The Effect of Si and Extrusion Process on the Microstructure and Tensile Properties of Mg-Mg2Si Composite

AbstractThis investigation has been carried out to study the influence of extrusion process on microstructure and tensile properties of Mg-Mg2Si composite with different amounts of Si (3, 5 and 7wt.%). Microstructural examination was carried out using optical microscopy (OM). The cast specimens were extruded at 350°C at different extrusion ratios (6:1, 12:1 and 18:1). The results showed that the specimens with lower Si contents, have higher ultimate tensile strength (UTS) and tensile elongation values. Moreover, there was a considerable improvement in tensile properties for the specimens extruded with the ratio of 12:1 and 18:1 in comparison to the specimens of 6:1. This can be attributed to the significant reduction in size of primary Mg2Si particles from more than 200μm to 20μm, 10μm and 5μm after extrusion with the ratio of 6:1, 12:1 and 18:1, respectively. The highest UTS values were found to be 265MPa for extruded with 1:18 ratio of Mg-3Si composite

Development of a convolutional neural network joint detector for non-orthogonal multiple access uplink receivers

We present a novel approach to signal detection for Non-Orthogonal Multiple Access (NOMA) uplink receivers using Convolutional Neural Networks (CNNs) in a single-shot fashion. The defacto NOMA detection method is the so-called Successive Interference Cancellation which requires precise channel estimation and accurate successive detection of the user equipment with the higher powers. It is proposed converting incoming packets into 2D image-like streams. These images are fed to a CNN-based deep learning network commonly used in the image processing literature for image classification. The classification label for each packet converted to an image is the transmitted symbols by all user equipment joined together. CNN network is trained using uniformly distributed samples of incoming packets at different signals to noise ratios. Furthermore, let’s performed hyperparameter optimization using the exhaustive search method. Our approach is tested using a modeled system of two user equipment systems in a 64-subcarrier Orthogonal Frequency Division Multiplexing (OFDM) and Rayleigh channel. It is found that a three-layer CNN with 32 filters of size 7×7 has registered the highest training and testing accuracy of about 81. In addition, our result showed significant improvement in Symbol Error Rate (SER) vs. Signal to Noise Ratio (SNR) compared to other state-of-the-art approaches such as least square, minimum mean square error, and maximum likelihood under various channel conditions. When the channel length is fixed at 20, our approach is at least one significant Figure better than the maximum likelihood method at (SNR) of 2 dB. Finally, the channel length to 12 is varied and it is registered about the same performance. Hence, our approach is more robust to joint detection in NOMA receivers, particularly in low signal-to-noise environment

A Detailed Hydrodynamic Study of the Split-Plate Airlift Reactor by using Non-Invasive Gamma-Ray Techniques

This study focused on detailed investigations of selected local hydrodynamics in split airlift reactor by using an unconventional measurements facility: computed tomography (CT) and radioactive particle tracking (RPT). The local distribution in a cross-sectional manner with its radial\u27s profiles for gas holdup, liquid velocity flow field, shear stresses, and turbulent kinetic energy were studied under various gas velocity 1, 2 and 3 cm/s with various six axial level z = 12, 20, 40, 60, 90 and 112 cm. The distribution in gas–liquid phases in the whole split reactor column, the riser and downcomer sides, including their behavior at the top and bottom sections of the split plate was also described. The outcomes of this study displayed an exemplary gas–liquid phases dispersion approximately in all reactor\u27s zones and had large magnitude over the ring of the sparger as well as upper the split plate. Furthermore, the outcomes pointed out that the distribution of this flow may significantly impacts the performance of the split reactor, which may have essential influence on its performance particularly for microorganisms culturing applications. These outcomes are dependable as benchmark information to validate computational fluid dynamics (CFD) simulations and other models

A Detailed Hydrodynamic Study of the Split-Plate Airlift Reactor by using Non-Invasive Gamma-Ray Techniques

This study focused on detailed investigations of selected local hydrodynamics in split airlift reactor by using an unconventional measurements facility: computed tomography (CT) and radioactive particle tracking (RPT). The local distribution in a cross-sectional manner with its radial\u27s profiles for gas holdup, liquid velocity flow field, shear stresses, and turbulent kinetic energy were studied under various gas velocity 1, 2 and 3 cm/s with various six axial level z = 12, 20, 40, 60, 90 and 112 cm. The distribution in gas-liquid phases in the whole split reactor column, the riser and downcomer sides, including their behavior at the top and bottom sections of the split plate was also described. The outcomes of this study displayed an exemplary gas-liquid phases dispersion approximately in all reactor\u27s zones and had large magnitude over the ring of the sparger as well as upper the split plate. Furthermore, the outcomes pointed out that the distribution of this flow may significantly impacts the performance of the split reactor, which may have essential influence on its performance particularly for microorganisms culturing applications. These outcomes are dependable as benchmark information to validate computational fluid dynamics (CFD) simulations and other models

