Hasil untuk "Structural engineering (General)"

M. Ekeberg, Cecilia Lövkvist, Y. Lan et al.

Spatially proximate amino acids in a protein tend to coevolve. A protein's three-dimensional (3D) structure hence leaves an echo of correlations in the evolutionary record. Reverse engineering 3D structures from such correlations is an open problem in structural biology, pursued with increasing vigor as more and more protein sequences continue to fill the data banks. Within this task lies a statistical inference problem, rooted in the following: correlation between two sites in a protein sequence can arise from firsthand interaction but can also be network-propagated via intermediate sites; observed correlation is not enough to guarantee proximity. To separate direct from indirect interactions is an instance of the general problem of inverse statistical mechanics, where the task is to learn model parameters (fields, couplings) from observables (magnetizations, correlations, samples) in large systems. In the context of protein sequences, the approach has been referred to as direct-coupling analysis. Here we show that the pseudolikelihood method, applied to 21-state Potts models describing the statistical properties of families of evolutionarily related proteins, significantly outperforms existing approaches to the direct-coupling analysis, the latter being based on standard mean-field techniques. This improved performance also relies on a modified score for the coupling strength. The results are verified using known crystal structures of specific sequence instances of various protein families. Code implementing the new method can be found at http://plmdca.csc.kth.se/.

Walter Nsengiyumva, Shuncong Zhong, Jiewen Lin et al.

Abstract In recent years, composite materials have gained popularity in numerous high-tech and engineering applications, owing to their outstanding physico-mechanical properties. They were initially used as fairings/reinforcements for different structures, but their application has recently shifted from general-purpose structures to primary and secondary load-bearing structures, where structural failures would result in catastrophic safety repercussions. This increased scope of application has prompted the introduction of composite structures featuring significant thickness and complexity. As such, the application of nondestructive testing and evaluation (NDT&E) to localize and characterize flaws in these materials at their incipient initiations could save resources, eliminate unplanned breakdown, and provide a timely window for repair-maintenance activities. Therefore, this paper critically reviews the recent advances in NDT&E as applied to the inspection of thick composite parts and sandwich structures (composites with a thickness ≥15 mm) and determines possible research prospects to address the limitations of the current technologies. A brief overview of defects/damage occurring in composite structures is provided followed by the main NDT&E techniques used to detect these flaws. Since there are many NDT&E techniques available, this work limits its scope on techniques that focus on the detection, localization, and characterization of flaws in thick composites and sandwich structures.

Bixia Zhou, Xulei Jiang, Xinxin Zhou et al.

Currently, the clinical treatment of critical bone defects attributed to various causes remains a great challenge, and repairing these defects with synthetic bone substitutes is the most common strategy. In general, tissue engineering materials that mimic the structural, mechanical and biological properties of natural bone have been extensively applied to fill bone defects and promote in situ bone regeneration. Hydrogels with extracellular matrix (ECM)-like properties are common tissue engineering materials, among which methacrylate-based gelatin (GelMA) hydrogels are widely used because of their tunable mechanical properties, excellent photocrosslinking capability and good biocompatibility. Owing to their lack of osteogenic activity, however, GelMA hydrogels are combined with other types of materials with osteogenic activities to improve the osteogenic capability of the current composites. There are three main aspects to consider when enhancing the bone regenerative performance of composite materials: osteoconductivity, vascularization and osteoinduction. Bioceramics, bioglass, biomimetic scaffolds, inorganic ions, bionic periosteum, growth factors and two-dimensional (2D) nanomaterials have been applied in various combinations to achieve enhanced osteogenic and bone regeneration activities. Three-dimensional (3D)-bioprinted scaffolds are a popular research topic in bone tissue engineering (BTE), and printed and customized scaffolds are suitable for restoring large irregular bone defects due to their shape and structural tunability, enhanced mechanical properties, and good biocompatibility. Herein, the recent progress in research on GelMA-based composite hydrogel scaffolds as multifunctional platforms for restoring critical bone defects in plastic or orthopedic clinics is systematically reviewed and summarized. These strategies pave the way for the design of biomimetic bone substitutes for effective bone reconstruction with good biosafety. Graphical Abstract This review provides novel insights into the development and current trends of research on GelMA-based hydrogels as effective bone tissue engineering (BTE) scaffolds for correcting bone defects, and these contents are summarized and emphasized from various perspectives (osteoconductivity, vascularization, osteoinduction and 3D-bioprinting). In addition, advantages and deficiencies of GelMA-based bone substitutes used for bone regeneration are put forward, and corresponding improvement measures are presented prior to their clinical application in near future (created with BioRender.com).

S. Qiu, G. Zhu

Xiaowei Ma, Jiachen Guo, Lin Zhang et al.

This paper details an integrated experimental and numerical analysis of the structural performance of axially compressed Q1100 ultra-high strength steel (UHSS) welded box-section stub columns. Material characterisation was performed through tensile tests on tensile coupons extracted from both the base metal and the heat-affected zone (HAZ) to obtain their constitutive relationships. Meticulous quantification of initial geometric imperfections and residual stress fields, comprising both membrane and bending components, was carried out, with measured peak tensile residual stresses near the weld seam attaining 37.2% of the nominal yield strength. All nine stub column specimens failed by local buckling, and a clear inverse trend was observed between the normalised axial strength and the plate width-to-thickness ratio. A high-fidelity finite element (FE) model was established, integrating the measured imperfections, residual stress patterns, and the strength reduction in the HAZ. The accuracy of FE model was confirmed through rigorous validation against test results. A subsequent parametric analysis expanded the data over a wide range of cross-section slenderness, enabling a thorough evaluation of structural local buckling behaviour. Comparisons with predictions from major design codes, such as EN 1993-1-1, AISC 360, and AS 4100, showed that these standards are consistently conservative for the studied UHSS sections, with the conservatism being most pronounced for stocky cross-sections. This research provides essential insights and suggests practical refinements to bridge existing gaps in design codes for UHSS structural applications.

Hadi Amarloo, Mohammad Noaman, Su-Peng Yu et al.

Abstract Rydberg atom-based sensors use atoms dressed by lasers to detect and measure radio frequency electromagnetic fields. The absorptive properties of the atomic gas, configured as a Rydberg atom-based sensor, change in the presence of a radio frequency electromagnetic field. While these sensors are reasonably sensitive, the best conventional radio frequency sensors still outperform Rydberg atom-based sensors with respect to sensitivity. One approach to increase the sensitivity of Rydberg atom-based sensors is to engineer the vapor cell that contains the atomic gas. In this work, we introduce a passive, all-dielectric amplifier integrated into a Rydberg atom-based sensor vapor cell. The vapor cell is a combination of a slot waveguide and a photonic crystal. The structural features of the vapor cell yield a power amplification of ~24 dB. The radio frequency electromagnetic field is coupled adiabatically into the slot waveguide and slowed to increase the interaction between the radio frequency field and the atoms to effectively amplify the incoming signal, i.e., increase the Rabi frequency on the radio frequency transition. The work shows the utility of vapor cell engineering for atom-based quantum technologies and paves the way for other such devices.

Hind Al-Ahmed, Khaled Alshaketheep, Ahmad Shajrawi et al.

This paper seeks to discuss green marketing strategies that are becoming particularly popular as organizations strive to boost sustainability and accounting performance. As well as, exploring the moderating role of AI in green marketing strategy's impact on firms’ accounting performance (return on assets, return on equity, and profit margins). A parallel research approach was used: a survey of firms’ annual reports and content analysis of interviews with marketing managers of different companies operating in different industries. It concluded that green marketing practices, in particular the use of AI, greatly enhance the competitive performance and accounting capabilities of a company. As a powerful technology, AI can be employed to enhance green marketing practice and enable the organization to achieve sustainable growth. This research bridges the gap between sustainability and technology and demonstrates how the relationship between accounting performance and green marketing is moderated using AI in order to maintain competitor and financial advantages. This research advises organizations to emphasize being sustainable and make greater investments in AI development to improve their marketing strategy. These two concerns with sustainability and technology adoption can determine the success of organizations in the long term.

Fulya Gökşen, Çağatay Takva, Yenal Takva et al.

