International Journal of Current Engineering and Technology
The International Journal of Current Engineering and Technology (IJCET) is a peer-reviewed, open access scholarly journal established in 2010 with the objective of promoting excellence in engineering research and technological innovation. The journal publishes original research articles, review papers and technical communications across all major disciplines of engineering and applied sciences, providing an international platform for academicians, researchers and industry professionals to share high-quality contributions. E-ISSN: 2277-4106 (Online) P-ISSN: 2347-5161 (Print) Frequency: Bimonthly: Jan/Feb, Mar/Apr, May/Jun, Jul/Aug, Sep/Oct, Nov/Dec Editorial Office: editor.ijcet@evegenis.org, editorial.ijcet@gmail.com All submissions undergo a rigorous double-blind peer review process to ensure originality, technical soundness and academic relevance. The journal encourages interdisciplinary research and aims to support the dissemination of innovative solutions addressing contemporary engineering challenges. Aim and Scope IJCET aims to promote cutting-edge research and industrial innovation in the field of engineering and technology. The journal covers, but is not limited to, the following areas: ■ Mechanical, Civil, Electrical and Electronics Engineering ■ Computer Science, Information Technology and Artificial Intelligence ■ Communication Systems, Signal Processing and Embedded Systems ■ Materials Science, Manufacturing and Industrial Engineering ■ Renewable Energy, Sustainable Technologies and Environmental Engineering ■ Robotics, Automation, Internet of Things (IoT) and Smart Systems Key Commitments ■ Global Reach: The journal maintains an international perspective, welcoming submissions and catering to an audience from all corners of the world. ■ Current Relevance: A strong emphasis is placed on research that addresses contemporary global issues, emerging trends, and recent developments across various disciplines. ■ Quality Assurance: All submitted manuscripts undergo a rigorous double-blind peer-review process to ensure the highest standards of academic validity, originality, and excellence.
A Comprehensive Survey of Database Administration and Governance in Salesforce Platforms
Salesforce, as a leading cloud-based Customer Relationship Management (CRM) platform, plays a critical role in enabling digital transformation, scalable data management, and intelligent business operations. This paper presents a comprehensive analysis of Salesforce platform architecture, database administration, and data governance mechanisms. It explores the Salesforce ecosystem, including its multi-tenant architecture, data storage strategies, and metadata-driven framework that support secure, flexible, and efficient data environments. The study further examines key database administration aspects such as data modeling, lifecycle management, and performance optimization to enhance scalability and operational efficiency. Additionally, it highlights Salesforce security and governance features, including identity management, access control, encryption, and monitoring, which ensure data protection and regulatory compliance. A detailed literature review emphasizes recent advancements in Salesforce-based systems, particularly in multi-cloud integration, interoperability, and AI-driven governance. The findings indicate that Salesforce significantly improves data security, system performance, and decision-making capabilities. However, challenges such as integration complexity and lack of standardized governance frameworks still require further research and development.
Salesforce, Cloud CRM, Data Governance, Multi-Cloud Integration, Database Administration, Data Security, Scalability
Copyright (c) 2026 International Journal of Current Engineering and Technology
Comparative Study on Air Pollution Prediction using Machine Learning Techniques
The Air Quality Index (AQI) measures how air pollution affects human health. As pollution levels rise in Indian cities, we need reliable prediction models for better environmental management. This paper analyses different machine learning techniques for predicting AQI. We use Support Vector Regression (SVR), Random Forest Regression (RFR), and CatBoost Regression (CR) on data from New Delhi, Bangalore, Kolkata, and Hyderabad. We evaluate model performance using Root Mean Square Error (RMSE) and accuracy. Experimental results show that RFR performs best in most cities, while CR is most effective in New Delhi. To tackle dataset imbalance, we use the Synthetic Minority Oversampling Technique (SMOTE), which improves prediction accuracy for all models. Additionally, we assess other models, including SARIMA, Support Vector Machine (SVM), and Long Short-Term Memory (LSTM) for Ahmedabad. Among these, SVM with a radial basis function (RBF) kernel shows the best results. The findings emphasize how combining data balancing methods with machine learning models can improve AQI prediction. This approach can help with pollution control strategies and better decision-making.
