Applied Mechanics and Materials

The accurate estimation of thermal contact conductance (TCC) at material contact interfaces is cru cial for determining the temperature distribution in a system, particularly in vacuum conditions such as outer space. Improper estimates of TCC, especially in vacuum environments, may result in under design of thermal management systems resulting in the formation of hot spots, leading to material and system failure. This study introduces two inverse techniques for determining the TCC at the contact interface. The validity of the proposed inverse methods is established by comparing TCC values at the interface with those obtained from experiments performed using the ASTM D5470-17 standard, which is applicable under the assumption of one-dimensional heat transfer. Experiments are meticu lously conducted to ensure the validity of the one-dimensional heat transfer assumption. The variation observed in the TCC estimates obtained from experiments and the inverse methodology is discussed to establish the validity of the proposed inverse techniques. Consequently, these techniques offer ap plicability in scenarios where one-dimensional heat transfer is compromised due to factors such as asperity distribution, vacuum conditions, or low thermal conductivity of the specimen.

High-performance volume holographic grating (VHG) is an important coupling element for a holographic waveguide system. Small angular bandwidth and low diffraction efficiency restrict the applications of VHGs. Based on asymmetrical recording, a reflection VHG with large angular bandwidth and high diffraction efficiency are designed and prepared. The relationship between the recording angles and the diffraction efficiency is discussed first and several combinations of the recording angles are found. Then the relationship between the recording angles and the angular bandwidth is further analyzed, which could obtain the optimal recording setup. The experimental results show that when the incident angle of the reference light and signal light is 10° and 59°, the angular bandwidth of the fabricated VHG reaches 25° and the diffraction efficiency is 90%. However, the wavelength shift happens. The recording angle is modified to improve wavelength shift. The method proposed in this paper could help design a VHG with large angular bandwidth and high diffraction efficiency.

The micro-perforated panel (MPP) absorber has provided better noise control solutions in the medium to high-frequency range than the traditional fibrous porous absorbers regarding absorption characteristics and durable features in challenging environments. But, the low-frequency performance of the MPP absorber with a constrained air back cavity is not satisfactory. Researchers in the last decades proposed many solutions to enhance the acoustic performance of the absorbers, but the cost and complexities involved limited their wide applications. In this paper, the back cavity is partitioned to have a multi-cavities arrangement behind the MPP, which facilitates the multiple Helmholtz resonator (HR) effects. Maa model for the MPP absorber is modified to accommodate multiple HR effects and find the acoustic impedance and sound absorption coefficient of the proposed absorber. The individual absorption peaks of the absorber can be tuned along the frequency axis to have wideband absorption characteristics. 3D printed MPP sample with a multi-cavities structure is mounted in two microphone impedance tube setup to validate the predicted results.

The aircraft's navigation system routinely makes use of the Global Navigation Satellite System (GNSS) during numerous phases of a flight. A primary concern is Ionospheric Gradients, which might impact the global positioning system's positional accuracy. Data from a single GNSS reference station is required for Ionospheric Spatial Gradient estimation using the well-known Time-Step Method. Temporal decorrelation faults are one type of inaccuracy that accompany the Time-Step Method. Conversely, the Station-Pair technique uses two GNSS reference stations that are closely separated to estimate the Spatial Gradient. When GNSS stations are far apart, the Station-Pair Method is ineffective in determining delay gradients in ionospheric plasma at short baselines. An attractive alternative is Satellite-Pair Method which uses observations from a single GNSS reference station. Satellite-Pair approach compares the Ionospheric delays of two satellites that are being monitored by the same receiver at the same time. GNSS data for the year of January to December 2021 was obtained from the mid latitude stations p502 (Imperial County, California) with Geographical Latitude and Graphical Longitude 32°58'55.2"N and 115°25'19.2"W and p509 (Holtville, California) with Geographical Latitude and Graphical Longitude 32°48'40.18"N and 115°22'48.95"W located in California, USA. The maximum Ionospheric Spatial Gradient for disturbed day (15 June 2021) using Satellite-Pair Method is found to be 4.6047 mm/100km, whereas for Existing Time-Step and Station-Pair Methods are 2.2089 mm/100km and 1.8859 mm/100km.The Spatial Gradients are found to be occurred mostly between 2000hrs to 2200hrs UT.

