International Journal of Integrated Engineering
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Effect of B30 Palm Oil Methyl Ester Biodiesel with Isobutanol Fuel Additive on Engine Performance of a Diesel Engine
Get PDFModern society is concerned about pollution and fossil fuel depletion. Many studies examined biodiesel substitution, the renewable diesel fuel known as "biofuel" is derived from materials such as vegetable oils, animal fats, and grease ASTM D7567 describes it. Biodiesel\u27s ability to run on diesel engines without modification makes it appealing and may affect engine performance and emissions because of its a higher cetane number, less volatility. These qualities can affect diesel combustion and fuel injections lead to less power and higher nitrogen oxides (NOx). Thus, this research uses palm oil and isobutanol fuel additives to boost engine performance and exhaust emissions. This experiment uses fuel samples of 5% 10% 15% 20% isobutanol and POME (B30) in diesel engine and normal diesel as the baseline of the experiment. Brake power, Brake specific fuel consumption, and Torque are the engine performance parameters. Isobutanol can enhance the performance of biodiesel fuel, particularly at higher speeds. B30ISO20 consistently exhibited the highest brake power and lowest brake-specific fuel consumption. The torque of the fuel sample improved with the addition of isobutanol, especially at higher concentrations
Microstructure and Phase Chemistry of Vacuum Induction Melting Fabricated-Equimolar AlCoCrFeNi HEA During Spinodal Dissolution Annealing
Get PDFThe quinary equimolar AlCoCrFeNi high entropy alloy (HEA) as a promising candidate for advanced engineering applications has grasped significant consideration in recent years due to its ability to undergo tailorable microstructure transformation and properties. The transient understanding of elemental distribution and response to the cooling rate during dissolution annealing and binodal decomposition are still required to evaluate. The present study investigates variations in phase chemistry and microstructure during dissolution annealing at 1h and 16h at 800˚C (air cooled) by FESEM-EDS mapping and XRD analysis. Secondly, to identify binodal decomposition in samples annealed at 1250oC for 20h is revealed at different cooling rates (water quenching and furnace cooling) employing FESEM-EDS. Remarkable binodal decomposition was witnessed with distinct phase composition and phase boundaries during slow cooling, while thin interfacial face centered cubic (FCC) phase separation occurred in a rapidly cooled sample. However, heating at 800˚C for 1h and 16h revealed modulated microstructure with rearrangements in the chemical composition of phases compared to cast microstructure. Al-Ni rich dendritic region and Cr-Fe rich interdendritic region interdiffusion during dissolution annealing at 800oC with Ni and Cr cross mobilisation. However, Co remains in uniform distribution in both regions. It confirms microstructure tailor ability and variance in engineering applicability of quinary equimolar AlCoCrFeNi high entropy alloy with different thermal treatments
Novel Programmable Solar Based SIMO Converter for SMPS Applications with IOT Infrastructure
Get PDFThe technological advancements lead to depend more on electronic goods which consume DC power. The DC appliances need converter circuits that are unique concerning their voltage and current ratings. In this paper, IoT enabled Programmable DC-DC converter is proposed for Solar dependent on DC Loads. The economically viable reconfigurable converter is achieved using a customized IoT board SPELEC. The primary step of the design to feed the SIMO converter from 230-Watt solar panel, the second stage 25 Khz pulses are generated from the SPELEC board to trigger the converter MOSFETs and in the Third stage of design, an MPPT Petrube and Observe (P&O) algorithm is implemented to maintain SIMO converter output Voltage’s constant irrespective of the solar panel voltage fluctuations based on duty change in trigger pulses to the MOSFETs. The design aimed to cater to DC loads of different voltages as 9V 12 V and 24 V act as a solar spike. IoT-enabled features are Solar Panel voltage and Load Currents along with Load isolation using Blynk Mobile operated Relay control. The Sensor data is uploaded for visualization and analysis on Thingspeak Cloud. The recorded voltage is in the range of 0 to 12v and current is 0 to 1.5A and power is from 0 to 20watts. The SPELEC Converter performance is compared with the Arduino-based converter and an improvement in ripples is recorded. 
