The Smoothed Particle Hydrodynamics (SPH) method has been applied to solve the Boussinesq equations in order to simulate hypothetical one-dimensional dam break flows (DBFs) across varying depth ratios. Initial simulations reveal that the influence of Boussinesq terms remains minimal during the early stages of DBF when the depth ratio is less than 0.4. However, these terms become increasingly significant at later stages of the flow. In comparison to simulations based on the Saint-Venant equations, the Boussinesq-SPH model underestimates flow depths in regions of constant elevation while overestimating the propagation speed of the positive surge wave, with this overestimation becoming more pronounced as the depth ratio increases. Notably, the first and third Boussinesq terms exert the greatest influence on the simulation results. The findings also indicate the presence of non-hydrostatic pressure distributions within the DBF, which contribute to the accelerated movement of the positive surge. This study offers valuable insights into the modelling of flows that exhibit non-hydrostatic behaviour, and the results may be instrumental in improving the analysis of similar flow phenomena, especially those involving complex pressure distributions and wave propagation dynamics.
This paper investigates the search for an exact analytic solution to a temporal first-order differential equation that represents the number of customers in a non-stationary or time-varying $M / D / 1$ queueing system. Currently, the only known solution to this problem is through simulation. However, a study proposes a constant ratio, $\beta$ (Ismail's ratio), that relates the time-dependent mean arrival and mean service rates, offering an exact analytical solution. The stability dynamics of the time-varying $M / D / 1$ queueing system are then examined numerically in relation to time, $\beta$, and the queueing parameters. On another note, many potential queueing-theoretic applications to traffic management optimization are provided. The paper concludes with a summary, combined with open problems and future research pathways.
Laser additive manufacturing, a pivotal technology in advanced manufacturing, is extensively applied in the restoration industry. However, its development has been hindered by challenges such as residual stress and excessive grain size during the manufacturing process. The integration of ultrasonic enhancement technology with laser cladding has emerged as a prominent research direction, offering significant improvements in the quality and performance of the cladding layer. This review focuses on two primary approaches: ultrasonic-enhanced synchronous laser cladding and ultrasonic strengthening as a post-processing method. The ultrasonic processes discussed include ultrasonic vibration, ultrasonic rolling, ultrasonic impact, and their composite variants. Each method is evaluated for its ability to modify the microstructure, alleviate defects, and enhance the mechanical properties of the cladding layer. While ultrasonic enhancement during synchronous laser cladding primarily facilitates greater molten pool agitation, post-processing techniques induce severe plastic deformation on the surface of the cladding layer. Both approaches have been shown to reduce residual stress, refine grain structure, and improve surface hardness. The underlying mechanisms governing these improvements, particularly microstructural evolution and grain refinement, are examined in detail. Additionally, the potential advantages and limitations of each ultrasonic introduction method are discussed. Finally, the application prospects and future development trends of ultrasonic-enhanced laser cladding are explored, with particular attention to the role of ultrasonic technology in enhancing the durability, wear resistance, and corrosion resistance of cladding layers. The synergy between ultrasonic techniques and laser cladding promises to expand the potential of additive manufacturing in both industrial and repair applications.
The Pearl River Delta Water Resources Allocation Project is characterized by an extensive distribution of buildings along a lengthy alignment and the application of diverse construction methodologies. Given these complexities, comprehensive safety monitoring measures are essential during both the temporary construction and operational phases to ensure the structural integrity and safety of the project. This study examines the critical aspects of safety monitoring, tailored to the unique characteristics and demands of the project, by focusing on the monitoring objectives, specific monitoring tasks, and the inherent challenges posed by the project's scope and variety. Emphasis is placed on identifying key safety monitoring difficulties, such as maintaining accuracy across varying construction methods and terrain conditions, and ensuring compliance with evolving regulatory standards. Additionally, innovative solutions and advanced monitoring techniques that address these challenges are explored, highlighting the integration of novel technologies and approaches that enhance monitoring effectiveness. The discussion is framed within the context of existing engineering requirements and regulatory frameworks, providing insights into the strategic implementation of safety monitoring protocols that are both adaptable and robust. This paper contributes to the ongoing discourse on the safety management of large-scale water resource projects by presenting a detailed analysis of the challenges encountered and the innovations employed to mitigate risks, thus supporting sustainable and safe development in complex engineering environments.
The scouring process, characterised by the erosion of sediment around bridge piers due to fluid flow, poses a significant risk to the structural integrity of bridges. Scour depth, defined as the vertical distance from the initial riverbed level to the bottom of the scour hole, is driven by the formation of vortices near bridge piers. Mitigating scour damage after it has advanced to a critical stage is often more disruptive and costly than preemptive measures based on accurate predictions. In response to this challenge, a range of one-dimensional (1D) and two-dimensional (2D) numerical modelling techniques has been developed for scour depth estimation around bridge piers. Among the available methods, the Hydrologic Engineering Center's River Analysis System (HEC-RAS) is widely employed, with the majority of studies focusing on the 1D modelling approach. The current study evaluates the relative efficacy of 1D and 2D models using the case of the Kelanisiri Bridge, which traverses the Kelani River in Sri Lanka. The performance of the 1D model was assessed by comparing predicted water levels at an intermediate river gauge with field data, while the 2D model was calibrated and validated against observed riverbed levels. Both approaches were applied to estimate scour depths following the 2016 flood event. The findings revealed that the 2D HEC-RAS model provided a superior match with observed field data when compared to the 1D model, achieving a coefficient of determination (R$^2$) of 0.98 and a root mean square error (RMSE) of 0.13, indicating a higher degree of accuracy and reliability. As a result, the 2D model is recommended as the more effective approach for predicting scour depth around bridge piers. Further validation of these numerical results through scaled laboratory physical modelling is recommended to ensure greater accuracy in future predictive efforts.
As global focus on climate change intensifies, carbon credits have become an important tool for reducing greenhouse gas emissions. Africa, with its abundant natural resources and potential for sustainable development, is well-positioned to capitalize on this growing market. This article explores how Africa can enhance its participation in the carbon credit market, transforming environmental initiatives into economic opportunities by addressing key implementation challenges. By utilizing the Stepwise Weight Assessment Ratio Analysis (SWARA) method within an interval-valued spherical fuzzy (IVSF) framework, the study supports collective decision-making. It identifies three crucial factors: access to financing issue, the absence of clear policies and legal frameworks, and the lack of capacity and expertise within governments, businesses, and communities. The research provides practical recommendations for governments aiming to effectively implement the carbon credit concept.
This work aims to apply the spherical fuzzy set (SFS), a flexible framework for handling ambiguous human opinions, to improve decision-making processes in recycled water. It specifically looks at the application of Sugeno-Weber (SW) triangular norms in the spherical fuzzy (SF) information domain, providing reliable approximations that are necessary for decision-making. A new class of aggregation operators is presented in this paper. These operators are specifically made for spherical fuzzy information systems and include the interval value spherical fuzzy Sugeno–Weber power weighted average (IVSFSWPA), interval value spherical fuzzy Sugeno–Weber power geometric (IVSFSWPWG), and interval value spherical fuzzy Sugeno–Weber power weighted average (IVSFSWPWA). The realistic features and special cases of these operators are demonstrated, highlighting how well they fit into practical scenarios. A new method for multi-attribute decision-making (MADM) is used for a range of real-world applications with different requirements or characteristics. The efficacy of the recommended methodologies is demonstrated with an example of a recycled water selection process. Additionally, a thorough comparison method is provided to show how the suggested aggregation strategies work and are relevant by contrasting their results with those of the current methods. The study's conclusion highlights the potential contribution of the recommended research to the advancement of decision-making techniques in dynamic and complex environments. It also summarizes its findings and discusses its prospects moving forward.
Manufacturers are increasingly leveraging both online and offline channels to diversify their sales strategies. However, competition between these channels presents challenges in maximising profits for all parties involved. This study investigates the use of cost-sharing contracts by manufacturers to promote marketing in both online and offline channels, with the goal of achieving Pareto improvements in supply chain profitability. The model also accounts for consumers’ reference quality perceptions in online channels, offering a comprehensive evaluation of how cost-sharing contracts influence the operational strategies and performance of both online and offline enterprises. An empirical analysis is conducted using the “US Stores Sales” dataset from Kaggle, comprising 4,249 samples with 20 recorded characteristics per sample. The findings indicate that: (1) Cost-sharing in marketing efforts facilitates a Pareto improvement in profits for manufacturers, online enterprises, and offline retailers, with manufacturers experiencing the most significant benefit. (2) When the manufacturer assumes a larger share of marketing costs for one channel (e.g., online or offline) and a smaller share for the other, the party receiving the higher cost-sharing proportion typically sees increased profitability, while the other party’s profitability may diminish. (3) Empirical analysis suggests that manufacturers should prioritise supporting online businesses’ marketing activities, as this strategy is more likely to result in higher overall profits for the manufacturer. (4) Interestingly, when equal cost-sharing proportions are offered to both online and offline enterprises for the sake of fairness, the manufacturer’s profitability is enhanced. Moreover, the profitability of online enterprises tends to increase when the equal cost-sharing proportion is smaller. These findings validate the proposed model and underscore the critical role of strategic cost-sharing contracts in optimising Online to Offline (O2O) supply chain performance. Further research could explore the implications of varying consumer preferences and digitalisation trends on the effectiveness of such strategies.
Rice is a staple food for a significant portion of the global population, particularly in countries where it constitutes the primary source of sustenance. Accurate classification of rice varieties is critical for enhancing both agricultural yield and economic outcomes. Traditional classification methods are often inefficient, leading to increased costs, higher misclassification rates, and time loss. To address these limitations, automated classification systems employing machine learning (ML) algorithms have gained attention. However, when raw data is inadequately organized or scattered, classification accuracy can decline. To improve data organization, normalization processes are often employed. Despite its widespread use, the specific contribution of normalization to classification performance requires further validation. In this study, a dataset comprising two rice varieties Osmancik and Cammeo produced in Turkey was utilized to evaluate the impact of normalization on classification outcomes. The k-Nearest Neighbor (KNN) algorithm was applied to both normalized and non-normalized datasets, and their respective performances were compared across various training and testing ratios. The normalized dataset achieved a classification accuracy of 0.950, compared to 0.921 for the non-normalized dataset. This approximately 3% improvement demonstrates the positive effect of data normalization on classification accuracy. These findings underscore the importance of incorporating normalization in ML models for rice classification to optimize performance and accuracy.
To investigate the variation in the diffusion patterns of natural gas leaks in the Floating Production Storage and Offloading (FPSO) system, with the aim of formulating appropriate emergency response strategies and minimizing accident losses, a study was conducted on the gas leak issues of oil and gas processing equipment in the FPSO upper module. A consequence prediction and assessment model was established based on Computational Fluid Dynamics (CFD) methods. Sixteen working conditions and one control working condition were developed to simulate the diffusion characteristics of combustible gas leaks. The simulations provided insights into the gas leakage patterns under different conditions and identified the most hazardous scenario for gas leaks in the FPSO upper module. The results indicate that the density and shape of the equipment within the upper module significantly influence the diffusion outcome. After a leak, high concentrations of combustible gas were observed near the crude oil heat exchanger skid in Industrial Zone II. The effects of individual factors on gas diffusion were significant, and the interactions among multiple factors were complex. Wind speed had a more pronounced effect on longitudinal gas diffusion compared to wind direction and leak aperture, while wind direction significantly influenced lateral gas diffusion. The leak aperture, on the other hand, had a more substantial impact on vertical gas diffusion.
