bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of partial discharge source in shunt reactor and evaluation of its benefits
Authors: Miyazaki Satoru , Kuraishi Takashi , Takahashi Tsuguhiro
Published: August 2024

In recent years, the “asset management” or “managing assets” technique has been expected to support the rationalization of the maintenance and operation of electric power equipment, especially as a countermeasure for aging equipment. For this purpose, the development of diagnostic methods for aging, remaining life, and faults is necessary. Furthermore, it is important to accumulate case studies applying such diagnostic methods to real equipment and the analysing benefits of the applications of the diagnostic methods. In this report, frequency response analysis and a partial discharge measurement are applied to a shunt reactor suspected of occurrence of partial discharge. Results of the diagnostic methods suggest the breakage of the earth bar connecting the iron‐core blocks and the occurrence of the partial discharge at the iron core. From these diagnostic findings, the shunt‐reactor operator decided to postpone the replacement for 2 years, compared with the case where no diagnostic methods were applied. In this report, the benefits of deciding the postponement is also evaluated.
Evolution of Endpoint Detection and Response (EDR) in Cyber Security: A Comprehensive Review
Authors: Kaur Harpreet , Sanjaiy SL Dharani , Paul Tirtharaj , Kumar Thakur Rohit , Kumar Reddy K. Vijay , Mahato Jay , Naveen Kaviti
Published: August 2024

Endpoint Detection and Response (EDR) solutions are pivotal in modern cybersecurity strategies, enabling organizations to detect, investigate, and respond to cyber threats effectively. This detailed examination of EDR technology traces its development from inception to its current state. It delves into the core concepts of EDR, highlighting its importance in endpoint security and threat identification. The document explores the historical background and driving forces behind EDR's advancement, emphasizing technological progressions like machine learning, behavioral analytics, and threat intelligence that enhance EDR capabilities. It also addresses challenges faced by EDR solutions, such as scalability, performance issues, and evasion tactics by sophisticated adversaries. Through case studies and industry trends analysis, the paper showcases EDR's efficacy in combating cyber threats and its integration into broader cybersecurity frameworks. Furthermore, it discusses the future outlook of EDR technology, considering the impact of emerging technologies like artificial intelligence, automation, and decentralized architectures. By consolidating insights from academic studies, industry analyses, and practical applications, this paper provides a comprehensive overview of the evolution of EDR in cybersecurity.
Auto encoder-guided Feature Extraction for Pneumonia Identification from Chest X-ray Images
Authors: Rana Neeta , Marwaha Hitesh
Published: August 2024

The World Health Organization recognizes pneumonia as a significant global health issue. Artificial intelligence, particularly machine learning, and deep learning has emerged as valuable tools for improving pneumonia diagnosis. However, these techniques face a major challenge: the lack of labeled data. To tackle this, we propose using unsupervised learning models, which can produce comparable results even with limited training data. Our study presents an unsupervised learning approach utilizing autoencoders to detect pneumonia from chest X-ray images. Our method uses Variational autoencoders for feature extraction, which are then employed in classification using a Random Forest classifier. The model is trained on a dataset containing two classes of X-ray images: pneumonia and normal. Our approach demonstrates effectiveness comparable to existing supervised learning methods.
Predicting Wear Properties of Alloy 7090/SiC Nanoparticle Composites Using Artificial Neural Networks for aerospace application
Authors: Hussain Beporam Iftekhar , Kaliappan Seeniappan , I Manikandan , Polisetty Lava Kumar , Saravanan M. , Maranan Ramya
Published: August 2024

In the current study, we have explored the wear characteristics of Al 7090 alloy-silicon carbide nanoparticles composites that can be applied to aerospace. The composite material is prepared very carefully by stir casting in the laboratory, and silicon carbide nanoparticles are incorporated to enhance the strength. Wear testing was done using the Taguchi Design of Experiments methodology, and factors like load, speed, and composition were systematically varied. Finally, the results of the experiment, on the basis on which wear behavior was inferred to extract optimal conditions in terms of Sw and friction force , are reported. Furthermore, an ANN model is developed, calculations are done by the feed-forward backpropagation algorithm, and the Levenberg-Marquardt optimization algorithm is applied to optimize the parameters . A completely representative of 500 readings are undertaken, and 70% are used for training; 15% are used for testing and the remaining 15% are taken for validation. Surprisingly, the trained ANN model prediction accuracy rate reached 100%, a linear regression plot showing a good representation of the model’s accuracy. Conclusively, our results demonstrate that the developed ANN model is the most effective approach for obtaining the optimal prediction of Sw and friction force , thereby the ANN model can be used for predicting the performance of other composites.
Role of Psychological Contract in Employee Engagement in Higher Education: Empirical Study on Uttarakhand
Authors: Khanna Malhotra Rupa , Sharma C.A. Priti , Upreti Himani , Sharma Shruti , Prakash Namrata , Mittal Shilpi
Published: August 2024