In the recent era- very frequently people come across health issues due to consumption of poor-quality food items- which leads to issues such as food poisoning, vomiting, diarrhea, etc., For a full development of fruits and vegetables, all the nutrients are necessary during its growth. But due to circumstances like soil defects, infections, water scarcity, waterlogging, etc., the vegetables & fruits gets infected with some diseases. So there arises a necessity of a system which inspects for any presence of disease in fruits & vegetables, with reduced manual intervention. This paper provides a detailed overview of a system developed using the Python programming language. Its aim is to recognize and classify various fruits and vegetables, while also identifying any diseases affecting them and determining the specific type of infection. In order to recognize the details accurately, the system is designed to use convolutional neural networks (CNN) and the results are displayed using computer vision techniques. The analysis, implementation, and future improvements of the proposed system are briefed in this paper. For this, we have used Anaconda navigator software (Jupyter notebook, IDLE).

Ceiling cassette air-conditioning units play a pivotal role in the HVAC industry, renowned for their high efficiency, especially in high-rise buildings. However, the routine maintenance of these units poses significant challenges. The current methods are labor-intensive, time-consuming, and wasteful of water, leading to adverse effects on workers' health due to chemical exposure and the physical strain of manual cleaning. In response, this research proposes an innovative solution leveraging Arduino, high-pressure water nozzles, and electronic components to revolutionize maintenance procedures. By automating cleaning processes, this system aims to reduce both the time required for servicing and the physical exertion demanded from workers while also minimizing water wastage and eliminating exposure to harmful chemicals. This study comprehensively evaluates the effectiveness of this technological intervention against conventional methods, highlighting its potential to not only optimize maintenance efficiency but also enhance worker safety and well-being.

This article focuses on the development and testing of a sensor-based motorcycle restraint system equipped with an automated braking mechanism. The system integrates ultrasonic sensors, a DC linear motor, and an Arduino microcontroller to enhance motorcycle safety by detecting obstacles and applying brakes automatically. A prototype was constructed using a wooden frame and bicycle wheels to emulate the motorcycle's dynamics. The braking system utilized a genuine motorcycle drum brake, and the DC linear motor was linked to activate the brake lever based on sensor feedback. LED strips and a buzzer provided visual and audible warnings, indicating the presence and proximity of obstacles. The system was tested under various conditions to evaluate its responsiveness, accuracy, and dependability. The findings revealed that the ultrasonic sensors provided precise distance measurements, allowing for a timely response in obstacle detection scenarios. The automatic braking mechanism demonstrated a 65% reduction in reaction time compared to manual braking, improving rider safety significantly. The system also managed to reduce the braking distance at speeds of 50 km/h, demonstrating its efficacy in emergency situations. Data collected during prototype testing indicated that the system effectively engaged the brake within a 10 cm detection range, issued appropriate warnings, and accurately monitored brake wear. Despite some limitations, such as environmental sensitivity and the prototype's use of simplified materials, the research underscores the system's potential to enhance motorcycle safety. Future recommendations include improving sensor reliability in adverse weather conditions, upgrading the prototype to mimic full-scale motorcycle dynamics, and incorporating additional features like traction control and rider-assist technology.

Single-event and multi-bit effects are the result of radiation and ionized particles in extreme settings like space, which can lead to random failures on any electronic component. To keep the functionality of the device unaltered, these must be reduced. FPGA plays a vital role in satellite and aerospace applications in which dynamic reconfiguration essential. Cascaded Integration Comb (CIC) filters are mostly utilized in multidata signal processing and satellite communication systems as low pass filters in rate converter modules. The configuration memory of FPGA used to design CIC filter is affected with soft errors with single and multi-bit due to high radiation in higher altitude and different environment regions. The methods like triple modular redundancy (TMR) is very effective in overcoming single event transients and single-event upsets, but incur area three times of the original module. Scrubbing is a serial process method that goes over each word in memory in search of mistakes that need to be fixed. It entails a non-negligible Time to Detect (TTD) prior to repair, in which time further functionality could happen parallely and jeopardize the system. Thus, effective multi-bit error detection correction of configuration memory in FPGA is essential in maintaining the application to work for an extended time. In this research, built-in multi-bit error correction for FPGA configuration memory is proposed. The proposed work can replace time consuming scrubbing process and high area utilizing TMR for error tolerant design. To safeguard FPGA, a multi-bit error detection and correction system is performed by using multi dimensional parity with minimum area overhead. Furthermore, the suggested method can identify and rectify error when triggered by an interrupt manager reducing time to detect (TTD).

