these results and new 2-D simulation results that include the effects of realistic cryogenic target perturbations on the compressed core. This work was supported by the U.S. Department of Energy Office of Inertial Confinement Fusion under Cooperative Agreement No. DE-FC52-92SF19460, the University of Rochester, and the New York State Energy Research and Development Authority. The support of DOE does not constitute an endorsement by DOE of the views expressed in this article. (Author)
Optimal consumption problem in the Vasicek model
Directory of Open Access Journals (Sweden)
Jakub Trybuła
2015-01-01
Full Text Available We consider the problem of an optimal consumption strategy on the infinite time horizon based on the hyperbolic absolute risk aversion utility when the interest rate is an Ornstein-Uhlenbeck process. Using the method of subsolution and supersolution we obtain the existence of solutions of the dynamic programming equation. We illustrate the paper with a numerical example of the optimal consumption strategy and the value function.
Dietary omega-3 fatty acids aid in the modulation of inflammation and metabolic health
Directory of Open Access Journals (Sweden)
J. Bruce German
2011-07-01
Full Text Available This article focuses on the role of omega-3 fatty acids as precursors for lipid signaling molecules known as oxylipins. Although omega-3 fatty acids are beneficial in autoimmune disorders, inflammatory diseases and heart disease, they are generally underrepresented in the American diet. A literature review confirms that the consumption of omega-3 fatty acids - whether in food sources such as walnuts, flax seeds and fatty fish (including salmon and sardines, or in supplements - is associated with decreased morbidity and mortality. This growing body of evidence, including the results of a recent study of patients with kidney disease, highlights the need to measure omega-3 fatty acids and their oxylipin products as markers of metabolic health and biomarkers of disease. In addition, there is substantial evidence of the need to increase the omega-3 fatty acid content of American diets to optimize metabolic health.
Optimization model for the design of distributed wastewater treatment networks
Directory of Open Access Journals (Sweden)
Ibrić Nidret
2012-01-01
Full Text Available In this paper we address the synthesis problem of distributed wastewater networks using mathematical programming approach based on the superstructure optimization. We present a generalized superstructure and optimization model for the design of the distributed wastewater treatment networks. The superstructure includes splitters, treatment units, mixers, with all feasible interconnections including water recirculation. Based on the superstructure the optimization model is presented. The optimization model is given as a nonlinear programming (NLP problem where the objective function can be defined to minimize the total amount of wastewater treated in treatment operations or to minimize the total treatment costs. The NLP model is extended to a mixed integer nonlinear programming (MINLP problem where binary variables are used for the selection of the wastewater treatment technologies. The bounds for all flowrates and concentrations in the wastewater network are specified as general equations. The proposed models are solved using the global optimization solvers (BARON and LINDOGlobal. The application of the proposed models is illustrated on the two wastewater network problems of different complexity. First one is formulated as the NLP and the second one as the MINLP. For the second one the parametric and structural optimization is performed at the same time where optimal flowrates, concentrations as well as optimal technologies for the wastewater treatment are selected. Using the proposed model both problems are solved to global optimality.
A model for optimizing the production of pharmaceutical products
Directory of Open Access Journals (Sweden)
Nevena Gospodinova
2017-05-01
Full Text Available The problem associated with the optimal production planning is especially relevant in modern industrial enterprises. The most commonly used optimality criteria in this context are: maximizing the total profit; minimizing the cost per unit of production; maximizing the capacity utilization; minimizing the total production costs. This article aims to explore the possibility for optimizing the production of pharmaceutical products through the construction of a mathematical model that can be viewed in two ways – as a single-product model and a multi-product model. As an optimality criterion it is set the minimization of the cost per unit of production for a given planning period. The author proposes an analytical method for solving the nonlinear optimization problem. An optimal production plan of Tylosin tartrate is found using the single-product model.
Hierarchical models and iterative optimization of hybrid systems
Energy Technology Data Exchange (ETDEWEB)
Rasina, Irina V. [Ailamazyan Program Systems Institute, Russian Academy of Sciences, Peter One str. 4a, Pereslavl-Zalessky, 152021 (Russian Federation); Baturina, Olga V. [Trapeznikov Control Sciences Institute, Russian Academy of Sciences, Profsoyuznaya str. 65, 117997, Moscow (Russian Federation); Nasatueva, Soelma N. [Buryat State University, Smolina str.24a, Ulan-Ude, 670000 (Russian Federation)
2016-06-08
A class of hybrid control systems on the base of two-level discrete-continuous model is considered. The concept of this model was proposed and developed in preceding works as a concretization of the general multi-step system with related optimality conditions. A new iterative optimization procedure for such systems is developed on the base of localization of the global optimality conditions via contraction the control set.
Constrained optimization via simulation models for new product innovation
Pujowidianto, Nugroho A.
2017-11-01
We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.
Empty tracks optimization based on Z-Map model
Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao
2017-12-01
For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.
Optimal hedging with the cointegrated vector autoregressive model
DEFF Research Database (Denmark)
Gatarek, Lukasz; Johansen, Søren
We derive the optimal hedging ratios for a portfolio of assets driven by a Coin- tegrated Vector Autoregressive model (CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the...
Stochastic Robust Mathematical Programming Model for Power System Optimization
Energy Technology Data Exchange (ETDEWEB)
Liu, Cong; Changhyeok, Lee; Haoyong, Chen; Mehrotra, Sanjay
2016-01-01
This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.
Modeling and optimization of an electric power distribution network ...
African Journals Online (AJOL)
Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...
Integrated modeling of ozonation for optimization of drinking water treatment
van der Helm, A.W.C.
2007-01-01
Drinking water treatment plants automation becomes more sophisticated, more on-line monitoring systems become available and integration of modeling environments with control systems becomes easier. This gives possibilities for model-based optimization. In operation of drinking water treatment
Directory of Open Access Journals (Sweden)
Mario Domingues de Paula Simões
2011-04-01
twelve months of the contract time span, based on the optimization of the omega measurement (consider all moments, subjected to value at risk restrictions. In order for this omega measurement to be employed, the simulation of short term prices is used and the model then applied to a small hydroelectric generation facility. The results indicate that the seazonalization decision will change substantially when there are value at risk restrictions, forcing the optimal decision to be closer the flat allocation throughout the year.
Shape optimization in biomimetics by homogenization modelling
International Nuclear Information System (INIS)
Hoppe, Ronald H.W.; Petrova, Svetozara I.
2003-08-01
Optimal shape design of microstructured materials has recently attracted a great deal of attention in material science. The shape and the topology of the microstructure have a significant impact on the macroscopic properties. The present work is devoted to the shape optimization of new biomorphic microcellular ceramics produced from natural wood by biotemplating. We are interested in finding the best material-and-shape combination in order to achieve the optimal prespecified performance of the composite material. The computation of the effective material properties is carried out using the homogenization method. Adaptive mesh-refinement technique based on the computation of recovered stresses is applied in the microstructure to find the homogenized elasticity coefficients. Numerical results show the reliability of the implemented a posteriori error estimator. (author)
A tutorial on fundamental model structures for railway timetable optimization
DEFF Research Database (Denmark)
Harrod, Steven
2012-01-01
This guide explains the role of railway timetables relative to all other railway scheduling activities, and then presents four fundamental timetable formulations suitable for optimization. Timetabling models may be classified according to whether they explicitly model the track structure, and whe......This guide explains the role of railway timetables relative to all other railway scheduling activities, and then presents four fundamental timetable formulations suitable for optimization. Timetabling models may be classified according to whether they explicitly model the track structure...
Observation of chi(c1) Decays into Vector Meson Pairs phi phi, omega omega, and omega phi
Ablikim, M.; Achasov, M. N.; An, L.; An, Q.; An, Z. H.; Bai, J. Z.; Baldini, R.; Ban, Y.; Becker, J.; Berger, N.; Bertani, M.; Bian, J. M.; Bondarenko, O.; Boyko, I.; Briere, R. A.; Bytev, V.; Cai, X.; Cao, G. F.; Cao, X. X.; Chang, J. F.; Chelkov, G.; Chen, G.; Chen, H. S.; Chen, J. C.; Chen, M. L.; Chen, S. J.; Chen, Y.; Chen, Y. B.; Cheng, H. P.; Chu, Y. P.; Cronin-Hennessy, D.; Dai, H. L.; Dai, J. P.; Dedovich, D.; Deng, Z. Y.; Denysenko, I.; Destefanis, M.; Ding, Y.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Duan, M. Y.; Fan, R. R.; Fang, J.; Fang, S. S.; Feng, C. Q.; Fu, C. D.; Fu, J. L.; Gao, Y.; Geng, C.; Goetzen, K.; Gong, W. X.; Greco, M.; Grishin, S.; Gu, M. H.; Gu, Y. T.; Guan, Y. H.; Guo, A. Q.; Guo, L. B.; Guo, Y. P.; Hao, X. Q.; Harris, F. A.; He, K. L.; He, M.; He, Z. Y.; Heng, Y. K.; Hou, Z. L.; Hu, H. M.; Hu, J. F.; Hu, T.; Huang, B.; Huang, G. M.; Huang, J. S.; Huang, X. T.; Huang, Y. P.; Hussain, T.; Ji, C. S.; Ji, Q.; Ji, X. B.; Ji, X. L.; Jia, L. K.; Jiang, L. L.; Jiang, X. S.; Jiao, J. B.; Jiao, Z.; Jin, D. P.; Jin, S.; Jing, F. F.; Kavatsyuk, M.; Komamiya, S.; Kuehn, W.; Lange, J. S.; Leung, J. K. C.; Li, Cheng; Li, Cui; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, J. C.; Li, Lei; Li, N. B.; Li, Q. J.; Li, W. D.; Li, W. G.; Li, X. L.; Li, X. N.; Li, X. Q.; Li, X. R.; Li, Z. B.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, G. R.; Liao, X. T.; Liu, B. J.; Liu, B. J.; Liu, C. L.; Liu, C. X.; Liu, C. Y.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, G. C.; Liu, H.; Liu, H. B.; Liu, H. M.; Liu, H. W.; Liu, J. P.; Liu, K.; Liu, K. Y.; Liu, Q.; Liu, S. B.; Liu, X.; Liu, X. H.; Liu, Y. B.; Liu, Y. W.; Liu, Yong; Liu, Z. A.; Liu, Z. Q.; Loehner, H.; Lu, G. R.; Lu, H. J.; Lu, J. G.; Lu, Q. W.; Lu, X. R.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, T.; Luo, X. L.; Ma, C. L.; Ma, F. C.; Ma, H. L.; Ma, Q. M.; Ma, T.; Ma, X.; Ma, X. Y.; Maggiora, M.; Malik, Q. A.; Mao, H.; Mao, Y. J.; Mao, Z. P.; Messchendorp, J. G.; Min, J.; Mitchell, R. E.; Mo, X. H.; Muchnoi, N. Yu.; Nefedov, Y.; Ning, Z.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pelizaeus, M.; Peters, K.; Ping, J. L.; Ping, R. G.; Poling, R.; Pun, C. S. J.; Qi, M.; Qian, S.; Qiao, C. F.; Qin, X. S.; Qiu, J. F.; Rashid, K. H.; Rong, G.; Ruan, X. D.; Sarantsev, A.; Schulze, J.; Shao, M.; Shen, C. P.; Shen, X. Y.; Sheng, H. Y.; Shepherd, M. R.; Song, X. Y.; Sonoda, S.; Spataro, S.; Spruck, B.; Sun, D. H.; Sun, G. X.; Sun, J. F.; Sun, S. S.; Sun, X. D.; Sun, Y. J.; Sun, Y. Z.; Sun, Z. J.; Sun, Z. T.; Tang, C. J.; Tang, X.; Tang, X. F.; Tian, H. L.; Toth, D.; Varner, G. S.; Wan, X.; Wang, B. Q.; Wang, K.; Wang, L. L.; Wang, L. S.; Wang, M.; Wang, P.; Wang, P. L.; Wang, Q.; Wang, S. G.; Wang, X. L.; Wang, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. G.; Wang, Z. Y.; Wei, D. H.; Wen, Q. G.; Wen, S. P.; Wiedner, U.; Wu, L. H.; Wu, N.; Wu, W.; Wu, Z.; Xiao, Z. J.; Xie, Y. G.; Xu, G. F.; Xu, G. M.; Xu, H.; Xu, Y.; Xu, Z. R.; Xu, Z. Z.; Xue, Z.; Yan, L.; Yan, W. B.; Yan, Y. H.; Yang, H. X.; Yang, M.; Yang, T.; Yang, Y.; Yang, Y. X.; Ye, M.; Ye, M. H.; Yu, B. X.; Yu, C. X.; Yu, L.; Yuan, C. Z.; Yuan, W. L.; Yuan, Y.; Zafar, A. A.; Zallo, A.; Zeng, Y.; Zhang, B. X.; Zhang, B. Y.; Zhang, C. C.; Zhang, D. H.; Zhang, H. H.; Zhang, H. Y.; Zhang, J.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, L.; Zhang, S. H.; Zhang, T. R.; Zhang, X. J.; Zhang, X. Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Z. P.; Zhang, Z. Y.; Zhao, G.; Zhao, H. S.; Zhao, Jiawei; Zhao, Jingwei; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, S. J.; Zhao, T. C.; Zhao, X. H.; Zhao, Y. B.; Zhao, Z. G.; Zhao, Z. L.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, Y. H.; Zheng, Z. P.; Zhong, B.; Zhong, J.; Zhong, L.; Zhou, L.; Zhou, X. K.; Zhou, X. R.; Zhu, C.; Zhu, K.; Zhu, K. J.; Zhu, S. H.; Zhu, X. L.; Zhu, X. W.; Zhu, Y. S.; Zhu, Z. A.; Zhuang, J.; Zou, B. S.; Zou, J. H.; Zuo, J. X.; Zweber, P.
2011-01-01
Using (106 +/- 4) x 10(6) psi(3686) events accumulated with the BESIII detector at the BEPCII e(+) e(-) collider, we present the first measurement of decays of chi(c1) to vector meson pairs phi phi, omega omega, and omega phi. The branching fractions are measured to be (4.4 +/- 0.3 +/- 0.5) x
An Increase in the Omega-6/Omega-3 Fatty Acid Ratio Increases the Risk for Obesity
Simopoulos, Artemis P.
2016-01-01
In the past three decades, total fat and saturated fat intake as a percentage of total calories has continuously decreased in Western diets, while the intake of omega-6 fatty acid increased and the omega-3 fatty acid decreased, resulting in a large increase in the omega-6/omega-3 ratio from 1:1 during evolution to 20:1 today or even higher. This change in the composition of fatty acids parallels a significant increase in the prevalence of overweight and obesity. Experimental studies have suggested that omega-6 and omega-3 fatty acids elicit divergent effects on body fat gain through mechanisms of adipogenesis, browning of adipose tissue, lipid homeostasis, brain-gut-adipose tissue axis, and most importantly systemic inflammation. Prospective studies clearly show an increase in the risk of obesity as the level of omega-6 fatty acids and the omega-6/omega-3 ratio increase in red blood cell (RBC) membrane phospholipids, whereas high omega-3 RBC membrane phospholipids decrease the risk of obesity. Recent studies in humans show that in addition to absolute amounts of omega-6 and omega-3 fatty acid intake, the omega-6/omega-3 ratio plays an important role in increasing the development of obesity via both AA eicosanoid metabolites and hyperactivity of the cannabinoid system, which can be reversed with increased intake of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). A balanced omega-6/omega-3 ratio is important for health and in the prevention and management of obesity. PMID:26950145
An Increase in the Omega-6/Omega-3 Fatty Acid Ratio Increases the Risk for Obesity
Directory of Open Access Journals (Sweden)
Artemis P. Simopoulos
2016-03-01
Full Text Available In the past three decades, total fat and saturated fat intake as a percentage of total calories has continuously decreased in Western diets, while the intake of omega-6 fatty acid increased and the omega-3 fatty acid decreased, resulting in a large increase in the omega-6/omega-3 ratio from 1:1 during evolution to 20:1 today or even higher. This change in the composition of fatty acids parallels a significant increase in the prevalence of overweight and obesity. Experimental studies have suggested that omega-6 and omega-3 fatty acids elicit divergent effects on body fat gain through mechanisms of adipogenesis, browning of adipose tissue, lipid homeostasis, brain-gut-adipose tissue axis, and most importantly systemic inflammation. Prospective studies clearly show an increase in the risk of obesity as the level of omega-6 fatty acids and the omega-6/omega-3 ratio increase in red blood cell (RBC membrane phospholipids, whereas high omega-3 RBC membrane phospholipids decrease the risk of obesity. Recent studies in humans show that in addition to absolute amounts of omega-6 and omega-3 fatty acid intake, the omega-6/omega-3 ratio plays an important role in increasing the development of obesity via both AA eicosanoid metabolites and hyperactivity of the cannabinoid system, which can be reversed with increased intake of eicosapentaenoic acid (EPA and docosahexaenoic acid (DHA. A balanced omega-6/omega-3 ratio is important for health and in the prevention and management of obesity.
On Optimal Input Design and Model Selection for Communication Channels
Energy Technology Data Exchange (ETDEWEB)
Li, Yanyan [ORNL; Djouadi, Seddik M [ORNL; Olama, Mohammed M [ORNL
2013-01-01
In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.
Modeling groundwater vulnerability to pollution using Optimized DRASTIC model
International Nuclear Information System (INIS)
Mogaji, Kehinde Anthony; Lim, Hwee San; Abdullar, Khiruddin
2014-01-01
The prediction accuracy of the conventional DRASTIC model (CDM) algorithm for groundwater vulnerability assessment is severely limited by the inherent subjectivity and uncertainty in the integration of data obtained from various sources. This study attempts to overcome these problems by exploring the potential of the analytic hierarchy process (AHP) technique as a decision support model to optimize the CDM algorithm. The AHP technique was utilized to compute the normalized weights for the seven parameters of the CDM to generate an optimized DRASTIC model (ODM) algorithm. The DRASTIC parameters integrated with the ODM algorithm predicted which among the study areas is more likely to become contaminated as a result of activities at or near the land surface potential. Five vulnerability zones, namely: no vulnerable(NV), very low vulnerable (VLV), low vulnerable (LV), moderate vulnerable (MV) and high vulnerable (HV) were identified based on the vulnerability index values estimated with the ODM algorithm. Results show that more than 50% of the area belongs to both moderate and high vulnerable zones on the account of the spatial analysis of the produced ODM-based groundwater vulnerability prediction map (GVPM).The prediction accuracy of the ODM-based – GVPM with the groundwater pH and manganese (Mn) concentrations established correlation factors (CRs) result of 90 % and 86 % compared to the CRs result of 62 % and 50 % obtained for the validation accuracy of the CDM – based GVPM. The comparative results, indicated that the ODM-based produced GVPM is more reliable than the CDM – based produced GVPM in the study area. The study established the efficacy of AHP as a spatial decision support technique in enhancing environmental decision making with particular reference to future groundwater vulnerability assessment
Optimizing Classroom Acoustics Using Computer Model Studies.
Reich, Rebecca; Bradley, John
1998-01-01
Investigates conditions relating to the maximum useful-to-detrimental sound ratios present in classrooms and determining the optimum conditions for speech intelligibility. Reveals that speech intelligibility is more strongly influenced by ambient noise levels and that the optimal location for sound absorbing material is on a classroom's upper…
Optimization and emergence in marine ecosystem models
DEFF Research Database (Denmark)
Mariani, Patrizio; Visser, Andre
2010-01-01
Ingestion rates and mortality rates of zooplankton are dynamic parameters reflecting a behavioural trade-off between encounters with food and predators. An evolutionarily consistent behaviour is that which optimizes the trade-off in terms of the fitness conferred to an individual. We argue that i...
CREATION OF OPTIMIZATION MODEL OF STEAM BOILER RECUPERATIVE AIR HEATER
Directory of Open Access Journals (Sweden)
N. B. Carnickiy
2006-01-01
Full Text Available The paper proposes to use a mathematical modeling as one of the ways intended to improve quality of recuperative air heater design (RAH without significant additional costs, connected with the change of design materials or fuel type. The described conceptual mathematical AHP optimization model of RAH consists of optimized and constant parameters, technical limitations and optimality criteria.The paper considers a methodology for search of design and regime parameters of an air heater which is based on the methods of multi-criteria optimization. Conclusions for expediency of the given approach usage are made in the paper.
Optimization Research of Generation Investment Based on Linear Programming Model
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
Correlations in state space can cause sub-optimal adaptation of optimal feedback control models
Aprasoff, Jonathan; Donchin, Opher
2011-01-01
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedb...
A measurement of the Omega /sup -/ lifetime
Bourquin, M; Chatelus, Y; Chollet, J C; Degré, A; Froidevaux, D; Fyfe, A R; Gaillard, J M; Gee, C N P; Gibson, W M; Igo-Kemenes, P; Jeffreys, P W; Merkel, B; Morand, R; Plothow, H; Repellin, J P; Saunders, B J; Sauvage, G; Schiby, B; Siebert, H W; Smith, V J; Streit, K P; Strub, R; Tovey, Stuart N; Tresher, J J
1979-01-01
In an experiment at the CERN-SPS charged-hyperon beam, a sample of 2500 Omega /sup -/ to Lambda K/sup -/ decays has been collected at Omega /sup -/ momenta at 98.5 and 115 GeV/c. The Omega /sup -/ lifetime is found to be tau /sub Omega /=(0.822+or-0.028)*10/sup -10/ s. (15 refs).
Observation of an Excited Charm Baryon Omega*C Decaying to OmegaC0 Gamma
International Nuclear Information System (INIS)
Aubert, B
2006-01-01
The authors report the first observation of an excited singly-charmed baryon (Omega)* c (css) in the radiative decay (Omega) c 0 γ, where the (Omega) c 0 baryon is reconstructed in the decays to the final states (Omega) - π + , (Omega) - π + π 0 , (Omega) - π + π - π + , and Ξ - K - π + π + . This analysis is performed using a dataset of 230.7 fb -1 collected by the BABAR detector at the PEP-II asymmetric-energy B Factory at the Stanford Linear Accelerator Center. The mass difference between the (Omega)* c and the (Omega) c 0 baryons is measured to be 70.8 ± 1.0(stat) ± 1.1(syst) MeV/c 2 . They also measure the ratio of inclusive production cross sections of (Omega)* c and (Omega) c 0 in e + e - annihilation
Multipurpose optimization models for high level waste vitrification
International Nuclear Information System (INIS)
Hoza, M.
1994-08-01
Optimal Waste Loading (OWL) models have been developed as multipurpose tools for high-level waste studies for the Tank Waste Remediation Program at Hanford. Using nonlinear programming techniques, these models maximize the waste loading of the vitrified waste and optimize the glass formers composition such that the glass produced has the appropriate properties within the melter, and the resultant vitrified waste form meets the requirements for disposal. The OWL model can be used for a single waste stream or for blended streams. The models can determine optimal continuous blends or optimal discrete blends of a number of different wastes. The OWL models have been used to identify the most restrictive constraints, to evaluate prospective waste pretreatment methods, to formulate and evaluate blending strategies, and to determine the impacts of variability in the wastes. The OWL models will be used to aid in the design of frits and the maximize the waste in the glass for High-Level Waste (HLW) vitrification
Portfolio optimization for index tracking modelling in Malaysia stock market
Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun
2016-06-01
Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.
OMEGA polar-drive target designs
International Nuclear Information System (INIS)
Radha, P. B.; Marozas, J. A.; Marshall, F. J.; Shvydky, A.; Collins, T. J. B.; Goncharov, V. N.; McKenty, P. W.; Sangster, T. C.; Skupsky, S.; McCrory, R. L.; Meyerhofer, D. D.
2012-01-01
Low-adiabat polar-drive (PD) [Skupsky et al., Phys. Plasmas 11, 2763 (2004)] implosion designs for the OMEGA [Boehly et al., Opt. Commun. 133, 495 (1997)] laser are described. These designs for cryogenic deuterium–tritium and warm plastic shells use a temporal laser pulse shape with three pickets followed by a main pulse [Goncharov et al., Phys. Rev. Lett. 104, 165001 (2010)]. The designs are at two different on-target laser intensities, with different in-flight aspect ratios (IFARs). These designs permit studies of implosion energetics and target performance closer to ignition-relevant intensities (∼7 × 10 14 W/cm 2 at the quarter-critical surface, where nonlocal heat conduction and laser–plasma interactions can play an important role) but at lower values of IFAR ∼ 22 or at lower intensity (∼3 × 10 14 W/cm 2 ) but at a higher IFAR (IFAR ∼ 32, where shell instability can play an important role). PD geometry requires repointing of laser beams to improve shell symmetry. The higher-intensity designs optimize target performance by repointing beams to a lesser extent, compensating for the reduced equatorial drive by increasing the energies of the repointed beams. They also use custom beam profiles that improve equatorial illumination at the expense of irradiation at higher latitudes. These latter designs will be studied when new phase plates for the OMEGA Laser System, corresponding to the custom beam profiles, are obtained.
Modelling, simulating and optimizing boiler heating surfaces and evaporator circuits
DEFF Research Database (Denmark)
Sørensen, K.; Condra, T.; Houbak, Niels
2003-01-01
A model for optimizing the dynamic performance of boiler have been developed. Design variables related to the size of the boiler and its dynamic performance have been defined. The object function to be optimized takes the weight of the boiler and its dynamic capability into account. As constraints...... for the optimization a dynamic model for the boiler is applied. Furthermore a function for the value of the dynamic performance is included in the model. The dynamic models for simulating boiler performance consists of a model for the flue gas side, a model for the evaporator circuit and a model for the drum....... The dynamic model has been developed for the purpose of determining boiler material temperatures and heat transfer from the flue gas side to the water-/steam side in order to simulate the circulation in the evaporator circuit and hereby the water level fluctuations in the drum. The dynamic model has been...
An optimal control model of crop thinning in viticulture
Schamel Guenter H.; Schubert Stefan F.
2016-01-01
We develop an economic model of cluster thinning in viticulture to control for grape quantity harvested and grape quality, applying a simple optimal control model with the aim to raise grape quality and related economic profits. The model maximizes vineyard owner profits and allows to discuss two relevant scenarios using a phase diagram analysis: (1) when the initial grape quantity is sufficiently small, thinning grapes will not be optimal and (2) when the initial grape quantity is high enoug...
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Zhang, Xiangsheng; Pan, Feng
2015-01-01
Aimed at the parameters optimization in support vector machine (SVM) for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO) algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effective...
Parameters Optimization and Application to Glutamate Fermentation Model Using SVM
Directory of Open Access Journals (Sweden)
Xiangsheng Zhang
2015-01-01
Full Text Available Aimed at the parameters optimization in support vector machine (SVM for glutamate fermentation modelling, a new method is developed. It optimizes the SVM parameters via an improved particle swarm optimization (IPSO algorithm which has better global searching ability. The algorithm includes detecting and handling the local convergence and exhibits strong ability to avoid being trapped in local minima. The material step of the method was shown. Simulation experiments demonstrate the effectiveness of the proposed algorithm.
DEFF Research Database (Denmark)
Lindholt, Jes S; Kristensen, Katrine L; Burillo, Elena
2018-01-01
BACKGROUND: Animal models support dietary omega-3 fatty acids protection against abdominal aortic aneurysm (AAA), but clinical data are scarce. The sum of red blood cell proportions of the omega-3 eicosapentaenoic and docosahexaenoic acids, known as omega-3 index, is a valid surrogate for long-te...
An optimization strategy for a biokinetic model of inhaled radionuclides
International Nuclear Information System (INIS)
Shyr, L.J.; Griffith, W.C.; Boecker, B.B.
1991-01-01
Models for material disposition and dosimetry involve predictions of the biokinetics of the material among compartments representing organs and tissues in the body. Because of a lack of human data for most toxicants, many of the basic data are derived by modeling the results obtained from studies using laboratory animals. Such a biomathematical model is usually developed by adjusting the model parameters to make the model predictions match the measured retention and excretion data visually. The fitting process can be very time-consuming for a complicated model, and visual model selections may be subjective and easily biased by the scale or the data used. Due to the development of computerized optimization methods, manual fitting could benefit from an automated process. However, for a complicated model, an automated process without an optimization strategy will not be efficient, and may not produce fruitful results. In this paper, procedures for, and implementation of, an optimization strategy for a complicated mathematical model is demonstrated by optimizing a biokinetic model for 144Ce in fused aluminosilicate particles inhaled by beagle dogs. The optimized results using SimuSolv were compared to manual fitting results obtained previously using the model simulation software GASP. Also, statistical criteria provided by SimuSolv, such as likelihood function values, were used to help or verify visual model selections
Qualitative and Quantitative Integrated Modeling for Stochastic Simulation and Optimization
Directory of Open Access Journals (Sweden)
Xuefeng Yan
2013-01-01
Full Text Available The simulation and optimization of an actual physics system are usually constructed based on the stochastic models, which have both qualitative and quantitative characteristics inherently. Most modeling specifications and frameworks find it difficult to describe the qualitative model directly. In order to deal with the expert knowledge, uncertain reasoning, and other qualitative information, a qualitative and quantitative combined modeling specification was proposed based on a hierarchical model structure framework. The new modeling approach is based on a hierarchical model structure which includes the meta-meta model, the meta-model and the high-level model. A description logic system is defined for formal definition and verification of the new modeling specification. A stochastic defense simulation was developed to illustrate how to model the system and optimize the result. The result shows that the proposed method can describe the complex system more comprehensively, and the survival probability of the target is higher by introducing qualitative models into quantitative simulation.
