Search results for: temperature distribution

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 184

Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

Procedia PDF Downloads 57

Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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Rubber seed oil is an attractive alternative feedstock for biodiesel production because it is not related to food-chain plant. Rubber seed oil contains large amount of free fatty acids, which causes problem in biodiesel production. Free fatty acids can react with alkaline catalyst in biodiesel production. Acid esterification is used as pre-treatment to convert unwanted compound to desirable biodiesel. Phase separation of oil and methanol occurs at low ratio of methanol to oil and causes low reaction rate and conversion. Acid esterification requires large excess of methanol in order to increase the miscibility of methanol in oil and accordingly, it is a more expensive separation process. In this work, the kinetics of esterification of rubber seed oil with methanol is developed from available experimental results. Reactive distillation process was designed by using Aspen Plus program. The effects of operating parameters such as feed ratio, molar reflux ratio, feed temperature, and feed stage are investigated in order to find the optimum conditions. Results show that the reactive distillation process is proved to be better than conventional process. It consumes less feed methanol and less energy while yielding higher product purity than the conventional process. This work can be used as a guideline for further development to industrial scale of biodiesel production using reactive distillation.

Keywords: biodiesel, reactive distillation, rubber seed oil, transesterification

Procedia PDF Downloads 338

Authors: Ritula Thakur, Babankumar S. Bansod, Puneet Mehta, S. Chatterji

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Moisture plays an important role in storage, harvesting and processing of food grains and related agricultural products. It is an important characteristic of most agricultural products for maintenance of quality. Accurate knowledge of the moisture content can be of significant value in maintaining quality and preventing contamination of cereal grains. The present work reports the design and development of microcontroller based low cost non-destructive moisture meter, which uses complex impedance measurement method for moisture measurement of wheat using parallel plate capacitor arrangement. Moisture can conveniently be sensed by measuring the complex impedance using a small parallel-plate capacitor sensor filled with the kernels in-between the two plates of sensor, exciting the sensor at 30 KHz and 100 KHz frequencies. The effects of density and temperature variations were compensated by providing suitable compensations in the developed algorithm. The results were compared with standard dry oven technique and the developed method was found to be highly accurate with less than 1% error. The developed moisture meter is low cost, highly accurate, non-destructible method for determining the moisture of grains utilizing the fast computing capabilities of microcontroller.

Keywords: complex impedance, moisture content, electrical properties, safety of food

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

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A process that utilizes a combination of additive manufacturing (AM), a preceramic polymer, and a chopped carbon fiber precursorto fabricate Silicon Carbon/ Carbon fibers (SiC/C) composites have been developed. The study has shown a promising, cost-effective, and efficient route to fabricate complex SiC/C composites using additive manufacturing. A key part of this effort was the mapping of the material’s microstructure through the thickness of the composite. Microstructural features in the pyrolyzed composites through the successive AM layers, such as defects, crystal size and their distribution, interatomic spacing, chemical bonds, were investigated using high-resolution scanning and transmission electron microscopy. As a result, the microstructure developed in SiC/C composites after printing, cure, and pyrolysis has been successfully mapped through the thickness of the derived composites. Dense and nearly defect-free parts after polymer to ceramic conversion were observed. The ceramic matrix composite displayed three coexisting phases, including silicon carbide, silicon oxycarbide, and turbostratic carbon. Lattice fringes imaging and X-Ray Diffraction analysis showed well-defined SiC and turbostratic carbon features. The cross-sectional mapping of the printed-then-pyrolyzed structures has confirmed consistent structural and chemical features within the internal layers of the AM parts. Noteworthy, however, is that a crust-like area with high crystallinity has been observed in the first and last external layers. Not only do these crust-like regions have structural characteristics distinct from the internal layers, but they also have elemental distributions different than the internal layers.

