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Found 6515 publications
Investigating the Impact of Varying Sand Content on the Physical Characteristics of Expansive Clay Soils from Syria
Publication Name: Geotechnical and Geological Engineering
Publication Date: 2024-06-01
Volume: 42
Issue: 4
Page Range: 2675-2691
Description:
Expansive clayey soils often pose challenges for construction projects due to their low bearing capacity, swelling, and shrinkage properties. While previous research has explored additives to enhance these soils’ properties, the potential of sand remains underexplored. This study investigates the impact of varying sand percentages on expansive clayey soils’ consistency, compaction, and permeability. This study examines how adding different percentages of sand influences the physical properties of expansive clayey soils. Laboratory tests involved systematic testing of texture, compaction, and permeability. Findings reveal a notable improvement in the physical properties of the soil with the addition of sand. Results from the laboratory tests provided data for empirical equations that facilitate the prediction of soil properties based on the sand content. The enhancement in soil properties underscores the potential of sand as an additive for expansive clayey soils. The empirical equations presented here provide practical benefits to geotechnical engineers and practitioners engaged in construction projects involving these soils, offering them valuable insights into the benefits of sand additives to improve physical characteristics. The insights gained from this research hold promising prospects for improving construction practices and addressing the challenges associated with these soils.
Open Access: Yes
Numerical study to investigate the effect of sample size sensitivity on porous materials with respect to different geometrical parameters
Publication Name: Results in Materials
Publication Date: 2024-06-01
Volume: 22
Issue: Unknown
Page Range: Unknown
Description:
Porous materials play a crucial role in various industrial applications, where precise determination of geometric parameters like dynamic tortuosity, as well as viscous and thermal characteristic lengths, is essential for optimizing acoustical performance. Up to this point, there has been no published size sensitivity test that recommends the ideal sample size for analyzing these parameters in an industrial environment. The present article analyzes different reconstructed porous material samples using conventional CFD and coupled FEA-CFD simulations and suggests optimal sample size and specific simulation setup optimized for industrial purposes, which grant high accuracy and reasonable computational cost. The present paper analyzed several samples, which were reconstructed by micro-CT and analyzed in Star-CCM+ simulation environment. It was found that the optimal sample size (1.5×1.5×1.5 mm or 2.5×2.5×2.5 mm) is different for specific average pore sizes. It was proven through various numerical simulations based on reconstructed porous material samples that running only one coupled CFD-FEM simulation is satisfactory to directly determine all investigated parameters. It was demonstrated that the computationally demanding numerical model could be simplified in specific cases using a rigid body and highlight the limitations.
Open Access: Yes
Application of Digitalisation in Regulated Environments for Predictive Failure Modelling
Publication Name: IFAC Papersonline
Publication Date: 2024-06-01
Volume: 58
Issue: 8
Page Range: 222-227
Description:
This paper explores the challenges of applying digitalization in regulated pharmaceutical manufacturing environments. A large range of complex equipment including pumps, valves and vessels may be associated with pharmaceutical batch production processes. Maintenance of such equipment are often based on reactive or preventative strategies which are not always effective and not completely successful in preventing costly downtime or scrap. This research examines how predictive maintenance Key Performance Indicators (KPIs) can be developed through data capture using non-intrusive sensors and their integration with production data derived from Programmable Logic Controllers (PLCs), Enterprise Resource Planning (ERP) systems, and Product Lifecycle Management (PLM) systems. The significance of regulation and the associated challenges in applying digitalization within such a highly regulated environment are also considered. This research aims to shed light on the potential benefits and challenges of implementing digital solutions for predictive maintenance in regulated manufacturing environments to contribute to the enhancement of operational efficiency and product quality while reducing costs due to outages.