Optimal treatment interruptions control of TB transmission model
Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.
2018-03-01
A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.
Pavement maintenance optimization model using Markov Decision Processes
Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.
2017-09-01
This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.
Optlang: An algebraic modeling language for mathematical optimization
DEFF Research Database (Denmark)
Jensen, Kristian; Cardoso, Joao; Sonnenschein, Nikolaus
2016-01-01
Optlang is a Python package implementing a modeling language for solving mathematical optimization problems, i.e., maximizing or minimizing an objective function over a set of variables subject to a number of constraints. It provides a common native Python interface to a series of optimization...
Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.
Aprasoff, Jonathan; Donchin, Opher
2012-04-01
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.
Markowitz portfolio optimization model employing fuzzy measure
Ramli, Suhailywati; Jaaman, Saiful Hafizah
2017-04-01
Markowitz in 1952 introduced the mean-variance methodology for the portfolio selection problems. His pioneering research has shaped the portfolio risk-return model and become one of the most important research fields in modern finance. This paper extends the classical Markowitz's mean-variance portfolio selection model applying the fuzzy measure to determine the risk and return. In this paper, we apply the original mean-variance model as a benchmark, fuzzy mean-variance model with fuzzy return and the model with return are modeled by specific types of fuzzy number for comparison. The model with fuzzy approach gives better performance as compared to the mean-variance approach. The numerical examples are included to illustrate these models by employing Malaysian share market data.
Directory of Open Access Journals (Sweden)
Fei Wang
2017-07-01
Full Text Available The optimized dispatch of different distributed generations (DGs in stand-alone microgrid (MG is of great significance to the operation’s reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL and combined cooling-heating-power (CCHP model of micro-gas turbine (MT, a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV, wind turbine (WT, fuel cell (FC, diesel engine (DE, MT and energy storage (ES. Four typical scenarios were designed according to different day types (work day or weekend and weather conditions (sunny or rainy in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers’ comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO to propose modified chaos particle swarm optimization (MCPSO whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.
A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting
International Nuclear Information System (INIS)
Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge
2014-01-01
Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily
Czech Academy of Sciences Publication Activity Database
Radošinská, J.; Bačová, B.; Knezl, V.; Beňová, T.; Žurmanová, J.; Soukup, Tomáš; Arnoštová, P.; Slezák, J.; Goncalvesová, E.; Tribulová, N.
2013-01-01
Roč. 31, č. 9 (2013), s. 1876-1885 ISSN 0263-6352 R&D Projects: GA ČR(CZ) GA304/08/0256; GA MŠk(CZ) 7AMB12SK158 Institutional research plan: CEZ:AV0Z50110509 Institutional support: RVO:67985823 Keywords : hypertension * omega-3 polyunsaturated fatty acids * ventricular fibrillation * sinus rhythm restoration * myocardial connexin-43 * protein kinase C * myosin heavy chain Subject RIV: EA - Cell Biology Impact factor: 4.222, year: 2013
Review: Optimization methods for groundwater modeling and management
Yeh, William W.-G.
2015-09-01
Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.
Zhuang, Pan; Wang, Wenqiao; Wang, Jun; Zhang, Yu; Jiao, Jingjing
2018-03-03
Polyunsaturated fatty acids (PUFA) have been reported to exert pleiotropic protective effects against various chronic diseases. However, epidemiologic evidence linking specific PUFA intake to mortality has been limited and contradictory. We aim to assess the associations between specific dietary PUFA and mortality among adults in China and America, respectively. Participants from China Health and Nutrition Survey (CHNS, n = 14,117) and National Health and Nutrition Examination Survey [NHANES (n = 36,032)] were prospectively followed up through the year 2011. Cox regression models were used to investigate hypothesized associations. A total of 1007 and 4826 deaths accrued over a median of 14 and 9.1 years of follow-up in CHNS and NHANES, respectively. Dietary marine omega-3 PUFA was robustly associated with a reduced all-cause mortality [Hazard ratio (HR) comparing extreme categories: 0.74, 95% CI: 0.61-0.89; P omega-6/omega-3 ratio of 6-10 was associated with a lower risk of death in CHNS. Intakes of different specific PUFA show distinct associations with mortality and these relationships also vary between Chinese and US populations. These findings suggest maintaining an omega-6/omega-3 balance diet for overall health promotion outcomes (NCT03155659). Copyright © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization
International Nuclear Information System (INIS)
Raza, Wasim; Kim, Kwang-Yong
2007-01-01
In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem
Particle swarm optimization of a neural network model in a ...
Indian Academy of Sciences (India)
. Since tool life is critically affected by the tool wear, accurate prediction of this wear ... In their work, they established an improvement in the quality ... objective optimization of hard turning using neural network modelling and swarm intelligence ...
Analysis and optimization of a camber morphing wing model
Directory of Open Access Journals (Sweden)
Bing Li
2016-09-01
Full Text Available This article proposes a camber morphing wing model that can continuously change its camber. A mathematical model is proposed and a kinematic simulation is performed to verify the wing’s ability to change camber. An aerodynamic model is used to test its aerodynamic characteristics. Some important aerodynamic analyses are performed. A comparative analysis is conducted to explore the relationships between aerodynamic parameters, the rotation angle of the trailing edge, and the angle of attack. An improved artificial fish swarm optimization algorithm is proposed, referred to as the weighted adaptive artificial fish-swarm with embedded Hooke–Jeeves search method. Some comparison tests are used to test the performance of the improved optimization algorithm. Finally, the proposed optimization algorithm is used to optimize the proposed camber morphing wing model.
Optimization and evaluation of probabilistic-logic sequence models
DEFF Research Database (Denmark)
Christiansen, Henning; Lassen, Ole Torp
to, in principle, Turing complete languages. In general, such models are computationally far to complex for direct use, so optimization by pruning and approximation are needed. % The first steps are made towards a methodology for optimizing such models by approximations using auxiliary models......Analysis of biological sequence data demands more and more sophisticated and fine-grained models, but these in turn introduce hard computational problems. A class of probabilistic-logic models is considered, which increases the expressibility from HMM's and SCFG's regular and context-free languages...
Adaptive surrogate model based multiobjective optimization for coastal aquifer management
Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin
2018-06-01
In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.
Reduced order modeling in topology optimization of vibroacoustic problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2017-01-01
complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...
Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO
Directory of Open Access Journals (Sweden)
Adel Taieb
2017-01-01
Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.
Study of \\Omega_c^0 and \\Omega_c^{*0} Baryons at Belle
Solovieva, E.; Chistov, R.; Collaboration, for the Belle
2008-01-01
We report results from a study of the charmed double strange baryons \\Omega_c^0 and \\Omega_c^{*0} at Belle. The \\Omega_c^0 is reconstructed using the \\Omega_c^0 --> \\Omega^- \\pi^+ decay mode, and its mass is measured to be (2693.6 \\pm 0.3 {+1.8 \\atop -1.5}) MeV/c^2. The \\Omega_c^{*0} baryon is reconstructed in the \\Omega_c^0 \\gamma mode. The mass difference M_{\\Omega_c^{*0}} - M_{\\Omega_c^0} is measured to be (70.7 \\pm 0.9 {+0.1 \\atop -0.9}) MeV/c^2. The analysis is performed using 673 fb^{-1...
Optimization of an Image-Guided Laser-Induced Choroidal Neovascularization Model in Mice.
Directory of Open Access Journals (Sweden)
Yan Gong
Full Text Available The mouse model of laser-induced choroidal neovascularization (CNV has been used in studies of the exudative form of age-related macular degeneration using both the conventional slit lamp and a new image-guided laser system. A standardized protocol is needed for consistent results using this model, which has been lacking. We optimized details of laser-induced CNV using the image-guided laser photocoagulation system. Four lesions with similar size were consistently applied per eye at approximately double the disc diameter away from the optic nerve, using different laser power levels, and mice of various ages and genders. After 7 days, the mice were sacrificed and retinal pigment epithelium/choroid/sclera was flat-mounted, stained with Isolectin B4, and imaged. Quantification of the area of the laser-induced lesions was performed using an established and constant threshold. Exclusion criteria are described that were necessary for reliable data analysis of the laser-induced CNV lesions. The CNV lesion area was proportional to the laser power levels. Mice at 12-16 weeks of age developed more severe CNV than those at 6-8 weeks of age, and the gender difference was only significant in mice at 12-16 weeks of age, but not in those at 6-8 weeks of age. Dietary intake of omega-3 long-chain polyunsaturated fatty acid reduced laser-induced CNV in mice. Taken together, laser-induced CNV lesions can be easily and consistently applied using the image-guided laser platform. Mice at 6-8 weeks of age are ideal for the laser-induced CNV model.
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
RF building block modeling: optimization and synthesis
Cheng, W.
2012-01-01
For circuit designers it is desirable to have relatively simple RF circuit models that do give decent estimation accuracy and provide sufficient understanding of circuits. Chapter 2 in this thesis shows a general weak nonlinearity model that meets these demands. Using a method that is related to
An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty
Directory of Open Access Journals (Sweden)
Feng Zhou
2015-11-01
Full Text Available An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1 application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2 algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2 incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.
Low Complexity Models to improve Incomplete Sensitivities for Shape Optimization
Stanciu, Mugurel; Mohammadi, Bijan; Moreau, Stéphane
2003-01-01
The present global platform for simulation and design of multi-model configurations treat shape optimization problems in aerodynamics. Flow solvers are coupled with optimization algorithms based on CAD-free and CAD-connected frameworks. Newton methods together with incomplete expressions of gradients are used. Such incomplete sensitivities are improved using reduced models based on physical assumptions. The validity and the application of this approach in real-life problems are presented. The numerical examples concern shape optimization for an airfoil, a business jet and a car engine cooling axial fan.
Vector-model-supported approach in prostate plan optimization
International Nuclear Information System (INIS)
Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Lehman, Margot; Pryor, David; Chan, Lawrence Wing Chi
2017-01-01
Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration
Vector-model-supported approach in prostate plan optimization
Energy Technology Data Exchange (ETDEWEB)
Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Lehman, Margot; Pryor, David [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)
2017-07-01
Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100 previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration
Ishak, Wan Maznah Wan; Katas, Haliza; Yuen, Ng Pei; Abdullah, Maizaton Atmadini; Zulfakar, Mohd Hanif
2018-04-17
Wound healing is a physiological event that generates reconstitution and restoration of granulation tissue that ends with scar formation. As omega fatty acids are part of membrane phospholipids and participate in the inflammatory response, we investigated the effects of omega-3, omega-6, and omega-9 fatty acids in the form of oils on wound healing. Linseed (LO), evening primrose (EPO), and olive oils (OO) rich in omega-3, omega-6, and omega-9 fatty acids were formulated into emulsions and were topically applied on rats with excision wounds. All omega-3-, omega-6-, and omega-9-rich oil formulations were found to accelerate wound closure compared to untreated, with significant improvement (p < 0.05) being observed at day 14. EPO induced early deposition of collagen as evaluated by Masson trichrome staining that correlated well with the hydroxyproline content assay, with the highest level at days 3 and 7. Vascular endothelial growth factor (VEGF) showed greater amount of new microvasculature formed in the EPO-treated group, while moderate improvement occurs in the LO and OO groups. EPO increased both the expression of proinflammatory cytokines and growth factors in the early stage of healing and declined at the later stage of healing. LO modulates the proinflammatory cytokines and chemokine but did not affect the growth factors. In contrast, OO induced the expression of growth factors rather than proinflammatory cytokines. These data suggest that LO, EPO, and OO emulsions promote wound healing but they accomplish this by different mechanisms.
Optimal inventory management and order book modeling
Baradel, Nicolas; Bouchard, Bruno; Evangelista, David; Mounjid, Othmane
2018-01-01
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic
Optimal parametric modelling of measured short waves
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
the importance of selecting a suitable sampling interval for better estimates of parametric modelling and also for better statistical representation. Implementation of the above algorithms in a structural monitoring system has the potential advantage of storing...
Optimization models in a transition economy
Sergienko, Ivan V; Koshlai, Ludmilla
2014-01-01
This book opens new avenues in understanding mathematical models within the context of a transition economy. The exposition lays out the methods for combining different mathematical structures and tools to effectively build the next model that will accurately reflect real world economic processes. Mathematical modeling of weather phenomena allows us to forecast certain essential weather parameters without any possibility of changing them. By contrast, modeling of transition economies gives us the freedom to not only predict changes in important indexes of all types of economies, but also to influence them more effectively in the desired direction. Simply put: any economy, including a transitional one, can be controlled. This book is useful to anyone who wants to increase profits within their business, or improve the quality of their family life and the economic area they live in. It is beneficial for undergraduate and graduate students specializing in the fields of Economic Informatics, Economic Cybernetic...
Optimization of experimental human leukemia models (review
Directory of Open Access Journals (Sweden)
D. D. Pankov
2012-01-01
Full Text Available Actual problem of assessing immunotherapy prospects including antigenpecific cell therapy using animal models was covered in this review.Describe the various groups of currently existing animal models and methods of their creating – from different immunodeficient mice to severalvariants of tumor cells engraftment in them. The review addresses the possibility of tumor stem cells studying using mouse models for the leukemia treatment with adoptive cell therapy including WT1. Also issues of human leukemia cells migration and proliferation in a mice withdifferent immunodeficiency degree are discussed. To assess the potential immunotherapy efficacy comparison of immunodeficient mouse model with clinical situation in oncology patients after chemotherapy is proposed.
Optimality models in the age of experimental evolution and genomics.
Bull, J J; Wang, I-N
2010-09-01
Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.
Optimization models for flight test scheduling
Holian, Derreck
As threats around the world increase with nations developing new generations of warfare technology, the Unites States is keen on maintaining its position on top of the defense technology curve. This in return indicates that the U.S. military/government must research, develop, procure, and sustain new systems in the defense sector to safeguard this position. Currently, the Lockheed Martin F-35 Joint Strike Fighter (JSF) Lightning II is being developed, tested, and deployed to the U.S. military at Low Rate Initial Production (LRIP). The simultaneous act of testing and deployment is due to the contracted procurement process intended to provide a rapid Initial Operating Capability (IOC) release of the 5th Generation fighter. For this reason, many factors go into the determination of what is to be tested, in what order, and at which time due to the military requirements. A certain system or envelope of the aircraft must be assessed prior to releasing that capability into service. The objective of this praxis is to aide in the determination of what testing can be achieved on an aircraft at a point in time. Furthermore, it will define the optimum allocation of test points to aircraft and determine a prioritization of restrictions to be mitigated so that the test program can be best supported. The system described in this praxis has been deployed across the F-35 test program and testing sites. It has discovered hundreds of available test points for an aircraft to fly when it was thought none existed thus preventing an aircraft from being grounded. Additionally, it has saved hundreds of labor hours and greatly reduced the occurrence of test point reflight. Due to the proprietary nature of the JSF program, details regarding the actual test points, test plans, and all other program specific information have not been presented. Generic, representative data is used for example and proof-of-concept purposes. Apart from the data correlation algorithms, the optimization associated
Optimal Pricing and Advertising Policies for New Product Oligopoly Models
Gerald L. Thompson; Jinn-Tsair Teng
1984-01-01
In this paper our previous work on monopoly and oligopoly new product models is extended by the addition of pricing as well as advertising control variables. These models contain Bass's demand growth model, and the Vidale-Wolfe and Ozga advertising models, as well as the production learning curve model and an exponential demand function. The problem of characterizing an optimal pricing and advertising policy over time is an important question in the field of marketing as well as in the areas ...
Desiccant wheel thermal performance modeling for indoor humidity optimal control
International Nuclear Information System (INIS)
Wang, Nan; Zhang, Jiangfeng; Xia, Xiaohua
2013-01-01
Highlights: • An optimal humidity control model is formulated to control the indoor humidity. • MPC strategy is used to implement the optimal operation solution. • Practical applications of the MPC strategy is illustrated by the case study. - Abstract: Thermal comfort is an important concern in the energy efficiency improvement of commercial buildings. Thermal comfort research focuses mostly on temperature control, but humidity control is an important aspect to maintain indoor comfort too. In this paper, an optimal humidity control model (OHCM) is presented. Model predictive control (MPC) strategy is applied to implement the optimal operation of the desiccant wheel during working hours of a commercial building. The OHCM is revised to apply the MPC strategy. A case is studied to illustrate the practical applications of the MPC strategy
AN OPTIMAL MAINTENANCE MANAGEMENT MODEL FOR AIRPORT CONCRETE PAVEMENT
Shimomura, Taizo; Fujimori, Yuji; Kaito, Kiyoyuki; Obama, Kengo; Kobayashi, Kiyoshi
In this paper, an optimal management model is formulated for the performance-based rehabilitation/maintenance contract for airport concrete pavement, whereby two types of life cycle cost risks, i.e., ground consolidation risk and concrete depreciation risk, are explicitly considered. The non-homogenous Markov chain model is formulated to represent the deterioration processes of concrete pavement which are conditional upon the ground consolidation processes. The optimal non-homogenous Markov decision model with multiple types of risk is presented to design the optimal rehabilitation/maintenance plans. And the methodology to revise the optimal rehabilitation/maintenance plans based upon the monitoring data by the Bayesian up-to-dating rules. The validity of the methodology presented in this paper is examined based upon the case studies carried out for the H airport.
On topological groups admitting a base at identity indexed with $\\omega^\\omega$
Leiderman, Arkady G.; Pestov, Vladimir G.; Tomita, Artur H.
2015-01-01
A topological group $G$ is said to have a local $\\omega^\\omega$-base if the neighbourhood system at identity admits a monotone cofinal map from the directed set $\\omega^\\omega$. In particular, every metrizable group is such, but the class of groups with a local $\\omega^\\omega$-base is significantly wider. The aim of this article is to better understand the boundaries of this class, by presenting new examples and counter-examples. Ultraproducts and non-arichimedean ordered fields lead to natur...
The f2(1565) in pbar-p -> (omega-omega)pizero interactions at rest
Baker, C.A.; Batty, C.J.; Braune, K.; Bugg, D.V.; Cramer, O.; Crede, V.; Djaoshvili, N.; Dunnweber, W.; Faessler, M.A.; Hessey, N.P.; Hidas, P.; Hodd, C.; Jamnik, D.; Kilinowsky, H.; Kisiel, J.; Klempt, E.; Kolo, C.; Montanet, L.; Pick, B.; Roethel, W.; Sarantsev, A.; Scott, I.; Strassburger, C.; Thoma, U.; Volcker, C.; Wallis, S.; Walther, D.; Wittmack, K.; Zou, B.S.
2011-01-01
Data are presented on the reaction pbar-p -> omega-omega-pizero at rest from the Crystal Barrel detector. These data identify a strong signal due to f2(1565) -> omega-omega. The relative production from initial pbar-p states 3P2, 3P1 and 1S0 is well determined from omega-omega decay angular correlations; P-state annihilation dominates strongly. A combined fit is made with data on pbar-p -> 3pizero at rest, where f2(1565) -> pizero-pizero is observed.
The Role for Dietary Omega-3 Fatty Acids Supplementation in Older Adults
Directory of Open Access Journals (Sweden)
Alessio Molfino
2014-10-01
Full Text Available Optimal nutrition is one of the most important determinants of healthier ageing, reducing the risk of disability, maintaining mental and physical functions, and thus preserving and ensuring a better quality of life. Dietary intake and nutrient absorption decline with age, thus increasing the risk of malnutrition, morbidity and mortality. Specific nutrients, particularly long-chain omega-3 polyunsaturated fatty acids (PUFAs, might have the potential of preventing and reducing co-morbidities in older adults. Omega-3 PUFAs are able to modulate inflammation, hyperlipidemia, platelet aggregation, and hypertension. Different mechanisms contribute to these effects, including conditioning cell membrane function and composition, eicosanoid production, and gene expression. The present review analyzes the influence of omega-3 PUFAs status and intake on brain function, cardiovascular system, immune function, muscle performance and bone health in older adults. Omega-3 FAs may have substantial benefits in reducing the risk of cognitive decline in older people. The available data encourage higher intakes of omega-3 PUFAs in the diet or via specific supplements. More studies are needed to confirm the role of omega-3 FAs in maintaining bone health and preventing the loss of muscle mass and function associated with ageing. In summary, omega-3 PUFAs are now identified as potential key nutrients, safe and effective in the treatment and prevention of several negative consequences of ageing.
The role for dietary omega-3 fatty acids supplementation in older adults.
Molfino, Alessio; Gioia, Gianfranco; Rossi Fanelli, Filippo; Muscaritoli, Maurizio
2014-10-03
Optimal nutrition is one of the most important determinants of healthier ageing, reducing the risk of disability, maintaining mental and physical functions, and thus preserving and ensuring a better quality of life. Dietary intake and nutrient absorption decline with age, thus increasing the risk of malnutrition, morbidity and mortality. Specific nutrients, particularly long-chain omega-3 polyunsaturated fatty acids (PUFAs), might have the potential of preventing and reducing co-morbidities in older adults. Omega-3 PUFAs are able to modulate inflammation, hyperlipidemia, platelet aggregation, and hypertension. Different mechanisms contribute to these effects, including conditioning cell membrane function and composition, eicosanoid production, and gene expression. The present review analyzes the influence of omega-3 PUFAs status and intake on brain function, cardiovascular system, immune function, muscle performance and bone health in older adults. Omega-3 FAs may have substantial benefits in reducing the risk of cognitive decline in older people. The available data encourage higher intakes of omega-3 PUFAs in the diet or via specific supplements. More studies are needed to confirm the role of omega-3 FAs in maintaining bone health and preventing the loss of muscle mass and function associated with ageing. In summary, omega-3 PUFAs are now identified as potential key nutrients, safe and effective in the treatment and prevention of several negative consequences of ageing.
Multi-objective optimization of GENIE Earth system models.
Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J
2009-07-13
The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.
Anode baking process optimization through computer modelling
Energy Technology Data Exchange (ETDEWEB)
Wilburn, D.; Lancaster, D.; Crowell, B. [Noranda Aluminum, New Madrid, MO (United States); Ouellet, R.; Jiao, Q. [Noranda Technology Centre, Pointe Claire, PQ (Canada)
1998-12-31
Carbon anodes used in aluminum electrolysis are produced in vertical or horizontal type anode baking furnaces. The carbon blocks are formed from petroleum coke aggregate mixed with a coal tar pitch binder. Before the carbon block can be used in a reduction cell it must be heated to pyrolysis. The baking process represents a large portion of the aluminum production cost, and also has a significant effect on anode quality. To ensure that the baking of the anode is complete, it must be heated to about 1100 degrees C. To improve the understanding of the anode baking process and to improve its efficiency, a menu-driven heat, mass and fluid flow simulation tool, called NABSIM (Noranda Anode Baking SIMulation), was developed and calibrated in 1993 and 1994. It has been used since then to evaluate and screen firing practices, and to determine which firing procedure will produce the optimum heat-up rate, final temperature, and soak time, without allowing unburned tar to escape. NABSIM is used as a furnace simulation tool on a daily basis by Noranda plant process engineers and much effort is expended in improving its utility by creating new versions, and the addition of new modules. In the immediate future, efforts will be directed towards optimizing the anode baking process to improve temperature uniformity from pit to pit. 3 refs., 4 figs.
Fuzzy multiobjective models for optimal operation of a hydropower system
Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.
2013-06-01
Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.
Airfoil Shape Optimization based on Surrogate Model
Mukesh, R.; Lingadurai, K.; Selvakumar, U.
2018-02-01
Engineering design problems always require enormous amount of real-time experiments and computational simulations in order to assess and ensure the design objectives of the problems subject to various constraints. In most of the cases, the computational resources and time required per simulation are large. In certain cases like sensitivity analysis, design optimisation etc where thousands and millions of simulations have to be carried out, it leads to have a life time of difficulty for designers. Nowadays approximation models, otherwise called as surrogate models (SM), are more widely employed in order to reduce the requirement of computational resources and time in analysing various engineering systems. Various approaches such as Kriging, neural networks, polynomials, Gaussian processes etc are used to construct the approximation models. The primary intention of this work is to employ the k-fold cross validation approach to study and evaluate the influence of various theoretical variogram models on the accuracy of the surrogate model construction. Ordinary Kriging and design of experiments (DOE) approaches are used to construct the SMs by approximating panel and viscous solution algorithms which are primarily used to solve the flow around airfoils and aircraft wings. The method of coupling the SMs with a suitable optimisation scheme to carryout an aerodynamic design optimisation process for airfoil shapes is also discussed.
Aerodynamic Modelling and Optimization of Axial Fans
DEFF Research Database (Denmark)
Sørensen, Dan Nørtoft
A numerically efficient mathematical model for the aerodynamics oflow speed axial fans of the arbitrary vortex flow type has been developed.The model is based on a blade-element principle, whereby therotor is divided into a number of annular streamtubes.For each of these streamtubes relations......-Raphson method, andsolutions converged to machine accuracy are found at small computing costs.The model has been validated against published measurementson various fan configurations,comprising two rotor-only fan stages, a counter-rotatingfan unit and a stator-rotor-stator stage.Comparisons of local...... and integrated propertiesshow that the computed results agree well with the measurements.Integrating a rotor-only version of the aerodynamic modelwith an algorithm for numerical designoptimization, enables the finding of an optimum fan rotor.The angular velocity of the rotor, the hub radius and the spanwise...
Robust and fast nonlinear optimization of diffusion MRI microstructure models.
Harms, R L; Fritz, F J; Tobisch, A; Goebel, R; Roebroeck, A
2017-07-15
Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of
A model for optimal constrained adaptive testing
van der Linden, Willem J.; Reese, Lynda M.
2001-01-01
A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum
A model for optimal constrained adaptive testing
van der Linden, Willem J.; Reese, Lynda M.
1997-01-01
A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum
Optimal Experimental Design for Model Discrimination
Myung, Jay I.; Pitt, Mark A.
2009-01-01
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of
Omega-3 deficiency impairs honey bee learning
Arien, Yael; Dag, Arnon; Zarchin, Shlomi; Masci, Tania
2015-01-01
Deficiency in essential omega-3 polyunsaturated fatty acids (PUFAs), particularly the long-chain form of docosahexaenoic acid (DHA), has been linked to health problems in mammals, including many mental disorders and reduced cognitive performance. Insects have very low long-chain PUFA concentrations, and the effect of omega-3 deficiency on cognition in insects has not been studied. We show a low omega-6:3 ratio of pollen collected by honey bee colonies in heterogenous landscapes and in many hand-collected pollens that we analyzed. We identified Eucalyptus as an important bee-forage plant particularly poor in omega-3 and high in the omega-6:3 ratio. We tested the effect of dietary omega-3 deficiency on olfactory and tactile associative learning of the economically highly valued honey bee. Bees fed either of two omega-3–poor diets, or Eucalyptus pollen, showed greatly reduced learning abilities in conditioned proboscis-extension assays compared with those fed omega-3–rich diets, or omega-3–rich pollen mixture. The effect on performance was not due to reduced sucrose sensitivity. Omega-3 deficiency also led to smaller hypopharyngeal glands. Bee brains contained high omega-3 concentrations, which were only slightly affected by diet, suggesting additional peripheral effects on learning. The shift from a low to high omega-6:3 ratio in the Western human diet is deemed a primary cause of many diseases and reduced mental health. A similar shift seems to be occurring in bee forage, possibly an important factor in colony declines. Our study shows the detrimental effect on cognitive performance of omega-3 deficiency in a nonmammal. PMID:26644556
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
. The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...
Optimal maintenance policies in incomplete repair models
International Nuclear Information System (INIS)
Kahle, Waltraud
2007-01-01
We consider an incomplete repair model, that is, the impact of repair is not minimal as in the homogeneous Poisson process and not 'as good as new' as in renewal processes but lies between these boundary cases. The repairs are assumed to impact the failure intensity following a virtual age process of the general form proposed by Kijima. In previous works field data from an industrial setting were used to fit several models. In most cases the estimated rate of occurrence of failures was that of an underlying exponential distribution of the time between failures. In this paper, it is shown that there exist maintenance schedules under which the failure behavior of the failure-repair process becomes a homogeneous Poisson process
Applicability Of Resources Optimization Model For Mitigating
African Journals Online (AJOL)
Dr A.B.Ahmed
previous work. The entire model can be summarized as algorithm below. F u ll L en g th. Research. Article. 1 .... performance metric used is the total sum of utilities of all the peers in the system at .... Hua, J. S., Huang, D. C. Yen, S. M. and Chena, C. W. (2012) “A dynamic ... Workshop on Quality of Service: 174-192. Yahaya ...