Keywords: SiC, preceramic polymer, additive manufacturing, ceramic

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: Nattapol Pourprasert, Siriwan Manowan

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This study aims to find out what budget problems Thailand is facing with and how the results from the comparison between the budgeting reform by Thailand and the reforms by OECD member countries can be used for carrying out budgeting reform of Thailand. The findings from the study on the budget problems that Thailand is facing with reveal that the budgeting system of Thailand lacks of the assessment for the cost-effectiveness of the expenditure of borrowed money and budgets in order to determine whether the expenses are worth the taxes collected from people or not. This is because most popularity policies have unlimited budgets which can lead to the financial risks. Also, these policies create great tax burdens for the descendants in the future and affect the fair distribution of incomes but the Parliament of Thailand never considers these facts. The findings from the comparison between Thai budgeting reform and those by OECD member countries manifest that the traditional budgeting system of Thailand is the department-based budgeting, which is still used without being changed or adjusted in order to fit the new administrative regimes. This traditional budgeting system suggests that a department is responsible for budgeting tasks. Meanwhile, in OECD member countries, budgeting reforms are carried out simultaneously with the reforms of civil service systems so that they are driven in the same directions. The budgeting reforms that rely only on the analyses on economic or technical dimension can hardly lead to success. The budgeting systems of OECD member countries are designed to deal with the unique problems that each of the member countries is facing with rather than adopting the modern system developed by other countries. The budgeting system that has a complicated concept and practice has to be implemented under a flexible strategy so that the departments that implement it can learn about and adjust itself to the system. Continuous and consistent development and training for staff members are also necessary.

Keywords: budgeting reforms, Thailand, OECD member countries, budget problems

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Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Nitish Suvarna, Anjali Awasthi

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In an era marked by rapid technological advancements, the integration of Autonomous Vehicles into supply chain networks represents a transformative shift, promising to redefine the paradigms of logistics and transportation. This thesis delves into a comprehensive assessment of the impact of autonomous vehicles on supply chain performance, with a particular focus on network design, operational efficiency, and environmental sustainability. Employing the advanced simulation capabilities of anyLogistix (ALX), the study constructs a digital twin of a conventional supply chain network, encompassing suppliers, production facilities, distribution centers, and customer endpoints. The research methodically integrates Autonomous Vehicles into this intricate network, aiming to unravel the multifaceted effects on transportation logistics including transit times, cost-efficiency, and sustainability. Through simulations and scenarios analysis, the study scrutinizes the operational resilience and adaptability of supply chains in the face of dynamic market conditions and disruptive technologies like Autonomous Vehicles. Furthermore, the thesis undertakes carbon footprint analysis, quantifying the environmental benefits and challenges associated with the adoption of Autonomous Vehicles in supply chain operations. The insights from this research are anticipated to offer a strategic framework for industry stakeholders, guiding the adoption of Autonomous Vehicles to foster a more efficient, responsive, and sustainable supply chain ecosystem. The findings aim to serve as a cornerstone for future research and practical implementations in the realm of intelligent transportation and supply chain management.

Keywords: autonomous vehicle, agri-food supply chain, ALX simulation, anyLogistix

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Authors: Hiba El Assibi

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This study aims to weakly solve Kalah, a two-player board game, by developing a start-to-finish winning strategy using an optimized Minimax algorithm with Alpha-Beta Pruning. In weakly solving Kalah, our focus is on creating an optimal strategy from the game's beginning rather than analyzing every possible position. The project will explore additional enhancements like symmetry checking and code optimizations to speed up the decision-making process. This approach is expected to give insights into efficient strategy formulation in board games and potentially help create games with a fair distribution of outcomes. Furthermore, this research provides a unique perspective on human versus Artificial Intelligence decision-making in strategic games. By comparing the AI-generated optimal moves with human choices, we can explore how seemingly advantageous moves can, in the long run, be harmful, thereby offering a deeper understanding of strategic thinking and foresight in games. Moreover, this paper discusses the evaluation of our strategy against existing methods, providing insights on performance and computational efficiency. We also discuss the scalability of our approach to the game, considering different board sizes (number of pits and stones) and rules (different variations) and studying how that affects performance and complexity. The findings have potential implications for the development of AI applications in strategic game planning, enhancing our understanding of human cognitive processes in game settings, and offer insights into creating balanced and engaging game experiences.

