Engineering Research Express

Magnetic field sensors are an integral part of many industrial and biomedical applications, and their utilization continues to grow at a high rate. The development is driven both by new use cases and demand like internet of things as well as by new technologies and capabilities like flexible and stretchable devices. Magnetic field sensors exploit different physical principles for their operation, resulting in different specifications with respect to sensitivity, linearity, field range, power consumption, costs etc. In this review, we will focus on solid state magnetic field sensors that enable miniaturization and are suitable for integrated approaches to satisfy the needs of growing application areas like biosensors, ubiquitous sensor networks, wearables, smart things etc. Such applications require a high sensitivity, low power consumption, flexible substrates and miniaturization. Hence, the sensor types covered in this review are Hall Effect, Giant Magnetoresistance, Tunnel Magnetoresistance, Anisotropic Magnetoresistance and Giant Magnetoimpedance.

The objective of this research paper is to design, simulate and compare components of a race car braking system. The Racecar is an FSAE car that is designed around the rules and regulations of the FSAE rulebook, the main aim of this project is to make components lightweight and improve their performance as compared to their OEM counterparts. The braking system involves the mathematical calculation of pedal ratio, brake torque, heat generated in brake discs, and required clamping force using MATLAB to achieve peak deceleration after which these values would be used to design and simulate the components. The paper presents some innovative new ideas applied in an FSAE car and also involves designing techniques like topology optimization which was done using Altair inspire. Finally, all the components were designed in Solidworks, and simulations like Factor of safety, von mises stress, and strain were performed using ANSYS 18.1. The paper also compares the work of other authors as well and explains the differentiating factors between our and their design.

This study employs Direct Metal Laser Sintering (DMLS) technology to investigate surface roughness in stainless steel 316L 3D printing processes. Utilizing the Taguchi method in experimental design, we examine the influence of independent variables—laser power, scan speed, and hatch spacing - on surface roughness quality. Results indicate that laser power has the greatest impact, followed by scan speed and hatch spacing. Notably, both laser power and hatch spacing positively affect surface roughness, while scan speed adversely affects the top surface quality of printed components. This research enhances comprehension of the intricate relationship between process parameters and surface quality in DMLS-based 3D printing, offering insights for optimizing surface roughness in stainless steel 316L applications. The study holds practical significance for enhancing the quality and performance of 3D-printed components across diverse engineering and manufacturing sectors.

Thin-film solar cells are preferable for their cost-effective nature, least use of material, and an optimistic trend in the rise of efficiency. This paper presents a holistic review regarding 3 major types of thin-film solar cells including cadmium telluride (CdTe), copper indium gallium selenide (CIGS), and amorphous silicon (α-Si) from their inception to the best laboratory-developed module. The remarkable evolution, cell configuration, limitations, cell performance, and global market share of each technology are discussed. The reliability, availability of cell materials, and comparison of different properties are equally explored for the corresponding technologies. The emerging solar cell technologies holding some key factors and solutions for future development are also mentioned. The summarized part of this comparative study is targeted to help the readers to decipher possible research scopes considering proper applications and productions of solar cells.

This systematic review focuses on the exploration and advancement of sustainable and eco-friendly polymer composite materials derived from bast fibers. Bast fibers, obtained from the phloem of certain plants like flax, hemp, jute, and kenaf, represent a renewable and environmentally benign resource. Their integration into polymer based composites has gained significant attention due to the growing environmental concerns and the need for sustainable material development. The importance of this study lies in its comprehensive examination of bast fibers as viable alternatives to the synthetic fibers in polymer composite materials. By harnessing the natural strength, light weight, and biodegradability of bast fibers, this review contributes to the creation of materials that are not only environmentally sustainable but also possess enhanced mechanical properties suitable for various industrial and domestic applications.

This study presents an ultrasound speckle suppression method to detect the stones in the human kidney. An initial image is first improved using image enhancement techniques, which are used to change the image's intensities. Next, median filters smooth the picture and eliminate noise. Pre-processed images are segmented using a thresholding technique. The median filter extracts impulsive noise from salt-and-pepper noise. The suggested approach locates stones using location coordinates. Hospital and clinical ultrasound images were used to evaluate the proposed scheme and algorithm. The suggested scheme has been assessed by different performance measuring parameters. Physicians are likely to benefit from the research in terms of clinical diagnosis and educational training. Based on 50 test cases, the proposed plan was correct 96.82% of the time and sensitive 92.16% of the time. Furthermore, the peak signal to noise ratio is 1.82, and the average signal to noise ratio is 1.58, demonstrating the efficacy of the proposed approach.

