Structural Analysis Techniques Research Articles

Combined Displacement/Intercalation Mechanism of Ag0.33V2O5 Cathode for Rechargeable Zinc‐Ion Batteries

Zinc‐ion batteries are gaining recognition as viable options for energy storage systems due to their air stability, abundance, affordability, and ease of use. However, existing zinc‐storage materials primarily consist of intercalation cathode materials, necessitating the development of host structures with enhanced performance. Herein, the use of silver vanadate, Ag0.33V2O5, as a cathode material is explored and its detailed displacement/intercalation mechanism is elucidated, encompassing silver, proton, and zinc‐ion storage behaviors. Electrochemical behavior, structural analysis, and diffusion barrier calculation techniques are used to delineate cation diffusion pathways. Additionally, 3D electron density mapping is performed to visualize the cation reaction mechanism. The proposed material demonstrates an impressive reversible capacity of about 303 mAh g−1 at a current of 0.1 A g−1, along with outstanding cycle retention stability even at high current densities.

Study on structural analysis technique of loess tunnel based on multi-index evaluation

Abstract The geological environment of loess tunnel is very complicated in the process of construction and operation, and the actual supporting parameters and surrounding rock pressure of loess tunnel have great uncertainties, which increases the difficulty of performance evaluation. In this paper, a distributed optical fiber monitoring system for loess tunnel is established by means of field investigation, theoretical analysis and field monitoring, which can monitor the tunnel displacement rate, the initial steel arch stress, the axial force of the anchor bolt, the lining stress and the width of the lining crack. Based on the theory of extension, the long-term performance evaluation model of loess tunnel is established, which comprehensively and objectively considers the influence of various influencing factors on the long-term performance of the tunnel, makes a quantitative judgment on the long-term performance of the typical section of loess tunnel, and provides a theoretical basis for the next tunnel maintenance plan, which is of great significance for the improvement of the maintenance technology of loess tunnel.

Analysis and Design of a Multistorey Building on Sloped and Flat Grounds (Stilt + Ground + 4)

This project focuses on the planning, static analysis, and structural design of a (Stilt + Ground + 4) residential building, located on both sloping and flat ground, using ETABS software. The primary goal is to study the impact of ground conditions on the structural behavior and design considerations of the building. The project incorporates planning principles to create a functional and efficient layout, ensuring compliance with Indian Standard codes for beams, columns, slabs, and other structural elements. Key aspects such as load distribution, stability, reinforcement detailing, and member sizing are thoroughly examined to ensure the building's safety and adherence to IS guidelines. A comparative analysis between sloping and flat ground conditions highlights the differences in design parameters, such as member forces, moments, and reinforcement requirements, with particular attention to the unique challenges posed by sloping ground. The findings of the study aim to offer insights into cost- effective and optimized design strategies that cater to different site conditions. By exploring these variations, the study contributes to the development of advanced modeling techniques for structural analysis and design. It also emphasizes the importance of adaptable strategies to ensure safe, resilient, and efficient residential buildings, regardless of topography. This research enhances the understanding of how varying ground conditions influence the design process and promotes the development of residential structures that are both safe and cost-efficient across diverse terrains. Keywords: Residential Building Design, Sloping Ground, Flat Ground, ETABS, Static Analysis, Structural Components, Indian Standards, Comparative Study, Planning Principles, Reinforcement Detailing.

Scalable graphene nanogrid FET biosensors: Fabrication & characterization for sub-femtomolar detection of viral proteins

The development of highly sensitive biosensors has been significantly advanced by graphene nanostructures, particularly nanogrids, due to their remarkable surface area-to-volume ratio, which enhances biomolecule detection at ultra-low concentrations. This study introduces a scalable fabrication technique for graphene nanogrids integrated into field-effect transistor (FET) biosensors, specifically designed for sub-femtomolar detection of viral proteins. Through the optimization of pore size and distribution, the graphene nanogrid FET biosensors demonstrated high signal-to-noise ratios (SNR) and overcame challenges associated with non-specific antigen interference. The surface antigen was detected at 0.25 fM in serum, even in the presence of Hepatitis C. In addition to these advancements, structural analysis techniques, including XPS and TEM, were employed to observe the effects of lattice temperature and core structures on the electronic band gap, which directly influenced electron mobility. Lattice temperature effects were analyzed for their impact on sensitivity, revealing that optimized temperature control significantly improved detection performance, while precise adjustments in pore morphology and material composition reduced device non-linearity and minimized quantification errors. By operating in heterodyne mode (80 kHz–2 MHz) and utilizing a probabilistic neural network (PNN), the sensor mitigated Debye screening effects, achieving a 70 % increase in SNR, detecting 0.20 fM of Hepatitis B viral proteins with 60 % sensitivity and 6 % standard deviation, demonstrating potential for ultra-sensitive biomedical detection with enhanced electron mobility and reduced non-linearity.

Pengaruh Citra Destinasi dan Komunikasi Pemasaran Terhadap Loyalitas melalui Kepuasan Pengunjung Destinasi Pantai Lon Malang

This study aims to examine the effect of destination image and marketing communication on loyalty through visitor satisfaction. This type of research is quantitative research with Structural Equation Modeling data analysis techniques using the SmartPLS version 4.0 statistical program. In this study, the population is not known for certain (infinite) and the sample used is tourists visiting Lon Beach, Malang. This study uses a questionnaire with a Likert Scale. The results of the study obtained that destination image affects loyalty with a p-value <0.05 and t-statistic> 1.96, while destination image does not affect satisfaction with a p-value> 0.05 and t-statistic <1.96, but marketing communication has an effect on loyalty with a p-value <0.05 and t-statistic> 1.96, and communication also has an effect on satisfaction with a p-value <0.05 and t-statistic> 1.96.

A Virtual Assembly Technology for Virtual–Real Fusion Interaction of Ship Structure Based on Three-Level Collision Detection

With the rapid advancement of new-generation information technology, the virtual–real fusion interaction has increasingly become a crucial technique for structural analysis to determine the strength envelope of hulls. A high-precision assembly of the experimental devices in a virtual environment is vital. A virtual assembly method for a structural virtual–real fusion test based on the oriented bounding box (OBB) algorithm, the Devillers and Guigue algorithm, and differential triangle facets algorithm are proposed in this paper. The experiment of the connector in a typical offshore floating platform is performed as a case, which indicates that the virtual assembly method proposed in this paper enables the assessment of assembly virtually prior to the actual experiment, and the assembly accuracy can reach 0.01 mm. The digitalization and virtual–real fusion interaction for the mechanical experiment of hulls are advanced to ensure efficiency, safety, and economy.

Rapid Size Determination of Quasispherical Gold Nanoparticles by Electrocatalysis Efficiency-Regulated Electrochemiluminescence.

The size of gold nanoparticles (AuNPs) largely decides their properties and applications, making the rapid screening of AuNP size important. Despite the fact that AuNP-amplified electrochemiluminescence (ECL) is widely used in various ECL sensing applications, the mechanism of ECL enhancement remains elusive, especially the quantitative relationship between the enhanced ECL intensity and the size of AuNPs. In this work, taking quasispherical and citrate-stabilized AuNPs as model nanoparticles, we have reported that the ECL intensity of the S2O82--O2 system enhanced significantly with the increasing AuNP size. AuNPs acted as bielectrocatalysts for reducing the S2O82- and O2. The further study of enhancement mechanism demonstrates that AuNPs with increasing size facilitate the electron transfer and promote the generation of radicals required for the ECL emission, which produces more emitters-singlet oxygen. Meanwhile, the high surface density of citrate on small AuNPs suppresses the ECL signal by forming an electrostatic barrier. On the basis of the above phenomena, an ECL-based rapid AuNP size screening approach has been established. The accuracy of this platform is verified by the consistent results in comparison to transmission electron microscopy (TEM) measurements. This work not only provides deep insight into the correlation between the AuNP size and the ECL enhancement but also contributes an alternative to the TEM technique for the rapid AuNP size screening. Additionally, this study also extends the exploration of ECL-based structure analysis techniques toward nanomaterials through clarifying the structure-electrocatalytic activity correlation.