Keywords: minimax, alpha beta pruning, transposition tables, weakly solving, game theory

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Authors: A. H. M. Zehadul Karim

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Cameron Highlands (4°28’N, 101°23’E) is an attractive mountainous region with steep slopes located in the state of Pahang, Malaysia stretching between 1070 and 1830m above sea level with a total land area of 71,218ha. It is one of the few places in Malaysia that has a tropical highland climate as the mean annual temperature of it is 18 °C (64 °F) thus making the atmosphere perfect for specialized agriculture. Being ecologically suitable, Cameron Highlands has recently been identified as a very strategic farming area, producing multifarious vegetables, flowers and tea with a commercial motive of marketing them to Singapore and all over the urban areas of Malaysia to meet the domestic and international demands. The main intricacies of this plantation agriculture are fully dependent on the policies formulated by a group of emerging entrepreneurs who employ foreign labourers to make these agricultural activities a success in the agrarian sector in Malaysia. Based on the socio-anthropological perspective, the paper entirely relies on empirical field data generated by interviewing 10 farm owners and 200 foreign workers to find out the intricacies of this plantation agriculture which makes the research innovative and pragmatically significant. The paper deals with important issues relating to this productive plantation agriculture of Cameron Highlands and as such, narrates the various exceptional and holistic skills adopted for this type of farming.

Keywords: Cameron Highlands Malaysia, plantation agriculture, issues and challenges, mechanisms

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Authors: Mohammed Abaoli, Omer Kara

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The current research has investigated the soil quality status under dryland vegetation of Yabello district, Southern Ethiopia in which we should identify the nature and extent of salinity problem of the area for further research bases. About 48 soil samples were taken from 0-30, 31-60, 61-90 and 91-120 cm soil depths by opening 12 representative soil profile pits at 1.5 m depth. Soil color, texture, bulk density, Soil Organic Carbon (SOC), Cation Exchange Capacity (CEC), Na, K, Mg, Ca, CaCO₃, gypsum (CaSO₄), pH, Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP) were analyzed. The dominant soil texture was silty-clay-loam.  Bulk density varied from 1.1 to 1.31 g/cm³. High SOC content was observed in 0-30 cm. The soil pH ranged from 7.1 to 8.6. The electrical conductivity shows indirect relationship with soil depth while CaCO₃ and CaSO₄ concentrations were observed in a direct relationship with depth. About 41% are non-saline, 38.31% saline, 15.23% saline-sodic and 5.46% sodic soils. Na concentration in saline soils was greater than Ca and Mg in all the soil depths. Ca and Mg contents were higher above 60 cm soil depth in non-saline soils. The concentrations of SO₂^-4 and HCO^-3 were observed to be higher at the most lower depth than upper. SAR value tends to be higher at lower depths in saline and saline-sodic soils, but decreases at lower depth of the non-saline soils. The distribution of ESP above 60 cm depth was in an increasing order in saline and saline-sodic soils. The result of the research has shown the direction to which extent of salinity we should consider for the Commiphora plant species we want to grow on the area. 

Keywords: commiphora species, dryland vegetation, ecological significance, soil quality, salinity problem

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Authors: Haneef Ur Rehman, Afsheen Aman, Abdul Hameed Baloch, Shah Ali Ul Qader

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Pectinase is a heterogeneous group of enzymes that catalyze the hydrolysis of pectin substances and widely has been used in food and textile industries. In current study, pectinase from B. licheniformis KIBGE-IB21 was immobilized within different polymers (calcium alginate beads, polyacrylamide gel and agar-agar matrix) to enhance its catalytic properties. Polyacrylamide gel was found to be most promising one and gave maximum (89%) immobilization yield. While less immobilization yield was observed in case of calcium alginate beads that only retained 46 % activity. The reaction time for maximum pectinolytic activity was increased from 5.0 to 10 minutes after immobilization. The temperature of pectinase for maximum enzyme activity was increased from 45 °C to 50 °C and 55 °C when it was immobilized within agar-agar and calcium alginate beads, respectively. The optimum pH of pectinase didn’t alter when it was immobilized within polyacrylamide gel and calcium alginate beads, but in case of agar-agar it was changed from pH 10 to pH 9.0. Thermal stability of pectinase was improved after immobilization and immobilized pectinase showed higher toleration against different temperatures as compared to free enzyme. It can be concluded that the entrapment is a simple, single step and promising procedure to immobilized pectinase within different synthetic and non-synthetic polymers and enhanced its catalytic properties.

