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Unveiling reservoir dynamics: Influence of mineralogy and rock architecture on petrophysical properties in the Bahariya Formation, Gebel El Dist, Western Desert, Egypt
No full textThis study focuses on the surface analogy of the Bahariya reservoir, located in Gebel El Dist. It includes mineralogical, architectural and petrophysical investigations on its rock types. Three sandstone facies are recognized in the Section, these are quartz arenite, quartz wacke (QW), and mudstone. The radiography diffraction analysis revealed that these facies are composed of quartz, feldspars, dolomite, pyrite, siderite goethite, hematite, clay minerals, glauconite, and gypsum. These minerals represent the grain framework and binding materials of depositional and diagenetic origin. The quartz arenite and the quartz wacke facies represent the two main types of reservoir rocks in the studied section. The conducted laboratory measurements addressed both reservoir rock and fluid properties. The measured petrophysical and fluid properties are helium porosity (f), grain density (rg), gas permeability (k), cementation index (m), saturation (n) exponent. The acoustic velocities and all related Elastic moduli were measured as well. All results were statistically analyzed to obtain several meaningful and/or applicable relationships. The raised petrophysical models relate minerals proportion deduced from the radiography diffraction analysis to the laboratory measured petrophysical properties. These models were found beneficial in reservoir evaluation and confirming the impact of the mineralogy and the rock architecture on these characteristics
Machine learning prediction of climate-induced disaster property damages considering hazard- and community-related attributes
No full textThe rapid increase in the earth’s average temperature has led to an unpreceded surge in the frequency and impacts of Climate-Induced Disaster (CID) across the globe. Subsequently, the costs of CID damages have been growing, and climate action failure and extreme weather events were identified among the most severe global risks over the next decade. Within this context, machine learning-based models are developed to predict CID property damages. The models integrate both community- and hazard-related characteristics as inputs to predict CID property damages. The models are trained and tested using wind-related property damage data in New York State through integrating the Federal Emergency Management Agency’s community data and the National Atmospheric and Oceanic Administration’s hazard data. The current study utilizes different supervised machine learning techniques to develop several CID property damage prediction models. The developed models yielded a coefficient of determination of 0.66, 0.81, 0.72, 0.77, and 0.79 for the regression trees, random forest, bagging, gradient boosting, and extreme gradient boosting respectively. The developed models are expected to aid community stakeholders in developing urban center preparedness plans under CID, which can facilitate strategic urban resilience planning under different climate-induced hazards
Quality of life: quantitative analysis in New Urbanism and LEED-ND certified neighbourhoods
No full textGiven the substantial rise in the urban population, it is imperative to evaluate the quality of life (QoL) in residential communities. New Urbanism (NU) and Leadership in Energy and Environmental Design for Neighborhood Development (LEED-ND) are globally recognised neighbourhood design initiatives that strive to improve QoL. Nevertheless, the degree to which these initiatives effectively enhance QoL remains questionable. This assessment seeks to evaluate the effectiveness of key design practices in these two initiatives by examining the satisfaction levels of residents. It focuses on five key attributes that contribute to enhancing the QoL in residential neighbourhoods: safety, comfort, connectivity, sense of place, and aesthetic appeal. Three neighbourhoods were selected for analysis in the USA. The residents’ questionnaire was utilised as the main tool for the quantitative analysis. The findings revealed a positive association between safety and comfort and overall QoL. NU neighbourhoods showed the highest satisfaction levels, while LEED-ND neighbourhoods had the lowest. Key determinants of QoL were identified as well. The main contribution of this study is to provide insights for enhancing the design parameters of NU and LEED-ND certification to improve QoL and bridge the gap between professionals’ perspectives and residents’ preferences
Graphene oxide nanoribbons (GONRs) as pH-tolerant electrodes for supercapacitors: Effect of charge carriers and loading
