International Journal of Integrated Engineering
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Assessing Potentiality of Underground Coal Gasification for the Coalfields of Bangladesh
Get PDFUnderground coal gasification (UCG) can be a viable unconventional coal mining method for long-sought mining solution for the coalfields of Bangladesh, while conventional mining techniques (i.e., underground or opencast) have been disputed for decades. However, there is essentially no work done on UCG potentiality analysis considering the properties of all the coalfields collectively based on the worldwide experiences. To increase a better understanding of UCG prospect identification of Coalfields of Bangladesh, this study is therefore of interest. The study explores the essential factors required to assess the potentiality of 5 Coalfields of Bangladesh for UCG application. The quantification of threshold values was retrieved from published data of known trials occurred around the world. These were then compared with the available data of Coalfields of Bangladesh. In terms of the UCG prospects, all the coalfields passed the depth, thickness, ash content and rank factors to a significant extent. But faulting, overburden or aquifer proximity are somewhat critical for all the coalfields except Jamalganj. This work can help initiating further steps through the analogous approach for siting the first UCG trial in Bangladesh
Effect of Aging Treatment and TiO2 Nano Particles Addition on the Microstructure and Mechanical Properties of 2024 Aluminum Alloy
Get PDFIn this study we reinforced aluminum alloy 2024 with the different mass fractions (0 wt.%, 2.5 wt.%, 5 wt.% and 7.5 wt.%) of titanium dioxide nanoparticles using stir casting method followed by solution annealing at 500 °C for 3 h, quenching in water and aging at 175°C for 3 h. The main objective was to study an effect of an addition of TiO2 nanoparticles on the microstructure and the mechanical properties of the 2024 aluminum alloy composite fabricated by stir casting. Scanning electron microscopy, energy-dispersive analysis, as well as X-ray diffraction analysis were implemented to characterize the microstructure, elemental and phase composition of the samples. The tensile and Vickers hardness tests were carried out to evaluate the mechanical properties. The results showed that the addition of 7.5 wt.% TiO2 nanoparticles increases the ultimate tensile strength by 37 % and elongation by 71 % while decreases the hardness by 14 % comparing with the initial alloy. The highest hardness was demonstrated in the alloy with 5 wt. % TiO2.
 
Assessment of Agricultural Drought Using the Normalized Difference Drought Index (NDDI) to Prediction Drought at Corong River Basin
Get PDFAs a complex and widespread natural phenomenon, drought poses a significant threat to the agricultural sector, especially in developing countries, resulting in significant economic losses. Its close relationship with water resilience and crop production necessitates sophisticated monitoring approaches for agricultural drought. Leveraging satellite remote sensing technology and various data types such as multispectral, thermal infrared, and microwave, can monitor drought on a large scale. This technology provides a comprehensive perspective for timely and spatial data collection, facilitating the monitoring of vegetation in vast agricultural areas. The study focuses on developing an agricultural drought model from 2017 to 2021, using Landsat 8 imagery. The model integrates the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI), resulting in the establishment of the Normalized Difference Drought Index (NDDI) method. To predict agricultural drought in the Corong River Basin, the study employs the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Findings reveal varying degrees of dryness in the Corong River River Basin, with 77% categorized as Strong dry conditions, 1% as Dry, 0.3% as Moderate wetness, and 21.6% as wetness. Drought predominantly occurs between July and October, impacting approximately 78% of the total dry area and extending across almost the entire region. The SARIMA (0,0,1)(3,0,0)12 model, with a MAPE value of 0.2399, emerges as the most effective for predicting agricultural drought. These forecasted results provide critical insights into the level of agricultural drought in the Corong River Basin and valuable information for drought mitigation strategies, especially in regulating the distribution of irrigation water
Performance Analysis of Nano Transistor Based Binary and Ternary Logic Gates
