Avanti Publishers
Not a member yet
711 research outputs found
Sort by
Awareness and Energy Conservation Behaviors: A Case Study of Institutional Buildings in Hail, Saudi Arabia
Full text linkThe growing challenges of carbon emissions and global warming necessitate global efforts to improve energy efficiency and reduce energy consumption. The Kingdom of Saudi Arabia (KSA) faces significant challenges in ensuring a sustainable electricity supply in buildings, including high energy demand driven by extreme climate conditions, heavy reliance on fossil fuels, and inefficiencies in energy distribution and consumption patterns. This study explores the relationship between employee awareness, energy conservation behaviors, and electricity consumption in three architecturally identical institutional buildings in Hail province, which exhibit significant variations in energy use. Using a mixed method of qualitative and quantitative approaches, structured questionnaires were distributed to 27 employees, with 21 responses analyzed through SPSS using a five-point Likert scale. Results reveal that behavior, rather than awareness, is the primary driver of energy consumption, as Building 3 exhibited the highest energy-saving behaviors despite moderate awareness levels. Workplace norms, peer influence, and reinforcement mechanisms significantly impact energy-saving actions, while awareness alone proves insufficient in fostering consistent behavioral engagement
Insight into Employability of Mohr Coulomb and Hardening Soil Model in the Undrained Analysis
Full text linkQuite often soil at the site is saturated with water. Any addition of the load onto such soil with low permeability results in generation of excess pore water pressure. Real life problems such as construction of footing, construction of embankment on saturated clayey soil and deep excavation falls under this category. The numerical modelling of such problems must be capable of simulating generation of excess pore water pressure accurately. Mohr Coulomb model is the most widely used constitutive model in the numerical analysis of soil problems. However, being elastic-perfectly plastic, application of this model in simulation of short term undrained simulations needs to be investigated. In the present study, efficacy of the Mohr Coulomb model and Hardening Soil model present in the PLAXIS have been investigated for coupled analysis. It is found that Mohr Coulomb model overestimates the undrained shear strength of the soil significantly and fails to produce the realistic stress path. Hardening soil model captured the realistic pore pressure response whereas the Mohr Coulomb model underestimated the pore pressure and resulted in unrealistic pore pressure evolution. It is recommended that advanced constitutive models such as Hardening Soil model should be employed in short term undrained numerical analysis
Educating for Unbuilt Futures: AI as a Co-Speculative Partner in Climate-Resilient Architectural Pedagogy
Full text linkArchitectural education stands at a critical intersection of accelerating climate crises, technological transformation, and social complexity. At the center of this transition lies Artificial Intelligence (AI)—a defining technology reshaping both design processes and cognitive paradigms. Although AI is becoming increasingly embedded in architectural practice, its pedagogical potential remains predominantly instrumental, often limited to applications in form generation and performance optimization. This study reframes AI as a co-speculative pedagogical partner—a reflective agent capable of nurturing ethical, ecological, and contextually responsive design intelligence. Responding to contemporary challenges such as climate instability, resource scarcity, and spatial inequality, the research aligns with the Sustainable Development Goals (SDGs 4, 11, and 13). A multi-layered qualitative methodology was adopted to: (i) synthesize theoretical perspectives from speculative design, cognitive science, and environmental philosophy; (ii) examine international frameworks (NAAB, RIBA, UNESCO) to understand how AI’s pedagogical dimension is articulated; and (iii) compare traditional studio pedagogies with emerging AI-augmented workflows. Together, these layers construct a reproducible framework for evaluating AI’s educational integration. The findings identify five interconnected competency domains—technological literacy, strategic design thinking, environmental sensitivity, ethical awareness, and collaborative agency—derived from recent studies and international educational frameworks. While these domains resonate with existing institutional standards, they also reveal the need for new pedagogical models that situate AI within broader ecological and ethical objectives. The study argues that AI can function as a medium for contextual intelligence—bridging computational logic with embodied, climate-responsive creativity. The proposed framework reimagines architectural education as a reflective and adaptive ecosystem where AI enhances, rather than replaces, human judgment. It fosters a synergistic dialogue between data-driven reasoning and embodied design intelligence, preparing future architects to act ethically, creatively, and ecologically within complex design environments
Formulation of a Water-Based Drilling Fluid with Natural Aloe Vera Additive for Enhancing Filtration Properties
