Search results for " optimization."

showing 10 items of 2333 documents

Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach

2022

Solar energy is one of the most widely exploited renewable/sustainable resources for electricity generation, with photovoltaic and concentrating solar power technologies at the forefront of research. This study focuses on the development of a neural network prediction model aimed at assessing the energy producibility of dish–Stirling systems, testing the methodology and offering a useful tool to support the design and sizing phases of the system at different installation sites. Employing the open-source platform TensorFlow, two different classes of feedforward neural networks were developed and validated (multilayer perceptron and radial basis function). The absolute novelty of this approac…

concentrating solar powerSettore ING-IND/11 - Fisica Tecnica AmbientaleControl and Optimizationneural networkRenewable Energy Sustainability and the EnvironmentEnergy Engineering and Power TechnologyBuilding and ConstructionSolar energysolar energy; concentrating solar power; dish–Stirling; neural network; energy performance forecastingenergy performance forecastingdish–StirlingElectrical and Electronic EngineeringEngineering (miscellaneous)Energy (miscellaneous)Energies; Volume 15; Issue 24; Pages: 9298
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An effective approach for the maintenance scheduling in large systems with required reliability level: A case study

2015

This paper deals with the problem of the maintenance scheduling in a multi-component system for which a required reliability level has to be warranted until the next planned stop for maintenance. Particularly, the tackled problem concerns both the determination of the elements set on which to perform preventive maintenance and the optimal number of maintenance crews in order to warranty the required reliability level at the minimum maintenance cost. The problem is formulated as a mathematical programming model that becomes very hard to solve for large practical systems. For such reason, a new effective approach based on a constrained genetic algorithm is herein proposed and tested with refe…

constrained genetic algorithmSettore ING-IND/17 - Impianti Industriali Meccanicimathematical programming modelMaintenance scheduling optimizationSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazioneseries–parallel system
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The Acceptable Alternative Vehicle Fuel Price

2019

Historically, petroleum fuels have been the dominant fuel used for land transport. However, the growing need for sustainable national economics has urged us to incorporate more economical and ecological alternative vehicle fuels. The advantages and disadvantages of them complicate the decision-making process and compel us to develop adequate mathematical methods. Alternative fuel (compressed natural gas, liquefied petroleum gas, and ethanol fuel mixtures), the standard prices and their ratios were investigated. A mathematical model to determine a critical ratio between alternative and conventional fuel prices had already been developed. The results of this were investigated. The results sho…

conventional fuelalternative fuel; conventional fuel; investment; lifetime; efficiency; mathematical modelControl and Optimization020209 energyEnergy Engineering and Power Technologyalternative fuel02 engineering and technology010501 environmental sciences01 natural sciencesLiquefied petroleum gaslcsh:Technologychemistry.chemical_compoundLand transport0202 electrical engineering electronic engineering information engineeringEthanol fuelElectrical and Electronic EngineeringEngineering (miscellaneous)0105 earth and related environmental scienceslifetimeWaste managementRenewable Energy Sustainability and the Environmentlcsh:TinvestmentCompressed natural gasInvestment (macroeconomics)chemistryBiofuelefficiencyFuel efficiencyEnvironmental sciencePetroleummathematical modelEnergy (miscellaneous)Energies
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Lower bound limit analysis by bem: Convex optimization problem and incremental approach

2013

Abstract The lower bound limit approach of the classical plasticity theory is rephrased using the Multidomain Symmetric Galerkin Boundary Element Method, under conditions of plane and initial strains, ideal plasticity and associated flow rule. The new formulation couples a multidomain procedure with nonlinear programming techniques and defines the self-equilibrium stress field by an equation involving all the substructures (bem-elements) of the discretized system. The analysis is performed in a canonical form as a convex optimization problem with quadratic constraints, in terms of discrete variables, and implemented using the Karnak.sGbem code coupled with the optimization toolbox by MatLab…

convex optimizationelastoplasticityApplied MathematicsMathematical analysisGeneral EngineeringSGBEMUpper and lower boundsself-equilibrium streNonlinear programmingComputational MathematicsQuadratic equationLimit analysisConvex optimizationCanonical formSettore ICAR/08 - Scienza Delle CostruzioniGalerkin methodBoundary element methodAnalysislower bound limit analysiMathematicsEngineering Analysis with Boundary Elements
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MACRO-ZONES SGBEM APPROACH FOR STATIC SHAKEDOWN ANALYSIS AS CONVEX OPTIMIZATION

2013

A new strategy utilizing the Multidomain SGBEM for rapidly performing shakedown analysis as a convex optimization problem has been shown in this paper. The present multidomain approach, called displacement method, makes it possible to consider step-wise physically and geometrically nonhomogeneous materials and to obtain a self-equilibrium stress equation regarding all the bem-elements of the structure. Since this equation includes influence coefficients, which characterize the input of the quadratic constraints, it provides a nonlinear optimization problem solved as a convex optimization problem. Furthermore, the strategy makes it possible to introduce a domain discretization exclusively of…

convex optimizationshakedownsubstructuringsymmetric BEMSettore ICAR/08 - Scienza Delle Costruzioni
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Predictive control of convex polyhedron LPV systems with Markov jumping parameters

