Experimental Analysis Research Articles

Effect of combined additions of Sc, Zr and Ti on hot-cracking resistance and precipitation behaviour in Al-Mg alloy by L-PBF

The request for high-performance aluminum components prompts research into innovative alloys compatible with laser-based additive manufacturing processes, leveraging grain refiners in their composition to mitigate hot-cracking and enhance strength. While the addition of Sc and Zr in Al-Mg alloys has been widely investigated, the high cost and supply risks associated with Sc necessitate reducing its amount and replacing, at least partially, with other inoculants. In this preliminary study, the amount of Sc replaceable with different concentrations of Zr or Ti is evaluated investigating the laser powder bed fusion processability of three powder feedstocks: a pre-alloyed Al-Mg-Zr-Sc powder, a blend of the previous alloy with addition of Zr particles, and a further blend of an alloy depleted of Zr with added Ti particles. The experimental analyses on the laser-processed alloys showed that the standard and the Zr-enriched alloys featured a bimodal microstructure free from cracks with fine equiaxed grains at the edge of the molten pools and coarser grains at their centers. In the alloy variant depleted in Zr with addition of Ti particles a columnar structure was observed and hot-cracks appeared. Thermodynamic simulations of phase formation allowed defining the precipitation kinetics during solidification and direct aging, showing increased precipitation in alloys with higher Zr content, while the presence of Ti resulted in sluggish precipitation. Experimental aging tests demonstrated significant increases in microhardness, with peak values of the modified alloys achieved after 12 h at 375°C.

Medicinal Properties of Crotalaria burhia: A Review

Background: Natural products have a crucial role in the discovery and development of drug molecules. The secondary metabolites derived from the plant have potential therapeutic value and reveal many pharmacological effects. Crotalaria burhia Buchham, a Leguminaceae herb, is mostly present in arid parts of India, Pakistan, China, and Afghanistan. Shinio, Bhip, Bhata, Ghugato, and Ban Sutra are just a few of the names it goes by. It is used to cure gout, eczema, hydrophobia, and inflammation. Plant root porridge is used for typhoid, wounds and cuts, rheumatism, flatulence, earaches, nasal bleeding, and stone problems. The powder form of the plant is used for digestive disorders. The plant has potent pharmacological activity and is also carcinogenic and anticarcinogenic in nature. Various phytoconstituents are present, like tannins, amino acids, alkaloids, steroids, triterpenoids, mucilage, flavonoids, gum, polyphenols, anthraquinones, carbohydrates, glycosides, and saponins. Croburhine is a novel pyrrolizidine alkaloid obtained from it. This review focuses on the existing knowledge of the phytochemistry and pharmacological action of C. burhia, which will provide broad information for a proper assessment of the plant as a medicinal agent. Methods: The experimental analysis and data reported on the species of Crotalaria were reviewed from 2005 to 2022. Various databases were used as article sources, like Medline and Pubmed, and a literature review was done using the keywords Crotalaria burhia, habitat, species, pharmacological action, and traditional uses. Result: On the basis of our perception, we have stated that the species Crotalaria burhia is a golden herb that possesses potent pharmacological activities. It is widely used as a conventional drug for the cure of various diseases, but its active constituents need to be evaluated more for future drug development and pharmacological action. Conclusion: There were a total of 21 research articles about the phytochemical screening of herbs, which showed the presence of different active constituents like alkaloids, tannins, flavonoids, steroids, glycosides, mucilage, gum, polyphenols, carbohydrates, terpenoids, etc., which are responsible for different pharmacological activities like antioxidant, antimicrobial, anti-inflammatory, antinociceptive, antihypertensive, antitumor, and analgesic activity.