This study investigates the drying kinetics of Irish potato slices using an Arduino controlled convective heat dryer. The experiment examines drying temperatures of 60, 65, 70, and 75°C, coupled with potato slice thicknesses of 3 and 5 mm. The drying process is crucial in preserving food products and extending their shelf life. Understanding the drying kinetics of potato slices under different conditions is essential for optimizing the drying process and maintaining product quality. The experimental setup allows for precise control of drying parameters, facilitating accurate data collection. The research aims to analyze the drying characteristics, including drying rate, moisture content, and drying time, at various temperature and thickness combinations. From the mathematical models obtained, it is evident that correlation coefficients closest to unity is at 70°C for chip thickness of 3 mm whereas the correlation coefficients closest to unity is at 60°C for chip thickness of 5 mm. Also, it is clearly observed that the efficiency of the system is highest with chip thickness of 3 mm dried at 70°C and performance evaluation results indicate that dryer efficiency is contingent on both temperature and thickness of the chips. These findings contribute to enhancing the efficiency and effectiveness of convective heat drying methods for potato slices, offering insights into temperature and thickness effects on the drying process. This study provides valuable information for food processing industries seeking to improve drying techniques for potato products.

Multipath interference poses a significant challenge in satellite-based navigation systems, including NAVIC (Navigation with Indian Constellation), degrading the accuracy of position estimates. This study proposes a comprehensive approach to address multipath errors in NavIC receivers, combining multipath error calculation using the code minus carrier method with multipath reduction through mode decomposition techniques EMD- empirical mode decomposition, VMD-variational mode decomposition, and SVMD-successive variational mode decomposition. Data was collected from a NavIC receiver located at KLEF University in Guntur, India with latitude 16.44 N, and longitude 80.62 E during the period from April 12th to 14th, 2017. Initially, multipath errors are calculated by subtracting NavIC carrier phase measurements from code phase measurements, providing insights into the magnitude of multipath interference. Subsequently, the received signal is decomposed using EMD, VMD, and SVMD to extract intrinsic modes or oscillatory components representing different signal characteristics. The direct signal is reconstructed by selectively filtering or removing multipath-related modes, reducing multipath interference. To evaluate the effectiveness of each decomposition method, the SDE (standard deviation error) of the reconstructed multipath signal is computed. The decomposition method yielding the lowest SDE is identified as the optimal approach for multipath reduction in NavIC receivers. By integrating the code minus carrier method with mode decomposition techniques, significant enhancements in navigation performance can be achieved, facilitating reliable and precise positioning for various applications.

Vehicle theft is a major issue, underscoring the shortcomings of conventional security systems that frequently depend on expensive and sophisticated sensors. In order to solve this problem, a smart car security system that combines GPS and GSM technology with biometric fingerprint authentication on an affordable Arduino-based platform is created. The main goal is to improve car security by using fingerprint recognition, which uses distinct and difficult-to-copy biometric data, to guarantee that only authorized individuals may access the vehicle. The technology offers a high degree of security by prohibiting unauthorized people from entering the car using fingerprint authentication. Moreover, the system makes use of GSM technology to provide instantaneous notifications in the case of unlawful entry attempts and to allow real-time communication between the owner and the car. The owner may act quickly to safeguard their car thanks to this instant notice. The precise tracking capabilities provided by GPS technology further improve the security framework and are crucial for the prompt recovery of stolen cars. The owner may feel secure knowing that their vehicle's position is always tracked thanks to this extensive tracking technology. The main focus of the issue statement is the requirement for an inexpensive, dependable, and easy-to-use vehicle security system that can overcome the shortcomings of traditional systems. Many car owners are unable to use traditional systems since they are frequently costly and complicated. Using GPS modules for position tracking, GSM modules for communication, and fingerprint sensors for identification, the system is designed and implemented according to the approach. This method offers a flexible solution that may be extensively used while also ensuring high security and system adaptability to different vehicle kinds. This all-encompassing strategy seeks to lower theft rates, improve owner happiness, and offer a strong security framework that can be customized to fit different kinds of vehicles.

