Thermal Dynamics Research Articles

Combining a Multi-Lake Model Ensemble and a Multi-Domain CORDEX Climate Data Ensemble for Assessing Climate Change Impacts on Lake Sevan.

Global warming is shifting the thermal dynamics of lakes, with resulting climatic variability heavily affecting their mixing dynamics. We present a dual ensemble workflow coupling climate models with lake models. We used a large set of simulations across multiple domains, multi-scenario, and multi GCM- RCM combinations from CORDEX data. We forced a set of multiple hydrodynamic lake models by these multiple climate simulations to explore climate change impacts on lakes. We also quantified the contributions from the different models to the overall uncertainty. We employed this workflow to investigate the effects of climate change on Lake Sevan (Armenia). We predicted for the end of the 21st century, under RCP 8.5, a sharp increase in surface temperature and substantial bottom warming , longer stratification periods (+55days) and disappearance of ice cover leading to a shift in mixing regime. Increased insufficient cooling during warmer winters points to the vulnerability of Lake Sevan to climate change. Our workflow leverages the strengths of multiple models at several levels of the model chain to provide a more robust projection and at the same time a better uncertainty estimate that accounts for the contributions of the different model levels to overall uncertainty. Although for specific variables, for example, summer bottom temperature, single lake models may perform better, the full ensemble provides a robust estimate of thermal dynamics that has a high transferability so that our workflow can be a blueprint for climate impact studies in other systems.

Unlocking Heat Transfer Potential in Multi-Sided Porous Geometries: A Study on Magnetothermal Effects and Entropy Generation

This study investigates heat transfer efficiency and irreversibility generation in multi-sided porous thermal systems filled with a Cu-Al2O3-water hybrid nanofluid. The research examines convective heat transfer across various polygonal geometries, ranging from four-sided to infinitely-sided (circular) structures, aiming to maximize thermal system performance intended for scientific and industrial applications. For a standardized comparison, the fluid volume and active heating and cooling lengths are kept constant for all the geometries considered. The analysis includes varying flow-controlling variables like the modified Rayleigh number (Ram), Hartmann number (Ha), and Darcy number (Da) to evaluate how they affect heat transfer efficiency and entropy generation, including total, magnetic, and viscous entropy. The numerical simulations, conducted using the finite element approach, explore Ram values ranging from 10 to 104, Ha from 0 to 70, and Da from 10-4 to 10-2. Streamline and isothermal contours analyze flow behavior, while heatline tools reveal thermal energy transport dynamics. Results show up to a 20% improvement in heat transfer efficiency in optimized configurations. Key findings indicate that hexagonal structures can be viable alternatives to circular tubes in space-constrained applications, offering comparable thermal performance. Interestingly, pentagonal cavities exhibit the highest irreversibility due to symmetry loss. The study offers insightful information for enhancing thermal system design in various industrial settings, particularly for applications requiring efficient heat transfer in limited spaces.

Synergistic effects of magnetic fields and Y-obstacles on a nanofluid-based split lid-driven thermal system

This study investigates the complex hydrothermal behavior in a novel split-driven square cavity filled with CuO-water nanofluid and featuring a Y-shaped obstacle. The research explores the interplay among mixed convection, magnetohydrodynamics (MHD), and geometric factors in a previously unexamined configuration. The upper wall is split into two isothermally heated, translating sections, while the bottom wall and Y-shaped obstacle provide cooling boundaries. Using finite element analysis, we examine the effects of Reynolds number (Re = 10-200), Rayleigh number (Ra = 103-106), Hartmann number (Ha = 0-70), and magnetic field inclination (λ = 0-150°) on flow patterns, heat transfer, and entropy generation. Energy flux vectors are utilized to analyze thermal energy transport dynamics. Key findings are as follows. (1) Increasing Re enhances fluid mixing, resulting in up to a 65% increase in the average Nusselt number (Nu). (2) Nu peaks at Ra ≈ 105, then slightly decreases due to complex force interactions. (3) Increasing Ha suppresses convection, reducing Nu by up to 30%. (4) Optimal heat transfer occurs at λ ≈ 75°. (5) The Y-shaped obstacle enhances heat transfer by up to 30%. These results provide insights for optimizing thermal management in applications requiring precise temperature control, potentially improving energy efficiency in advanced heat transfer systems.