Autism spectrum disorder identification with multi-site functional magnetic resonance imaging

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by enduring difficulties in social interaction and communication. People analyzed with ASD may display repetitive behaviors and limited interests. Autism is classified as a spectrum disorder, implying that the symptom intensity might range from mild to severe depending on the individual. To detect ASD in this paper an attribute feature graph approach is designed by using the stastical dependencies features that necessarily accomplish the diagnosis of ASD. In the first phase the features extracted are designed based on the functional magnetic resonance imaging (fMRI) data, in the next-step the attribute feature graph layer learns the features of the node information of various nodes by ASD classification. Further, in the third step, it is employed to independently extract distinguishing features from the functional connectivity matrices of the brain that are derived from fMRI. The custom convolutional neural network (CNN) used in this study is trained on a comprehensive dataset comprising individuals diagnosed with ASD and typically developing individuals. In the fourth stage, a prototype learning is developed to augment the classification performance of the custom-CNN. The experimental analysis further carried out states that the proposed model works efficiently in comparison with the existing system.

Research on vibration fatigue behavior of blade structures based on infrared thermography

In recent years, infrared thermography has been widely used in mechanical testing because of its non-contact, rapidity and high accuracy. In order to explore the advantages of infrared thermography in vibration fatigue monitoring of blade structures, the characterization of the vibration fatigue behavior of blade structures is carried out based on infrared thermography with the validation and assistance of laser vibrometry. Firstly, the numerical simulation and experimental analysis were used to determine the size and location of the maximum stress in blade structures. Afterwards, the linear relationship between the stress and amplitude(σν-A curve) of blade structures was calibrated by laser vibrometry, and thus the S-N curve was fitted. Eventually, the heat dissipation law and crack extension process for vibration fatigue of blade structures was analyzed by infrared thermography, and the fatigue limit of the blade structure was predicted by combining infrared thermography and the Luong bilinear method. It is shown that the heat dissipation law and crack extension process for vibration fatigue of blade structures can be effectively analyzed by infrared thermography. Infrared thermography saves some economic and time costs for fatigue limit prediction, and the method is within 2.6% of the results predicted by the Basquin model. This paper provides a certain reference basis for the research methodology for vibration fatigue behavior of blade structures.

PSDCLS: Parallel simultaneous diffusion–confusion image cryptosystem based on Latin square

Today, due to the unparalleled growth of multimedia data sharing, especially digital images, between users over insecure channels in real-time applications, cryptography algorithms have gained increasing attention for the secure and efficient transmission. In classical chaos-based image cryptosystems, the confusion and diffusion operations are often applied as two separate and independent phases, which threatens the cryptosystem security. To address these problems, in this paper, a fast image cryptosystem based on parallel simultaneous diffusion–confusion strategy has been proposed using Latin squares, called PSDCLS. It consists of three main steps. First, the initial parameters of the Hénon-Sine chaotic map are produced from SHA256 of both the plain image content and the user’s secret key. Second, a chaos-based random Latin square is constructed by employing the chaotic sequence produced through the Hénon-Sine chaotic map. Third, a parallel simultaneous diffusion–confusion scheme is proposed by using Latin square and vectorization technique to overcome the problems of computational complexity and high risk of separable and iterative confusion–diffusion operations in the classical chaos-based image cryptosystems. To analyze and evaluate the security and performance of PSDCLS cryptosystem, we conducted extensive simulations and experiments on various benchmark images. Experimental results and analyses show that PSDCLS achieves excellent scores for information entropy (>7.99), correlation coefficients close to 0, key space (2512), NPCR (>99.60%), UACI (>33.46%). The encryption time for test images of size 512 × 512 and 512×512×3 was around 0.026 and 0.081 s, respectively. Therefore, PSDCLS is highly robust against common cryptographic attacks and serves as a swift cryptosystem for real-time encryption applications. The source code of PSDCLS is accessible at: https://github.com/EbrahimZarei64/PSDCLS.