In last decades, remote sensing technology has rapidly progressed, leading to the development of numerous earth satellites such as Landsat 7, QuickBird, SPOT, Sentinel-2, and IKONOS. These satellites provide multispectral images with a lower spatial resolution and panchromatic images with a higher spatial resolution. However, satellite sensors are unable to capture images with high spatial and spectral resolutions simultaneously due to storage and bandwidth constraints, among other things. Image fusion in remote sensing has emerged as a powerful tool for improving image quality and integrating important features from multiple source images into one, all while maintaining the integrity of critical features. It is especially useful for high-resolution remote sensing applications that need to integrate features from multiple sources and hence a vital pre-processing step for various applications, including medical, computer vision, and satellite imaging. This review initially gives a basic framework for image fusion, followed by statistical analysis and a comprehensive review of various state-of-the-art image fusion methods, where they are classified based on the number of sensors used, processing levels, and type of information being fused. Subsequently, a thorough analysis of STF and pansharpening techniques for remote sensing applications has been covered, where the dataset of the DEIMOS-2 satellite is employed for evaluating various pansharpening methods while MODIS and Landsat images are employed in the spatiotemporal fusion method. A comparative evaluation of several approaches has been carried out to assess the merits and drawbacks of the current approaches. Several real-time applications of remote sensing image fusion have been explored, and current and future directions in fusion research for remote sensing have been discussed, along with the obstacles they present.

Shear sensors are used for measuring shear stress and shear strain in solid bodies when mechanical forces are applied. For the preparation of these sensors, researchers reported innovative materials either alone or in the form of blends, alloys, and composites. Shear sensors are not easily available for purchase, therefore, this review focuses on the working principles of various kinds of shear sensors being explored by researchers. Several technologies and materials are used, such as piezoelectric materials, piezoresistive materials, Fiber Bragg Grating, capacitive sensing, and structural colors. This article also looks at fabrication-based challenges that restrict the commercial use of shear sensors. A variety of shear sensor devices are evaluated for measuring shear stress/strain for many different applications such as health monitoring and biomedical, robotics, and or fracture in materials.

Cutting fluids provide cooling at the cutting tool and on the surface of work piece, lubricate the tool-workpiece interface and evacuate chips from the cutting zone in the machining processes. The primary reason for using cutting fluid is to reduce the temperature at cutting zone and friction wear either through cooling or lubrication. To maximize the efficiency of cutting fluids in machining processes the knowledge of machining conditions and cutting fluid types are critically important. However, misemploy of the cutting fluid and non efficient method of disposal can raise health issues and environmental impact. In this paper, an attempt has been made to provide overview of cutting fluids type, cooling techniques and main alternatives as dry machining, cryogenic cooling, minimum quantity lubrication and hybrid cooling minimizing use of cutting fluids. The inclusion of solid lubricants, nano fluids in lubrication/cooling techniques results in increase in the productivity of the process due to reduction in friction and heat at the cutting zone. The cutting parameters and type of tools utilized by various researchers have been summed up and introduced in this paper to provide useful information to various researcher works.

The medical images of people are important and sensitive and cannot be shared with the public considering privacy measures. Maintaining the confidentiality of the medical image is essential, and leakage of such information can cause great loss. Therefore, the information has to be secured while being transferred through a third party, which can be any network medium. Thus, there is a need for developing a robust encryption algorithm. These algorithms improve the security of the ongoing pictures by compromising the nature of the picture and utilizing complex calculations. Algorithms that work on the nature of the picture by utilizing complex cycles, for example, error diffusion, halftoning, wavelet transform, and dithering, lead to time complexity. Thus, a compact and efficient cryptographic algorithm is proposed with fewer mathematical computations that ensure the secured transmission and reception of medical images through the medium using Significant Visual Cryptography (SVC). In SVC, initially, the quality of the secret images (SI) is improved by using the Error Abatement Technique (EAT). The output of EAT is used to generate random share values, which are then implanted in cover pictures. The shares that are transmitted do not reveal the secret information present in the original image because of the steganography features involved in this technique. The integrated check value (ICV) is calculated over the region of interest (ROI) at the encryption and decryption sides to provide additional security. Quality and security analyses have been carried out to ensure the robustness of the algorithm. The detailed study proved that the proposed algorithm beat the constraints of the current calculations. The concept of checking the integrity value and steganography features enhanced the effectiveness of the algorithm.