Thermal and Flow Dynamics of Magnetohydrodynamic Burgers' Fluid Induced by a Stretching Cylinder with Internal Heat Generation and Absorption

This study investigates the flow dynamics of magnetohydrodynamic Burgers' fluid induced by a stretching cylinder, emphasizing the effects of internal heat generation and absorption. A temperature-dependent heat source is integrated to examine the characteristics of thermal energy transfer within the system. By applying boundary layer theory, we transform the governing partial differential equations into a standard system of ordinary differential equations through similarity transformations. The BVP4C method is utilized to accurately solve the resulting equations for velocity and temperature profiles. Graphical representations illustrate the influence of various physical parameters on both thermal and flow profiles, supported by comprehensive analytical interpretations. To validate our findings, a comparison with existing literature is performed, confirming the consistency and significance of our results. This research offers valuable insights into the thermal and fluid behaviors of Burgers' fluids, with promising applications in the development of advanced biomedical devices.

The oxygen vacancy defect induced by Ar plasma significantly reduces the initial reaction energy barrier of micron thermite and improves its combustion reaction efficiency

In order to reduce the initial reaction energy barrier and combustion reaction efficiency of micron thermite, this work firstly combined Ar plasma surface treatment technology and defect engineering strategy, and applied MoO3, Co3O4 and CuO containing oxygen vacancy to micron thermites to explore the effect of oxygen vacancy defect on the combustion reaction performance of thermites system. Taking the Al/MoO3 thermite system as an example, the results of thermal analysis and molecular dynamics simulation show that the presence of oxygen vacancy promotes the atomic migration of the thermite component atoms at the contact interface, thus reducing the initial reaction activation energy of Al/MoO3 by 29.8 % and increasing the reaction heat release by 56.7 %. This work expands the application of plasma in the field of energetic materials and provides a more efficient and safer method for their modification.

Shorter Ice Duration and Changing Phenology Influence Under-Ice Lake Temperature Dynamics.

Temperate lakes worldwide are losing ice cover but the implications for under-ice thermal dynamics are poorly constrained. Using a 92-year record of ice phenology from a temperate and historically dimictic lake, we examined trends, variability, and drivers of ice phenology and under-ice temperatures. The onset of ice formation decreased by 23days century-1, which can be largely attributed to warming air temperatures. Ice-off date has become substantially more variable with spring air temperatures and cumulative February through April snowfall explaining over 80% of the variation in timing. As a result of changing ice phenology, total ice duration contracted by a month and more than doubled in interannual variability. Using weekly under-ice temperature profiles for the most recent 36years, we found that shorter ice duration decreased winter inverse stratification and was associated with an extended spring mixing period. We illustrate the limitations of relying on discrete ice clearance dates in our assumptions around under-ice thermal dynamics by presenting high-frequency under-ice observations in two recent winters: one with intermittent ice cover and a year with slow spring ice clearance.

On Assessing a Potential Reuse of the Indonesian Post-Operation Offshore Oil/Gas Pipelines as A Cold-Water Pipe for an Ocean Thermal Energy Conversion (OTEC) System: A Thermal and Fluid Dynamic Perspective

One of the main issues arising in offshore oil and gas decommissioning is associated with significant required costs. Research assessing the potential reuse of the post-operation offshore oil and gas pipeline (POGP) in Indonesia for the Ocean Thermal Energy Conversion (OTEC) system offer double the potential cost reductions in POGP decommissioning and OTEC development. In the context of OTEC development, research on increasing system efficiency makes a significant effort by modifying working fluids and usually by employing the assumption that the temperature of the cold seawater at the surface outlet of the Cold-Water Pipe (CWP) is practically the same as that at the inlet of the CWP at a depth of about 900 m. Unfortunately, this was not the case when the POGP was to be reused for the OTEC system because there was difficulty in applying additional insulation to the existing subsea pipelines. The temperature change in the cold seawater is even more critical considering that oil and gas operations at a depth of 900 m could be associated with more than 60 km of pipeline length to reach an onshore system for a typical seabed bathymetry. This paper assesses the potential reuse of the POGP as a CWP for the Ocean OTEC system. The temperature distribution within CWP is analyzed using a thermal and fluid dynamics approach. The results show that the reuse of POGP for the OTEC system could offer an excellent opportunity for capital cost reductions because the POGP has a remaining service life of over 20 years. However, the results of the analysis of heat and mass transfers show that the temperature change in cold seawater at CWP is about 3 to 6 oC, depending on the technical scenarios of the pipelines. The POGP used in the OTEC system could be suitable for a 20 kW OTEC system with practically no cost of pipelines, which usually accounts for a significant investment cost.

CityLearn v2: energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities

As more distributed energy resources become part of the demand-side infrastructure, quantifying their energy flexibility on a community scale is crucial. CityLearn v1 provided an environment for benchmarking control algorithms. However, there is no standardized environment utilizing realistic building-stock datasets for distributed energy resource control benchmarking without co-simulation or third-party frameworks. CityLearn v2 extends CityLearn v1 by providing a stand-alone simulation environment that leverages the End-Use Load Profiles for the U.S. Building Stock dataset to create grid-interactive communities for resilient, multi-agent, and objective control of distributed energy resources with dynamic occupant feedback. While the v1 environment used pre-simulated building thermal loads, the v2 environment uses data-driven thermal dynamics and eliminates the need for co-simulation with building energy performance software. This work details the v2 environment and provides application examples that use reinforcement learning control to manage battery energy storage system, vehicle-to-grid control, and thermal comfort during heat pump power modulation.

Low-Frequency Electrical Heating for In Situ Conversion of Shale Oil: Modeling Thermal Dynamics and Decomposition

In situ conversion presents a viable strategy for exploiting low to moderate maturity shale oil. Traditional methods, however, require dense well patterns and substantial energy, which are major hurdles. This study introduces a novel approach employing low-frequency electrical heating via production wells to enhance heat transfer without necessitating additional heating wells. Utilizing a self-developed simulator, we developed a numerical model to evaluate the efficacy of this method in augmenting reservoir temperature and facilitating substance decomposition. Findings indicate that low-frequency electrical heating significantly elevates reservoir temperatures, accelerates hydrocarbon cracking, and boosts fluid production. A sensitivity analysis on various heating strategies and reservoir characteristics showed that elevated heating power can further pyrolyze the heavy oil in the product to light oil, while higher porosity formations favor increased oil and gas output. The study also explores the effect of thermal conductivity on heating efficiency, suggesting that while better conductivity improves heat distribution, it may increase the proportion of heavy oils in the output. Overall, this investigation offers a theoretical foundation for refining in situ conversion technologies in shale oil extraction, enhancing both energy efficiency and production quality.

Electro-thermal dynamics in superconducting generators: An In-Depth investigation of AC losses and cooling techniques for a 10 MW rotor coil system

In the pursuit of optimizing superconducting generator systems, a comprehensive understanding of their electro-thermal behaviors is crucial. This study builds upon previous research on an 8-pole, 10 MW superconducting generator by Inanir et al. (2022, Journal of Superconductivity and Novel Magnetism, 35(11), 3189) and focuses on an in-depth electro-thermal analysis of the rotor coil system. The emphasis is on assessing the AC losses experienced during transitory current changes. By simultaneously solving Ampere's equation and the heat conduction equation under specific boundary conditions, the research provides a detailed insight into the interaction between electrical and thermal dynamics within the rotor coils. The paper highlights the importance of temperature dynamics in various cooling and current conditions. The results demonstrate that achieving an optimal balance in cooling, particularly with the use of liquid nitrogen, is critical for efficient operation. This study not only advances the understanding of superconducting generators but also highlights potential strategies for improving their reliability and efficiency.

