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NPK Biofertilizer Production from Banana Peel, Feather and Bone Ashes and their Comparative Advantage to 20:10:10 Inorganic Fertilizer
No full textThe possibility of formulating nitrogen, phosphorus and potassium (NPK) biofertilizer from ashes of waste organic materials such as chicken feathers, bone and banana peels is investigated in this study by first subjecting the agricultural waste to 80-250 heat in a muffle furnace to produce ash. Kjeldatherm block digestion unit, UV spectrophotometer, and flame photometers, respectively helped in measuring the concentrations of N, P and K inherent in the fertilizer precursors as well as in 5 formulated blends (i.e., A, B, C, D & E). It was discovered that NPK in the single substrate and blends favorably compared with standard NPK 20:10:10 chemical fertilizer to some extent. Among single material fertilizer sources, feather ash with 0.179:1:0.134 NPK and bone ash with 0.009:1:0.021 NPK had the closest nutrient content with the standard, showing potential promise. On the other hand, Blend E is the same as the standard, followed by Blend A, B, D and C, which are hierarchically close in elemental composition to the standard. The choice of these biofertilizers is dependent on their nutrient compositions, the type of crops to be grown, and the soil mineral requirements. Most importantly, different NPK ratio organic fertilizers produced in this study can competitively be produced in a large scale to address huge costs associated with the NPK 20:10:10 standard commercial fertilizer. Blend E (NPK 20:10:10) can be formulated locally by farmers in rural areas easily using this particular agricultural residue or a host of other confirmed farm wastes
Motor Bearing Failure Identification Using Multiple Long Short-Term Memory Training Strategies
Get PDFIn the context of condition-based maintenance of rotating machines in manufacturing systems, the early diagnosis of possible faults related to rolling elements of the bearing is mainly based on techniques from artificial intelligence, namely, Machine Learning (ML) and Deep Learning (DL). Approaches based on using Deep Learning methods have been the most coveted in recent years. Among a variety of models, the type of architecture known as Long-Short-Term Memory (LSTM) of Recurrent Neural Network (RNN) has both the ability to capture long-term dependencies and to adapt to sequential data modeling. It is therefore able to work on data without any preprocessing. This paper studies using four types of LSTM networks to diagnose bearing faults in a classification approach. It aims to intervene on both the input parameters and the network architecture, to achieve high performance. The proposed method is carried out in two different ways. In the first case, the data inputs are raw frames of vibration signals. However, in the second case, the network inputs are pre-computed time-frequency features. The results clearly showed that LSTMs are more accurate with the latter
Ethical Knowledge Sharing Leveraging Blockchain: An Overview
Get PDFThe knowledge that is acquired through a learning process has ethical concerns when shared, as there can be restrictions on the parties who can use the piece of knowledge, redistribution approaches protecting the creator\u27s rights, privacy, and confidentiality concerns, accuracy and trustworthiness, openness and transparency, and informed consent. Blockchain structure encompasses a series of coupled blocks that are intrinsically linked with the conservation of authenticity, ensuring irrefutability, and the semi-anonymity of transactions. As pioneers in reviewing BC-based ethical Knowledge Sharing (KS), we categorize the model into 4 classes and critically evaluate the literature relative to knowledge-associated features, ethical knowledge-sharing aspects, BC-associated features, and network features. We heaped a commencing sample of 69 document references by selecting the literature for eligibility conditions pursued from intellectual resource search platforms, leveraging a profound and overly extended-period technique. We investigate and emphasize that, owing to innate security properties, blockchain can facilitate ethical KS in numerous ways, such as leveraging a dedicated consensus approach for ethical KS (Class 1), leveraging blockchain itself for knowledge storage and sharing due to its mutation-proof, non-tamperable, fault tolerance features (Class 2), ensuring the confidentiality of knowledge by leveraging additional encryption techniques on blockchain (Class 3), and leveraging smart contracts for attribute-based searching, knowledge fusion, access control, reward-driven KS, etc. (Class 4). Critical evaluation unveils that from BC-based ethical KS frameworks, 50% utilize smart contracts with blockchain for knowledge-based activities, 90% leverage progressive BC architecture, 6.7% leverage proof-of-knowledge consensus, 93.4% share propositional knowledge, and 70% share explicit knowledge. Moreover, accuracy, openness and transparency, privacy, trustworthiness, truthfulness, and confidentiality have been the dominant factors in ethical KS principles of interest. Finally, we examine the openings and hurdles of the model of blockchain-based ethical KS, then propose actions to diminish them, and afterward present future directions, implications, and limitations for the concept
Transforming Vehicular Networks: How 6G can Revolutionize Intelligent Transportation?