Fuzzy optimization model for land use change
L. Jahanshahloo; E. Haghi
2014-01-01
There are some important questions in Land use change literature, for instance How much land to allocate to each of a number of land use type in order to maximization of (household or individual) rent -paying ability, minimization of environmental impacts or maximization of population income. In this paper, we want to investigate them and propose mathematical models to find an answer for these questions. Since Most of the parameters in this process are linguistics and fuzzy logic is a powerfu...
Quantifying Distributional Model Risk via Optimal Transport
Blanchet, Jose; Murthy, Karthyek R. A.
2016-01-01
This paper deals with the problem of quantifying the impact of model misspecification when computing general expected values of interest. The methodology that we propose is applicable in great generality, in particular, we provide examples involving path dependent expectations of stochastic processes. Our approach consists in computing bounds for the expectation of interest regardless of the probability measure used, as long as the measure lies within a prescribed tolerance measured in terms ...
Optimering af model for spredning af luftforurening
DEFF Research Database (Denmark)
Pedersen, Jens Christian
2008-01-01
De nuværende luftforureningsmodeller har problemer med at bevare massen af diverse kemiske stoffer og med at der ind i mellem optræder negative værdier. Derfor arbejder specialestuderende Ayoe Buus Hansen på om at forbedre den model DMU bruger til at beskrive transport og spredning af luftforuren...... luftforurening på alle skalaer på den nordlige halvkugle ved at sammenligne tre alternative beregningsmodeller. ...
Surrogate-Based Optimization of Biogeochemical Transport Models
Prieß, Malte; Slawig, Thomas
2010-09-01
First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.
Learning optimal quantum models is NP-hard
Stark, Cyril J.
2018-02-01
Physical modeling translates measured data into a physical model. Physical modeling is a major objective in physics and is generally regarded as a creative process. How good are computers at solving this task? Here, we show that in the absence of physical heuristics, the inference of optimal quantum models cannot be computed efficiently (unless P=NP ). This result illuminates rigorous limits to the extent to which computers can be used to further our understanding of nature.
Optimization of Operations Resources via Discrete Event Simulation Modeling
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
Space engineering modeling and optimization with case studies
Pintér, János
2016-01-01
This book presents a selection of advanced case studies that cover a substantial range of issues and real-world challenges and applications in space engineering. Vital mathematical modeling, optimization methodologies and numerical solution aspects of each application case study are presented in detail, with discussions of a range of advanced model development and solution techniques and tools. Space engineering challenges are discussed in the following contexts: •Advanced Space Vehicle Design •Computation of Optimal Low Thrust Transfers •Indirect Optimization of Spacecraft Trajectories •Resource-Constrained Scheduling, •Packing Problems in Space •Design of Complex Interplanetary Trajectories •Satellite Constellation Image Acquisition •Re-entry Test Vehicle Configuration Selection •Collision Risk Assessment on Perturbed Orbits •Optimal Robust Design of Hybrid Rocket Engines •Nonlinear Regression Analysis in Space Engineering< •Regression-Based Sensitivity Analysis and Robust Design ...
Optimal foraging in marine ecosystem models: selectivity, profitability and switching
DEFF Research Database (Denmark)
Visser, Andre W.; Fiksen, Ø.
2013-01-01
ecological mechanics and evolutionary logic as a solution to diet selection in ecosystem models. When a predator can consume a range of prey items it has to choose which foraging mode to use, which prey to ignore and which ones to pursue, and animals are known to be particularly skilled in adapting...... to the preference functions commonly used in models today. Indeed, depending on prey class resolution, optimal foraging can yield feeding rates that are considerably different from the ‘switching functions’ often applied in marine ecosystem models. Dietary inclusion is dictated by two optimality choices: 1...... by letting predators maximize energy intake or more properly, some measure of fitness where predation risk and cost are also included. An optimal foraging or fitness maximizing approach will give marine ecosystem models a sound principle to determine trophic interactions...
An optimal control model of crop thinning in viticulture
Directory of Open Access Journals (Sweden)
Schamel Guenter H.
2016-01-01
Full Text Available We develop an economic model of cluster thinning in viticulture to control for grape quantity harvested and grape quality, applying a simple optimal control model with the aim to raise grape quality and related economic profits. The model maximizes vineyard owner profits and allows to discuss two relevant scenarios using a phase diagram analysis: (1 when the initial grape quantity is sufficiently small, thinning grapes will not be optimal and (2 when the initial grape quantity is high enough, it is optimal to thin grapes from the beginning of the relevant planning horizon and to reduce the quantity over time until the stock of grapes arrives at its optimum. Depending on the model's parameters, the “stopping time” for thinning grapes is reached sooner or later. After the stopping time, grape quantity evolves solely according to natural decay. The results relate to observed dynamics in viticulture and for other horticultural crops.
Neutron density optimal control of A-1 reactor analoque model
International Nuclear Information System (INIS)
Grof, V.
1975-01-01
Two applications are described of the optimal control of a reactor analog model. Both cases consider the control of neutron density. Control loops containing the on-line controlled process, the reactor of the first Czechoslovak nuclear power plant A-1, are simulated on an analog computer. Two versions of the optimal control algorithm are derived using modern control theory (Pontryagin's maximum principle, the calculus of variations, and Kalman's estimation theory), the minimum time performance index, and the quadratic performance index. The results of the optimal control analysis are compared with the A-1 reactor conventional control. (author)
Time dependent optimal switching controls in online selling models
Energy Technology Data Exchange (ETDEWEB)
Bradonjic, Milan [Los Alamos National Laboratory; Cohen, Albert [MICHIGAN STATE UNIV
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
Optimal control of information epidemics modeled as Maki Thompson rumors
Kandhway, Kundan; Kuri, Joy
2014-12-01
We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.
International Nuclear Information System (INIS)
Miller, D.M.
1978-01-01
A micromachining tool system with X- and omega-axes is used to machine spherical, aspherical, and irregular surfaces with a maximum contour error of 100 nonometers (nm) and surface waviness of no more than 0.8 nm RMS. The omega axis, named for the angular measurement of the rotation of an eccentric mechanism supporting one end of a tool bar, enables the pulse increments of the tool toward the workpiece to be as little as 0 to 4.4 nm. A dedicated computer coordinates motion in the two axes to produce the workpiece contour. Inertia is reduced by reducing the mass pulsed toward the workpiece to about one-fifth of its former value. The tool system includes calibration instruments to calibrate the micromachining tool system. Backlash is reduced and flexing decreased by using a rotary table and servomotor to pulse the tool in the omega-axis instead of a ball screw mechanism. A thermally-stabilized spindle roates the workpiece and is driven by a motor not mounted on the micromachining tool base through a torque-smoothing pulley and vibrationless rotary coupling. Abbe offset errors are almost eliminated by tool setting and calibration at spindle center height. Tool contour and workpiece contour are gaged on the machine; this enables the source of machining errors to be determined more readily, because the workpiece is gaged before its shape can be changed by removal from the machine
The potential role of omega-3 fatty acids supplements in increasing athletic performance
Directory of Open Access Journals (Sweden)
Șerban GLIGOR
2017-03-01
Full Text Available Polyunsaturated omega-3 and omega-6 fatty acids are essential fatty acids that cannot be produced by the body itself and therefore must be provided through nutrition. Omega-6 and particularly omega-3 fatty acids have important roles in the organism, contributing to the maintenance and promotion of health. The optimal proportion of omega-6/omega-3 fatty acids is 2:1, or even better 1:1. They are involved in normal growth and development, play a role in the prevention of coronary and cardiovascular diseases, of diabetes mellitus, of arterial hypertension, arthritis and cancer. Omega-3 fatty acids mainly have an anti-inflammatory effect, but also act as hypolipidemic and antithrombotic agents. A potential role of omega-3 fatty acids is that of increasing physical performance. Their role in the physical activity refers on one side to the global health of athletes and on the other side to their anti-inflammatory effect, as high intensity physical exercise induces increased free-radical production and microtraumas, with the induction of an inflammatory status. The anti-inflammatory effect of these fatty acids manifests through an increased production of endogenous antioxidant enzymes, through decreasing the production of prostaglandins metabolites, decreasing the production of leukotriene B4, etc. They are also effective on reducing muscle pain post eccentric exercise and on decreasing the severity of bronchoconstriction induced by exercise, as well as improving pulmonary function variables. In conclusion it seems that supplementing diets with omega-3 fatty acids, apart from having benefic effects on health and on the prevention and management of certain affections, proves to be a beneficial for physical activity and athletic performance.
Optimal Resource Management in a Stochastic Schaefer Model
Richard Hartman
2008-01-01
This paper incorporates uncertainty into the growth function of the Schaefer model for the optimal management of a biological resource. There is a critical value for the biological stock, and it is optimal to do no harvesting if the biological stock is below that critical value and to exert whatever harvesting effort is necessary to prevent the stock from rising above that critical value. The introduction of uncertainty increases the critical value of the stock.
Sparse optimization for inverse problems in atmospheric modelling
Czech Academy of Sciences Publication Activity Database
Adam, Lukáš; Branda, Martin
2016-01-01
Roč. 79, č. 3 (2016), s. 256-266 ISSN 1364-8152 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Inverse modelling * Sparse optimization * Integer optimization * Least squares * European tracer experiment * Free Matlab codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.404, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0457037.pdf
TLM modeling and system identification of optimized antenna structures
Directory of Open Access Journals (Sweden)
N. Fichtner
2008-05-01
Full Text Available The transmission line matrix (TLM method in conjunction with the genetic algorithm (GA is presented for the bandwidth optimization of a low profile patch antenna. The optimization routine is supplemented by a system identification (SI procedure. By the SI the model parameters of the structure are estimated which is used for a reduction of the total TLM simulation time. The SI utilizes a new stability criterion of the physical poles for the parameter extraction.
Study and optimization of the partial discharges in capacitor model ...
African Journals Online (AJOL)
Page 1 ... experiments methodology for the study of such processes, in view of their modeling and optimization. The obtained result is a mathematical model capable to identify the parameters and the interactions between .... 5mn; the next landing is situated in 200 V over the voltage of partial discharges appearance and.
Runtime Optimizations for Tree-Based Machine Learning Models
N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)
2014-01-01
htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression
An Extended Optimal Velocity Model with Consideration of Honk Effect
International Nuclear Information System (INIS)
Tang Tieqiao; Li Chuanyao; Huang Haijun; Shang Huayan
2010-01-01
Based on the OV (optimal velocity) model, we in this paper present an extended OV model with the consideration of the honk effect. The analytical and numerical results illustrate that the honk effect can improve the velocity and flow of uniform flow but that the increments are relevant to the density. (interdisciplinary physics and related areas of science and technology)
Optimal dimensioning model of water distribution systems | Gomes ...
African Journals Online (AJOL)
This study is aimed at developing a pipe-sizing model for a water distribution system. The optimal solution minimises the system's total cost, which comprises the hydraulic network capital cost, plus the capitalised cost of pumping energy. The developed model, called Lenhsnet, may also be used for economical design when ...
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Modeling the optimal management of spent nuclear fuel
International Nuclear Information System (INIS)
Nachlas, J.A.; Kurstedt, H.A. Jr.; Swindle, D.W. Jr.; Korcz, K.O.
1977-01-01
Recent governmental policy decisions dictate that strategies for managing spent nuclear fuel be developed. Two models are constructed to investigate the optimum residence time and the optimal inventory withdrawal policy for fuel material that presently must be stored. The mutual utility of the models is demonstrated through reference case application
Variability aware compact model characterization for statistical circuit design optimization
Qiao, Ying; Qian, Kun; Spanos, Costas J.
2012-03-01
Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.
Meat-based functional foods for dietary equilibrium omega-6/omega-3.
Reglero, Guillermo; Frial, Paloma; Cifuentes, Alejandro; García-Risco, Mónica R; Jaime, Laura; Marin, Francisco R; Palanca, Vicente; Ruiz-Rodríguez, Alejandro; Santoyo, Susana; Señoráns, Francisco J; Soler-Rivas, Cristina; Torres, Carlos; Ibañez, Elena
2008-10-01
Nutritionists encourage improving the diet by combining meat products with fish or other sea-related foods, in order to equilibrate the omega-6/omega-3 ratio. Strong scientific evidence supports the beneficial health effects of a balanced omega-6/omega-3 PUFA (poly unsaturated fatty acids) diets. In the present work, the scientific bases of new functional meat products with both a balanced omega-6/omega-3 ratio and a synergic combination of antioxidants are discussed. The aim is to contribute to the dietary equilibrium omega-6/omega-3 and to increase the antioxidant intake. Conventional meat products supplemented with a specific fatty acids and antioxidants combination led to functional foods with healthier nutritional parameters.
Fuzzy Simulation-Optimization Model for Waste Load Allocation
Directory of Open Access Journals (Sweden)
Motahhare Saadatpour
2006-01-01
Full Text Available This paper present simulation-optimization models for waste load allocation from multiple point sources which include uncertainty due to vagueness of the parameters and goals. This model employs fuzzy sets with appropriate membership functions to deal with uncertainties due to vagueness. The fuzzy waste load allocation model (FWLAM incorporate QUAL2E as a water quality simulation model and Genetic Algorithm (GA as an optimization tool to find the optimal combination of the fraction removal level to the dischargers and pollution control agency (PCA. Penalty functions are employed to control the violations in the system. The results demonstrate that the goal of PCA to achieve the best water quality and the goal of the dischargers to use the full assimilative capacity of the river have not been satisfied completely and a compromise solution between these goals is provided. This fuzzy optimization model with genetic algorithm has been used for a hypothetical problem. Results demonstrate a very suitable convergence of proposed optimization algorithm to the global optima.
FY14 LLNL OMEGA Experimental Programs
Energy Technology Data Exchange (ETDEWEB)
Heeter, R. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fournier, K. B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Baker, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Barrios, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bernstein, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brown, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Celliers, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chen, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coppari, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fratanduono, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Johnson, M. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Huntington, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jenei, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kraus, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ma, T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Martinez, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McNabb, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Millot, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moore, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nagel, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Park, H. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Patel, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Perez, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ping, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pollock, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ross, J. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rygg, J. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Smith, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zylstra, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Collins, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Landen, O. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hsing, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-10-13
In FY14, LLNL’s High-Energy-Density Physics (HED) and Indirect Drive Inertial Confinement Fusion (ICF-ID) programs conducted several campaigns on the OMEGA laser system and on the EP laser system, as well as campaigns that used the OMEGA and EP beams jointly. Overall these LLNL programs led 324 target shots in FY14, with 246 shots using just the OMEGA laser system, 62 shots using just the EP laser system, and 16 Joint shots using Omega and EP together. Approximately 31% of the total number of shots (62 OMEGA shots, 42 EP shots) shots supported the Indirect Drive Inertial Confinement Fusion Campaign (ICF-ID). The remaining 69% (200 OMEGA shots and 36 EP shots, including the 16 Joint shots) were dedicated to experiments for High- Energy-Density Physics (HED). Highlights of the various HED and ICF campaigns are summarized in the following reports.
FY15 LLNL OMEGA Experimental Programs
Energy Technology Data Exchange (ETDEWEB)
Heeter, R. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Baker, K. L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Barrios, M. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Beckwith, M. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Casey, D. T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Celliers, P. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chen, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coppari, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fournier, K. B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fratanduono, D. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Frenje, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Huntington, C. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kraus, R. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lazicki, A. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Martinez, D. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McNaney, J. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Millot, M. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pak, A. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Park, H. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ping, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pollock, B. B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Smith, R. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wehrenberg, C. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Widmann, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Collins, G. W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Landen, O. L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hsing, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-12-04
In FY15, LLNL’s High-Energy-Density Physics (HED) and Indirect Drive Inertial Confinement Fusion (ICF-ID) programs conducted several campaigns on the OMEGA laser system and on the EP laser system, as well as campaigns that used the OMEGA and EP beams jointly. Overall these LLNL programs led 468 target shots in FY15, with 315 shots using just the OMEGA laser system, 145 shots using just the EP laser system, and 8 Joint shots using Omega and EP together. Approximately 25% of the total number of shots (56 OMEGA shots and 67 EP shots, including the 8 Joint shots) supported the Indirect Drive Inertial Confinement Fusion Campaign (ICF-ID). The remaining 75% (267 OMEGA shots and 86 EP shots) were dedicated to experiments for High-Energy-Density Physics (HED). Highlights of the various HED and ICF campaigns are summarized in the following reports.
Decision Support Model for Optimal Management of Coastal Gate
Ditthakit, Pakorn; Chittaladakorn, Suwatana
2010-05-01
The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.
Kuroda, T; Ohta, H; Onoe, Y; Tsugawa, N; Shiraki, M
2017-10-01
This study investigated the relationships between intakes of polyunsaturated fatty acids, omega-3 fatty acids, and omega-6 fatty acids and bone mineral density in Japanese women aged 19 to 25 years. Intakes of omega-3 fatty acids (n-3) were positively associated with peak bone mass at the hip. Lifestyle factors such as physical activity and nutrition intake are known to optimize the peak bone mass (PBM). Recently, intake of polyunsaturated fatty acids (PUFAs) has been reported to contribute to bone metabolism. In this study, the relationships of intakes of n-3 and omega-6 (n-6) fatty acids with PBM were evaluated in Japanese female subjects. A total of 275 healthy female subjects (19-25 years) having PBM were enrolled, and lumbar and total hip bone mineral density (BMD) and bone metabolic parameters were measured. Dietary intakes of total energy, total n-3 fatty acids, eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and total n-6 fatty acids were assessed by a self-administered questionnaire. Physical activity information was also assessed. The mean ± SD age was 20.6 ± 1.4 years, and BMI was 21.2 ± 2.7 kg/m 2 . BMI and serum bone alkaline phosphatase contributed significantly to lumbar BMD on multiple regression analysis. Intake of n-3 fatty acids and physical activity were also significantly related to total hip BMD. Using EPA or DHA instead of total n-3 fatty acids in the model did not result in a significant result. Adequate total n-3 fatty acid intake may help maximize PBM at the hip.
Best management practices (BMPs) are perceived as being effective in reducing nutrient loads transported from non-point sources (NPS) to receiving water bodies. The objective of this study was to develop a modeling-optimization framework that can be used by watershed management p...
Comparison of Omega-2 and Omega-3 calibration explosions basing on regional seismic data
International Nuclear Information System (INIS)
Mikhajlova, N.N.; Sokolova, I.N.
2001-01-01
Comparison of different parameters of seismic records of Omega-2 and Omega-3 calibration explosions was performed. It was shown that despite the equal charge the level of seismic oscillations was lower during the Omega-3 explosion than during Omega-2. Spectral composition, polarization of oscillations, wave picture is identical at a given station for both explosions. Assumptions were made on the reason of such difference in seismic effect. (author)
Modeling and energy efficiency optimization of belt conveyors
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2011-01-01
Highlights: → We take optimization approach to improve operation efficiency of belt conveyors. → An analytical energy model, originating from ISO 5048, is proposed. → Then an off-line and an on-line parameter estimation schemes are investigated. → In a case study, six optimization problems are formulated with solutions in simulation. - Abstract: The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment and operation levels. Specifically, variable speed control, an equipment level intervention, is recommended to improve operation efficiency of belt conveyors. However, the current implementations mostly focus on lower level control loops without operational considerations at the system level. This paper intends to take a model based optimization approach to improve the efficiency of belt conveyors at the operational level. An analytical energy model, originating from ISO 5048, is firstly proposed, which lumps all the parameters into four coefficients. Subsequently, both an off-line and an on-line parameter estimation schemes are applied to identify the new energy model, respectively. Simulation results are presented for the estimates of the four coefficients. Finally, optimization is done to achieve the best operation efficiency of belt conveyors under various constraints. Six optimization problems of a typical belt conveyor system are formulated, respectively, with solutions in simulation for a case study.
A stochastic discrete optimization model for designing container terminal facilities
Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista
2017-11-01
As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.
Hierarchical Swarm Model: A New Approach to Optimization
Directory of Open Access Journals (Sweden)
Hanning Chen
2010-01-01
Full Text Available This paper presents a novel optimization model called hierarchical swarm optimization (HSO, which simulates the natural hierarchical complex system from where more complex intelligence can emerge for complex problems solving. This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. This performance improvement is obtained by constructing the HSO hierarchies, which means that an agent in a higher level swarm can be composed of swarms of other agents from lower level and different swarms of different levels evolve on different spatiotemporal scale. A novel optimization algorithm (named PS2O, based on the HSO model, is instantiated and tested to illustrate the ideas of HSO model clearly. Experiments were conducted on a set of 17 benchmark optimization problems including both continuous and discrete cases. The results demonstrate remarkable performance of the PS2O algorithm on all chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms.
Optimization of turning process through the analytic flank wear modelling
Del Prete, A.; Franchi, R.; De Lorenzis, D.
2018-05-01
In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.
DEFF Research Database (Denmark)
Jacobsen, Charlotte
Due to the health beneficial effects of marine omega-3 fatty acids there is an increasing interest in developing functional foods containing these healthy fatty acids. However, such foods are very susceptible to lipid oxidation, which will give rise to undesirable off-flavours and unhealthy...... oxidation products. Efficients strategies to prevent lipid oxidation are therefore required. Such strategies include addition of antioxidants or the use of omega-3 delivery emulsions. However, antioxidant efficacy in complex omega-3 enriched foods are influenced by many factors including the lipophilicity...... of the antioxidants. Selection of the optimal antioxidant system is therefore a major challenge. Likewise, a range of factors can influence the ability of omega-3 delivery systems to protect the omega-3 fatty acids against oxidation after addition to food systems. These challenges will be discussed...
Optimal Patent Life in a Variety-Expansion Growth Model
Lin, Hwan C.
2013-01-01
This paper presents more channels through which the optimal patent life is determined in a R&D-based endogenous growth model that permits growth of new varieties of consumer goods over time. Its modeling features include an endogenous hazard rate facing incumbent monopolists, the prevalence of research congestion, and the aggregate welfare importance of product differentiation. As a result, a patent’s effective life is endogenized and less than its legal life. The model is calibrated to a glo...
An aircraft noise pollution model for trajectory optimization
Barkana, A.; Cook, G.
1976-01-01
A mathematical model describing the generation of aircraft noise is developed with the ultimate purpose of reducing noise (noise-optimizing landing trajectories) in terminal areas. While the model is for a specific aircraft (Boeing 737), the methodology would be applicable to a wide variety of aircraft. The model is used to obtain a footprint on the ground inside of which the noise level is at or above 70 dB.
Optimization algorithms intended for self-tuning feedwater heater model
International Nuclear Information System (INIS)
Czop, P; Barszcz, T; Bednarz, J
2013-01-01
This work presents a self-tuning feedwater heater model. This work continues the work on first-principle gray-box methodology applied to diagnostics and condition assessment of power plant components. The objective of this work is to review and benchmark the optimization algorithms regarding the time required to achieve the best model fit to operational power plant data. The paper recommends the most effective algorithm to be used in the model adjustment process.
Group Elevator Peak Scheduling Based on Robust Optimization Model
Directory of Open Access Journals (Sweden)
ZHANG, J.
2013-08-01
Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.
Development of optimized dosimetric models for HDR brachytherapy
International Nuclear Information System (INIS)
Thayalan, K.; Jagadeesan, M.
2003-01-01
High dose rate brachytherapy (HDRB) systems are in clinical use for more than four decades particularly in cervical cancer. Optimization is the method to produce dose distribution which assures that doses are not compromised at the treatment sites whilst reducing the risk of overdosing critical organs. Hence HDRB optimization begins with the desired dose distribution and requires the calculations of the relative weighting factors for each dwell position with out changing the source activity. The optimization for Ca. uterine cervix treatment is simply duplication of the dose distribution used for Low dose rate (LDR) applications. In the present work, two optimized dosimetric models were proposed and studied thoroughly, to suit the local clinical conditions. These models are named as HDR-C and HDR-D, where C and D represent configuration and distance respectively. These models duplicate exactly the LDR pear shaped dose distribution, which is a golden standard. The validity of these models is tested in different clinical situations and in actual patients (n=92). These models: HDR-C and HDR-D reduce bladder dose by 11.11% and 10% and rectal dose by 8% and 7% respectively. The treatment time is also reduced by 12-14%. In a busy hospital setup, these models find a place to cater large number of patients, while addressing individual patients geometry. (author)
Discounted cost model for condition-based maintenance optimization
International Nuclear Information System (INIS)
Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van
2010-01-01
This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.
Optimization of morphing flaps based on fluid structure interaction modeling
DEFF Research Database (Denmark)
Barlas, Athanasios; Akay, Busra
2018-01-01
This article describes the design optimization of morphing trailing edge flaps for wind turbines with ‘smart blades’. A high fidelity Fluid Structure Interaction (FSI) simulation framework is utilized, comprised of 2D Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) models....... A coupled aero-structural simulation of a 10% chordwise length morphing trailing edge flap for a 4 MW wind turbine rotor is carried out and response surfaces are produced with respect to the flap internal geometry design parameters for the design conditions. Surrogate model based optimization is applied...
Innovative supply chain optimization models with multiple uncertainty factors
DEFF Research Database (Denmark)
Choi, Tsan Ming; Govindan, Kannan; Li, Xiang
2017-01-01
Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today’s business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate...... to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models...
Directory of Open Access Journals (Sweden)
Hediyeh Karimi
2013-01-01
Full Text Available It has been predicted that the nanomaterials of graphene will be among the candidate materials for postsilicon electronics due to their astonishing properties such as high carrier mobility, thermal conductivity, and biocompatibility. Graphene is a semimetal zero gap nanomaterial with demonstrated ability to be employed as an excellent candidate for DNA sensing. Graphene-based DNA sensors have been used to detect the DNA adsorption to examine a DNA concentration in an analyte solution. In particular, there is an essential need for developing the cost-effective DNA sensors holding the fact that it is suitable for the diagnosis of genetic or pathogenic diseases. In this paper, particle swarm optimization technique is employed to optimize the analytical model of a graphene-based DNA sensor which is used for electrical detection of DNA molecules. The results are reported for 5 different concentrations, covering a range from 0.01 nM to 500 nM. The comparison of the optimized model with the experimental data shows an accuracy of more than 95% which verifies that the optimized model is reliable for being used in any application of the graphene-based DNA sensor.
Energy Technology Data Exchange (ETDEWEB)
Benakli, Karim; Darmé, Luc; Goodsell, Mark D. [Sorbonne Universités, UPMC Univ Paris 06, UMR 7589,LPTHE, F-75005, Paris (France); CNRS, UMR 7589,LPTHE, F-75005, Paris (France)
2015-11-16
We study two realisations of the Fake Split Supersymmetry Model (FSSM), the simplest model that can easily reproduce the experimental value of the Higgs mass for an arbitrarily high supersymmetry scale M{sub S}, as a consequence of swapping higgsinos for equivalent states, fake higgsinos, with suppressed Yukawa couplings. If the LSP is identified as the main Dark matter component, then a standard thermal history of the Universe implies upper bounds on M{sub S}, which we derive. On the other hand, we show that renormalisation group running of soft masses aboveM{sub S} barely constrains the model — in stark contrast to Split Supersymmetry — and hence we can have a “Mega Split” spectrum even with all of these assumptions and constraints, which include the requirements of a correct relic abundance, a gluino life-time compatible with Big Bang Nucleosynthesis and absence of signals in present direct detection experiments of inelastic dark matter. In an appendix we describe a related scenario, Fake Split Extended Supersymmetry, which enjoys similar properties.
GRAVITATIONAL LENS MODELING WITH GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZERS
International Nuclear Information System (INIS)
Rogers, Adam; Fiege, Jason D.
2011-01-01
Strong gravitational lensing of an extended object is described by a mapping from source to image coordinates that is nonlinear and cannot generally be inverted analytically. Determining the structure of the source intensity distribution also requires a description of the blurring effect due to a point-spread function. This initial study uses an iterative gravitational lens modeling scheme based on the semilinear method to determine the linear parameters (source intensity profile) of a strongly lensed system. Our 'matrix-free' approach avoids construction of the lens and blurring operators while retaining the least-squares formulation of the problem. The parameters of an analytical lens model are found through nonlinear optimization by an advanced genetic algorithm (GA) and particle swarm optimizer (PSO). These global optimization routines are designed to explore the parameter space thoroughly, mapping model degeneracies in detail. We develop a novel method that determines the L-curve for each solution automatically, which represents the trade-off between the image χ 2 and regularization effects, and allows an estimate of the optimally regularized solution for each lens parameter set. In the final step of the optimization procedure, the lens model with the lowest χ 2 is used while the global optimizer solves for the source intensity distribution directly. This allows us to accurately determine the number of degrees of freedom in the problem to facilitate comparison between lens models and enforce positivity on the source profile. In practice, we find that the GA conducts a more thorough search of the parameter space than the PSO.
Hyperopt: a Python library for model selection and hyperparameter optimization
Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.
2015-01-01
Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.
