A parameter-tuned genetic algorithm for the resource investment problem with discounted cash flows and generalized precedence relations

A resource investment problem with discounted cash flows (RIPDCF) is a project-scheduling problem in which (a) the availability levels of the resources are considered decision variables and (b) the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, the RIPDCF in which the activities are subject to generalized precedence relations is first modeled. Then, a genetic algorithm (GA) is proposed to solve this model. In addition, design of experiments and response surface methodology are employed to both tune the GA parameters and to evaluate the performance of the proposed method in 240 test problems. The results of the performance analysis show that the efficiency of the proposed GA method is relatively well.     

Influence of Different Salts on the G-Quadruplex Structure Formed from the Reversed Human Telomeric DNA Sequence

G-rich telomeric DNA plays a major role in the stabilization of chromosomes and can fold into a plethora of different G-quadruplex structures in the presence of mono- and divalent cations. The reversed human telomeric DNA sequence (5′-(GGG ATT)₄; RevHumTel) was previously shown to have interesting properties that can be exploited for chemical sensing and as a chemical switch in DNA nanotechnology. Here, we analyze the specific G-quadruplex structures formed by RevHumTel in the presence of K⁺, Na⁺, Mg²⁺ and Ca²⁺ cations using circular dichroism spectroscopy (CDS) and Förster resonance energy transfer (FRET) based on fluorescence lifetimes. CDS is able to reveal strand and loop orientations, whereas FRET gives information about the distances between the 5′-end and the 3′-end, and also, the number of G-quadruplex species formed. Based on this combined information we derived specific G-quadruplex structures formed from RevHumTel, i.e., a chair-type and a hybrid-type G-quadruplex structure formed in presence of K⁺, whereas Na⁺ induces the formation of up to three different G-quadruplexes (a basket-type, a propeller-type and a hybrid-type structure). In the presence of Mg²⁺ and Ca²⁺ two different parallel G-quadruplexes are formed (one of which is a propeller-type structure). This study will support the fundamental understanding of the G-quadruplex formation in different environments and a rational design of G-quadruplex-based applications in sensing and nanotechnology.     

Experimental investigation and modeling of a direct-coupled PV/T air collector

Photovoltaic/thermal (PV/T) systems refer to the integration of photovoltaic and solar thermal technologies into one single system, in that both useful heat energy and electricity are produced. The impetus of this paper is to model a direct-coupled PV/T air collector which is designed, built, and tested at a geographic location of Kerman, Iran. In this system, a thin aluminum sheet suspended at the middle of air channel is used to increase the heat exchange surface and consequently improve heat extraction from PV panels. This PV/T system is tested in natural convection and forced convection (with two, four and eight fans operating) and its unsteady results are presented in with and without glass cover cases. A theoretical model is developed and validated against experimental data, where good agreement between the measured values and those calculated by the simulation model were achieved. Comparisons are made between electrical performance of the different mode of operations and it is concluded that there is an optimum number of fans for achieving maximum electrical efficiency. Also, results show that setting glass cover on photovoltaic panels leads to an increase in thermal efficiency and decrease in electrical efficiency of the system.     

Effects of the porous medium and water-silver biological nanofluid on the performance of a newly designed heat sink by using first and second laws of thermodynamics

The aim of this numerical investigation is to evaluate the laminar forced convection of biologically synthesized water-silver nanofluid through a heat sink (HS) filled with porous foam (PHS) using first and second laws of thermodynamics. The impacts of inlet velocity (V = 0.5–3 m·s⁻¹) and volume fraction of nanofluid (φ = 0–1%) on the performance metrics of HS are assessed and the outcomes are compared with those of the non-porous HS (NHS). The outcomes revealed that for both the PHS and NHS, the increase of V causes an intensification in convection coefficient, pumping power, and entropy generation due to fluid friction, while the maximum CPU temperature, thermal resistance, and entropy generation due to the heat transfer reduces by boosting V. Also, it was found that the augmentation of V results in intensification in convection coefficient, pumping power, overall hydrothermal performance, and frictional entropy generation, while the opposite is true for maximum CPU temperature, thermal resistance, and thermal entropy generation. Furthermore, it was reported that, except for φ = 0.5%, the overall hydrothermal performance of NHS is better than that of PHS, while PHS has better second-law performance than NHS in all the studied cases. Also, it can be concluded that the best hydrothermal performance for PHS belongs to φ = 1% and V = 0.5 m·s⁻¹, while for NHS, these values are 1% and 2 m·s⁻¹.     