Get PDFAs technology scales down to the nanoscale regime, several short channel effects emerge, which have a greater impact on device performance. Researchers are exploring for innovative materials that can fit into nanometer-sized spaces to improve the performance of digital circuits. This paper provides Nano transistor-based digital circuits for improving digital circuit performance over traditional MOSFET-based circuits. Carbon nanotubes (CNTs) and graphene nano ribbons (GNR) have been investigated as possible candidates because to their high carrier mobility. The influence of CNTFET and GNRFET parametric variation with threshold voltage on performance metrics such as delay, and power has been investigated. A comparison of MOSFET, CNTFET, and GNRFET-based logic circuits is performed. A primer on ternary logic is also provided. Because of the dependence of the threshold voltage on the shape of carbon nanotubes and graphene nano ribbons, it is possible to use it for ternary logic design. Following that, ternary logic circuits are constructed with CNTFETs and GNRFETs. It has been determined that CNTFET and GNRFET-based circuits are more energy efficient than standard MOSFET circuits. It is also established that innovative ternary logic offers a relatively fast and low power digital circuit design option. All digital circuits were simulated using the HSPICE tool for the 32nm technology node
Designing for Homeless in Kuala Lumpur: Concepts and Case Studies
Get PDFHomelessness issue in Kuala Lumpur has no permanent solution. There are current needs to provide definite helps and solutions. This paper aims to identify and explore the concepts and ideas in providing shelter for the homeless in Kuala Lumpur. A qualitative and conventional content analysis of narrative data is implemented to achieve the research aim. Series of case studies explains the concepts and ideas that may be implemented as part of the possible solutions in providing shelter for the homeless in Kuala Lumpur. This study will hopefully provide significant finding that may be applied towards designing a proper basic community shelter for the homeless in Kuala Lumpur
IoT-Based Automatic Transfer Switch System Design on Solar Home System
Get PDFThe challenge hybrid system power sources face is switching from one source to another. This transfer is required to anticipate the depletion of energy sources in the battery owing to unfavorable weather, such that the solar panels do not receive sufficient sunlight. An automatic switching process with minimal time lag is required to maintain the continuity of the electrical energy flow. In addition, there is a growing need to analyze the energy consumption in certain areas and periods. This project designed and built an Internet of Things (IoT) based Automatic Transfer Switch (ATS) system. The ATS prototype uses the Arduino MEGA 2560 microcontroller to switch the power source and the ESP32 DevKit V1 microcontroller to send the data logger to the IoThingsHub cloud platform for monitoring systems that are useful for sustainable ecosystems. The sensor exhibited accuracies of 99.8% for voltage and 96.5% for current readings. The ATS prototype could switch between power sources with an average time lag of 47 ms. The results of the field trials show that the ATS prototype design utilized solar photovoltaic for approximately 26% of the usage, with a 100 Ah 12V battery system and three 100 Wp solar panels in sunny/partly cloudy conditions for 50 W lamp loads
Hardness and Microstructure Characterization of Hardfacing Alloys Deposited by The Shielded Metal Arc Welding (SMAW) on AISI 1045 Medium Carbon Steel
Get PDFA ring frame is a machine used for yarn production in the textile industry. Continuous use of the machine results in wear on the shaft timing pulley on the ring frame machine. To improve this condition, repairs are needed, one of which uses the hardfacing method. This study aims to determine the effect of hardfacing on the microstructure and hardness of the shaft timing pulley made from AISI 1045. The hardfacing process used the shielded metal arc welding (SMAW) method with welding current variations of 115 A, 125 A, 135 A, 145 A, and 155 A. In this study, the electrode used was AWS A5.1 E7018 with a diameter of 3.2 mm. The hardfacing product obtained was then finished with a lathe to produce a shaft with a final diameter of 30 mm. In this study, microstructure and hardness tests were carried out on specimens before and after finishing. The results of this study showed that an increase in current caused an increase in the number of pearlite phases in the weld metal and HAZ (heat-affected zone) areas. While in the base metal, the increase in current increased the number of ferrite phases. The highest hardness value was found in specimens that were hardfaced with a current of 145 A. However, the hardness of the hardfacing layer will decrease with the use of currents greater than 145 A. The hardness of the specimens with hardfacing treatment at a current of 145 A resulted in hardness in the weld metal, HAZ, and base metal of 225 HV, 209 HV, and 203 HV, respectively. After the finishing process, the weld metal, HAZ, and base metal in this specimen produced a hardness of 225 HV, 217 HV, and 208 HV, respectively