Earthquakes have great damage potential and importance in risk management and structural engineering, causing fires in buildings such as residences and commercial spaces. Post-earthquake fires (PEF) are secondary disasters that can cause material and moral destruction and loss of life. Similar to natural disasters, they show the time of occurrence and possible scenarios in places. This study aims to analyse and examine what precautions can be taken to prevent or minimize PEF through risk assessment. In this study, a literature review was conducted with the tracking method, focusing on examples from the world where the fires that occur as a secondary effect of the earthquake can cause devastating damages and significant disasters, and inferences are made by classifying the data obtained. Many factors, such as gas leaks due to earthquakes, cracks in pipelines, and short circuits in electrical installations, can cause fires. In addition, flammable liquid or combustible gas emissions and fire protection disturbances create significant fire hazards after earthquakes. In this paper, in which the causes and consequences of fires are analysed, risks, the evaluation process depending on the risks, the precautions that can be taken according to the situations that the risks will cause, and the models developed are emphasized. The research is a reference study with the expectation that there will be an increase in the number of studies examining experimental and physical PEF models.

Paresh Kulkarni, Satish Chinchanikar

Soft computing techniques, with their self-learning capabilities, fuzzy principles, and evolutionary computational philosophy, are being increasingly utilized in modeling complex machining processes. This study develops artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models to predict cutting force, surface roughness, and tool life during Inconel 718 turning with a hybrid nanofluid under minimum quantity lubrication. The hybrid nanofluid was created by combining 50�50% multi-walled carbon nanotubes and aluminum oxide nanoparticles with vegetable-based palm oil. ANFIS and ANN models were constructed with data from well-designed machining trials. The ANFIS model predicted machining performance using fuzzy logic, whereas the ANN model employed a feedforward neural network design. The results showed that both models were able to accurately predict the machining performance. However, ANFIS outperforms ANN in terms of accuracy, with prediction errors of 4.47% and 10.97% for surface roughness, and 6.05% and 9.86% for tool life, respectively. However, the accuracy of cutting force prediction was slightly higher with the ANN. This shows that ANFIS could be a better option for forecasting the machining performance while turning Inconel 718. However, this study suggests further investigation into ANFIS modeling, with a focus on membership function parameter optimization through hybrid optimization techniques.

Xue‐Hua Ding, Li‐Zhi Wang, Yong‐Zheng Chang et al.

Abstract The emergence of flexible organic crystals changed the perception of molecular crystals that were regarded as brittle entities over a long period of time, and sparked a great interest in exploring mechanically compliant organic crystalline materials toward next‐generation smart materials during the past decade. Schiff base compounds are considered to be one of the most promising candidates for flexible organic crystals owing to their easy synthesis, high yield, stimuli responsiveness and good mechanical properties. This paper gives an overview of the recent development of Schiff base flexible organic crystals (including elastic organic crystals, plastic organic crystals, and flexible organic crystals integrating elasticity and plasticity) from serendipitous discovery to design strategies and versatile applications such as stimuli responses, optical waveguides, optoelectronic devices, biomimetic soft robots, and organic photonic integrated circuits. Notably, atomic force microscopy‐micromanipulation technique has been utilized to bring the multifunctional applications of flexible organic crystals from the macroscopic level to the microscopic world. Since understanding mechanical flexibility at the molecular level through crystal engineering can assist us to trace down the structural origin of mechanical properties, we focus on the packing structures of various Schiff base flexible organic crystals driven by non‐covalent intermolecular interactions and their close correlation with mechanical behaviors. We hope that the information given here will help in the design of novel flexible organic crystals combined with other unique properties, and promote further research into the area of mechanically compliant organic crystalline materials toward multifunctional applications.

“Prestress Technology” Editorial Office

Mohamed Hafez Fahmy Aly, Islam Mahmoud Abou El-Naga, Ahmed Abdul Hay Soliman et al.

Abstract Slab track is a recent technology used to cope up with the train high axle loads and speed, it has replaced the ballast material in classical ballasted track with either reinforced concrete slab or asphalt layer in order to increase both stability and durability of the railway lines. This paper aims to propose a new slab track design model which can be used to design/analyze any slab track systems under vertical loads using AREMA and EN specifications for high-speed systems (300 kmph). This model has been validated through experimental work held in Heriot-Watt University then applied to the most common slab track systems (BÖGL, Shinkansen, and RHEDA 2000) in the world. The standard section of RHEDA 2000 slab track has shown the best structural performance and efficiency compared with BÖGL and Shinkansen standard sections regarding the rail deflection, stresses of rails, and stress of replacement soil layer and subgrade soil. This paper has concluded the rail deflection is the most critical factor for the slab track design regarding EN specifications while the subgrade stresses is the vital criterion concerning AREMA specifications. Furthermore, EN-Specifications are found to be more conservative than AREMA specifications for the design or analysis of all the slab track types.

Nicoleta Elisabeta Pascu, Victor Adir, George Adir et al.

This paper is about very interesting elements found in the daily life: signs, symbols and pictograms. From the sunrise till sunset, the people is surrounded by these things which may help to have an easier life. We have learned a lot about the capacity of these elements to act as a main guide, using many times just graphics. We have understood that signs, symbols and pictograms must catch the people`s attention. These ones have to guide, allow, warn or forbidden something, inform or assure the final destination for a traveler. We have identified the typology of these graphic representations and the working process to create pictograms. Some findings and results are explained in the paper.

rusul fadhil, Ismail Sh. Hburi, Hassanein Fleih et al.

An Image with high-resolution is associated with huge size data space because each information of the image is arranged into 2D picture elements' values, each of them containing its associated value of the RGB bits. The depiction of picture data makes it challenging to distribute picture files using the Internet. For Internet users, the time it takes to upload and download photos has all time been the main concern. A high-resolution image takes up more storage space, in addition to the data transit difficulty. The Analysis of Principal Component, or PCA for a brief notation, is a mathematical approach utilized to lessen the data dimensionality. It extracts the main pattern of a linear system using the factoring matrices technique.  The objectives of this paper are to see how effective PCA is in reducing digital picture features and to investigate the (feature-reduced) images’ quality on comparison with different values of the variance. As per the synthesizing of the initial research, the dimension or size reduction technique through the Analysis of Principal Component typically involves of 4-important steps: (1) picture-data normalizing (2) matrix of the covariance calculating using picture-data. (3) discovering the picture-data projection (with fewer number of features) to a new basis use the Single Value Decomposition technique (SVD) (4) determining the picture-data projection (with fewer number of characteristics) to a new basis. According to testing results, the PCA approach considerably decreases the size of picture data while sustaining the original picture’s fundamental properties. This approach reduced file size by 35.3 percent for the best feature lowered quality. The upload time of picture files through the Internet has substantially improved, particularly for mobile device downloads.

A. Elsafty, H. Sayad, I. Shaaban

This work examines engineering education in Egypt provided by state (government funded) universities. There have been concerns from all stakeholders about the graduates’ knowledge and skills. The chronic problems with higher education in Egypt in general have been previously reported in the Literature, but this paper provides insights form engineering academics with many years of experience in Egyptian engineering education and a fresh look from a business perspective at the phenomenon. In this manuscript, the institutions are analyzed using the integrated business anatomy model, in order to identify the underlying causes of the problems observed. The structural, operational and environmental (both external and internal) challenges that lead to the current status are clearly detected. The analysis highlighted several constraints that hinder radical reforms. Amongst these constraints is the legal and organizational framework in which the state funded universities operate. Other social, technological and economic factors also play important parts. The recipe for improvement provided by the authors has taken all these elements into consideration. This work hopes to provide focus and direction for future reform efforts.

Jie Li

Murad A. Qurishee, Weidong Wu, Babatunde Atolagbe et al.

With cutting edge deep learning breakthrough, numerous innovations in many fields including civil engineering are stimulated. However, a fundamental issue that civil engineering research community currently facing is lack of a publicly available, free, quality-controlled and human-annotated large dataset that supports and drives civil engineering deep learning research and applications on such as intelligent transportation including connected vehicle, structural health monitoring, and bridge inspection. This paper is a general discussion about demanding needs and construction of a long-anticipated dataset for researchers and engineers in civil engineering and beyond for providing critical training, testing and benchmarking data. The establishment of such a free dataset will remove a major hurdle and boost deep learning research in civil engineering and we hope this work will urge researchers, engineers, government agencies and even computer scientists to work together to start building such datasets. A framework has been developed for the proposed database. Also, some pilot study databases were developed for concrete crack detection, pavement crack detection using normal and infrared thermography, as well as pedestrian and bicyclist detection. A convolution neural network model called Faster RCNN was deployed to check the detection accuracy and a 98% detection accuracy of the proposed datasets was obtained.