The research study was pursued with an attempt to Study the Role of Psychological Contract in the Employees Engagement with specific objectives of Learning the Role of Psychological Contract in the Employees Engagement, identifying the numerousmagnitudes of Employee Engagement, studying the impact of Psychological Contract on every aspect of Employee Engagement and studying the impact of age, tenure and gender on Employee Engagement. Stratified random sampling technique was adopted as means of data collection from 600 full-time employees working in private HEI in Uttarakhand using structured and self-administered questionnaires: PC Questionnaire and ER Questionnaire checking their validity and reliability. The need of the study was to establish relationship between employee engagement or retention with the psychological contracts and the outcomesestablish the same.Many Organisations willantagonize difficulties in the coming years. Major amongst the most imperiousproblems will be procuring, preparing, overseeing and holding millennial employees. A theoretical commitment of this examination is that it joins two territories of research not already explored together with regards to establishments; psychological contracts and worker retention. The outcomes show that there is a solid connection between psychological contract satisfaction and employee engagement, however the relationship does not seem, by all accounts, to be directed by some other factor, for example, age, gender or tenure. Following specific results were from a practical perspective, there is a growing interest in understanding employee engagement, as it is perceived that the growth and prosperity of organizations will rely heavily on the committed and competent workforce. The suggestion that the relationship between PCfulfilment and ER are positively related irrespective of age and gender is indicative of the fact that management need to pay more focus on the fulfilment of motivating psychological contract rather than adherence to merely hygiene factors.
Impact of blockchain on IT
Authors: Kumari Jyoti , Ojha Megha , Singh Praveen , Archana
Published: August 2024

Blockchain, an emerging technology reshaping numerous industries, has garnered significant attention from researchers due to its myriad benefits and the plethora of research opportunities it presents across various sectors. With the rapid evolution of blockchain research publications, there's a growing demand for thorough investigative studies to assess the current knowledge landscape in this field. While a few review articles have addressed recent developments and challenges in blockchain technology, there hasn't been any bibliometric analysis utilizing the Web of Science (WoS) as a dataset to gauge the assertiveness of the art inblockchain research. Hence, conducting a comprehensive bibliometric study becomes imperative. This study focused on analyzing all unionidentifications, and articles, and examiningdocuments on blockchain indexed by WoS from [7] to [19], categorizing them into five research topics. The findings yielded valuable insights, including trends in annual journals and quotes, popular seekfields, first-leading papers, preferred journalboards, and notable funding sources. The study's conclusions offer various recommendations that can serve as a benchmark for both novice and qualified researchers embarking on blockchain research endeavours’. can be used as a benchmark before beginning a blockchain study development in the prospect.
From Detection to Recovery: The Promise of AI in Managing Postpartum Depression in India
Authors: Shah Priyanka , Yadav Kanchan
Published: August 2024

Post-Partum Depression (PPD) influences an enormous number of new mothers in India and impacts both the well-being and improvement of their posterity as well as the new mothers' prosperity. To upgrade PPD location, treatment, and the executives in different medical care settings in India, this exploration researches the conceivable outcomes of using computerized reasoning (simulated intelligence). The study examines how AI technologies could be incorporated into existing healthcare systems to control PPD. This incorporates handling issues like the shortage of psychological wellness subject matter experts, the shame related to emotional well-being, and the shortfall of fitting and delicate screening procedures. Through simulated intelligence calculations, normal language handling, and manmade intelligence-driven chatbots for treatment, it underscores leap forwards in artificial intelligence that permit early discovery and individualized treatment regimens. The paper also discusses the ethical implications of AI technology, such as concerns regarding privacy and the requirement for long-term research to evaluate the continued effectiveness of AI tools. Future drives center around carrying artificial intelligence applications to oppressed populaces and fortifying the joining of these innovations with traditional medical care administrations to give an exhaustive and solid strategy for PPD executives in India.
Supply Chain Management and its Role in Rail Transport
Authors: Kumar Manoj , Vipin  , Agarwal Ashish
Published: August 2024

This empirical study article explores the role of supply chain management (SCM) in the context of rail transportation and provides an outline of SCM. Effective supply chain management techniques are crucial for the smooth running of the rail industry, which plays a vital part in global logistics networks. The study looks at a number of SCM-related topics in rail transport, such as logistics planning, inventory control, transportation, and supply chain partner cooperation. To assess their perceptions of SCP in transport coordinated factors from the expense and administration viewpoints, a survey and interviews with the rail transport logistics industry were undertaken. The study's findings demonstrated that rail transportation has reached a particular level of maturity and sophistication in its SCP. The influence of SCM on rail transport efficiency, cost savings, and customer satisfaction is examined using empirical data and industry case studies. The study's conclusions offer management guidance to the rail industry so they may comprehend their SCP in transport coordinated operations and recognize regions for development. The results emphasize the value of SCM in streamlining rail transport operations and offer guidance for both scholars and industry professionals.
Comparative Evaluation of Satellite- Based Merra-2 against Ground-based Data for PM2.5 and TC Concentrations in Ghaziabad, India
Authors: Sinha Rishika , Madan Preha , Singh Rahul , Gupta Lovleen
Published: August 2024

This study compares satellite-based observations of PM2.5 and Total Carbon (TC) concentrations derived from NASA’s MERRA-2 reanalysis dataset for the Ghaziabad region with ground-based observations at two sites (Site A and Site B) from June 2018 to May 2019. Results reveal consistent underestimation by MERRA-2, with daily mean biases of -85.34 (Site A) and -111.31 (Site B) for PM2.5, and -54.77 (Site A) to -59.08 (Site B) for TC, alongside monthly mean biases of -81.30 to -103.74 for PM2.5 and -54.77 to -59.08 for TC. The absolute error indicates a 49.01% to 53.85% underestimation for both PM2.5 and TC. Daily FAC2 values show around 39% agreement for PM2.5, reducing to 0.27 (Site A) and 0.3 (Site B) monthly, indicating reduced agreement over time. For TC, daily FAC2 is notably low at 0.04 (Site A) and 0.06 (Site B), with no monthly agreement within a factor of 2 of ground-level data. Strong correlations (R²=0.68-0.84 for PM2.5; R²=0.94-0.96 for TC) between biases and ground-level data are observed, indicating proportional relationships. However, discrepancies increase with higher PM2.5 mass concentration, highlighting MERRA-2’s limitations during elevated pollution periods. Significant monthly variations are observed in GLC-PM2.5 concentrations at Site A (F= 61.42, p= 1.68×10-11) and Site B (F=25.15, p=2.96×10-06), and For GLC-TC concentrations at Site A (F=103.85, p=4.10×10-16) and Site B (F=55.70, p=7.54×10-11). Both GLC and MERRA-2 PM2.5 and TC concentrations follow a consistent monthly pattern, with higher levels during post-monsoon and winter seasons and lower levels during monsoon and pre-monsoon periods. This study underscores MERRA-2’s limitations in estimating PM2.5 and TC concentrations compared to ground-based observations and emphasises the necessity for further refinement and validation of the MERRA-2 model to enhance accuracy across different spatial and temporal scales.
Toward the use of an intermediate value of the modulus of deformation of soils in geotechnical design
Authors: Mukhamejanova Assel , Aldungarova Aliya , Alibekova Nurgul , Karaulov Sabit , Kudaibergenov Nurlan , Yespolova Zukhra , Kurmanova Dametyk , Baizakova Gulmira , Kazhimkanuly Dias
Published: August 2024

This study presents the results of a critical analysis of the existing methods of selecting the values of ground deformation modulus used in calculating the settlement of designed foundations. The importance of improving the reliability of the determination of the modulus of deformation for ensuring the reliability, economic efficiency and safety of structures is highlighted. It is revealed that the determination of the deformation modulus is not performed at the full depth of soil samples, which can lead to the risk of accidents at facilities. To increase the reliability of deformation modulus determination, a method of interpolation of values based on data from nearby wells is proposed. A new model for determining intermediate values of the deformation modulus is presented, which can be used in calculating the settlement of designed buildings. The results of test problems confirm the high efficiency of the proposed method not only for the calculation of foundation settlement using the values of ground deformation modulus, but also for the control determination of refined values of ground deformation modulus at the stage of geotechnical engineering surveys.
Approximation of strength and deformation properties of soils by ArcGIS Topo to Raster tool
Authors: Aldungarova Aliya , Alibekova Nurgul , Karaulov Sabit , Aitkazina Ayazhan , Makhiyev Bekbolat , Khapin Alexandr , Kazhimkanuly Dias
Published: August 2024

This study examines the application of Topo to Raster interpolation technique in ArcGIS software to analyze the strength and deformation properties of soil at a construction site in Astana. Topo to Raster methodology allows converting topographic data into raster format, which provides a more detailed view of the landscape and its characteristics. In optimizing the design of foundations and making design decisions in complex ground conditions, the use of this technique allows to take into account the spatial variability of soil properties at different depths. The results of the study show that the Topo to Raster interpolation technique in ArcGIS provides more accurate and reliable predictions of strength and deformation characteristics in the study area. The created heat maps based on this methodology allow taking into account realistic scenarios of soil behavior and improve the accuracy of predicting foundation settlement, which is critical for comparison with the limit values recommended in the SP RK [1].
Impact of Solid Waste Dumping on Groundwater for Suitability of Drinking and Irrigation Purpose: A Case Study
Authors: Niphakar Gayatri , Dubal Harshada , Patil Jaya , Deshpande Medha
Published: August 2024

