74 research outputs found
Effects of Ag-water nanofluid on hydrodynamics and thermal behaviors of three-dimensional separated step flow
No full textIn this research, three-dimensional simulation of nanofluid flow over an inclined step is investigated numerically. The considered nanofluid in this study is a mixture composed by water as base fluid and nanoparticles of silver (Ag), such that the range of volume fraction of these nanoparticles has been changed from 0 to 0.2. The effects of these volume fractions on the hydrodynamics and thermal behaviors are analyzed with all details. Results show that the volume fraction of nanoparticles has a greater influence on the temperature distributions than velocity distributions. Also, the increase of nanoparticles volume fraction leads to a significant enhancement in the friction coefficient, mean bulk temperature and Nusselt number. Keywords: Nanofluid, Nanoparticle volume fraction, Three-dimensional step flow, Separatio
Effect of specimen bed on the material removal due to the repetitive single ball impacts
No full textSpecimen wear due to the repetitive single ball impact is investigated experimentally by a drop test machine. Effect of the impact energy, incidence angle and bed material is studied. Specimen mass loss is measured after 1000 impacts. The crater dimension on the specimen surface is measured to indicate its correlation with the wear variation. Results show that the rubber bed has the undeniable positive role in decrement of the wear due to impact comparing with the steel bed. A relation between the energies which give the same wear, in both cases of the rubber and steel bed, is extracted. Results can be helpful in designing the appropriate bed where the medium and high energy impacts encouraged
Trade credit
No full textThis dissertation develops a new tractable solution method to calculate the set of equilibrium outcomes for a broad variety of dynamic economic models. These outcomes---players' payoffs in repeated games, continuation values of agents in recursive contracts, or the set of stationary distributions in recursive competitive equilibria---are given by the fixed-points of a class of set-valued contraction mapping operators.
I then use the method to analyze a dynamic model of trade credit. This model features a principal/seller of an intermediate good who repeatedly sells on credit and lacks collateral to a cash-constrained buyer/agent who receives new history dependent private information each period and takes private and public actions, including, possibly, defaulting on his debt.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-12-01The student, Meysam Zare, accepted the attached license on 2019-12-05 at 13:06.The student, Meysam Zare, submitted this Dissertation for approval on 2019-12-05 at 13:21.This Dissertation was approved for publication on 2019-12-06 at 07:57.DSpace SAF Submission Ingestion Package generated from Vireo submission #14717 on 2020-02-28 at 17:38:02Made available in DSpace on 2020-03-02T22:38:57Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-12-06Embargo set by: Seth Robbins for item 114036
Lift date: 2022-03-02T22:39:04Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 114036 on 2022-03-03T10:15:25Z
Numerical investigation of entropy generation in laminar forced convection flow over inclined backward and forward facing steps in a duct under bleeding condition
No full textNumerical simulation of laminar forced convection flow with entropy generation analysis in a duct with two expansions - Blocked-off method
No full textIn the present paper, numerical simulations of laminar forced convection flow and entropy generation analysis in a 2-D duct with two sudden expansions are investigated. These two expansions are created by four inclined backward facing steps and beget the separation flows and vortex regions. The vortex regions have the significant effects on the heat transfer rates and flow irreversibility. The inclination angle of steps is one of effective parameters on the control of the separation flows, heat transfer rates and flow irreversibility. In this paper, after calculation of velocity fields and temperature distributions, the effect of the step inclination angle on the separated flows, Nusselt number, friction coefficient, entropy generation number and Bejan number is studied. To obtain the temperature distributions and velocity fields, the set of governing equations including mass, momentum and energy equations are solved by the finite volume methods and computational fluid dynamic (CFD) techniques. For simulating the inclined surfaces of steps in Cartesian coordinates, the blocked-off method is used. Also, thermodynamic second law analysis is employed to calculate the entropy generation and flow irreversibility. Finally, the effect of the Brickman number on the entropy generation number and Bijan number is investigated graphically
Using moving least square with particle swarm optimization to solve nonlinear transient convective–radiative heat transfer problems in the existence of a magnetic field
No full textIn the current research, a novel hybrid scheme is proposed to solve nonlinear equations arising in heat transfer through the combination of meta-heuristic algorithms and interpolation methods. In order to define a proper objective function for minimization by particle swarm optimization (PSO), the constrained problem is converted into an unconstrained one through the penalty method. Furthermore, the moving least square (MLS) technique is implemented to interpolate and approximate the derivatives appeared in the equation. The main problem for challenging this combined scheme is nonlinear transient convective–radiative heat transfer in existence of a magnetic field. To study the efficiency of the MLS, the results would be contrasted with those extracted by a finite difference method (FDM) based PSO approach. Through five distinctive examples, the evolutionary diagrams as well as temperature distributions found by different methods are displayed, and the effects of the constant parameters are investigated. Besides, the simulations of this research work clearly depict good agreements of the numerical results obtained by the suggested idea with those reported in literature. © 2025 John Wiley & Sons Ltd