Mechanical fatigue is an essential phenomenon that occurs when the structures are exposed to dynamic, fluctuating loadings. Especially automotive components are regularly exposed to random vibration loadings. Vibration fatigue failures may arise even in components that meet static requirements and are stable and robust, because of dynamic and fluctuating loadings. The primary focus of this study is the research of the vibration fatigue. Hence, in addition to the analyses, the tests are conducted. In order to study the analyses and tests, aluminum cross-section beams are designed and manufactured. The notched sections added to the beam geometry to acquire a more distinct fatigue life compared to other parts of the beams. The results obtained from the experimental tests are used to correlate the effect of notch parameters on fatigue life.

Objective: Designing an effective multiplier assists in enhancing microprocessor system performance and complex digital signal processing. The main objective of this work is to design a 16 × 16 Wallace structure multiplier with a parallel prefix adder and evaluate the design's area, power performance, and utilization of resources using three distinct architectures: pipeline, wave pipeline, and hybrid pipeline. Methods: The 16 × 16 Wallace tree multiplier is designed using a parallel prefix adder in the Verilog HDL environment. The Wallace tree multiplier is integrated with a 3-tap FIR filter, and performances are evaluated through a distinct architecture by applying an ECG signal. It is suggested to use a hybrid wave-pipeline multiplier architecture to increase the Wallace tree multiplier's speed and reduce the delay. Delay optimization: In a hybrid pipelining system, the clock duration is relative to the maximum performance difference, whereas in a standard pipeline method, it is comparative to the greatest delay. In the hybrid pipeline multiplier, the last two rows of the partial products are added by parallel prefix adders (PPAs). To lower the delay, the hybrid multiplier uses the Han-Carlson adder for addition. Findings: The hybrid multiplier is executed in the FIR filter for ECG denoising in order to validate its performance. Xilinx ISE is used to synthesize the multiplier structures, whereas Verilog HDL is used for design. Comparing the suggested hybrid design to traditional pipelined designs, the outcome demonstrates that performance is increased while resource use and power optimization are reduced. Novelty: In this work, the hybrid pipeline approach has been applied to the existing Wallace multiplier architecture, and it offers better results in terms of power, area, and delay. The results indicate that the proposed hybrid design outperforms compared to traditional pipelined designs, achieving 48.83% improved delayed performance along with reduced resource usage and power consumption.

The vibration response of laminated sandwich beams, with a core layer filled with various foam materials, referred to as Foam-based Sandwich Laminated Composite (FSLC) beams, has been studied. First, to precisely capture the varying material properties across the thickness of the sandwich beams, a modified layerwise displacement theory was employed. This approach addresses the inhomogeneity of the foam material in the core, yielding more accurate results than conventional classical laminated plate theories typically used for analyzing laminated composite structures. Secondly, to assess the impact of foam properties on dynamic behavior, FSLC beams incorporating three distinct types of foam have been analyzed. Thirdly, a proof-of-concept experimental test was conducted to demonstrate the functionality of the proposed model under dynamic loading conditions. The natural frequencies and damping coefficients of the FSLC beams have been determined using the modified layerwise theory. The dynamic response of the FSLC beams under impulse loading has also been analyzed. It was observed that the addition of foam in the core layer enhances the damping properties of the sandwich beam by approximately ten percent while reducing the natural frequencies by approximately five percent under all types of loading considered.