He, L; Huang, G H; Lu, H W
2010-04-15
Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the "true" ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes. 2009 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
He, L., E-mail: li.he@ryerson.ca [Department of Civil Engineering, Faculty of Engineering, Architecture and Science, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3 (Canada); Huang, G.H. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada); College of Urban Environmental Sciences, Peking University, Beijing 100871 (China); Lu, H.W. [Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, S4S 0A2 (Canada)
2010-04-15
Solving groundwater remediation optimization problems based on proxy simulators can usually yield optimal solutions differing from the 'true' ones of the problem. This study presents a new stochastic optimization model under modeling uncertainty and parameter certainty (SOMUM) and the associated solution method for simultaneously addressing modeling uncertainty associated with simulator residuals and optimizing groundwater remediation processes. This is a new attempt different from the previous modeling efforts. The previous ones focused on addressing uncertainty in physical parameters (i.e. soil porosity) while this one aims to deal with uncertainty in mathematical simulator (arising from model residuals). Compared to the existing modeling approaches (i.e. only parameter uncertainty is considered), the model has the advantages of providing mean-variance analysis for contaminant concentrations, mitigating the effects of modeling uncertainties on optimal remediation strategies, offering confidence level of optimal remediation strategies to system designers, and reducing computational cost in optimization processes.
A model for optimization of process integration investments under uncertainty
International Nuclear Information System (INIS)
Svensson, Elin; Stroemberg, Ann-Brith; Patriksson, Michael
2011-01-01
The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency. -- Highlights: → Stochastic programming approach to long-term planning of process integration investments. → Extensive mathematical model formulation. → Multi-stage investment decisions and scenario-based modelling of uncertain energy prices. → Results illustrate how investments made now affect later investment and operation opportunities. → Approach for evaluation of robustness with respect to variations in probability distribution.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik
2008-01-01
is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....
Optimization model for rotor blades of horizontal axis wind turbines
Institute of Scientific and Technical Information of China (English)
LIU Xiong; CHEN Yan; YE Zhiquan
2007-01-01
This paper presents an optimization model for rotor blades of horizontal axis wind turbines. The model refers to the wind speed distribution function on the specific wind site, with an objective to satisfy the maximum annual energy output. To speed up the search process and guarantee a global optimal result, the extended compact genetic algorithm (ECGA) is used to carry out the search process.Compared with the simple genetic algorithm, ECGA runs much faster and can get more accurate results with a much smaller population size and fewer function evaluations. Using the developed optimization program, blades of a 1.3 MW stall-regulated wind turbine are designed. Compared with the existing blades, the designed blades have obviously better aerodynamic performance.
Modeling of biological intelligence for SCM system optimization.
Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang
2012-01-01
This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.
Optimization of Excitation in FDTD Method and Corresponding Source Modeling
Directory of Open Access Journals (Sweden)
B. Dimitrijevic
2015-04-01
Full Text Available Source and excitation modeling in FDTD formulation has a significant impact on the method performance and the required simulation time. Since the abrupt source introduction yields intensive numerical variations in whole computational domain, a generally accepted solution is to slowly introduce the source, using appropriate shaping functions in time. The main goal of the optimization presented in this paper is to find balance between two opposite demands: minimal required computation time and acceptable degradation of simulation performance. Reducing the time necessary for source activation and deactivation is an important issue, especially in design of microwave structures, when the simulation is intensively repeated in the process of device parameter optimization. Here proposed optimized source models are realized and tested within an own developed FDTD simulation environment.
Modeling of Biological Intelligence for SCM System Optimization
Directory of Open Access Journals (Sweden)
Shengyong Chen
2012-01-01
Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.
Modeling of Biological Intelligence for SCM System Optimization
Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang
2012-01-01
This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724
On the errors on Omega(0): Monte Carlo simulations of the EMSS cluster sample
DEFF Research Database (Denmark)
Oukbir, J.; Arnaud, M.
2001-01-01
We perform Monte Carlo simulations of synthetic EMSS cluster samples, to quantify the systematic errors and the statistical uncertainties on the estimate of Omega (0) derived from fits to the cluster number density evolution and to the X-ray temperature distribution up to z=0.83. We identify...... the scatter around the relation between cluster X-ray luminosity and temperature to be a source of systematic error, of the order of Delta (syst)Omega (0) = 0.09, if not properly taken into account in the modelling. After correcting for this bias, our best Omega (0) is 0.66. The uncertainties on the shape...
Pareto-Optimal Model Selection via SPRINT-Race.
Zhang, Tiantian; Georgiopoulos, Michael; Anagnostopoulos, Georgios C
2018-02-01
In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of Pareto-optimal models that optimize by compromising more than one predefined objectives simultaneously. This paper introduces SPRINT-Race, the first multi-objective racing algorithm in a fixed-confidence setting, which is based on the sequential probability ratio with indifference zone test. SPRINT-Race addresses the problem of MOMS with multiple stochastic optimization objectives in the proper Pareto-optimality sense. In SPRINT-Race, a pairwise dominance or non-dominance relationship is statistically inferred via a non-parametric, ternary-decision, dual-sequential probability ratio test. The overall probability of falsely eliminating any Pareto-optimal models or mistakenly returning any clearly dominated models is strictly controlled by a sequential Holm's step-down family-wise error rate control method. As a fixed-confidence model selection algorithm, the objective of SPRINT-Race is to minimize the computational effort required to achieve a prescribed confidence level about the quality of the returned models. The performance of SPRINT-Race is first examined via an artificially constructed MOMS problem with known ground truth. Subsequently, SPRINT-Race is applied on two real-world applications: 1) hybrid recommender system design and 2) multi-criteria stock selection. The experimental results verify that SPRINT-Race is an effective and efficient tool for such MOMS problems. code of SPRINT-Race is available at https://github.com/watera427/SPRINT-Race.
Comparisons of criteria in the assessment model parameter optimizations
International Nuclear Information System (INIS)
Liu Xinhe; Zhang Yongxing
1993-01-01
Three criteria (chi square, relative chi square and correlation coefficient) used in model parameter optimization (MPO) process that aims at significant reduction of prediction uncertainties were discussed and compared to each other with the aid of a well-controlled tracer experiment
The Optimal Portfolio Selection Model under g-Expectation
Directory of Open Access Journals (Sweden)
Li Li
2014-01-01
complicated and sophisticated, the optimal solution turns out to be surprisingly simple, the payoff of a portfolio of two binary claims. Also I give the economic meaning of my model and the comparison with that one in the work of Jin and Zhou, 2008.
Real-Time Optimization for Economic Model Predictive Control
DEFF Research Database (Denmark)
Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca
2012-01-01
In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...
Optimal Tax Reduction by Depreciation : A Stochastic Model
Berg, M.; De Waegenaere, A.M.B.; Wielhouwer, J.L.
1996-01-01
This paper focuses on the choice of a depreciation method, when trying to minimize the expected value of the present value of future tax payments.In a quite general model that allows for stochastic future cash- ows and a tax structure with tax brackets, we determine the optimal choice between the
Multiscale modeling and topology optimization of poroelastic actuators
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe; Sigmund, Ole
2012-01-01
This paper presents a method for design of optimized poroelastic materials which under internal pressurization turn into actuators for application in, for example, linear motors. The actuators are modeled in a two-scale fluid–structure interaction approach. The fluid saturated material microstruc...
Heister, A.; Barate, R.; De Bonis, I.; Decamp, D.; Goy, C.; Lees, J.P.; Merle, E.; Minard, M.N.; Pietrzyk, B.; Boix, G.; Bravo, S.; Casado, M.P.; Chmeissani, M.; Crespo, J.M.; Fernandez, E.; Fernandez-Bosman, M.; Garrido, L.; Grauges, E.; Martinez, M.; Merino, G.; Miquel, R.; Mir, L.M.; Pacheco, A.; Ruiz, H.; Colaleo, A.; Creanza, D.; de Palma, M.; Iaselli, G.; Maggi, G.; Maggi, M.; Nuzzo, S.; Ranieri, A.; Raso, G.; Ruggieri, F.; Selvaggi, G.; Silvestris, L.; Tempesta, P.; Tricomi, A.; Zito, G.; Huang, X.; Lin, J.; Ouyang, Q.; Wang, T.; Xie, Y.; Xu, R.; Xue, S.; Zhang, J.; Zhang, L.; Zhao, W.; Abbaneo, D.; Azzurri, P.; Buchmuller, O.; Cattaneo, M.; Cerutti, F.; Clerbaux, B.; Drevermann, H.; Forty, R.W.; Frank, M.; Gianotti, F.; Greening, T.C.; Hansen, J.B.; Harvey, J.; Hutchcroft, D.E.; Janot, P.; Jost, B.; Kado, M.; Mato, P.; Moutoussi, A.; Ranjard, F.; Rolandi, Gigi; Schlatter, D.; Schneider, O.; Sguazzoni, G.; Tejessy, W.; Teubert, F.; Valassi, A.; Videau, I.; Ward, J.; Badaud, F.; Falvard, A.; Gay, P.; Henrard, P.; Jousset, J.; Michel, B.; Monteil, S.; Montret, J-C.; Pallin, D.; Perret, P.; Hansen, J.D.; Hansen, J.R.; Hansen, P.H.; Nilsson, B.S.; Waananen, A.; Kyriakis, A.; Markou, C.; Simopoulou, E.; Vayaki, A.; Zachariadou, K.; Blondel, A.; Bonneaud, G.; Brient, J.-C.; Rouge, A.; Rumpf, M.; Swynghedauw, M.; Verderi, M.; Videau, H.; Ciulli, V.; Focardi, E.; Parrini, G.; Antonelli, A.; Antonelli, M.; Bencivenni, G.; Bologna, G.; Bossi, F.; Campana, P.; Capon, G.; Chiarella, V.; Laurelli, P.; Mannocchi, G.; Murtas, F.; Murtas, G.P.; Passalacqua, L.; Pepe-Altarelli, M.; Spagnolo, P.; Halley, A.; Lynch, J.G.; Negus, P.; O'Shea, V.; Raine, C.; Thompson, A.S.; Wasserbaech, S.; Cavanaugh, R.; Dhamotharan, S.; Geweniger, C.; Hanke, P.; Hansper, G.; Hepp, V.; Kluge, E.E.; Putzer, A.; Sommer, J.; Tittel, K.; Werner, S.; Wunsch, M.; Beuselinck, R.; Binnie, D.M.; Cameron, W.; Dornan, P.J.; Girone, M.; Marinelli, N.; Sedgbeer, J.K.; Thompson, J.C.; Ghete, V.M.; Girtler, P.; Kneringer, E.; Kuhn, D.; Rudolph, G.; Bouhova-Thacker, E.; Bowdery, C.K.; Finch, A.J.; Foster, F.; Hughes, G.; Jones, R.W.L.; Pearson, M.R.; Robertson, N.A.; Jakobs, K.; Kleinknecht, K.; Quast, G.; Renk, B.; Sander, H.G.; Wachsmuth, H.; Zeitnitz, C.; Bonissent, A.; Carr, J.; Coyle, P.; Leroy, O.; Payre, P.; Rousseau, D.; Talby, M.; Ragusa, F.; David, A.; Dietl, H.; Ganis, G.; Huttmann, K.; Lutjens, G.; Mannert, C.; Manner, W.; Moser, H.G.; Settles, R.; Stenzel, H.; Wiedenmann, W.; Wolf, G.; Boucrot, J.; Callot, O.; Davier, M.; Duflot, L.; Grivaz, J.F.; Heusse, P.; Jacholkowska, A.; Lefrancois, J.; Veillet, J.J.; Yuan, C.; Bagliesi, Giuseppe; Boccali, T.; Foa, L.; Giammanco, A.; Giassi, A.; Ligabue, F.; Messineo, A.; Palla, F.; Sanguinetti, G.; Sciaba, A.; Tenchini, R.; Venturi, A.; Verdini, P.G.; Blair, G.A.; Cowan, G.; Green, M.G.; Medcalf, T.; Misiejuk, A.; Strong, J.A.; Teixeira-Dias, P.; von Wimmersperg-Toeller, J.H.; Clifft, R.W.; Edgecock, T.R.; Norton, P.R.; Tomalin, I.R.; Bloch-Devaux, Brigitte; Colas, P.; Emery, S.; Kozanecki, W.; Lancon, E.; Lemaire, M.C.; Locci, E.; Perez, P.; Rander, J.; Renardy, J.F.; Roussarie, A.; Schuller, J.P.; Schwindling, J.; Trabelsi, A.; Vallage, B.; Konstantinidis, N.; Litke, A.M.; Taylor, G.; Beddall, A.; Booth, C.N.; Cartwright, S.; Combley, F.; Lehto, M.; Thompson, L.F.; Affholderbach, K.; Boehrer, Armin; Brandt, S.; Grupen, C.; Ngac, A.; Prange, G.; Sieler, U.; Giannini, G.; Rothberg, J.; Armstrong, S.R.; Berkelman, Karl; Cranmer, K.; Ferguson, D.P.S.; Gao, Y.; Gonzalez, S.; Hayes, O.J.; Hu, H.; Jin, S.; Kile, J.; McNamara, P.A., III; Nielsen, J.; Pan, Y.B.; von Wimmersperg-Toeller, J.H.; Wiedenmann, W.; Wu, J.; Wu, Sau Lan; Wu, X.; Zobernig, G.
2002-01-01
The inclusive production of the omega(782) vector meson in hadronic Z decays is measured and compared to model predictions. The analysis is based on 4 million hadronic Z decays recorded by the ALEPH detector between 1991 and 1995. The production rate for x_p = p_meson/p_beam > 0.05 is measured in the omega -> pi^+ pi^- pi^0 decay mode and found to be 0.585 +- 0.019_stat +- 0.033_sys per event. Inclusive eta meson production is also measured in the same decay channel for x_p > 0.10, obtaining 0.355 +- 0.011_stat +- 0.024_sys per event. The branching ratio for omega -> mu^+ mu^- is investigated. A total of 18.1 +- 5.9 events are observed, from which the muonic branching ratio is measured for the first time to be BR(omega -> mu^+ mu^-) = (9.0 +- 2.9_stat +- 1.1_sys)*10^-5.
A Multiobjective Optimization Model in Automotive Supply Chain Networks
Directory of Open Access Journals (Sweden)
Abdolhossein Sadrnia
2013-01-01
Full Text Available In the new decade, green investment decisions are attracting more interest in design supply chains due to the hidden economic benefits and environmental legislative barriers. In this paper, a supply chain network design problem with both economic and environmental concerns is presented. Therefore, a multiobjective optimization model that captures the trade-off between the total logistics cost and CO2 emissions is proposed. With regard to the complexity of logistic networks, a new multiobjective swarm intelligence algorithm known as a multiobjective Gravitational search algorithm (MOGSA has been implemented for solving the proposed mathematical model. To evaluate the effectiveness of the model, a comprehensive set of numerical experiments is explained. The results obtained show that the proposed model can be applied as an effective tool in strategic planning for optimizing cost and CO2 emissions in an environmentally friendly automotive supply chain.
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
Optimal inference with suboptimal models: Addiction and active Bayesian inference
Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl
2015-01-01
When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321
Galerkin v. discrete-optimal projection in nonlinear model reduction
Energy Technology Data Exchange (ETDEWEB)
Carlberg, Kevin Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Barone, Matthew Franklin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Antil, Harbir [George Mason Univ., Fairfax, VA (United States)
2015-04-01
Discrete-optimal model-reduction techniques such as the Gauss{Newton with Approximated Tensors (GNAT) method have shown promise, as they have generated stable, accurate solutions for large-scale turbulent, compressible ow problems where standard Galerkin techniques have failed. However, there has been limited comparative analysis of the two approaches. This is due in part to difficulties arising from the fact that Galerkin techniques perform projection at the time-continuous level, while discrete-optimal techniques do so at the time-discrete level. This work provides a detailed theoretical and experimental comparison of the two techniques for two common classes of time integrators: linear multistep schemes and Runge{Kutta schemes. We present a number of new ndings, including conditions under which the discrete-optimal ROM has a time-continuous representation, conditions under which the two techniques are equivalent, and time-discrete error bounds for the two approaches. Perhaps most surprisingly, we demonstrate both theoretically and experimentally that decreasing the time step does not necessarily decrease the error for the discrete-optimal ROM; instead, the time step should be `matched' to the spectral content of the reduced basis. In numerical experiments carried out on a turbulent compressible- ow problem with over one million unknowns, we show that increasing the time step to an intermediate value decreases both the error and the simulation time of the discrete-optimal reduced-order model by an order of magnitude.
[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].
Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang
2011-12-01
To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.
Statistical study of auroral omega bands
Directory of Open Access Journals (Sweden)
N. Partamies
2017-09-01
Full Text Available The presence of very few statistical studies on auroral omega bands motivated us to test-use a semi-automatic method for identifying large-scale undulations of the diffuse aurora boundary and to investigate their occurrence. Five identical all-sky cameras with overlapping fields of view provided data for 438 auroral omega-like structures over Fennoscandian Lapland from 1996 to 2007. The results from this set of omega band events agree remarkably well with previous observations of omega band occurrence in magnetic local time (MLT, lifetime, location between the region 1 and 2 field-aligned currents, as well as current density estimates. The average peak emission height of omega forms corresponds to the estimated precipitation energies of a few keV, which experienced no significant change during the events. Analysis of both local and global magnetic indices demonstrates that omega bands are observed during substorm expansion and recovery phases that are more intense than average substorm expansion and recovery phases in the same region. The omega occurrence with respect to the substorm expansion and recovery phases is in a very good agreement with an earlier observed distribution of fast earthward flows in the plasma sheet during expansion and recovery phases. These findings support the theory that omegas are produced by fast earthward flows and auroral streamers, despite the rarity of good conjugate observations.
FY16 LLNL Omega Experimental Programs
Energy Technology Data Exchange (ETDEWEB)
Heeter, R. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ali, S. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Benstead, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Celliers, P. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coppari, F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Eggert, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Erskine, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Panella, A. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fratanduono, D. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hua, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Huntington, C. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jarrott, L. C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jiang, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kraus, R. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lazicki, A. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); LePape, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Martinez, D. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); McNaney, J. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Millot, M. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moody, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pak, A. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Park, H. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ping, Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pollock, B. B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rinderknecht, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ross, J. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rubery, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sio, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Smith, R. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Swadling, G. F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wehrenberg, C. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Collins, G. W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Landen, O. L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hsing, W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-12-01
In FY16, LLNL’s High-Energy-Density Physics (HED) and Indirect Drive Inertial Confinement Fusion (ICF-ID) programs conducted several campaigns on the OMEGA laser system and on the EP laser system, as well as campaigns that used the OMEGA and EP beams jointly. Overall, these LLNL programs led 430 target shots in FY16, with 304 shots using just the OMEGA laser system, and 126 shots using just the EP laser system. Approximately 21% of the total number of shots (77 OMEGA shots and 14 EP shots) supported the Indirect Drive Inertial Confinement Fusion Campaign (ICF-ID). The remaining 79% (227 OMEGA shots and 112 EP shots) were dedicated to experiments for High-Energy-Density Physics (HED). Highlights of the various HED and ICF campaigns are summarized in the following reports. In addition to these experiments, LLNL Principal Investigators led a variety of Laboratory Basic Science campaigns using OMEGA and EP, including 81 target shots using just OMEGA and 42 shots using just EP. The highlights of these are also summarized, following the ICF and HED campaigns. Overall, LLNL PIs led a total of 553 shots at LLE in FY 2016. In addition, LLNL PIs also supported 57 NLUF shots on Omega and 31 NLUF shots on EP, in collaboration with the academic community.
FY16 LLNL Omega Experimental Programs
International Nuclear Information System (INIS)
Heeter, R. F.; Ali, S. J.; Benstead, J.; Celliers, P. M.; Coppari, F.; Eggert, J.; Erskine, D.; Panella, A. F.; Fratanduono, D. E.; Hua, R.; Huntington, C. M.; Jarrott, L. C.; Jiang, S.; Kraus, R. G.; Lazicki, A. E.; LePape, S.; Martinez, D. A.; McNaney, J. M.; Millot, M. A.; Moody, J.; Pak, A. E.; Park, H. S.; Ping, Y.; Pollock, B. B.; Rinderknecht, H.; Ross, J. S.; Rubery, M.; Sio, H.; Smith, R. F.; Swadling, G. F.; Wehrenberg, C. E.; Collins, G. W.; Landen, O. L.; Wan, A.; Hsing, W.
2016-01-01
In FY16, LLNL's High-Energy-Density Physics (HED) and Indirect Drive Inertial Confinement Fusion (ICF-ID) programs conducted several campaigns on the OMEGA laser system and on the EP laser system, as well as campaigns that used the OMEGA and EP beams jointly. Overall, these LLNL programs led 430 target shots in FY16, with 304 shots using just the OMEGA laser system, and 126 shots using just the EP laser system. Approximately 21% of the total number of shots (77 OMEGA shots and 14 EP shots) supported the Indirect Drive Inertial Confinement Fusion Campaign (ICF-ID). The remaining 79% (227 OMEGA shots and 112 EP shots) were dedicated to experiments for High-Energy-Density Physics (HED). Highlights of the various HED and ICF campaigns are summarized in the following reports. In addition to these experiments, LLNL Principal Investigators led a variety of Laboratory Basic Science campaigns using OMEGA and EP, including 81 target shots using just OMEGA and 42 shots using just EP. The highlights of these are also summarized, following the ICF and HED campaigns. Overall, LLNL PIs led a total of 553 shots at LLE in FY 2016. In addition, LLNL PIs also supported 57 NLUF shots on Omega and 31 NLUF shots on EP, in collaboration with the academic community.
Challenges when developing omega-3 enriched foods
DEFF Research Database (Denmark)
Jacobsen, Charlotte
2010-01-01
the influence of important factors such as oil quality, delivery systems for omega-3 fatty acids, processing conditions, composition of the food matrix on lipid oxidation in different omega-3 enriched foods (milk, yoghurt, mayonnaise and mayonnaise-based salads, dressing, energy bar and fish paté). Moreover...
Optimal Designs for the Generalized Partial Credit Model
Bürkner, Paul-Christian; Schwabe, Rainer; Holling, Heinz
2018-01-01
Analyzing ordinal data becomes increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and finds application in many large scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons' abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We will derive t...
Hybrid Modeling and Optimization of Yogurt Starter Culture Continuous Fermentation
Directory of Open Access Journals (Sweden)
Silviya Popova
2009-10-01
Full Text Available The present paper presents a hybrid model of yogurt starter mixed culture fermentation. The main nonlinearities within a classical structure of continuous process model are replaced by neural networks. The new hybrid model accounts for the dependence of the two microorganisms' kinetics from the on-line measured characteristics of the culture medium - pH. Then the model was used further for calculation of the optimal time profile of pH. The obtained results are with agreement with the experimental once.
Modeling, estimation and optimal filtration in signal processing
Najim, Mohamed
2010-01-01
The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the
Cost optimization model and its heuristic genetic algorithms
International Nuclear Information System (INIS)
Liu Wei; Wang Yongqing; Guo Jilin
1999-01-01
Interest and escalation are large quantity in proportion to the cost of nuclear power plant construction. In order to optimize the cost, the mathematics model of cost optimization for nuclear power plant construction was proposed, which takes the maximum net present value as the optimization goal. The model is based on the activity networks of the project and is an NP problem. A heuristic genetic algorithms (HGAs) for the model was introduced. In the algorithms, a solution is represented with a string of numbers each of which denotes the priority of each activity for assigned resources. The HGAs with this encoding method can overcome the difficulty which is harder to get feasible solutions when using the traditional GAs to solve the model. The critical path of the activity networks is figured out with the concept of predecessor matrix. An example was computed with the HGAP programmed in C language. The results indicate that the model is suitable for the objectiveness, the algorithms is effective to solve the model
DEFF Research Database (Denmark)
Jacobsen, Charlotte
2008-01-01
There is an increasing interest in the use of healthy long chain omega-3 oils in foods. Incorporation of omega-3 oils into foods decreases their oxidative stability and therefore precautions need to be taken to avoid lipid oxidation. This review summarises the major factors to take into considera...... into consideration when developing food emulsions enriched with omega-3 oils and examples on how oxidation can be reduced in products such as mayonnaise, spreads, milk, yoghurt are also given.......There is an increasing interest in the use of healthy long chain omega-3 oils in foods. Incorporation of omega-3 oils into foods decreases their oxidative stability and therefore precautions need to be taken to avoid lipid oxidation. This review summarises the major factors to take...
Effect of omega-3 on auditory system
Directory of Open Access Journals (Sweden)
Vida Rahimi
2014-01-01
Full Text Available Background and Aim: Omega-3 fatty acid have structural and biological roles in the body 's various systems . Numerous studies have tried to research about it. Auditory system is affected a s well. The aim of this article was to review the researches about the effect of omega-3 on auditory system.Methods: We searched Medline , Google Scholar, PubMed, Cochrane Library and SID search engines with the "auditory" and "omega-3" keywords and read textbooks about this subject between 19 70 and 20 13.Conclusion: Both excess and deficient amounts of dietary omega-3 fatty acid can cause harmful effects on fetal and infant growth and development of brain and central nervous system esspesially auditory system. It is important to determine the adequate dosage of omega-3.
Replica Analysis for Portfolio Optimization with Single-Factor Model
Shinzato, Takashi
2017-06-01
In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.
Models and Algorithms for Container Vessel Stowage Optimization
DEFF Research Database (Denmark)
Delgado-Ortegon, Alberto
.g., selection of vessels to buy that satisfy specific demands), through to operational decisions (e.g., selection of containers that optimize revenue, and stowing those containers into a vessel). This thesis addresses the question of whether it is possible to formulate stowage optimization models...... container of those to be loaded in a port should be placed in a vessel, i.e., to generate stowage plans. This thesis explores two different approaches to solve this problem, both follow a 2-phase decomposition that assigns containers to vessel sections in the first phase, i.e., master planning...
Modelling of Rabies Transmission Dynamics Using Optimal Control Analysis
Directory of Open Access Journals (Sweden)
Joshua Kiddy K. Asamoah
2017-01-01
Full Text Available We examine an optimal way of eradicating rabies transmission from dogs into the human population, using preexposure prophylaxis (vaccination and postexposure prophylaxis (treatment due to public education. We obtain the disease-free equilibrium, the endemic equilibrium, the stability, and the sensitivity analysis of the optimal control model. Using the Latin hypercube sampling (LHS, the forward-backward sweep scheme and the fourth-order Range-Kutta numerical method predict that the global alliance for rabies control’s aim of working to eliminate deaths from canine rabies by 2030 is attainable through mass vaccination of susceptible dogs and continuous use of pre- and postexposure prophylaxis in humans.
Characterization, Modeling, and Optimization of Light-Emitting Diode Systems
DEFF Research Database (Denmark)
Thorseth, Anders
are simulated SPDs similar to traditional light sources, and with high light quality. As part of this work the techniques have been applied in practical illumination applications. The presented examples are historical artifacts and illumination of plants to increase photosynthesis....... comparing the chromaticity of the measured SPD with tted models, the deviation is found to be larger than the lower limit of human color perception. A method has been developed to optimize multicolored cluster LED systems with respect to light quality, using multi objective optimization. The results...
An Optimization Waste Load Allocation Model in River Systems
Amirpoor Daylami, A.; jarihani, A. A.; Aminisola, K.
2012-04-01
In many river systems, increasing of the waste discharge leads to increasing pollution of these water bodies. While the capacity of the river flow for pollution acceptance is limited and the ability of river to clean itself is restricted, the dischargers have to release their waste into the river after a primary pollution treatment process. Waste Load Allocation as a well-known water quality control strategy is used to determine the optimal pollutant removal at a number of point sources along the river. This paper aim at developing a new approach for treatment and management of wastewater inputs into the river systems, such that water quality standards in these receiving waters are met. In this study, inspired by the fact that cooperation among some single point source waste dischargers can lead to a more waste acceptance capacity and/or more optimum quality control in a river, an efficient approach was implemented to determine both primary waste water treatment levels and/or the best releasing points of the waste into the river. In this methodology, a genetic algorithm is used as an optimization tool to calculate optimal fraction removal levels of each one of single or shared discharger. Besides, a sub-model embedded to optimization model was used to simulate water quality of the river in each one of discharging scenarios based on the modified Streeter and Phelps quality equations. The practical application of the model is illustrated with a case study of the Gharesoo river system in west of Iran.
Optimal model-free prediction from multivariate time series
Runge, Jakob; Donner, Reik V.; Kurths, Jürgen
2015-05-01
Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation.
Groundwater Pollution Source Identification using Linked ANN-Optimization Model
Ayaz, Md; Srivastava, Rajesh; Jain, Ashu
2014-05-01
Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration
The case for repeatable analysis with energy economy optimization models
International Nuclear Information System (INIS)
DeCarolis, Joseph F.; Hunter, Kevin; Sreepathi, Sarat
2012-01-01
Energy economy optimization (EEO) models employ formal search techniques to explore the future decision space over several decades in order to deliver policy-relevant insights. EEO models are a critical tool for decision-makers who must make near-term decisions with long-term effects in the face of large future uncertainties. While the number of model-based analyses proliferates, insufficient attention is paid to transparency in model development and application. Given the complex, data-intensive nature of EEO models and the general lack of access to source code and data, many of the assumptions underlying model-based analysis are hidden from external observers. This paper discusses the simplifications and subjective judgments involved in the model building process, which cannot be fully articulated in journal papers, reports, or model documentation. In addition, we argue that for all practical purposes, EEO model-based insights cannot be validated through comparison to real world outcomes. As a result, modelers are left without credible metrics to assess a model's ability to deliver reliable insight. We assert that EEO models should be discoverable through interrogation of publicly available source code and data. In addition, third parties should be able to run a specific model instance in order to independently verify published results. Yet a review of twelve EEO models suggests that in most cases, replication of model results is currently impossible. We provide several recommendations to help develop and sustain a software framework for repeatable model analysis.
Kolosionis, Konstantinos; Papadopoulou, Maria P.
2017-04-01
Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.
Diyana Rosli, Anis; Adenan, Nur Sabrina; Hashim, Hadzli; Ezan Abdullah, Noor; Sulaiman, Suhaimi; Baharudin, Rohaiza
2018-03-01
This paper shows findings of the application of Particle Swarm Optimization (PSO) algorithm in optimizing an Artificial Neural Network that could categorize between ripeness and unripeness stage of citrus suhuensis. The algorithm would adjust the network connections weights and adapt its values during training for best results at the output. Initially, citrus suhuensis fruit’s skin is measured using optically non-destructive method via spectrometer. The spectrometer would transmit VIS (visible spectrum) photonic light radiation to the surface (skin of citrus) of the sample. The reflected light from the sample’s surface would be received and measured by the same spectrometer in terms of reflectance percentage based on VIS range. These measured data are used to train and test the best optimized ANN model. The accuracy is based on receiver operating characteristic (ROC) performance. The result outcomes from this investigation have shown that the achieved accuracy for the optimized is 70.5% with a sensitivity and specificity of 60.1% and 80.0% respectively.
Advanced Nuclear Fuel Cycle Transitions: Optimization, Modeling Choices, and Disruptions
Carlsen, Robert W.
Many nuclear fuel cycle simulators have evolved over time to help understan the nuclear industry/ecosystem at a macroscopic level. Cyclus is one of th first fuel cycle simulators to accommodate larger-scale analysis with it liberal open-source licensing and first-class Linux support. Cyclus also ha features that uniquely enable investigating the effects of modeling choices o fuel cycle simulators and scenarios. This work is divided into thre experiments focusing on optimization, effects of modeling choices, and fue cycle uncertainty. Effective optimization techniques are developed for automatically determinin desirable facility deployment schedules with Cyclus. A novel method fo mapping optimization variables to deployment schedules is developed. Thi allows relationships between reactor types and scenario constraints to b represented implicitly in the variable definitions enabling the usage o optimizers lacking constraint support. It also prevents wasting computationa resources evaluating infeasible deployment schedules. Deployed power capacit over time and deployment of non-reactor facilities are also included a optimization variables There are many fuel cycle simulators built with different combinations o modeling choices. Comparing results between them is often difficult. Cyclus flexibility allows comparing effects of many such modeling choices. Reacto refueling cycle synchronization and inter-facility competition among othe effects are compared in four cases each using combinations of fleet of individually modeled reactors with 1-month or 3-month time steps. There are noticeable differences in results for the different cases. The larges differences occur during periods of constrained reactor fuel availability This and similar work can help improve the quality of fuel cycle analysi generally There is significant uncertainty associated deploying new nuclear technologie such as time-frames for technology availability and the cost of buildin advanced reactors
Nuclear-fuel-cycle optimization: methods and modelling techniques
International Nuclear Information System (INIS)
Silvennoinen, P.
1982-01-01
This book present methods applicable to analyzing fuel-cycle logistics and optimization as well as in evaluating the economics of different reactor strategies. After an introduction to the phases of a fuel cycle, uranium cost trends are assessed in a global perspective. Subsequent chapters deal with the fuel-cycle problems faced by a power utility. The fuel-cycle models cover the entire cycle from the supply of uranium to the disposition of spent fuel. The chapter headings are: Nuclear Fuel Cycle, Uranium Supply and Demand, Basic Model of the LWR (light water reactor) Fuel Cycle, Resolution of Uncertainties, Assessment of Proliferation Risks, Multigoal Optimization, Generalized Fuel-Cycle Models, Reactor Strategy Calculations, and Interface with Energy Strategies. 47 references, 34 figures, 25 tables
A Convex Optimization Model and Algorithm for Retinex
Directory of Open Access Journals (Sweden)
Qing-Nan Zhao
2017-01-01
Full Text Available Retinex is a theory on simulating and explaining how human visual system perceives colors under different illumination conditions. The main contribution of this paper is to put forward a new convex optimization model for Retinex. Different from existing methods, the main idea is to rewrite a multiplicative form such that the illumination variable and the reflection variable are decoupled in spatial domain. The resulting objective function involves three terms including the Tikhonov regularization of the illumination component, the total variation regularization of the reciprocal of the reflection component, and the data-fitting term among the input image, the illumination component, and the reciprocal of the reflection component. We develop an alternating direction method of multipliers (ADMM to solve the convex optimization model. Numerical experiments demonstrate the advantages of the proposed model which can decompose an image into the illumination and the reflection components.
A model for HIV/AIDS pandemic with optimal control
Sule, Amiru; Abdullah, Farah Aini
2015-05-01
Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is pandemic. It has affected nearly 60 million people since the detection of the disease in 1981 to date. In this paper basic deterministic HIV/AIDS model with mass action incidence function are developed. Stability analysis is carried out. And the disease free equilibrium of the basic model was found to be locally asymptotically stable whenever the threshold parameter (RO) value is less than one, and unstable otherwise. The model is extended by introducing two optimal control strategies namely, CD4 counts and treatment for the infective using optimal control theory. Numerical simulation was carried out in order to illustrate the analytic results.
An Optimal Electric Dipole Antenna Model and Its Field Propagation
Directory of Open Access Journals (Sweden)
Yidong Xu
2016-01-01
Full Text Available An optimal electric dipole antennas model is presented and analyzed, based on the hemispherical grounding equivalent model and the superposition principle. The paper also presents a full-wave electromagnetic simulation for the electromagnetic field propagation in layered conducting medium, which is excited by the horizontal electric dipole antennas. Optimum frequency for field transmission in different depth is carried out and verified by the experimental results in comparison with previously reported simulation over a digital wireless Through-The-Earth communication system. The experimental results demonstrate that the dipole antenna grounding impedance and the output power can be efficiently reduced by using the optimal electric dipole antenna model and operating at the optimum frequency in a vertical transmission depth up to 300 m beneath the surface of the earth.
PEMILIHAN SAHAM YANG OPTIMAL MENGGUNAKAN CAPITAL ASSET PRICING MODEL (CAPM
Directory of Open Access Journals (Sweden)
Dioda Ardi Wibisono
2017-08-01
Full Text Available Optimal portfolio is the basis for investors to invest in stock. Capital Asset Pricing Model (CAPM is a method to determine the value of the risk and return of a company stock. This research uses a secondary data from the closing price of the monthly stock price (monthly closing price, Stock Price Index (SPI, and the monthly SBI rate. The samples of this research are 41 stocks in LQ45 February-July 2015 on the Indonesian Stock Exchange (ISE. The study period is during 5 year from October 2010 - October 2015. The result of analysis shows that the optimal portfolio consists of 18 companies. The average return of the optimal portfolio is higher than the average risk-free return (SBI rate and the average market return. This proves that investing in stocks is more profitable than a risk-free investment. � Keywords: Stock, CAPM, return, risk�
Mathematical model of the metal mould surface temperature optimization
Energy Technology Data Exchange (ETDEWEB)
Mlynek, Jaroslav, E-mail: jaroslav.mlynek@tul.cz; Knobloch, Roman, E-mail: roman.knobloch@tul.cz [Department of Mathematics, FP Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic); Srb, Radek, E-mail: radek.srb@tul.cz [Institute of Mechatronics and Computer Engineering Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic)
2015-11-30
The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.
Mathematical model of the metal mould surface temperature optimization
International Nuclear Information System (INIS)
Mlynek, Jaroslav; Knobloch, Roman; Srb, Radek
2015-01-01
The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article
Optimization of recurrent neural networks for time series modeling
DEFF Research Database (Denmark)
Pedersen, Morten With
1997-01-01
The present thesis is about optimization of recurrent neural networks applied to time series modeling. In particular is considered fully recurrent networks working from only a single external input, one layer of nonlinear hidden units and a li near output unit applied to prediction of discrete time...... series. The overall objective s are to improve training by application of second-order methods and to improve generalization ability by architecture optimization accomplished by pruning. The major topics covered in the thesis are: 1. The problem of training recurrent networks is analyzed from a numerical...... of solution obtained as well as computation time required. 3. A theoretical definition of the generalization error for recurrent networks is provided. This definition justifies a commonly adopted approach for estimating generalization ability. 4. The viability of pruning recurrent networks by the Optimal...
Modeling, simulation and optimization for science and technology
Kuznetsov, Yuri; Neittaanmäki, Pekka; Pironneau, Olivier
2014-01-01
This volume contains thirteen articles on advances in applied mathematics and computing methods for engineering problems. Six papers are on optimization methods and algorithms with emphasis on problems with multiple criteria; four articles are on numerical methods for applied problems modeled with nonlinear PDEs; two contributions are on abstract estimates for error analysis; finally one paper deals with rare events in the context of uncertainty quantification. Applications include aerospace, glaciology and nonlinear elasticity. Herein is a selection of contributions from speakers at two conferences on applied mathematics held in June 2012 at the University of Jyväskylä, Finland. The first conference, “Optimization and PDEs with Industrial Applications” celebrated the seventieth birthday of Professor Jacques Périaux of the University of Jyväskylä and Polytechnic University of Catalonia (Barcelona Tech), and the second conference, “Optimization and PDEs with Applications” celebrated the seventy-fi...
Combustion optimization and HCCI modeling for ultra low emission
Energy Technology Data Exchange (ETDEWEB)
Koten, Hasan; Yilmaz, Mustafa; Zafer Gul, M. [Marmara University Mechanical Engineering Department (Turkey)], E-mail: hasan.koten@marmara.edu.tr
2011-07-01
With the coming shortage of fossil fuels and the rising concerns over the environment it is important to develop new technologies both to reduce energy consumption and pollution at the same time. In the transportation sector, new combustion processes are under development to provide clean diesel combustion with no particulate or NOx emissions. However, these processes have issues such as limited power output, high levels of unburned hydrocarbons, and carbon monoxide emissions. The aim of this paper is to present a methodology for optimizing combustion performance. The methodology consists of the use of a multi-objective genetic algorithm optimization tool; homogeneous charge compression ignition engine cases were studied with the ECFM-3Z combustion model. Results showed that injected fuel mass led to a decrease in power output, a finding which is in keeping with previous research. This paper presented on optimization tool which can be useful in improving the combustion process.
Ant Colony Optimization for Markowitz Mean-Variance Portfolio Model
Deng, Guang-Feng; Lin, Woo-Tsong
This work presents Ant Colony Optimization (ACO), which was initially developed to be a meta-heuristic for combinatorial optimization, for solving the cardinality constraints Markowitz mean-variance portfolio model (nonlinear mixed quadratic programming problem). To our knowledge, an efficient algorithmic solution for this problem has not been proposed until now. Using heuristic algorithms in this case is imperative. Numerical solutions are obtained for five analyses of weekly price data for the following indices for the period March, 1992 to September, 1997: Hang Seng 31 in Hong Kong, DAX 100 in Germany, FTSE 100 in UK, S&P 100 in USA and Nikkei 225 in Japan. The test results indicate that the ACO is much more robust and effective than Particle swarm optimization (PSO), especially for low-risk investment portfolios.
Optimal control in a model of malaria with differential susceptibility
Hincapié, Doracelly; Ospina, Juan
2014-06-01
A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.
Optimization Model for Web Based Multimodal Interactive Simulations.
Halic, Tansel; Ahn, Woojin; De, Suvranu
2015-07-15
This paper presents a technique for optimizing the performance of web based multimodal interactive simulations. For such applications where visual quality and the performance of simulations directly influence user experience, overloading of hardware resources may result in unsatisfactory reduction in the quality of the simulation and user satisfaction. However, optimization of simulation performance on individual hardware platforms is not practical. Hence, we present a mixed integer programming model to optimize the performance of graphical rendering and simulation performance while satisfying application specific constraints. Our approach includes three distinct phases: identification, optimization and update . In the identification phase, the computing and rendering capabilities of the client device are evaluated using an exploratory proxy code. This data is utilized in conjunction with user specified design requirements in the optimization phase to ensure best possible computational resource allocation. The optimum solution is used for rendering (e.g. texture size, canvas resolution) and simulation parameters (e.g. simulation domain) in the update phase. Test results are presented on multiple hardware platforms with diverse computing and graphics capabilities to demonstrate the effectiveness of our approach.
In Search of Optimal Cognitive Diagnostic Model(s) for ESL Grammar Test Data
Yi, Yeon-Sook
2017-01-01
This study compares five cognitive diagnostic models in search of optimal one(s) for English as a Second Language grammar test data. Using a unified modeling framework that can represent specific models with proper constraints, the article first fit the full model (the log-linear cognitive diagnostic model, LCDM) and investigated which model…
PEM fuel cell model suitable for energy optimization purposes
International Nuclear Information System (INIS)
Caux, S.; Hankache, W.; Fadel, M.; Hissel, D.
2010-01-01
Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms.
PEM fuel cell model suitable for energy optimization purposes
Energy Technology Data Exchange (ETDEWEB)
Caux, S.; Hankache, W.; Fadel, M. [LAPLACE/CODIASE: UMR CNRS 5213, Universite de Toulouse - INPT, UPS, - ENSEEIHT: 2 rue Camichel BP7122, 31071 Toulouse (France); CNRS, LAPLACE, F-31071 Toulouse (France); Hissel, D. [FEMTO-ST ENISYS/FCLAB, UMR CNRS 6174, University of Franche-Comte, Rue Thierry Mieg, 90010 Belfort (France)
2010-02-15
Many fuel cell stack models or fuel cell system models exist. A model must be built with a main objective, sometimes for accurate electro-chemical behavior description, sometimes for optimization procedure at a system level. In this paper, based on the fundamental reactions present in a fuel cell stack, an accurate model and identification procedure is presented for future energy management in a Hybrid Electrical Vehicle (HEV). The proposed approach extracts all important state variables in such a system and based on the control of the fuel cell's gas flows and temperature, simplification arises to a simple electrical model. Assumptions verified due to the control of the stack allow simplifying the relationships within keeping accuracy in the description of a global fuel cell stack behavior from current demand to voltage. Modeled voltage and current dynamic behaviors are compared with actual measurements. The obtained accuracy is sufficient and less time-consuming (versus other previously published system-oriented models) leading to a suitable model for optimization iterative off-line algorithms. (author)
An internet graph model based on trade-off optimization
Alvarez-Hamelin, J. I.; Schabanel, N.
2004-03-01
This paper presents a new model for the Internet graph (AS graph) based on the concept of heuristic trade-off optimization, introduced by Fabrikant, Koutsoupias and Papadimitriou in[CITE] to grow a random tree with a heavily tailed degree distribution. We propose here a generalization of this approach to generate a general graph, as a candidate for modeling the Internet. We present the results of our simulations and an analysis of the standard parameters measured in our model, compared with measurements from the physical Internet graph.
Fast optimization of statistical potentials for structurally constrained phylogenetic models
Directory of Open Access Journals (Sweden)
Rodrigue Nicolas
2009-09-01
Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.
A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment
International Nuclear Information System (INIS)
Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir
2015-01-01
This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL ® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0–238 N s m −1 through the viscous and electromagnetic components, respectively. (paper)
RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE
Directory of Open Access Journals (Sweden)
Ming-Chang LEE
2015-07-01
Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets. The risk analysis and asset allocation are the key technology of banking and risk management. The aim of this paper, build a loan portfolio optimization model based on risk analysis. Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank. In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm. This paper solves the highly difficult problem by matrix operation method. Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space. It is easy calculation in proposed method.
An optimization model for transportation of hazardous materials
International Nuclear Information System (INIS)
Seyed-Hosseini, M.; Kheirkhah, A. S.
2005-01-01
In this paper, the optimal routing problem for transportation of hazardous materials is studied. Routing for the purpose of reducing the risk of transportation of hazardous materials has been studied and formulated by many researcher and several routing models have been presented up to now. These models can be classified into the categories: the models for routing a single movement and the models for routing multiple movements. In this paper, according to the current rules and regulations of road transportations of hazardous materials in Iran, a routing problem is designed. In this problem, the routs for several independent movements are simultaneously determined. To examine the model, the problem the transportations of two different dangerous materials in the road network of Mazandaran province in the north of Iran is formulated and solved by applying Integer programming model
Research on the decision-making model of land-use spatial optimization
He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu
2009-10-01
Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.
Parallel Optimization of 3D Cardiac Electrophysiological Model Using GPU
Directory of Open Access Journals (Sweden)
Yong Xia
2015-01-01
Full Text Available Large-scale 3D virtual heart model simulations are highly demanding in computational resources. This imposes a big challenge to the traditional computation resources based on CPU environment, which already cannot meet the requirement of the whole computation demands or are not easily available due to expensive costs. GPU as a parallel computing environment therefore provides an alternative to solve the large-scale computational problems of whole heart modeling. In this study, using a 3D sheep atrial model as a test bed, we developed a GPU-based simulation algorithm to simulate the conduction of electrical excitation waves in the 3D atria. In the GPU algorithm, a multicellular tissue model was split into two components: one is the single cell model (ordinary differential equation and the other is the diffusion term of the monodomain model (partial differential equation. Such a decoupling enabled realization of the GPU parallel algorithm. Furthermore, several optimization strategies were proposed based on the features of the virtual heart model, which enabled a 200-fold speedup as compared to a CPU implementation. In conclusion, an optimized GPU algorithm has been developed that provides an economic and powerful platform for 3D whole heart simulations.
Pumping Optimization Model for Pump and Treat Systems - 15091
Energy Technology Data Exchange (ETDEWEB)
Baker, S.; Ivarson, Kristine A.; Karanovic, M.; Miller, Charles W.; Tonkin, M.
2015-01-15
Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.
A Gas Scheduling Optimization Model for Steel Enterprises
Directory of Open Access Journals (Sweden)
Niu Honghai
2017-01-01
Full Text Available Regarding the scheduling problems of steel enterprises, this research designs the gas scheduling optimization model according to the rules and priorities. Considering different features and the process changes of the gas unit in the process of actual production, the calculation model of process state and gas consumption soft measurement together with the rules of scheduling optimization is proposed to provide the dispatchers with real-time gas using status of each process, then help them to timely schedule and reduce the gas volume fluctuations. In the meantime, operation forewarning and alarm functions are provided to avoid the abnormal situation in the scheduling, which has brought about very good application effect in the actual scheduling and ensures the safety of the gas pipe network system and the production stability.
Linear Model for Optimal Distributed Generation Size Predication
Directory of Open Access Journals (Sweden)
Ahmed Al Ameri
2017-01-01
Full Text Available This article presents a linear model predicting optimal size of Distributed Generation (DG that addresses the minimum power loss. This method is based fundamentally on strong coupling between active power and voltage angle as well as between reactive power and voltage magnitudes. This paper proposes simplified method to calculate the total power losses in electrical grid for different distributed generation sizes and locations. The method has been implemented and tested on several IEEE bus test systems. The results show that the proposed method is capable of predicting approximate optimal size of DG when compared with precision calculations. The method that linearizes a complex model showed a good result, which can actually reduce processing time required. The acceptable accuracy with less time and memory required can help the grid operator to assess power system integrated within large-scale distribution generation.
Learning with Admixture: Modeling, Optimization, and Applications in Population Genetics
DEFF Research Database (Denmark)
Cheng, Jade Yu
2016-01-01
the foundation for both CoalHMM and Ohana. Optimization modeling has been the main theme throughout my PhD, and it will continue to shape my work for the years to come. The algorithms and software I developed to study historical admixture and population evolution fall into a larger family of machine learning...... geneticists strive to establish working solutions to extract information from massive volumes of biological data. The steep increase in the quantity and quality of genomic data during the past decades provides a unique opportunity but also calls for new and improved algorithms and software to cope...... including population splits, effective population sizes, gene flow, etc. Since joining the CoalHMM development team in 2014, I have mainly contributed in two directions: 1) improving optimizations through heuristic-based evolutionary algorithms and 2) modeling of historical admixture events. Ohana, meaning...
Sustainable logistics and transportation optimization models and algorithms
Gakis, Konstantinos; Pardalos, Panos
2017-01-01
Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities. Logistics and transportation problems are examined within a sustainability perspective to offer a comprehensive assessment of environmental, social, ethical, and economic performance measures. Featured models, techniques, and algorithms may be used to construct policies on alternative transportation modes and technologies, green logistics, and incentives by the incorporation of environmental, economic, and social measures. Researchers, professionals, and graduate students in urban regional planning, logistics, transport systems, optimization, supply chain management, business administration, information science, mathematics, and industrial and systems engineering will find the real life and interdisciplinary issues presented in this book informative and useful.
Autonomous guided vehicles methods and models for optimal path planning
Fazlollahtabar, Hamed
2015-01-01
This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with A...
Confined compressive strength model of rock for drilling optimization
Directory of Open Access Journals (Sweden)
Xiangchao Shi
2015-03-01
Full Text Available The confined compressive strength (CCS plays a vital role in drilling optimization. On the basis of Jizba's experimental results, a new CCS model considering the effects of the porosity and nonlinear characteristics with increasing confining pressure has been developed. Because the confining pressure plays a fundamental role in determining the CCS of bottom-hole rock and because the theory of Terzaghi's effective stress principle is founded upon soil mechanics, which is not suitable for calculating the confining pressure in rock mechanics, the double effective stress theory, which treats the porosity as a weighting factor of the formation pore pressure, is adopted in this study. The new CCS model combined with the mechanical specific energy equation is employed to optimize the drilling parameters in two practical wells located in Sichuan basin, China, and the calculated results show that they can be used to identify the inefficient drilling situations of underbalanced drilling (UBD and overbalanced drilling (OBD.
The PDB_REDO server for macromolecular structure model optimization
Directory of Open Access Journals (Sweden)
Robbie P. Joosten
2014-07-01
Full Text Available The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB. The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011, Structure, 19, 1395–1412]. The PDB_REDO procedure aims for `constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallographers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.
Modeling marine surface microplastic transport to assess optimal removal locations
Sherman, Peter; Van Sebille, Erik
2016-01-01
Marine plastic pollution is an ever-increasing problem that demands immediate mitigation and reduction plans. Here, a model based on satellite-tracked buoy observations and scaled to a large data set of observations on microplastic from surface trawls was used to simulate the transport of plastics floating on the ocean surface from 2015 to 2025, with the goal to assess the optimal marine microplastic removal locations for two scenarios: removing the most surface microplastic and reducing the ...
Geometry Based Design Automation : Applied to Aircraft Modelling and Optimization
Amadori, Kristian
2012-01-01
Product development processes are continuously challenged by demands for increased efficiency. As engineering products become more and more complex, efficient tools and methods for integrated and automated design are needed throughout the development process. Multidisciplinary Design Optimization (MDO) is one promising technique that has the potential to drastically improve concurrent design. MDO frameworks combine several disciplinary models with the aim of gaining a holistic perspective of ...
Partner Selection Optimization Model of Agricultural Enterprises in Supply Chain
Feipeng Guo; Qibei Lu
2013-01-01
With more and more importance of correctly selecting partners in supply chain of agricultural enterprises, a large number of partner evaluation techniques are widely used in the field of agricultural science research. This study established a partner selection model to optimize the issue of agricultural supply chain partner selection. Firstly, it constructed a comprehensive evaluation index system after analyzing the real characteristics of agricultural supply chain. Secondly, a heuristic met...
Optimizing multi-pinhole SPECT geometries using an analytical model
International Nuclear Information System (INIS)
Rentmeester, M C M; Have, F van der; Beekman, F J
2007-01-01
State-of-the-art multi-pinhole SPECT devices allow for sub-mm resolution imaging of radio-molecule distributions in small laboratory animals. The optimization of multi-pinhole and detector geometries using simulations based on ray-tracing or Monte Carlo algorithms is time-consuming, particularly because many system parameters need to be varied. As an efficient alternative we develop a continuous analytical model of a pinhole SPECT system with a stationary detector set-up, which we apply to focused imaging of a mouse. The model assumes that the multi-pinhole collimator and the detector both have the shape of a spherical layer, and uses analytical expressions for effective pinhole diameters, sensitivity and spatial resolution. For fixed fields-of-view, a pinhole-diameter adapting feedback loop allows for the comparison of the system resolution of different systems at equal system sensitivity, and vice versa. The model predicts that (i) for optimal resolution or sensitivity the collimator layer with pinholes should be placed as closely as possible around the animal given a fixed detector layer, (ii) with high-resolution detectors a resolution improvement up to 31% can be achieved compared to optimized systems, (iii) high-resolution detectors can be placed close to the collimator without significant resolution losses, (iv) interestingly, systems with a physical pinhole diameter of 0 mm can have an excellent resolution when high-resolution detectors are used
Robust Optimization Model for Production Planning Problem under Uncertainty
Directory of Open Access Journals (Sweden)
Pembe GÜÇLÜ
2017-01-01
Full Text Available Conditions of businesses change very quickly. To take into account the uncertainty engendered by changes has become almost a rule while planning. Robust optimization techniques that are methods of handling uncertainty ensure to produce less sensitive results to changing conditions. Production planning, is to decide from which product, when and how much will be produced, with a most basic definition. Modeling and solution of the Production planning problems changes depending on structure of the production processes, parameters and variables. In this paper, it is aimed to generate and apply scenario based robust optimization model for capacitated two-stage multi-product production planning problem under parameter and demand uncertainty. With this purpose, production planning problem of a textile company that operate in İzmir has been modeled and solved, then deterministic scenarios’ and robust method’s results have been compared. Robust method has provided a production plan that has higher cost but, will result close to feasible and optimal for most of the different scenarios in the future.
Influence of model errors in optimal sensor placement
Vincenzi, Loris; Simonini, Laura
2017-02-01
The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.
Linear versus quadratic portfolio optimization model with transaction cost
Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah
2014-06-01
Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.
McDonald, Cameron; Bauer, Judy; Capra, Sandra; Coll, Joseph
2014-04-16
Loss of lean body mass (LBM) is a common occurrence after treatment for breast cancer and is related to deleterious metabolic health outcomes [Clin Oncol, 22(4):281-288, 2010; Appl Physiol Nutr Metab, 34(5):950-956, 2009]. The aim of this research is to determine the effectiveness of long chain omega-3 fatty acids (LCn-3s) and exercise training alone, or in combination, in addressing LBM loss in breast cancer survivors. A total of 153 women who have completed treatment for breast cancer in the last 12 months, with a Body Mass Index (BMI) of 20 to 35 kg/m2, will be randomly assigned to one of 3 groups: 3g/d LCn-3s (N-3), a 12-week nutrition and exercise education program plus olive oil (P-LC) or the education program plus LCn-3s (EX+N-3). Participants randomised to the education groups will be blinded to treatment, and will receive either olive oil placebo (OO+N-3) or LCn-3 provision, while the N-3 group will be open label. The education program includes nine 60-75 min sessions over 12 weeks that will involve breast cancer specific healthy eating advice, plus a supervised exercise session run as a resistance exercise circuit. They will also be advised to conduct the resistance training and aerobic training 5 to 7 days per week collectively. Outcome measures will be taken at baseline, 12-weeks and 24-weeks. The primary outcome is % change in LBM as measured by the air displacement plethysmograhy. Secondary outcomes include quality of life (FACT-B + 4) and inflammation (C-Reactive protein: CRP). Additional measures taken will be erythrocyte fatty acid analysis, fatigue, physical activity, menopausal symptoms, dietary intake, joint pain and function indices. This research will provide the first insight into the efficacy of LCn-3s alone or in combination with exercise in breast cancer survivors with regards to LBM and quality of life. In addition, this study is designed to improve evidence-based dietetic practice, and how specific dietary prescription may link with
Polar-Direct-Drive Experiments on OMEGA
International Nuclear Information System (INIS)
Marshall, F.J.; Craxton, R.S.; Bonino, M.J.; Epstein, R.; Glebov, V.Yu.; Jacobs-Perkins, D.; Knauer, J.P.; Marozas, J.A.; McKenty, P.W.; Noyes, S.G.; Radha, P.B.; Seka, W.; Skupsky, S.; Smalyuk
2006-01-01
Polar direct drive (PDD), a promising ignition path for the NIF while the beams are in the indirect-drive configuration, is currently being investigated on the OMEGA laser system by using 40 beams in six rings repointed to more uniformly illuminate the target. The OMEGA experiments are being performed with standard, ''warm'' targets with and without the use of an equatorial ''Saturn-like'' toroidally shaped CH ring. Target implosion symmetry is diagnosed with framed x-ray backlighting using additional OMEGA beams and by time-integrated x-ray imaging of the stagnating core
Omega-6/Omega-3 and PUFA/SFA in Colossoma macropomum Grown in Roraima, Brazil
Directory of Open Access Journals (Sweden)
Antonio Alves Melho Filho
2013-05-01
Full Text Available In this study was evaluated the fatty acids composition of tambaqui (Colossoma macropomum fillet, fish species cultivated in Roraima State, Brazil. For the extraction of tambaqui oil was used Sohxlet device and then it was methylated. The oil was identified using a gas chromatograph and were identified 24 acids and these were divided into characteristic groups such as: saturated fatty acids (SFA, monounsaturated fatty acids (MUFA, polyunsaturated fatty acids (PUFA and series fatty acids omega-6 and omega-3. The ratios obtained were PUFA/SFA and omega-6/omega-3. The results of chromatographic analysis were subjected to tests by variance ANOVA and multiple comparisons of Tukey at 5%. The ratios omega-6/omega-3 and PUFA/SFA showed values of 8.58 and 0.75 respectively.