Keywords: pectinase, characterization immobilization, polyacrylamide, agar-agar, calcium alginate beads

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Authors: Muhammad Faisal, Zai-Jin You, Muhammad Naeem

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Concerns about the environment, public health, and the economy are raised by the fact that the world produces around 6 trillion cigarettes annually. Arguably the most pervasive forms of environmental litter, this dangerous trash must be eliminated. The researchers wanted to get an idea of how much pollution is seeping out of cigarette butts in metropolitan areas by studying their distribution and concentration. In order to accomplish this goal, the cigarette butt pollution indicator was applied in 29 different areas. The locations were monitored monthly for a full calendar year. The conditions for conducting the investigation of the venues were the same on both weekends and during the weekdays. By averaging the metal leakage ratio in various climates and the average weight of cigarette butts, we were able to estimate the total amount of heavy metal leakage. The findings revealed that the annual average value of the index for the areas that were investigated ranged from 1.38 to 10.4. According to these numbers, just 27.5% of the areas had a low pollution rating, while 43.5% had a major pollution status or worse. Weekends witnessed the largest fall (31% on average) in all locations' indices, while spring and summer saw the largest increase (26% on average) compared to autumn and winter. It was calculated that the average amount of heavy metals such as Cr, Cu, Cd, Zn, and Pb that seep into the environment from discarded cigarette butts in commercial, residential, and park areas, respectively, is 0.25 µg/m2, 0.078 µg/m2, and 0.18 µg/m2. Butt from cigarettes is one of the most prevalent forms of litter in the area that was examined. This litter is the origin of a wide variety of contaminants, including heavy metals. This toxic garbage poses a significant risk to the city.

Keywords: heavy metal, hazardous waste, waste management, litter

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Authors: Filipa Vasconcelos

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The administration of endoplasmic reticulum amino peptidases (ERAP1 or ERAP2) inhibitors can be used for therapeutic approaches against cancer and auto-immune diseases. However, one of the main shortcomings of drug delivery systems (DDS) is associated with the drug off-target distribution, which can lead to an increase in its side effects on the patient’s body. To overcome such limitations, the encapsulation of four representative compounds of ERAP inhibitors into Polycaprolactone (PCL), Polyvinyl-alcohol (PVA), crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes is proposed as a safe and controlled drug release system. The use of electrospun fibrous meshes as a DDS allows efficient solvent evaporation giving limited time to the encapsulated drug to recrystallize, continuous delivery of the drug while the fibers degrade, prevention of initial burst release (sustained release), tunable dosages, and the encapsulation of other agents. This is possible due to the fibers' small diameters and resemblance to the extracellular matrix (confirmed by scanning electron microscopy results), high specific surface area, and good mechanical strength/stability. Furthermore, release studies conducted on PCL, PVA, crosslinked PVA, and PVA with nanoparticles (liposomes) electrospun fibrous meshes with each of the ERAP compounds encapsulated demonstrated that they were capable of releasing >60%, 50%, 40%, and 45% of the total ERAP concentration, respectively. Fibrous meshes with ERAP_E compound encapsulated achieved higher released concentrations (75.65%, 62.41%, 56.05%, and 65.39%, respectively). Toxicity studies of fibrous meshes with encapsulated compounds are currently being accessed in vitro, as well as pharmacokinetics and dynamics studies. The last step includes the implantation of the drug-loaded fibrous meshes in vivo.

