Field Of Engineering Research Articles

Advanced synthetic routes of metal organic frameworks and their diverse applications

Abstract Metal-organic frameworks (MOFs) are crystalline materials characterized by their porous structures, formed through coordination bonding between metal ions/clusters and multidentate organic linkers. MOFs have emerged as a significant class of materials with applications in energy storage, CO2 adsorption, and catalysis. This study serves as a brief introduction to the currently available synthesis methods of MOFs, aimed at acquainting beginners in the field of chemical engineering with the ongoing developments in MOF research. The discussed synthesis methods encompass traditional solvothermal/hydrothermal approaches, microwave synthesis of MOFs, one-pot synthesis, MOF nanocomposites, isothermal synthesis, and fluid-fluid synthesis. Notably, the MOF/NH2/Fe3O4 combination exhibited enhanced adsorption capacity of 618 mg/g and retained an efficiency of over 90 %. This study displays a valuable technique for designing functional MOF hybrid composites. By combining MOFs with specific materials, numerous advantages can be achieved in the newly created compounds (MOF composites), including synergistic effects beneficial in catalytic applications, and overcoming the challenges associated with using bare MOFs.

Experimental Study on Mechanical Behavior of Skirt–Pile Foundations in Saturated Clay under Horizontal Load

Skirt–pile foundations have gained widespread attention in the field of offshore engineering due to their ease of installation and high bearing capacity. In this study, the ultimate bearing capacity, pile bending moment distribution and development, cumulative deformation characteristics, and cyclic stiffness development of skirt–pile foundations were investigated using physical model tests. The experimental results indicate that the ultimate bearing capacity and deformation resistance of the foundation can effectively be improved by increasing the skirt diameter. The cumulative deformation of the skirt–piles exhibited rapid development during the initial stages of cyclic loading, eventually stabilizing. Under long-term cyclic loading, the existence of the skirt can share the bending moment, which then affects the internal force distribution of the pile foundation along the axis. The pile foundation’s cyclic stiffness reduces as the loading cycles increase and increases as the skirt diameter and length grow. Meanwhile, the horizontal cyclic stiffness decreases as the number of cycles increases, stabilizing after 3000 cycles. This study can not only deepen the understanding of the deformation laws of skirt–pile foundations in clay soil but also offers some references for the design of offshore pile foundations.

Fully automated operational modal identification based on scale-space peak picking algorithm and power spectral density estimation

Modal analysis is a fundamental and essential research direction in the field of structural engineering. The ultimate goal is to determine the modal parameters of the structures. However, the existing modal analysis algorithms often require a large number of parameter adjustments and manual intervention during operation, which cannot be fully automated. In order to realize the automatic identification of modal parameters, the automatic operational modal identification method (AOMI) is proposed based on the interpolated power spectral density estimation (IPSE). To achieve more precise spectrum analysis in the low-frequency band, IPSE is employed to perform Fourier transform on the original frequency domain segment with optimized frequency resolution. This enhances the sharpness of the obtained spectrum in the low-frequency range, making peak frequencies more discernible. Subsequently, the scale-space peak picking algorithm is used to automatically obtain the peak of the power spectral density (PSD), thus enabling the automatic identification of the natural frequency. Finally, the frequency domain decomposition method (FDD) is used to identify modal parameters based on the natural frequencies. The effectiveness of AOMI is verified through the modal identification of the old steel truss bridge and the three layer framework. Under the environmental excitation, the frequencies identified by the IPSE method is close to that of FDD, Bayesian fast fourier transform (FFT) and covariance driven stochastic subspace identification (SSI-COV). Furthermore, the PSD obtained through IPSE has sharper peak than that of FDD and the Welch’s method. The damping ratio identification accuracy and modal assurance criterion (MAC) are satisfactory in AOMI, which can improve the automatic performance.

