Search Results (22)

This study investigates the fire dynamics and structural response of steel-framed warehouse racking systems under various fire scenarios, emphasizing the critical importance of fire safety measures in mitigating structural damage. Through advanced computational simulations (Fire Dynamics Simulator) and thermomechanical analysis, this research reveals that fire intensity and progression are highly influenced by the ignition point and the stored material types, with maximum recorded temperatures reaching 720 °C and 970 °C in different scenarios. The results highlight the localization of significant strain and drift ratios in structural elements near the ignition zone, underscoring their vulnerability. This study demonstrates the rapid loss of load-bearing capacity in steel elements at elevated temperatures, leading to severe deformations and increased collapse risks. Key findings emphasize the necessity of strategically positioned sprinkler systems and the integration of passive fire protection measures, such as fire-resistant coatings, to enhance structural resilience. Performance-based fire design approaches, aligning with FEMA-356 criteria, offer realistic frameworks for improving the fire safety of warehouse structures. Full article

Oil spills pose significant threats to marine ecosystems, and while existing tools simulate spill dispersion and predict impacts, they often lack full integration of accident specifics, detailed drift simulations, and thorough impact analyses. This paper presents the EcoSensitivity decision support system, a comprehensive platform designed to improve oil spill responses by integrating immediate and cumulative environmental impact assessments. The EcoSensitivity system addresses these gaps by combining the Accidental Damage and Spill Assessment Model (ADSAM), oil drift modeling, and the PlanWise4Blue (PW4B) application, which enables high-resolution cumulative impact assessments. This unified tool provides decision-makers with rapid, data-driven insights, facilitating a more informed and effective response to oil spills. EcoSensitivity represents a substantial advancement in operational modeling, supporting ecosystem resilience and aiding in strategic planning for marine conservation. Full article

Federated Learning (FL) enables decentralized data utilization while maintaining edge user privacy, but it faces challenges due to statistical heterogeneity. Existing approaches address client drift and data heterogeneity issues. However, real-world settings often involve low-quality data with noisy features, such as covariate drift or adversarial samples, which are usually ignored. Noisy samples significantly impact the global model’s accuracy and convergence rate. Assessing data quality and selectively aggregating updates from high-quality clients is crucial, but dynamically perceiving data quality without additional computations or data exchanges is challenging. In this paper, we introduce the FedDQA (Federated learning via Data Quality-Aware) (FedDQA) framework. We discover increased data noise leads to slower loss reduction during local model training. We propose a loss sharpness-based Data-Quality-Awareness (DQA) metric to differentiate between high-quality and low-quality data. Based on the DQA, we design a client selection algorithm that strategically selects participant clients to reduce the negative impact of noisy clients. Experiment results indicate that FedDQA significantly outperforms the baselines. Notably, it achieves up to a 4% increase in global model accuracy and demonstrates faster convergence rates. Full article

International shipping is a fundamental component of the global economy. As the industry expands, the demand for high-capacity vessels increases, raising concerns about their impact on the marine environment. While awaiting access to port facilities, vessels often anchor to save fuel and prevent drifting, but this practice is a significant cause of mechanical disturbance to the seafloor and benthic habitats. Identifying and quantifying anchoring pressure is essential for better managing and mitigating the damage to the seafloor. The Automatic Identification System (AIS) can be utilized to assess anchoring pressure by transmitting vessel information (e.g., position, type and size) to other vessels and coastal stations. This research evaluates anchoring pressure in a strategically located bunkering area around the Maltese Islands using AIS data collected from an antenna at the University of Malta. An arbitrary index was developed to determine anchoring pressure, and the AIS data was used to create GIS maps showing the location and size of vessels within the bunkering area, as well as plots depicting anchoring pressure by vessel type, seasonality, and density. This study serves as a blueprint for future assessments of anchoring pressures from various maritime activities in other areas around the Maltese Islands and provides a decision support tool for national policy-making related to Descriptor 6 (Seafloor Integrity) of the Marine Strategy Framework Directive (MSFD), the Maritime Spatial Planning Directive (MSPD), and the management plan for Sites of Community Interest (SCI) and Marine Protected Areas (MPAs). Full article