Breakdown of thermalization in spin chains with single-ion anisotropy

The principles of ergodicity and thermalization constitute the foundation of statistical mechanics, positing that a many-body system progressively loses its local information as it evolves. Nevertheless, these principles can be disrupted when thermalization dynamics lead to the conservation of local information, as observed in the phenomenon known as many-body localization. Quantum spin chains provide a fundamental platform for exploring the dynamics of closed interacting quantum many-body systems. This study explores the dynamics of a spin chain with S≥1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S\\ge 1/2$$\\end{document} within the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$J_1-J_2,$$\\end{document} incorporating a non-uniform magnetic field and single-ion anisotropy. Through the use of exact numerical diagonalization, we unveil that a nearly constant-gradient magnetic field suppresses thermalization, a phenomenon termed Stark many-body localization (SMBL), previously observed in S=1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S=1/2$$\\end{document} chains. Furthermore, our findings reveal that the sole presence of single-ion anisotropy is sufficient to prevent thermalization in the system. Interestingly, when the magnitudes of the magnetic field and anisotropy are comparable, they compete, favoring delocalization. Despite the potential hindrance of SMBL by single-ion anisotropy in this scenario, it introduces an alternative mechanism for localization. Our interpretation, considering local energetic constraints and resonances between degenerate eigenstates, not only provides insights into SMBL but also opens avenues for future experimental investigations into the enriched phenomenology of disordered free localized S≥1/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S\\ge 1/2$$\\end{document} systems.

Optimal control of Hydrocarbon Reducer (HC) injection based on Trust-Region-Reflective Algorithm (TRRA) and physical models for Diesel Oxidation Catalyst (DOC)

The aim of this paper is to control the DOC outlet gas temperature between 600 ± 15 °C by optimizing the hydrocarbon (HC) injection into the Diesel Oxidation Catalyst (DOC) for active regeneration of the downstream Diesel Particulate Filter (DPF). First, based on the physical model of the DOC thermal dynamics, the energy conservation equation for the gas phase temperature is simplified by using variable substitution, and the energy conservation equation for the solid phase temperature is simplified by considering only the heat generated by the HC injection. By solving the simplified model using the Trapezoidal Rule-Backward Differentiation Formula 2 (TR-BDF2) method and optimizing the model parameters in combination with the Gauss-Newton method, the computational efficiency and accuracy were significantly improved. Next, the DOC downstream temperature observer is designed by combining the solution characteristics of the DOC model with the unscented Kalman filter (UKF) algorithm to ensure that the catalyst operates within the optimal temperature range. Then, this paper verifies the accuracy of the model and observer through bench tests covering four steady-state operation conditions and World Harmonized Transient Cycle (WHTC) test cycle, and the results show that the model and observer exhibit high accuracy in both steady-state and transient operation conditions. Finally, the DOC temperature was successfully maintained between 600 ± 15 °C by optimizing the control of the HC injection rate, thus achieving the expected temperature control target. These research results provide theoretical and practical support for diesel engine emission control and DPF active regeneration.

Modeling of a metal hydride energy storage tank dynamics using hybrid numerical, experimental, and machine learning methods