The primary focus of this research is to investigate the eigen values and strain energy release rate (SERR) of delaminated adhesively bonded single lap joint (SLJ). To achieve this, the study utilizes finite element analysis (FEA) to calculate eigenvalues for the adhesively bonded joints. These predictions are then compared with published data to validate the accuracy of the FEA model. Experimental work is also conducted on intact and delaminated bonded joints to further verify the FEA model reliability. Furthermore, the virtual crack closure technique (VCCT) in ABAQUS software was used to determine SERR values around the delamination edge. Simulation solutions are obtained for various overlapping lengths (e.g., 25, 30, 35, and 40 mm) to predict the natural frequency under different boundary conditions, bond thickness ratios (a/h), and delamination shapes. Similarly, changes in the lamination scheme are considered to predict SERR values. It has been noted that the natural frequency response decreases with increase in bond thickness ratio. Furthermore, a higher number of end restrictions contribute to improved outcomes. There is no significant impact of delamination shape on the natural frequency response. Notably, the cross-ply lamination sequence exhibits higher SERR values around the delamination edge than other sequences.

Heusler alloys are intermetallic compounds formed in two combinations: Full-Heusler (X2YZ) and Half-Heusler (XYZ). X and Y can be any transition element, and Z belongs to the main group. This shows that there can be a huge variation in the combinations, leading to various properties and applications. We aimed at predicting the combination leading to shape memory properties using machine learning tools and then synthesizing the same. The predictions are done by training the tool with input data. We employed the lattice strain, valence electron concentration ratio, mechanical stress, difference in entropy, and saturation magnetization as input features. The correlation between the martensitic and austenitic temperature was evaluated in terms of regression metrics. The random forest and decision tree modeling were executed. Test scores were obtained using frequency ordering, PCA, linear regression, and correlation matrix to forecast magnetically controlled shape memory effect. The silhouette score matched the transition temperature at which the material showed shape memory behavior. Additionally, from 70% of the training data, a combination of Iron (Fe), Nickel (Ni), and Aluminum (Al) as Full Heusler alloys stimulated the algorithms in gaining the accuracy of predictive modeling by minimizing the error. Through DFT-based bandgap and density of states calculations, the Fe2NiAl Heusler compound is hypothesized to behave as a half-metallic ferromagnet by considering the atomic number, the number of valence electrons, and the local magnetic moment. The experimental validation will be done along with magnetization studies, magneto-transport, and magneto-caloric measurements.

Beams find extensive applications in Nanoelectromechanical systems (NEMS) and Microelectromechanical systems (MEMS). The mechanical characteristics of these microstructures are significantly influenced by both their inherent microstructure and the forces acting at the micro/nano scales. Classical continuum theories fall short in capturing these small-scale effects due to the absence of a length scale parameter in their constitutive relations. To address this limitation, the existing literature primarily relies on the stress gradient nonlocal approach, which, however, has been found flawed and its universal applicability questioned in various scenarios. Therefore, the authors have endeavored to emphasize the strain gradient nonlocal approach, which has been relatively less explored. In this study, carbon nanotubes are modeled using the isotropic Timoshenko beam theory. To introduce the small-scale size effect into the model, the second-order negative strain gradient theory (NSGT) is employed. The Euler-Lagrange differential equations of motion and their corresponding boundary conditions are derived through Hamilton's principle. Analytical solutions are developed for static bending under uniformly distributed transverse load and free vibration problems using Navier's approach. Mathematical results are presented to validate the proposed solutions. Both analyses reveal that the nonlocal effect implemented in this study stiffens the structures, resulting in reduced static deflection and increased natural frequencies. It is noteworthy that beams with dimensions comparable to microstructural length scales exhibit a significant nonlocal effect, which diminishes as the structure's size increases. Additionally, the response obtained using the Timoshenko beam model is softer in comparison to the Euler-Bernoulli model due to the consideration of shear deformation.