Pomegranate seed oil extraction by cold pressing, microwave and ultrasound treatments

AbstractIn this study, pomegranate seed oil was extracted by microwave-assisted extraction, ultrasound-assisted extraction, and cold pressing techniques. Dimethyl succinate was the solvent of microwave and ultrasound-assisted extraction methods. The optimum conditions were determined by using response surface methodology (RSM, Design Expert software version 7.0 and Box-Behnken design). The ultrasound-assisted extraction technique was found to be superior to the microwave-assisted extraction technique in terms of extraction efficiency. The maximum extraction efficiency of microwave-assisted extraction was 22.01% under the optimized conditions (liquid/solid ratio, 5/1; time, 3 min; and microwave power, 300 W). The maximum extraction efficiency obtained by ultrasound-assisted extraction was 26.31% under the optimized conditions (liquid/solid ratio, 10/1; pulse duration/pulse interval ratio, 1; temperature 60 °C; and time, 20 min). The extraction efficiencies were compared at the optimum conditions with hexane, which is the most used solvent for pomegranate seed oil extraction, and the difference was insignificant. The results of this study are very important, especially in the field of green chemistry and chemical engineering.

Reverse Engineering of Building Layout Plan through Checking the Setting out of a Building on a Site Using 3D Laser Scanning Technology for Sustainable Building Construction: A Case Study

Among smart construction technologies, 3D laser scanning technology is used in a variety of applications, including progress measurement, quantity management, reverse engineering (RE), health monitoring, mechanical electronic plumbing (MEP), and so on, using point clouds data (PCD) in the architecture, engineering, and construction (AEC) field. This technology is one of the important data acquisition technologies in construction status to perform active project management through the complete and accurate three-dimensional and visual judgment of building acts. The surveying work for setting out a building is the first step in constructing a building; the location of the building must match the design plan for a building to be sustainable. This is because, if a location deviation exceeds the permitted range, the building must be demolished and rebuilt. When this happens, sustainable construction management is impossible due to delays in the construction schedule, increased construction costs, waste generation, and so on. The purpose of this study is to investigate a case where the accuracy of setting out a building was measured in the construction stage of a building and the building layout design was modified by RE. Although the foundation construction of the case building was in progress, it was confirmed that the setting out of the building measured using a 3D laser scanner did not match with the building layout plan. Therefore, there was no legal problem even if the layout plan is modified according to the measured results, so the building layout plan was modified through RE. Consequently, it was confirmed that a case building under construction became sustainable through RE, and that sustainable construction management was possible by preventing construction schedule delays, increased construction costs, and waste generation.

Equitable infrastructure: Achieving resilient systems and restorative justice through policy and research innovation

Abstract Recent major investments in infrastructure in the United State and globally present a crucial opportunity to embed equity within the heart of resilient infrastructure decision-making. Yet there is a notable absence of frameworks within the engineering and scientific fields for integrating equity into planning, design, and maintenance of infrastructure. Additionally, whole-of-government approaches to infrastructure, including the Justice40 Initiative, mimic elements of process management that support exploitative rather than exploratory innovation. These and other policies risk creating innovation traps that limit analytical and engineering advances necessary to prioritize equity in decision-making, identify and disrupt mechanisms that cause or contribute to inequities, and remediate historic harms. Here, we propose a three-tiered framework toward equitable and resilient infrastructure through restorative justice, incremental policy innovation, and exploratory research innovation. This framework aims to ensure equitable access and benefits of infrastructure, minimize risk disparities, and embrace restorative justice to repair historical and systemic inequities. We outline incremental policy innovation and exploratory research action items to address and mitigate risk disparities, emphasizing the need for community-engaged research and the development of equity metrics. Among other action items, we recommend a certification system – referred to as Social, Environmental, and Economic Development (SEED) – to train infrastructure engineers and planners and ensure attentiveness to gaps that exist within and dynamically interact across each tier of the proposed framework. Through the framework and proposed actions, we advocate for a transformative vision for equitable infrastructure that emphasizes the interconnectedness of social, environmental, and technical dimensions in infrastructure planning, design, and maintenance.