Full text linkThe search for natural additives to improve the performance of water-based drilling fluids (WBDF) has been fueled by the growing need for environmentally friendly and sustainable drilling processes. The objective of this study is to examine the potential utilization of Aloe Vera (AV) powder as a natural additive in WBDF through an experimental analysis of filtration properties. All experimental studies adhered to the American Petroleum Institute (API) standard procedure in order to accomplish the objectives mentioned above. In this experiment, a mixture of water phase volume of (350 ml) and chemical components like xanthan gum (0.8 gm), sodium hydroxide (0.8 gm), bentonite (13 gm), and barite (18 gm) were used to prepare base mud. Samples 1, 2, and 3 are created using 0.25%, 0.5%, and 0.75% weight of aloe vera powder (size less than 150 µm) in relation to water volume, while sample 4 was created using 0.5% weight of aloe vera powder (size less than 212 µm) in relation to water volume. The standard cell is used in the low-pressure mud filtration test, which was conducted for 30 minutes at room temperature with an API condition of 100 psi. Based on the laboratory analysis, this study suggests that AV powder has the potential to be an environmentally beneficial additive for usage in specialized drilling environments rather than generalized drilling operations. Specially, the 0.5% concentration of AV powder with particle size less than 150 µm demonstrated improved fluid loss management for water-based drilling fluid. This study offers a comprehensive evaluation of its influence on the fluid's behavior, with a focus on the drilling fluid's filtration performance. The outcome of the experiment indicates that WBDF containing aloe vera is an economical and environmentally beneficial additive for reducing filtration loss and preventing significant fluid loss during drilling operations
Exploration of White Hydrogen: Drawing Global Analogy to Unveil the Potential of the Andaman Basin's Sea Floor Spreading Center
Full text linkHydrogen is increasingly recognized as a critical element in the global energy transition, offering a path to decarbonize power generation, industry, and transportation. While green and blue hydrogen dominate current production strategies, natural hydrogen—commonly termed white hydrogen—remains largely underexplored despite its potential as a continuous, low-cost, and carbon-neutral energy resource. White hydrogen forms endogenously through geological processes, including serpentinization of ultramafic rocks, mantle-derived reactions, radiolysis, and organic matter decomposition. Global occurrences in cratonic shields, ophiolites, intracratonic basins, and mid-ocean ridges demonstrate the widespread yet underutilized nature of this resource. This study investigates the Andaman Basin, a tectonically active seafloor spreading center, as a prospective frontier for white hydrogen exploration. Integrating geological and seismic observations with the hydrogen system model, I evaluate the mechanisms controlling hydrogen generation, migration, and accumulation. Seismic data reveal structural and stratigraphic features conducive to serpentinization-driven hydrogen generation, fault-controlled migration pathways, and potential entrapment beneath marine shales. The study further identifies complementary targets in the western Andaman subduction zone. A strategic exploration framework combining play- and prospect-level investigations—including geophysical surveys, soil gas sampling, exploratory drilling, and laboratory analyses—is proposed to systematically delineate potential accumulations. The findings underline the scientific and economic promise of white hydrogen in the Andaman Basin, offering insights for sustainable energy development and informing global analogs in hydrogen exploration
Advances in the Fabrication, Mechanisms, and Applications of Monodisperse Droplets in Microfluidics
Full text linkMonodisperse microfluidic droplets, with precisely controlled size, high stability, and compartmentalization, have emerged as powerful tools in biomedicine, chemistry, and materials science. This review systematically summarizes key droplet generation methods, including T-junction, flow-focusing, and co-flow configurations, emphasizing how droplet size, frequency, and morphology are governed by channel geometry and operating parameters. Numerical modeling approaches–particularly Volume-of-Fluid (VOF), Level-Set (LS), and Phase-Field (PF) methods–are evaluated for their capabilities in capturing droplet formation dynamics and guiding device design, with VOF highlighted as the most reliable due to its mass-conservation properties. Applications of monodisperse droplets are further discussed in three major domains: biomedicine, chemical reactions, and materials fabrication. Overall, this review consolidates current advances in droplet fabrication, mechanisms, applications and outlines future directions to promote cross-disciplinary innovations
Brief History, Design Innovations, Sustainability, and the Future Prospects of Aquaponics: A Review
Full text linkThe rising demand for food due to the increasing population is one of the world's major issues. It is aggravated by the decreasing area for food production due to land conversion and the effects of climate change that threaten food security. Thus, alternative methods for producing more food efficiently and sustainably have been the focus recently. Aquaponics is a promising food production technology that combines fish and plants within a single system. Among the existing techniques, the recirculating aquaponics system, or RAS, is one of the most sophisticated land-based aquaculture production systems, integrating hydroponics to promote the reuse and recycling of nutrient-rich water while maintaining high-quality fish and plants. Aquaponics originated from traditional practices that utilized abundant natural resources. Modern developments have evolved from small, modular systems to medium- and large-scale, commercial designs, incorporating automation and the Internet of Things (IoT) to enhance efficiency and precision. This paper reviews the evolution of aquaponics, highlighting existing designs, innovations, and performance. Additionally, it explores future work in aquaponics aimed at improving profitability and sustainability