To accelerate the exchange of water rights between regions and address the uneven costs of water resource ecological protection among different districts in urban areas, it is essential to make an analysis of regional water resource ecological compensation responsibilities. Establishing a rational standard for ecological compensation based on water resources remains a key method for quantifying the ecological value of water resources. In this study, all districts within a national central city in southwestern China were divided into four functional zones as the research subjects. The water resource ecological footprint method was employed to calculate the water ecological footprint of each zone. The ecological carrying capacity was utilized as the benchmark to determine the water resource ecological deficit or surplus, and the corresponding ecological monetary value of water resources was estimated. The results indicated that the city, as a whole, exhibited a water resource ecological surplus, with a monetary value of 5.088 billion CNY. The western zone, a key urban development area, recorded the highest water resource ecological footprint and the largest ecological deficit. In contrast, the northeastern zone, abundant in water resources, presented the highest water resource ecological surplus, with a monetary value of 9.196 billion CNY. Compensation amounts for the central-eastern and western zones were calculated as 4.169 billion and 7.661 billion CNY, respectively. These findings align with the local water resources' sustainable utilization conditions. The relationship between regional economic development, water conservation, and sustainable development was further analyzed in this study, proposing a water resource ecological compensation model with certain districts and counties as beneficiaries.
Water is regarded as the most critical natural resource in Idaho, with drinking water identified as its most essential aspect. To assess public perceptions and evaluations of drinking water quality, a survey instrument was developed and distributed to Idaho residents over the past 35 years. Key areas of focus included the safety of home drinking water, the use of in-home water filters, consumption of bottled water, frequency of water testing, and concerns about potential pollutants. Surveys were administered in 1988, 1993, 1998, 2002, 2005, 2010, 2015, 2018, and 2022, with findings indicating a gradual decline in perceived drinking water safety, from 90.2% in 1988 to 80.2% in 2022. The use of in-home water filtration systems increased significantly, rising from 16.2% in 1988 to 29.7% in 2022, potentially driven by extensive advertising campaigns rather than increased contamination concerns. Bottled water usage peaked at 33% in 2010 but has since declined to less than 11% in 2022, a trend attributed to heightened public awareness of tap water safety and environmental concerns related to plastic waste. No significant long-term patterns in water testing were observed, although rural residents, who rely on private wells, were more likely to test their water due to the absence of regular testing requirements. Hard water (with a high content of Ca and/or Mg) emerged as the primary contaminant identified by respondents, with no other significant pollutants widely reported. These findings offer valuable insights into shifting public perceptions of water quality and the factors influencing household water consumption practices in Idaho over the last three decades.
Internal audits serve as critical assurance services that support the enhancement of operational efficiency and financial performance within organizations. This study examines the role of internal auditing in improving these aspects in privatised financial institutions, specifically focusing on BLESSING Finance. Given the profit-driven orientation of management in such institutions, there is a pressing need to identify strategies that maximize profitability. Enhancing operational efficiency is pivotal, as it reduces operational costs while increasing productivity. Internal auditing contributes significantly by identifying deficiencies within internal controls and providing audit opinions that inform management in drafting appropriate policies and procedures. This research utilized a mixed-methods approach, combining qualitative data from interviews and quantitative data from questionnaires, to assess the impact of internal auditing on operational efficiency and financial performance. The findings demonstrate that internal audits have a positive and significant effect on both operational efficiency and financial performance, highlighting the value of internal audits as a strategic tool for financial institutions. It is recommended that BLESSING Finance’s management prioritize the recruitment of qualified auditors with the necessary skills and expertise to perform audits effectively and efficiently, thereby further enhancing the institution’s operational efficiency and financial outcomes. The study underscores the importance of robust internal audit functions as a key driver of strategic and financial success in financial institutions.
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