Replication in Requirements Engineering: the NLP for RE Case

[Context] Natural language processing (NLP) techniques have been widely applied in the requirements engineering (RE) field to support tasks such as classification and ambiguity detection. Despite its empirical vocation, RE research has given limited attention to replication of NLP for RE studies. Replication is hampered by several factors, including the context specificity of the studies, the heterogeneity of the tasks involving NLP, the tasks’ inherent hairiness , and, in turn, the heterogeneous reporting structure. [Solution] To address these issues, we propose a new artifact, referred to as ID-Card , whose goal is to provide a structured summary of research papers emphasizing replication-relevant information. We construct the ID-Card through a structured, iterative process based on design science. [Results] In this paper: (i) we report on hands-on experiences of replication, (ii) we review the state-of-the-art and extract replication-relevant information, (iii) we identify, through focus groups, challenges across two typical dimensions of replication: data annotation and tool reconstruction, and (iv) we present the concept and structure of the ID-Card to mitigate the identified challenges. [Contribution] This study aims to create awareness of replication in NLP for RE. We propose an ID-Card that is intended to foster study replication, but can also be used in other contexts, e.g., for educational purposes.

Investigation on the properties of sustainable alkali-activated GGBS mortar with nano silica and dredged marine sand: Mechanical, microstructural and durability aspects

In recent years, alkali-activated mortar (AAM) has emerged as a promising alternative to ordinary Portland cement (OPC) due to concerns regarding the environmental impact resulting from cement production, which releases carbon dioxide and degrades the quality of the environment. To address these concerns, researchers have explored the addition of supplementary binder materials to enhance cement properties and mitigate pollution. The effectiveness of these binder materials depends heavily on their chemical composition and fineness. Notably, ground granulated blast furnace slag (GGBS) enhances the strength and durability of the cement. In response to the scarcity of river sand (RS), dredged marine sand (DMS) has gained popularity as a potential substitute within the civil engineering field. Furthermore, the integration of nanomaterials has shown promising improvements in the mechanical and microstructural properties of mortar. Therefore, this study aims to investigate the properties of mortar by incorporating nano silica (NS) within the range of 1% to 7%, varying the molarity from 2 M to 8 M, and substituting RS with DMS. The tests carried out encompass a range of evaluations, including compressive strength, flexural strength, SEM-EDS, XRD, UPV, RCPT, and carbonation analysis, to comprehensively assess the properties of the mortar. The study reveals that the AAM demonstrates optimal performance when 50% of RS is replaced by DMS in the absence of NS. Once this optimal point is determined, further analyses are conducted at this value while varying the concentrations of NS from 1–7%. The experimental results indicate that replacing 50% of RS with DMS and incorporating 6% NS leads to maximum compressive strength (49.2 MPa) and flexural strength (9.36 MPa) in the assessed properties. Furthermore, the incorporation of NS in GGBS-based AAM mixes enhances durability by improving resistance against chloride penetration, reducing water absorption, and minimizing carbonation diffusion. Additionally, the microstructural and mineralogical characterization of GGBS-NS-based AAM specimens demonstrates the formation of C-S-H and C-A-S-H gels as the end products of the reactions.

Engineering Clock Transitions in Molecular Lanthanide Complexes.

Molecular lanthanide (Ln) complexes are promising candidates for the development of next-generation quantum technologies. High-symmetry structures incorporating integer spin Ln ions can give rise to well-isolated crystal field quasi-doublet ground states, i.e., quantum two-level systems that may serve as the basis for magnetic qubits. Recent work has shown that symmetry lowering of the coordination environment around the Ln ion can produce an avoided crossing or clock transition within the ground doublet, leading to significantly enhanced coherence. Here, we employ single-crystal high-frequency electron paramagnetic resonance spectroscopy and high-level ab initio calculations to carry out a detailed investigation of the nine-coordinate complexes, [HoIIIL1L2], where L1 = 1,4,7,10-tetrakis(2-pyridylmethyl)-1,4,7,10-tetraaza-cyclododecane and L2 = F- (1) or [MeCN]0 (2). The pseudo-4-fold symmetry imposed by the neutral organic ligand scaffold (L1) and the apical anionic fluoride ion generates a strong axial anisotropy with an mJ = ±8 ground-state quasi-doublet in 1, where mJ denotes the projection of the J = 8 spin-orbital moment onto the ∼C4 axis. Meanwhile, off-diagonal crystal field interactions give rise to a giant 116.4 ± 1.0 GHz clock transition within this doublet. We then demonstrate targeted crystal field engineering of the clock transition by replacing F- with neutral MeCN (2), resulting in an increase in the clock transition frequency by a factor of 2.2. The experimental results are in broad agreement with quantum chemical calculations. This tunability is highly desirable because decoherence caused by second-order sensitivity to magnetic noise scales inversely with the clock transition frequency.