This study presents an integrated analysis combining numerical simulations, experimental investigations, and machine learning models to simulate the performance of metal hydride systems for hydrogen storage under various conditions by using a LaNi5 metal hydride cylindrical tank of 500 NL capacity, with a focus on PCM thermal enhancements and surface water heating and cooling. Numerical simulations offer insights into thermal and reaction dynamics, while experimental data are used for model validation and supplemented with additional numerical data for training a FFNN model to predict dynamic hydrogen flow, surface temperature, and surface heat flux. The obtained mean RMSEs for charging/discharging experimental data is 2.8 SOC% for the state of charge and 0.3 °C for surface temperatures. The study compares the effectiveness of water cooling and heating in metal hydride surface across different temperatures, highlighting their impact on the efficiency of hydrogen absorption and desorption processes. Energy consumption is shown to be non-linear; during charging, heat flux peaks before decreases rapidly within around 0.2 h. During discharging, heat flux rises steadily. The study also explores the impact of adding copper fins to the PCM covering metal hydride system, revealing significant improvements in charging and discharging efficiency, specifically, the integration of 16 copper fins led to a notable decrease in complete charging time from approximately 6.5 h to just over 5.2 h, and in complete discharging time from around 4.5 h to under 3.96 h. Using PCM, the highest heat flux is 5 times less during charge and 2 times less during discharge than that for water cooling mode.

An efficient computational investigation on accurate daily soil temperature prediction using boosting ensemble methods explanation based on SHAP importance analysis

Accurately predicting soil temperature (Ts) serves as the foundation of geothermal applications, modern irrigation strategies in arid agricultural landscapes, and understanding ecosystem changes. Also, this parameter is crucial for estimating crop water requirements, thereby enabling efficient management of scarce water resources in these moisture-limited environments. Therefore, the development of a sophisticated intelligent algorithm based on boosting ensemble including XGBoost, CatBoost, LightGBM, and AdaBoost models which incorporates nine different scenarios from meteorological variables as input parameters, offers valuable insights into subsurface thermal dynamics at various depths for accurately predicting thermal gradients within the soil profile, is imperative for soil science investigations. To unravel the underlying mechanisms influencing the models' predictions of Ts, the SHapley Additive exPlanations (SHAP) methodology was employed. This algorithm quantifies the contributory significance of each input variable and facilitates the explication of input-output dependencies. In this study, the model's performance was evaluated at two meteorological monitoring sites, denoted as Penjwen and Bazian, situated within the geopolitical boundaries of the Kurdistan region in Iraq using a suite of statistical indicators, including the correlation coefficient (R), the root mean square error (RMSE), the Nash-Sutcliffe efficiency (NSE), and the mean absolute error (MAE). These metrics provided a comprehensive assessment of the model's predictive accuracy and reliability. Moreover, this localized analysis provided insights into the model's efficacy under specific regional climatic conditions. At station Penjwen, the results based on the RMSE values indicated that the LightGBM and CatBoost methods performed better than other models in Ts estimation at depths of 5 cm and 10 cm, with RMSE values of 2.502 °C and 2.164 °C, respectively. Also, at station Bazian, CatBoost and LightGBM approaches showed the best results at depths of 5 cm and 10 cm, with RMSE values of 2.069 °C and 1.786 °C, respectively. The study's findings suggest that meteorological variables can serve as effective inputs for predicting Ts using the proposed algorithms.

A real-time phase transition modeling of supercritical steam cycle and load variation rate enhancement of thermal power plants under deep peak shaving

The ambitious green revolution to renewable energy sources in global power grids necessitates massive integration of solar and wind energy, which involves intermittent and unpredictable challenges. Thermal power plants are crucial in stabilizing the grid and addressing these challenges through flexibility reformation including deep peak shaving and frequent load variations since the unsteady state energy transfer and thermal dynamics during combustion and heat transformation in thermodynamic processes vary significantly. These conditions lead to issues such as furnace instability and latent heat of phase transition. This study introduces a novel approach to modeling phase transitions of supercritical steam cycle, and investigatesthe length, position, temperature, and energy transfer of the working medium and components under normal and low operational states. Conducting and analyzing the thermal feasible region associating the security of components and working medium this study establishes a control strategy for dynamic heat transfer to reduce component degradation effects andenhance load variation rate under flexible operations. Simulation model of a supercritical power unit based on the proposed method demonstrates an accuracy of 97.94%. Results from the optimal approach in maximizing load variation rate show the effectiveness and achieve 1.2%p.e./min most under transition process.

