5,684 research outputs found
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Mathematical Problems in Rock Mechanics and Rock Engineering
With increasing requirements for energy, resources and space, rock engineering projects are being constructed more often and are operated in large-scale environments with complex geology. Meanwhile, rock failures and rock instabilities occur more frequently, and severely threaten the safety and stability of rock engineering projects. It is well-recognized that rock has multi-scale structures and involves multi-scale fracture processes. Meanwhile, rocks are commonly subjected simultaneously to complex static stress and strong dynamic disturbance, providing a hotbed for the occurrence of rock failures. In addition, there are many multi-physics coupling processes in a rock mass. It is still difficult to understand these rock mechanics and characterize rock behavior during complex stress conditions, multi-physics processes, and multi-scale changes. Therefore, our understanding of rock mechanics and the prevention and control of failure and instability in rock engineering needs to be furthered. The primary aim of this Special Issue “Mathematical Problems in Rock Mechanics and Rock Engineering” is to bring together original research discussing innovative efforts regarding in situ observations, laboratory experiments and theoretical, numerical, and big-data-based methods to overcome the mathematical problems related to rock mechanics and rock engineering. It includes 12 manuscripts that illustrate the valuable efforts for addressing mathematical problems in rock mechanics and rock engineering
Synthetic Aperture Radar (SAR) Meets Deep Learning
This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
Advances in Binders for Construction Materials
The global binder production for construction materials is approximately 7.5 billion tons per year, contributing ~6% to the global anthropogenic atmospheric CO2 emissions. Reducing this carbon footprint is a key aim of the construction industry, and current research focuses on developing new innovative ways to attain more sustainable binders and concrete/mortars as a real alternative to the current global demand for Portland cement.With this aim, several potential alternative binders are currently being investigated by scientists worldwide, based on calcium aluminate cement, calcium sulfoaluminate cement, alkali-activated binders, calcined clay limestone cements, nanomaterials, or supersulfated cements. This Special Issue presents contributions that address research and practical advances in i) alternative binder manufacturing processes; ii) chemical, microstructural, and structural characterization of unhydrated binders and of hydrated systems; iii) the properties and modelling of concrete and mortars; iv) applications and durability of concrete and mortars; and v) the conservation and repair of historic concrete/mortar structures using alternative binders.We believe this Special Issue will be of high interest in the binder industry and construction community, based upon the novelty and quality of the results and the real potential application of the findings to the practice and industry
Modeling and Simulation in Engineering
The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering
RELIABILITY ANALYSIS OF OPEN PIT SLOPE: CASE STUDY OF BOZSHAKOL MINE
The increase in the probability of failures in pit slope design are influenced by the presence of the inherent variability of rock mass properties. This could result in uncertainties during geotechnical design. Although, utilizing conservative approach such as overdesigning to account for the worst-case scenario, can effectively address these issues in practice. Despite this, one of the approach’s shortcomings is that it is quite expensive. In order to tackle these difficulties, it is crucial to devise a probabilistic technique that allows for thorough consideration of these uncertainties associated with geotechnical parameters when designing mine pit. With this in mind, the objective of this study is to execute the reliability analysis of the Bozshakol mine pit slope design. This method would involve utilising advanced numerical models, such as Slide 2 and RS 2 to design selected pit sectors by determining their factor of safety and probability of failure based on the input variables obtained from the case study area. The first-order reliability method was used to analyse the results obtained from the model. Furthermore, the expected outcomes provide a means of addressing these uncertainties and establishing a specific target for the probability of failure in pit slope design. Subsequently, an evaluation was conducted to estimate the reliability indices of geotechnical domains pertaining to the pit sectors. This was accomplished in order to determine the reliability of the pit design and to identify probable risks of unforeseen pit failures that could be addressed in a timely manner
Predicting and Understanding Binding Affinities of Synthetic Anion Receptors
Anion receptors are molecules that can recognise and bind anions. They have applications in organocatalysis, anion sensing and the removal of anions from wastewater. Some anion receptors are also able to transport anions across cell membranes and show promise for the treatment of diseases such as cystic fibrosis and cancer. As such, it is of interest to develop computational methods that can reliably predict the physicochemical properties and anion binding affinities of these molecules. However, efforts to computationally model these molecules are hampered by the sheer size of typical receptors, making them too expensive to treat using accurate quantum chemical methods. Whilst efficient approximations such as local-correlation methods have been developed, the broader accuracy of these methods, particularly in their application to ionic non-covalent systems remains unclear. To address this gap, this thesis has carried out an extensive validation of local-correlation methods, and economical density functional theory (DFT) methods for receptors with different binding motifs. Additionally, multiscale models have also been examined with the view to extending the scope of these methods to model very large anion receptors. DFT methods giving good agreement with highly accurate calculations at a fraction of the cost were identified. The use of semiempirical methods combined with DFT in a multiscale model for calculating anion binding affinities lead to unexpectedly large errors with modest savings of computational time, while some "three-fold corrected" methods show promise in reducing the cost of geometry optimisations of large receptors. These validated protocols were subsequently applied to investigate the structure-binding relationships of a wide range of dual-hydrogen bonding receptors. Notably, different receptor motifs were found to have different conformational preferences, which could explain why experimentally, thioureas, thiosquaramides and croconamides show weaker chloride binding affinities than would be expected based on their acidity. The results suggest that pre-organising anion receptors in the conformer that facilitates hydrogen bond formation could be a promising strategy for the development of anion receptors. It is envisaged that these findings will aid in the design and screening of novel anion receptors with increased binding affinity and selectivity
Quantifying the Impacts of Flash Flooding on Dominica’s Material Stocks in Buildings: A GIS-based methodological framework for Small Island States
Economic growth is usually accompanied by extensive extraction of natural resources, especially in developing countries. From a “material-stock-flow-service” perspective, the substantial part (e.g., construction materials) of the extracted natural resources as inflows to a society get accumulated in the built environment as “material stocks” (MS). Depending on the end-use types of their containers, MS provide essential services to a society such as housing, education and transportation. When an environmental hazard strikes, MS lose their functionality due to the destruction of the physical structure of their carriers, resulting in extra construction waste that then must be cleared for recovery. To make a society more resilient to environmental hazards, which is especially important in small island states with limited natural and human resources, the knowledge of exposure of MS to hazard risk is critical.