The role of Omega-3 and Omega-9 fatty acids for the treatment of neuropathic pain after neurotrauma.
Galán-Arriero, Iriana; Serrano-Muñoz, Diego; Gómez-Soriano, Julio; Goicoechea, Carlos; Taylor, Julian; Velasco, Ana; Ávila-Martín, Gerardo
2017-09-01
Omega-3 polyunsaturated fatty acids (PUFAs), such as docosaexaenoic acid (DHA) and eicosapentaenoic acid (EPA), mediate neuroactive effects in experimental models of traumatic peripheral nerve and spinal cord injury. Cellular mechanisms of PUFAs include reduced neuroinflammation and oxidative stress, enhanced neurotrophic support, and activation of cell survival pathways. Bioactive Omega-9 monounsaturated fatty acids, such as oleic acid (OA) and 2-hydroxy oleic acid (2-OHOA), also show therapeutic effects in neurotrauma models. These FAs reduces noxious hyperreflexia and pain-related anxiety behavior following peripheral nerve injury and improves sensorimotor function following spinal cord injury (SCI), including facilitation of descending inhibitory antinociception. The relative safe profile of neuroactive fatty acids (FAs) holds promise for the future clinical development of these molecules as analgesic agents. This article is part of a Special Issue entitled: Membrane Lipid Therapy: Drugs Targeting Biomembranes edited by Pablo V. Escribá. Copyright © 2017 Elsevier B.V. All rights reserved.
Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model
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Hong Xue
2018-01-01
Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to
Chen, Dian-Yong; He, Jun; Li, Xue-Qian; Liu, Xiang
2009-01-01
In this work, we discuss the contribution of the mesonic loops to the decay rates of $\\chi_{c1}\\to \\phi\\phi,\\,\\omega\\omega$ which are suppressed by the helicity selection rules and $\\chi_{c1}\\to \\phi\\omega$ which is a double-OZI forbidden process. We find that the mesonic loop effects naturally explain the clear signals of $\\chi_{c1}\\to \\phi\\phi,\\,\\omega\\omega$ decay modes observed by the BES collaboration. Moreover, we investigate the effects of the $\\omega-\\phi$ mixing which may result in t...
Astarita, G.; McKenzie, J.H.; Wang, B.; Strassburg, K.; Doneanu, A.; Johnson, J.; Baker, A.; Hankemeier, T.; Murphy, J.; Vreeken, R.J.; Langridge, J.; Kang, J.X.
2014-01-01
A balanced omega-6/omega-3 polyunsaturated fatty acid (PUFA) ratio has been linked to health benefits and the prevention of many chronic diseases. Current dietary intervention studies with different sources of omega-3 fatty acids (omega-3) lack appropriate control diets and carry many other
Omega-3 fatty acids and the genetic risk of early onset acute coronary syndrome.
Leung Yinko, S S L; Thanassoulis, G; Stark, K D; Avgil Tsadok, M; Engert, J C; Pilote, L
2014-11-01
Recent gene-environment interaction studies suggest that diet may influence an individual's genetic predisposition to cardiovascular risk. We evaluated whether omega-3 fatty acid intake may influence the risk for acute coronary syndrome (ACS) conferred by genetic polymorphisms among patients with early onset ACS. Our population consisted of 705 patients of white European descent enrolled in GENESIS-PRAXY, a multicenter cohort study of patients aged 18-55 years and hospitalized with ACS. We used a case-only design to investigate interactions between the omega-3 index (a validated biomarker of omega-3 fatty acid intake) and 30 single nucleotide polymorphisms (SNPs) robustly associated with ACS. We used logistic regression to assess the interaction between each SNP and the omega-3 index. Interaction was also assessed between the omega-3 index and a genetic risk score generated from the 30 SNPs. All models were adjusted for age and sex. An interaction for increased ACS risk was found between carriers of the chromosome 9p21 variant rs4977574 and low omega-3 index (OR 1.57, 95% CI 1.07-2.32, p = 0.02), but this was not significant after correction for multiple testing. Similar results were obtained in the adjusted model (OR 1.55, 95% CI 1.05-2.29, p = 0.03). We did not observe any interaction between the genetic risk score or any of the other SNPs and the omega-3 index. Our results suggest that omega-3 fatty acid intake may modify the genetic risk conferred by chromosome 9p21 variation in the development of early onset ACS and requires independent replication. Copyright © 2014 Elsevier B.V. All rights reserved.
Optimizing ZigBee Security using Stochastic Model Checking
DEFF Research Database (Denmark)
Yuksel, Ender; Nielson, Hanne Riis; Nielson, Flemming
, we identify an important gap in the specification on key updates, and present a methodology for determining optimal key update policies and security parameters. We exploit the stochastic model checking approach using the probabilistic model checker PRISM, and assess the security needs for realistic......ZigBee is a fairly new but promising wireless sensor network standard that offers the advantages of simple and low resource communication. Nevertheless, security is of great concern to ZigBee, and enhancements are prescribed in the latest ZigBee specication: ZigBee-2007. In this technical report...
Optimizing Markovian modeling of chaotic systems with recurrent neural networks
International Nuclear Information System (INIS)
Cechin, Adelmo L.; Pechmann, Denise R.; Oliveira, Luiz P.L. de
2008-01-01
In this paper, we propose a methodology for optimizing the modeling of an one-dimensional chaotic time series with a Markov Chain. The model is extracted from a recurrent neural network trained for the attractor reconstructed from the data set. Each state of the obtained Markov Chain is a region of the reconstructed state space where the dynamics is approximated by a specific piecewise linear map, obtained from the network. The Markov Chain represents the dynamics of the time series in its statistical essence. An application to a time series resulted from Lorenz system is included
Utilization-Based Modeling and Optimization for Cognitive Radio Networks
Liu, Yanbing; Huang, Jun; Liu, Zhangxiong
The cognitive radio technique promises to manage and allocate the scarce radio spectrum in the highly varying and disparate modern environments. This paper considers a cognitive radio scenario composed of two queues for the primary (licensed) users and cognitive (unlicensed) users. According to the Markov process, the system state equations are derived and an optimization model for the system is proposed. Next, the system performance is evaluated by calculations which show the rationality of our system model. Furthermore, discussions among different parameters for the system are presented based on the experimental results.
Transfer prices assignment with integrated production and marketing optimization models
Directory of Open Access Journals (Sweden)
Enrique Parra
2018-04-01
Full Text Available Purpose: In decentralized organizations (today a great majority of the large multinational groups, much of the decision-making power is in its individual business units-BUs-. In these cases, the management control system (MCS uses transfer prices to coordinate actions of the BUs and to evaluate their performance with the goal of guaranteeing the whole corporation optimum. The purpose of the investigation is to design transfer prices that suit this goal. Design/methodology/approach: Considering the results of the whole company supply chain optimization models (in the presence of seasonality of demand the question is to design a mechanism that creates optimal incentives for the managers of each business unit to drive the corporation to the optimal performance. Mathematical programming models are used as a start point. Findings: Different transfer prices computation methods are introduced in this paper for decentralised organizations with two divisions (production and marketing. The methods take into account the results of the solution of the whole company supply chain optimization model, if exists, and can be adapted to the type of information available in the company. It is mainly focused on transport costs assignment. Practical implications: Using the methods proposed in this paper a decentralized corporation can implement more accurate transfer prices to drive the whole organization to the global optimum performance. Originality/value: The methods proposed are a new contribution to the literature on transfer prices with special emphasis on the practical and easy implementation in a modern corporation with several business units and with high seasonality of demand. Also, the methods proposed are very flexible and can be tuned depending on the type of information available in the company.
Optimal Retail Price Model for Partial Consignment to Multiple Retailers
Directory of Open Access Journals (Sweden)
Po-Yu Chen
2017-01-01
Full Text Available This paper investigates the product pricing decision-making problem under a consignment stock policy in a two-level supply chain composed of one supplier and multiple retailers. The effects of the supplier’s wholesale prices and its partial inventory cost absorption of the retail prices of retailers with different market shares are investigated. In the partial product consignment model this paper proposes, the seller and the retailers each absorb part of the inventory costs. This model also provides general solutions for the complete product consignment and the traditional policy that adopts no product consignment. In other words, both the complete consignment and nonconsignment models are extensions of the proposed model (i.e., special cases. Research results indicated that the optimal retail price must be between 1/2 (50% and 2/3 (66.67% times the upper limit of the gross profit. This study also explored the results and influence of parameter variations on optimal retail price in the model.
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Transport Routes Optimization Model Through Application of Fuzzy Logic
Directory of Open Access Journals (Sweden)
Ivan Bortas
2018-03-01
Full Text Available The transport policy of the European Union is based on the mission of restructuring road traffic into other and energy-favourable transport modes which have not been sufficiently represented yet. Therefore, the development of the inland waterway and rail transport, and connectivity in the intermodal transport network are development planning priorities of the European transport strategy. The aim of this research study was to apply the scientific methodology and thus analyse the factors that affect the distribution of the goods flows and by using the fuzzy logic to make an optimization model, according to the criteria of minimizing the costs and negative impact on the environment, for the selection of the optimal transport route. Testing of the model by simulation, was performed on the basis of evaluating the criteria of the influential parameters with unprecise and indefinite input parameters. The testing results show that by the distribution of the goods flow from road transport network to inland waterways or rail transport, can be predicted in advance and determine the transport route with optimal characteristics. The results of the performed research study will be used to improve the process of planning the transport service, with the aim of reducing the transport costs and environmental pollution.
Distributionally Robust Return-Risk Optimization Models and Their Applications
Directory of Open Access Journals (Sweden)
Li Yang
2014-01-01
Full Text Available Based on the risk control of conditional value-at-risk, distributionally robust return-risk optimization models with box constraints of random vector are proposed. They describe uncertainty in both the distribution form and moments (mean and covariance matrix of random vector. It is difficult to solve them directly. Using the conic duality theory and the minimax theorem, the models are reformulated as semidefinite programming problems, which can be solved by interior point algorithms in polynomial time. An important theoretical basis is therefore provided for applications of the models. Moreover, an application of the models to a practical example of portfolio selection is considered, and the example is evaluated using a historical data set of four stocks. Numerical results show that proposed methods are robust and the investment strategy is safe.
Optimization of arterial age prediction models based in pulse wave
Energy Technology Data Exchange (ETDEWEB)
Scandurra, A G [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Meschino, G J [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Passoni, L I [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Dai Pra, A L [Engineering Aplied Artificial Intelligence Group, Mathematics Department, Mar del Plata University (Argentina); Introzzi, A R [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Clara, F M [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina)
2007-11-15
We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff.
Routing and Scheduling Optimization Model of Sea Transportation
barus, Mika debora br; asyrafy, Habib; nababan, Esther; mawengkang, Herman
2018-01-01
This paper examines the routing and scheduling optimization model of sea transportation. One of the issues discussed is about the transportation of ships carrying crude oil (tankers) which is distributed to many islands. The consideration is the cost of transportation which consists of travel costs and the cost of layover at the port. Crude oil to be distributed consists of several types. This paper develops routing and scheduling model taking into consideration some objective functions and constraints. The formulation of the mathematical model analyzed is to minimize costs based on the total distance visited by the tanker and minimize the cost of the ports. In order for the model of the problem to be more realistic and the cost calculated to be more appropriate then added a parameter that states the multiplier factor of cost increases as the charge of crude oil is filled.
Optimization of arterial age prediction models based in pulse wave
International Nuclear Information System (INIS)
Scandurra, A G; Meschino, G J; Passoni, L I; Dai Pra, A L; Introzzi, A R; Clara, F M
2007-01-01
We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff
Simulation platform to model, optimize and design wind turbines
Energy Technology Data Exchange (ETDEWEB)
Iov, F.; Hansen, A.D.; Soerensen, P.; Blaabjerg, F.
2004-03-01
This report is a general overview of the results obtained in the project 'Electrical Design and Control. Simulation Platform to Model, Optimize and Design Wind Turbines'. The motivation for this research project is the ever-increasing wind energy penetration into the power network. Therefore, the project has the main goal to create a model database in different simulation tools for a system optimization of the wind turbine systems. Using this model database a simultaneous optimization of the aerodynamic, mechanical, electrical and control systems over the whole range of wind speeds and grid characteristics can be achieved. The report is structured in six chapters. First, the background of this project and the main goals as well as the structure of the simulation platform is given. The main topologies for wind turbines, which have been taken into account during the project, are briefly presented. Then, the considered simulation tools namely: HAWC, DIgSILENT, Saber and Matlab/Simulink have been used in this simulation platform are described. The focus here is on the modelling and simulation time scale aspects. The abilities of these tools are complementary and they can together cover all the modelling aspects of the wind turbines e.g. mechanical loads, power quality, switching, control and grid faults. However, other simulation packages e.g PSCAD/EMTDC can easily be added in the simulation platform. New models and new control algorithms for wind turbine systems have been developed and tested in these tools. All these models are collected in dedicated libraries in Matlab/Simulink as well as in Saber. Some simulation results from the considered tools are presented for MW wind turbines. These simulation results focuses on fixed-speed and variable speed/pitch wind turbines. A good agreement with the real behaviour of these systems is obtained for each simulation tool. These models can easily be extended to model different kinds of wind turbines or large wind
Optimal difference-based estimation for partially linear models
Zhou, Yuejin; Cheng, Yebin; Dai, Wenlin; Tong, Tiejun
2017-01-01
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
Optimal dividends in the Brownian motion risk model with interest
Fang, Ying; Wu, Rong
2009-07-01
In this paper, we consider a Brownian motion risk model, and in addition, the surplus earns investment income at a constant force of interest. The objective is to find a dividend policy so as to maximize the expected discounted value of dividend payments. It is well known that optimality is achieved by using a barrier strategy for unrestricted dividend rate. However, ultimate ruin of the company is certain if a barrier strategy is applied. In many circumstances this is not desirable. This consideration leads us to impose a restriction on the dividend stream. We assume that dividends are paid to the shareholders according to admissible strategies whose dividend rate is bounded by a constant. Under this additional constraint, we show that the optimal dividend strategy is formed by a threshold strategy.
Using Optimization Models for Scheduling in Enterprise Resource Planning Systems
Directory of Open Access Journals (Sweden)
Frank Herrmann
2016-03-01
Full Text Available Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.
Vehicle Propulsion Systems Introduction to Modeling and Optimization
Guzzella, Lino
2013-01-01
This text provides an introduction to the mathematical modeling and subsequent optimization of vehicle propulsion systems and their supervisory control algorithms. Automobiles are responsible for a substantial part of the world's consumption of primary energy, mostly fossil liquid hydrocarbons and the reduction of the fuel consumption of these vehicles has become a top priority. Increasing concerns over fossil fuel consumption and the associated environmental impacts have motivated many groups in industry and academia to propose new propulsion systems and to explore new optimization methodologies. This third edition has been prepared to include many of these developments. In the third edition, exercises are included at the end of each chapter and the solutions are available on the web.
Power Consumption in Refrigeration Systems - Modeling for Optimization
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Skovrup, Morten Juel
2011-01-01
Refrigeration systems consume a substantial amount of energy. Taking for instance supermarket refrigeration systems as an example they can account for up to 50−80% of the total energy consumption in the supermarket. Due to the thermal capacity made up by the refrigerated goods in the system...... there is a possibility for optimizing the power consumption by utilizing load shifting strategies. This paper describes the dynamics and the modeling of a vapor compression refrigeration system needed for sufficiently realistic estimation of the power consumption and its minimization. This leads to a non-convex function...... with possibly multiple extrema. Such a function can not directly be optimized by standard methods and a qualitative analysis of the system’s constraints is presented. The description of power consumption contains nonlinear terms which are approximated by linear functions in the control variables and the error...
Dynamics of underactuated multibody systems modeling, control and optimal design
Seifried, Robert
2014-01-01
Underactuated multibody systems are intriguing mechatronic systems, as they possess fewer control inputs than degrees of freedom. Some examples are modern light-weight flexible robots and articulated manipulators with passive joints. This book investigates such underactuated multibody systems from an integrated perspective. This includes all major steps from the modeling of rigid and flexible multibody systems, through nonlinear control theory, to optimal system design. The underlying theories and techniques from these different fields are presented using a self-contained and unified approach and notation system. Subsequently, the book focuses on applications to large multibody systems with multiple degrees of freedom, which require a combination of symbolical and numerical procedures. Finally, an integrated, optimization-based design procedure is proposed, whereby both structural and control design are considered concurrently. Each chapter is supplemented by illustrated examples.
Optimal Control of Drug Therapy in a Hepatitis B Model
Directory of Open Access Journals (Sweden)
Jonathan E. Forde
2016-08-01
Full Text Available Combination antiviral drug therapy improves the survival rates of patients chronically infected with hepatitis B virus by controlling viral replication and enhancing immune responses. Some of these drugs have side effects that make them unsuitable for long-term administration. To address the trade-off between the positive and negative effects of the combination therapy, we investigated an optimal control problem for a delay differential equation model of immune responses to hepatitis virus B infection. Our optimal control problem investigates the interplay between virological and immunomodulatory effects of therapy, the control of viremia and the administration of the minimal dosage over a short period of time. Our numerical results show that the high drug levels that induce immune modulation rather than suppression of virological factors are essential for the clearance of hepatitis B virus.
Optimal difference-based estimation for partially linear models
Zhou, Yuejin
2017-12-16
Difference-based methods have attracted increasing attention for analyzing partially linear models in the recent literature. In this paper, we first propose to solve the optimal sequence selection problem in difference-based estimation for the linear component. To achieve the goal, a family of new sequences and a cross-validation method for selecting the adaptive sequence are proposed. We demonstrate that the existing sequences are only extreme cases in the proposed family. Secondly, we propose a new estimator for the residual variance by fitting a linear regression method to some difference-based estimators. Our proposed estimator achieves the asymptotic optimal rate of mean squared error. Simulation studies also demonstrate that our proposed estimator performs better than the existing estimator, especially when the sample size is small and the nonparametric function is rough.
OMEGA for the Future of Biofuels
Trent, Jonathan
2010-01-01
OMEGA: Offshore Membrane Enclosure for Growing Algae. To develop a photobioreactor (PBR) for growing algae (Oil, food, fertilizer) that does not compete with agriculture for land (deployed offshore), water or fertilizer (uses/treats wastewater).
The structure of omega3 food emulsions
DEFF Research Database (Denmark)
Jensen, Louise Helene Søgaard; Loussert, C.; Horn, Anna Frisenfeldt
Fish oil is rich in polyunsaturated omega-3 fatty acids (omega-3 PUFAs) which are generally recognized as being beneficial to the health [1]. The addition of fish oil to food products is attractive to both the consumers and the food industry. Indeed, these components will improve nutritional value...... and add product value. Omega-3 PUFAs are rich in double bonds in their fatty acid chains and this attribute renders them highly susceptible to lipid oxidation. Omega-3 PUFAs can be added to food products as neat oil or as a delivery system such as oil-in-water emulsions. In this last configuration...... and the prooxidants. But this protective aspect is a really complex process and it is dependent on the food matrix to which the oil is added [2]. Oxidation is presumed to be initiated at the emulsifier layer, i.e. the interface layer between the oil and water where the oil is most likely to come into contact...
Polymer models with optimal good-solvent behavior
D'Adamo, Giuseppe; Pelissetto, Andrea
2017-11-01
We consider three different continuum polymer models, which all depend on a tunable parameter r that determines the strength of the excluded-volume interactions. In the first model, chains are obtained by concatenating hard spherocylinders of height b and diameter rb (we call them thick self-avoiding chains). The other two models are generalizations of the tangent hard-sphere and of the Kremer-Grest models. We show that for a specific value r* , all models show optimal behavior: asymptotic long-chain behavior is observed for relatively short chains. For r < r* , instead, the behavior can be parametrized by using the two-parameter model, which also describes the thermal crossover close to the θ point. The bonds of the thick self-avoiding chains cannot cross each other, and therefore the model is suited for the investigation of topological properties and for dynamical studies. Such a model also provides a coarse-grained description of double-stranded DNA, so that we can use our results to discuss under which conditions DNA can be considered as a model good-solvent polymer.
Atmospherical simulations of the OMEGA/MEX observations
Melchiorri, R.; Drossart, P.; Combes, M.; Encrenaz, T.; Fouchet, T.; Forget, F.; Bibring, J. P.; Ignatiev, N.; Moroz, V.; OMEGA Team
The modelization of the atmospheric contribution in the martian spectrum is an important step for the OMEGA data analysis.A full line by line radiative transfer calculation is made for the gas absorption; the dust opacity component, in a first approximation, is calculated as an optically thin additive component.Due to the large number of parameters needed in the calculations, the building of a huge data base to be interpolated is not envisageable, for each observed OMEGA spectrum with calculation for all the involved parameters (atmospheric pressure, water abundance, CO abundance, dust opacity and geometric angles of observation). The simulation of the observations allows us to fix all the orbital parameters and leave the unknown parameters as the only variables.Starting from the predictions of the current meteorological models of Mars we build a smaller data base corresponding on each observation. We present here a first order simulation, which consists in retrieving atmospheric contribution from the solar reflected component as a multiplicative (for gas absorption) and an additive component (for suspended dust contribution); although a fully consistent approach will require to include surface and atmosphere contributions together in synthetic calculations, this approach is sufficient for retrieving mineralogic information cleaned from atmospheric absorption at first order.First comparison to OMEGA spectra will be presented, with first order retrieval of CO2 pressure, CO and H2O abundance, and dust opacity.
Proficient brain for optimal performance: the MAP model perspective.
Bertollo, Maurizio; di Fronso, Selenia; Filho, Edson; Conforto, Silvia; Schmid, Maurizio; Bortoli, Laura; Comani, Silvia; Robazza, Claudio
2016-01-01
Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the "neural efficiency hypothesis." We also observed more ERD as related to optimal-controlled performance in conditions of "neural adaptability" and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques.
Proficient brain for optimal performance: the MAP model perspective
Directory of Open Access Journals (Sweden)
Maurizio Bertollo
2016-05-01
Full Text Available Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1 and optimal-controlled (Type 2 performances. Methods. Ten elite shooters (6 male and 4 female with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques.
Maintenance modeling and optimization integrating human and material resources
International Nuclear Information System (INIS)
Martorell, S.; Villamizar, M.; Carlos, S.; Sanchez, A.
2010-01-01
Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.
Multiobjective Optimization Modeling Approach for Multipurpose Single Reservoir Operation
Directory of Open Access Journals (Sweden)
Iosvany Recio Villa
2018-04-01
Full Text Available The water resources planning and management discipline recognizes the importance of a reservoir’s carryover storage. However, mathematical models for reservoir operation that include carryover storage are scarce. This paper presents a novel multiobjective optimization modeling framework that uses the constraint-ε method and genetic algorithms as optimization techniques for the operation of multipurpose simple reservoirs, including carryover storage. The carryover storage was conceived by modifying Kritsky and Menkel’s method for reservoir design at the operational stage. The main objective function minimizes the cost of the total annual water shortage for irrigation areas connected to a reservoir, while the secondary one maximizes its energy production. The model includes operational constraints for the reservoir, Kritsky and Menkel’s method, irrigation areas, and the hydropower plant. The study is applied to Carlos Manuel de Céspedes reservoir, establishing a 12-month planning horizon and an annual reliability of 75%. The results highly demonstrate the applicability of the model, obtaining monthly releases from the reservoir that include the carryover storage, degree of reservoir inflow regulation, water shortages in irrigation areas, and the energy generated by the hydroelectric plant. The main product is an operational graph that includes zones as well as rule and guide curves, which are used as triggers for long-term reservoir operation.
Optimization of atmospheric transport models on HPC platforms
de la Cruz, Raúl; Folch, Arnau; Farré, Pau; Cabezas, Javier; Navarro, Nacho; Cela, José María
2016-12-01
The performance and scalability of atmospheric transport models on high performance computing environments is often far from optimal for multiple reasons including, for example, sequential input and output, synchronous communications, work unbalance, memory access latency or lack of task overlapping. We investigate how different software optimizations and porting to non general-purpose hardware architectures improve code scalability and execution times considering, as an example, the FALL3D volcanic ash transport model. To this purpose, we implement the FALL3D model equations in the WARIS framework, a software designed from scratch to solve in a parallel and efficient way different geoscience problems on a wide variety of architectures. In addition, we consider further improvements in WARIS such as hybrid MPI-OMP parallelization, spatial blocking, auto-tuning and thread affinity. Considering all these aspects together, the FALL3D execution times for a realistic test case running on general-purpose cluster architectures (Intel Sandy Bridge) decrease by a factor between 7 and 40 depending on the grid resolution. Finally, we port the application to Intel Xeon Phi (MIC) and NVIDIA GPUs (CUDA) accelerator-based architectures and compare performance, cost and power consumption on all the architectures. Implications on time-constrained operational model configurations are discussed.
Models for optimizing the conveying process; Modelle in der Foerderprozessoptimierung
Energy Technology Data Exchange (ETDEWEB)
Koehler, U. [Vattenfall Europe Mining AG, Cottbus (Germany)
2007-05-15
Load- and time controlled use of excavator-conveyor-spreader equipment combinations in the overburden operation is of essential importance for achieving economic cost structures in opencast lignite mines. These effects result from optimizations based on realistic models. Vattenfall Europe Mining AG has successfully implemented a constant linkage of information from the geological model to the direct GPS-based operational management. With the help of this large-scale system model it was possible for the first time to operate two modernized bucket wheel excavators simultaneously with a spreader adjusted to performance limits. At the same time, quality requirements of overburden dumping were fulfilled. Special importance is attached to an uninterrupted, continuous mode of operation at the real, current capacity limit in the systems characteristic field. The Article explains the initial situation and the state-of-the-art technology for the model design as basis for the optimization of linked excavation, conveying and dumping systems. Furthermore, potential considerations from reports presented on the occasion of the Colloquium for Innovative Lignite Mining (KIB) and possible steps for the further technological development are outlined. (orig.)
Maintenance modeling and optimization integrating human and material resources
Energy Technology Data Exchange (ETDEWEB)
Martorell, S., E-mail: smartore@iqn.upv.e [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Villamizar, M.; Carlos, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Sanchez, A. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia (Spain)
2010-12-15
Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.
MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE
Directory of Open Access Journals (Sweden)
I GEDE ERY NISCAHYANA
2016-08-01
Full Text Available When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK, Bank Permata Tbk (BNLI.JK, Suryamas Dutamakmur Tbk (SMDM.JK dan Semen Gresik Indonesia Tbk (SMGR.JK were estimated by GARCH(1,1 model with standard innovations following the standard normal distribution and the t-distribution. The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94% of FMII stock, 0.0473 (5% of BNLI stock, 0% of SMDM stock, 1% of SMGR stock.
Optimization of Regional Geodynamic Models for Mantle Dynamics
Knepley, M.; Isaac, T.; Jadamec, M. A.
2016-12-01
The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.
Validation, Optimization and Simulation of a Solar Thermoelectric Generator Model
Madkhali, Hadi Ali; Hamil, Ali; Lee, HoSung
2017-12-01
This study explores thermoelectrics as a viable option for small-scale solar thermal applications. Thermoelectric technology is based on the Seebeck effect, which states that a voltage is induced when a temperature gradient is applied to the junctions of two differing materials. This research proposes to analyze, validate, simulate, and optimize a prototype solar thermoelectric generator (STEG) model in order to increase efficiency. The intent is to further develop STEGs as a viable and productive energy source that limits pollution and reduces the cost of energy production. An empirical study (Kraemer et al. in Nat Mater 10:532, 2011) on the solar thermoelectric generator reported a high efficiency performance of 4.6%. The system had a vacuum glass enclosure, a flat panel (absorber), thermoelectric generator and water circulation for the cold side. The theoretical and numerical approach of this current study validated the experimental results from Kraemer's study to a high degree. The numerical simulation process utilizes a two-stage approach in ANSYS software for Fluent and Thermal-Electric Systems. The solar load model technique uses solar radiation under AM 1.5G conditions in Fluent. This analytical model applies Dr. Ho Sung Lee's theory of optimal design to improve the performance of the STEG system by using dimensionless parameters. Applying this theory, using two cover glasses and radiation shields, the STEG model can achieve a highest efficiency of 7%.