Enhancing Heat Transfer Performance In Simulated Fischer–Tropsch Fluidized Bed Reactor Through Tubes Ends Modifications

Fluidized bed reactors are essential in a wide range of industrial applications, encompassing processes such as Fischer–Tropsch synthesis and catalytic cracking. The optimization of performance and reduction in energy consumption in these reactors necessitate the use of efficient heat transfer mechanisms. The present work examines the considerable impact of tube end geometries, superficial gas velocity, and radial position on heat transfer coefficients within fluidized bed reactors. It was found that the tapered tube end configurations have been empirically proven to improve energy efficiency in fluidized bed reactors significantly. For example, at a superficial gas velocity of 0.4 m/s, the tapered end form\u27s local heat transfer coefficient (LHTC) demonstrated a significant 20% enhancement compared to the flat end shape. The results and findings of this work make a valuable contribution to the advancement of complex models, enhance the efficiency of fluidized bed reactor processes, and encourage further investigation into novel tube geometries

Real-Time classification of various types of falls and activities of daily livings based on CNN LSTM network

In this research, two multiclass models have been developed and implemented, namely, a standard long-short-term memory (LSTM) model and a Convolutional neural network (CNN) combined with LSTM (CNN-LSTM) model. Both models operate on raw acceleration data stored in the Sisfall public dataset. These models have been trained using the TensorFlow framework to classify and recognize among ten different events: five separate falls and five activities of daily livings (ADLs). An accuracy of more than 96% has been reached in the first 200 epochs of the training process. Furthermore, a real-time prototype for recognizing falls and ADLs has been implemented and developed using the TensorFlow lite framework and Raspberry PI, which resulted in an acceptable performance

Abiotic molecular oxygen production -- ionic pathway from sulphur dioxide

Molecular oxygen, O$_2$, is vital to life on Earth and possibly on other planets. Although the biogenic processes leading to its accumulation in Earth's atmosphere are well understood, its abiotic origin is still not fully established. Here, we report combined experimental and theoretical evidence for electronic-state-selective production of O$_2$ from SO$_2$, a major chemical constituent of many planetary atmospheres and one which played an important part on Earth in the Great Oxidation event. The O$_2$ production involves dissociative double ionisation of SO$_2$ leading to efficient formation of the O$_2^+$ ion which can be converted to abiotic O$_2$ by electron neutralisation. We suggest that this formation process may contribute significantly to the abundance of O$_2$ and related ions in planetary atmospheres, especially in those where CO$_2$, which can lead to O$_2$ production by different mechanisms, is not the dominant component

Cloud of Things and fog computing in Iraq: Potential applications and sustainability

This paper depicts the principles of Cloud of Things and fog computing and discusses its possible uses in Iraq with sustainability measures. The capacity of cloud computing to supply elastic, as-needed computer resources has garnered widespread interest worldwide. However, fog computing and a Cloud of Things enhance the Internet of Things by relocating computation to devices on the network's periphery. This study looks at how the Cloud of Things and fog computing are used now in Iraq, the obstacles, and the future uses of these technologies in various fields. To fully reap the benefits of the Cloud of Things and fog computing in Iraq, the study also emphasizes the significance of infrastructure development, policy design, cybersecurity, and other measures. This study will discuss the use of questionnaires in research. There are two distinct components to this. The first section includes questions regarding the respondents' affiliations, including their roles, departments, organization sizes, and ministries. The rest of the study's factors are discussed with inquiries in line with issues of cyber security, privacy, sustainability, cost of implementation, feasibility, trust, IT infrastructure, and government support. The survey's final open-ended inquiry will help us to compile a wide range of perspectives on what kinds of Cloud of Things and fog computing services based on the Iraqi government's needs

A Comprehensive Review Of The Influence Of Heat Exchange Tubes On Hydrodynamic, Heat, And Mass Transfer In Bubble And Slurry Bubble Columns

Bubble and slurry bubble column reactors (BCRs/SBCRs) are used for various chemical, biochemical, and petrochemical applications. They have several operational and maintenance advantages, including excellent heat and mass transfer rates, simplicity, and low operating and maintenance cost. Typically, a catalyst is present in addition to biochemical processes where microorganisms are used to produce industrially valuable bio-products. Since most applications involve complicated gas-liquid, gas-liquid-solid, and exothermic processes, the BCR/SBCR must be equipped with heat-exchanging tubes to dissipate heat and control the reactor\u27s overall performance. In this review, past and very recent experimental and numerical investigations on such systems are critically discussed. Furthermore, gaps to be filled and critical aspects still requiring investigation are identified