Ant Colony Optimization Technique Based Harmonic Suppression in Active Power Filters
Get PDFThis work recommends an innovative scheme for atonement of the reactive powers and minimization of harmonics with the application of Ant Colony based Optimization algorithm (ACOA) to achieve a preferred proportional and integral controller gain, which is applied to the shunt connected active filters. The utilization of dynamic eager heuristic, positive feedback &distributed evaluation are the key preferences for the ACOA algorithm. An ACOA constructed improved PI controller is recommended to supersede the common PI controller which contributes in exceptional trail of DC power in APF under nonlinear load (NLL) circumstances. Moreover, there is a demand to confirm the strength of the ACOA algorithm, the outcomes are presented and equated to the particle swam optimization (PSO) based PI controller. The active filters are utilized in this analysis to minimize the global harmonic distortion of the source current in addition to the further parameters like active & reactive powers are observed and correlated by applying nature influenced algorithms like ACOA and PSO to attain the superior results. The suggested investigation can be carried out in the Matlab/Simulink software
Performance Evaluation of Single-Phase Grid-Connected Photovoltaic Inverter Using LC and LCL Filter Based on the Reduction of THD
Get PDFSolar photovoltaic (PV) energy and its applications continue to grow in popularity as a means of enhancing society\u27s sustainable development. There are a lot of issues to consider when PV systems are linked to the grid. One of the challenges, particularly only with large-scale use of PV systems, is harmonics in PV systems. This research investigates the use of well-known filters to reduce harmonics in PV systems. Filtering is required to decrease the harmonics due to the non-sinusoidal nature of PWM voltages at the converter output. To join the converter to the grid and decrease harmonics, a simple LC filter has traditionally been utilized. The use of LCL filters, on the other hand, has been proposed. The purpose of this research is to look at the impact of T-filters or LCL Filters on the overall working of a photovoltaic system that is connected to a grid. The perturb & observe algorithm is used for MPPT operation and The proportional-integral controller (PI) is used as the current controller in the closed-loop grid-connected PV system for the generation of pulses. The single-Phase Grid-Connected photovoltaic System for both LC & LCL Filters is implemented in this paper using MATLAB/Simulink. Total Harmonic Distortion is utilized as the performance metric in this comparison. The value of %THD for the proposed system i.e.8.06% emphasizes its necessity for implementation in practicality
A Hybrid Deep Learning Model for Detecting Driver Fatigue Using Electroencephalogram Signals
Get PDFRoad accidents caused by driver fatigue are a significant public safety concern, and detecting driver fatigue is crucial for preventing such incidents. Existing methods for detecting driver fatigue are limited in their effectiveness, and there is a need for more accurate and reliable methods. This study presents a solution to the problem of accurately identifying driver fatigue using electroencephalogram (EEG) signals. The approach involves the development of a hybrid deep learning model that incorporates both a deep belief network (DBN) and a recurrent neural network (RNN). We trained and evaluated our model on a dataset of EEG signals collected from drivers in normal and fatigued states. The effectiveness of the hybrid model in accurately categorizing driver fatigue was evaluated in comparison to two other classifiers. The results of the study indicate that the hybrid model outperformed the other classifiers in terms of accuracy, sensitivity, specificity, precision, and F1 score, suggesting its superior performance. We observed that the model’s accuracy and loss remained consistent even when the number of epochs was low, indicating that the model effectively learned to classify EEG signals and did not overfit the training data. Further evaluation of the hybrid model with varying numbers of epochs revealed that the optimal number for the model was 50. Additionally, analysis of the loss function during training demonstrated that the model effectively learned to classify EEG signals without overfitting the training data. The proposed hybrid model achieved an overall accuracy of 99.98%, with perfect sensitivity (100%) and high specificity (99.95%), precision (99.95%), recall (100%), and F1 score (99.98%). These results indicate that the proposed hybrid deep learning model outperformed the individual DBN and RNN models in classifying EEG signals. Our study’s results demonstrate the potential of the proposed hybrid model to accurately detect driver fatigue, which could contribute to the development of more effective and reliable methods for preventing road accidents caused by driver fatigue
The Effects of Novel Sandwich Wafer Mounting Technique on Silicon Wafer Chipping Performance
Get PDFDie chipping, which may result in crack die, is a major quality concern for semiconductor manufacturers. Since crack die cannot always be screened during testing process, it is critical to evaluate a process that will minimise chipping during the wafer dicing process. In this study, novel mounting techniques were introduced to assess the chipping performance of wafer dicing process. Three non-circuitry silicon wafers were evaluated with 300 µm wafer thickness and 6 x 6 mm die size including various mounting techniques were tested. The conventional wafer mounting technique was found generated high chipping due to insufficient gripping during the mechanical wafer dicing process. The novel mounting techniques introduced in this publication, including semi sandwich and full sandwich wafer mounting techniques, added a cushioning effect and additional gripping method for higher stability during the dicing process. The full sandwich mounting technique demonstrated significant improvement in wafer dicing chipping performance compared to the conventional mounting process. The results of this study suggest that the new mounting technique can effectively minimise die chipping during wafer dicing, which can improve the quality and yield of semiconductor products.