Experimental and numerical analysis of an asphalt solar collector with a conductive asphalt mixture

Asphalt solar collectors (ASCs) have emerged as a promising renewable energy source. They offer a practical solution for generating renewable energy and thereby reduce the reliance on fossil fuels. In this study, a computational analysis and experimental validation of an ASC with a conductive asphalt mixture were conducted. The ASC that was investigated had 3000 mm long serpentine copper tubes positioned at the center of a 1000 mm ×60 mm ×8 mm sample of hot-mix asphalt. Ten 250 W infrared bulbs installed in two rows served as the simulated heat source of the ASC. The ASC had a water flow in the range of 14–97 L⁄h and solar intensities of 600, 800, and 1000W/m2. The thermal response of the ASC was modeled using the COMSOL Multiphysics 5.6.0.280 heat-transfer module. The experimental results indicted that the efficiency of the ASC was 53.56% or 64.1% with either reference or conductive mixtures, respectively. When a conductive mixture was used in the ASC, its surface temperature decreased by 11.37% when compared to that obtained using the reference mixture. The numerical simulation revealed that the average deviation between the numerical and experimental temperature data of the water that flowed within the ASC tubes was between 6% and 14%. The use of conductive asphalt mix would enhance the thermal performance of ASCs.

Monitoring bridge bearings based on rubber-based composite materials

To improve the real-time monitoring capability of bridge structure safety, intelligent bridge bearings were prepared based on rubber based composite materials. The study selected T4/3-5 intelligent rubber bearings and conducted a systematic experimental analysis on their response characteristics under different loading speeds and holding states. By measuring the displacement and resistance changes of the intelligent bearings under various load conditions, their sensitivity and stability were evaluated. These experiments confirmed that the T4/3-5 intelligent rubber bearings exhibited a total creep deformation of approximately 1 mm and 1.5 mm under loads of 60 kN and 45 kN, respectively. This suggests that the molecular chains reach a relatively stable configuration under high loads and are not prone to further changes. Moreover, the resistance reduction ratio under a load of 60 kN is approximately 0.57, while under a load of 45 kN it is approximately 0.62, indicating that nickel powder particles in the composite material form a more stable conductive network after molecular rearrangement. At different loading rates, the displacement-load and load-resistance curves of the bearings show consistent trends, and the creep and resistance relaxation behaviors exhibit certain regularity with the concentration of load size. Through the analysis of these data, the study elucidated the resistance change mechanism in the bearings and validated the feasibility of intelligent bearings as a real-time load monitoring tool.

Experimental analysis for comparison of wireless transmission technologies: Wi-Fi, Bluetooth, ZigBee and LoRa for mobile multi-robot in hostile sites

This research paper conducts a thorough comparison of four prominent transmission technologies suitable for mobile robots operating in challenging environments. Emphasizing key factors such as signal strength, noise resistance, and data transfer efficiency, the study aims to identify the optimal communication solution in hostile conditions. The exploration delves into the intricacies of received signal strength indication (RSSI) and signal-to-noise ratio (SNR), revealing distinctive traits and trade-offs among the technologies. Navigating through the complexities of frequency bands, modulation types, and communication topologies, the paper examines the impact of obstacles, energy consumption dynamics, and potential real-world applications. Beyond contributing to the fields of robotics and communication, the study offers practical insights for stakeholders seeking resilient and efficient transmission methods for mobile robotic applications. Advocating for long range (LoRa) as the preferred transmission technology in hostile environments, the paper highlights its unmatched immunity to noise, stability, and minimal energy consumption. These findings provide valuable guidance for technology choices in collaborative mobile robot operations under challenging conditions. This research sets the stage for future developments in robotic communication, underscoring the crucial role of selecting the right transmission means for mission-critical applications in hostile environments.

Exploring the Sound Absorption and Sound Insulation Capabilities of Natural Fiber Composites: Nipa Palm Peduncle Fiber

This study investigates the acoustic properties of nipa palm peduncle fiber (NPPF) composites, a promising natural fiber with a tensile strength of 277 MPa, a yield strength of 49.0 MPa, and a Young’s modulus of 12.0 GPa. We focus on understanding how NPPF’s physical characteristics influence its sound absorption and insulation capabilities. Through experimental analysis, we found that the sample density directly affects the sound absorption coefficient (SAC) and transmission loss (TL), with denser samples exhibiting better noise reduction. Using the Johnson-Champoux-Allard-Lafarge (JCAL) model, we correlated these acoustic properties with the material’s non-acoustic parameters including flow resistivity (σ), open porosity (), tortuosity (α∞), viscous (Λ) and thermal (Λ' ) characteristic lengths along with static thermal permeability (). The results validate the JCAL model’s predictions, offering insights into designing effective, eco-friendly acoustic materials. This study not only highlights NPPF composites’ notable acoustic performance but also underlines their potential for contributing to sustainable development.

Connection between MiR-490 and CCND1 and GSK3β genes play an effective role in Wnt signaling pathway in colorectal cancer.

The Wnt signaling pathway is identified as one of the main disrupted pathways in Colorectal cancer (CRC). Results from studies focusing on this route will aid greatly in the detection and treatment of CRC. MicroRNAs (MiRs), particularly MiR-490, has emerged as key regulator of gene expression in biological pathways, making it an attractive research target. This is notably true for the Wnt signaling pathway, which is usually disordered in CRC tissues. This study aimed to evaluate the expression level of MiR-490 isomiRs and determine some of its key target genes involved in Wnt signaling pathway in CRC tissues and cell lines, based on experimental and bioinformatics analysis. Elevated expression of GSK3β and CCND1 indicate that the progression of CRC tumor is associated with the inhibitory effect of MiR-490 isomiRs on the Wnt/β-catenin signaling pathway. This finding was supported by the observation of a positive connection between the expression pattern of miR-490-3p and 5p, and CCND1 and GSK3β in CRC. The valuable results of this study provide a means of identifying biomarkers with the potential to either inhibit or activate CRC cellular pathways.

Experimental investigation and thermodynamic analysis of application of hybrid nanofluid in a parabolic solar trough collector.

In this research, thermal modeling has been done to investigate the effect of nanofluid on the performance of the linear parabolic collector. Therminol vapor/liquid phase fluid (VP-1) has been used as a base fluid; iron oxide nanoparticles have been used to produce mono-nanofluid; and iron oxide multi-walled carbon nanotubes nanocomposite has been used as nanoparticles to produce hybrid nanofluid. The fluid flow inside the absorber tube of the collector is assumed to be turbulent. The results show that when hybrid nanofluid and mono-nanofluid are used, the energy and exergy efficiencies of the collector are higher than those for the conditions of using the base fluid, but their amount is slightly lower with the use of hybrid nanofluid than when the working fluid is mono-nanofluid. According to the obtained results, the highest energy efficiency of the linear parabolic collector using nanofluid and mono-nanofluid is 70.2% and 70.4%, respectively, and the highest exergy efficiency is 35.7% and 35.9%, respectively. Despite this, the friction coefficient of mono-nanofluid compared to hybrid nanofluid was obtained on average about 9% higher. The results showed that the criterion for evaluating the performance of the collector (hydrodynamic thermal efficiency) when hybrid nanofluid is used is more than when mono-nanofluid is used.

Network architecture for single image super‐resolution: A comprehensive review and comparison

AbstractSingle image super‐resolution (SISR) is a promising research direction in computer vision and image processing for improving the visual perception of low‐quality images. In recent years, deep learning algorithms have driven tremendous development in SR, and SR methods based on various network architectures have significantly improved the quality of reconstructed images. Although there has been a large amount of reviews focusing on SISR, few studies have focused specifically on network architectures for SISR. This paper aims to provide a systematic overview of the design ideas of SISR using multiple architectures, including Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Transformer, and Diffusion model. In addition, an experimental analysis and comparison of state‐of‐the‐art SR algorithms have been performed on publicly available quantitative and qualitative datasets. Finally, some future directions are discussed that may help other community researchers.