No full textGlobal energy consumption is increasing, which is driving up demand for improved energy storage technologies. Supercapacitors have attracted a lot of attention because of their fast charging and discharging rate, high power density, and long-term cycling stability when compared to regular batteries. Graphene oxide nanoribbons (GONRs) have garnered significant attention recently due to their unique ultrathin two-dimensional structure characteristics, making them a promising material for electrochemical energy storage devices such as supercapacitors. This study evaluates the supercapacitance behavior of graphene oxide nanoribbons (GONRs) resulting from oxidative longitudinal unzipping of multi-walled carbon nanotubes (MWCNTs) via chemical oxidation. The following techniques were used to assess the changes: Raman spectroscopy, XPS, TEM, FT-IR, XRD, and EDS. GONR\u27s supercapacitive behavior was thoroughly investigated using different loadings and evaluation systems (three and two-electrode systems) in a range of media (H2SO4, KOH, Li2SO4, and K2SO4). GONRs demonstrated good stability, maintaining ≈ 100 % of their efficiency and capacitance at a high current density of 10 A/g even after 10,000 cycles, a broad potential window (up to 1.7 V), and a relatively high capacitance (approximately 400–800 F/g) in all tested electrolytes making it a universal electrode suitable for all types of aqueous-based electrolytes. The effects of charge carriers, electrolyte pH, and material loading are found to have a significant impact on the specific capacitance of GONRs. As a cationic charge carrier, H+ is found to be superior to Li+ and K+, with Li+ and K+ not significantly different. However, it is discovered that as an anionic charge carrier, OH− is superior to SO42−. Overall, H2SO4 was discovered to be the best electrolyte for GONRs, even at high material loading, because it recorded the highest supercapacitance in both two- and three-electrode systems, using a combination of electrical double layer and pseudo-capacitive mechanisms. Increasing the loading of the GONRs is found to reduce their capacitance, and hence further modifications to prevent the GONRs stacking are needed. The reported specific capacitance for the highly loaded GONRs is higher than that of the previously reported values for GO or RGO
Simulation Model for Optimizing Heavy Equipment Among Multiple Concurrent Projects
No full textThe efficient management of resources is a significant challenge for construction companies, particularly when allocating heavy equipment across multiple concurrent projects. Heavy equipment accounts for a substantial portion of a project\u27s direct costs and is often limited due to its high price. Program managers must make crucial decisions about which projects to allocate owned equipment to and which to rent equipment for, with incorrect decisions resulting in high idle rates for owned equipment and higher costs due to equipment rental. To address this issue, a simulation model was developed to simulate multiple projects concurrently and identify the necessary resources, particularly heavy equipment. The model optimized the allocation of resources between rented and owned equipment based on various factors, including original value, depreciation period, storage fees, idle rates, maintenance fees, and transportation fees. The model will also help construction companies make informed decisions about investing in new equipment and increasing the number of existing equipment. The simulation model was built using AnyLogic software and automatically modeled on-site activities and their required resources based on user inputs in an Excel file. The user inputs the necessary costs of owned and rented equipment, and the model simulates the projects based on their schedules and optimizes the allocation of required resources. The model aimed to assist construction managers and companies in managing their resources, especially those that have a high impact on the direct cost of the project. Ultimately, the model aimed to minimize equipment costs across the program or company as a whole rather than just on a project-by-project basis
Prototyping of compliant grippers using FFF and TPU
No full textPurpose: The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters. Design/methodology/approach: After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated. Findings: The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes. Research limitations/implications: The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged. Originality/value: This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments
Analysis of efficient VOCs gas detection SAW sensor based on ZnO/diamond/Si multilayered structure