Get PDFVehicular Ad-hoc Networks (VANETs) have enabled intelligent transportation systems by facilitating communication between vehicles and roadside infrastructure. However, the current 5G and 4G networks that support VANETs have certain limitations that hinder the full potential of VANET applications. These limitations include constraints in bandwidth, latency, connectivity, and security. The upcoming 6G network is expected to revolutionize VANETs by introducing several advancements. 6G will provide ultra-fast communication with significantly reduced latency, enabling real-time and high-bandwidth data exchange between vehicles. The network will also offer highly reliable and secure connectivity, ensuring the integrity and privacy of VANET communications. Precise localization and sensing capabilities will be enhanced in 6G-based VANETs, enabling accurate positioning of vehicles and improved situational awareness. This will facilitate collision avoidance, traffic management, and cooperative driving applications. Moreover, integrating edge computing in 6G networks will bring computing resources closer to the edge, lowering response times and facilitating faster decision-making in time-critical scenarios. This paper explores the key features and capabilities of 6G technology and how it can revolutionize intelligent transportation, addressing challenges and opportunities for adopting 6G in VANETs
A Review on the Implementation and Effectiveness of Lean Manufacturing Strategies for Industrial and Service Sectors
Get PDFEnsuring a neat, clean, organized, safe, and productive workplace is essential for every organization. Waste and abnormalities may lead to a high loss of productivity and, consequently, capital, along with a significant compromise to the health and safety of the stakeholders. To overcome such challenges, Lean manufacturing is implemented worldwide. The main aim of this technique is to reduce or eliminate certain types of waste (such as those related to motion, transportation, overproduction, waiting time, etc.) that may contribute to financial loss for the companies. The Lean technique is hybridized with other industrial engineering methods such as DMAIC, Six Sigma, Kanban, etc., depending on the situation. This paper reviews some of the vital work in the last five years on implementing Lean manufacturing for various industrial, commercial, and service setups. It first introduces Lean manufacturing, discusses its implementation procedure and tools and techniques, and presents an analysis of previous attempts made by researchers and engineers using Lean to minimize waste, maximize productivity and efficiency, and enhance quality. The article ends with concluding remarks and highlighting the directions for future research. The novelty of this article lies in the fact that along with a basic introduction and review of the last five years’ literature, it also sheds light on current trends; recent developments; Lean integration with Six-Sigma, Kanban, Kaizen; automation and digital technology interventions to increase the effectiveness of Lean manufacturing; contribution of Lean in sustainable development
Analysis of Brush Seal Interaction with Steam Turbine Rotor-Shafts
Get PDFHigh-speed turbines are a major source for power production. They utilize high pressure and temperature fluid flow. Sealing of these machines to decrease the flow losses has been a major engineering challenge since the inception of steam turbines. From an engineering viewpoint, seals are used to introduce friction in the fluid flow path. This reduces the flow leakage. Improved seal performance offers substantial opportunities for turbine performance. Reduced leakages in steam turbines can lead to greater efficiency and power output. They can also allow tighter control of turbine secondary flows. However, sealing these machines is a major challenge. There are several seal locations on a steam turbine that have significant performance derivatives. These include the interstage shaft packing, the end packing, and the bucket tip seals. Brush seals are ideal for these locations because they can reduce the flow losses. This study analysed the efficiency of the steam turbine by using ANSYS APDL. It assessed the leakage performance of the brush seal for different cases and geometries. It also used porous medium modelling of the bristle pack to provide insight for designers. The outputs of interest were the rotor-shaft temperature and the efficiency of the entire turbine with the brush seal
Performance Analysis of Fractionalized Order PID Controller-based on Metaheuristic Optimisation Algorithms for Vehicle Cruise Control Systems
Get PDFRecently, automotive manufacturers have prioritized cruise control systems and controllers, recognizing them as essential components requiring precise and adaptable designs to keep up with technological advancements. The motion of vehicles is inherently complex and variable, leading to significant non-linearity within the cruise control system (CCS). Due to this non-linearity, conventional PID controllers often perform suboptimally under varying conditions. This research introduces a fractionalized-order PID (FrOPID) controller, which has an extra parameter that makes regular PID controllers work better. A comparative analysis is conducted between classical PID controllers and FrOPID controllers optimized using three metaheuristic algorithms: Harris Hawks Optimization (HHO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). The evaluation is carried out using a linearized model of the vehicle cruise control system (VCCS). The results demonstrate that fractionalized-order PID controllers significantly outperform conventional PID controllers, particularly regarding rise time and settling time. Among the designs that were considered, the one that combines HHO and FrOPID works the best at finding a balance between responsiveness and stability. It is also the most durable and flexible, able to adapt to changes in vehicle mass and environmental conditions. This highlights the effectiveness of fractionalized-order controllers in managing the dynamic behavior of vehicles