An experimental analysis on thermal performance of interloping threaded cooling channels in injection mold cavity

An experimental analysis on thermal performance of interloping threaded cooling channels in injection mold cavity

Experiment and simulation study on the functional fatigue of shape memory alloy beam actuators

The functional fatigue behavior of shape memory alloy (SMA) beam actuators is gaining importance as their utilization in engineering applications becomes more widespread. However, research on the functional fatigue behavior of SMA beam actuators under bending conditions is not as extensive as that on SMA wires. In this paper, an experimental study and theoretical analysis of the functional fatigue behavior of SMA beam actuators were conducted. A measuring method for bending deflection and an automatic thermal cyclic test bench was designed. A series of functional fatigue tests were conducted on SMA beam actuators under different bias load conditions and the functional fatigue patterns were obtained. The material damage factor is defined and calculated through specimen tests. By incorporating the damage factor to modify the existing constitutive model, a model considering functional fatigue and tension-compression asymmetry is obtained. Finite element analysis (FEA) is performed based on this modified model to simulate the actuating performance of SMA beam actuators and to compute the deflection at different numbers of cycles. Additionally, a small parameter study on the actuator shape is conducted using FEA. By comparing the FEA results with functional fatigue experimental data, the effectiveness of the modified model is validated, demonstrating its capability to describe functional fatigue and predict actuator lifespan.

Is Thomas Tuchel wrong? Evaluation of hexagonal shaped drills based on machine learning and position data

As a variation of small-sided games (SSGs), Thomas Tuchel's hexagonal shaped possession drills attracted a lot of attention in coaches’ soccer education. Changing certain variables (e.g. pitch size) is one traditional approach to provide an optimal stimulus for a specific training goal. Therefore, the presented field study investigated whether hexagonal shaped drills show changes in tactical key performance indicators (KPIs) using positional data in a controlled experimental setting. Data were collected using player tracking systems (1 Hz) in 5 versus 5 SSGs in both the full-size pitch and pitch with cut-off corners condition. At match-related level, trial duration and outcome were examined. At player-related level, the tactical KPIs effective playing space (EPS), length-per-width ratio, space control and overplayed defenders were analyzed. The results show significant differences in length-per-width ratio (attacking team), the EPS and space control (30m-zone). However, it could not be confirmed that hexagonal shaped drills are played more vertically and faster toward the goal than on a normal pitch, as there were no changes in trial duration, outcome or overplayed defenders. Nevertheless, an experimental positional data analysis paradigm is a useful approach to investigate tactical principles in high-level professional soccer.

Ensuring Privacy and Recovery: Public Key Encryption for Secure Data De-Duplication with Keyword Search

In the current era of information explosion, user’s demand for data storage is increasing, and data on the cloud has become the first choice of users and enterprises. Clous storage facilitates the backup and sharing of data, efficiently reducing user’s storage expenses. The duplicate data of different users is stored multiple times, leading to a sudden decrease in the storage utilization of cloud servers. Data stored in plaintext form can directly remove duplicate data, while cloud servers are semi-trusted and usually need to achieve secure de-duplication and recover data in cipher text for different users, and relationship of trapdoor are equal in cipher text to achieve secure de-duplication. The proposed scheme is secure and efficient through security analysis and experimental simulation analysis. Keywords: Data De-duplication, Mobile Edge Computing, Authentication, Security, Cryptographic Techniques, Data Integrity.

Experimental and numerical analysis of seismic performance of jacket platforms subjected to onshore and offshore earthquakes

Offshore platforms located in seismically active areas may be subjected to different seismic effects during service. The seismic performance of offshore platforms under different earthquakes was studied using shaking table tests and finite element analysis (FEA). The dynamic properties, acceleration, displacement and strain responses of the scale model under near-field, far-field and offshore earthquakes were studied. On this basis, more consideration was given to soil-pile-structure interactions (SPSIs), and this finite element (FE) model was analyzed for seismic fragility using incremental dynamic analysis (IDA). By combining the results of the tests and FEA, it was found that the dynamic response of the platform was significantly larger under offshore earthquakes than under onshore earthquakes. The collapse resistance of offshore platform under offshore earthquakes was inferior to that under onshore earthquakes. Therefore, seismic performance assessment of long-period offshore platforms based on onshore earthquakes may overestimate its seismic capacity and pose potential risks to platforms in service.

