There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.

Energy models for demand forecasting—A review

A critical synthesis of thermophysical characteristics of nanofluids

This article reports on the International Nanofluid Property Benchmark Exercise, or INPBE, in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles or “nanofluids,” was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods, and optical methods. The nanofluids tested in the exercise were comprised of aqueous and nonaqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (±10% or less) about the sample average with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

A Benchmark Study on the Thermal Conductivity of Nanofluids

Recent advances in modeling and simulation of nanofluid flows-Part I: Fundamentals and theory

Electricity consumption forecasting in Italy using linear regression models

https://hal.archives-ouvertes.fr/hal-00573480/document

Numerical investigation of nanofluids forced convection in circular tubes

Numerical investigation on nanofluids turbulent convection heat transfer inside a circular tube

A numerical study of nanofluid forced convection in ribbed channels

Turbulent flow and heat transfer are key issues in nature and numerous engineering applications such as human body, fluid machinery, machining facilities, and refrigeration systems. Insight into relevant transient and steady-state thermo-fluidic physics in such scenarios acts as constructive guidance for both engineers and scientists to improve the performance and reliability of facilities, analyze engineering failures, and understand complicated natural phenomena. Unfortunately, such complex fluid flow and heat transfer problems can rarely be solved analytically due to the strong nonlinearity of the Navier–Stokes equations and the complex nature of turbulence with heat transfer. Instead, advanced modeling and measurement techniques become compensatory yet powerful tools and have been widely used. Especially in recent years, a large number of advanced analytical, computational, and experimental techniques have been developed, which greatly contribute to the exploration of turbulence and heat transfer mechanisms. The main objective of this Special Issue is to bring important information on advanced modeling and measurement techniques together. Their feasibility and performance in investigating various engineering problems are evaluated. In this Special Issue, five original research papers were accepted for publication based on critical peer review by qualified reviewers. We hope that such a frontier of turbulence and heat transfer could be continued to track the updated trend year by year. An introductory review of the accepted papers is presented here. In the paper entitled ‘‘The impact research of control modes in steam turbine control system (digital electric hydraulic) to the low frequency oscillation of grid,’’ theoretical models for frequency domain analysis were developed to investigate the effects of steam turbine control modes on low-frequency oscillation of grid. The effectiveness of such theoretical analysis was well validated by simulation using the control system’s toolbox in MATLAB. In the paper entitled ‘‘Research on the aerodynamic characteristics of a lift drag hybrid vertical axis wind turbine,’’ the effects of various parameters on unsteady aerodynamic and starting performances of a newly designed lift drag hybrid vertical axis wind turbine were numerically investigated. The performances of various turbulence models were evaluated based on experimental data. Fruitful guidance for engineering design was also obtained. In the paper entitled ‘‘Pressure fluctuation prediction in pump mode using large eddy simulation and unsteady Reynolds-averaged Navier–Stokes in a pump-turbine,’’ both large eddy simulation and unsteady Reynolds-averaged Navier– Stokes equations in conjunction with a two-equation turbulence model were adopted to predict pressure fluctuation in pump mode of a pump-turbine. By comparisons between experimental and numerical results, the performances of these two different modeling methods were evaluated. In the paper entitled ‘‘Temperature field measurement of spindle ball bearing under radial force based on fiber Bragg grating sensors,’’ fiber Bragg grating temperature sensors were proven to be an effective method in the measurement of temperature distribution in outer ring of a spindle ball bearing. Such a temperature field is physically beneficial for the reduction of spindle thermal error. Finally, in the paper entitled ‘‘Experimental investigation of flow boiling heat transfer and pressure drops characteristic of R1234ze(E), R600a, and a mixture of R1234ze(E)/R32 in a horizontal smooth tube,’’ the effects of mass flux, heat flux, and quality of several refrigerants on flow boiling and pressure drop characteristics in a horizontal smooth tube was experimentally investigated. The corresponding experimental methods and findings from this study are useful for the design of evaporators.

Sergio Nardini

Papers

Electricity consumption forecasting in Italy using linear regression models

Numerical investigation of nanofluids forced convection in circular tubes

Numerical investigation on nanofluids turbulent convection heat transfer inside a circular tube

A numerical study of nanofluid forced convection in ribbed channels

Advanced approaches of modeling and measurement for turbulence and heat transfer