Optimizing Biomedical Facilities Performance with Dombeya Fiber-Paper Particle Hybrid Reinforced Epoxy Composites
Get PDFSince the last two decades, the use of natural fiber reinforced polymer composites has garnered significant application considerations over the synthetic fiber reinforced composites due to their numerous advantages and unique properties. Likewise, epoxy resin has attracted the interest of many researchers for composite synthesis, basically because of its chemical stability, thermal and mechanical characteristics. Hence, the primary aim of this study was to investigate the influence of dombeya fiber and paper particulate on the physical and mechanical properties of dombeya fiber and paper particulate-reinforced polymer composites for structural applications. Dombeya fiber and paper particles are renewable and biodegradable materials, thereby making them environmentally friendly materials to replace synthetic materials. Hand lay-up technique was utilized to fabricate the hybrid-reinforced biocomposites after which they were subjected to mechanical, wear, density, and moisture absorption properties. The surface morphology of the fractured surface was also analyzed to investigate its microstructural features. It was discovered from the results that hybrid biocomposites demonstrated improved properties over the unreinforced composite, with composites from 9-wt% dombeya fiber-paper particles reinforced biocomposite exhibiting the most suitable properties with commensurate density with the unreinforced epoxy matrix. These obtained characteristics support the material as a suitable material for biomedical apparatus application such as orthopedic implants, surgical instruments, and bone fixation devices.
Assessment of Buckling Failure in Oil Storage Tanks: Finite Element Simulation of Combined Internal and External Pressure Scenarios
Get PDFInvestigating the structural behaviour and buckling susceptibility of cylindrical oil storage tanks is crucial for ensuring their safe and reliable operation. In this study, the structural behaviour and buckling susceptibility of closed roof-top cylindrical oil storage tanks under combined internal and external pressure scenarios were investigated using the finite element analysis (FEA) technique. By utilizing the FEA technique, the combined effect of wind-induced pressure of 250 Pa, applied on the outer surface of the tank and internal pressure of 0.5 MPa, applied on the outer surface of the storage was analysed. The result reveals significant stress concentrations and deformation patterns, particularly on the windward side of the tank, thus, emphasizing the susceptibility of the storage tank to buckling under the specified operating conditions for both the filled and half-filled tank; with internal pressure emerging as the primary contributor to mechanical strain and deformation experienced in the tank, while the wind load plays a secondary but significant role in the deformation of the tank. The fe-safe predicted useful life shows that under the specified operating conditions, the filled storage tank will survive 1 429 hours (2 months) while the half-filled tank will survive 3 551 hours (5 months) before failure due to buckling. Thus, the useful life estimation results show the importance of varying oil levels and operating conditions in the structural assessments of storage tanks
A Review of Fatigue Failure and Life Estimation Models: From Classical Methods to Innovative Approaches
Get PDFThis review paper encompasses a comprehensive exploration of fatigue failure and fatigue life estimation techniques which spans from the classical methods to new and innovative approaches. The paper looks into the limitations and advancements of these techniques and highlights their respective strengths and areas for improvement. Some of the models such as artificial neural networks and genetic algorithms exhibit clear advantages in terms of processing speed, accuracy, and adaptability to diverse materials and loading scenarios. For instance, in estimating fatigue life under multiaxial loading, the stress scale factor model emerges as a viable alternative to the critical plane-based approach, as this technique offers superior efficiency under both constant and variable amplitude loadings. Additionally, optimization algorithms such as artificial neural networks and genetic algorithms show promising potential in efficiently estimating fatigue life due to their rapid computational capabilities. Despite the notable successes achieved by these techniques, none of them can be ascribed as a universal model capable of accurately estimating the fatigue life of all materials across diverse operating conditions as each of the techniques possesses its unique strengths and weaknesses, thus, necessitating the study for a better understanding of their applicability. Hence, this paper serves as a valuable compilation of various fatigue analysis techniques, targeted at paving the way towards the development of a universal model capable of handling different materials and loading conditions