Curvature-mediated rapid extravasation and penetration of nanoparticles against interstitial fluid pressure for improved drug delivery

Elevated interstitial fluid pressure (IFP) within pathological tissues (e.g., tumors, obstructed kidneys, and cirrhotic livers) creates a significant hindrance to the transport of nanomedicine, ultimately impairing the therapeutic efficiency. Among these tissues, solid tumors present the most challenging scenario. While several strategies through reducing tumor IFP have been devised to enhance nanoparticle delivery, few approaches focus on modulating the intrinsic properties of nanoparticles to effectively counteract IFP during extravasation and penetration, which are precisely the stages obstructed by elevated IFP. Herein, we propose an innovative solution by engineering nanoparticles with a fusiform shape of high curvature, enabling efficient surmounting of IFP barriers during extravasation and penetration within tumor tissues. Through experimental and theoretical analyses, we demonstrate that the elongated nanoparticles with the highest mean curvature outperform spherical and rod-shaped counterparts against elevated IFP, leading to superior intratumoral accumulation and antitumor efficacy. Super-resolution microscopy and molecular dynamics simulations uncover the underlying mechanisms in which the high curvature contributes to diminished drag force in surmounting high-pressure differentials during extravasation. Simultaneously, the facilitated rotational movement augments the hopping frequency during penetration. This study effectively addresses the limitations posed by high-pressure impediments, uncovers the mutual interactions between the physical properties of NPs and their environment, and presents a promising avenue for advancing cancer treatment through nanomedicine.

Experimental evaluation of tribo-performances of bump foil journal bearing with different materials of foil

Abstract In this paper, the bump-type foil journal bearings is developed with five different foil materials: Inconel X750 (IN-X750), Stainless steel 316 (SS316), Beryllium copper (BC), Spring steel EN42J (SP EN42J) and Phosphor bronze (PB). To develop the bump-type FJB, a complete fabrication process is described in details along with the design of fixtures. This fabrication process includes various machining operations such as milling, rolling, cutting, threading, forming etc. The forming load versus deflection curve is obtained for all the foil materials with the metal forming operation. After fabricating it, the load-deflection test is performed to evaluate the structural characteristics of these developed bump-type foil bearings. Further, the experiment analysis of bump-type foil bearings is performed to evaluate its tribological characteristics such as wear rate and surface roughness. Moreover, the rubbing temperature of bump-type FJB is also captured by using the thermal imager. From these study, it is observed that the metal forming operation is the most challenging step in the fabrication of bump-type foil bearings. The brittleness behavior of BC foil increases after the heat treatment. The experimental results show that the minimum wear rate and maximum surface roughness of bump-type FJB is found for the IN-X750 foil due to its higher toughness and hardness. The maximum spring-back effect in bump-type FJB is found for the Spring steel EN42J. These results demonstrate that the maximum structural damping and stiffness of bump-type FJB is found for the Phosphor bronze and Inconel-X750 respectively.

Theoretical and Experimental Analysis of the Effect of Vaporization Heat on the Interaction between Laser and Biological Tissue

A theoretical model, based on the classical Pennes’ bioheat theory, incorporating various boundary conditions, was established and compared to analyze the influence of the latent heat of vaporization via simulation. The aim was to elucidate the extent of its influence. The thermal damage rate, governed by the vaporization heat of biological tissue, is introduced as a key factor. Functional relationships between temperature and incident laser power, spatial position, and time are derived from the classical Pennes’ bioheat equation. According to the theoretical model, numerical simulations and experimental validations are conducted using Comsol Multiphysics 6.0, considering the tissue latent heat of vaporization. The model incorporating the latent heat of vaporization proved more suitable for analyzing the interactions between laser and biological tissue, evident from the degree of fit between simulated and experimental data. The minimum deviations between theoretical and experimental observations were determined to be 2.43% and 5.11% in temperature and thermal damage, respectively. Furthermore, this model can be extended to facilitate the theoretical analysis of the impact of vaporization heat from different primary tissue components on laser-tissue interaction.