Mounting temperature impedes the conversion efficiency of photovoltaic systems. Studies have shown drastic efficiency escalation of PV modules, if cooled by nanofluids. Ability of nanofluids to supplement the efficiency improvement of PV cells has sought attention of researchers. This chapter presents the magnitude of improved efficiency found by different researchers due to the cooling via nanofluids. The effect of factors (such as, nanoparticle size, nanofluid concentration, flowrate of nanofluid and geometry of channel containing nanofluid) influencing the efficiency of PV systems has been discussed. Collective results of different researchers indicate that the efficiency of the PV/T systems (using nanofluids as coolant) increases with increasing flowrate. Efficiency of these systems increases with increasing concentration of nanofluid up to a certain amount, but as the concentration gets above this certain value, the efficiency tends to decline due to agglomeration/clustering of nanoparticles. Pertaining to the most recent studies, stability of nanoparticles is still the major unresolved issue, hindering the commercial scale application of nanofluids for the cooling of PV panels. Eventually, the environmental and economic advantages of these systems are presented.
As an important issue for establishing structural health monitoring–oriented finite element models for large steel pylons, identification of beam-end stiffness draws the attention of the engineering circle. Since the methods adopted by other researchers for parameter identification are impracticable, a beam-end stiffness identification method which combines in situ measurements for the structure’s global dynamic properties with effective multi-variable optimization methods is utilized to improve the accuracy of established finite element models. A 131-m-high large transmission tower is employed as a case study to validate the method. In situ measurements for the tower’s global dynamic characteristics are performed, and identifications of Young’s modulus for 20 semi-rigid connections distributed along each of the tower’s four main chords are undertaken utilizing three multi-variable optimization methods, that is, the first-order method, the subproblem approximation method, and the response surface method. Static numerical simulations on two detailed connection models prove that multiple uncertain parameters can be correctly and simultaneously identified when appropriate optimization techniques are chosen. Finally, the influence of beam-end stiffness identification on the structural health monitoring–oriented structural safety assessment is revealed by calculating the wind-induced dynamic structural responses for the single tower and the transmission tower-line system, which indicates that identification of the correct beam-end stiffness and updating the structural health monitoring–oriented finite element model are indispensable procedures for reliable structural health monitoring.
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