A Comprehensive Study on Ensemble Methods for Software Error Detection

Software Developers often find it painful and tedious to locate or pinpoint the errors that reside in the source code which causes serious hindrance in the progression of developing any software. In the field of software engineering, it is very crucial to understand the software metrics that are directly involved with the progression of the software. Besides, various classification algorithms have been used to foresee the errors in building the software. In this paper, we focus especially on ensemble algorithms as they tend to provide more precise and statistically efficient outcomes than the other traditional algorithms. This paper contains twenty software metrics that are pivotal in identifying errors in software applications. Eight Java projects have been gathered to showcase the significance of the software metrics in predicting errors. In this study, three ensemble methods are considered, MultiBoostAB, Dagging, and Decorate. For a detailed inspection of the performance, accuracy, recall, precision, F-measure, and ROC Curve were appraised. The comparisons exhibit Decorate as the highest-performing method and Dagging as the lowest.

Experimental Study on Low-Cycle Fatigue Characteristics of Marine Structural Steel

This research focuses on the experimental investigation of the low-cycle fatigue characteristics of marine structural steel. The study aimed to explore the behavior of marine-grade steel under low-cycle fatigue conditions. The experimental parameters include the fatigue life of the material, crack propagation behavior, and a comprehensive analysis of mechanical properties associated with various loading conditions. Based on the experimental results, a low-cycle fatigue crack propagation rate model for marine structural steel plates was established using CTOD as a characterization parameter. The primary objective of this research is likely to enhance the durability and safety of maritime structures, providing valuable technical insights for the field of naval engineering.

Development of Biphasic Injectable Hydrogels for Meniscus Scaffold from Photocrosslinked Glycidyl Methacrylate-Modified Poly(Vinyl Alcohol)/Glycidyl Methacrylate-Modified Silk Fibroin

The development of a hydrogel material with a modified chemical structure of poly(vinyl alcohol) (PVA) and silk fibroin (SF) using glycidyl methacrylate (GMA) (denoted as PVA-g-GMA and SF-g-GMA) is an innovative approach in the field of biomaterials and meniscus tissue engineering in this study. The PVA-g-GMA/SF-g-GMA hydrogel was fabricated using different ratios of PVA-g-GMA to SF-g-GMA: 100/0, 75/25, 50/50, 25/75, and 0/100 (w/w of dry substances), using lithium phenyl (2,4,6-trimethylbenzoyl)phosphinate (LAP) as a free radical photoinitiator, for 10 min at a low ultraviolet (UV) intensity (365 nm, 6 mW/cm2). The mechanical properties, morphology, pore size, and biodegradability of the PVA-g-GMA/SF-g-GMA hydrogel were investigated. Finally, for clinical application, human chondrocyte cell lines (HCPCs) were mixed into PVA-g-GMA/SF-g-GMA solutions and fabricated into hydrogel to study the viability of live and dead cells and gene expression. The results indicate that as the SF-g-GMA content increased, the compressive modulus of the PVA-g-GMA/SF-g-GMA hydrogel dropped from approximately 173 to 11 kPa. The degradation rates of PVA-g-GMA/SF-g-GMA 100/0, 75/25, and 50/50 reached up to 15.61%, 17.23%, and 18.93% in 4 months, respectively. In all PVA-g-GMA/SF-g-GMA conditions on day 7, chondrocyte cell vitality exceeded 80%. The PVA-g-GMA/SF-g-GMA 75:25 and 50:50 hydrogels hold promise as a biomimetic biphasic injectable hydrogel for encapsulated augmentation, offering advantages in terms of rapid photocurability, tunable mechanical properties, favorable biological responses, and controlled degradation.