Some remarks on the optimization of eigenvalue problems involving the p-Laplacian
Directory of Open Access Journals (Sweden)
Wacław Pielichowski
2008-01-01
Full Text Available Given a bounded domain \\(\\Omega \\subset \\mathbb{R}^n\\, numbers \\(p \\gt 1\\, \\(\\alpha \\geq 0\\ and \\(A \\in [0,|\\Omega |]\\, consider the optimization problem: find a subset \\(D \\subset \\Omega \\, of measure \\(A\\, for which the first eigenvalue of the operator \\(u\\mapsto -\\text{div} (|\
Numerical modeling and optimization of machining duplex stainless steels
Directory of Open Access Journals (Sweden)
Rastee D. Koyee
2015-01-01
Full Text Available The shortcomings of the machining analytical and empirical models in combination with the industry demands have to be fulfilled. A three-dimensional finite element modeling (FEM introduces an attractive alternative to bridge the gap between pure empirical and fundamental scientific quantities, and fulfill the industry needs. However, the challenging aspects which hinder the successful adoption of FEM in the machining sector of manufacturing industry have to be solved first. One of the greatest challenges is the identification of the correct set of machining simulation input parameters. This study presents a new methodology to inversely calculate the input parameters when simulating the machining of standard duplex EN 1.4462 and super duplex EN 1.4410 stainless steels. JMatPro software is first used to model elastic–viscoplastic and physical work material behavior. In order to effectively obtain an optimum set of inversely identified friction coefficients, thermal contact conductance, Cockcroft–Latham critical damage value, percentage reduction in flow stress, and Taylor–Quinney coefficient, Taguchi-VIKOR coupled with Firefly Algorithm Neural Network System is applied. The optimization procedure effectively minimizes the overall differences between the experimentally measured performances such as cutting forces, tool nose temperature and chip thickness, and the numerically obtained ones at any specified cutting condition. The optimum set of input parameter is verified and used for the next step of 3D-FEM application. In the next stage of the study, design of experiments, numerical simulations, and fuzzy rule modeling approaches are employed to optimize types of chip breaker, insert shapes, process conditions, cutting parameters, and tool orientation angles based on many important performances. Through this study, not only a new methodology in defining the optimal set of controllable parameters for turning simulations is introduced, but also
WE-D-BRE-04: Modeling Optimal Concurrent Chemotherapy Schedules
International Nuclear Information System (INIS)
Jeong, J; Deasy, J O
2014-01-01
Purpose: Concurrent chemo-radiation therapy (CCRT) has become a more common cancer treatment option with a better tumor control rate for several tumor sites, including head and neck and lung cancer. In this work, possible optimal chemotherapy schedules were investigated by implementing chemotherapy cell-kill into a tumor response model of RT. Methods: The chemotherapy effect has been added into a published model (Jeong et al., PMB (2013) 58:4897), in which the tumor response to RT can be simulated with the effects of hypoxia and proliferation. Based on the two-compartment pharmacokinetic model, the temporal concentration of chemotherapy agent was estimated. Log cell-kill was assumed and the cell-kill constant was estimated from the observed increase in local control due to concurrent chemotherapy. For a simplified two cycle CCRT regime, several different starting times and intervals were simulated with conventional RT regime (2Gy/fx, 5fx/wk). The effectiveness of CCRT was evaluated in terms of reduction in radiation dose required for 50% of control to find the optimal chemotherapy schedule. Results: Assuming the typical slope of dose response curve (γ50=2), the observed 10% increase in local control rate was evaluated to be equivalent to an extra RT dose of about 4 Gy, from which the cell-kill rate of chemotherapy was derived to be about 0.35. Best response was obtained when chemotherapy was started at about 3 weeks after RT began. As the interval between two cycles decreases, the efficacy of chemotherapy increases with broader range of optimal starting times. Conclusion: The effect of chemotherapy has been implemented into the resource-conservation tumor response model to investigate CCRT. The results suggest that the concurrent chemotherapy might be more effective when delayed for about 3 weeks, due to lower tumor burden and a larger fraction of proliferating cells after reoxygenation
Efficacies of vitamin D and omega-3 polyunsaturated fatty acids on experimental endometriosis.
Akyol, Alpaslan; Şimşek, Memet; İlhan, Raşit; Can, Behzat; Baspinar, Melike; Akyol, Hadice; Gül, H Fatih; Gürsu, Ferit; Kavak, Burçin; Akın, Mustafa
2016-12-01
The aim of this study was to investigate the effects of 1,25-dihydroxyvitamin-D3 (vitamin D) and omega-3 polyunsaturated fatty acids (omega-3 PUFA) on experimentally induced endometriosis in a rat model. A prospective, single-blind, randomized, controlled experimental study was performed on 30 Wistar female rats. Endometriosis was surgically induced by implanting endometrial tissue on the abdominal peritoneum. Four weeks later, a second laparotomy was performed to assess pre-treatment implant volumes and cytokine levels. The rats were randomized into three groups: vitamin D group (42 μg/kg/day), omega-3 PUFA group (450 mg/kg/day), and control group (saline 0.1 mL/rat/day). These treatments were administered for 4 weeks. At the end of treatment, a third laparotomy was performed for the assessment of cytokine levels, implant volumes (post-treatment) and implants were totally excised for histopathologic examination. Pre- and post-treatment volumes, cytokine levels within the groups, as well as stromal and glandular tissues between the groups were compared. The mean post-treatment volume was statistically significantly reduced in the omega-3 PUFA group (p=0.02) and the level of the interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), vascular endothelial growth factor (VEGF) in the peritoneal fluid were significantly decreased at the end of treatment in the omega-3 PUFA group (p=0.02, p=0.03, and p=0.03, respectively). In the vitamin D group, only IL-6 levels were significantly decreased. In the histopathologic examination, the glandular tissue and stromal tissue scores of the implants were significant lower in the omega-3 PUFA group (p=0.03 and p=0.02). Omega-3 PUFA caused significant regression of endometriotic implants. Vitamin D has not been as effective as omega-3 PUFA on endometriosis. Copyright © 2016. Published by Elsevier B.V.
Metabolites derived from omega-3 polyunsaturated fatty acids are important for cardioprotection.
Gilbert, Kim; Malick, Mandy; Madingou, Ness; Touchette, Charles; Bourque-Riel, Valérie; Tomaro, Leandro; Rousseau, Guy
2015-12-15
Although controversial, some data suggest that omega-3 polyunsaturated fatty acids (PUFA) are beneficial to cardiovascular diseases, and could reduce infarct size. In parallel, we have reported that the administration of Resolvin D1 (RvD1), a metabolite of docosahexaenoic acid, an omega-3 PUFA, can reduce infarct size. The present study was designed to determine if the inhibition of two important enzymes involved in the formation of RvD1 from omega-3 PUFA could reduce the cardioprotective effect of omega-3 PUFA. Sprague-Dawley rats were fed with a diet rich in omega-3 PUFA during 10 days before myocardial infarction (MI). Two days before MI, rats received a daily dose of Meloxicam, an inhibitor of cyclooxygenase-2, PD146176, an inhibitor of 15-lipoxygenase, both inhibitors or vehicle. MI was induced by the occlusion of the left coronary artery for 40min followed by reperfusion. Infarct size and neutrophil accumulation were evaluated after 24h of reperfusion while caspase-3, -8 and Akt activities were assessed at 30min of reperfusion. Rats receiving inhibitors, alone or in combination, showed a larger infarct size than those receiving omega-3 PUFA alone. Caspase-3 and -8 activities are higher in ischemic areas with inhibitors while Akt activity is diminished in groups treated with inhibitors. Moreover, the study showed that RvD1 restores cardioprotection when added to the inhibitors. Results from this study indicate that the inhibition of the metabolism of Omega-3 PUFA attenuate their cardioprotective properties. Then, resolvins seem to be an important mediator in the cardioprotection conferred by omega-3 PUFA in our experimental model of MI. Copyright © 2015 Elsevier B.V. All rights reserved.
Research on NC laser combined cutting optimization model of sheet metal parts
Wu, Z. Y.; Zhang, Y. L.; Li, L.; Wu, L. H.; Liu, N. B.
2017-09-01
The optimization problem for NC laser combined cutting of sheet metal parts was taken as the research object in this paper. The problem included two contents: combined packing optimization and combined cutting path optimization. In the problem of combined packing optimization, the method of “genetic algorithm + gravity center NFP + geometric transformation” was used to optimize the packing of sheet metal parts. In the problem of combined cutting path optimization, the mathematical model of cutting path optimization was established based on the parts cutting constraint rules of internal contour priority and cross cutting. The model played an important role in the optimization calculation of NC laser combined cutting.
A model of optimization for local energy infrastructure development
International Nuclear Information System (INIS)
Juroszek, Zbigniew; Kudelko, Mariusz
2016-01-01
The authors present a non-linear, optimization model supporting the planning of local energy systems development. The model considers two forms of final energy – heat and electricity. The model reflects both private and external costs and is designed to show the social perspective. It considers the variability of the marginal costs attributed to local renewable resources. In order to demonstrate the capacity of the model, the authors present a case study by modelling the development of the energy infrastructure in a municipality located in the south of Poland. The ensuing results show that a swift and significant shift in the local energy policy of typical central European municipalities is needed. The modelling is done in two scenarios – with and without the internalization of external environmental costs. The results confirm that the internalization of the external costs of energy production on a local scale leads to a significant improvement in the allocation of resources. - Highlights: • A model for municipal energy system development in Central European environment has been developed. • The variability of marginal costs of local, renewable fuels is considered. • External, environmental costs are considered. • The model reflects both network and individual energy infrastructure (e.g. individual housing boilers). • A swift change in Central European municipal energy infrastructure is necessary.
International Nuclear Information System (INIS)
Harish, V.S.K.V.; Kumar, Arun
2016-01-01
Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.
Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory
Dees, Patrick D.; Zwack, Matthew R.; Edwards, Stephen; Steffens, Michael
2016-01-01
It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information
Optimal Filtering in Mass Transport Modeling From Satellite Gravimetry Data
Ditmar, P.; Hashemi Farahani, H.; Klees, R.
2011-12-01
Monitoring natural mass transport in the Earth's system, which has marked a new era in Earth observation, is largely based on the data collected by the GRACE satellite mission. Unfortunately, this mission is not free from certain limitations, two of which are especially critical. Firstly, its sensitivity is strongly anisotropic: it senses the north-south component of the mass re-distribution gradient much better than the east-west component. Secondly, it suffers from a trade-off between temporal and spatial resolution: a high (e.g., daily) temporal resolution is only possible if the spatial resolution is sacrificed. To make things even worse, the GRACE satellites enter occasionally a phase when their orbit is characterized by a short repeat period, which makes it impossible to reach a high spatial resolution at all. A way to mitigate limitations of GRACE measurements is to design optimal data processing procedures, so that all available information is fully exploited when modeling mass transport. This implies, in particular, that an unconstrained model directly derived from satellite gravimetry data needs to be optimally filtered. In principle, this can be realized with a Wiener filter, which is built on the basis of covariance matrices of noise and signal. In practice, however, a compilation of both matrices (and, therefore, of the filter itself) is not a trivial task. To build the covariance matrix of noise in a mass transport model, it is necessary to start from a realistic model of noise in the level-1B data. Furthermore, a routine satellite gravimetry data processing includes, in particular, the subtraction of nuisance signals (for instance, associated with atmosphere and ocean), for which appropriate background models are used. Such models are not error-free, which has to be taken into account when the noise covariance matrix is constructed. In addition, both signal and noise covariance matrices depend on the type of mass transport processes under
Diffusion theory model for optimization calculations of cold neutron sources
International Nuclear Information System (INIS)
Azmy, Y.Y.
1987-01-01
Cold neutron sources are becoming increasingly important and common experimental facilities made available at many research reactors around the world due to the high utility of cold neutrons in scattering experiments. The authors describe a simple two-group diffusion model of an infinite slab LD 2 cold source. The simplicity of the model permits to obtain an analytical solution from which one can deduce the reason for the optimum thickness based solely on diffusion-type phenomena. Also, a second more sophisticated model is described and the results compared to a deterministic transport calculation. The good (particularly qualitative) agreement between the results suggests that diffusion theory methods can be used in parametric and optimization studies to avoid the generally more expensive transport calculations
Fractional and multivariable calculus model building and optimization problems
Mathai, A M
2017-01-01
This textbook presents a rigorous approach to multivariable calculus in the context of model building and optimization problems. This comprehensive overview is based on lectures given at five SERC Schools from 2008 to 2012 and covers a broad range of topics that will enable readers to understand and create deterministic and nondeterministic models. Researchers, advanced undergraduate, and graduate students in mathematics, statistics, physics, engineering, and biological sciences will find this book to be a valuable resource for finding appropriate models to describe real-life situations. The first chapter begins with an introduction to fractional calculus moving on to discuss fractional integrals, fractional derivatives, fractional differential equations and their solutions. Multivariable calculus is covered in the second chapter and introduces the fundamentals of multivariable calculus (multivariable functions, limits and continuity, differentiability, directional derivatives and expansions of multivariable ...
Energy Technology Data Exchange (ETDEWEB)
Widen, Joakim
2011-01-15
This is the final report from a project in which an early-design-phase tool for photovoltaic (PV) systems has been developed. The aim of the tool is to provide a quick and easy way to estimate the electricity production and the economy of a PV system. Although it is effective and easy to use, the model takes into account all the important factors that affect the design, performance and economy of a system, and makes it possible with more in-depth analyses as well. The intended users of the tool are both electricity end-users thinking on investing in a small-scale system and large investors planning in an early project phase for large-scale PV systems. The developed tool is a simulation tool rather than an optimization tool. However, as the model is efficient and simple to use, it is easy to vary parameters and input data in different scenarios to arrive at an optimal solution. In order for the tool to realistically estimate the load matching of a PV system, which depends on seasonal and diurnal variations in both load and production profiles, the computations are made on an hourly basis. An hourly resolution is the most common one in meteorological data and to increase the resolution further is neither practically possible nor required for accuracy. The hourly irradiation data used in the model were collected from the publicly available STRAaNG database, which is maintained by the Swedish Meteorological and Hydrological Institute (SMHI). Idealized hourly load profiles for typical Swedish end-user categories are also included in the tool. A general computational model was implemented in Matlab, which provided easy testing, visualization and validation of the model. The computations involved can be summarized in four main steps: 1 Radiation computations. This involves a transposition of radiation components to the tilted plane of the PV array. The model takes the orientation of the system into account and uses assumed albedo values of the surroundings to add ground
Systemic Model for Optimal Regulation in Public Service
Directory of Open Access Journals (Sweden)
Lucica Matei
2006-05-01
Full Text Available The current paper inscribes within those approaching the issue of public services from the interdisciplinary perspective. Public service development and imposing standards of efficiency and effectiveness, as well as for citizens’ satisfaction bring in front line the systemic modelling and establishing optimal policies for organisation and functioning of public services. The issue under discussion imposes an interface with powerful determinations of social nature. Consequently, the most adequate modelling might be that with a probabilistic and statistic nature. The fundamental idea of this paper, that obviously can be broadly developed, starts with assimilating the way of organisation and functioning of a public service with a waiting thread, to which some hypotheses are associated concerning the order of provision, performance measurement through costs or waiting time in the system etc. We emphasise the openness and dynamics of the public service system, as well as modelling by turning into account the statistic knowledge and researches, and we do not make detailed remarks on the cybernetic characteristics of this system. The optimal adjustment is achieved through analysis on the feedback and its comparison with the current standards or good practices.
Optimizing DNA assembly based on statistical language modelling.
Fang, Gang; Zhang, Shemin; Dong, Yafei
2017-12-15
By successively assembling genetic parts such as BioBrick according to grammatical models, complex genetic constructs composed of dozens of functional blocks can be built. However, usually every category of genetic parts includes a few or many parts. With increasing quantity of genetic parts, the process of assembling more than a few sets of these parts can be expensive, time consuming and error prone. At the last step of assembling it is somewhat difficult to decide which part should be selected. Based on statistical language model, which is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence, the most commonly used parts will be selected. Then, a dynamic programming algorithm was designed to figure out the solution of maximum probability. The algorithm optimizes the results of a genetic design based on a grammatical model and finds an optimal solution. In this way, redundant operations can be reduced and the time and cost required for conducting biological experiments can be minimized. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Optimization models using fuzzy sets and possibility theory
Orlovski, S
1987-01-01
Optimization is of central concern to a number of discip lines. Operations Research and Decision Theory are often consi dered to be identical with optimizationo But also in other areas such as engineering design, regional policy, logistics and many others, the search for optimal solutions is one of the prime goals. The methods and models which have been used over the last decades in these areas have primarily been "hard" or "crisp", i. e. the solutions were considered to be either fea sible or unfeasible, either above a certain aspiration level or below. This dichotomous structure of methods very often forced the modeller to approximate real problem situations of the more-or-less type by yes-or-no-type models, the solutions of which might turn out not to be the solutions to the real prob lems. This is particularly true if the problem under considera tion includes vaguely defined relationships, human evaluations, uncertainty due to inconsistent or incomplete evidence, if na tural language has to be...
Optimized combination model and algorithm of parking guidance information configuration
Directory of Open Access Journals (Sweden)
Tian Ye
2011-01-01
Full Text Available Abstract Operators of parking guidance and information (PGI systems often have difficulty in providing the best car park availability information to drivers in periods of high demand. A new PGI configuration model based on the optimized combination method was proposed by analyzing of parking choice behavior. This article first describes a parking choice behavioral model incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system. Then relationships were developed for estimating the arrival rates at car parks based on driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. A mathematical program was formulated to determine the optimal display PGI sign configuration to minimize total travel time. A genetic algorithm was used to identify solutions that significantly reduced queue lengths and total travel time compared with existing practices. These procedures were applied to an existing PGI system operating in Deqing Town and Xiuning City. Significant reductions in total travel time of parking vehicles with PGI being configured. This would reduce traffic congestion and lead to various environmental benefits.
Optimizing Cardiovascular Benefits of Exercise: A Review of Rodent Models
Davis, Brittany; Moriguchi, Takeshi; Sumpio, Bauer
2013-01-01
Although research unanimously maintains that exercise can ward off cardiovascular disease (CVD), the optimal type, duration, intensity, and combination of forms are yet not clear. In our review of existing rodent-based studies on exercise and cardiovascular health, we attempt to find the optimal forms, intensities, and durations of exercise. Using Scopus and Medline, a literature review of English language comparative journal studies of cardiovascular benefits and exercise was performed. This review examines the existing literature on rodent models of aerobic, anaerobic, and power exercise and compares the benefits of various training forms, intensities, and durations. The rodent studies reviewed in this article correlate with reports on human subjects that suggest regular aerobic exercise can improve cardiac and vascular structure and function, as well as lipid profiles, and reduce the risk of CVD. Findings demonstrate an abundance of rodent-based aerobic studies, but a lack of anaerobic and power forms of exercise, as well as comparisons of these three components of exercise. Thus, further studies must be conducted to determine a truly optimal regimen for cardiovascular health. PMID:24436579
Observer model optimization of a spectral mammography system
Fredenberg, Erik; Åslund, Magnus; Cederström, Björn; Lundqvist, Mats; Danielsson, Mats
2010-04-01
Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.
Optimal experiment design for identification of grey-box models
DEFF Research Database (Denmark)
Sadegh, Payman; Melgaard, Henrik; Madsen, Henrik
1994-01-01
Optimal experiment design is investigated for stochastic dynamic systems where the prior partial information about the system is given as a probability distribution function in the system parameters. The concept of information is related to entropy reduction in the system through Lindley's measur...... estimation results in a considerable reduction of the experimental length. Besides, it is established that the physical knowledge of the system enables us to design experiments, with the goal of maximizing information about the physical parameters of interest.......Optimal experiment design is investigated for stochastic dynamic systems where the prior partial information about the system is given as a probability distribution function in the system parameters. The concept of information is related to entropy reduction in the system through Lindley's measure...... of average information, and the relationship between the choice of information related criteria and some estimators (MAP and MLE) is established. A continuous time physical model of the heat dynamics of a building is considered and the results show that performing an optimal experiment corresponding to a MAP...
Optimization control of LNG regasification plant using Model Predictive Control
Wahid, A.; Adicandra, F. F.
2018-03-01
Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.
Stochastic Modelling and Optimization of Complex Infrastructure Systems
DEFF Research Database (Denmark)
Thoft-Christensen, Palle
In this paper it is shown that recent progress in stochastic modelling and optimization in combination with advanced computer systems has now made it possible to improve the design and the maintenance strategies for infrastructure systems. The paper concentrates on highway networks and single large...... bridges. united states has perhaps the largest highway networks in the world with more than 0.5 million highway bridges; see Chase, S.B. 1999. About 40% of these bridges are considered deficient and more than $50 billion is estimated needed to correct the deficiencies; see Roberts, J.E. 2001...
In vitro placental model optimization for nanoparticle transport studies
Directory of Open Access Journals (Sweden)
Cartwright L
2012-01-01
Full Text Available Laura Cartwright1, Marie Sønnegaard Poulsen2, Hanne Mørck Nielsen3, Giulio Pojana4, Lisbeth E Knudsen2, Margaret Saunders1, Erik Rytting2,51Bristol Initiative for Research of Child Health (BIRCH, Biophysics Research Unit, St Michael's Hospital, UH Bristol NHS Foundation Trust, Bristol, UK; 2University of Copenhagen, Faculty of Health Sciences, Department of Public Health, 3University of Copenhagen, Faculty of Pharmaceutical Sciences, Department of Pharmaceutics and Analytical Chemistry, Copenhagen, Denmark; 4Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Venice, Italy; 5Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas, USABackground: Advances in biomedical nanotechnology raise hopes in patient populations but may also raise questions regarding biodistribution and biocompatibility, especially during pregnancy. Special consideration must be given to the placenta as a biological barrier because a pregnant woman's exposure to nanoparticles could have significant effects on the fetus developing in the womb. Therefore, the purpose of this study is to optimize an in vitro model for characterizing the transport of nanoparticles across human placental trophoblast cells.Methods: The growth of BeWo (clone b30 human placental choriocarcinoma cells for nanoparticle transport studies was characterized in terms of optimized Transwell® insert type and pore size, the investigation of barrier properties by transmission electron microscopy, tight junction staining, transepithelial electrical resistance, and fluorescein sodium transport. Following the determination of nontoxic concentrations of fluorescent polystyrene nanoparticles, the cellular uptake and transport of 50 nm and 100 nm diameter particles was measured using the in vitro BeWo cell model.Results: Particle size measurements, fluorescence readings, and confocal microscopy indicated both cellular uptake of
An Optimal Commitment Model of Exchange Rate Stabilization
Kyung-Soo Kim
2006-01-01
Recently East Asian countries that have amassed large US dollar reserves face a growing threat of big losses from a sudden decline in the dollar. This threat evokes an issue of the optimal commitment of exchange rate stabilization once raised by Isard (1995) who interpreted the cost of breaking the parity as the capital gain awarded to speculators, in the event the domestic currency is devalued. The only difference in this paper is revaluation. This paper models the central bankï¿½ï¿½s optima...
Modeling and optimization of parallel and distributed embedded systems
Munir, Arslan; Ranka, Sanjay
2016-01-01
This book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability.
A dynamic model of optimal reduction of marine oil pollution
Energy Technology Data Exchange (ETDEWEB)
Deissenberg, C. [CEFI-CNRS, Les Milles (France); Gottinger, H.W. [International Inst. for Environmental Economics and Management, Bad Waldsee (Germany); Gurman, V. [RAS, Program Systems Inst., Pereslavl-Zalessky (Russian Federation); Marinushkin, D. [Pereslavl Univ., Pereslavl-Zalessky (Russian Federation)
2001-07-01
This paper proposes a system of dynamic models to describe the interactive behaviour of different agents (polluters, inspectors, and a principal pollution control agency) involved in the processes of marine oil pollution and of its prevention and purification, under some realistic assumptions, In particular, short- and long-term economic responses of polluters to monitoring efforts, as well as possible collusions between polluters and inspectors, are taken into account. A numerical example is considered using the results of Deissenberg et al., (2001), which show the existence of optimal fines and inspector wage rates that minimize (along with other variables) a simple and visual 'social damage' criterion. (Author)
Off-road vehicle dynamics analysis, modelling and optimization
Taghavifar, Hamid
2017-01-01
This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.
Optimal design of a NGNP heat exchanger with cost model
International Nuclear Information System (INIS)
Ridluan, Artit; Danchus, William; Tokuhiro, Akira
2009-01-01
With steady increase in energy consumption, the vulnerability of the fossil fuel supply, and environmental concerns, the U.S. Department of Energy (DOE) has initiated the Next Generation Nuclear Power Plants (NGNP), also known as Very High Temperature Reactor (VHTR). The VHTR is planned to be operational by 2021 with possible demonstration of a hydrogen generating plant. Various engineering design studies on both the reactor plant and energy conversion system are underway. For this and related Generation IV plants, it is the goal to not only meet safety criteria but to also be efficient, economically competitive, and environmentally friendly (proliferation resistant). Traditionally, heat exchanger (HX) design is based on two main approaches: Log-Mean Temperature Difference (LMTD) and effectiveness-NTU (ε-NTU). These methods yield the dimension of the HX under anticipate condition and vice-versa. However, one is not assured that the dimension calculated give the best performing HX when economics are also considered. Here, we develop and show a specific optimization algorithm (exercise) using LMTD and simple (optimal) design theory to establish a reference case for the Printed Circuit Heat Exchanger (PCHE). Computational Fluid Dynamics (CFD) was further used as a design tool to investigate the optimal design of PCHE thermohydraulic flow. The CFD results were validated against the Blasius correlation before being subjected to optimal design analyses. Benchmark results for the pipe flow indicated that the predictive ability of SST k-ω is superior to the other (standard and RNG k-ε and RSM) turbulence models. The difference between CFD and the empirical expression is less than 10%. (author)
Measuring the Star Formation History Of Omega Centauri
Weisz, Daniel
2011-10-01
We propopse to apply the technique of color-magnitude diagram {CMD} fitting to archival HST/ACS and WFC3 imaging of Omega Centauri in order to measure its star formation history {SFH}. As the remnant of a captured satellite galaxy, the SFH of Omega Cen will provide key insights into its formation and evolution before and after its incorporation into the Milky Way. The derivation of SFHs from CMD analysis has been well-established in the Local Group and nearby galaxies, but has never been applied within our Galaxy. Archival HST imaging of Omega Cen provides for exquisitely deep CMDs with broad wavelength coverage {near-UV through I-band}, which allows for clear separation of age-sensitive CMD features, and can be leveraged to highly constrain its star formation rate as a function of time. In addition, the CMD fitting technique also allows us to test for consistency in recovered SFHs using different stellar models, and quantitatively tie the UV characteristics of ancient stellar populations to a SFH.