One of the principal industrial hubs in central Maharashtra is Aurangabad. The city’s garbage production is steadily rising, and more waste is being dumped at the Naregaon dumpsite for the disposal of municipal solid waste (MSW). People in and around dumping site are dependent on groundwater for their domestic and irrigation use. This paper aims to research how the disposal of MSW affects the quality of the ground water near the dumping site. An attempt has been made to establish a Water Quality Index (WQI) for various groundwater quality parameters (pH, Temperature, Electrical Conductivity, Total Dissolved Solids, Total Hardness, Calcium Hardness, Magnesium Hardness, Carbonate, Bicarbonate, Calcium, Magnesium, Dissolved Oxygen, Chlorides, Sulphates, Phosphate, Nitrate, Fluoride, Sodium, Potassium, Coliform count) at 30 different locations in the periphery of 2 Km around dumping site. Spatial distribution of these parameters is shown by using Geographic Information System (GIS). The various irrigation indices which are mathematical equation that transforms water quality data into a numeric value that describes the quality of irrigation, such as Electrical Conductivity (EC), Sodium Absorption Ratio (SAR), Residual Sodium Carbonate (RSC), Permeability Index (PI), Kelly’s Ratio (KR), Magnesium Hazard, Sodium Percentage (SP). Metal index (MI) was calculated to assess the contamination of the groundwater with the metals (Copper, Lead, Cadmium, Arsenic, Manganese, Chromium) which erected seriously at most sites particularly for drinking utilization. The study concludes that the contamination is caused by the improper disposal of solid waste over a long period of time, and it is essential to protect against risks of pollution.
Enhancement of Mechanical Properties in Hybrid Polymer Composites through Titanium Nanoparticles and Kenaf Fiber Integration
Authors: R Tamilselvan , S Magibalan , R Rajkumar , S Eswaran , N Senniangiri
Published: August 2024

Aerospace, home goods, and automobiles all have a need for high-performance composites manufactured using polymer matrix that are lightweight, and durable. This research looks at the mechanical properties of hybrid polymeric composites supplemented with titanium nanoparticles and Kenaf fiber ranging from 0 to 20 wt.%. During the production process, titanium nanoparticles (NPs) are dispersed inside the polymer matrix using mechanical mixing and sonication. The next step is to calculate the mechanical properties of the nanocomposites, including their impact, bending, and tensile strengths. Out of the five different hybrid types, the S3 hybrids had the best mechanical properties, including a tensile strength of 60 MPa, a flexural strength of 68.41 MPa, and an impact energy of 5.17 J. Volumetric degradation is reduced by 10-15% under typical load conditions after 17.5 wt.% titanium nanoparticles are added, in comparison to Sample S1 hybrids. One possible explanation for the reduced propensity for volumetric deterioration is the inclusion of titanium nanofillers in the fiber matrix composition. Additionally, the physical characteristics are examined in order to grasp the overall performance of the nanocomposites. The results will be useful in developing eco-friendly materials with good performance for applications in various fields, like construction, the packaging industry, and the automotive industry, where improved mechanical properties are required. Titanium nanoparticles have the potential to significantly enhance the functionality of organic fiber-reinforced polymeric composites, as this work has shown.
Water Treatment Using Atmospheric Pressure Plasma: Dielectric Barrier Discharge and Corona Discharge Method, and Reactive Species Analysis
Authors: Chavan Umesh , Patil Suvarna
Published: August 2024

This paper explores the application of atmospheric pressure plasma technology as an emerging method in the field of water treatment. Specifically, the dielectric barrier discharge (DBD) and corona discharge methods are employed for water purification, with a focus on characterizing different species present in both untreated and treated water samples. The results indicate the generation of various reactive species following the atmospheric pressure plasma processes, notably including reactive oxygen and hydrogen species such as nitrate, nitrite, hydrogen peroxide, and ozone. Throughout the experimentation, it is noted that there are no significant alterations in pH values, while there is an increase in nitrate, nitrite, hydrogen peroxide, and electrical conductivity. Here effect of various electrode materials are also studied. Three electrodes were used for experimentation which are copper, steel and brass. This augmentation of reactive species opens up diverse applications for plasma-activated water, including but not limited to agriculture, water disinfection, purification, and desalination. Notably, corona discharge generated more reactive species compared to the DBD method.
Utilization of Participatory Rural Appraisal Techniques for Housing Condition Evaluation for Sustainable Development: A Case Study of Earthen Dwelling
Authors: R Harisankar , Siva Rathan R T Arjun , Arlikatti Sudha
Published: August 2024

The interactions between hazard exposure, social vulnerability, and physical vulnerability conditions cause major impacts during disasters. Infrastructure and housing problems are given more importance and considered as the root of many other concerns. As a self-disaster recovery approach, earthen construction techniques have gained greater acceptance due to the utilization of local materials, indigenous building practices that do not depend on highly skilled paid labour, and affordability. Earthen construction techniques are practiced globally, in various geographical conditions adapted to serve as site-specific hazard mitigation measures. This study utilized Participatory Rural Appraisal (PRA) techniques, to examine the vernacular earthen practices of the Rajanga village of Dhenkanal District, Odisha State, India, and performed a qualitative analysis of its disaster resilience capacity. This village is located in a very high-damage risk zone for wind and cyclones. Findings suggest that PRA methods are effective in exploring construction practices and conducting a cause-issue-effect analysis after synthesizing various PRA inputs. Poor housing conditions in the village are due to a deterioration of various building elements and lack of hazard-resistant features increasing the vulnerability to disasters. In conclusion, PRA methods can be utilized as an effective tool for the exchange of knowledge between researchers and rural community members at large, for initiating a co-design process and conducting capacity building. Earthen construction methods have a greater potential for sustainable development, where it is engineered using traditional knowledge and new knowledge and incorporated with disaster-resilient features.
ANN-Based Prediction of Compressive Strength in Glass Wool Reinforced Brick
Authors: Pamu Yashwanth , SVSNDL Prasanna
Published: August 2024

The construction industry continuously seeks innovative materials and methodologies to enhance structural integrity while minimizing environmental impact. This study investigates the predictive capabilities of Artificial Neural Networks (ANN) in estimating the compressive strength of clay brick. Employing a dataset derived from comprehensive experimental trials encompassing varying compositions and curing conditions, an ANN model was developed and trained to predict the compressive strength of glass wool reinforced composite bricks. The inputs to the ANN comprised key parameters including the proportions of glass wool content, load at failure, area of cross-section and burning temperature. The model was optimized through iterative training processes to attain robustness and accuracy in predicting compressive strength. Subsequently, validation was performed using separate test datasets to evaluate the model’s generalization capacity. The results demonstrate the efficacy of the ANN model in accurately forecasting the compressive strength of glass wool reinforced clay brick. The analysis reveals nuanced correlations between glass wool content, load at failure, area of cross-section and burning temperature, and the resultant strength, shedding light on the intricate dynamics governing these composite materials. This ANN-based predictive approach presents a useful tool for engineers and stakeholders in the construction industry to anticipate and optimize the compressive strength of glass wool reinforced clay bricks. Furthermore, the findings contribute to advancing the understanding of these novel composite materials, fostering sustainable and resilient construction practices.
Optimizing truss members using Machine Learning
Authors: Osama Marwan , Hamza Manar Magdi , Hasan Ahmed M.M. , Othman Mohamed N. , Matar Yaser M. , Ahmed Ahmed M.
Published: August 2024

This paper aims to produce an optimization methodology for a truss for minimal stress on critical sections using Machine learning models. This is done by varying the height and length of the truss span and applying live loads on different joints. The optimization of the truss is done through feed forward with back propagation artificial neural network model, The optimized truss is modelled and analysed using finite element and stiffness software. The paper presents the results and identifies the best dimensions for the truss design with a safety factor.
Novel Mechanical Strength Prediction Models of Fibre Reinforced Concrete Using Statistical Analysis
Authors: Mounika Ganta , Sai Teja Sangeetham , Sarayu Vitikala , Narendar Kongari
Published: August 2024

Fibre Reinforced Concrete (FRC) has emerged as a promising construction material due to its enhanced mechanical properties and improved performance under various loading conditions. This study focuses on the development of Non-Linear Regression (NLR) models for predicting the 28-day mechanical characteristics like Compressive (CS), Splitting tensile (STS) and Flexural strengths (FS) of FRC. Through an extensive review of existing literature and empirical data, various factors affecting the mechanical properties of FRC have been identified that include the cement content, fine and coarse aggregate content, super plasticizer content, fibre content and water cement ratio. Leveraging this comprehensive understanding, NLR equations have been formulated to capture the complex relationships between these variables and the 28-day resulting mechanical strengths. The accuracy and reliability of the models have been rigorously assessed through statistical analysis and performance evaluation metrics like R2, Root Mean Square Error (RMSE) and probability (p) value. The NLR model for CS demonstrated an R2 of 0.933, RMSE of 5.6 MPa and a p-value of 4.39e-34, similarly the NLR model for STS demonstrated an R2 of 0.932, RMSE of 1.07 MPa and a p-value of 5.22e-11 and finally FS model of FRC demonstrated an R2 of 0.94, RMSE of 1.23 MPa and a p-value of 7.54e-15 respectively.
Information modeling of construction project management processes at the design stage
Authors: Chebotarev Dmitry , Sinenko Sergey
Published: August 2024

The article analyzes the current situation and the results of BIM research at home and abroad, compares the advantages and disadvantages of BIM technology and traditional two-dimensional drawing technology in project management, analyzes the characteristics of projects and the problems that need to be solved. The principles of modern project management are given. The project management process is established on the basis of theoretical methods. The results of the study have a certain theoretical value for the implementation of BIM in construction practice and increasing the level of integration of management information.
Identification of Significant Attributes for the Development of an Assessment Tool Applicable to Green Campuses in India
Authors: Janhavi Mahale , Kanchan Khare
Published: August 2024

Green campuses play a significant role in transforming societies and fostering a sustainable future as they are anticipated to make a significant contribution toward environmental sustainability. The evaluation and prioritization of the green campus initiatives are likely to be underresearched. The global movement toward green building initiated following the development of various green building rating tools (GBRT) for assessment. These tools require modification to account for sustainability considerations. When applied to educational campuses in India, the limitations of the eight existing GBRTs were revealed. To address these limitations, a scientific study of eight GBRTs including two Indian GBRTs such as Indian Green Building Council (IGBC), Green Rating for Integrated Habitat Assessment (GRIHA) and other six international GBRTs like Building Research Establishment Environmental Assessment Method (BREEAM), Leadership in Energy and Environmental Design (LEED) was conducted. This study identified significant green attributes for green campuses, with a particular focus on green campuses in India. A questionnaire survey was conducted to gather data on these attributes. Principal component analysis (PCA) was applied to 249 valid responses from the survey, resulting in the extraction of 56 significant attributes of green campuses under nine components. This study discusses the significant attributes identified through this analysis.
Spatial interpolation of intermediate strength properties of soil to determine the bearing capacity of the foundation
Authors: Aldungarova Aliya , Alibekova Nurgul , Karaulov Sabit , Yespolova Zukhra , Kurmanova Dametyk , Baizakova Gulmira
Published: August 2024

This study is aimed at determining the intermediate strength characteristics of soil at a given depth between boreholes using geoinformation systems. Changes in the strength characteristics of soils under the influence of load are studied, which is important for assessing the bearing capacity of the foundation and developing optimal solutions for its improvement and strengthening. A comparative analysis of Kriging and IDW methods in ArcGIS software package for determining the spatial variation of soil strength characteristics (c, φ) was carried out. The results showed differences in the values of specific cohesion and angle of internal friction varying depending on the chosen interpolation method. The proposed methodology for determining the intermediate soil strength characteristics takes into account the soil overlay, the thickness of the layers and the relative position of the known values obtained from the monolith selection. This is important for accurate determination of the bearing capacity of the foundation.
Strength And Durability Properties of Sustainable Concrete Utilising Rice Husk Ash and Silica Fume
Authors: R Premkumar , S Keerthick Balaji , Balaveeradurai  , P Velraja , Jayakanth
Published: August 2024

Supplemental cementitious material has been commonly added to concrete in recent years. By replacing some of the Ordinary Portland Cement (OPC) in concrete with cementitious elements like fly ash and silica fume, the mechanical properties of the mixture can be enhanced. There is an impending fly ash shortage in Arkansas because to nearby coal plant businesses. The possible use of rice husk ash (RHA) to replace cementitious materials has been investigated in this study. RHA is a waste product that is produced during agricultural processes. Due to its elevated silica content, it can be used as cementitious materials. In this investigation, concrete was modified to partially replace Ordinary Portland Cement using silica fume (0 to 20%) and RHA (0 to 30 %) at different percentages. In this investigation, a Class C fly ash that is often utilised locally was also included for comparison analysis with concrete specimens modified with RHA and silica fume. Both the fresh concrete mix’s and hardened concrete’s mechanical characteristics were ascertained through laboratory testing. The durability of the material will be improved, and the quantity of cement required will be reduced by the addition of silica fume and RHA to concrete. This includes improvements in water absorption, sorpitivity, effective porosity, permeability, acid resistance, and resistance to fast chloride penetration. Nevertheless, the incorporation of silica fume and RHA in concrete leads to an elevation in water demands in comparison to the standard regular Portland cement mixture.
Experimental Investigations on Nano Silica Concrete
Authors: Manoj G. , Thirugnanasambandam S.
Published: August 2024

In construction industry the innovation and advancement technology has major scope in new inventions. Nano materials plays their role in the improvement of the construction sector by enhancing the material properties. Nano particles which are having high surface area compared to its volume. Nano materials are more reactive and improve the concrete mechanical properties. In order to study the performance of the nano silica concrete, the various mix ratios were used. The optimum dosage of nano silica in concrete was found. Various dosages of nano silica 0%, 1.5%, 2%, 2.5%, 4%, 6%, 8% were attempted. A constant water to cementitious materials ratio of 0.45 was kept for all mixtures. The results indicate that the incorporation of nano silica increased the compressive strength of the concrete when compared to control concrete. Compressive strength, Modulus of Elasticity and flexural strength of the nano silica-based concrete were also examined.
Development of Small-Scale Model House Using Cupola Slag
Authors: Kasare Yogesh , Meshram Sangita , Pusate Samyak , Ghurde Viplav , Banshpal Soham , Bhogekar Prasad , Khandare Rudraksh
Published: August 2024

The increase in waste from industries has resulted in growing concern for the environment. This form of waste is directly deposited on land, leading to contamination. This waste can be effectively used in the production of various building materials. This not only contributes to the reduction of pollution but also provides an economical alternative for sustainable infrastructure. The utilization of various waste materials is being utilized to enable the development of sustainable building resources. The aim of this study is to investigate the utilization of various types of industrial waste, including cupola Slag, fly ash in the fabrication of building blocks. This study examines different combinations of ingredients for producing building blocks with blends of cupola slag (55% to 80%), fly ash (10 % to 30 %), and maintaining a consistent cement content of 10%. This study consists of total 5 possible mix proportions of cupola slag, with fly ash and cement. This study provides comprehensive information about the properties, test conducted and recommended mixtures. An analysis of the physico-mechanical properties of the building blocks was conducted, and it was found that they meet the standards set by the Indian Standards. The findings indicate that the cupola slag-fly ash-cement (CS-70-FA20) is the best combination and has potential to produce sustainable building blocks. A small-scale model house was built from the developed building blocks of best combination.
Mechanical Performance of Natural Fiber-Reinforced Concrete using Banana Stem and Sugarcane Fibers
Authors: Sales Showna Lee T. , Abellana Virgilio Y. , Lobarbio Camila Flor Y. , Puyoc Christopher T. , Galagar Jayson R. , Laseras Chavey S.
Published: August 2024

Concrete, widely used in construction, boasts high compressive strength but suffers from low tensile strength, leading to rapid crack propagation and brittle failures. Natural Fiber-Reinforced Concrete (NFRC) mitigates these issues by incorporating short, uniformly distributed fibers into the concrete matrix. This research explores NFRC using banana pseudostem fiber, sugarcane bagasse fiber, and their blend. The objectives include optimizing mix designs by varying fiber volumes, assessing the physical and mechanical properties of Banana Pseudo Stem NFRC, Sugarcane Bagasse NFRC, and Hybrid Fiber-Reinforced Concrete (HyFRC), and evaluating NFRC’s resistance to micro-crack propagation through SEM analysis. Natural fibers of 30mm, 40mm, and 50mm lengths were used, with sugarcane bagasse fibers at 0.25%, 0.50%, and 0.75% volume fractions, and banana pseudo-stem fibers at 1%, 1.5%, and 2%. Results showed that a 1.5% increase in 50mm banana pseudo-stem fibers reduced compressive strength by 26.7% but boosted flexural strength by 71.78%. A 0.75% increase in 40mm sugarcane bagasse fibers raised compressive and flexural strength by 33.14% and 150.09%, respectively. Combining 75% banana with 25% sugarcane fibers improved compressive and flexural strength by 13.92% and 64.43%, respectively. The optimal mix included 1.5% of 50mm banana fibers, 0.75% of 40mm sugarcane fibers, and a 75%:25% banana to sugarcane ratio. Integrating natural fibers into concrete shows promise for enhancing reinforced concrete’s strength.
Evaluation of independent energy storage stations: A case study of the western Inner Mongolia region in China
Authors: Jiang Dalin , Li Tao , Men Dongpo , Wei Wensheng , Wu Lin
Published: August 2024

This study presents an economic evaluation of independent energy storage stations (IEES) in the Western Inner Mongolia power market. The study evaluates the profitability and investment return period of a hypothetical 100 MW/200 MWh energy storage station under the current spot market conditions. The results indicate that the IESS achieves an annual operating time of 668 hours, with a potential arbitrage income of 15.39 million CNY, leading to a static investment payback period of 10.81 years. The findings underscore the necessity for improved cost recovery mechanisms, such as capacity compensation, to make energy storage investments more viable in the face of current market constraints.
Differences in the Effect of Sanding Wind Speed Thresholds on Wind Erosion Assessment Results
Authors: Wang Lu , Zhao Xia , Ouyang Shuliang , Jin Xiongxiong
Published: August 2024

Soil wind erosion is an important cause of topsoil loss in arid and semi-arid areas of China, and the estimation of wind erosion is related to meteorology, topography, soil, vegetation and other factors, and the threshold value of sand initiation wind speed directly affects the results of wind erosion assessment. Qinghai Province as a key area of wind and sand prevention and control, assessment of wind erosion is significant, this paper corrects the sand threshold of wind factor, comparing the unique value of 5.5 mꞏs-1 and the distributed threshold calculated by the formula method, respectively, to participate in the calculation of the amount of wind erosion. The results show that: when the threshold value of 5.5 mꞏs-1 is taken, the wind erosion modulus in 2020 is 34.11 tꞏhm-2ꞏa-1, and the erosion amount is 1.175 billion t. When the threshold value is calculated using the distributed threshold of the formula method, the wind erosion modulus is 58.79 tꞏhm-2ꞏa-1, and the erosion amount is 2.933 billion t. The formula method is a combination of soil particle size, soil moisture and vegetation cover to obtain the critical sand-generating wind speed, which is more accurate in the Qaidam basin and Gonghe basin. The results show that the average soil wind erosion intensity in Qinghai Province is intensity erosion, and the spatial wind erosion intensity is higher in Qaidam Basin, Gonghe Basin and the western region of Sanjiangyuan, while the erosion is weaker in eastern and southeastern Qinghai. Wind erosion occurs mostly in winter and spring.
A study on the effect of air humidity on jet flames of hydrogen ships
Authors: Jia Huidong , An Zuxu , Qi Baiyi , Yang Guogang , Ma Xiangkun
Published: August 2024

With the rapid development of the shipping industry and the proposal of “double carbon” strategy, green shipping has become the center of development in China. Hydrogen-powered ships are powered by hydrogen fuel cells, which have the advantages of zero pollution, zero emission, fast charging speed, and high stability during operation; these features make hydrogen-powered ships have a broader development prospect. Due to the flammable and explosive nature of hydrogen, when hydrogen leakage occurs, combustion and explosion are very likely to occur, so hydrogen safety has also become a major problem for hydrogen-powered ships before they are widely used.In this thesis, the effect of ambient humidity on the hydrogen jet flame is investigated by numerical simulation of hydrogen jet flame generated from a hydrogen fuel cell ship in an open environment using CFD computational fluid dynamics software. The results show that under different ambient air humidity, the upper part of the jet flame is shifted to the cockpit to different degrees, and the difference of its flame shape is small. With the increase of ambient air humidity, the molar concentration of hydrogen distributed on the wall surface of the cockpit decreases gradually, and the temperature decreases gradually.
Research on spatial and temporal patterns of carbon emissions and influencing factors in the Yellow River Basin based on county scale
Authors: Kong Xuekai , Wang Yaping , Du Jiusheng , He Shi , Wang Lei
Published: August 2024

The increase of carbon emission is the main driver of global warming, which has seriously threatened the sustainable development of human society and the balance of the ecosystem. This paper focuses on county-level cities within the Yellow River Basin. Using land use data, energy consumption data and nighttime light remote sensing data, carbon emissions resulting from land use are computed for from 2000 to 2020, and studies its spatiotemporal evolution characteristics and the influencing factors. The results indicate that: (1) From 2000 to 2020, the carbon emissions in the Yellow River Basin increased continuously, with forests and construction areas being the primary carbon sink and source, respectively. Significant variations existed in carbon emissions in different counties, exhibiting an "east-high, west-low" spatial distribution pattern, while the center of carbon emissions showed a tendency to migrate towards the northwest. (2) The intensity of carbon emissions from land use, along with land use structure, economic development level, and population size all influence carbon emissions, with economic development level having the most significant impact. Adjusting industrial structure can effectively restrain the growth of carbon emissions. The area of land occupied per unit of GDP in the secondary industry consistently inhibits carbon emissions. These research findings hold significant implications for scientifically formulating land use policies and promoting basinwide collaborative emissions reduction initiatives in the Yellow River Basin.
Study on Precipitation Cycle Division in Guanzhong Area Based on Water Quantity Balance
Authors: Li Jiayu , Yan Bowen
Published: August 2024

The basis of the precipitation cycle (hydrological cycle) division method is the climate change of seasons currently. As the global climate changes, it becomes questionable whether the basis of this division method is still sufficient. In this paper, the precipitation series of 25 meteorological stations in Guanzhong area of Shaanxi province from 1970 to 2008 has been taken as the basic data, Total Water Quantity Balance Method is used to divide the annual precipitation cycle, and then, contrast the result with the cycle comes from the wavelet analysis. The study show that: the Total Water Quantity Balance method and wavelet analysis were the consistent on the division of precipitation annual cycle, and the best annual cycle of precipitation in Guanzhong area is changed into 11 months rather than 12 months. From the perspective of the Total Water Quantity Balance method, the annual precipitation cycle in Guanzhong area has been shortened to a certain extent. It is valuable to explore the response change of hydrological law under climate change condition.
Study on the separation of cenospheres from fly ash based on dry separation
Authors: Shen Rui , He Ping , Yoriya Sorachon , Chen Naichao , Wu Jiang , Hu Tianyang , He Kangsai , Cai Qian
Published: August 2024

Cenospheres, as an important value-added product in fly ash, are particles with a hollow spherical structure. Cenospheres are widely used in industry for their unique properties. However, most of the industries use wet separation, which consumes a lot of water and land resources and pollutes the ecological environment, so it is of great significance to study dry separation. In this study, a customized cyclone separator was used to separate cenospheres from fly ash, and the effect of inlet wind speed on the separation efficiency was investigated. The best separation efficiency was achieved at an inlet wind speed of 13 m/s for a fly ash mixture configured with 15% hollow cenospheres, with a Newton's efficiency of 0.687, which is slightly higher than that of the wet method of 0.6. The larger the pore size, the easier the cenospheres could be separated.
Research on lifecycle management of energy consumption and carbon emissions in public buildings
Authors: Guo Lushan , Zhang Kun , Wang Xiaofei
Published: August 2024

As urbanization accelerates, public buildings' energy consumption and carbon emissions increase. This study investigates lifecycle management strategies to enhance energy efficiency and reduce emissions in public buildings. Key contributions include developing a multi-objective optimization model, constructing energy flow-carbon flow diagrams, and creating simulation modules to provide practical and theoretical guidance for sustainable energy management in public buildings. The findings offer valuable insights for policymakers and building professionals aiming to achieve carbon neutrality.
Research on the evaluation and analysis method of green construction of substation project
Authors: Wang Jian , Wang Jiake , Liu Bin , Gu Heng
Published: August 2024

Analyzed the main influencing factors of green construction in substations. Pollutions such as dust, exhaust gas, and sewage were analyzed. And electricity waste and oil consumption from the perspective of energy consumption were analyzed too. Characteristics of green construction data was studied. We established a green degree evaluation classification, and used the higher the score, the darker the green color to indicate the higher the degree of greening. Basic principles and specific calculation methods of cloud models was proposed, and we constructed a green construction evaluation cloud model. Taking the green construction of a certain substation as an example, the degree of green construction could be evaluated well. This methodology could effectively evaluate the green level of substation construction.