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Thermal protection of a flange is critical for preventing tower icing and collapse of wind turbines (WTs) in extremely cold weather. This study aims to develop a novel thermal protection system for the WTs flanges using an electrical heat-tracing element.

A three-dimensional model and the Poly-Hexacore mesh structure are used, and the fluid-solid coupling method was validated and then deployed to analyze the heat transfer and convection process. Intra-volumetric heat sources are applied to represent the heat generated by the heating element, and the dynamic boundary conditions are considered. The steady temperature and temperature uniformity of the flange are the assessment criteria for the thermal protection performance of the heating element.

Enlarging the heating area and increasing the heating power improved the flange's temperature and temperature uniformity. A heating power of 4.9 kW was suitable for engineering applications with the lowest temperature nonuniformity. Compared with continuous heating, the increased temperature nonuniformity was buffered, and the electrical power consumption was reduced by half using pulse heating. Pulse heating time intervals of 1, 3 and 4 h were determined for the spring, autumn and winter, respectively.

The originality of this study is to propose a novel electrical heat-tracing thermal protection system for the WTs flanges. The effect of different arrangements, heating powers and heating strategies was studied, by which the theoretical basis is provided for a stable and long-term utilization of the WT flange.

The purpose of this paper is to quantify the effects of thermal conductivity (TC), dielectric constant and dissipation factor (DF) of circuit laminates on the temperature rise with active components and RF trace heating.

Temperature rise measurements were made on surface mounted chip resistors (to simulate active components) at various dissipated power levels, with and without “via farms”. The RF heating temperature rise of 50 ohm microstrip transmission lines on 0.5 mm laminates was also measured by the same method.

The chip resistor temperature rise correlated with the independently measured TC of the laminate materials. The use of a “via farm” substantially reduced the temperature rise in all materials, but the higher TC laminates still conferred a measurable advantage. The trace temperature rise due to RF heating correlated with both TC and DF.

It was shown that the one‐dimensional heat transfer model does not accurately calculate the temperature rise due to significant in‐plane heat spreading, particularly with lower TC materials.

This paper details how temperature rise of both active components and 50 ohm transmission lines is affected by the thermal and electrical properties of the circuit laminate.

UNTIL recently, water was the Cinderella of chemical raw materials. This is despite the bizarre fact, on which biology depends, that water is so hospitable to life that 30 seconds exposure to air of a Petri dish containing pure sterile water will ensure that it becomes a culture of bacteria, moulds and algae.

Pipeline Induction Heat (PIH), on behalf of Kestrel Subsea (main contractors to Occidental Petroleum (Caledonia Ltd.), recently completed a contract to internally clean and coat 17.6 kilometres of 6in and 10in diameter pipes. These pipelines may carry a mix of crude oil and corrosive gas at elevated temperatures, and therefore were internally protected against corrosion. The project was the first of its kind in the North Sea and combined the application of a cold cure liquid epoxy paint with a novel PIH‐designed electrical heating system, which ensured that the entire 17.6 kilo‐metre length of pipeline was maintained at acceptable temperatures throughout the cleaning and coating operations. This not only aided chemical cleaning but also ensured a rapid and satisfactory cure for the coating.

The purpose of this paper is to understand corrosion behavior of copper and aluminum in monopropylene glycol-based heat transfer fluid by using synthetic and green inhibitors.

Weight loss, potentiodynamic and impedance measurements were applied to specimens to obtain their electrochemical characteristics and corrosion behaviors. Ageing test was applied to the fluids that contain different corrosion inhibitors to see the effect of inhibitors on fluid structure, and surface morphologies were examined by scanning electron microscopy (SEM).

The corrosion tests showed that synthetic inhibitors have better anti-corrosion potential than green inhibitors.

Like the synthetic corrosion inhibitors, there is growing interest in green inhibitors. Synthetic corrosion inhibitors are expensive and toxic for live beings, but green inhibitors from naturel sources are easy to reach and non-toxic for live beings and environment.

For solar heating systems, there is a need to select the correct heat transfer fluid; corrosion behavior of fluid plays a major role in the operation because the big part of the heating system consists of copper and aluminum close to ferrius metals and stainless steel.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

Food—national dietary standards—is a sensitive index of socio‐economic conditions generally; there are others, reflecting different aspects, but none more sensitive. A country that eats well has healthy, robust people; the housewife who cooks hearty, nourishing meals has a lusty, virile family. It is not surprising, therefore, that all governments of the world have a food policy, ranking high in its priorities and are usually prepared to sacrifice other national policies to preserve it. Before the last war, when food was much less of an instrument of government policy than now—there were not the shortages or the price vagaries—in France, any government, whatever its colour, which could not keep down the price of food so that the poor man ate his fill, never survived long; it was—to make use of the call sign of those untidy, shambling columns from our streets which seem to monopolize the television news screens—“out!” Lovers of the Old France would say that the country had been without stable government since 1870, but the explanation for the many changes in power in France in those pre‐war days could be expressed in one word—food!

The year 2013-14 was very significant for Raychem RPG Ltd (RRL) - a joint venture between RPG group, India and TE Connectivity, USA. The sales were looking up and order book was promising. Newly restructured units were working well and business in new segments was picking up. There were several initiatives undertaken by the CEO in last five years of his tenure. His team had achieved the desired stability and turnaround was successful. A high-growth future in a slowing global economic scenario had to be converted into a more profitable opportunity. However, he faced several questions. Was the strategic transformation journey that he embarked on four years ago complete? Could he have done something different? Which were the areas where the next focus should be? Did RRL have the required competences to succeed in those areas? How would RRL manage the changing expectations of the two JV partners?

A large number of coatings have been described which serve very specific purposes. An example is a foam coating which may be applied by spraying, dipping, or other normal procedures. On curing, however, there is sufficient gas generation to foam the coating. A fine cellular structure results. The resulting layer is thick but light and has a very high strength‐to‐volume ratio as well as insulating properties [Downey Finishing Corp., 1629 S. 55th Ave., Cicero, IL 60650].