The determination of glucose concentrations in the blood and urine were important to monitor the health of human being. This study was carried out to study the effect GO thicknesses in enhancing the sensitivity of the Au/GO sensor for detection of glucose with various concentration. The partial unclad SMF was fabricated by using low-cost mechanical etching technique. The cladding thickness was successfully reduced from 125μm to 124μm by using this technique. To enhance the strength of evanescent field, Au nanoparticles were deposited on top of unclad fiber via drop casting method. To excite surface plasmon polaritons. GO with various layers from one to five layers were coated on the Au coated partial unclad SMF. The optimum sensitivity of the Au/GO SMF was resulted as three layers of GO with laser excitation under infrared range, λ=1310nm was employed. In conclusion, the effect of GO thicknesses mainly influenced the performance of the proposed sensor, in which the best thickness of GO to enhance the evanescent field and the excitation of SPP is three layers.

Aluminum alloy sheets are widely considered for manufacturing lightweight thin-walled structural components in the automotive and aerospace industries. However, the poor formability of the material at room temperature is still a technical challenge. Warm forming evolved as a promising technology where the sheet metal is deformed at elevated temperatures below the recrystallization temperature. Numerical modeling is vital in the modern scenario to better understand formability and to improve the designing of tooling for complex sheet components during warm forming. Hence, it is imperative to understand the accuracy of material models on formability predictions at elevated temperatures. This work presents the effect of three yield criteria, namely, von Mises, Hill-48, and Barlat-89, on the formability predictions of AA6082-O sheet at elevated temperature, say, 200 °C. Analytical necking-based Marciniak-Kuczynski forming limit diagrams (MK-FLD) at the elevated temperature were predicted by incorporating these yield models. The accuracy of predicted MK-FLDs was validated with experimental data. Furthermore, finite element (FE) modeling of limiting dome height (LDH) tests was performed using sample sizes that developed deformation modes towards biaxial, plane strain, and uniaxial modes. The effect of different yield models on the forming behavior was studied in terms of part depths and major surface strain distributions. The compatibility of yield criteria on accuracy in prediction was assessed by overlapping with the experimental data. It was demonstrated that Barlat-89 was best suited compared to Hill48 and von Mises yield models.

To enhance the interfacial bonding capacity between basalt fiber and cementitious matrix, and to maximize the efficacy of basalt fiber in augmenting toughness, fracture resistance, and flexural strength within the cementitious matrix, the basalt fiber underwent treatment using a solution of γ-amino propyl triethoxy silane (KH550). Employing a single-fiber electron tensile testing instrument, the fracture strength and fracture elongation of basalt fibers were examined under various treatment conditions, leading to the determination of the optimal treatment concentration and immersion time. Subsequently, the scanning electron microscope (SEM) and energy-dispersive spectroscopy (EDS) were employed to investigate the surface morphology and elemental composition of the self-assembled molecular coating on the basalt fibers. Lastly, the UTM universal testing machine was utilized to subject concrete beams to loading, while the XTDIC digital speckle correlation full-field strain measurement system was employed to analyze strain conditions and crack propagation throughout the loading process. The experiments indicate that the KH550 system solution can spontaneously generate a fish-scale-like coating on the basalt fibers, thereby enhancing the interconnection between basalt fibers and cementitious materials, optimizing the role of basalt fibers in enhancing toughness and flexural resistance within cementitious materials, and retarding the initiation and development of concrete cracks.

This study investigates the Mg-6.5Zn-7.24Sn-1.22Ca alloy, focusing on its microstructural evolution, corrosion resistance, and mechanical performance under varying thermal and mechanical treatments. The alloy was cast under an argon environment, homogenized at 400°C for 18 hours, and hot rolled at 400°C with a 15% thickness reduction. Microstructural analysis through XRD, SEM-EDS, and optical microscopy revealed grain refinement, phase redistribution, and reduced porosity after rolling. Corrosion behavior in 3.5% NaCl solution, assessed via electrochemical techniques and weight loss measurements, indicated superior corrosion resistance in the homogenized condition due to reduced micro-galvanic coupling. Rolling, however, increased corrosion susceptibility due to strain-induced defects. High-temperature ( 200°C- 350°C ) tensile tests at strain rates of 10-4 and 5×10-4 s-1 demonstrated that tensile strength decreases with temperature, driven by dynamic recrystallization and grain boundary sliding. Strain rate variations revealed increased tensile strength at higher rates due to enhanced dislocation density and strain hardening. These findings highlight the interplay between processing conditions, strain rates, and alloy performance, offering insights for optimizing magnesium alloys for advanced engineering applications.