2012

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon…

convex polyhedronMarkov chainlinear parameter varying systemsLinear systemMathematicsofComputing_NUMERICALANALYSISLinear matrix inequalityOptimal controlModel predictive controlControl theoryConvex polytopeConvex optimizationMarkov jumping parametersInvariant (mathematics)predictive controlMathematics2012 24th Chinese Control and Decision Conference (CCDC)
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Modeling long-range memory with stationary Markovian processes

2009

In this paper we give explicit examples of power-law correlated stationary Markovian processes y(t) where the stationary pdf shows tails which are gaussian or exponential. These processes are obtained by simply performing a coordinate transformation of a specific power-law correlated additive process x(t), already known in the literature, whose pdf shows power-law tails 1/x^a. We give analytical and numerical evidence that although the new processes (i) are Markovian and (ii) have gaussian or exponential tails their autocorrelation function still shows a power-law decay =1/T^b where b grows with a with a law which is compatible with b=a/2-c, where c is a numerical constant. When a<2(1+c) th…

correlation methodMarkov processeMathematical optimizationStationary distributionStatistical Mechanics (cond-mat.stat-mech)LogarithmStochastic processdiffusionAutocorrelationFOS: Physical sciencesProbability density functionContext (language use)White noiseExponential functionStatistical physicswhite noiseCondensed Matter - Statistical MechanicsMathematics
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A second solvatomorph of poly[[μ4-N,N′-(1,3,5-oxadiazinane-3,5-diyl)bis(carbamoylmethanoato)]nickel(II)dipotassium] : crystal structure, Hirshfeld su…

2021

The title compound, poly[triaquabis[μ4-N,N′-(1,3,5-oxadiazinane-3,5-diyl)bis(carbamoylmethanoato)]dinickel(II)tetrapotassium], [K4Ni2(C7H6N4O7)2(H2O)3] n , is a second solvatomorph of poly[(μ4-N,N′-(1,3,5-oxadiazinane-3,5-diyl)bis(carbamoylmethanoato)nickel(II)dipotassium] reported previously [Plutenko et al. (2021). Acta Cryst. E77, 298–304]. The asymmetric unit of the title compound includes two structurally independent complex anions [Ni(C7H6N4O7)]2−, which exhibit an L-shaped geometry and consist of two almost flat fragments perpendicular to one another: the 1,3,5-oxadiazinane fragment and the fragment including other atoms of the anion. The central Ni atom is in a square-planar N2O2 co…

crystal structureshape analysischemistry.chemical_elementCrystal structureEnergy minimizationIonpseudomacrocyclic ligandCrystalchemistry.chemical_compoundtemplate reactionSHAPE analysisAmidehirshfeld surface analysisAtomHirshfeld surface analysisGeneral Materials Sciencesemi-empirical geometry optimizationCrystallographynickel(ii) complexGeneral ChemistrykompleksiyhdisteetCondensed Matter Physicsnickel(II) complexkiteetTemplate reactionNickelCrystallographychemistryQD901-999nikkelihydrazide-based ligand
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Primary Data Collection and Environmental/Energy Audit of Hot Mix Asphalt Production

2020

The development of the road construction sector determines the consequences on consumption of non-renewable resources, energy expenditure and environmental pollution. Recent sustainability issues have highlighted the importance of efficient design and quality-oriented techniques in this sector, due to the huge amount of materials involved in construction and maintenance activities. Thus, it is necessary to properly quantify the environmental impacts of asphalt mixtures used for pavement construction, considering the whole life cycle of the products. Life cycle assessment (LCA) represents the most appropriate methodological framework for assessing the environmental burdens of a product, from…

data collectionControl and Optimization020209 energyEnergy Engineering and Power TechnologyEnvironmental pollutionContext (language use)02 engineering and technology010501 environmental scienceslcsh:Technology01 natural sciencesEmissionenergy consumption0202 electrical engineering electronic engineering information engineeringSettore ICAR/04 - Strade Ferrovie Ed AeroportiProduction (economics)Electrical and Electronic EngineeringEngineering (miscellaneous)Life-cycle assessment0105 earth and related environmental sciencesAsphalt production; Data collection; Eco-profile; Emissions; Energy consumptionSettore ING-IND/11 - Fisica Tecnica AmbientaleData collectioneco-profilelcsh:TRenewable Energy Sustainability and the Environmentasphalt productionemissionsEnvironmental economicsProduct (business)AsphaltSustainabilityEnvironmental scienceEnergy (miscellaneous)Energies
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Data Compensation with Gaussian Processes Regression: Application in Smart Building's Sensor Network

2022

Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-qu…

data compensationControl and OptimizationRenewable Energy Sustainability and the Environmentsmart building; sensor maintenance; data compensation; Gaussian process regressionsmart buildingEnergy Engineering and Power TechnologyBuilding and ConstructionElectrical and Electronic Engineeringsensor maintenanceEngineering (miscellaneous)Gaussian process regressionEnergy (miscellaneous)
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