Inspection and comparative analysis of light and thermal response dynamics of Cu/V₂O₅/n-Si and Cu/La-V₂O₅/n-Si MIS diodes

Schottky Barrier Diodes (SBDs) are pivotal in modern electronics for their quick switching and low forward voltage drop, enabled by metal-semiconductor junctions. SBDs are renowned for their performance, primarily due to their metal-semiconductor intersection. This study focuses on Cu/V2O5/n-Si and Cu/La-V2O5/n-Si SBDs, examining the impact of lanthanum doping on their performance. Transition Metal Oxides (TMOs) like Vanadium Pentoxide (V2O5) offer unique electronic, magnetic and optical properties making them suitable for various applications. The fabrication process involved sol-gel spin coating and DC magnetron sputtering to create a thin V2O5 layer on n-type silicon wafers, followed by copper contact deposition. Galvanizing temperatures ranged 300° C to 500° C to study the structural, optical, and morphological changes in V2O5 thin films. Key findings include the significant reduction in ideality factor (n) with increasing annealing temperatures for Cu/V2O5/n-Si SBDs, reaching as low n value of 5.26 at 500°C, indicating improved device performances. For Cu/La-V2O5/n-Si SBDs, the ideality factor consistently decreased with higher light intensities, showcasing enhanced performance due to La doping. Barrier height (ɸB) also varied, with higher values observed for La-doped V2O5, enhancing charge recombination and increasing oxygen vacancies. Photodiode parameters were significantly enhanced by doping of the La. The Cu/La-V2O5/n-Si SBDs demonstrated high photosensitivity (PS = 3327.5 %), photo responsivity (R = 33.39 mA/W) and detectivity (D* = 9.82 × 10¹⁰ Jones), making them highly efficient for optoelectronic applications. Overall, this study highlights the potential of Cu/La-V2O5/n-Si SBDs for high-efficiency, optoelectronic applications, with optimized doping concentrations and annealing conditions significantly improving their performance.

Initial impacts of wildfire on overwintering conditions for a Species-at-Risk snake

Peatlands are important ecosystems that are becoming increasingly vulnerable to climate-mediated disturbances such as wildfire, which can threaten peatland hydrological, biogeochemical, and ecological function. However, the magnitude of these changes and their impacts to peatland-dependent species worldwide is a key knowledge gap. Peatlands in the eastern Georgian Bay, Ontario, region provide overwintering habitat for the eastern massasauga rattlesnake (Sistrurus c. catenatus), a species considered at-risk across its North American range. Overwintering habitat is considered suitable when peat temperature is above 0°C and the water table position provides moisture without risk of prolonged flooding. This combination of suitable ecohydrological conditions, also known as the life zone or resilience zone, commonly occurs in hummocks which are raised microforms on the peatland surface. Due to a changing climate, peatlands are at risk of increased wildfire frequency and burn severity which may reduce overwintering habitat availability and suitability through changes in peat thermal and hydrological properties. In 2018, a wildfire burned over 11,000 ha of the eastern Georgian Bay landscape which supports critical habitat for the massasauga at the northern limit of the species range. To assess the potential impact of wildfire on massasauga overwintering habitat, we monitored water table position, snow depth, and peat thermal dynamics in hummocks across a burn severity gradient (unburned to severely burned) in three burned and three unburned peatlands across three winters (2019–2022). We found that hummocks were able to provide unflooded habitat above 0°C regardless of peat burn severity; however, there was moderate evidence that hummock burn severity influenced mean daily resilience zone size. Overall, hummock overwintering suitability appears to be dominantly controlled by peatland surface topography and interannual winter weather. With the frequency and intensity of wildfires predicted to increase globally under a changing climate, it is critical to understand how interannual variability of winter weather conditions influences overwintering habitat suitability after wildfire, to identify peatland ecosystems that provide resilient species at risk habitat.