Open Access: Yes
Introduction of a Novel Structure for a Light Unmanned Free Balloon’s Payload: A Comprehensive Hybrid Study
Publication Name: Sensors
Publication Date: 2024-05-01
Volume: 24
Issue: 10
Page Range: Unknown
Description:
Payloads for light unmanned free balloons must meet several safety requirements such as being able to protect the inner electronics in order to extract scientific data and to reduce the chance of inflicting personal injury in case of an accidental fall. This article proposes a novel payload structure, which exhibits the form of a dodecahedron. The actual form was determined by carrying out theoretical drop tests on different polyhedrons using the finite element method (FEM). From the simulations, it could be deduced that the dodecahedron was the optimal choice, since the duration of the impact was longer, while the impact force was slightly lower. The payload was produced by additive technologies; therefore, after performing tensile tests on probable materials, PLA was selected as the optimal candidate. The theoretical results about the dodecahedron’s ability were validated by laboratory and real-life drop tests, where the new payload was subjected to 56% less impact force under a 78% longer collision time compared to a classic, rectangular cuboid design. Based on these tests, it was demonstrated that the new structure is safer and it is applicable.
Open Access: Yes
DOI: 10.3390/s24103182
Impacts of nuclear energy, greener energy, and economic progress on the load capacity factor: What we learn from the leading nuclear power economies?
Publication Name: Geoscience Frontiers
Publication Date: 2024-05-01
Volume: 15
Issue: 3
Page Range: Unknown
Description:
The worldwide tremor of environmental degradation commonly represents the escalation of emissions levels and ecological footprints that harm the planet's biocapacity. This is because of using gigantic non-renewable energy resources, urbanization stream and massive economic activities in the major industrialized nations. Amid this situation, we investigate the influence of disaggregated energy measures, e.g., renewable, and nuclear energy, income growth and urbanization on the load capacity factor (biocapacity divided by the ecological footprint) of major nuclear power countries, such as France, the USA, Canada, China, and Russia during 1990–2021. To this end, we utilize the CS-ARDL procedure because of the endogeneity, common correlation, non-stationarity in data and heterogeneity in panel units. We contribute to considering the supply side dynamic of environmental degradation parameter, the load capacity, from the perspective of the top nuclear power nations that deviates our analysis from the prevailing scholarly works. However, our findings confirm a significantly positive impact of renewable and nuclear energy on the load capacity factor in improving environmental safety. Besides, economic growth and urbanization negatively affect the load capacity dynamics in spurring environmental degradation. Our findings are robust across an alternative estimation technique, namely the Dumitrescu and Hurlin (DH) causation analysis. Therefore, we recommend formulating pragmatic policies to deter the detrimental effects of income and urbanization by properly utilizing sustainable energy resources to conserve the natural environment.
Open Access: Yes
Water Droplet Collison and Erosion on High-Speed Spinning Wheels
Publication Name: SAE International Journal of Engines
Publication Date: 2024-04-04
Volume: 17
Issue: 5
Page Range: Unknown
Description:
The water droplet erosion (WDE) on high-speed rotating wheels appears in several engineering fields such as wind turbines, stationary steam turbines, fuel cell turbines, and turbochargers. The main reasons for this phenomenon are the high relative velocity difference between the colliding particles and the rotor, as well as the presence of inadequate material structure and surface parameters. One of the latest challenges in this area is the compressor wheels used in turbochargers, which has a speed up to 300,000 rpm and have typically been made of aluminum alloy for decades, to achieve the lowest possible rotor inertia. However, while in the past this component was only encountered with filtered air, nowadays, due to developments in compliance with tightening emission standards, various fluids also collide with the spinning blades, which can cause mechanical damage. One such fluid is the condensed water in the low-pressure exhaust gas recirculation channel (LP-EGR) formulated at cold starts and low-speed high load conditions. This kind of design has been developed to reduce nitrogen oxide emissions and is used in both gasoline and diesel engines. This article presents a state-of-the-art review of this WDE process, focusing on the formation of the condensed water before the compressor wheel, summarizing the influencing factors of WDE and the effects of the damage including using component testbench experiences and simulation methodologies. Inspection possibilities such as high-speed camera measurement and vibration analysis are also an important part of the document.