This study employs Direct Metal Laser Sintering (DMLS) technology to investigate surface roughness in stainless steel 316L 3D printing processes. Utilizing the Taguchi method in experimental design, we examine the influence of independent variables—laser power, scan speed, and hatch spacing - on surface roughness quality. Results indicate that laser power has the greatest impact, followed by scan speed and hatch spacing. Notably, both laser power and hatch spacing positively affect surface roughness, while scan speed adversely affects the top surface quality of printed components. This research enhances comprehension of the intricate relationship between process parameters and surface quality in DMLS-based 3D printing, offering insights for optimizing surface roughness in stainless steel 316L applications. The study holds practical significance for enhancing the quality and performance of 3D-printed components across diverse engineering and manufacturing sectors.

This study describes the physical, chemical, mechanical as well as morphological characterization of surface modified novel Bauhinia Variegata (BVR) stem fibers. Surface modifications for the fiber are accomplished with bleaching, benzoylation, and alkalization treatments. Using standard test methods, the chemical constituents of BVR fiber are evaluated like α- cellulose 62.5%, hemicellulose 10.8%, lignin18.2% and wax 0.8%. Scanning electron microscopy (SEM) was used to see how different the chemical reactions affect the fiber and SEM images confirmed the enhanced rough surface and existence of voids, along with the subtraction of unusual substances from the fiber surface. In both treated as well as untreated BVR, a Fourier-transform infrared spectroscopy (FTIR) analysis established the presence of cellulose, hemicelluloses, and lignin components. X-ray diffraction test evaluated the crystalline index for treated and raw fiber. The thermogravimetric test provides proof of enhanced thermal sustainability in the BVR upon treating chemically. The increased tensile strength and Young's modulus upon chemical treatment confirm the improvement in the mechanical properties of the BVR fiber. The moisture absorption test revealed that the hydrophilic nature of BVR was reduced after the chemical treatment, promoting greater fiber-matrix adhesion. Presently studied BVR fiber seems to be a good substitute to the harmful man-made fibers for making of bio composites.

This paper presents an efficient approach to detect, diagnose and estimate the severity of failures in various components of bearings in induction motors using vibration signature analysis. This automated method integrates the Fisher Score feature selection method and an efficient hyperparameter tuning model with machine learning models, including Support Vector Machine (SVM), k-Nearest Neighbor (k-NN) and Decision Tree (DT), to accurately classify defects in bearings. This approach ensures accurate classification of bearing defects within less computation time. This work is carried out with vibration signals, recorded from a laboratory experimental setup on Machine Fault Simulator (MFS), focusing on ball bearing with defects in inner race, outer race and ball itself. Time and Frequency domain analysis are employed to compute the features for fault investigation in ball bearings using machine learning models. The computed results demonstrate that the proposed feature selection method with hyperparameter tuning achieved remarkable maximum accuracy among X, Y and XY combinations of datasets, with 97% in DT, 94% in SVM and 95.23% in k-NN models during the frequency domain analysis. Notably, these model accuracies improved to 99.04% in DT, 98% in SVM and 98% in k-NN during further analysis with Fisher Score technique. Consequently, the testing loss using this hyperparameter tuning function remains very low. Overall, this paper compares the results of time and frequency domain analysis and introduces a promising approach for both efficient and accurate fault detection and severity estimation in bearings of induction motors, potentially reducing the need for extensive manpower and sensor usage.

The automotive industry's relentless pursuit of improved safety, performance, and durability has spurred a continuous search for innovative solutions for crucial components like brake discs. These components endure extreme thermal and mechanical stresses, making them highly susceptible to corrosion and wear. Inadequate corrosion resistance and excessive wear of brake disc material during service remain significant concerns, with the latter resulting in brake emissions in the form of dust and particulate matter that pose health risks to humans. As exhaust emission standards grow more stringent, it becomes imperative to address brake disc wear issues while maintaining material braking performance. This paper extensively examines recent brake disc coating advancements specifically designed to combat corrosion and wear challenges. It explores how these protective coatings interact with the broader automotive ecosystem, highlighting their pivotal role in ensuring safer, more resilient, and environmentally responsible vehicles. This paper also evaluates traditional coating technologies and materials alongside emerging alternatives for brake disc applications.

The work primarily focuses on increasing the efficiency of EV drive in electric two-wheeler by working on several aspects, such as modulating the vehicle's design, optimizing the control strategy, and increasing the speed range using a dual-motor approach. The dynamics of electric two-wheeler have been discussed with a mathematical vehicle model and further tuning of several aspects. Besides, this paper also introduces a novel Augmented Teaching and Learning based Optimization (ATLBO) technique designed exclusively to control BLDC motors for the electric two-wheeler vehicle. Besides, the designed technique has been implemented for the widely used commercial e-bike of Hero Company. Most two-wheeler electric motors are mounted on the rear side of the wheel, which has a limited speed range. Therefore, an analysis has been performed to increase the vehicle's speed range using a dual motor, from 45 km hr⁻¹ to 62 km hr⁻¹, proving to be a viable alternative to a single motor generally used in an electric bike. ATLBO technique has been designed against a conventional TLBO to optimize the proportional-integral-derivative (PID) controller for the speed control of a linear brushless DC (BLDC) motor. The proposed method has several advantages, including ease of implementation, a consistent convergence characteristic, and high computational efficiency. Furthermore, the literature has validated the merits of the presented novel control technique. The only disadvantage of using a dual motor is the initial cost, but the overall cost is moderated in the long-term usage for its augmented performance parameters. The performance parameters of the above technique are analyzed against other optimization techniques like conventional Teaching and Learning based optimization (TLBO), Particle Swarm Optimization (PSO). MATLAB/Simulink models the brushless DC motor and implements ATLBO, TLBO, and PSO algorithms. It has been found that the response obtained from ATLBO is comparatively much faster than other optimization techniques, which supports the motor for quick acceleration as well as more efficient in improving the step response characteristics such as rise time, settling time, and steady-state error in the speed control of a linear BLDC motor.

The automotive industry's relentless pursuit of improved safety, performance, and durability has spurred a continuous search for innovative solutions for crucial components like brake discs. These components endure extreme thermal and mechanical stresses, making them highly susceptible to corrosion and wear. Inadequate corrosion resistance and excessive wear of brake disc material during service remain significant concerns, with the latter resulting in brake emissions in the form of dust and particulate matter that pose health risks to humans. As exhaust emission standards grow more stringent, it becomes imperative to address brake disc wear issues while maintaining material braking performance. This paper extensively examines recent brake disc coating advancements specifically designed to combat corrosion and wear challenges. It explores how these protective coatings interact with the broader automotive ecosystem, highlighting their pivotal role in ensuring safer, more resilient, and environmentally responsible vehicles. This paper also evaluates traditional coating technologies and materials alongside emerging alternatives for brake disc applications.

Aluminium (Al)-Lithium (Li) alloys have found widespread applications in aerospace and military domains. Primarily, they are found to have low density, leading to weight savings and several economic considerations. The paper explores the historical development of Al-Li alloys across distinct generations, highlighting their evolution. It also delves into the diverse applications of Al-Li alloys in aerospace and military domains. A concise discussion of the mechanical behaviour and tensile strengths is presented across the first, second, and third generations of Al-Li alloys. This review includes a discussion on microstructural investigation, emphasizing metallurgical factors such as increased efficiency, various precipitate phases, and intergranular features. Weldability and tribological properties of Al-Li alloys, with a specific emphasis on the corrosion aspects of these alloys, are discussed. Furthermore, the review assesses the future development and manufacturing flexibility of Al-Li Metal Matrix Composites. In summary, this comprehensive review consolidates insights into the utilization, evolution, and characteristics of Al-Li Metal Matrix Composites, providing valuable information for researchers and practitioners aiming to enhance the performance of these alloys in aerospace applications.

In recent years, with the rapid growth of communication technology and the necessity for Radiofrequency (RF) front-end devices, the one-port Surface Acoustic Wave Resonator (SAWR) has turned out to be a significant component in the design of a SAW device. Hence, the present study concentrates on and around one-port multi-layer SAW resonators with their applications in communication systems. A comparative and critical analysis of various parameters is explored including temperature coefficient of frequency (TCF), Quality factor (Q-factor), phase velocity, impedance ratio, bandwidth, sensitivity, metallization ratio, etc to discuss the advantages and disadvantages of conventional one-port multi-layer SAW resonator. Through the analysis, future research trends as well as the applications of one port multi-layer SAW resonator are also discussed. The study also explores that the one port multi-layer SAW resonator finds employability in various applications like multimedia and mobile communication, medical field sensing technology, broadband signal processing at high frequencies, etc. Thus, significant, and efficient parameters of the resonator can be easily identified through comparative and critical analysis. The outcome of this study will help the researchers to enhance their work in this specific field in the future.

In last decades, remote sensing technology has rapidly progressed, leading to the development of numerous earth satellites such as Landsat 7, QuickBird, SPOT, Sentinel-2, and IKONOS. These satellites provide multispectral images with a lower spatial resolution and panchromatic images with a higher spatial resolution. However, satellite sensors are unable to capture images with high spatial and spectral resolutions simultaneously due to storage and bandwidth constraints, among other things. Image fusion in remote sensing has emerged as a powerful tool for improving image quality and integrating important features from multiple source images into one, all while maintaining the integrity of critical features. It is especially useful for high-resolution remote sensing applications that need to integrate features from multiple sources and hence a vital pre-processing step for various applications, including medical, computer vision, and satellite imaging. This review initially gives a basic framework for image fusion, followed by statistical analysis and a comprehensive review of various state-of-the-art image fusion methods, where they are classified based on the number of sensors used, processing levels, and type of information being fused. Subsequently, a thorough analysis of STF and pansharpening techniques for remote sensing applications has been covered, where the dataset of the DEIMOS-2 satellite is employed for evaluating various pansharpening methods while MODIS and Landsat images are employed in the spatiotemporal fusion method. A comparative evaluation of several approaches has been carried out to assess the merits and drawbacks of the current approaches. Several real-time applications of remote sensing image fusion have been explored, and current and future directions in fusion research for remote sensing have been discussed, along with the obstacles they present.

The review paper deals with a literature review on buckling analysis by different methods of laminated plates with different types of stiffeners which has been conducted in recent years. Analytical studies, experimental studies, finite element analysis, and other computational methods have been implemented by researchers on the stiffened panels under compression and shear for determination of the buckling behavior of the panel with I-type, blade-type, T-type, and hat-stiffeners. Some literature has been found on the panel with the influence of variation of the stiffener depth for the determination of buckling capacity. Very few literatures, non-linear finite element (FE) have been implemented for the determination of the effect of debonding damage between plate-stiffener of the panel but have not been reported parametric data about the effect of cohesive parameters of plate-stiffener and delamination of plies of the composites stiffened panel for post-buckling analysis. This paper also provides a literature survey based on the buckling performance of the plates with the application of different shapes of stiffeners.

The automotive industry's relentless pursuit of improved safety, performance, and durability has spurred a continuous search for innovative solutions for crucial components like brake discs. These components endure extreme thermal and mechanical stresses, making them highly susceptible to corrosion and wear. Inadequate corrosion resistance and excessive wear of brake disc material during service remain significant concerns, with the latter resulting in brake emissions in the form of dust and particulate matter that pose health risks to humans. As exhaust emission standards grow more stringent, it becomes imperative to address brake disc wear issues while maintaining material braking performance. This paper extensively examines recent brake disc coating advancements specifically designed to combat corrosion and wear challenges. It explores how these protective coatings interact with the broader automotive ecosystem, highlighting their pivotal role in ensuring safer, more resilient, and environmentally responsible vehicles. This paper also evaluates traditional coating technologies and materials alongside emerging alternatives for brake disc applications.

Since the use of the Internet has increased exponentially, numerous organizations, including the financial industry, offer services online. As a result, financial scams are expanding in quantity and complexity worldwide, resulting in massive revenue losses and making digital fraudulent transactions a severe issue. Abnormal attempts and illegal access are instances of these dangers that fraudulent activity detection systems must identify. Machine learning and data mining approaches have been extensively used to address this issue in recent years.
However, these approaches must be enhanced regarding real-time detection speed, tackling enormous amounts of data, and finding undiscovered attack patterns. Consequently, the present study provides a real-time architecture for averting and identifying digital transaction fraud, which relies on the Isolation Forest (IForest) approach and big data analytic tools, including Spark Streaming, sparkling water, Kafka, and PostgreSQL. This architecture seeks to improve present detection strategies by increasing accuracy for detection when considering enormous amounts of data. Two real datasets of online transactional fraud are used to assess the proposed architecture, and the findings are compared to relevant studies. The investigation results showed that IForest performed flawlessly, achieving an accuracy of 0.99 in two datasets.

This study examines a new intelligent control method for a single-link flexible manipulator that addresses backlash and model uncertainty. First, a smooth backlash inverse model is constructed to mitigate backlash nonlinearity. Subsequently, a 'disturbance-like' term is formulated to recharacterize the coupled term composed of external disturbances and model uncertainty. A new adaptive controller is proposed to compensate for the unknown 'disturbance-like' term. Using the proposed control method, the stability of the system is evaluated using the direct Lyapunov theory, ensuring uniform ultimate boundedness. Finally, numerical simulations and experiments are conducted using the Quanser platform. The numerical simulation and experimental results show that the proposed control can ensure a faster convergence rate and effectively reduce actuator input chattering.

Optical sensors, particularly fiber Bragg grating (FBG) sensors have achieved a fast ingress into the fields of medical diagnostic and vital signs monitoring. Wearable smart textiles equipped with FBG sensors are catching huge research attention in different applications for measurement and monitoring of physiological parameters. In this paper, we report a simple technique for remote monitoring of sleep disorder using a smart vest implemented with four FBG stress sensors located at different sides of the vest and free space optics (FSO) transmission system. The sleep disorder of the patient is monitored in real time through shifts in the original Bragg wavelengths of sensors by stress loading during random changes in patient's sleeping postures. The reflected wavelength from a stress loaded sensor at a certain posture is transmitted over 0.5 km long FSO channel towards remote medical center, photodetected, and then can be processed in a PC to record the restlessness in a certain time interval in terms of total number of times sleeping postures are changed, total time spent at a certain posture etc. To correctly detect the stress loaded FBG sensor at the medical center, various parameters of FBG sensors and demultiplexer are carefully adjusted to minimize the power leakages from unloaded sensors that may result into errors in the detection. Maximum dynamic range around 45 dB has been achieved ensuring accurate detection. This study not only provides a cost-efficient and non-intrusive solution for monitoring the sleep disorder of patients but also can be used for real-time monitoring of various other ailments, such as lung, brain, and cardiac diseases in future.

Two niobium elliptical 1.3 GHz superconducting radio frequency (SRF) electron photoinjector cavities were successfully recovered after mechanical inner surface damage. Both cavities had deep imprints in the critical high surface electric field area around the photoelectric cathode position. The lengthy repair procedure, which consists of surface inspection and defect characterization, mechanical polishing and light chemical etching is described in detail. In the process, a new high pressure rinsing (HPR) nozzle system optimized for the special photoinjector geometry was also developed. Subsequent cold RF tests demonstrate complete performance recovery. This is the first time that photoinjector cavities damaged in the high electric-field region could be recovered.

Confirming the pozzolanic activity is crucial to ensure their compatibility and performance in geopolymer composite (GC) applications, as it improves the geopolymerization process and optimizes the strength characteristics of GCs. This work evaluates the pozzolanic properties of Fly ash (FA), Basic Oxygen Furnace (BOF) slag, and Iron Ore Tailings (IOT) for their potential use in the development of Engineered Geopolymer Composites (EGC). IOT partially substitutes fine aggregate, while FA and BOF slag are the major precursors. Pozzolanic properties of the aforementioned materials were assessed through the Frattini, saturated lime test (SLT), and strength activity index (SAI). The Frattini test values recorded were 90, 47, and 30% of CaO removal, denoting their degree of pozzolanicity respectively for BOF Slag, FA, and IOT. In the SLT, the formation of stable calcium silicate hydrates and aluminates are verified by the reaction of the test pozzolans with lime, thereby conforming their pozzolanicity. The results from the Frattini and SAI tests showed a significant correlation, indicating an effective pozzolanicity measure of the test materials. However, the results from the SLT did not align with the outcomes from the Frattini and SAI tests. This contradiction suggests that the SLT is ineffective compared to the other two test methods in measuring the pozzolanic activity of the test materials. The research findings provide valuable insights into the potential usage of these materials (pozzolans) as sustainable building materials in the construction industry.

