Numerical investigation on the electronic components' cooling for different coolants by finite element method

In this study, we conducted a numerical simulation to examine the cooling performance of an aluminum finned heat sink attached to a silicon chip, placed in a chamber of a rectangular cross-section. The heat sink is cooled by convective heat transfer utilizing nine commercially available gaseous coolants, namely air, hydrogen, helium, nitrogen, oxygen, carbon dioxide, freon12 vapor, propane, and ammonia. To select an appropriate coolant for electronic devices in terms of thermal–hydraulic performance, the maximum temperature on the chip domain and the associated pressure drop in the cooling channel as a function of coolant velocity are analyzed for the aforementioned fluids. It has been found that the minimum temperature is recorded for propane and freon12 vapor, which is approximately 31.1°C, for a coolant velocity of 0.5 m/s, but freon12 vapor shows the highest pressure drop, approximately 900 mPa, among all coolants. In the overall velocity regime, hydrogen shows the best cooling performance in terms of both cooling capacity and hydrodynamic characteristics. But considering safety issues, helium can be a better alternative. This comprehensive study provides a better understanding of different coolant performances, which will aid engineers to develop an effective cooling technique to accommodate the inexorably rising power demand.     

40 Years of IMWA in Poland

Mine Water and the Environment - In diesem IMWA-Einblick wird die langjährige und umfangreiche Tätigkeit polnischer Hydrogeologen auf dem Themengebiet des Grubenwassers dargestellt....     

ACTION OF PHYSISORBED COLLECTOR IN PARTICLE–BUBBLE ATTACHMENT

Journal of Mining Science - The action of the arbitrary physisorbed species of a collector at a mineral is compared with the theoretical evidence on particle–bubble attachment. The lack of...     

Rare Metal and Rare Earth Recovery from Silica Gel—Eudialyte Concentrate Leaching Product

Journal of Mining Science - The effect of various parameters (S:L ratio, duration, temperature and intensity of ultrasonic treatment) on recovery efficiency of zirconium and rare earth elements...     

Adsorption Properties of Modified Saponite in Removal of Heavy Metals from Process Water

Journal of Mining Science - The adsorption properties of electrochemically and thermally modified saponite relative to heavy metals are analyzed. The tests have found the efficient use and...     

Application of a micro-channel reactor for process intensification in high purity syngas production via H2O/CO2 co-splitting

A stainless steel micro-channel reactor was tailor-made to an in house-design for process intensification propose. The reactor was used for a two-step thermochemical cycles of H₂O and CO₂ co-splitting reaction, in the presence of La_0.3Sr_0.7Co_0.7Fe_0.3O₃ (LSCF). LSCF was coated inside the reactor using wash-coat technique. Oxygen storage capacity of LSCF was determined at 4465 μmol/g, using H₂-TPR technique. H₂O-TPSR and CO₂-TPSR results suggested that a formation of surface hydroxyl group was the cause of H₂O splitting favorable behavior of LSCF. Optimal operating reduction/oxidation temperature was found at 700 °C, giving 2266 μmol/g of H₂, 705 μmol/g of CO, and 67% of solid conversion, when the H₂O and CO₂ ratio was 1 to 1, and WSHV was 186,000 mL/g.h. Activation energy of H₂O spitting and CO₂ splitting was estimated at 87.33 kJ/mol, and 102.85 kJ/mol The pre-exponential factor of H2O splitting and CO2 splitting was 595.24 s^?1 and 698.79 s^?1, respectively.     

Comparison of theoretical methods of the hydrogen storage capacities of nanoporous carbons

The hydrogen storage capacities of nanoporous carbons, simulated as graphene slit-shaped pores, have been calculated using simple theoretical methods that do not involve computationally expensive calculations. The theoretical methods calculate the storage of hydrogen molecules on a solid porous material by using the Equation Of State, EOS, of the hydrogen gas and the interaction potential energy of H₂ with the surfaces of the pores of the material. Calculations have been carried out using the same interaction potential energy and empirical EOS. The interaction potential energy is obtained from calculations of H₂ on graphene, using a DFT-based method that includes the dispersion interactions. The storage capacities have been calculated as a function of pressure in the range 0.1–25 MPa, of pore width in the range 4.7–20 Å and at 80.15 and 298.15 K. The storage capacities obtained with the methods are compared and the advantages and limitations of the methods are discussed, as well as the storage capacities predicted by the methods for wide pores. These simple theoretical methods are useful to design novel materials for hydrogen storage.     

An EWMA signed ranks control chart with reliable run length performances

During the design phase of a control chart, the determination of its exact run length properties plays a vital role for its optimal operation. Markov chain or integral equation methods have been extensively applied in the design phase of conventional control charts. However, for distribution-free schemes, due to the discrete nature of the statistics being used (such as the sign or the Wilcoxon signed rank statistics, for instance), it is impossible to accurately compute their run length properties. In this work, a modified distribution-free phase II exponentially weighted moving average (EWMA)-type chart based on the Wilcoxon signed rank statistic is considered and its exact run length properties are discussed. A continuous transformation of the Wilcoxon signed rank statistic, combined with the classical Markov chain method, is used for the determination of the average run length in the in- and out-of control cases. Moreover, its exact performance is derived without any knowledge of the distribution of sample observations. Finally, an illustrative example is provided showing the practical implementation of our proposed chart.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.