Development of an integrated energy and thermal planner for a series hybrid off-road autonomous tracked vehicle

Electrifying off-road vehicle powertrains enhances energy efficiency and auxiliary power generation but poses control challenges due to extreme temperatures, complex terrain, powerful cooling systems, and high-power demands. This paper presents the Integrated Energy and Thermal Planner (IETP), a unified approach to energy and thermal management for off-road series hybrid tracked vehicles. The IETP addresses challenges posed by extreme ambient temperatures, high-power demands, and complex non-linear thermal dynamics by integrating the control of thermal systems with energy planning. The synergistic operation of the ICE-Generator and thermal actuators reduces battery degradation by up to 29% compared to traditional separated energy and thermal management. Additionally, IETP improves fuel efficiency by at least 10% in power-demanding high-speed driving scenarios. Key contributions include the ’priority-speed’ formulation, which optimizes the ICE-Gen’s operating point in a computationally efficient manner, and a systematic sensitivity analysis to balance planning accuracy with hardware constraints. Real-time planner-in-the-loop application mitigates execution delays through a memory buffer and compensation strategy. Despite uncertainties in modeling and preview assumptions, the IETP demonstrates robustness, with future work aimed at further improving transient compensation and estimation routines. This integrated strategy enhances both the efficiency and durability of hybrid electric vehicles in extreme off-road environments.

A thermal flexible rotor dynamic modelling for rapid prediction of thermo-elastic coupling vibration characteristics in non-uniform temperature fields

The flexible rotors within aero-engines operate in complex thermal environments, where temperature influences both the vibration frequency and amplitude. This study establishes a simple thermal flexible rotor dynamics model to rapidly and precisely predict thermo-elastic coupling vibration characteristics within a non-uniform temperature field. The thermal potential energy of the thermal rotor element is derived for any temperature field, and the motion equation is obtained using the Euler-Lagrange equation. Specifically, the generalized vector of an arbitrary point and cross-sectional non-uniform thermal stress of the thermal rotor element are considered in the thermal potential energy. The model's frequency error is <1 % under identical boundary conditions. Numerical findings indicate that thermal stress, temperature-dependent material properties, and the coupling effect collectively reduce the natural frequency (NF), with thermal stress having a more pronounced impact under axial constraint. Additionally, thermal stress and material decrease the amplitude across a broad range of rotation speeds, contrasting with thermal bending. This model will play a key role in the iterative calculation of thermo-elastic coupling vibration control due to its accuracy and simplicity.

Enhancing model temperature estimations in shallow, turbid, coastal regions: Mobile Bay, Alabama

Accurate estimation of water column temperature is vital for modeling physical and biogeochemical processes. A key process in the thermal dynamics of the upper ocean is the attenuation of solar radiation. In shallow-turbid coastal systems, spatially and temporally varying optical characteristics present challenges for commonly used attenuation parameterization schemes. This study investigates the dependency of temperature with a ROMS model of Mobile Bay, a shallow, turbid estuary, using six different attenuation approaches including three base cases: Conventional approach PS77 based on water type-9; Novel approach SAL relating in situ PAR attenuation to salinity; and Surface trapped irradiance method ST. In addition, these base cases are also tested with surface atmospheric heat flux correction (QC). Simulations were validated against observations from various sources to identify the optimal approach at annual and synoptic scales. While all simulations showed effective temperature performance over an annual cycle, monthly analysis revealed some seasonality, with winter months typically performing better than summer months. The influence of QC notably enhanced temperature performance in both annual and synoptic scales, given that surface heat flux primarily drove temperature changes in this shallow system. The best overall performance was determined to be the ST approach incorporating QC. Conversely, PS77 without QC demonstrated the poorest performance. The SAL model with QC, notably improved performance over PS77 with QC, yet demonstrated comparable yet weaker performance compared to the ST model with QC. The study also implies that neglecting subseasonal validation in long-term regional climate modeling could introduce uncertainty into analyzing events tied to subseasonal temperatures.