Keywords: drug delivery, electrospinning, ERAP inhibitors, liposomes

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Authors: Aditya Pal, S. Z. S. Tabish, Kumar Neeraj Jha

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In the construction industry, engineering procurement and construction (EPC) projects are becoming increasingly prevalent; they provide clients with benefits such as decreased workload, streamlined execution, and a singular point of accountability. EPC projects entail round-the-clock operations, which calls for an analysis of the variables that impact productivity during nocturnal hours. The current body of research on the distinctions between daytime and nighttime construction lacks a comprehensive examination of nocturnal attributes. The objective of this research is to ascertain the critical factors that influence the productivity of nighttime construction by conducting site investigations and reviewing relevant literature. The influence of factors such as illumination conditions, equipment deployment, quality procedures, and government regulations on productivity is subject to careful examination. The studies rank the significance of these factors in accordance with the relative importance index (RII) and entropy weighted method (EWM). The primary determinants identified in the study are temperature (RII: 0.8444), weather conditions (RII: 0.8222), and material and apparatus maintenance (RII: 0.8222). The findings function as recommendations for project managers and EPC contractors to reduce setbacks and increase efficiency. By comparing the outcomes of EWM and RII, the most effective approach to resolving the most crucial characteristics is achieved.

Keywords: productivity, nighttime work, statistical methods, construction, entropy weighted method, relative importance indexing

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Authors: Hyunchul Oh

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One of the challenges in modern separation science and technology is the separation of hydrogen isotopes mixtures since D2 and H2 consist of almost identical size, shape and thermodynamic properties. Recently, quantum sieving of isotopes by confinement in narrow space has been proposed as an alternative technique. Despite many theoretical suggestions, however, it has been difficult to discover a feasible microporous material up to now. Among various porous materials, the novel class of microporous framework materials (COFs, ZIFs and MOFs) is considered as a promising material class for isotope sieving due to ultra-high porosity and uniform pore size which can be tailored. Hence, we investigate experimentally the fundamental correlation between D2/H2 molar ratio and pore size at optimized operating conditions by using different ultramicroporous frameworks. The D2/H2 molar ratio is strongly depending on pore size, pressure and temperature. An experimentally determined optimum pore diameter for quantum sieving lies between 3.0 and 3.4 Å which can be an important guideline for designing and developing feasible microporous frameworks for isotope separation. Afterwards, we report a novel strategy for efficient hydrogen isotope separation at technologically relevant operating pressure through the development of quantum sieving exploited by the pore aperture engineering. The strategy involves installation of flexible components in the pores of the framework to tune the pore surface.

Keywords: gas adsorption, hydrogen isotope, metal organic frameworks(MOFs), quantum sieving

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Authors: Y. Wang, S. Zhang, X. Chen

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The longitudinal compressive strength of fibre reinforced plastic (FRP) possess a large stochastic variability, which limits efficient application of composite structures. This study aims to address how the random fibre packing affects the uncertainty of FRP compressive strength. An novel approach is proposed to generate random fibre packing status by a combination of Latin hypercube sampling and random sequential expansion. 3D nonlinear finite element model is built which incorporates both the matrix plasticity and fibre geometrical instability. The matrix is modeled by isotropic ideal elasto-plastic solid elements, and the fibres are modeled by linear-elastic rebar elements. Composite with a series of different nominal fibre volume fractions are studied. Premature fibre waviness at different magnitude and direction is introduced in the finite element model. Compressive tests on uni-directional CFRP (carbon fibre reinforced plastic) are conducted following the ASTM D6641. By a comparison of 3D FE models and compressive tests, it is clearly shown that the stochastic variation of compressive strength is partly caused by the random fibre packing, and normal or lognormal distribution tends to be a good fit the probabilistic compressive strength. Furthermore, it is also observed that different random fibre packing could trigger two different fibre micro-buckling modes while subjected to longitudinal compression: out-of-plane buckling and twisted buckling. The out-of-plane buckling mode results much larger compressive strength, and this is the major reason why the random fibre packing results a large uncertainty in the FRP compressive strength. This study would contribute to new approaches to the quality control of FRP considering higher compressive strength or lower uncertainty.