Genetic Algorithm Optimization of Crude Oil Pipeline Operations for Wax Control: A Case Study of CNPC-Niger Petroleum Company
Full text linkWax formation and deposition in crude oil pipelines pose a very significant challenge, such as flow restriction, increased cost of maintenance and potential shutdowns. The goals of this study are to reduce wax accumulation in the China National Petroleum Corporation-Niger Petroleum (CNPC-NP) pipeline network, which connects the Agadem oil fields to the SORAZ refinery, by optimizing critical operating conditions. The Reliability of Aspen HYSYS for analyzing wax behavior was validated by the simulation model that closely matched the real-world data, with a simulated flow rate of 182.49 m³/h with, only 0.27% higher than the actual 182 m³/h. The study suggested changing the operating condition using a genetic algorithm method of optimization, which indicates a slight increase in the pressure from 0.6 MPa to 0.65 MPa, while decreasing in temperature from 51°C to 48.5°C and a potential increase in the flow rate to 187.49 187.49 m³/h. Furthermore, the results of the optimization led to a decrease in wax thickness from 0.058 mm to 0.0409 mm, which indicated an improvement in pipeline operating conditions. Also, the economic analysis revealed, the total capital investment was roughly 2.4 million. The financial indicators include an Internal Rate of Return (IRR) of 9%, a Net Present Value (NPV) of $2.14 million and a Profitability Index (PI) of 1.99, all of which were higher than the IRR of the current CNPC-Niger Petroleum, which was 8%. The results show that the economic performance of the crude oil pipeline system can be improved, and wax formation risk can be effectively decreased by combining simulation-driven decision-making with strategic operational parameter adjustment
Unveiling the Geological Mysteries: Tectonics, Evolution, and Hydrocarbon Play Types of the Andaman–Nicobar Basin from Seismic Data
Full text linkThe Andaman–Nicobar Basin, located at the convergent margin between the Indian and Eurasian plates, is one of the most tectonically dynamic and geologically complex frontier basins in the northeastern Indian Ocean. Utilizing over 23,500-line kilometers of newly acquired 2D seismic data (2021–2023) integrated with legacy datasets and well information, this study redefines the basin’s tectonic framework, stratigraphic evolution, and hydrocarbon potential. Seismic interpretation delineates a classic arc–trench–backarc system comprising the Andaman Trench, accretionary prism, volcanic arc, and backarc spreading centers, reflecting ongoing subduction and extensional tectonics. Paleo-flattening and facies analyses reveal a multi-phase evolution involving initial rifting in the Late Eocene–Oligocene, post-rift marine transgression with carbonate platform development, and Miocene to Recent inversion related to India–Eurasia collision. Four key hydrocarbon play types are identified: syn-rift clastic, early post-rift carbonate, early post-rift clastic, and late post-rift clastic systems, with reservoir porosity ranging from 12% to 25% and thickness up to 2.5 km. This work refines earlier tectono-stratigraphic models by delineating new structural highs, spreading centers, and untested plays in forearc and western backarc sectors. The results highlight promising exploration potential, particularly within early post-rift carbonate and late post-rift clastic plays, offering a robust framework for future hydrocarbon exploration in this frontier basin
A Convolutional‑Neural‑Network Surrogate for Steady‑State Radiative Heating in Thermoforming
Full text linkThermoforming is widely used to produce lightweight packaging and durable components, yet controlling the temperature field during the heating stage remains challenging. Finite‑element models that capture conduction, convection and diffuse‑radiative exchange provide accurate predictions, but their high computational cost precludes real‑time optimization and digital‑twin deployment. In this study a convolutional‑neural‑network (CNN) surrogate is developed to predict steady‑state temperature distributions for a polymer sheet heated by an array of radiative heaters. A parametric study sampled heater temperature distributions, sheet thicknesses and initial temperatures, and a nonlinear finite‑element model was discretized and used to compute steady‑state temperature fields. The resulting dataset of input vectors and temperature maps served to train a fully convolutional neural network, whose weights were optimized with the Adam algorithm by minimizing the mean‑squared error. On a held‑out test set the surrogate achieved a coefficient of determination of 0.96 and a mean relative error less than 3%, while producing predictions in under 1 second—an order‑of‑magnitude speedup relative to the finite‑element solver. Gradient‑based inversion of the trained network successfully recovered heater temperature distributions that reproduced target temperature fields, even under simulated heater failures, demonstrating the feasibility of fault‑tolerant control. These results show that the proposed CNN surrogate bridges high‑fidelity simulation and real‑time control, enabling digital‑twin implementations for thermoforming and providing a foundation for future extensions to transient heating and experimental validation