Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Fuel Performance Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,189 records · Page 66

Modeling Synergistic Fuel Cell Membrane Degradation with Mitigating Effects of Cerium

During operation, polymer-electrolyte-membrane (PEM) fuel cells undergo mechanical and chemical degradation mechanisms, which behave synergistically and lead to accelerated membrane degradation over time. This study builds upon previous modeling work on mechanical degradation as described by a pinhole in the membrane and the effects of cerium on chemical degradation.1 By combining these two models, analysis can be carried out on the coupled degradation methods and how the mitigation effects of cerium disrupt the degradation cycle. The mechanical model represents a pinhole in the membrane using an effective void fraction, which allows for increased gas crossover through the membrane and impacts the membrane transport and mechanical properties. A microkinetic model for the chemical degradation is included in the model, including attack of the membrane polymer by hydroxyl radicals as well as the mitigation reaction for quenching of hydroxyl radicals with cerium. A concentrated solution theory approach is used to model the transport of cerium ions throughout the cell.2 The model results show how the location of cerium in the cell can be used to prevent chemical degradation. In addition, the model shows how cerium slows down the rate of pinhole growth by reducing the gas crossover and membrane thinning rate. Finally, the model can be used to optimize the distribution of cerium in the membrane and catalyst layers by balancing trade-offs between lowering degradation rates and decreasing fuel cell performance.

25 ENERGY STORAGE↗

Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays

Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydrogen station in situ back-to-back fueling data for design and modeling

Hydrogen technologies are rapidly spreading, with significant attention to the mobility sector requiring a robust and widespread fueling infrastructure. Hydrogen stations are indeed fundamental to transitioning from pilot projects towards large-scale implementation in many countries. Operating under extreme conditions, the new stations need more informed designs and equipment to meet the growing demand and their more frequent utilization. Via a set of experimental research activities and investigated scenarios carried out at the Cal State LA Hydrogen Research and Fueling Facility, here this paper shares a novel and comprehensive set of data collected over a period of one year on fueling events frequency and refueling process station behaviors. A performance evaluation of the station is presented under different load scenarios in severe conditions during "back-to-back fuelings", with monitoring of fundamental parameters for infrastructure sizing, including dynamic cooling response, pressure levels, thermodynamics, and the state of charge of the vehicle. The presented data analysis could surely contribute as closer-to-reality inputs for a variety of station performance modeling tools.

08 HYDROGEN↗

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sensitivity analysis, surrogate modeling, and optimization of pebble-bed reactors considering normal and accident conditions

This research provides a valuable tool that streamlines the optimization process while significantly increasing its accuracy. This study creates a robust framework for reactor design optimization by incorporating comprehensive modeling using the Comprehensive Reactor Analysis Bundle, or BlueCRAB, within the Multiphysics Object-Oriented Simulation Environment (MOOSE). BlueCRAB is the United States Nuclear Regulatory Commission's code suite for non-light water reactor analysis and includes the Griffin, Pronghorn, and Bison applications. This not only improves the efficiency of the optimization process but also enhances the reliability of the results. Such a tool is essential for advancing the state-of-the-art in pebble-bed reactor technology and is critical for achieving the goals of Generation IV reactors, which aim for safe, sustainable, and economically viable nuclear energy solutions. This work presents and applies this workflow on pebble-bed reactors while considering both normal and off-normal conditions. A representative gas-cooled pebble-bed reactor at equilibrium core conditions serves as the nominal design specification for normal operation and is based on previous research. The depressurized loss-of-forced-cooling accident is deployed for off-normal conditions in this work. After defining design-related parameters and quantities of interest regarding reactor safety and performance, this multiphysics model is sampled using the MOOSE stochastic tools module. The result is a comprehensive dataset of configurations, enabling sensitivity analysis and the generation of surrogate models. Subsequently, the dataset and surrogate models are employed in two optimization studies aimed at maximizing fuel utilization and economic profit while adhering to safety and operational constraints. Performing the optimization process with fuel utilization as the metric leads to an improvement of approximately 10%, compared to engineering-judgment-based nominal conditions. The optimization on economic profit leads to an estimated increase of ~300 million USD over the lifetime of the reactor.

97 MATHEMATICS AND COMPUTING↗

Verification of a Depletion Method in SCALE for the Advanced High Temperature Reactor

This study describes a new approach employing the Dancoff correction method to model the TRISO-based fuel form used by the Advanced High-Temperature Reactor (AHTR) reactor design concept. The Dancoff correction method is used to perform isotope depletion analysis using the TRITON sequence of SCALE and is verified by code-to-code comparisons. The current AHTR fuel design has TRISO particles concentrated along the edges of a slab fuel element. This geometry prevented the use of the DOUBLEHET treatment, previously developed in SCALE to model spherical and cylindrical fuel. The new method permits fuel depletion on complicated geometries that traditionally can be handled only by continuous energy based depletion code systems. The method was initially tested on a fuel configuration typical of the Next Generation Nuclear Plant (NGNP), where DOUBLEHET treatment is possible. A confirmatory study was performed on the AHTR reference core geometry using the VESTA code, which uses the continuous energy MCNP5 code as a transport solver and ORIGEN2.2 code for depletion calculations. Comparisons of the results indicate good agreement of whole core characteristics, such as the multiplication factor and the isotopics, including their spatial distribution. Key isotopes analyzed included 235U, 239Pu, 240Pu, and 241Pu. The results from this study indicate that the Dancoff factor method can generate estimates of core characteristics with reasonable precision for scoping studies of configurations where DOUBLEHET treatment cannot be performed.

AHTR↗

Robust attitude control for Cassini spacecraft flying by Titan

This paper summarizes a few years attitude control design work on Cassini spacecraft with emphasis on the mission of Titan flyby. The study consists of modeling of the spacecraft dynamics, fuel sloshing, aerodynamic disturbance, controller design, nonlinear simulation, and establishing geometric command profiles. Both classical bang-bang control and modern robust H-infinity control have been designed and evaluated in nonlinear simulation to access the system tracking performance. Design procedures as well as their critical design issues are discussed in detail. Full model nonlinear simulations indicate that a simple 12-state H-infinity controller achieves better radar tracking performance than the classical bang-bang controller with less fuel throughout the flyby mission. Detailed robustness analysis of both designs will be published elsewhere.

Chiang, R.↗

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗

Transportation Deployment; NREL (National Renewable Energy Laboratory)

Automakers, commercial fleet operators, component manufacturers, and government agencies all turn to the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) to help put more green vehicles on the road. The lab’s independent analysis and evaluation pinpoint fuel-efficient and low-emission strategies to support economic and operational goals, while breaking down barriers to widespread adoption. Customized assessment of existing equipment and practices, energy-saving alternatives, operational considerations, and marketplace realities factor in the multitude of variables needed to ensure meaningful performance, financial, and environmental benefits. NREL provides integrated, unbiased, 360-degree sustainable transportation deployment expertise encompassing alternative fuels, advanced vehicles, and related infrastructure. Hands-on support comes from technical experts experienced in advanced vehicle technologies, fleet operations, and field data collection coupled with extensive modeling and analysis capabilities. The lab’s research team works closely with automakers and vehicle equipment manufacturers to test, analyze, develop, and evaluate high-performance fuel-efficient technologies that meet marketplace needs.

33 ADVANCED PROPULSION SYSTEMS↗

An investigation on the fuel savings potential of hybrid hydraulic refuse collection vehicles

Highlights: • Driving cycle acquisition in a refuse collection vehicle. • Vehicle modeling and validation for numerical simulations based on the measured driving cycle. • Fuel consumption analysis for a conventional diesel vehicle and a hybrid hydraulic vehicle. - Abstract: Refuse trucks play an important role in the waste collection process. Due to their typical driving cycle, these vehicles are characterized by large fuel consumption, which strongly affects the overall waste disposal costs. Hybrid hydraulic refuse vehicles offer an interesting alternative to conventional diesel trucks, because they are able to recuperate, store and reuse braking energy. However, the expected fuel savings can vary strongly depending on the driving cycle and the operational mode. Therefore, in order to assess the possible fuel savings, a typical driving cycle was measured in a conventional vehicle run by the waste authority of the City of Stuttgart, and a dynamical model of the considered vehicle was built up. Based on the measured driving cycle and the vehicle model including the hybrid powertrain components, simulations for both the conventional and the hybrid vehicle were performed. Fuel consumption results that indicate savings of about 20% are presented and analyzed in order to evaluate the benefit of hybrid hydraulic vehicles used for refuse collection.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SAS4A/SASSYS-1 Version 5.7 and 5.6 Release Notes

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. In this report, the major developments that were implemented in Versions 5.7 and 5.6 are summarized and an overview of all changes made between versions is presented. SAS Version 5.7 and 5.6 introduced a number of modeling improvements that allow users to capture important phenomena, such as pump heating and metallic fuel performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermal Spectrum Molten Salt-Fueled Reactor Reference Plant Model

This report details a fully coupled neutronics thermal hydraulics reference plant model for a thermal spectrum molten salt-fueled reactor. The Multiphysics model is developed on the Nuclear Regulatory Commission's Comprehensive Reactor Analysis Bundle available on the Idaho National Laboratory high-performance computer, which natively and seamlessly couples Griffin and Sam codes of the Multiphysics Object-Oriented Simulation Environment (MOOSE) based applications. Griffin provides the reactor physics capabilities, k-eigenvalue, delayed neutron precursor concentrations, and transient solutions for stationary and flowing fuels. Sam provides the solution of mass, momentum, and energy conservation equations of the whole system with a set of system components for one-dimensional single-phase flow. The neutronics feedback model relies primarily on fuel and moderator temperatures, fuel salt density, and delayed neutron precursors distributions. This report presents our results for the coupled steady state core and an unprotected loss of flow event. Although this model is prototypical regarding capabilities in the Comprehensive Reactor Analysis Bundle, its results are consistent with experimental data of the pump transient tests that were performed at zero power of the Molten Salt Reactor Experiment (MSRE).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An Experimental and Numerical Investigation to Characterize the Low-Temperature Heat Release in Stoichiometric and Lean Combustion

This work reports on an experimental and modeling study on the low-temperature heat release (LTHR) characteristics for three RON 90 binary blends (n-heptane blended with isooctane, toluene and ethanol) in a Cooperative Fuel Research (CFR) engine at lean and stoichiometric conditions that are representative of homogeneous charge compression ignition (HCCI) and spark-ignition (SI) end-gas combustion conditions, respectively. An analysis of the end-gas temperature-pressure (T-P) trajectories was performed to identify the intake conditions leading to similar T-P trajectories between the two lambdas for each fuel blend. A heat release analysis was then conducted for the identified cases, where fuel-to-fuel differences in LTHR were identified and found to be sensitive to the operating condition. Simulations were conducted for these cases using a recently updated chemical kinetic model and a 0-D engine model, where good qualitative and reasonable quantitative agreements in LTHR were obtained. Sensitivity analysis was also performed directly on the rates of LTHR, to understand the controlling chemical reactions of LTHR, providing further insights into the fuel-to-fuel differences. The results demonstrate the significant promoting effect of n-heptane on LTHR rates, while inhibiting effects were seen for ethanol and toluene. Also highlighted was the importance of H atom abstraction reactions from the chemistry of each fuel component, which could lead to contradictory fuel behavior depending on the locations of the H site of the abstraction reaction due to the different ensuing pathways for the primary fuel radicals.

LTHR, RON 90 binary blends, sensitivity analysis↗

Reactivity Feedback Modeling in SAM

System Analysis Module (SAM) is being developed at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report presents the development of Point-Kinetics modeling and reactivity feedback mechanisms in SAM. It also presents a new capability for predicting the thermal expansion in various structural components by coupling SAM with an external thermomechanics module (Tensor Mechanics) from the MOOSE framework. The analysis of the transient behavior of a nuclear reactor requires the coupled simulation of reactor kinetics and thermal-hydraulics of the reactor core, especially for those unprotected transients where the reactor scram system may not function properly. The point kinetics model has been widely used for reactor safety analysis due to its simplicity to capture the transient behavior of the reactor. Various reactivity feedback models have been developed and integrated with the Point-Kinetics module, including fuel axial expansion, core radial expansion, fuel Doppler, and coolant density reactivity. The reactivity feedback models in SAM are similar to the respective models used in SAS4A/SASSYS-1. This report first presents the brief theory of the Point-Kinetics module and reactivity feedback models. A number of verification tests have been performed where the code simulations are compared to the analytical model results. The reactivity feedback due to the thermal deformation, such as the fuel axial expansion and core radial expansion, is important for SFR transient analysis. Simplified thermal expansion models for the fuel pin and reactor constrain system (e.g. grid plate) are developed and verified in SAM. Additionally, a coupling interface is developed to couple SAM with external thermomechanical analysis modules for more accurate predictions of the thermal expansion of different components during the transients. The current coupling interface has been tested with the Tensor Mechanics module from MOOSE. These point kinetics and reactivity feedback modeling capabilities have also been demonstrated by simulating the early stage of the unprotected loss-of-flow (ULOF) accident in the Advanced Burner Test Reactor (ABTR). Both the stand-alone SAM and coupled SAM and Tensor Mechanics simulations are performed. It is confirmed that the major physics phenomena in the heat transport system of the ABTR reactor are captured by SAM, and the point kinetics model, reactivity feedback models, and the coupling schemes are working well as expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Counterflow ignition of n-butanol at atmospheric and elevated pressures