Keywords: compressive strength, FRP, micro-buckling, random fibre packing

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Authors: M. Wajahat, M. Shoaib, A. Waheed

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As a result of increase in world energy demand as well as the demand for heating, refrigeration and air conditioning, energy engineers are now more inclined towards the renewable energy especially solar based thermal driven refrigeration and air conditioning systems. This research is emphasized on solar assisted adsorption refrigeration system to provide comfort conditions for a building in Islamabad. The adsorption chiller can be driven by low grade heat at low temperature range (50 -80 °C) which is lower than that required for generator in absorption refrigeration system which may be furnished with the help of common flat plate solar collectors (FPC). The aim is to offset the total energy required for building’s heating and cooling demand by using FPC’s thus reducing dependency on primary energy source hence saving energy. TRNSYS is a dynamic modeling and simulation tool which can be utilized to simulate the working of a complete solar based adsorption chiller to meet the desired cooling and heating demand during summer and winter seasons, respectively. Modeling and detailed parametric analysis of the whole system is to be carried out to determine the optimal system configuration keeping in view various design constraints. Main focus of the study is on solar thermal loop of the adsorption chiller to reduce the contribution from the auxiliary devices.

Keywords: flat plate collector, energy saving, solar assisted adsorption chiller, TRNSYS

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Authors: Jalil Salimi, Mandana Asadi, Naser Fathi

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Urmia Lake (UL) has undergone a significant decline in water levels, resulting in severe environmental, socioeconomic, and health-related challenges. This paper examines the restoration process of UL from a water governance perspective. By applying a water governance model, the study evaluates the process based on six selected principles: stakeholder engagement, transparency and accountability, effectiveness, equitable water use, adaptation capacity, and water usage efficiency. The dominance of structural and physicalist approaches to water governance has led to a weak understanding of social and environmental issues, contributing to social crises. Urgent efforts are required to address the water crisis and reform water governance in the country, making water-related issues a top national priority. The UL restoration process has achieved significant milestones, including stakeholder consensus, scientific and participatory planning, environmental vision, intergenerational justice considerations, improved institutional environment for NGOs, investments in water infrastructure, transparency promotion, environmental effectiveness, and local issue resolutions. However, challenges remain, such as power distribution imbalances, bureaucratic administration, weak conflict resolution mechanisms, financial constraints, accountability issues, limited attention to social concerns, overreliance on structural solutions, legislative shortcomings, program inflexibility, and uncertainty management weaknesses. Addressing these weaknesses and challenges is crucial for the successful restoration and sustainable governance of UL.

Keywords: evaluation, restoration process, Urmia Lake, water governance, water resource management

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Authors: Mohamed Ghorab

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Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

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Authors: Maria Viktoria Melgo

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This study aimed to determine the possible association between calcium intake and wealth indices of selected female adults. Specifically, it aimed to: a) determine the calcium intake adequacy of the respondents. b) determine the relationship, if any, between calcium intake adequacy, area and wealth indices. The study used the survey design and employed convenience sampling in selecting participants. Two hundred females aged 20 – 64 years old were covered in the study from depressed and non-depressed areas. Data collected were calcium intake taken from two 24-hour food recall and Food Frequency Questionnaire (FFQ) and wealth indices using housing characteristics, household assets and access to utilities and infrastructure. Descriptive statistics and Chi-square test were used to determine the frequency distribution and association between the given variables, respectively, using Statistical Package for Social Sciences (SPSS) and OpenEpi software. The results showed that there were 86% of respondents in the depressed area with an inadequate calcium intake while there were 78% of respondents in the non-depressed area with an adequate calcium intake. No significant relationship was obtained in most wealth indices with calcium intake adequacy and area but appliance and ownership of main material of the house showed a significant relationship to calcium intake adequacy by area. The study recommends that the Local Government Unit (LGU) should provide seminars or nutrition education that will further enhance the knowledge of the people in the community. The study also recommends to conduct a similar study but with different, larger sample size, different location nonetheless if it is in urban or rural and include the anthropometry measurement of the respondents.