Air Pollution Prediction, Machine Learning, Deep Learning, NF-VAE, IoT, Time-Series Forecasting, Multivariate Data, Smart Cities
Safety-by-Design Approach for Preventing Falls and Formwork Collapse in Construction
Construction sites remain highly prone to accidents, with falls from heights and formwork collapses being main causes of fatalities worldwide. Traditional safety practices emphasize worker training and hazard mitigation; however, the Safety-by-Design (SbD) approach shifts the focus toward eliminating risks at the design stage itself. This study explores the role of SbD in addressing fall hazards and formwork failures through a comprehensive review of existing literature. Evidence indicates that a significant proportion of construction accidents are linked to design-related factors, highlighting the critical responsibility of designers in improving safety outcomes. SbD promotes the integration of safety considerations into planning, material selection, and structural design, including provisions such as guardrails, scaffolding systems, and stable formwork structures. The approach not only reduces accidents and associated costs but also enhances productivity and fosters a proactive safety culture. Despite its potential, challenges remain in implementation, particularly in developing countries, necessitating further research and strategic adoption frameworks.
Safety-by-Design, Construction Safety, Falls from Heights, Formwork Collapse, Design Risk Management
Implementing AI-Driven Test Automation Frameworks in Enterprise Digital Transformation Projects
The growing Complexity of the enterprise applications and the speed at which the digital transformation is taking place has rendered the traditional testing methods ineffectual, and this has necessitated intelligent automation solutions. The significance of this study is that currently organizations rely on AI-based tools to guarantee the quality of software, lessen the number of manual data flows, and facilitate constant delivery. This paper discusses the application of AI-based test automation in efficiency and scalability of enterprise systems. The use of artificial intelligence (AI) and machine learning (ML) is demonstrated to reduce the maintenance issue and enhance the detectability of defects and script stability. The main methods of test optimization, automatic test generation, and intelligent prioritization are discussed to show how they can simplify the work of testing and enable faster releases. The combination of AI and CI/CD pipelines also allows the processes of constant validation, fast deployment, and automatic failure analysis. The paper also identifies such challenges as prioritization, issues of collaboration, cost of maintenance, and fragmentation of devices. All in all, the results of the research point to the idea that AI-based test automation is a strategic enabler of enterprise agility, operational resilience, and sustainable digital development.
Enterprises, Digital Transformation, Test Automation, Artificial Intelligence (AI), Machine Learning (ML).
Clustering and Classification Techniques in Machine Learning-based Intrusion Detection Systems: A Review
The rapid proliferation of networked digital systems has substantially expanded the threat landscape for cyber intrusions, necessitating robust and adaptive security mechanisms. Intrusion Detection Systems (IDS) constitute a critical component of network security infrastructure by identifying unauthorized access attempts and malicious behavior in real time. Traditional signature-based detection techniques, while effective against known threats, exhibit notable limitations in identifying novel and polymorphic attack patterns. This limitation has driven extensive research into machine learning (ML)-based IDS frameworks that leverage statistical and structural properties of network traffic for automated threat detection. Among ML paradigms, clustering and classification methods have emerged as particularly effective strategies. Classification algorithms employ supervised learning to discriminate between normal and attack traffic based on labeled training data, while clustering techniques utilize unsupervised learning to discover anomalous groupings in unlabeled network data. This paper presents a systematic and comprehensive review of clustering and classification techniques applied in ML-based IDS, examining foundational algorithms including Logistic Regression, K-Nearest Neighbor, Decision Tree, Random Forest, Support Vector Machine, K-Means, and Hierarchical Clustering. The study further analyzes widely adopted benchmark datasets, evaluates performance metrics, and discusses current research challenges. Identified gaps include the handling of high-dimensional feature spaces, computational constraints in IoT environments, and the development of lightweight hybrid detection models. Directions for future research are outlined to guide the design of more intelligent, scalable, and efficient intrusion detection frameworks.
A Review of Environmental Sustainability in Piping System Design and Material Selection
Piping systems are vital infrastructure in the industry, and the classic design methods are oriented on the issues of safety and reliability and pay insignificant attention to the lifecycle environmental impact. This paper is a critical analysis of the concept of environmental sustainability in piping systems. It will analyze the engineering principles of sustainability, material selection, and design solutions. The paper addresses the failure of traditional piping regulations, such as ASME B31, to address the issue of energy usage, greenhouse gas production, and ecological disruption. The concept of life cycle assessment (LCA) is brought up as one of the methods to estimate the environmental effectiveness of the piping materials and the installation practices over the course of their lifecycle. Recycled metals, bio-based materials and smart materials are discussed as new materials that could reduce environmental footprints and enhance longevity of the systems. Moreover, the paper also addresses digital technologies such as BIM, digital twins and monitoring through IoT as a solution towards the improvement of energy efficiency and sustainable decisions. It highlights the importance of combined, data-driven solutions in order to build resilient and environmentally friendly piping solutions.
Environmental sustainability, Piping systems, Sustainable material selection, Life cycle assessment (LCA), Energy-efficient design, Industrial infrastructure
Healthcare Predictive Analytics based on Machine Learning Techniques for Identifying Cardiovascular Risks Screening
Cardiovascular diseases (CVDs) can be considered a severe concern to the universal health that affects the mortality rates. Clinical decision-making and early diagnosis can be challenged with the help of intelligent systems, which are based on data-driven models. The suggested solution would utilize the DenseNet-based deep learning model in making accurate predictions of heart disease using UCI Cleveland dataset. The data undergoes pre-processing with systematic data treatment of missing values, removal of duplicates, feature selection via correlation and standardization. In terms of predicting cardiac disease, the proposed model performs exceptionally well, with an accuracy of 99.65, precision of 98.38, recall of 98.77, and F1-score of 97.96. To provide comparative analysis, conventional machine learning classifiers such as KNN, MLP and Logistic Regression. The effectiveness model as demonstrated by the comprehensive performance gains indicate a high level of capturing of complex clinical patterns, which is effective in screening early cardiovascular risks in healthcare predictive analytics and is able to maintain model interpretability, hence making it a promising solution in early and automated heart disease detection in clinical environment.
Cardiovascular prediction, Heart disease UCI Cleveland dataset, Machine learning, DenseNet, Deep learning artificial intelligence.
Fake News Generation and Detection: Adversarial use of Generative AI in Text Synthesis
The extensive growth of online media platforms, as well as the extensive use of generative artificial intelligence, has made the production and distribution of fake news particularly more active. Models of languages and vision have now been advanced to create a high level of reality in text, images and videos that become even harder to detect any misinformation by means of the old standard verification channels. The paper is a detailed analysis of fake news and its main premises, the core issues, and the role of generative AI in the development and detection of fake news that keeps changing. The paper examines uni-modal deepfake detection models in text, image and video modalities, and cross-modal consistency analysis, which utilizes semantic consistency between heterogeneous data. In addition, the study contrasts traditional machine learning approaches with more modern ones, detailing the benefits and downsides of each, as well as their suitability for large-scale and multilingual tasks. A number of popular benchmark datasets are presented to give an idea of the experimental evaluation practice. Additionally, stability metrics such as recall (REC), accuracy (ACC), precision (PRE), F1-score (F1), and ROC-AUC are assessed to ascertain the efficacy of detection. Find that deep learning models are more generalizable and perform better overall, but they are still vulnerable to adversarial manipulation and new generative methods.
Fake News Detection, Generative Artificial Intelligence, Deep Learning, Natural Language Processing, Deepfake Detection
Artificial Intelligence-Driven Prediction of Hotel Booking Demand for Revenue Optimization
The rising competitiveness in the hospitality industry requires proper and smart forecasting models to maximize the hotel booking demand and revenue management plans. The proposed study is a hybrid CNN-Bi-LSTM model to predict the canceling of hotel bookings based on the Kaggle hotel booking demand dataset. An organized preprocessing system adopted, such as the missing value imputation, the treatment of ADR outliers, the encoding of labels, feature engineering, correlation-based feature importance analysis and, to enhance the model's dependability and data quality, the class balancing performed using SMOTE. The architecture proposed combines Convolutional Neural Networks (CNN) to obtain meaningful feature representations and Bidirectional Long Short-Term Memory (Bi-LSTM) networks to learn temporal patterns of booking. The applied approach has proven to be effective based on the results of performance evaluation with the help of confusion matrix-based measures 98.95% accuracy (acc), 98.82% precision (prec), 99.91% recall (rec), and 98.90% F1-score (F1). A comparative analysis indicates that the hybrid CNN-Bi-LSTM is much better than the classical models, which include Decision Tree, Random Forest, and standalone XGBoost. The results affirm the soundness, generalization and applicability of the suggested framework regarding the intelligent hotel booking demand forecasting and decision-making
Hotel Industry, CNN-Bi-LSTM, Revenue Management, Demand Predictions, Hospitality Sector
Typology of Housing and Household Energy Behaviors in Cameroon: Diagnosis for better Energy Efficiency
This research analyzes the determinants of domestic energy efficiency in Cameroon through a quantitative study of 333 households in Douala, Yaoundé, and Ngaoundéré. Using Chi-square χ^2independence tests, the study explores correlations between sociodemographic factors, housing characteristics, and installed energy capacity. Key Results include: Material Inertia: A strong geographical dependence exists between cities and construction materials p < 0.001. Adobe bricks with cement mortar, dominant in Ngaoundéré, offer under-exploited thermal efficiency potential compared to the cement-dominated metropolitan areas of Douala and Yaoundé. Generational Transition: Refrigeration equipment follows a life cycle, with a critical acquisition phase between ages 25 and 35, identifying this as the pivot segment for introducing high-performance technologies. The Performance Paradox: Analysis demonstrates that physical size and equipment type are not reliable indicators of installed power. Only the Energy Class (A+, A++) allows for a real and significant reduction in power demand < 50 kW. Information Deficit: A major obstacle was identified: 69% of users are unaware of their appliance's energy class, a technical ignorance that increases with the surface area of the dwelling.
Habitats, Behaviors, Households; Diagnosis, Energy Efficiency
Typologie of housing and household Energy behaviors in Cameroon : diagnosis for better Energy efficiency.
This research analyzes the determinants of domestic energy efficiency in Cameroon through a quantitative study of 333 households in Douala, Yaoundé, and Ngaoundéré. Using Chi-square independence tests, the study explores correlations between sociodemographic factors, housing characteristics, and installed energy capacity. Key Results include:Material Inertia: A strong geographical dependence exists between cities and construction materials p < 0.001. Adobe bricks with cement mortar, dominant in Ngaoundéré, offer under-exploited thermal efficiency potential compared to the cement-dominated metropolitan areas of Douala and Yaoundé.Generational Transition: Refrigeration equipment follows a life cycle, with a critical acquisition phase between ages 25 and 35, identifying this as the pivot segment for introducing high-performance technologies.The Performance Paradox: Analysis demonstrates that physical size and equipment type are not reliable indicators of installed power. Only the Energy Class (A+, A++) allows for a real and significant reduction in power demand < 50 kW.Information Deficit: A major obstacle was identified: 69% of users are unaware of their appliance's energy class, a technical ignorance that increases with the surface area of the dwelling.<!-- [if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:15.75pt; height:18pt' o:ole=""> <v:imagedata src="file:///C:\Users\SIMOK~1\AppData\Local\Temp\msohtmlclip1\01\clip_image001.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1025" DrawAspect="Content" ObjectID="_1834224128"> </o:OLEObject> </xml><![endif]-->
Habitats; Behaviors; Households; Diagnosis; Energy Efficiency
Design and Modification of Thermoelectric Tube using Different Materials
By using thermoelectric generators it is possible to develop independent electric energy source in burning and heating systems – in households and industrial heating. With this energy source it is possible to provide with electricity systems appliances, lightening and other consumers. Potential placements for generators are on furnace walls, on flue way walls, on flue pipe walls after furnace. Generators can improve efficiency of combustion, because there is amount of waste heat that leaves through flue pipe in burning process. There are no boundaries for combining elements in system as just the space for their placement. As more elements are linked in chain, as much electric energy is produced. This is one of methods to develop a cogeneration process in domestic boiler house or industrial heating, or burning systems. In research thermoelectric element current, voltage, power and efficiency are defined in different temperature differences.
Water as a Refrigerant for Heat Pump Technology: A Review
Even though water (R718) is one of the oldest refrigerants, it is very difficult to use it in compression refrigeration cycle due to its low molecular mass, high boiling point, low specific cooling capacity and a relatively higher value of kinematic viscosity. This paper gives us a glimpse about one of the technique which can be used to use water in compression cycle and also compares its theoretical analysis with the conventional refrigerants already being used. This paper can study the effect on various parameters under similar operation conditions for the comparative study of water and other refrigerants.
Cold Testing of IC Engines using Solar Energy
Cold testing of IC engines is becoming essential with the growing demand for environment friendly testing processes. This paper explains the processes of hot and cold testing and gives an example of sample calculations needed to energise a test bed using solar energy.
Mathematical Analysis for Small-Scale Osmotic Power Generation
According to the ‘Guardian’ the rise in the carcinogens and other harmful compounds are on rise since 1971. The increase have been noted to be 2% per year. United States contribute to 10% increase between 1999 and 2011. Harnessing energy from various renewable sources is the need of the hour and this paper puts forward a method which is in research stage at Statkraft*. The paper gives a mathematical investigation for it’s use for small scale applications and the methodology is further generalized. The results obtained can be used for respective applications as they are largely pertinent.
The paper aims in improvisation of the grinding process for elastic materials like rubber, plastic, composites, metals, waxes etc. Nowadays, we find a lot of wastage of these materials. Some of them like plastic, artificial rubber composites are very much harmful for our environment. This research will basically help in cautious use of the above mentioned pollutants. For example, Thermoplastics are difficult to grind small sized particle at ambient temperature because they are soften adhere in lumpy masses and clog screens. In cryogenic grinding when thermoplastic is chilled by dry ice, liquid carbon dioxide or liquid nitrogen they can be finally grounded to powder suitable for electrostatic spraying and other powder processes. Advantages of these processes are to increase productivity through optimized particle size, elimination of caking product within the mill, increases protection from the fire and product oxidation due to inert milling atmosphere..
Cryogenic system for High Temperature Superconducting Power Cable-A Review
Materials which shows superconductivity above liquid nitrogen temperature are known as high temperature superconductors. J.G. Bednorz and K.A. Mueller were awarded noble prize for discovering high temperature superconductors in 1987. Since last 3 decades there has been significant augmentation in the field of superconductivity. The primary advantage of HTS power cable over conventional cable is the ability to carry more power per circuit with lower energy cost per megawatt delivered. Power transmission is loosely defined as the transfer of electrical energy from source to a load over conductors that carry relatively large currents, while being maintained at large voltage. In order to achieve liquid nitrogen temperature, efficient cryogenic system is required. Hence, it is integrated with HTS power cables. Several HTS cables have been designed, developed and operated in various parts around the world. Most of them are used for experimentation purpose. Very few of them are used in electrical grids. Use of high temperature superconductivity in electrical grids will have a major positive impact on power system operation and control. HTS power cable is placed into heat-insulated pipe which is filled with cryogen. Circulation of cryogen removes heat seeping through the insulation. HTS power cables with different design considerations can be used for transmission of AC and DC.
Review on Effective Utilization of Electric Energy for Water Heating by Water Changing Property
Electricity is major parameter in our life which having wide application. By survey we use maximum electric energy for comfort life. In during various application of domestic we use hot water. To heat a water use various equipment which based on electric energy. In this experiment pH of water will be changes by using natural resources by observe what will be effect on heating purpose. Energy important and major source use in industries as well as Domestic purposes. This project will give one idea about how will improve efficiency and to save energy of heating coil which are used in industry and domestic for to heat water. We know that now days we concentrated on to saving energy because one day all natural energy sources will be end. So now we concentrate on saving energy in any field and to utilize energy so it span time will increase. In America they are used shell gases which are new technique but one day it will be vanish. If we survey in world there are so many energy required to produce electricity and every person used electric energy so we need highest energy efficiency equipment. In boiler there is convention and non -convention method also some time we used coal but with considering time is money so they change input from coal to electric energy. This experiment we get best utilization of nature resource for to save energy. There will be getting best method to reduce electric energy so whenever coil or electric furnace boiler used there will be water treated process will conduct. There is hypothesis is if change in pH of water due to that electricity required to heat water is also vary.
Review on Heat Transfer Enhancement of a Plate Fin Type Heat Exchanger by Different Shapes of Fins
Heat transfer enhancement techniques as passive, active or a combination of passive and active methods are commonly used in areas such as process industries, heating and cooling in evaporators, thermal power plants, air- conditioning equipment, refrigerators, radiators for space vehicles, automobiles (in tracked vehicle it plays very important roll), etc. Passive techniques, where inserts, extended surfaces like fins of various shapes and sizes are used in the flow passage to enhance the heat transfer rate, are benefited compared with active techniques, because the insert manufacturing process is easier and it can be easily applied in an existing heat exchanger. In design of compact heat exchangers, passive techniques can play an important role if a proper passive configuration/combinations can be selected according to the heat exchanger working condition (both flow and heat transfer conditions). Ribs, fins, dimples, Vortices etc., are the most commonly passive heat transfer enhancement devices. In this paper, major emphasis is given to work with different shapes of fins, and their arrangement because, these are found effective heat transfer enhancement tools.
Review on Optimization of Tilt Angle for Solar CSP for effective steam generation
Ample of Solar power is available in universe . It can be used for various applications . One of them is steam generation . Parabolic shaped dishes Concentrating Solar Power (CSP) technology can be found one of the most important option for generating renewable electricity at the required scale .The paper presented here , we have tried to do the optimization of tilt angle of Solar concentrators by using Taguchi Method . This is a statistical approach to optimize the variable process parameters and improve the quality of concerned components that are manufactured. The objective of this study is to illustrate the procedure adopted in using Taguchi Method to find best tilt angle for CSP . First, a Taguchi experiment was used to perform an efficient experimental design and analyzed the robustness of the tilt angles for fixed south-facing PV modules. The objective is to maximize the steam generated from the modules .
Solar driers applied for drying of agricultural and foodproductswitha retrospective study
Solar drying has several advantages over the traditional drying method and it has been now modernized and developed for drying various agricultural and food products. Solar energy drying which is proven to be an environment friendly and economically viable in the developing countries. The working condition with respective to design of various solar driers with thermal drying factors has been reviewed.
Performance investigation of centrifugal pump by varying blade angles of the Impeller–A Review
Centrifugal pumps are probably among the most often used machinery in industrial facilities as well as in common life. Centrifugal pump is widely used as a universal machine, so improving hydrodynamic performances of the centrifugal pump is important for energy saving. With the development of computational fluid dynamics (CFD), numerical simulation has become the main method for performance prediction and structure design of the pump. The impeller is the most important part in a centrifugal pump since it is the place where the mechanical energy is converted into hydraulic energy. Hence the parameters related to the impeller are directly affecting the performance of the pump. One of them is the blade exit angle; if it is not correctly designed, it can negatively affect the head and the hydraulic efficiency of the pump. The previous research suggests that a larger blade angle is suitable. Also, exit blades angle variation contributes more in the performance.
Experimental Investigation of Solar Adsorption Refrigeration System using Activated Charcoal-Methanol Working Pair
The extensive effort has made to develop the intermittent solid adsorption system that promises good alternative for solar refrigeration. Most research methods have used activated carbon–methanol for working pairs, and this has been considered as the most suitable working pair for solar solid adsorption Refrigeration. Going through the existing literature, it is revealed that there are no investigations on the simultaneous use of water cooled condenser, bypass way for adsorption process. Many researchers studied on TIM (transparent insulation material) for increasing the efficiency of solar collector. But, in this study, it is analyzed the solar powered refrigerator using polycarbonate glass, water cooled condenser with natural conduction, bypass way for adsorption to enhance the performance of solar adsorption system. Using this cyclical process it is possible to obtained cooling temperature of 11˚C. For increasing the effectiveness of solar heating, polycarbonate glass is used to achieve generator temperature up to 114˚C. In this system two valves with provision for bypass is made for easy operation and maintaining the flow of methanol during day and night. The solar powered activated charcoal-methanol paired system gives the cooling temperature up to 11˚Cfor 6kg water and achieve system COP=0.02.
Methanol-Activated Charcoal Refrigeration
Geometry optimization of exhaust manifold using CFD
It is well known that a appropriately designed Exhaust manifold is important for the optimal performance of an IC engine. Though, the intake system is dominant on the cylinder filling process, the exhaust manifold has ability to influence the gas exchange process in various important aspects, like the piston work done during the exhaust stroke, the short-circuit of fresh charge from the intake into the exhaust. We know that if the back pressure of Exhaust gases is higher, it reduces efficiency of the engine. So aim should be to reduce the back pressure of the engine. Also amount of pressure drop is equal to back pressure. So ultimate goal is to reduce its pressure drop by changing its geometry, reducing friction in the manifold . In this paper only Geometry optimization is done. This paper presents 3-D simulation of Exhaust manifold of 4 cylinder, 4 Stroke, turbocharged diesel engine(4G11 Greaves Engine) of generator by using ANSYS-CFX code and results are discussed. A Steady state CFD simulations have been accomplished and experimental results are compared for validation. The CFD results gives an idea for changing its geometry.
Implementation of Bharat Stage VI norms for small and medium duty CI engines
The emissions from the internal combustion engine are a major threat to the environment and thus needs to be controlled and kept a close watch on. India has decided to jump directly to BS VI after BS IV leapfrogging BS V. This paper mentions a few methods by which the target can be achieved and newer and better methods to achieve BS VI target. The changes that can be made to meet the stringent norms are either in the engine architecture, air handling system, after-treatment devices etc. But a sure shot method for the conversion of existing engines is still not present and is a major gap in the study and requires immediate attention.
Effects of Splitter Blades on Centrifugal Pump Performance - A Review
In turbomachinery design like pumps and compressors impeller is a crucial part. Centrifugal pump design is well facilitated by the use of Computational Fluid Dynamics (CFD). Opportunities do exist to improve the pump performance. This improvement can be achieved by making geometrical changes in design of an impeller like blade inlet & outlet angles, impeller inlet & outlet diameter and number of blades. Increase in number of blades increases the head and in addition causes the efficiency to decrease. This decrease in efficiency is due to the blockage of the fluid due to reduced area and increased friction inside the casing. Addition of splitter blades decreases the clogging at impeller inlet resulting in increase in pump performance. In this paper overview of various works by previous researches & their finding about study of effect of splitter blades on the centrifugal pump performance are done. And it is observed that as the splitter blade length increases; the flow rate and power increases, the efficiency decreases as well as hydraulic performances are improved, pressure fluctuations are reduced, and operating range is extended.On the other hand, the additional splitter blades will have positive effect on the cavitation performance due to the changes at the impeller inlet channel.