The Method of the Probability Analysis of Area with Dissolved Gases in Power Transformer Insulating Oil

Transformer insulating oil plays an extremely important role in power transformers and is used for insulation, arc suppression, cooling and other purposes. However, its other focus is on dissolved gases analysis in the oil to monitor internal operating conditions, which is the responsibility of preventive maintenance. This paper uses the normal distribution theory and the American National Standard Specification (hereinafter referred to as ANSI/IEEE C57.104) to reorganize as a diagnostic tool. The range of each gas from three stages of the specification - normal, caution, and abnormal are incorporated to a stage of abnormal, which divide into equal different values of 1000 as the maternal body of a qualitative normal distribution. Then the benchmark is been calculated from those parameters of a qualitative normal distribution. The data of detection has to pass through "Gas chromatography” to generate dissolved gases.  At last, the benchmark value compares with dissolved gases to find the abnormal probability value as a diagnostic tool in maintenance evaluation of equipment. This method was developed using EXCEL application software, and repeatedly tested and verified with examples to confirm its feasibility and high accuracy. In addition, 10 cases accident data were extracted from the literature [11], and compared with the actual maintenance results. The accuracy was 80% for ANSI/IEEE C57.104 and 90% for this probability method. Therefore, this diagnostic method can replace the traditional multi-stage judgment and be represented by a single probability value to show.  Based on technology sharing, the development process is specially written into a technical article as reference by scholars and electrical maintenance personnel in the field of power engineering.
 Design Methods: Making a qualitative normal distribution employs EXCEL software and the discriminative rule of ANSI/IEEE C57.104.  Design Purpose: As a diagnostic tool with dissolved gases in insulating oil.  Design Effectiveness: Probability Method is better than traditional; it has those efficacies - the accuracy and feasibly and compete with tried and tested actual case.

Advancing Inclusivity in Biomechanical Engineering Research.

The ASME Journal of Biomechanical Engineering presents a Special Section dedicated to promoting inclusivity within the field of biomechanical engineering. This collection showcases diverse research articles and reviews that emphasize the importance of considering different backgrounds, experiences, and perspectives in biomechanics research. By amplifying underrepresented voices and broadening perspectives, this collection advances our understanding of biomechanical principles and fosters a more inclusive and equitable approach to research and development in engineering for human health.

Experimental Studies on Ground Improvement Using Stone Column

This research examined the ground improvement technique for enhancing the load-bearing capacity and enhancing of weak or compressible soils. In this study, we focus on how we minimize the cost of ground improvement and make environment friendly solution for ground improvement. The research involves a review of the existing literature, including the Objectives, methodology, and case studies related to stone column implementation. Laboratory testing and field investigations are conducted to assess the geotechnical properties of the soil and the behavior of stone columns under different loading conditions. The project aims to provide insights into the geotechnical behavior of stone columns and their effectiveness in stabilizing weak soils. Furthermore, the study will explore the economic and environmental aspects of this ground improvement technique. The findings of this research are expected to contribute valuable knowledge to the field of geotechnical engineering, assisting engineers and construction professionals in making informed decisions regarding ground improvement methods. Keywords : Ground Improvement, Stone Column, Soil Sample, cost effective, environment friendly, Load Bearing Capacity, Black Cotton Soil, Soil Stabilization.

Artificial neural network and ANFIS approaches for mechanical properties prediction and optimization of a turbine blade treated by laser shock peening

This research article covers a comprehensive investigation on the prediction and optimization of residual stresses, plastic deformations and damage induced by laser shock peening (LSP) on a thin Ti-6Al-4 V leading edge sample of a turbine blade. The study is based on a two-part approach: the first part involves a numerical simulation of the LSP process and the characterization of its effects on the material. The finite element analysis (FEA) is used to simulate the complex interactions between laser parameters, material properties and mechanical response. This numerical analysis generates valuable insights into the residual stress distribution, the plastic deformation and the potential damage within the sample being treated. Based on the numerical results, the second part highlights the novel application of the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS) methods. By taking advantage of the strength of ANN and ANFIS, the models are able to learn accurately from all the data generated by numerical simulations, allowing them to precisely predict and optimize the effects induced by LSP: residual stresses, plastic strains and damage. This paper provides a significant contribution to the field of materials science and engineering, by offering an in-depth comprehension of the LSP process impact on Ti-6Al-4 V leading-edge turbine blade specimens. The combined utilization of numerical analysis and artificial intelligence AI-driven techniques offers a comprehensive approach to optimize the LSP process, leading to the fatigue resistance improvement and service life extension of turbine blades and other critical aerospace components. The proven capability of ANN and ANFIS enables innovative solutions in aerospace engineering and surface treatment technologies, promoting the AI implementation in materials processing and design.