Keywords: association, calcium intake adequacy, metro Manila, Philippines, wealth indices

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Authors: A. S. Hakeem, B. Ahmed, M. Ehsan, A. Ibrahim, H. M. Irshad, T. Laoui

Abstract:

Alumina (Al2O3) - cubic boron nitride (cBN) ceramic composites were sintered by spark plasma sintering (SPS) using α-Al2O3 particle sizes; 150 µm, 150 nm and cBN particle size of 42 µm. Alumina-cBN composites containing 10, 20 and 30wt% cBN with and without Ni coated were sintering at an elevated temperature of 1400°C at a constant uniaxial pressure of 50 MPa. The effect of matrix particle size, cBN and Ni content on mechanical properties and thermal properties, i.e., thermal conductivity, diffusivity, expansion, densification, phase transformation, microstructure, hardness and toughness of the Al2O3-cBN/(Ni) composites under specific sintering conditions were investigated. The highest relative densification of 150 nm-Al2O3 containing 30wt% cBN (Ni coated) composite was 99% at TSPS = 1400°C. In case of 150 µm- Al2O3 compositions, the phase transformation of cBN to hBN were observed, and the relative densification decreased. Thermal conductivity depicts maximum value in case of 150 nm- Al2O3-30wt% cBN-Ni composition. The Vickers hardness of this composition at TSPS = 1400°C also showed the highest value of 29 GPa.

Keywords: alumina composite, cubic boron nitride, mechanical properties, phase transformation, Spark plasma sintering

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Authors: Ebrahim Solgi, Zahra Hamedani, Behrouz Mohammad Kari, Ruwan Fernando, Henry Skates

Abstract:

The use of thermal energy storage (TES) as part of a passive design strategy can reduce a building’s energy demand. TES materials do this by increasing the lag between energy consumption and energy supply by absorbing, storing and releasing energy in a controlled manner. The increase of lightweight construction in the building industry has made it harder to utilize thermal mass. Consequently, Phase Change Materials (PCMs) are a promising alternative as they can be manufactured in thin layers and used with lightweight construction to store latent heat. This research investigates utilizing PCMs, with the first step being measuring their performance under experimental conditions. To do this requires three components. The first is a calorimeter for measuring indoor thermal conditions, the second is a pyranometer for recording the solar conditions: global, diffuse and direct radiation and the third is a data-logger for recording temperature and humidity for the studied period. This paper reports on the design and implementation of an experimental setup used to measure the thermal characteristics of PCMs as part of a wall construction. The experimental model has been simulated with the software EnergyPlus to create a reliable simulation model that warrants further investigation.

Keywords: phase change materials, EnergyPlus, experimental evaluation, night ventilation

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Authors: Weerinda Appamana, Jirapong Keawkoon, Yamonporn Pacthong, Jirathiti Chitsanguansuk, Yanyong Sookklay

Abstract:

In the present work, spinning disc reactor has been used for the intensification of synthesis of biodiesel from refined palm oil (RPO) based on the transesterification reaction. Experiments have been performed using different spinning disc surface and under varying operating parameters viz. molar ratio of oil to methanol (over the range of 1:4.5–1:9), rotational speed (over the range of 500–2,000 rpm), total flow rate (over the range of 260-520 ml/min), and KOH catalyst loading of 1.50% by weight of oil. Maximum FAME (fatty acid methyl esters) yield (97.5 %) of biodiesel from RPO was obtained at oil to methanol ratio of 1:6, temperature of 60 °C, and rotational speed of 1500 rpm and flow rate of 520 mL/min using groove disc at KOH catalyst loading of 1.5 wt%. Also, higher yield efficiency (biodiesel produced per unit energy consumed) was obtained for using the spinning disc reactor based approach as compared to the ultrasound hydrodynamic cavitation and conventional mechanical stirrer reactors. It obviously offers a significant reduction in the reaction time for the transesterification, especially when compared with the reaction time of 90 minutes required for the conventional mechanical stirrer. It can be concluded that the spinning disk reactor is a promising alternative method for continuous biodiesel production.

Keywords: spinning disc reactor, biodiesel, process intensification, yield efficiency

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Authors: Gabriel Efomeh Omolaiye, Olatunji Seminu, Jimoh Ajadi, Yusuf Ayoola Jimoh

Abstract:

The Nigerian part of the Chad Basin till date has been one of the few critically studied basins, with few published scholarly works, compared to other basins such as Niger Delta, Dahomey, etc. This work was undertaken by the integration of 3D seismic interpretations and the well data analysis of eight wells fairly distributed in block A, Baga/Lake sub-basin in Borno basin with the aim of determining the thickness of Chad, Kerri-Kerri, Fika, and Gongila Formations in the sub-basin. Da-1 well (type-well) used in this study was subdivided into stratigraphic units based on the regional stratigraphic subdivision of the Chad basin and was later correlated with other wells using similarity of observed log responses. The combined density and sonic logs were used to generate synthetic seismograms for seismic to well ties. Five horizons were mapped, representing the tops of the formations on the 3D seismic data covering the block; average velocity function with maximum error/residual of 0.48% was adopted in the time to depth conversion of all the generated maps. There is a general thickening of sediments from the west to the east, and the estimated thicknesses of the various formations in the Baga/Lake sub-basin are Chad Formation (400-750 m), Kerri-Kerri Formation (300-1200 m), Fika Formation (300-2200 m) and Gongila Formation (100-1300 m). The thickness of the Bima Formation could not be established because the deepest well (Da-1) terminates within the formation. This is a modification to the previous and widely referenced studies of over forty decades that based the estimation of formation thickness within the study area on the observed outcrops at different locations and the use of few well data.

Keywords: Baga/Lake sub-basin, Chad basin, formation thickness, seismic, velocity

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Authors: Juiwen Liang, Choliang Chung

Abstract:

In this study, the silicon-base oxide nanofibers with hollow structure were prepared using single-nozzle electrospinning and heat treatment. Firstly, precursor solution was prepared: the Polyvinylpyrrolidone (PVP) and Tetraethyl orthosilicate (TEOS) dissolved in ethanol and to make sure the concentration of solution in appropriate using single-nozzle electrospinning to produce the nanofibers. Secondly, control morphology of the electrostatic spinning nanofibers was conducted, and design the temperature profile to created hollow nanofibers, exploring the morphology and properties of nanofibers. The characterized of nanofibers, following instruments were used: Atomic force microscopy (AFM), Field Emission Scanning Electron Microscope (FE-SEM), Transmission electron microscopy (TEM), Photoluminescence (PL), X-ray Diffraction (XRD). The AFM was used to scan the nanofibers, and 3D Graphics were applied to explore the surface morphology of fibers. FE-SEM and TEM were used to explore the morphology and diameter of nanofibers and hollow nanofiber. The excitation and emission spectra explored by PL. Finally, XRD was used for identified crystallization of ceramic nanofibers. Using electrospinning technique followed by subsequent heat treatment, we have successfully prepared silicon-base oxide nanofibers with hollow structure. Thus, the microstructure and morphology of electrostatic spinning silicon-base oxide hollow nanofibers were explored. Major characteristics of the nanofiber in terms of crystalline, optical properties and crystal structure were identified.

Keywords: electrospinning, single-nozzle, hollow, nanofibers

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Authors: Linyue Jia, Wenbo Du, Zhaohui Wang, Ke Liu, Shubo Li

Abstract:

Due to the great potential for weight reduction in aerospace and automotive industries, magnesium-rare earth (Mg-RE) based alloys with outstanding mechanical performance have been widely investigated for decades. However, magnesium alloys are still restricted in engineering applications because of their lower strength and ductility. Hence, there are large spaces and challenges in achieving high-performance Mg alloys. This work reports an Mg-Gd-Er-Zn-Zr alloy with ultrahigh strength and good ductility developed via hot extrusion, pre-deformation, and two-stage aging. The extruded alloy comprises fine dynamically recrystallized (DRXed) grains and coarse worked grains with a large aspect ratio. Pre-deformation has little effect on the microstructure and macro-texture and serves primarily to introduce a large number of dislocations, resulting in strain hardening and higher precipitation strengthening during subsequent aging due to more nucleation sites. As a result, the alloy exhibits a yield strength (YS) of 506 MPa, an ultimate tensile strength (UTS) of 549 MPa, and elongation (EL) of 8.2% at room temperature, showing superior strength-ductility balance than the other wrought Mg-RE alloys previously reported. The current study proposes a combination of pre-deformation and two-stage aging to further improve the mechanical properties of wrought Mg alloys for engineering applications.

Keywords: magnesium alloys, mechanical properties, microstructure, pre-deformation, two-stage aging

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Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

Abstract:

IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

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