Antecedents Of Career Optimism, Career Success, And Competence For Career Sustainability As A Professional Lecturer In Indonesia

This study aims to examine the relationship between the variables of career optimism, career success, and competence on career sustainability directly and indirectly in private universities in Indonesia. This study uses quantitative methods with structural equation modelling analysis techniques. The result is that career optimism has no effect on career competence, but career optimism has a positive effect on career sustainability. Furthermore, the results of indirect testing found that career competence is not able to intervene in the relationship between career optimism variables and career sustainability, but career success is able to strongly mediate the relationship between career optimism variables and career competence and strongly moderate the relationship between career optimism variables and career sustainability. The implication of this research is that all lecturers are expected to start thinking about their career sustainability, either by improving their abilities or taking higher education to reach a professional level as lecturers and educators.

Design, Analysis, and Optimization Testing of a Novel Modular Walking Device for Pipeline Robots

This article investigates the limitations associated with traditional wheel-type pipeline walking devices, which are characterized by a single movement mode and an inability to navigate complex or irregular pipeline structures. A modular walking device (MWD) designed for pipeline robots was developed utilizing structural and mechanical analysis techniques. The reliability of the mechanical analysis was validated through single-factor dynamic testing. To analyze and optimize the factors influencing the maneuverability and obstacle-crossing capabilities of the MWD, a three-factor, three-level orthogonal testing method was utilized. The factors examined included the rotational speed of the walking wheel (RS), the pre-tightening force of the wheel brackets (PF), and the height of the annular obstacle (OH). The evaluation metrics used were the slip rate and passability. The results indicated that a parameter combination of RS at 70 rpm, PF at 30 N, and OH at 10 mm produced a slip rate of 11.6% ± 1.5%. During the obstacle traversal process, the remainder of the device maintained a safe distance from the obstacles, with only the walking wheel making contact. The verification testing also confirmed that the MWD is capable of executing three distinct modes of motion: rectilinear, rotational, and helical. The MWD designed and developed in this study can switch between multiple motion modes and successfully overcome obstacles within 15 mm, providing a new equipment for universities to enhance mechanized pipeline detection technology.

Structural Analysis Technique and Its Validation for Large Range Mirror Refocusing System for Spaceborne Deployable Telescopes

Large aperture deployable telescopes with numerous onboard instruments are popular in the space industry for astronomy. Scientific data in various wavelength bands, from 0.6µ to 28µ, is provided by these instruments and is crucial for deep space exploration. The deployment mechanisms handle the alignment and functionality at the telescope level only. At instrument level, there is always a need for a refocusing system which can cater individual need of instrument for focusing independent to other instruments nearby. In this paper, we present a structural analysis technique for such a type of large range mirror refocusing mechanism, similar to the Near Infrared Spectrograph (NIRSpec) payload of the James Webb Space Telescope (JWST). The method relies on geometric non-linearity for large deflection, in which the structure's stiffness matrix changes as a function of loading. We have designed, analyzed structurally, and tested a 4mm range slider crank based compliant mechanism. The outcomes of linear and non-linear static analysis, computed numerically, have been compared. There are noticeable significant variations in one direction between the two analyses' results. The results are validated using appropriately designed and realized test setups, like measurements of displacement, changes in focus and image position of the optical system.

Three-Dimensional Electron Diffraction: A Revolutionary Technique for Structure Analysis of Nano-sized Minerals

Three-Dimensional Electron Diffraction: A Revolutionary Technique for Structure Analysis of Nano-sized Minerals

Implementing innovation in project-based learning in electro-mechanical engineering education

This study investigates the implementation of project-based learning (PBL) in electro-mechanical engineering education, emphasizing the modeling and application of an innovation process to enhance student engagement, motivation, and employability. Initially, the innovation process was systematically modeled using Structured Analysis and Design Technique (SADT) to manage and organize skills, knowledge, and resources effectively. This model was subsequently applied in an educational experience focused on highly technical aspects such as energy conversion modeling, mechanical improvements, material science, and efficiency analysis. These aspects were primarily applied in the context of permanent magnet synchronous machines employed in electric vehicle (EV) axles. The SADT modeling allowed for a clear delineation of the innovation phases, ensuring a structured approach to project execution. Statistical analysis of the PBL approach indicated significant improvements in student performance, with a 25% increase in problem-solving skills and a 30% enhancement in critical thinking abilities. The case study demonstrated that industry-oriented projects significantly boost student satisfaction, particularly in problem definition and solution identification, leading to a more engaging and effective learning experience.

ECLiPSE: a versatile classification technique for structural and morphological analysis of 2D and 3D single-molecule localization microscopy data

Single-molecule localization microscopy (SMLM) has gained widespread use for visualizing the morphology of subcellular organelles and structures with nanoscale spatial resolution. However, analysis tools for automatically quantifying and classifying SMLM images have lagged behind. Here we introduce Enhanced Classification of Localized Point clouds by Shape Extraction (ECLiPSE), an automated machine learning analysis pipeline specifically designed to classify cellular structures captured through two-dimensional or three-dimensional SMLM. ECLiPSE leverages a comprehensive set of shape descriptors, the majority of which are directly extracted from the localizations to minimize bias during the characterization of individual structures. ECLiPSE has been validated using both unsupervised and supervised classification on datasets, including various cellular structures, achieving near-perfect accuracy. We apply two-dimensional ECLiPSE to classify morphologically distinct protein aggregates relevant for neurodegenerative diseases. Additionally, we employ three-dimensional ECLiPSE to identify relevant biological differences between healthy and depolarized mitochondria. ECLiPSE will enhance the way we study cellular structures across various biological contexts.

The Role of Self-Efficacy as a Mediator Between Active Organization and Job Readiness

The world of work requires students to have abilities and work skills as a basis for negotiation since willingness to work is the basis. At the same time, the organization promotes students' self-efficacy, making them more mature and career-ready. This study aims to determine the importance of self-efficacy as a mediator between organizational activities and work readiness. The research method uses a quantitative approach. The subjects were 95 students from the Faculty of Economics and Management, Mulawarman University, who were selected through simple random sampling. The data collection method uses three types of scales: work readiness scale, organizational activity scale, and self-efficacy scale. Structural Equation Modeling analysis technique and statistical software Smart PLS are adopted. The research results show that self-efficacy can play a partial role as a mediator between organizational activity and students' job readiness, organizational activity can directly affect students' work motivation, and Organizational activity can affect students' self-efficacy. This study concludes that self-efficacy plays a vital role in improving students' job readiness, directly or indirectly, in the current millennium.

Organizational Performance Improvement Model Based on Talent Management Through Religiosity Organizational Citizenship Behavior

Purpose: This research aims to determine the influence of talent management on organizational performance; the influence of religiosity organizational citizenship behavior as a mediator on organizational performance; the influence of digital literacy as a mediator on organizational performance; the influence of talent management, digital literacy and religiosity organizational citizenship behavior simultaneously on employee performance and employee performance. organization, and designing a model for improving organizational performance through digital literacy and religiosity organizational citizenship behavior as mediators Theoretical Framework: Drawing from the practice-based view theory, this research focuses on several constructs and relationships between talent management, digital literacy and organizational citizenship behavior in ASNs in government agencies which have not yet been widely studied. This research is an effort to develop a model for improving organizational performance through talent management and ASN digital literacy and also combines aspects of organizational citizenship behavior which are based on religious values, which are still rarely used by previous researchers. The research method used is an explanatory survey approach to explain the relationship between variables through hypothesis testing in the field. Research that uses descriptive surveys and explanatory survey methods is carried out by collecting information from samples directly at the scene of the incident (empirical) through questionnaires with the aim of finding out the opinions of the samples regarding the research problem. And this research uses the Partial Least Squares Structural Equation Modeling analysis technique (PLS-SEM), to model many variables in research Results and Discussion: To examine the influence of mediator variables, Partial Least Squares Structural Equation Modeling analysis technique (PLS-SEM),to estimate the causal relationship between variables (causal model) that has been determined previously based on the theory. Answering research questions requires correct statistical data processing. The results of this research will be more powerful if adequate statistical data processing is used. Scientifically based research shows that findings can be evaluated and proven, and if other researchers used the same procedures, the results would almost certainly be the same. As a result, researchers chose statistical data processing techniques to use in these calculations. The result of research. Based on the results of research regarding "Model for Improving Organizational Performance Based on Talent Management Through Religious Organizational Citizen Behavior", the following results were obtained: Overview of talent management, religiosity organizational citizenship behavior, digital literacy, employee performance and organizational performance in Regency/City Government Agencies throughout West Java Province are in the high/good category, which means they are running in accordance with agency procedures. Talent management has a significant positive effect on organizational performance in Regency/City Government Agencies throughout West Java Province. This is based on the results of direct effect hypothesis testing, the t-statistics results obtained were 2.482 and the significance results (pvalue) obtained were 0.007 (0.007<0.05), so Ho was rejected and Ha was accepted. Religious organizational citizenship behavior is unable to mediate the influence of talent management on employee performance. This is based on the results of testing the indirect effect hypothesis, obtaining a significance result (pvalue) of 0.053 (0.053>0.05). Meanwhile, digital literacy is able to mediate the influence of Talent Management on Employee Performance. This is based on the results of testing the indirect effect hypothesis, obtained a significance result (pvalue) of 0.000 (0.000<0.05). Digital literacy, religiosity organizational citizenship behavior and employee performance are able to mediate the influence of talent management on organizational performance. This is based on the results of testing the indirect effect hypothesis, obtained a significance result (pvalue) <0.05. There is an increase in organizational performance through digital literacy and religiosity organizational citizenship behavior in talent management. Implications: The research results show that religiosity organizational citizenship behavior, digital literacy and employee performance are variables that can mediate the influence of talent management on organizational performance in Regency/City Government Agencies throughout West Java Province.

Image-based quantitative probing of 3D heterogeneous pore structure in CBM reservoir and permeability estimation with pore network modeling

Coalbed methane (CBM) recovery is attracting global attention due to its huge reserve and low carbon burning benefits for the environment. Fully understanding the complex structure of coal and its transport properties is crucial for CBM development. This study describes the implementation of mercury intrusion and μ-CT techniques for quantitative analysis of 3D pore structure in two anthracite coals. It shows that the porosity is 7.04%–8.47% and 10.88%–12.11%, and the pore connectivity is 0.5422–0.6852 and 0.7948–0.9186 for coal samples 1 and 2, respectively. The fractal dimension and pore geometric tortuosity were calculated based on the data obtained from 3D pore structure. The results show that the pore structure of sample 2 is more complex and developed, with lower tortuosity, indicating the higher fluid deliverability of pore system in sample 2. The tortuosity in three-direction is significantly different, indicating that the pore structure of the studied coals has significant anisotropy. The equivalent pore network model (PNM) was extracted, and the anisotropic permeability was estimated by PNM gas flow simulation. The results show that the anisotropy of permeability is consistent with the slice surface porosity distribution in 3D pore structure. The permeability in the horizontal direction is much greater than that in the vertical direction, indicating that the dominant transportation channel is along the horizontal direction of the studied coals. The research results achieve the visualization of the 3D complex structure of coal and fully capture and quantify pore size, connectivity, curvature, permeability, and its anisotropic characteristics at micron-scale resolution. This provides a prerequisite for the study of mass transfer behaviors and associated transport mechanisms in real pore structures.

Political marketing mix and the influence of social media promotion on voting decision through perceived value: a study of the 2020 South Tangerang city election