Analysis of gas diffusion in closed space: A Review
The hydro-chloro-fluorocarbon (HCFC) and hydro- fluorocarbon (HFC) are common refrigerant used for room air conditioner (RAC). But these are restricted due to a serious environmental issues owing to the high global warming potential (GPW). The replacement with low-GPW refrigerant such as R1234yf, R1234ze, R290 and R32 can be possible. R290 (propane) has major environmental and thermo-physical properties. But it is a flammable substance, thereby posing additional risks. When refrigerant leak into space, it may ignite if the concentration is higher than low flammable limit (LFL), there is always a region where the refrigerant concentration is higher than the LFL because the refrigerant concentration is 100% near the outlet from the air conditioner. Thus, understanding the refrigerant diffusion phenomena of low-GWP refrigerants is important to acquiring sufficient information for developing safety standards to assess the risks of using these refrigerants. In this study, diffusion phenomena were analyzed when a refrigerant leaked slowly from a room air conditioner (RAC) into a closed space.
Heat Transfer Enhancement in Shell and Tube Condenser
To increase the efficiency of the heat exchanger, the heat transfer enhancement techniques are utilized. This can be achieved once the heat transfer power of a given device is magnified or once the pressure losses generated by the device are reduced. Heat transfer enhancement is require to achieve a high heat transfer rate using minimum pumping power, to make the equipment compact, to minimize cost of energy and material, to get high heat transfer effectiveness, to increase efficiency etc. Condensers are primarily heat exchangers within which the refrigerant undergoes a phase transition which have various designs and come in many sizes. Shell and tube condenser is the most common type of condenser used in systems from 2 TR up to thousands of TR capacity. The Condensation of steam on single horizontal copper tube in a shell and tube condenser has been investigated using experimental and theoretical ways during this study. The outer surface of the tube was changed by brazing it with a copper wire lengthwise and helically to enhance the heat transfer constant. The result of varied the pitch of the helically brazed wire was studied with twenty five millimeter and thirty five millimeter pitch. Lengthwise Wire Brazed (LOWIB) and Helically Wire Brazed (HEWIB) Copper tubes with pitch twenty five millimeter and thirty five millimeter were found to extend the heat transfer constant by an element of about 1.5, 2 and 1.2 severally.
Effect of Different types of Baffles on Heat Transfer Pressure Drop of Shell and Tube Heat Exchanger: A review
Diverse sorts of heat exchangers are broadly utilized as a part of many design applications, for example, petroleum refining, refrigeration, cooling, nourishment industry, and so forth. Among various sorts of heat exchangers, manufacturing of shell and-tube heat exchanger is easy and multi-reason application conceivable outcomes for vaporous and fluid media in an extensive temperature and pressure territory. This paper manages a survey of exploratory research work that plans to look at the impacts of various baffles sorts on pressure loss and heat transfer in heat exchanger. Baffle is one of the basic part considered in design of STHE. Confuses, having an essential piece of STHE, offer help to keep of support tubes in bundle and as shell side it also helps to maintain the speed of stream. Different sorts of baffles are utilized as a part of STHEs. For example segmental, flower, ring, trefoil hole, plate and doughnut sort and helical. Be that as it may, conventional HX with segmental baffle indicate low heat exchange proficiency and extensive pressure loss. From the present review it can be inferred that helical baffles fill in as an all the more encouraging innovation due to having less loss of pressure in shell, better heat exchange execution, less fouling and less liquid incited vibration.
Design of Heliostat Field for Small Scale Central Receiver System
Central receiver system (CRS) is one of the type of concentrated solar power (CSP) technology which consists of heliostat field, receiver and power generation unit. Heliostats are nothing but the mirrors which concentrate solar radiation at one point on receiver which is located at the top of a high tower. Out of the total cost of system heliostat field contributes 50% and leads to about 47% of the annual energy losses. So placing of heliostats in field is most important in order to minimize optical losses and indirectly minimizes energy losses. In this Paper work, heliostat field is designed for no shadowing, blocking losses and optimized cosine efficiency for small field area specifically for Pune location. An algorithm is developed for heliostat distribution in heliostat field as per design using a MATLAB.