The strategic recovery of buoys is a critical task in executing deep-sea research missions, as nations extend their exploration of marine territories. This study primarily investigates the dynamics of remotely operated vehicle (ROV)-assisted salvage operations for floating bodies during the recovery of dynamic maritime targets. It focuses on the hydrodynamic coefficients of dual floating bodies in this salvage process. The interaction dynamics of the twin floats are examined using parameters such as the kinematic response amplitude operator (RAO), added mass, damping coefficient, and mean drift force. During the “berthing stage”, when the double floats are at Fr = 0.15–0.18, their roll and yaw Response Amplitude Operators are diminished, resulting in smoother motion. Thus, the optimal berthing speed range for this stage is Fr = 0.15–0.18. During the “side-by-side phase”, the spacing between the ROV and FLOAT under wave action should be approximately 0.4 L to 0.5 L. The coupled motion of twin floating bodies under the influence of following waves can further enhance their stability. The ideal towing speed during the “towing phase” is Fr = 0.2. This research aims to analyze the mutual influence between two floating bodies under wave action. By simulating the coupled motion of dual dynamic targets, we more precisely assess the risks and challenges inherent in salvage operations, thus providing a scientific basis for the design and optimization of salvage strategies. Full article

This study aimed to rigorously evaluate the impact of tuned mass dampers (TMDs) on structural response under seismic excitation. By strategically placing TMDs at various levels within the structures, the research sought to determine their effectiveness in mitigating structural movement. A single-degree-of-freedom (SDOF) system incorporating TMDs was utilized to model structures of 10, 13, and 16 stories, each configured with TMDs at different heights. The structures were subjected to near-fault earthquakes to assess the efficacy of TMDs in reducing structural response. The findings revealed significant enhancements in structural performance when TMDs were optimally positioned. Specifically, a 50% reduction in both acceleration and displacement, alongside a 65% decrease in maximum drift, underscored the effectiveness of TMD deployment. Furthermore, the study demonstrated that distributing multiple TMDs along the height of the structure provided superior drift control. Notably, positioning TMDs within the upper one-third of the structure yielded the most pronounced improvements in acceleration, displacement, and maximum drift. Finally, the research indicates that the strategic incorporation of TMDs can significantly enhance the seismic resilience of structures. The results highlight the substantial benefits of TMDs in optimizing acceleration, displacement, and drift, thereby affirming their critical role in seismic design and retrofitting strategies. Full article

Extensive research on organic solar cells (OSCs) over the past decade has led to efficiency improvements exceeding 18%. Enhancing the efficacy of binary organic solar cells involves multiple factors, including the strategic selection of materials. The choice of donor and acceptor materials, which must exhibit complementary absorption spectra, is crucial. Additionally, optimizing the solar cell structure, such as adjusting the thickness of layers and incorporating hole-transporting layers, can further increase efficiency. In this study, we simulated three different novels within the use of the inorganic SnO₂ on the OSCs within this specific arrangement of structures using a drift-diffusion model: direct and inverted binary; direct ternary configurations of OSCs, specifically ITO/PEDOT: PSS/PM6:L8-BO/SnO₂/Ag, ITO/SnO₂/PM6:L8-BO/PEDOT: PSS/Ag; and FTO/PEDOT: PSS/PM6:D18:L8-BO/SnO₂/Ag. These structures achieved power conversion efficiencies (PCE) of 18.34%, 18.37%, and 19.52%, respectively. The direct ternary device achieved an important V_oc of 0.89 V and an FF of 82.3%, which is high in comparison with other simulated results in the literature. Our research focused on the role of SnO₂ as an inorganic electron transport layer in enhancing efficiency in all three configurations. We also evaluated the properties of these structures by simulating external quantum efficiency (EQE), which results in a broadened absorption spectrum from 380 nm to 900 nm for both binary and ternary devices. Furthermore, we measured the spectral distribution of absorbed photons, and photo-charge extraction by linearly increasing voltage (photo-CELIV) to assess charge extraction and generation rates as well as charge mobility. These measurements help establish a robust model for practical application. Full article

Fish Aggregating Devices (FADs) are essential supplementary structures used in tropical tuna purse-seine fishing. They are strategically placed to attract tuna species and enhance fishing productivity. The hydrodynamic performance of FADs has a direct effect on their structural and environmental safety in the harsh marine environment. Conventional FADs are composed of materials that do not break down naturally, leading to the accumulation of waste in the ocean and potential negative effects on marine ecosystems. Therefore, this work aimed to examine the hydrodynamic performance of biodegradable drifting FADs (Bio-DFADs) in oceanic currents by numerical modelling. The Reynolds-averaged Navier–Stokes equation was used to solve the flow field and discretized based on the realizable k-ε turbulence model, employing the finite volume method. A set of Bio-DFADs was developed to assess the hydrodynamic performance under varying current velocities and attack angles, as well as different balsa wood diameters and sinker weights. The results indicated that the relative current velocity significantly affected the relative velocity of Bio-DFADs. The relative length of the raft significantly affected both the relative velocity and the relative wetted area in a pure stream. Finally, the diameter of the balsa wood affected the drift velocity, and the sinker’s relative weight affected the hydrodynamic performance of the Bio-DFADs. Full article

This research explores the architecture and efficacy of GaN/Al_xGa_1−xN-based heterojunction phototransistors (HPTs) engineered with both a compositionally graded and a doping-graded base. Employing theoretical analysis along with empirical fabrication techniques, HPTs configured with an aluminum compositionally graded base were observed to exhibit a substantial enhancement in current gain. Specifically, theoretical models predicted a 12-fold increase, while experimental evaluations revealed an even more pronounced improvement of approximately 27.9 times compared to conventional GaN base structures. Similarly, HPTs incorporating a doping-graded base demonstrated significant gains, with theoretical predictions indicating a doubling of current gain and experimental assessments showing a 6.1-fold increase. The doping-graded base implements a strategic modulation of hole concentration, ranging from 3.8 × 10¹⁶ cm⁻³ at the base–emitter interface to 3.8 × 10¹⁷ cm⁻³ at the base–collector junction. This controlled gradation markedly contributes to the observed enhancements in current gain. The principal mechanism driving these improvements is identified as the increased electron drift within the base, propelled by the intrinsic electric field inherent to both the compositionally and doping-graded structures. These results highlight the potential of such graded base designs in enhancing the performance of GaN/Al_xGa_1−xN HPTs and provide crucial insights for the advancement of future phototransistor technologies. Full article

In advancing the study of magnetization dynamics in STT-MRAM devices, we employ the spin drift–diffusion model to address the back-hopping effect. This issue manifests as unwanted switching either in the composite free layer or in the reference layer in synthetic antiferromagnets—a challenge that becomes more pronounced with device miniaturization. Although this miniaturization aims to enhance memory density, it inadvertently compromises data integrity. Parallel to this examination, our investigation of the interface exchange coupling within multilayer structures unveils critical insights into the efficacy and dependability of spintronic devices. We particularly scrutinize how exchange coupling, mediated by non-magnetic layers, influences the magnetic interplay between adjacent ferromagnetic layers, thereby affecting their magnetic stability and domain wall movements. This investigation is crucial for understanding the switching behavior in multi-layered structures. Our integrated methodology, which uses both charge and spin currents, demonstrates a comprehensive understanding of MRAM dynamics. It emphasizes the strategic optimization of exchange coupling to improve the performance of multi-layered spintronic devices. Such enhancements are anticipated to encourage improvements in data retention and the write/read speeds of memory devices. This research, thus, marks a significant leap forward in the refinement of high-capacity, high-performance memory technologies. Full article

The unprecedented global meltdown resulting from the COVID-19 crisis, exacerbated by the rise of political conflicts between leading world economies, has caused the world to drift into a new paradigm with abrupt changes of traditional modi operandi across the landscape. A significant structural change, “Work-From-Anywhere (WFX)”, though well known for its flexibility and other advantages, constitutes a serious barrier to the socialization and knowledge sharing (KS) needed in organizational management and career sustainability (CS). This study aims to thoroughly investigate how strategic management structures like management “Polychronicity” (MP) can dynamically recalibrate the mediation effects of KS dispositions on the relationship between WFX and CS. Our results reveal that WFX, due to the distancing component, considerably undermines teamwork, accountability, and supervision, promoting individualism and isolation among workers. Moreover, MP moderates the effects of WFX inconsistencies on CS, and this is achieved even better through KS. This paper is a landmark contribution to the literature on WFX and CS, leading the way to the empirical investigation of the WFX–KS–CS mechanism and a quantitative evaluation of the interactive effects among major elements of the social exchange (SE) context. Full article

The U.S. Energy Information Administration (EIA) provides crucial data on monthly and annual fuel consumption for electricity generation. These data cover significant fuels, such as coal, petroleum liquids, petroleum coke, and natural gas. Fuel consumption patterns are highly dynamic and influenced by diverse factors. Understanding these fluctuations is essential for effective energy planning and decision making. This study outlines a comprehensive analysis of fuel consumption trends in electricity generation. Utilizing advanced statistical methods, including time series analysis and autocorrelation, our objective is to uncover intricate patterns and dependencies within the data. This paper aims to forecast fuel consumption trends for electricity generation using data from 2015 to 2022. Several time series forecasting models, including all four benchmark methods (Mean, Naïve, Drift, and seasonal Naïve), Seasonal and Trend Decomposition using Loess (STL), exponential smoothing (ETS), and the Autoregressive Integrated Moving Average (ARIMA) method, have been applied. The best-performing models are determined based on Root Mean Squared Error (RMSE) values. For natural gas (NG) consumption, the ETS model achieves the lowest RMSE of 20,687.46. STL demonstrates the best performance for coal consumption with an RMSE of 5936.203. The seasonal Naïve (SNaïve) model outperforms the others for petroleum coke forecasting, yielding an RMSE of 99.49. Surprisingly, the Mean method has the lowest RMSE of 287.34 for petroleum liquids, but the ARIMA model is reliable for its ability to capture complex patterns. Residual plots are analyzed to assess the models’ performance against statistical parameters. Accurate fuel consumption forecasting is very important for effective energy planning and policymaking. The findings from this study will help policymakers strategically allocate resources, plan infrastructure development, and support economic growth. Full article

The hydrogen energy industry, as one of the most important directions for future energy transformation, can promote the sustainable development of the global economy and of society. China has raised the development of hydrogen energy to a strategic position. Based on the patent data in the past two decades, this study investigates the collaborative innovation relationships in China’s hydrogen energy field using complex network theory. Firstly, patent data filed between 2003 and 2023 are analyzed and compared in terms of time, geography, and institutional and technological dimensions. Subsequently, a patent collaborative innovation network is constructed to explore the fundamental characteristics and evolutionary patterns over five stages. Furthermore, centrality measures and community detection algorithms are utilized to identify core entities and innovation alliances within the network, which reveal that China’s hydrogen energy industry is drifting toward alliance innovation. The study results show the following: (1) the network has grown rapidly in size and scope over the last two decades and evolved from the initial stage to the multi-center stage, before forming innovation alliances; (2) core innovative entities are important supports and bridges for China’s hydrogen energy industry, and control most resources and maintain the robustness of the whole network; (3) innovation alliances reveal the closeness of the collaborative relationships between innovative entities and the potential landscape of China’s hydrogen energy industry; and (4) most of the innovation alliances cooperate only on a narrow range of technologies, which may hinder the overall sustainable growth of the hydrogen energy industry. Thereafter, some suggestions are put forward from the perspective of an industrial chain and innovation chain, which may provide a theoretical reference for collaborative innovation and the future development and planning in the field of hydrogen energy in China. Full article

This research addresses the strategic issue of why key decision-makers fail to foresee potential extreme ‘black swan’ events. Following a review of the literature, a conceptual framework is developed that identifies two types of organisational blindness that are reflected in Tetlock’s hedgehog cognitive thinking style, being the oversimplification of uncertainty (e.g., inductive biases) and an unquestioned, top-down, reference narrative. This framework is tested using a case study approach and qualitative analysis of secondary data sources available from the Royal Commission of Inquiry and other published reports following the 2010 methane explosion at the Pike River Coal Ltd.’s mine (Pike) in New Zealand, that killed 29 miners and caused the loss of all funds invested. The results indicate that the combined effect of both blindnesses meant that Pike’s collective intelligence was limited, and for the three key decision-makers at the Pike River mine, some type of extreme ‘black swan’ event was apparently inevitable. This research provides theoretical and practical contributions to the analysis of business and public policy decision-making under uncertainty. Full article

The harmonious landscape of Montagne des Français is a protected area in the far north of Madagascar. Our herpetofauna surveys were conducted on the eastern and western slopes according to habitat variations within the massif for 2014 and 2020. Our research updates the herpetofauna species richness, spatial distribution ranges, and ecological guilds within the protected area. We used direct opportunistic observations, systematic refuge examinations, and pitfall traps with drift fences at three sites to sample animals. Nineteen amphibian and fifty reptile species were recorded during this study. Three amphibian species and one reptile species, in addition to the snake Langaha pseudoalluaudi, last recorded in 2007, were discovered at Montagne des Français. Here, we present a database update for the herpetofauna species from Montagne des Français and provide a specific morphological description of the morphospecies considered as a new extension or localized distribution. This new database can help site managers develop new strategic conservation plans in response to habitat modification. Full article