Atmospheric Cloud Image Detection with Convolutional Neural Network (CNN)
Get PDFCloud is an aerosol consisting of visible mass of miniature liquid droplets, frozen crystal, or other particles suspended in the atmosphere. The study of atmospheric clouds is crucial for us to better understand and predict the behaviors of clouds, which has implications for climate, weather, aviation safety, agriculture, and energy production. Convolutional neural network (CNN) method is applied to train an atmospheric cloud image detection model to identify the presence of cloud and classify them. Supervised learning method is applied to train the model such that the machine is given labeled cloud image dataset to learn how to classify and predict the presence of cloud. U-Net architecture is used to train the atmospheric cloud image detection model because the architecture has the highest performance in image segmentation especially object detection in satellite images. The 38-Cloud Dataset which is used to train the model, is obtained from Landsat 8 Earth observation satellite. The dataset is randomly divided into training set (75% of the total images) and validation set (25% of the total images). Following this, the dataset is preprocessed and transformed into tensors to train the model. The training has been carried out for 50 epochs. Apart from the U-Net architecture proposed, the architecture is further modified with ResNet34 and VGG16 and the performance of each model is studied. The recognition accuracy obtained for atmospheric cloud image detection trained with the dataset achieved 97%. With this accuracy, U-Net architecture can be justified as a powerful and suitable convolutional neural network in performing atmospheric cloud image detection. 
Model-Based Glycaemic Control in Multicentre ICUs within Diabetic Patients: In-silico Analysis
Get PDFSliding-scale insulin therapy has been vastly used for glycaemic control but dysglycaemia remains high. Model-based glycaemic control that incorporates insulin nutrition protocol was proposed as this therapy provides personalized care to avoid dysglycaemia. Thus, this paper aims to implement in-silico simulation and identify which model-based control protocols yield better protocol within ICU diabetic patients based on performance and safety. Multicentre ICU patients of 282 were divided into diabetes mellitus (DM) and non-diabetes mellitus (NDM) cohort where in-silico simulations were done using Specialised Relative Insulin Nutrition Therapy (SPRINT), SPRINT+Glargine and Stochastic Targeted (STAR) protocols. Performance was verified based on the percentage of blood glucose (BG) time in band (TIB) 6.0 – 10.0 mmol/L and safety with number of mild and severe hypoglycaemia episodes. Among the three protocols, STAR protocol showed the highest median and interquartile range % BG TIB 6.0 – 10.0 mmol/L for DM and NDM patients with 71.6 % [57.9 – 79.8] and 77.4 % [62.9 – 88.8]. The number of hypoglycaemia episodes are the lowest in DM and NDM patients too compared to other protocols. These advantages show that STAR protocol can provide better patient outcomes for glycaemic control with personalized care
Indirect Liquid Cooling for Battery Thermal Management: A Review
Get PDFThe thermal management system of batteries is a critical aspect of battery management for optimizing battery performance and lifespan. Research has rapidly progressed in battery thermal management in the past decade, mainly by adopting indirect liquid cooling methods. This article provides an in-depth overview of the recent developments in indirect liquid cooling application for battery thermal management, encompassing fundamental principles, types of fluids, and the strengths and weaknesses of this method. Various heat transfer techniques, such as convective heat transfer and heat generation, are also examined to comprehend effective ways of precisely managing battery temperature. The benefits and challenges of this indirect liquid cooling approach are evaluated, considering crucial criteria like safety. The results of this review demonstrate that the indirect liquid cooling method holds promise as an effective solution to address thermal challenges in batteries, with the potential to enhance overall battery performance and durabilit