A decision support system for detecting and handling biased decision-makers in multi criteria group decision-making problems
No full textDetecting and handling biased decision-makers in the group decision-making process is overlooked in the literature. This paper aims to develop an anti-biased statistical approach, including extreme, moderate, and soft versions, as a decision support system for group decision-making (GDM) to detect and handle the bias. The extreme version starts with eliminating the biased decision-makers (DMs). For this purpose, the DMs with a lower Biasedness Index value than a predefined threshold are removed from the process. Next, it continues with a procedure to mitigate the effect of partially biased DMs by assigning different weights to DMs with respect to their biasedness level. To do so, two ratios for the remaining DMs are calculated: (i) Overlap Ratio, which shows the relative value of overlap between the confidence interval (CI) of each DM and the maximum possible overlap value. (ii) Relative confidence interval CI which reflects the relative value of CI for each DM compared to the confidence interval CI of all DMs. The final step is assigning weight to each DM, considering the two values Overlap Ratio and Relative confidence interval. DMs with closer opinions to the aggregated opinion of all DMs, or those with an adequate level of discrimination in their judgments gain more weight. The framework addresses and prescribes possible actions for all possible cases in GDM including without outliers, cases with partial outliers, and extreme cases with complete disagreement among DMs, or when none of the DMs show an adequate level of discrimination power. The moderate version preassigns a minimum weight to all unbiased DMs and then follows the weighting step for the remaining total weight. However, the soft version follows the preassignmnet of weights to all DMs in the initial pool, meaning there is no elimination in this setting. The proposed approach is tested for several scenarios with different sizes. Four performance measures are introduced to evaluate the effectiveness of the proposed method. The resulted performance measures show the reliability of the outcomes.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Logistic
Inference on the Macroscopic Dynamics of Spiking Neurons
No full textInternational audienceThe process of inference on networks of spiking neurons is essential to decipher the underlying mechanisms of brain computation and function. In this study, we conduct inference on parameters and dynamics of a mean-field approximation, simplifying the interactions of neurons. Estimating parameters of this class of generative model allows one to predict the system's dynamics and responses under changing inputs and, indeed, changing parameters. We first assume a set of known state-space equations and address the problem of inferring the lumped parameters from observed time series. Crucially, we consider this problem in the setting of bistability, random fluctuations in system dynamics, and partial observations, in which some states are hidden. To identify the most efficient estimation or inversion scheme in this particular system identification, we benchmark against state-of-the-art optimization and Bayesian estimation algorithms, highlighting their strengths and weaknesses. Additionally, we explore how well the statistical relationships between parameters are maintained across different scales. We found that deep neural density estimators outperform other algorithms in the inversion scheme, despite potentially resulting in overestimated uncertainty and correlation between parameters. Nevertheless, this issue can be improved by incorporating time-delay embedding. We then eschew the mean-field approximation and employ deep neural ODEs on spiking neurons, illustrating prediction of system dynamics and vector fields from microscopic states. Overall, this study affords an opportunity to predict brain dynamicsMeysam Hashemi is the corresponding author. Victor Jirsa and Meysam Hashemi contributed equally.</div
A multi-objective design optimization approach for floating offshore wind turbine support structures
No full textCorresponding Author Bayesian Network and Pest Management: A case study of trap plants on locust population
No full textABSTRACT Bayesian network approach has been effectively used in different experimental fields such as ecological decision making. There is also now growing instance of its usage and effectiveness in pest management. The fundamental principle to optimizing outcomes of agricultural products for pest management is the consideration of all chemical methods, physical methods, mechanical methods, transgenic plants, and trap plants. Some of methods have harmful environmental effects while some others are both environmental friendly and effective. Among them the use of trap plants can be one of the major approaches for pest control. The Locust is one of the most destructive pests and has unpredictable damages on agricultural products especially in poor countries where the volume of product has critical and crucial influence of human life. This research provides a case study on using Bayesian networks on the effect of a number of trap plants have on locust population, and considerations to predict and prevent the pests' harmful effects. According to the findings, the probability methods such as Bayesian networks can contribute effectively on pest management studies particularly trap plants to enhance decision making procedure in national and international perspective
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