No full textThis study investigates the Surface Acoustic Wave (SAW) characteristics of gas sensor devices based on the ZnO/Diamond/Si layered structure, utilizing Finite Element Method (FEM) simulations through the Comsol Multiphysics package. Analysis of device performance, including phase velocities, electromechanical coupling coefficient (K2), and reflectivity, is conducted for both Rayleigh and Sezawa wave modes. Additionally, the sensor\u27s sensitivity to gas concentration in the air is examined for various Volatile Organic Compounds (VOCs) using a thin Polyisobutylene (PIB) layer for sensor demonstration. The study highlights a notable sensitivity enhancement of the SAW sensor achieved through the Sezawa wave mode compared to the Rayleigh mode. For instance, a sensor sensitivity of 38.85 Hz/ppm is observed for the Sezawa mode in contrast to 14.30 Hz/ppm for the Rayleigh mode, as demonstrated with standard Tetrachloroethene (PCE)
Air-Purifying Concrete
No full textTraffic exhaust has had a negative environmental impact on society. This study aims to evaluate the use of nano-titanium dioxide in concrete pavement and its ability to purify the air from harmful gases such as NOx. The nanoparticles are synthesized for experimental work including the STM test and Sonicator bath that were performed to the classification of the product. The method to produce TiO2 nanoparticles yielded particles of size less than 15 nm. In order to utilize the photocatalytic properties of the produced particle, the air-purifying pavement blocks were poured into two layers. The top layer which contains the TiO2 nanoparticles was designed to be pervious to allow the maximum reaction between the polluted air and surface area allowing the UV light to penetrate. The bottom layer consists of conventional concrete pavement components. Using a tailor-made experimental setup, a measuring device was used to quantify the air quality parameters in and out of the glass chamber. Three control samples were tested under the same circumstance and results were compared. The outcome of this study reveals that the use of nano-TiO2 in concrete pavements reduces the percentage of NOx in the air. Recommendations are made to enlarge the scale of the project to be implemented effectively. Ultimately, this study can be a step toward cleaner air and reducing the effect of climate change
Investigating the potential of highly porous zopiclone-loaded 3D electrospun nanofibers for brain targeting via the intranasal route
No full textNanofibers (NFs) have proven to be very attractive tool as drug delivery plateform among the different plethora of nanosystems, owing to their unique features. They exhibit two- and three-dimensional structures some of which mimic structural environment of the body tissues, in addition to being safe, efficacious, and biocompatible drug delivery platform. Thus, this study embarked on fabricating polyvinyl alcohol/chitosan (PVA/CS) electrospun NFs encapsulating zopiclone (ZP) drug for intranasal brain targeted drug delivery. Electrospun NFs were optimized by adopting a three factor-two level full factorial design. The independent variables were: PVA/CS ratio (X1), flow rate (X2), and applied voltage (X3). The measured responses were: fiber diameter (Y1,nm), pore size (Y2,nm) and ultimate tensile strength (UTS,Y3,MPa). The selected optimum formula had resulted in NFs diameter of 215.90 ± 15.46 nm, pore size 7.12 ± 0.27 nm, and tensile strength around 6.64 ± 0.95 MPa. In-vitro biodegradability testing confirmed proper degradation of the NFs within 8 h. Moreover, swellability and breathability assessment revealed good hydrophilicity and permeability of the prepared NFs. Ex-vivo permeability study declared boosted ex-vivo permeation with an enhancement factor of 2.73 compared to ZP suspension. In addition, optimized NFs formula significantly reduced sleep latency and prolonged sleep duration in rats compared to IV ZP drug solution. These findings demonstrate the feasibility of employing the designed NFs as an effective safe platform for intranasal delivery of ZP for insomnia management
Scalable fuzzy multivariate outliers identification towards big data applications
No full textData outliers is intrinsically a fuzzy concept and should be treated as such. This paper is a continuation of a research on fuzzy outliers. Extending the BACON algorithm, FBACON1 and FBACON2 have been proposed as fuzzy solutions to the crisp decision boundary of BACON. This paper investigates the scalability potentials and drawbacks of FBACON1 and FBACON2 in Big Data. The investigation concluded that the sensitivity of FBACON2 towards Big Data. Therefore, this paper introduces FBACON3 as a more scalable solution than FBACON2. Three performance measures have been introduced to compare the performance of the three solutions. The study shows that FBACON1 provided the best computational performance followed by FBACON3. However, in terms of the other two measures FBACON2 and FBACON3 are tied but they outperformed FBACON1. Considering the sensitivity towards Big Data volumes and the computation time, FBACON3 is a better candidate than FBACON2. Code metadata: Permanent link to reproducible Capsule: