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Estimability and simple dynamical analyses of range (range-rate range-difference) observations to artificial satellites
Non-Bayesian statistics were used in simulation studies centered around laser range observations to LAGEOS. The capabilities of satellite laser ranging especially in connection with relative station positioning are evaluated. The satellite measurement system under investigation may fall short in precise determinations of the earth's orientation (precession and nutation) and earth's rotation as opposed to systems as very long baseline interferometry (VLBI) and lunar laser ranging (LLR). Relative station positioning, determination of (differential) polar motion, positioning of stations with respect to the earth's center of mass and determination of the earth's gravity field should be easily realized by satellite laser ranging (SLR). The last two features should be considered as best (or solely) determinable by SLR in contrast to VLBI and LLR.
Advanced Offshore Wind Turbine/Foundation Concept for the Great Lakes
This project investigated a conceptual 2-bladed rotor wind turbine design and assessed its feasibility for installation in the Great Lakes. The levelized cost of energy was used for this purpose. A location in Lake Erie near the coast of Cleveland, Ohio was selected as the application site. The loading environment was defined using wind and wave data collected at a weather station in Lake Erie near Cleveland. In addition, the probability distributions of the annual significant wave height and wind speed were determined. A model of the dependence of the above two quantities was also developed and used in the study of wind turbine system loads. Loads from ice floes and ridges were also included.The NREL 5 MW 3-bladed rotor wind turbine concept was used as the baseline design. The proposed turbine design employs variable pitch blade control with tip-brakes and a teeter mechanism. The rotor diameter, rated power and the tower dimensions were selected to closely match those of the NREL 5 MW wind turbine.A semi-floating gravity base foundation was designed for this project primarily to adapt to regional logistical constraints to transport and install the gravity base foundation. This foundation consists of, from bottom to top, a base plate, a buoyancy chamber, a taper zone, a column (with ice cone), and a service platform. A compound upward-downward ice cone was selected to secure the foundation from moving because of ice impact.The turbine loads analysis was based on International ElectroTechnical Committee (IEC) Standard 61400-1, Class III winds. The NREL software FAST was the primary computational tool used in this study to determine all design load cases. An initial set of studies of the dynamics of wind turbines using Automatic Dynamic Analysis of Mechanical Systems (ADAMS) demonstrated that FAST and ADAMS load predictions were comparable. Because of its relative simplicity and short run times, FAST was selected for this study. For ice load calculations, a method was developed and implemented in FAST to extend its capability for ice load modeling.Both upwind and downwind 2-bladed rotor wind turbine designs were developed and studied. The new rotor blade uses a new twist angle distribution design and a new pitch control algorithm compared with the baseline model. The coning and tilt angles were selected for both the upwind and downwind configurations to maximize the annual energy production. The risk of blade-tower impact is greater for the downwind design, particularly under a power grid fault; however, this risk was effectively reduced by adjusting the tilt angle for the downwind configuration.
Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection
Communication overhead in federated learning (FL) poses a significant challenge for network anomaly detection systems, where the myriad of client configurations and network conditions can severely impact system efficiency and detection accuracy. While existing approaches attempt to address this through individual optimization techniques, they often fail to maintain the delicate balance between reduced overhead and detection performance. This paper presents an adaptive FL framework that dynamically combines batch size optimization, client selection, and asynchronous updates to achieve efficient anomaly detection. Through extensive profiling and experimental analysis on two distinct datasets-UNSW-NBIS for general network traffic and ROAD for automotive networks-our framework reduces communication overhead by 97.6%; (from 700.0s to 16.8s) compared to synchronous baseline approaches while maintaining comparable detection accuracy (95.10%; vs. 95.12%;). Statistical validation using Mann-Whitney U test confirms significant improvements (p < 0.05) over existing FL approaches across both datasets, demonstrating the framework's adaptability to different network security contexts. Detailed profiling analysis reveals the efficiency gains through dramatic reductions in GPU operations and memory transfers while maintaining robust detection performance under varying client conditions.
The influence of respiratory motion on CT image volume definition
Purpose: Radiotherapy treatments are based on geometric and density information acquired from patient CT scans. It is well established that breathing motion during scan acquisition induces motion artifacts in CT images, which can alter the size, shape, and density of a patient's anatomy. The aim of this work is to examine and evaluate the impact of breathing motion on multislice CT imaging with respiratory synchronization (4DCT) and without it (3DCT). Methods: A specific phantom with a movable insert was used. Static and dynamic phantom acquisitions were obtained with a multislice CT. Four sinusoidal breath patterns were simulated to move known geometric structures longitudinally. Respiratory synchronized acquisitions (4DCT) were performed to generate images during inhale, intermediate, and exhale phases using prospective and retrospective techniques. Static phantom data were acquired in helical and sequential mode to define a baseline for each type of respiratory 4DCT technique. Taking into account the fact that respiratory 4DCT is not always available, 3DCT helical image studies were also acquired for several CT rotation periods. To study breath and acquisition coupling when respiratory 4DCT was not performed, the beginning of the CT image acquisition was matched with inhale, intermediate, or exhale respiratory phases, for each breath pattern. Other coupling scenarios were evaluated by simulating different phantom and CT acquisition parameters. Motion induced variations in shape and density were quantified by automatic threshold volume generation and Dice similarity coefficient calculation. The structure mass center positions were also determined to make a comparison with their theoretical expected position. Results: 4DCT acquisitions provided volume and position accuracies within ±3% and ±2 mm for structure dimensions >2 cm, breath amplitude ≤15 mm, and breath period ≥3 s. The smallest object (1 cm diameter) exceeded 5% volume variation for the breath patterns of higher frequency and amplitude motion. Larger volume differences (>10%) and inconsistencies between the relative positions of objects were detected in image studies acquired without respiratory control. Increasing the 3DCT rotation period caused a higher distortion in structures without obtaining their envelope. Simulated data showed that the slice acquisition time should be at least twice the breath period to average object movement. Conclusions: Respiratory 4DCT images provide accurate volume and position of organs affected by breath motion detecting higher volume discrepancies as amplitude length or breath frequency are increased. For 3DCT acquisitions, a CT should be considered slow enough to include lesion envelope as long as the slice acquisition time exceeds twice the breathing period. If this requirement cannot be satisfied, a fast CT (along with breath-hold inhale and exhale CTs to estimate roughly the ITV) is recommended in order to minimize structure distortion. Even with an awareness of a patient's respiratory cycle, its coupling with 3DCT acquisition cannot be predicted since patient anatomy is not accurately known.
WE-FG-202-01: Early Prediction of Radiotherapy Induced Skin Reactions Using Dynamic Infrared Imaging
Purpose: To predict radiotherapy induced skin reactions using dynamic infrared imaging. Methods: Thermal images were captured by our homebuilt system consisting of two flash lamps and an infrared (IR) camera. The surface temperature of the skin was first raised by ∼ 6 oC from ∼1 ms flashes. The camera then captured a series of IR images for 10 seconds. For each image, a baseline skin temperature was recorded for 0.5sec before heat impulse. The temporal temperature gradients were calculated between a reference point (immediately after the flash) and at a time point 9sec after that. Thermal effusivity, an intrinsic thermal property of a material, was calculated from the surface temperature decay of skin. We present experimental data in five patients undergoing radiation therapy, of which 2 were Head & Neck, 1 was Sarcoma and 2 were Breast cancer patients. The prescribed doses were 45 – 60 Gy in 25 – 30 fractions. Each patient was imaged before treatment and after every fifth fraction until end of the treatment course. An area on the skin, outside the radiation field, was imaged as control region. During imaging, each patient’s irradiated skins were scored based on RTOG skin morbidity scoring criteria. Results: Temperature gradient, which is the temperature recovery rate, depends on the thermal properties of underlying tissue. It was observed that, the skin temperature and temporal temperature gradient increases with delivered radiation dose and skin RTOG score. The treatment does not change effusivity of superficial skin layer, however there was a significant difference in effusivity between treated and control areas at depth of ∼ 1.5 – 1.8 mm, increases with dose. Conclusion: The higher temporal temperature gradient and effusivity from irradiated areas suggest that there is more fluid under the irradiated skin, which causes faster temperature recovery. The mentioned effects may be predictors of Moist Desquamation.
Unraveling Morphology and Chemistry Dynamics in Fluoroethylene Carbonate Generated Silicon Anode Solid Electrolyte Interphase Across Delithiated and Lithiated States: Relative Cycling Stability Enabled by an Elastomeric Polymer Matrix
The silicon solid electrolyte interphase (SEI) faces cyclical cracking and reconstruction due to the ∼350% volume expansion. Understanding the SEI dynamic morphology and chemistry evolution from delithiated to lithiated states is thereby paramount to engineering a stable Si anode. Fluoroethylene carbonate (FEC) is a preferred additive with widely demonstrated enhancement of the Si cycling. Thus, insights into the dynamics of the FEC-SEI may provide hints toward engineering the Si interface. Herein, complementary ATR-FTIR, AFM, tip IR, and XPS probing reveal the presence of an elastomeric polycarbonate-like matrix in the FEC-generated SEI which is absent from the FEC-free SEI. Adding FEC to the baseline 1 M LiPF 6 in EC:EMC (1:1) electrolyte promotes formation of a thinner and more conformal SEI, and subdues morphology and chemistry changes between consecutive half-cycles. From AFM, morphological stabilization of the FEC-SEI occurs earlier. Furthermore, conventional SEI biproducts such as Li 2 CO 3 and LiEDC appear in reduced quantities in the FEC-SEI implying a reduced quantity of Li-consuming species. The thin polymeric FEC-SEI enables deeper (de)lithiation of silicon. In conclusion, the enhanced mechanical compliance, chemical invariance, and reduced Li inventory consumption of the FEC-SEI are logically the key features underlying the Si cycling enhancement by FEC.
Reactor Subsystem Simulation for Nuclear Hybrid Energy Systems
Nuclear Hybrid Energy Systems (NHES) could be a key part of the solution to achieving energy security, may provide reliable power availability even with increasing renewable energy penetration into the power grid, and may allow repurposing excess electricity in times of low demand. Incorporating a fission-based power source in a multi-output system (electricity and process heat) can offer significant advantages over carbon-based production sources, such as coal or natural gas, including reduction in atmospheric carbon emissions. In an integrated multi-output system, thermal energy from the nuclear reactor subsystem can be diverted to industrial applications in times of low electricity demand. High temperature, high quality heat from advanced reactor designs might be used for hydrogen production or synthetic fuel production (coal-to-liquid or natural gas-to-liquid processes). Low temperature heat from advanced reactor designs or the current and future fleet of light water reactors (LWRs) might be applied to desalination processes or be stored for later use in low temperature ammonia or hydrocarbon-based thermal cycles. The NHES research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation. Many computational tools and methods are available for modeling a nuclear reactor, power conversion systems and associated process applications. One method is to develop a single program capable of modeling the entire system. Another is to combine two or more existing computer programs, each modeling a portion of the system for which it is validated, where the programs exchange information to compute the solution. The former method requires a lengthy development and verification and validation process. The latter method leverages industry standard software to reduce development and funding requirements. Preliminary system models have been developed by Idaho National Laboratory researchers and are currently being enhanced to assess integrated system performance given multiple sources (e.g., nuclear + wind) and multiple applications (i.e., electricity + process heat). Initial efforts to integrate a Fortran-based simulation of a small modular reactor (SMR) with the balance of plant model have been completed in FY12. This initial effort takes advantage of an existing SMR model developed at North Carolina State University to provide initial integrated system simulation for a relatively low cost. The SMR subsystem simulation details are discussed in this report.
SPITZER OBSERVATIONS OF LONG-TERM INFRARED VARIABILITY AMONG YOUNG STELLAR OBJECTS IN CHAMAELEON I
Infrared variability is common among young stellar objects, with surveys finding daily to weekly fluctuations of a few tenths of a magnitude. Space-based observations can produce highly sampled infrared light curves, but are often limited to total baselines of about 1 month due to the orientation of the spacecraft. Here we present observations of the Chameleon I cluster, whose low declination makes it observable by the Spitzer Space Telescope over a 200-day period. We observe 30 young stellar objects with a daily cadence to better sample variability on timescales of months. We find that such variability is common, occurring in ∼80% of the detected cluster members. The change in [3.6]–[4.5] color over 200 days for many of the sources falls between that expected for extinction and fluctuations in disk emission. With our high cadence and long baseline we can derive power spectral density curves covering two orders of magnitude in frequency and find significant power at low frequencies, up to the boundaries of our 200-day survey. Such long timescales are difficult to explain with variations driven by the interaction between the disk and stellar magnetic field, which has a dynamical timescale of days to weeks. The most likely explanation is either structural or temperature fluctuations spread throughout the inner ∼0.5 au of the disk, suggesting that the intrinsic dust structure is highly dynamic.
The Stellar Imager (SI) "Vision Mission"
The Stellar Imager (SI) is a Vision Mission in the Sun-Earth Connection (SEC) NASA Roadmap, conceived for the purpose of understanding the effects of stellar magnetic fields, the dynamos that generate them, and the internal structure and dynamics of the stars in which they exist. The ultimate goal is to achieve the best possible forecasting of solar/stellar activity and its impact on life in the Universe. The science goals of SI require an ultra-high angular resolution, a t ultraviolet wavelengths, on the order of 100 micro-arcsec and baselines on the order of 0.5 km. These requirements call for a large, multi-spacecraft (>20) imaging interferometer, utilizing precision formation flying in a stable environment, such as in a Lissajous orbit around the Sun-Earth L2 point. In this paper, we present an update on the ongoing SI mission concept and technology development studies.
A Qualitative Study on the Effects of Mesh Guideline Modification for Unstructured Mesh Generation of the NASA High Lift Common Research Model (HL-CRM)
As part of the 1st Geometry and Mesh Generation Workshop, unstructured tetrahedral and unstructured hybrid Computational Fluid Dynamics meshes were generated according to the meshing guidelines supplied by the 3rd High Lift Prediction Workshop. During this process, it was noted that application of some meshing guidelines became a bottleneck in the process and negatively impacted the quality of the meshes. A study is performed to compare the FUN3D simulation from the baseline medium-resolution workshop unstructured mesh with those on meshes resulting from guideline variations to the baseline. Recommendations on the elimination or reduction of meshing guidelines for high lift aerodynamic cases like the High Lift Common Research Model are based on the resulting data.
A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development
The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.
A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development
The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.
Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems
The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability margins. At each time point, the system was linearized about the current operating point using Simulink's built-in solver. Each linearized system in time was evaluated for its rigid-body gain margin (high frequency gain margin), rigid-body phase margin, and aero gain margin (low frequency gain margin) for each control axis. Using the stability margins derived from the baseline linearization approach, the time domain derived stability margins were determined by executing time domain simulations in which axis-specific incremental gain and phase adjustments were made to the nominal system about the expected neutral stability point at specific flight times. The baseline stability margin time histories were used to shift the system gain to various values around the zero margin point such that a precise amount of expected gain margin was maintained throughout flight. When assessing the gain margins, the gain was applied starting at the time point under consideration, thereafter following the variation in the margin found in the linear analysis. When assessing the rigid-body phase margin, a constant time delay was applied to the system starting at the time point under consideration. If the baseline stability margins were correctly determined via the linear analysis, the time domain simulation results should contain unstable behavior at certain gain and phase values. Examples will be shown from repeated simulations with variable added gain and phase lag. Faithfulness of margins calculated from the linear analysis to the nonlinear system will be demonstrated.