This research focuses on the quantity and spatial distribution of MS in buildings in the context of intense rainfall-triggered flash flooding in Dominica, a small island state in the Caribbean region. A Geographical Information System (GIS)-based stock-driven methodology is used to quantify four typical types of construction materials: concrete, aggregates, timber, and steel. To quantify exposed MS in buildings to flash flooding, an event-based flood model is used to generate flood inundation extents at the national scale. To investigate the degrees to which the exposed households are susceptible to the impacts of environmental hazards, this research also designs a resident survey to collect social factors contributing to household vulnerability to hazards. For 2020, the total MS in the building sector is estimated at 6,574 kt, equivalent to 91 t per capita, given Dominica’s population of the year. In terms of the distributions of MS in different material categories, concrete accounts for 86% of the total MS in buildings, followed by aggregate at 7%, timber at 4% and steel at 3%. Examining the exposure of MS in buildings to flash flooding, it is found that flood events of larger magnitudes would result in more MS contained in the exposed buildings. For flash flood events with 5-year, 10-year, and 20-year return periods, the numbers of exposed buildings are 2,781, 3,030, and 3,274, respectively, which contain 17%, 18%, and 19% of the total MS in buildings in Dominica. This research demonstrates how to link the results of material stock accounting to flash flood modelling, approaching the concept of socio-economic metabolism from an environmental hazard risk perspective. Knowledge of the quantity and spatial distribution of the exposed MS in buildings can assist local governments in making cost-effective mitigation plans before a hazard event. Although the designed survey was not implemented due to travel restrictions, it is a valuable instrument to collect the information about household vulnerability to environmental hazards, which can help hazard response agencies with more-efficient rescue operations during a hazardous event
Assessment of simplified momentum equations for free surface flows through rigid porous media
In many applications, free surface flow through rigid porous media has to be modeled. Examples refer to coastal engineering applications as well as geotechnical or biomedical applications. Albeit the frequent applications, slight inconsistencies in the formulation of the governing equations can be found in the literature. The main goal of this paper is to identify these differences and provide a quantitative assessment of different approaches. Following a review of the different formulations, simulation results obtained from three alternative formulations are compared with experimental and numerical data. Results obtained by 2D and 3D test cases indicate that the predictive differences returned by the different formulations remain small for most applications, in particular for small porous Reynolds number ReP < 5000. Thus it seems justified to select a simplified formulation that supports an efficient algorithm and coding structure in a computational fluid dynamics environment. An estimated accuracy depending on the porous Reynolds number or the mean grain diameter is given for the simplified formulation.Open Access funding enabled and organized by Projekt DEAL.Peer ReviewedPostprint (published version
Effective Processing and Analysis of Pyrite Concentrate for Industrial Application
In the past two decades a depletion of rich ore materials has led to a decrease in mining productivity and a commensurate increase in costs, as the industry moves to extraction from lower economic ores. To sustain productivity, these inherently higher energy costs and expenditures must be limited by ensuring a deep understanding of ore material composition, and optimization of extraction processes. To this end, this thesis is aimed at optimising the thermal decomposition process of cobalt-rich pyrite sourced from the Thackaringa mine in Broken Hill, being one step in the patented process of sulfur and cobalt extraction by our industry partner Cobalt Blue Holdings (Ltd).
The precursor material to thermal treatment was a pyrite ore concentrate powder constituting a complex multiphase composition, which needed to be characterized in terms of materials present and particle size distribution to identify influences on pyrite thermal decomposition to pyrrhotite. Main phases of pyrite (82.7(3) wt.%), albite (8.3(2) wt.%), quartz (4.96(12) wt.%), pyrrhotite 4M (3.06(10) wt.%), and rutile (0.923(14) wt.%) were identified and found consistent across a 50 kg aliquot obtained from the ‘Pyrite Hill’ subsite. Particle size distribution is broad (1 - 1000 µm), with 50(8) wt.% of the available pyrite manifesting in the 106 - 250 µm range, which was an essential result given how particle size influences the underlying ‘unreacted core’ reaction mechanism associated with pyrite particle decomposition. Powder X-ray diffraction was the primary characterization method used here, whereby a 7-min ball milling preparation technique was optimized to attain reproduceable results within 0.3 wt.% for main phases.
Analysis of thermal treatment indicated no change in gangue phases when treated between 450 - 750 °C. Reaction was seen commencing > 450 °C, though sometimes as low as 300 °C in the special case of reduced particle size and ideal particle-gas interfacing known to improve pyrite decomposition. Activation energies, as in the Arrhenius relation, of 220 - 250(50) kJ/mol and pre-exponential factors between 1.9(2)x1012 - 2.2(2)x1015 sec-1 were obtained and coincide with those found in literature. The progression of reaction is best described by a combination of volumetric shrinking sphere mechanics at 50 - 70 % pyrite conversion when treated between 450 - 550 °C. Enhancing interaction between concentrate particles and carrier gas appears to be greatest influence on thermal decomposition across all experimental designs increasing degree of reaction by 22% and 58% at 600- and 650 °C respectively
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