This study investigates the mechanical behavior of single and multi-wall carbon nanotubes (SWCNT/MWCNT) during torsional loading using the molecular dynamics (MD) simulation technique. The open-source software Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is utilized to conduct MD simulations to gain valuable insights into the response of pristine and defective carbon nanotubes. The torsional behavior of armchair SWCNTs with chiralities (5,5); (7,7); (10,10); (12,12) and (15,15) and zigzag SWCNTs (12,0); (17,0) and (22,0) is explored to understand the effect of chirality on the torsional properties. Furthermore, the impact of the aspect ratio is examined by varying the diameter of SWCNTs while keeping the length constant. The findings reveal a notable decrease in shear modulus with increasing tube diameter, providing a crucial understanding of the torsional behavior concerning SWCNT geometry. To assess the effect of vacancy defects, 1%, 2%, and 4% vacancy defects are introduced on (10,10) armchair SWCNTs, and their torsional response is analyzed. The predictions highlight a significant reduction in shear modulus by 25% for SWCNTs with the rising concentration of vacancy defects from 1% to 4%. Overall, this study contributes to a deeper comprehension of the mechanical properties of carbon nanotubes under torsional loading, paving the way for potential applications in nanotechnology and nanocomposite design.

The suspension system is crucial for durability testing, vibration analysis, and evaluating the smoothness and stability of vehicles. Leaf springs are commonly used in suspension systems of heavy-duty trucks. This study analyzed the durability using finite element analysis (FEA) and modeled a dual-leaf spring system on the HOWO truck, a popular vehicle in Vietnam. The research team compared the stress, displacement, and vibration of dual leaf springs made from two materials: steel and E-glass. Durability testing was conducted using HyperWorks software, and the team successfully built a vibration simulation model of the leaf spring suspension system using Matlab-Simulink software. The results showed that the stress in the E-glass material was lower, but its displacement was larger compared to steel, indicating that E-glass provides better smoothness than steel. The auxiliary springs only engage when the load on the main springs exceeds their capacity. Leaf springs made of E-glass showed slower damping of vibrations than steel but provided better smoothness.

The Yeoh constitutive model is widely utilized in finite element analysis for the compression packer rubber cylinder with special-shaped structures, owing to the model's ability to accurately predict the single tensile stress over broad ranges. Nevertheless, the Yeoh constitutive model demonstrates significant limitations in predicting the equal-biaxial tensile loading. Consequently, to achieve more precise forecasting of the compression packer rubber cylinder sealing performance, the novel Yeoh-Revised constitutive model is introduced in this paper. Initially, under the assumption of initial isotropy and totally incompressible of the hydrogenated nitrile butadiene rubber, the deformable sealing properties are analyzed using Yeoh-Revised and Yeoh models. The findings indicate that the Yeoh-Revised model is more effective in predicting the seal stability and reliability, thereby offering a suitable approach to determining the appropriate structure dimensions. Subsequently, the high pressure and high temperature test verifies that the material strength properties are the prerequisites to achieve a stable and reliable seal. The Yeoh-Revised constitutive model would offer reliable results for further slowing down the aging and optimizing the structural size.

The instrumented nanoindentation technique is widely used to investigate the local mechanical properties of cementitious composites. Due to its high-resolution load control and displacement sensing capabilities, this technique is increasingly being used to measure hardness, elastic modulus, creep parameters, and residual stresses that have been explored at micro and nanolevel. During the indentation of brittle materials, cracks may be generated around the impression, which depend on load conditions, material and indenter geometry. This work presents a simulation of the three-dimensional nanoindentation model established with finite element method and modified constitutive relation. The model is created to simulate on single phase (homogeneous) materials such as cement clinker (C3S and C2S separately) and the hydrated phase – Low Density CSH and High Density CSH separately that constitute the primary phases of cementitious matrix. Then numerical modelling (FEA) of indentation is conducted using the concrete damage plasticity (CDP) material model, with the constants calibrated for hardened cement paste. At the end, there was a good agreement when comparing the differences between the simulated and literature experimental results.