Exclusive $\\omega$ meson muoproduction on transversely polarised protons
Adolph, C.; Aghasyan, M.; Akhunzyanov, R.; Alexeev, M.G.; Alexeev, G.D.; Amoroso, A.; Andrieux, V.; Anfimov, N.V.; Anosov, V.; Augustyniak, W.; Austregesilo, A.; Azevedo, C.D.R.; Badelek, B.; Balestra, F.; Barth, J.; Beck, R.; Bedfer, Y.; Bernhard, J.; Bicker, K.; Bielert, E.R.; Birsa, R.; Bisplinghoff, J.; Bodlak, M.; Boer, M.; Bordalo, P.; Bradamante, F.; Braun, C.; Bressan, A.; Buechele, M.; Chang, W. -C.; Chatterjee, C.; Chiosso, M.; Choi, I.; Chung, S. -U.; Cicuttin, A.; Crespo, M.L.; Curiel, Q.; Dalla Torre, S.; Dasgupta, S.S.; Dasgupta, S.; Denisov, O. Yu.; Dhara, L.; Donskov, S.V.; Doshita, N.; Duic, V.; Duennweber, W.; Dziewiecki, M.; Efremov, A.; Eversheim, P.D.; Eyrich, W.; Faessler, M.; Ferrero, A.; Finger, M.; Fischer, H.; Franco, C.; von Hohenesche, N. du Fresne; Friedrich, J.M.; Frolov, V.; Fuchey, E.; Gautheron, F.; Gavrichtchouk, O.P.; Gerassimov, S.; Giordano, F.; Gnesi, I.; Gorzellik, M.; Grabmueller, S.; Grasso, A.; Grosse Perdekamp, M.; Grube, B.; Grussenmeyer, T.; Guskov, A.; Haas, F.; Hahne, D.; von Harrach, D.; Hashimoto, R.; Heinsius, F.H.; Heitz, R.; Herrmann, F.; Hinterberger, F.; Horikawa, N.; dHose, N.; Hsieh, C. -Y.; Huber, S.; Ishimoto, S.; Ivanov, A.; Ivanshin, Yu.; Iwata, T.; Jahn, R.; Jary, V.; Joosten, R.; Joerg, P.; Kabuss, E.; Ketzer, B.; Khaustov, G.V.; Khokhlov, Yu. A.; Kisselev, Yu.; Klein, F.; Klimaszewski, K.; Koivuniemi, J.H.; Kolosov, V.N.; Kondo, K.; Koenigsmann, K.; Konorov, I.; Konstantinov, V.F.; Kotzinian, A.M.; Kouznetsov, O.M.; Kraemer, M.; Kremser, P.; Krinner, F.; Kroumchtein, Z.V.; Kulinich, Y.; Kunne, F.; Kurek, K.; Kurjata, R.P.; Lednev, A.A.; Lehmann, A.; Levillain, M.; Levorato, S.; Lian, Y. -S.; Lichtenstadt, J.; Longo, R.; Maggiora, A.; Magnon, A.; Makins, N.; Makke, N.; Mallot, G.K.; Marchand, C.; Marianski, B.; Martin, A.; Marzec, J.; Matousek, J.; Matsuda, H.; Matsuda, T.; Meshcheryakov, G.V.; Meyer, M.; Meyer, W.; Michigami, T.; Mikhailov, Yu. V.; Mikhasenko, M.; Mitrofanov, E.; Mitrofanov, N.; Miyachi, Y.; Montuenga, P.; Nagaytsev, A.; Nerling, F.; Neyret, D.; Nikolaenko, V.I.; Novy, J.; Nowak, W.D.; Nukazuka, G.; Nunes, A.S.; Olshevsky, A.G.; Orlov, I.; Ostrick, M.; Panzieri, D.; Parsamyan, B.; Paul, S.; Peng, J. -C.; Pereira, F.; Pesek, M.; Peshekhonov, D.V.; Pierre, N.; Platchkov, S.; Pochodzalla, J.; Polyakov, V.A.; Pretz, J.; Quaresma, M.; Quintans, C.; Ramos, S.; Regali, C.; Reicherz, G.; Riedl, C.; Roskot, M.; Ryabchikov, D.I.; Rybnikov, A.; Rychter, A.; Salac, R.; Samoylenko, V.D.; Sandacz, A.; Santos, C.; Sarkar, S.; Savin, I.A.; Sawada, T.; Sbrizzai, G.; Schiavon, P.; Schmidt, K.; Schmieden, H.; Schoenning, K.; Schopferer, S.; Seder, E.; Selyunin, A.; Shevchenko, O. Yu.; Silva, L.; Sinha, L.; Sirtl, S.; Slunecka, M.; Smolik, J.; Sozzi, F.; Srnka, A.; Steffen, D.; Stolarski, M.; Sulc, M.; Suzuki, H.; Szabelski, A.; Szameitat, T.; Sznajder, P.; Takekawa, S.; Tasevsky, M.; Tessaro, S.; Tessarotto, F.; Thibaud, F.; Tosello, F.; Tskhay, V.; Uhl, S.; Veloso, J.; Virius, M.; Vondra, J.; Wallner, S.; Weisrock, T.; Wilfert, M.; ter Wolbeek, J.; Zaremba, K.; Zavada, P.; Zavertyaev, M.; Zemlyanichkina, E.; Ziembicki, M.; Zink, A.
2017-01-01
Exclusive production of $\\omega$ mesons was studied at the COMPASS experiment by scattering $160~\\mathrm{GeV}/\\mathit{c}$ muons off transversely polarised protons. Five single-spin and three double-spin azimuthal asymmetries were measured in the range of photon virtuality $1~(\\mathrm{GeV}/\\mathit{c})^2 < Q^2 < 10~(\\mathrm{GeV}/\\mathit{c})^2$, Bjorken scaling variable $0.003 < x_{\\mathit{Bj}} < 0.3$ and transverse momentum squared of the $\\omega$ meson $0.05~(\\mathrm{GeV}/\\mathit{c})^2 < p_{T}^{2} < 0.5~(\\mathrm{GeV}/\\mathit{c})^2$. The measured asymmetries are sensitive to the nucleon helicity-flip Generalised Parton Distributions (GPD) $E$ that are related to the orbital angular momentum of quarks, the chiral-odd GPDs $H_{T}$ that are related to the transversity Parton Distribution Functions, and the sign of the $\\pi\\omega$ transition form factor. The results are compared to recent calculations of a GPD-based model.
Modeling, hybridization, and optimal charging of electrical energy storage systems
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
Measurements of B Meson Decays to omega K* and omega rho
Energy Technology Data Exchange (ETDEWEB)
Aubert, B.
2005-02-14
We describe searches for B meson decays to the charmless vector-vector final states {omega}K* and {omega}{rho} in 89 million B{bar B} pairs produced in e{sup +}e{sup -} annihilation at {radical}s = 10.58 GeV.
Omega-3 Index and Anti-Arrhythmic Potential of Omega-3 PUFAs.
Tribulova, Narcis; Szeiffova Bacova, Barbara; Egan Benova, Tamara; Knezl, Vladimir; Barancik, Miroslav; Slezak, Jan
2017-10-30
Omega-3 polyunsaturated fatty acids (PUFAs), namely eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are permanent subjects of interest in relation to the protection of cardiovascular health and the prevention of the incidence of both ventricular and atrial arrhythmias. The purpose of this updated review is to focus on the novel cellular and molecular effects of omega-3 PUFAs, in the context of the mechanisms and factors involved in the development of cardiac arrhythmias; to provide results of the most recent studies on the omega-3 PUFA anti-arrhythmic efficacy and to discuss the lack of the benefit in relation to omega-3 PUFA status. The evidence is in the favor of omega-3 PUFA acute and long-term treatment, perhaps with mitochondria-targeted antioxidants. However, for a more objective evaluation of the anti-arrhythmic potential of omega-3 PUFAs in clinical trials, it is necessary to monitor the basal pre-interventional omega-3 status of individuals, i.e., red blood cell content, omega-3 index and free plasma levels. In the view of evidence-based medicine, it seems to be crucial to aim to establish new approaches in the prevention of cardiac arrhythmias and associated morbidity and mortality that comes with these conditions.
Traveling waves in an optimal velocity model of freeway traffic
Berg, Peter; Woods, Andrew
2001-03-01
Car-following models provide both a tool to describe traffic flow and algorithms for autonomous cruise control systems. Recently developed optimal velocity models contain a relaxation term that assigns a desirable speed to each headway and a response time over which drivers adjust to optimal velocity conditions. These models predict traffic breakdown phenomena analogous to real traffic instabilities. In order to deepen our understanding of these models, in this paper, we examine the transition from a linear stable stream of cars of one headway into a linear stable stream of a second headway. Numerical results of the governing equations identify a range of transition phenomena, including monotonic and oscillating travelling waves and a time- dependent dispersive adjustment wave. However, for certain conditions, we find that the adjustment takes the form of a nonlinear traveling wave from the upstream headway to a third, intermediate headway, followed by either another traveling wave or a dispersive wave further downstream matching the downstream headway. This intermediate value of the headway is selected such that the nonlinear traveling wave is the fastest stable traveling wave which is observed to develop in the numerical calculations. The development of these nonlinear waves, connecting linear stable flows of two different headways, is somewhat reminiscent of stop-start waves in congested flow on freeways. The different types of adjustments are classified in a phase diagram depending on the upstream and downstream headway and the response time of the model. The results have profound consequences for autonomous cruise control systems. For an autocade of both identical and different vehicles, the control system itself may trigger formations of nonlinear, steep wave transitions. Further information is available [Y. Sugiyama, Traffic and Granular Flow (World Scientific, Singapore, 1995), p. 137].
Liu, Qiang; Wan, Xiaoxia; Xie, Dehong
2014-06-01
The study presented here optimizes several steps in the spectral printer modeling workflow based on a cellular Yule-Nielsen spectral Neugebauer (CYNSN) model. First, a printer subdividing method was developed that reduces the number of sub-models while maintaining the maximum device gamut. Second, the forward spectral prediction accuracy of the CYNSN model for each subspace of the printer was improved using back propagation artificial neural network (BPANN) estimated n values. Third, a sequential gamut judging method, which clearly reduced the complexity of the optimal sub-model and cell searching process during printer backward modeling, was proposed. After that, we further modified the use of the modeling color metric and comprehensively improved the spectral and perceptual accuracy of the spectral printer model. The experimental results show that the proposed optimization approaches provide obvious improvements in aspects of the modeling accuracy or efficiency for each of the corresponding steps, and an overall improvement of the optimized spectral printer modeling workflow was also demonstrated.
Modeling and multidimensional optimization of a tapered free electron laser
Directory of Open Access Journals (Sweden)
Y. Jiao
2012-05-01
Full Text Available Energy extraction efficiency of a free electron laser (FEL can be greatly increased using a tapered undulator and self-seeding. However, the extraction rate is limited by various effects that eventually lead to saturation of the peak intensity and power. To better understand these effects, we develop a model extending the Kroll-Morton-Rosenbluth, one-dimensional theory to include the physics of diffraction, optical guiding, and radially resolved particle trapping. The predictions of the model agree well with that of the GENESIS single-frequency numerical simulations. In particular, we discuss the evolution of the electron-radiation interaction along the tapered undulator and show that the decreasing of refractive guiding is the major cause of the efficiency reduction, particle detrapping, and then saturation of the radiation power. With this understanding, we develop a multidimensional optimization scheme based on GENESIS simulations to increase the energy extraction efficiency via an improved taper profile and variation in electron beam radius. We present optimization results for hard x-ray tapered FELs, and the dependence of the maximum extractable radiation power on various parameters of the initial electron beam, radiation field, and the undulator system. We also study the effect of the sideband growth in a tapered FEL. Such growth induces increased particle detrapping and thus decreased refractive guiding that together strongly limit the overall energy extraction efficiency.
Modeling marine surface microplastic transport to assess optimal removal locations
Sherman, Peter; van Sebille, Erik
2016-01-01
Marine plastic pollution is an ever-increasing problem that demands immediate mitigation and reduction plans. Here, a model based on satellite-tracked buoy observations and scaled to a large data set of observations on microplastic from surface trawls was used to simulate the transport of plastics floating on the ocean surface from 2015 to 2025, with the goal to assess the optimal marine microplastic removal locations for two scenarios: removing the most surface microplastic and reducing the impact on ecosystems, using plankton growth as a proxy. The simulations show that the optimal removal locations are primarily located off the coast of China and in the Indonesian Archipelago for both scenarios. Our estimates show that 31% of the modeled microplastic mass can be removed by 2025 using 29 plastic collectors operating at a 45% capture efficiency from these locations, compared to only 17% when the 29 plastic collectors are moored in the North Pacific garbage patch, between Hawaii and California. The overlap of ocean surface microplastics and phytoplankton growth can be reduced by 46% at our proposed locations, while sinks in the North Pacific can only reduce the overlap by 14%. These results are an indication that oceanic plastic removal might be more effective in removing a greater microplastic mass and in reducing potential harm to marine life when closer to shore than inside the plastic accumulation zones in the centers of the gyres.
Economically optimized electricity trade modeling. Iran-Turkey case
International Nuclear Information System (INIS)
Shakouri G, H.; Eghlimi, M.; Manzoor, D.
2009-01-01
The advantages of power trade between countries, which are attainable for various facts, are distinguished now. Daily differences in the peak-load times of neighboring countries commonly occur for differences in the longitudes of their location. Seasonal differences are also caused by differences in the latitudes leading to different climates. Consequently, different load curves help to have such a production schedule that reduces blackouts and investments for power generation by planning for a proper trade between countries in a region. This paper firstly describes the methodology and framework for the power trade and then the results of an optimal power trade model between Iran and Turkey, which shows a potential benefit for both countries by peak shaving, are presented. The results, in the worst case design, represent optimality of about 1500 MW electricity export from Iran to Turkey at the Turkish peak times, as well as 447 MW electricity import from Turkey at the Iranian peak times. In addition, results derived from running a Long-Run model show that there will be greater potential for power export from Iran to Turkey, which is a guideline of an energy conservation strategy for both countries in the future. (author)
Modeling and PSO optimization of Humidifier-Dehumidifier desalination
Directory of Open Access Journals (Sweden)
Mohammad Hossein Ahmadi
2018-02-01
Full Text Available The aim of this study is modeling a solar-air heater humidification-dehumidification unit with applying particle swarm optimization to find out the maximum gained output ratio with respect to the mass flow rate of water and air entering humidifier, mass flow rate of cooling water entering dehumidifier, width and length of solar air heater and terminal temperature difference (TTD of dehumidifier representing temperature difference of inlet cooling water and saturated air to dehumidifier as its decision variable. A sensitivity analysis, furthermore, is performed to distinguish the effect of operating parameters including mass flow rate and streams’ temperature. The results showed that the optimum productivity decreases by decreasing the ratio of mass flow rate of water entering humidifier to air ones. Article History: Received: July 12th 2017; Revised: December 15th 2017; Accepted: 2nd February 2018; Available online How to Cite This Article: Afshar, M.A., Naseri, A., Bidi, M., Ahmadi, M.H. and Hadiyanto, H. (2018 Modeling and PSO Optimization of Humidifier-Dehumidifier Desalination. International Journal of Renewable Energy Development, 7(1,59-64. https://doi.org/10.14710/ijred.7.1.59-64
Modeling marine surface microplastic transport to assess optimal removal locations
International Nuclear Information System (INIS)
Sherman, Peter; Van Sebille, Erik
2016-01-01
Marine plastic pollution is an ever-increasing problem that demands immediate mitigation and reduction plans. Here, a model based on satellite-tracked buoy observations and scaled to a large data set of observations on microplastic from surface trawls was used to simulate the transport of plastics floating on the ocean surface from 2015 to 2025, with the goal to assess the optimal marine microplastic removal locations for two scenarios: removing the most surface microplastic and reducing the impact on ecosystems, using plankton growth as a proxy. The simulations show that the optimal removal locations are primarily located off the coast of China and in the Indonesian Archipelago for both scenarios. Our estimates show that 31% of the modeled microplastic mass can be removed by 2025 using 29 plastic collectors operating at a 45% capture efficiency from these locations, compared to only 17% when the 29 plastic collectors are moored in the North Pacific garbage patch, between Hawaii and California. The overlap of ocean surface microplastics and phytoplankton growth can be reduced by 46% at our proposed locations, while sinks in the North Pacific can only reduce the overlap by 14%. These results are an indication that oceanic plastic removal might be more effective in removing a greater microplastic mass and in reducing potential harm to marine life when closer to shore than inside the plastic accumulation zones in the centers of the gyres. (letter)
Stochastic Modeling and Optimization in a Microgrid: A Survey
Directory of Open Access Journals (Sweden)
Hao Liang
2014-03-01
Full Text Available The future smart grid is expected to be an interconnected network of small-scale and self-contained microgrids, in addition to a large-scale electric power backbone. By utilizing microsources, such as renewable energy sources and combined heat and power plants, microgrids can supply electrical and heat loads in local areas in an economic and environment friendly way. To better adopt the intermittent and weather-dependent renewable power generation, energy storage devices, such as batteries, heat buffers and plug-in electric vehicles (PEVs with vehicle-to-grid systems can be integrated in microgrids. However, significant technical challenges arise in the planning, operation and control of microgrids, due to the randomness in renewable power generation, the buffering effect of energy storage devices and the high mobility of PEVs. The two-way communication functionalities of the future smart grid provide an opportunity to address these challenges, by offering the communication links for microgrid status information collection. However, how to utilize stochastic modeling and optimization tools for efficient, reliable and economic planning, operation and control of microgrids remains an open issue. In this paper, we investigate the key features of microgrids and provide a comprehensive literature survey on the stochastic modeling and optimization tools for a microgrid. Future research directions are also identified.
Optimizing Crawler4j using MapReduce Programming Model
Siddesh, G. M.; Suresh, Kavya; Madhuri, K. Y.; Nijagal, Madhushree; Rakshitha, B. R.; Srinivasa, K. G.
2017-06-01
World wide web is a decentralized system that consists of a repository of information on the basis of web pages. These web pages act as a source of information or data in the present analytics world. Web crawlers are used for extracting useful information from web pages for different purposes. Firstly, it is used in web search engines where the web pages are indexed to form a corpus of information and allows the users to query on the web pages. Secondly, it is used for web archiving where the web pages are stored for later analysis phases. Thirdly, it can be used for web mining where the web pages are monitored for copyright purposes. The amount of information processed by the web crawler needs to be improved by using the capabilities of modern parallel processing technologies. In order to solve the problem of parallelism and the throughput of crawling this work proposes to optimize the Crawler4j using the Hadoop MapReduce programming model by parallelizing the processing of large input data. Crawler4j is a web crawler that retrieves useful information about the pages that it visits. The crawler Crawler4j coupled with data and computational parallelism of Hadoop MapReduce programming model improves the throughput and accuracy of web crawling. The experimental results demonstrate that the proposed solution achieves significant improvements with respect to performance and throughput. Hence the proposed approach intends to carve out a new methodology towards optimizing web crawling by achieving significant performance gain.
Optimization of the artificial urinary sphincter: modelling and experimental validation
International Nuclear Information System (INIS)
Marti, Florian; Leippold, Thomas; John, Hubert; Blunschi, Nadine; Mueller, Bert
2006-01-01
The artificial urinary sphincter should be long enough to prevent strangulation effects of the urethral tissue and short enough to avoid the improper dissection of the surrounding tissue. To optimize the sphincter length, the empirical three-parameter urethra compression model is proposed based on the mechanical properties of the urethra: wall pressure, tissue response rim force and sphincter periphery length. In vitro studies using explanted animal or human urethras and different artificial sphincters demonstrate its applicability. The pressure of the sphincter to close the urethra is shown to be a linear function of the bladder pressure. The force to close the urethra depends on the sphincter length linearly. Human urethras display the same dependences as the urethras of pig, dog, sheep and calf. Quantitatively, however, sow urethras resemble best the human ones. For the human urethras, the mean wall pressure corresponds to (-12.6 ± 0.9) cmH 2 O and (-8.7 ± 1.1) cmH 2 O, the rim length to (3.0 ± 0.3) mm and (5.1 ± 0.3) mm and the rim force to (60 ± 20) mN and (100 ± 20) mN for urethra opening and closing, respectively. Assuming an intravesical pressure of 40 cmH 2 O, and an external pressure on the urethra of 60 cmH 2 O, the model leads to the optimized sphincter length of (17.3 ± 3.8) mm
Three essays on multi-level optimization models and applications
Rahdar, Mohammad
The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation
Optimization Model for Headway of a Suburban Bus Route
Directory of Open Access Journals (Sweden)
Xiaohong Jiang
2014-01-01
Full Text Available Due to relatively low passenger demand, headways of suburban bus route are usually longer than those of urban bus route. Actually it is also difficult to balance the benefits between passengers and operators, subject to the service standards from the government. Hence the headway of a suburban bus route is usually determined on the empirical experience of transport planners. To cope with this problem, this paper proposes an optimization model for designing the headways of suburban bus routes by minimizing the operating and user costs. The user costs take into account both the waiting time cost and the crowding cost. The feasibility and validity of the proposed model are shown by applying it to the Route 206 in Jiangning district, Nanjing city of China. Weightages of passengers’ cost and operating cost are further discussed, considering different passenger flows. It is found that the headway and objective function are affected by the weightages largely.
Bidirectional Nonnegative Deep Model and Its Optimization in Learning
Directory of Open Access Journals (Sweden)
Xianhua Zeng
2016-01-01
Full Text Available Nonnegative matrix factorization (NMF has been successfully applied in signal processing as a simple two-layer nonnegative neural network. Projective NMF (PNMF with fewer parameters was proposed, which projects a high-dimensional nonnegative data onto a lower-dimensional nonnegative subspace. Although PNMF overcomes the problem of out-of-sample of NMF, it does not consider the nonlinear characteristic of data and is only a kind of narrow signal decomposition method. In this paper, we combine the PNMF with deep learning and nonlinear fitting to propose a bidirectional nonnegative deep learning (BNDL model and its optimization learning algorithm, which can obtain nonlinear multilayer deep nonnegative feature representation. Experiments show that the proposed model can not only solve the problem of out-of-sample of NMF but also learn hierarchical nonnegative feature representations with better clustering performance than classical NMF, PNMF, and Deep Semi-NMF algorithms.
Optimization of inlet plenum of A PBMR using surrogate modeling
International Nuclear Information System (INIS)
Lee, Sang-Moon; Kim, Kwang-Yong
2009-01-01
The purpose of present work is to optimize the design of inlet plenum of PBMR type gas cooled nuclear reactor numerically using a combining of three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis and surrogate modeling technique. Shear stress transport (SST) turbulence model is used as a turbulence closure. Three geometric design variables are selected, namely, rising channel diameter to plenum height ratio, aspect ratio of the plenum cross section, and inlet port angle. The objective function is defined as a linear combination of uniformity of three-dimensional flow distribution term and pressure drop in the inlet plenum and rising channels of PBMR term with a weighting factor. Twenty design points are selected using Latin-hypercube method of design of experiment and objective function values are obtained at each design point using RANS solver. (author)
An Optimization Model for Product Placement on Product Listing Pages
Directory of Open Access Journals (Sweden)
Yan-Kwang Chen
2014-01-01
Full Text Available The design of product listing pages is a key component of Website design because it has significant influence on the sales volume on a Website. This study focuses on product placement in designing product listing pages. Product placement concerns how venders of online stores place their products over the product listing pages for maximization of profit. This problem is very similar to the offline shelf management problem. Since product information sources on a Web page are typically communicated through the text and image, visual stimuli such as color, shape, size, and spatial arrangement often have an effect on the visual attention of online shoppers and, in turn, influence their eventual purchase decisions. In view of the above, this study synthesizes the visual attention literature and theory of shelf-space allocation to develop a mathematical programming model with genetic algorithms for finding optimal solutions to the focused issue. The validity of the model is illustrated with example problems.
Computational modeling, optimization and manufacturing simulation of advanced engineering materials
2016-01-01
This volume presents recent research work focused in the development of adequate theoretical and numerical formulations to describe the behavior of advanced engineering materials. Particular emphasis is devoted to applications in the fields of biological tissues, phase changing and porous materials, polymers and to micro/nano scale modeling. Sensitivity analysis, gradient and non-gradient based optimization procedures are involved in many of the chapters, aiming at the solution of constitutive inverse problems and parameter identification. All these relevant topics are exposed by experienced international and inter institutional research teams resulting in a high level compilation. The book is a valuable research reference for scientists, senior undergraduate and graduate students, as well as for engineers acting in the area of computational material modeling.
Modeling and Optimization for Management of Intermittent Water Supply
Lieb, A. M.; Wilkening, J.; Rycroft, C.
2014-12-01
In many urban areas, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at controlling valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Gradient-based optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability at system endpoints.
Optimal water resource allocation modelling in the Lowveld of Zimbabwe
Directory of Open Access Journals (Sweden)
D. Mhiribidi
2018-05-01
Full Text Available The management and allocation of water from multi-reservoir systems is complex and thus requires dynamic modelling systems to achieve optimality. A multi-reservoir system in the Southern Lowveld of Zimbabwe is used for irrigation of sugarcane estates that produce sugar for both local and export consumption. The system is burdened with water allocation problems, made worse by decommissioning of dams. Thus the aim of this research was to develop an operating policy model for the Lowveld multi-reservoir system.The Mann Kendall Trend and Wilcoxon Signed-Rank tests were used to assess the variability of historic monthly rainfall and dam inflows for the period 1899–2015. The WEAP model was set up to evaluate the water allocation system of the catchment and come-up with a reference scenario for the 2015/2016 hydrologic year. Stochastic Dynamic Programming approach was used for optimisation of the multi-reservoirs releases.Results showed no significant trend in the rainfall but a significantly decreasing trend in inflows (p < 0.05. The water allocation model (WEAP showed significant deficits ( ∼ 40 % in irrigation water allocation in the reference scenario. The optimal rule curves for all the twelve months for each reservoir were obtained and considered to be a proper guideline for solving multi- reservoir management problems within the catchment. The rule curves are effective tools in guiding decision makers in the release of water without emptying the reservoirs but at the same time satisfying the demands based on the inflow, initial storage and end of month storage.
Protein homology model refinement by large-scale energy optimization.
Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David
2018-03-20
Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.
Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method
Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.
2005-01-01
The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.
Models and Methods for Structural Topology Optimization with Discrete Design Variables
DEFF Research Database (Denmark)
Stolpe, Mathias
in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal shape and the topology of the structure. In some cases also the optimal material properties can be determined. Optimal structural design problems are modeled...... such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used in the conceptual design phase to find innovative designs. The strength of topology optimization is the capability of determining both the optimal......Structural topology optimization is a multi-disciplinary research field covering optimal design of load carrying mechanical structures such as bridges, airplanes, wind turbines, cars, etc. Topology optimization is a collection of theory, mathematical models, and numerical methods and is often used...
Time to Talk: Five Things to Know about Omega-3s for Heart Disease
... 5 Things To Know About Omega-3s for Heart Disease Share: Omega-3 fatty acids are a group ... shows omega-3s have a protective effect against heart disease. Experts agree that fish rich in omega-3 ...
A system-theory-based model for monthly river runoff forecasting: model calibration and optimization
Directory of Open Access Journals (Sweden)
Wu Jianhua
2014-03-01
Full Text Available River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff forecasting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.
Optimizing a gap conductance model applicable to VVER-1000 thermal–hydraulic model
International Nuclear Information System (INIS)
Rahgoshay, M.; Hashemi-Tilehnoee, M.
2012-01-01
Highlights: ► Two known conductance models for application in VVER-1000 thermal–hydraulic code are examined. ► An optimized gap conductance model is developed which can predict the gap conductance in good agreement with FSAR data. ► The licensed thermal–hydraulic code is coupled with the gap conductance model predictor externally. -- Abstract: The modeling of gap conductance for application in VVER-1000 thermal–hydraulic codes is addressed. Two known models, namely CALZA-BINI and RELAP5 gap conductance models, are examined. By externally linking of gap conductance models and COBRA-EN thermal hydraulic code, the acceptable range of each model is specified. The result of each gap conductance model versus linear heat rate has been compared with FSAR data. A linear heat rate of about 9 kW/m is the boundary for optimization process. Since each gap conductance model has its advantages and limitation, the optimized gap conductance model can predict the gap conductance better than each of the two other models individually.
International Nuclear Information System (INIS)
Goldman, L.M.; Seka, W.; Tanaka, K.; Simon, A.; Short, R.
1984-01-01
Extensive measurements have been carried out on scattered radiation in the spectral region between omega/2 and 3/2 omega from plasmas produced by 351 nm lasers. The relative intensities of the continuum radiation relative to the line features at omega/2 and 3/2 omega will be shown. A new spectral feature has been observed between 3/2 omega and omega which may be interpreted as an upscattered component produced by ordinary Raman scattering. The overall experimental evidence for ordinary Raman scattering vs stimulated Raman scattering will be discussed
Irregular Shaped Building Design Optimization with Building Information Modelling
Directory of Open Access Journals (Sweden)
Lee Xia Sheng
2016-01-01
Full Text Available This research is to recognise the function of Building Information Modelling (BIM in design optimization for irregular shaped buildings. The study focuses on a conceptual irregular shaped “twisted” building design similar to some existing sculpture-like architectures. Form and function are the two most important aspects of new buildings, which are becoming more sophisticated as parts of equally sophisticated “systems” that we are living in. Nowadays, it is common to have irregular shaped or sculpture-like buildings which are very different when compared to regular buildings. Construction industry stakeholders are facing stiff challenges in many aspects such as buildability, cost effectiveness, delivery time and facility management when dealing with irregular shaped building projects. Building Information Modelling (BIM is being utilized to enable architects, engineers and constructors to gain improved visualization for irregular shaped buildings; this has a purpose of identifying critical issues before initiating physical construction work. In this study, three variations of design options differing in rotating angle: 30 degrees, 60 degrees and 90 degrees are created to conduct quantifiable comparisons. Discussions are focused on three major aspects including structural planning, usable building space, and structural constructability. This research concludes that Building Information Modelling is instrumental in facilitating design optimization for irregular shaped building. In the process of comparing different design variations, instead of just giving “yes or no” type of response, stakeholders can now easily visualize, evaluate and decide to achieve the right balance based on their own criteria. Therefore, construction project stakeholders are empowered with superior evaluation and decision making capability.
Rare B Meson Decays With Omega Mesons
Energy Technology Data Exchange (ETDEWEB)
Zhang, Lei; /Colorado U.
2006-04-24
Rare charmless hadronic B decays are particularly interesting because of their importance in understanding the CP violation, which is essential to explain the matter-antimatter asymmetry in our universe, and of their roles in testing the ''effective'' theory of B physics. The study has been done with the BABAR experiment, which is mainly designed for the study of CP violation in the decays of neutral B mesons, and secondarily for rare processes that become accessible with the high luminosity of the PEP-II B Factory. In a sample of 89 million produced B{bar B} pairs on the BABAR experiment, we observed the decays B{sup 0} {yields} {omega}K{sup 0} and B{sup +} {yields} {omega}{rho}{sup +} for the first time, made more precise measurements for B{sup +} {yields} {omega}h{sup +} and reported tighter upper limits for B {yields} {omega}K* and B{sup 0} {yields} {omega}{rho}{sup 0}.
MicrOmega IR: a new infrared hyperspectral imaging microscope or in situ analysis
Vaitua, Leroi; Bibring, Jean-Pierre; Berthé, Michel
2017-11-01
constituents have diagnostic spectral signature in this range. A full demonstrator model of ExoMars/MicrOmega IR has been assembled at IAS and we will present the design and the experimental results.