 
Modeling of InGaAs/InGaP/GaAs/AlInP/Ge-Based Five Junction Solar Module with Wafer Bonding for Efficiency Improvement
Get PDFCurrently, a lot of works are done on solar PV modules to improve their efficiency. The world\u27s interest is developing towards the usage of solar energy, which is a clean and environmental friendly source of energy. The efficiency of a solar multijunction PV module is improved from the increasing number of junctions, but it also depends upon the quality of materials, their properties, and band gap energies. In this work, a five junctions solar module is designed where each junction contains its unique band gap energy. The high band gap energy materials encompass less lattice mismatched value while the low band gap materials have higher values. These mismatched materials are directly and electrically connected using wafer bonding. The AlInP relates to the window layer which improves the efficiency. Multijunction solar cells\u27 electrical components are determined by short-circuit current (Jsc), open-circuit voltage (Voc), peak power, and fill factors. The solar module with five junctions, utilizing InGaP/InGaAs/GaAs/AlInP/Ge, achieves enhanced efficiency of up to 46.7% when the materials have a standard band gap length of 1.5 Angstroms. Germanium is used as a substrate in the module in the bottom junction for the efficiency improvement of the multijunction PV modules. The simulation is done and the results are obtained through MATLAB/Simulink simulation
A Cascaded Synchronous Buck Converter for Light Electric Vehicle Charging Applications
Get PDFIn this work, a cascaded synchronous DC-DC converter topology is presented which is suitable for high current applications. In this topology, a synchronous buck converter is cascaded with a series capacitor synchronous buck converter, which exhibits very low step-down voltage gain – thus translating to a high current gain.. For this work, this converter is applied for charging a 24 V, 10 A h Lithium-ion (Li-ion) battery. The constant-current constant-voltage (CC/CV) technique is employed with the proposed converter for this application. Simulations for the system were carried out on MATLAB Simulink, using the SimPowerSystems toolbox. The converter operation is observed to align with a typical CC/CV charging profile, with a 93.3% charging efficiency. Consequently, this topology may be integrated into an off-board charger for light electric vehicles (LEVs) such as e-bikes and three-wheeler e-rickshaws – which are typically used in public transportation. Suitability of the given converter is further corroborated by the observed charging efficiency. This work can potentially aim to address the issue of downtime that drivers of electric three-wheelers may face during peak operating hours. Consequently, this can open doors for further adoption of light electric vehicles for public transportation
Performance of High Strength Concrete Containing Fine Metakaolin, Palm Oil Fuel Ash and Coal Bottom Ash as Substitute Material Towards Mechanical Properties
No full textThe increased use of high-strength concrete in the construction industry causes a significant amount of cement production that contributes to major carbon dioxide (CO2) emissions. However, various additives such as fine metakaolin (FMK), palm oil fuel ash (POFA), and coal bottom ash (CBA) can be used to improve concrete performance and reduce carbon footprint. A portion of cement in the concrete was replaced with 20% of FMK and various percentages of POFA (5%, 10%, 15%, and 20%) by weight. While sand was replaced with 10% of CBA. Slump test, water absorption test, compressive strength test, flexural strength test, and split tensile strength tests were performed on concrete samples comprising FMK and POFA as cement replacements and CBA as sand replacements in this research. The partial replacement of FMK and POFA for cement and sand for CBA decreased the workability of the concrete. The small particle size of FMK and POFA serve as fillers, reducing concrete\u27s water absorption. The replacement of POFA by 10% shows the highest compressive strength compared to the control sample. However, water absorption, flexural strength, and split tensile strength improved with the addition of up to 20% POFA. This proves that the incorporation of FMK, POFA, and CBA causes the reaction of alumina oxide, silica oxide, and calcium oxide with calcium hydroxide (C-H) from cement with water during the hydration process of the concrete