Dynamic Analysis of the hFan, a Parallel Hybrid Electric Turbofan Engine
NASA and a variety of aerospace industry stakeholders are investing in conceptual studies of electrified aircraft, including parallel hybrid electric aircraft such as the Subsonic Ultra Green Aircraft Research (SUGAR) Volt. At this point, little of the work published in the literature has examined the transient behavior of the turbomachinery in these systems. This paper describes a control system built around the hFan, the parallel hybrid electric turbofan engine designed for the SUGAR Volt concept aircraft. This control system is used to show that the hFan, running with its baseline concept of operations, is capable of transient operation throughout the envelope. The design parameters of this controller are varied to assess the amount of operability margin built into the engine design, and whether this margin can be reduced to enable more aggressive designs, that may feature better fuel economy. Further, studies are performed as parameters for the hFan electric motor are varied to determine how the motor impacts the engine's need for transient operability margin. The studies suggest that the engine may be redesigned with as much as a 3% reduction in high pressure compressor stall margin. It was also demonstrated that appropriate design and control of the electric motor may be able to buy an additional 0.5% stall margin reduction or a turbine inlet temperature reduction of 35 R, as tested at the sea-level static condition.
Dynamic Analysis of the hFan, a Parallel Hybrid Electric Turbofan Engine
NASA and a variety of aerospace industry stakeholders are investing in conceptual studies of electrified aircraft, including parallel hybrid electric aircraft such as the Subsonic Ultra Green Aircraft Research (SUGAR) Volt. At this point, little of the work published in the literature has examined the transient behavior of the turbomachinery in these systems. This paper describes a control system built around the hFan, the parallel hybrid electric turbofan engine designed for the SUGAR Volt concept aircraft. This control system is used to show that the hFan, running with its baseline concept of operations, is capable of transient operation throughout the envelope. The design parameters of this controller are varied to assess the amount of operability margin built into the engine design, and whether this margin can be reduced to enable more aggressive designs, that may feature better fuel economy. Further, studies are performed as parameters for the hFan electric motor are varied to determine how the motor impacts the engine's need for transient operability margin. The studies suggest that the engine may be redesigned with as much as a 3% reduction in high pressure compressor stall margin. It was also demonstrated that appropriate design and control of the electric motor may be able to buy an additional 0.5% stall margin reduction or a turbine inlet temperature reduction of 35 degR, as tested at the sea-level static condition.
Sediment transport and morphodynamic changes due to upstream variation and sea level rise on the Western Mekong Delta, Vietnam
The hydrological and morphological dynamics across the Vietnam Mekong Delta (VMD) coastline are increasingly shaped by human interventions and climate change, affecting the sustainability of socio-economic environments. This study employs the TELEMAC-MASCARET modeling system (TELEMAC-2D, TOMAWAC, and SISYPHE modules) to simulate hydrodynamics, sediment transport, and morphological changes for a 10-year period under baseline (SC1) and future climate (SC2) scenarios, considering wave climatology of Northeast (NEM) and Southwest monsoons (SWM). The results of sedimentation and erosion were analyzed across five key coastal zones from Ca Mau Cape (KV1) to Ha Tien (KV5). Model results highlight distinct seasonal patterns of sediment redistribution shaped by monsoonal flows, wave action, and seabed morphology. During the NEM, sediment deposition is concentrated near estuarine zones, while the SWM favors offshore sediment accumulation due to perpendicular wave actions, and shallow, gently sloping bathymetry that dissipates wave energy. Coastal erosion predominantly occurs at convex shoreline features subjected to stronger coastal currents, particularly in fine-grained sediment areas. Under future sea level rise and land subsidence scenarios, reduced flow velocities lead to lower bottom shear stress, promoting deposition and mitigating erosion problems despite increased wave energy. Besides that, sediment transport analyses across 14 cross-sections (C-S) reveal a southward trend during the NEM and a northward reversal during the SWM, with upstream sediment reductions primarily influencing near-estuarine zones and exerting minimal impact beyond the mid-coastal regions. Furthermore, these findings advance the understanding of sediment redistribution processes under climate change and seasonal change, and provide a scientific basis for adaptive coastal management and sustainable development.
Roadmap for the future of extreme wildfire events
Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.