In demanding applications, maintaining structural integrity in dissimilar welded joints like those between duplex stainless steel and Ni-based superalloys requires achieving the best possible mechanical properties. This work examines the impact of post-weld heat treatment (PWHT) on the mechanical characteristics of joints made via double-sided tungsten inert gas (TIG) welding. The dissimilar welded joint was investigated by exposing it to the PWHT for 12 h at 650 °C. Reducing the negative impact of heat generated by welding on the mechanical characteristics and microstructure of the fusion zone was the main goal. To study for changes in the microstructure before and after PWHT, optical microscopy and scanning electron microscopy methods were used for microstructural analysis. To determine the effect of PWHT on the welded joints, mechanical properties such as tensile strength, toughness, and ductility were also assessed. The mechanical properties showed significantly enhanced characteristics and refined grain structures in the fusion zone.

Optimum efficiency and fault tolerance are the most demanding and challenging issues in the domain of performance and reliability management in cloud computing environments. Optimized resource utilization is a key aspect for yielding efficiency in cloud platforms. Workload balancing through resource sharing is one of the key solutions for attaining performance in cloud environments. In addition, multiple cloud environments join hands to offer performance and fault tolerance through resource sharing. We provide a better and cloud-instances' priority-based efficient load balancing method for collaborative cloud platforms. The recommended efficient load balancing method shortens the waiting timespan and overcomes the starvation problem of low priority instances in intercloud environments. A functional prototype of the recommended load balancing method was deployed on a physical cloud infrastructure which was setup with the OpenStack cloud software on the Fedora Linux operating system. The pilot project execution findings exhibit a reduction in the timespan borne by instances for executing load balancing. This technique is useful for attaining fault tolerance and efficient resource utilization in intracloud and intercloud environments.

Natural and organic-based composite materials are widely used in many industrial applications due to their low cost, easy recyclability, economic feasibility, and ready availability. In this study, a polymer-based composite friction material consisting of Hemp-Colemanite composition (HCFCo) has been developed for the automotive sector to exhibit lower cost, environmentally friendly characteristics, and suitable friction-wear behaviors. For this purpose, three different ratios (%4, %8 and %12) of HCFCo composites were produced using a coating technique called impregnation process with a specially designed device. During the production stage, homogeneity of the composites was ensured, and then the final shape was given by the hot pressing method. Properties such as hardness, density, water and oil absorption, friction coefficient, and specific wear of HCFCo samples were examined. In addition, the microstructures of HCFCo composites were investigated to determine the bonding form between hemp fiber and colemanite. The results obtained revealed that the friction coefficient values decreased with an increase in temperature, while no significant change was observed in hardness and density values. Throughout the entire testing process, the friction coefficients varied between 0.14 and 0.29 on average. It was concluded that the developed fiber-reinforced composite can be reliably used in industrial applications and can contribute significantly to innovations in the literature.

Asphalt is a viscoelastic material which performs to resist rutting, fatigue cracking, and moisture susceptibility under different loading and temperature conditions. The use of innovative and renewable pavement construction materials is inevitable due to high axle loads, rapidly increasing traffic volumes, and varying climatic conditions. This study aims to assess the effect as well as the optimum dosage of paper waste lignin for use in hot mix asphalt (HMA). Lignin from the paper industry with dosage ratios of 5, 10, 15, and 20%, was utilized to study the effect of the addition of lignin to the asphalt binder. Virgin and lignin-modified binder samples, before and after the aging process, were subjected to physical testing through penetration, softening point, ductility, viscosity and specific gravity and rheological characteristics through dynamic shear rheometer (DSR), bending beam rheometer (BBR), and rational viscometer (RV). The fractional composition was assessed through saturates, aromatics, resins and asphaltenes (SARA) fractional composition technique. Statistical analysis was also performed to find correlation of different physical and rheological parameters. Furthermore, based on optimum dosage, the performance of asphalt mixtures was studied against rutting, fatigue cracking, and moisture susceptibility. The results indicated that the addition of lignin has improved the physical properties significantly. The amount of asphaltene decreased and aromatics increased in SARA fractional analysis. Moreover, the Colloidal Instability Index (CII) has also indicated a stable structure of the binder. The rheological characteristics are improved after modification. The asphalt mixture tests revealed that addition of lignin with optimum dosage (10%) has improved the performance against rutting, fatigue cracking and moisture susceptibility. Statistical analysis indicated good co-relation among different physical and rheological parameters. This study concludes that 10% dosage is the optimum dosage that can successfully replace the virgin asphalt binder for performance of hot mix asphalt.