How to design a broad mindfulness program: One approach to introducing mindfulness to a STEM commumity within a university setting.

Mindfulness has become popular in recent decades as a tool for psychological well-being. However, mindfulness has yet to find a solid footing as a routine practice within the Science, Technology, Engineering, and Mathematics (STEM) field. Here, we discuss the design of an introductory mindfulness program that provides the STEM community with a broad overview of various mindfulness methods. We also discuss delivery implementation methods and other considerations when designing mindfulness programming. This article provides resources for those interested in incorporating mindfulness into the STEM field, especially within the university setting.

Spectral analysis for weighted extended Vicsek polygons

Because of the application of fractal networks and their spectral properties in various fields of science and engineering, they have become a hot topic in network science. Moreover, deterministic weighted graphs are widely used to model complex real-world systems. This paper studys weighted extended Vicsek polygons W(G m,t ), which are based on the Vicsek fractal model and the extended fractal cactus model. The structure of these polygons is controlled by the positive integer coefficient m and the number of iterations t. From the construction of the graph, we derive recursive relations of all eigenvalues and their multiplicities of normalized Laplacian matrices from the two successive generations of the weighted extended Vicsek polygons. Then, we use the spectra of the normalized Laplacian matrices to study Kemeny’s constant, the multiplicative Kirchhoff index, and the number of weighted spanning trees and derive their exact closed-form expressions for the weighted extended Vicsek polygons. The above results help to analyze the topology and dynamic properties of the network model, so it has potential application prospects.

Nanofibrous Material-Reinforced Printable Ink for Enhanced Cell Proliferation and Tissue Regeneration

The three-dimensional (3D) printing of biomaterials, cells, and bioactive components, including growth factors, has gained interest among researchers in the field of tissue engineering (TE) with the aim of developing many scaffolds to sustain size, shape fidelity, and structure and retain viable cells inside a network. The biocompatible hydrogel employed in 3D printing should be soft enough to accommodate cell survival. At the same time, the gel should be mechanically strong to avoid the leakage of cells into the surrounding medium. Considering these basic criteria, researchers have developed nanocomposite-based printable inks with suitable mechanical and electroconductive properties. These nanomaterials, including carbon family nanomaterials, transition metal dichalcogenides, and polymeric nanoparticles, act as nanofillers and dissipate stress across polymeric networks through their electroactive interactions. Nanofiber-reinforced printable ink is one kind of nanocomposite-based ink that comprises dispersed nanofiber components in a hydrogel matrix. In this current review, we compile various TE applications of nanofiber-reinforced printable ink and describe the 3D-printing parameters, classification, and impact of cross-linkage. Furthermore, we discuss the challenges and future perspectives in this field.

High‐Resolution 3D Printing of Dual‐Curing Thiol‐Ene/Epoxy System for Fabrication of Microfluidic Devices for Bioassays

AbstractThe customized processing of polymer materials in the microscale by high‐resolution 3D printing provides an easy access to advanced applications in the fields of optics, microfluidics, tissue engineering, and life science. However, the 3D printing of enclosed structures in the scale of tens of microns such as closed microfluidic channels remains a challenge as channel structures often are clogged by residual cured resin. Dual‐curing systems based on off‐stoichiometric thiol‐ene and thiol‐ene/epoxy chemistry are well‐known for adhesive‐free bonding in the fabrication of cast or injection molded microfluidic devices. Herein, the first high‐resolution stereolithography 3D printing of a dual‐curing thiol‐ene/epoxy system in the microscale for the fabrication of customized microfluidic devices is presented. In the first curing step, by high‐resolution 3D printing open microfluidic structures are produced. Consecutively, the microchannels are sealed by adhesive‐free dry bonding upon thermal initiation, producing well‐controlled structures with channel sizes down to 80 µm. Before bonding, the intermediate material allows for tailored surface modification with biotin, which allows for consecutive immobilization of various biomolecules. A DNA‐bioassay with specific patterning is shown in the sealed chip. The presented work paves the way toward the fabrication of customized microfluidic devices for a large range of specific bioassays.