This research aims to examine the influence of Marketing Mix (4P) variables consisting of product, price, place, and promotion, perceived value, and vote decision. The approach used in this research is a quantitative approach. The sample used in this research is the community in South Tangerang City registered in the Permanent Voter List in the 2020 South Tangerang City Regional Election, totaling 175 respondents. Research data was obtained from the result of filling out a questionnaire and analyzed using Structural Equation Modeling analysis techniques with the help of the Smart PLS program. The results of this research show that (i) Political Product affects the voting decision; the higher the political product possessed by the political candidate, the higher the voting decision, and vice versa; (ii) Political Price affects the voting decision; the higher the Political Price, the higher the voting decision, and vice versa; (iii) Political Place does not have a significant effect on voting decision, which means that people in South Tangerang City prefer promotion through social media; (iv) Political Promotion affects the Voting Decision; the higher the Political Promotion, the higher the Voting Decision, and vice versa; (v) Political Promotion affects perceived value; the higher the political promotion, the higher the perceived value in the community, and vice versa; (vi) Perceived Value affects the Voting Decision; the higher the Perceived Value, the higher the Voting Decision, and vice versa; (vii) Perceived Value positively mediates the relationship between Political Promotion and Voting Decision. The promotion variable has the highest value and the strongest influence on voting decision. In general, the conclusion drawn from this research is that the implementation of Marketing Mix (4P) is important in influencing the voting decision of the community in South Tangerang City. Political candidates can pay attention to these aspects to strengthen their advantage in future political contests.

Systematic Elastostatic Stiffness Model of Over-Constrained Parallel Manipulators Without Additional Constraint Equations

The establishment of an elastostatic stiffness model for over constrained parallel manipulators (PMs), particularly those with over constrained subclosed loops, poses a challenge while ensuring numerical stability. This study addresses this issue by proposing a systematic elastostatic stiffness model based on matrix structural analysis (MSA) and independent displacement coordinates (IDCs) extraction techniques. To begin, the closed-loop PM is transformed into an open-loop PM by eliminating constraints. A subassembly element is then introduced, which considers the flexibility of both rods and joints. This approach helps circumvent the numerical instability typically encountered with traditional constraint equations. The IDCs and analytical constraint equations of nodes constrained by various joints are summarized in the appendix, utilizing multipoint constraint theory and singularity analysis, all unified within a single coordinate frame. Subsequently, the open-loop mechanism is efficiently closed by referencing the constraint equations presented in the appendix, alongside its elastostatic model. The proposed method proves to be both modeling and computationally efficient due to the comprehensive summary of the constraint equations in the Appendix, eliminating the need for additional equations. An example utilizing an over constrained subclosed loops demonstrate the application of the proposed method. In conclusion, the model proposed in this study enriches the theory of elastostatic stiffness modeling of PMs and provides an effective solution for stiffness modeling challenges they present.

Correlated 4D-STEM and EDS for the classification of fine Beta-precipitates in aluminum alloy AA 6063-T6

Tuning the properties of aluminum alloys AA 6063-T6 involves artificial aging to induce precipitate formation, particularly β’’ and β’ phases. Previous characterization challenges due to their similar appearance are addressed here by correlating 4D scanning transmission electron microscopy (4DSTEM) and energy-dispersive spectroscopy (EDS) mapping. This approach allows us to analyze the structure and composition of precipitates individually, overcoming limitations of conventional imaging and structural analysis techniques when the precipitates appear simultaneously, as is often the case. We present detailed characterizations of needle-shaped Beta precipitates, revealing distinct diffraction patterns (DPs) and compositional differences. The method's applicability extends beyond aluminum alloys, offering a promising strategy for complex composite material characterization with multimodal scanning transmission electron microscopy (STEM) techniques.

A study on civil engineering construction simulation technology based on artificial intelligence for civil buildings

Abstract This research delves into utilizing Artificial Intelligence (AI) in civil engineering, specifically construction simulations. The primary objective is to reconcile the discrepancies between conventional structural analysis techniques and the actual performance of structures. By integrating AI technologies—neural networks, cellular automata, and support vector machines— with data mining, this research proposes a novel approach for simulating civil building constructions. Traditional methods, often constrained by underlying assumptions, fail to capture the complex behaviors of engineering structures accurately. The developed AI simulation framework utilizes experimental and on-site data to construct digital models, enabling precise prediction of structural behaviors without the limitations of traditional assumptions. Results indicate that AI-enhanced simulations can significantly improve the accuracy of structural analysis, demonstrating potential for wider application in civil engineering. This advancement promises to enhance the predictability, efficiency, and safety of civil constructions, marking a significant step forward in the field.