Vital to the development of predictive combustion models is a robust understanding of the coupled effects of chemical kinetics and convective–diffusive transport at both atmospheric and elevated pressures. The current study describes a new variable-pressure non-premixed counterflow ignition experiment designed to address the need for well-characterized reference data to validate such models under conditions sensitive to both chemical and transport processes. A comprehensive characterization of system behavior is provided to demonstrate boundary condition and ignition quality as well as adherence to the assumption of quasi-one-dimensionality, and suggest limitations and best practices for counterflow ignition experiments. This effort reveals that the counterflow ignition experiment requires special attention to ignition location in order to ensure that the assumption of quasi-one-dimensionality is valid, particularly at elevated pressures. This experimental tool is then applied to the investigation of n-butanol for pressures of 1–4 atm, pressure-weighted strain rates of 200–400 s -1 , and fuel mole fractions of 0.05–0.25. Results are simulated using two n-butanol models available in the literature and used to validate and assess model performance. Comparison of experimental and numerical ignition results for n-butanol demonstrates that while existing models largely capture the trends observed with varying pressure, strain rate, and fuel loading, the models universally over-predict experimental ignition temperatures. While several transport coefficients are found to exhibit order-of-magnitude or greater sensitivities relative to reaction rates, variation of transport parameters is not able to account for the large deviations observed between experimental and numerical results. Additional comparison of ignition kernel structure and fuel breakdown pathways between two literature models suggests that an under-prediction in the radical pool growth with respect to temperature variation may be responsible for both the deviation from the experimental results and the discrepancy in ignition temperature results observed between models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

FIDES-II/P2M Simulation Exercise on AN3 and AN10 bump tests: main results

This paper presents simulations of bump tests conducted as part of the P2M (Power to Melt and Maneuverability) project within the OECD/NEA FIDES-II framework (Framework for Irradiation Experiments). To prepare fuel performance codes for analyzing the P2M experiments, an international Simulation Exercise (SE) was initiated under the P2M project. The objective of this exercise was to model the AN3 and AN10 bump tests carried out in the 1980s at the DR3 reactor (3rd RISØ Fission Gas Project), during which instrumented fuel rodlets (equipped with thermocouples and pressure sensors) were subjected to prolonged power transients and power dips. The ongoing simulation exercise involves seven organizations from industry, research, and regulatory bodies, each using different fuel performance codes. This paper provides detailed descriptions of the test cases and simulation results from six fuel performance codes (ALCYONE, BISON, FAST, FEMAXI, FRAPCON, and TRANSURANUS), with a particular focus on fission gas release kinetics.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Cooperative On-Ramp Merging with Time-Varying Vehicle-to-Vehicle Communication Delay Compensation via a Model-Free Approach

Cooperative merging strategies enabled by vehicle-to-vehicle (V2V) communication have shown promise in addressing congestion, fuel inefficiency, and collision risks. However, their performance can be severely degraded by time-varying and uncertain communication delays-an issue often overlooked in existing research, which primarily focuses on merging sequence determination and trajectory planning. Furthermore, practical considerations such as heterogeneous vehicle dynamics, varying road conditions, and real-time implementation complexities are frequently neglected. This paper presents a model-free, online planning framework for cooperative on-ramp merging of connected and automated vehicles (CAVs), explicitly accounting for time-varying V2V communication delays. Without relying on detailed vehicle dynamics, the proposed method introduces a data-driven delay compensation scheme. A co-simulation platform integrating high-fidelity vehicle dynamics, traffic simulation (SUMO), and V2V communication within MATLAB/Simulink is developed to evaluate the proposed method. Simulation results demonstrate that unaddressed V2V communication delays significantly impair merging performance. In contrast, the proposed framework enhances intervehicle distance tracking and maintains low CO2 emissions and fuel consumption, under communication delay across different communication frequencies. In conclusion, its lightweight design also facilitates real-time implementation, making it well-suited for deployment in practical CAV systems.

Accounting↗