Effects of the porous medium and water-silver biological nanofluid on the performance of a newly designed heat sink by using first and second laws of thermodynamics

The aim of this numerical investigation is to evaluate the laminar forced convection of biologically synthesized water-silver nanofluid through a heat sink (HS) filled with porous foam (PHS) using first and second laws of thermodynamics. The impacts of inlet velocity (V=0.5-3 m·s^-1) and volume fraction of nanofluid (φ=0-1%) on the performance metrics of HS are assessed and the outcomes are compared with those of the non-porous HS (NHS). The outcomes revealed that for both the PHS and NHS, the increase of V causes an intensification in convection coefficient, pumping power, and entropy generation due to fluid friction, while the maximum CPU temperature, thermal resistance, and entropy generation due to the heat transfer reduces by boosting V. Also, it was found that the augmentation of V results in intensification in convection coefficient, pumping power, overall hydrothermal performance, and frictional entropy generation, while the opposite is true for maximum CPU temperature, thermal resistance, and thermal entropy generation. Furthermore, it was reported that, except for φ=0.5%, the overall hydrothermal performance of NHS is better than that of PHS, while PHS has better second-law performance than NHS in all the studied cases. Also, it can be concluded that the best hydrothermal performance for PHS belongs to φ= 1% and V=0.5 m·s^-1, while for NHS, these values are 1% and 2 m·s^-1.     

Machine learning predictive models for optimal design of building-integrated photovoltaic-thermal collectors

This research article aims to examine the feasibility of several machine learning techniques to forecast the exergetic performance of a building-integrated photovoltaic-thermal (BIPVT) collector. In this regard, it uses multiple linear regression, multilayer perceptron, radial basis function regressor, sequential minimal optimization improved support vector machine, lazy.IBK, random forest (RF), and random tree approaches. Moreover, it implements the performance evaluation criteria (PEC) to evaluate the system's performance from the perspective of exergy. The use of these approaches serves the identification process to realize the relationship between the input–output parameters of the BIPVT system. The novelty of this work is that it utilizes and compares multiple learning algorithms to predict the PEC of BIPVT through design parameters. Hence, the research considers the parameter (PEC) as the essential output of the BIPVT collector, while the input parameters are the length, width, and depth of the duct, located under the PV modules, as well as the air mass flow rate. The results of the research for the statistical indexes of mean absolute error, root mean square error, relative absolute error (%), and root relative squared error (%) show values of (0.2967, 0.3885, 1.8754, and 1.5237) and (0.4957, 0.8153, 2.9586, and 2.8289), respectively, for the training and testing datasets. While R² ranges (0.9997-0.9999) for those datasets. Therefore, to estimate the exergy performance of the BIPVT collector, the RF model is superior to other proposed models.     

Effect of magnetic field on thermal conductivity and viscosity of a magnetic nanofluid loaded with carbon nanotubes

Journal of Mechanical Science and Technology - The present work examines experimentally the effect of magnetic field on the viscosity and thermal conductivity of a hybrid nanofluid containing...     

Energy and economic evaluation and multicriteria optimization of different arrangements of integrated photovoltaic thermal and heat recovery wheel system

The present research deals with the multicriteria optimization of two arrangements of a combined system including a building-integrated photovoltaic thermal (BIPV/T) with a heat recovery wheel (HRW) for Kermanshah weather condition in Iran. The considered arrangements have two operational approaches including heat and cool approaches. In the heat approach of the arrangement (I), the fresh ambient air is preheated in two steps by flowing first among the HRW and then through the BIPV/T collector. In the cool approach of the arrangement (I), the outdoor air stream enters the HRW and is precooled there by exchanging heat to the building exhaust air. The exhaust air then enters the BIPV/T collector and cools the PV panels, thereby augmenting their efficiency. The cool approach of the arrangement (II) is like the arrangement (I), while in the heat approach of the arrangement (II), the outdoor air first gets into the BIPV/T collector and then flows among the TW. The uniform end of annual cost (UAC) and yearly available energy are considered as the objective functions. The obtained results revealed that however energetic performance of the arrangement (I) is more suitable than the arrangement (II); its UAC is 4441$ higher than that of the arrangement (II).     

Application of PSO–ANN modelling for predicting the exergetic performance of a building integrated photovoltaic/thermal system

Engineering with Computers - The main objective of this study is to examine the feasibility of hybrid PSO–ANN technique to estimate the exergetic performance of a building integrated...     

Hydrothermal and entropy generation specifications of a hybrid ferronanofluid in microchannel heat sink embedded in CPUs

The objective of this numerical work is to evaluate the first law and second law performances of a hybrid nanofluid flowing through a liquid-cooled microchannel heatsink.The water-based hybrid nanofluid includes the Fe_3O_4 and carbon nanotubes(CNTs) nanoparticles.The heatsink includes a microchannel configuration for the flow field to gain heat from a processor placed on the bottom of the heatsink.The effects of Fe_3O_4 concentration(φFe_3O_4),CNT concentration(φ_(CNT)) and Reynolds number(Re) on the convective heat transfer coefficient,CPU surface temperature,thermal resistance,pumping power,as well as the rate of entropy generation due to the heat transfer and fluid friction is examined.The results indicated higher values of convective heat transfer coefficient,pumping power,and frictional entropy generation rate for higher values of Re,φFe_3O_4 and φ_(CNT).By increasing Re,φFe_3O_4 and φ_(CNT),the CPU surface temperature and the thermal resistance decrease,and the temperature distribution at the CPU surface became more uniform.To achieve the maximum performance of the studied heatsink,applying the hybrid nanofluid with low φFe_3O_4 and φ_(CNT) was suggested,while the minimum entropy generation was achieved with the application of nanofluid with high φFe_3O_4 and φ_(CNT).