Open Access: Yes
Enhancing seismic assessment and risk management of buildings: A neural network-based rapid visual screening method development
Publication Name: Engineering Structures
Publication Date: 2024-04-01
Volume: 304
Issue: Unknown
Page Range: Unknown
Description:
Some of the existing buildings are designed based on lower design standards or even without considering seismic design standards. Recent earthquakes have further highlighted the vulnerability of these buildings when subjected to severe seismic activity. Consequently, it has become imperative to conduct seismic vulnerability assessments of the existing building stock. Therefore, the assessment of the existing building stock is required through the utilization of Rapid Visual Screening (RVS) methods. However, the existing conventional RVS methods used in seismic building assessments have shown limited accuracy. Furthermore, because these methods were developed based on expert opinions and/or due to access limitations to detailed assessment-based generated data used for their development, further enhancing them is challenging. To address these limitations, a new RVS method, which leverages Neural Networks (NN) and building-specific parameters, for reinforced concrete, adobe mud, bamboo, brick, stone, and timber buildings has been proposed in this study. Unlike conventional methods that rely on site seismicity class, the developed data-driven approach incorporates building-specific parameters such as the fundamental structural period and building spectral acceleration. The developed RVS method is specifically tailored to analyze diverse types of buildings in regions with varying seismicity risks, all in preparation for an impending earthquake. In this study, the developed RVS method demonstrated a promising 68% test accuracy, effectively representing the building performance against earthquakes. These findings illustrate the potential of the developed NN based RVS method in assessing existing buildings, thereby mitigating potential loss of life and property during imminent earthquake and alleviating the associated economic burden. Furthermore, this study introduces a new RVS method that can pave the way for future advancements in the field of seismic vulnerability assessment of existing buildings.
Open Access: Yes
Brake Disc Deformation Detection Using Intuitive Feature Extraction and Machine Learning
Publication Name: Machines
Publication Date: 2024-04-01
Volume: 12
Issue: 4
Page Range: Unknown
Description:
In this work we propose proof-of-concept methods to detect malfunctions of the braking system in passenger vehicles. In particular, we investigate the problem of detecting deformations of the brake disc based on data recorded by acceleration sensors mounted on the suspension of the vehicle. Our core hypothesis is that these signals contain vibrations caused by brake disc deformation. Since faults of this kind are typically monitored by the driver of the vehicle, the development of automatic fault-detection systems becomes more important with the rise of autonomous driving. In addition, the new brake boosters separate the brake pedal from the hydraulic system which results in less significant effects on the brake pedal force. Our paper offers two important contributions. Firstly, we provide a detailed description of our novel measurement scheme, the type and placement of the used sensors, signal acquisition and data characteristics. Then, in the second part of our paper we detail mathematically justified signal representations and different algorithms to distinguish between deformed and normal brake discs. For the proper understanding of the phenomenon, different brake discs were used with measured runout values. Since, in addition to brake disc deformation, the vibrations recorded by our accelerometers are nonlinearly dependent on a number of factors (such as the velocity, suspension, tire pressure, etc.), data-driven models are considered. Through experiments, we show that the proposed methods can be used to recognize faults in the braking system caused by brake disc deformation.
Open Access: Yes
Investigating the Factors Influencing the Strength of Cold-Formed Steel (CFS) Sections
Publication Name: Buildings
Publication Date: 2024-04-01
Volume: 14
Issue: 4
Page Range: Unknown
Description:
The utilization of cold-formed steel (CFS) sections in construction has become widespread due to their favorable attributes, including their lightweight properties, high strength, recyclability, and ease of assembly. To ensure their continued safe and efficient utilization, this review provides a comprehensive investigation into the factors influencing the strength of CFS members. This analysis encompasses design codes, prediction methodologies, material properties, and various structural configurations. This review uncovers discrepancies among existing design codes, particularly noting conservative predictions in AISI and AS/NZS standards for composite and built-up sections. Additionally, the effectiveness of prediction methods such as the direct strength method and effective width method varies based on specific structural configurations and loading conditions. Furthermore, this review delves into recent advancements aimed at enhancing fire resistance, connection design, and the composite behavior of CFS structures. The influence of factors such as eccentricity, sheathing materials, and bolt spacing on structural performance is also examined. This study underscores the crucial role of accurate prediction methods and robust design standards in ensuring the structural integrity and safety of CFS constructions. Through a comparative analysis, it is revealed that AISI and AS/NZS standards exhibit conservatism in predicting nominal buckling loads compared to experimental data. Conversely, a non-linear finite element analysis demonstrates a strong correlation with laboratory tests, offering a more accurate prediction of nominal buckling capacity. Overall, this review offers comprehensive insights aimed at optimizing CFS structural design practices. By identifying key areas for future research and development, this work contributes to the ongoing advancement of safe and efficient CFS construction applications.
Open Access: Yes
