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At least 37 records · Page 2

Pseudospectral convex optimization for on-ramp merging control of connected vehicles

It can be a daunting task for human drivers to merge into highways because of the intricate vehicle negotiations and potential risk within limited time and space. Connected vehicle (CV) technologies could be a solution to this problem and offer many benefits to the road safety, traffic mobility, and energy efficiency. However, real-time optimal control of CVs is still an open challenge, due to the nonlinear vehicle dynamics, non-convex fuel consumption model, and highly dynamic uncertain inter-vehicle interactions. To tackle these issues, a novel real-time optimal control approach that balances the computational efficiency and solution optimality is proposed for the purpose of onboard application. To this end, the pseudospectral collocation method is integrated with a sequential convex programming approach to develop two new optimization algorithms, which are implemented within a model predictive control (MPC) framework to allow for real-time generation of optimal merging speed profiles. One algorithm leverages the line search technique to improve convergence, and the other benefits from the trust region method for better computational efficiency. The optimality and convergence process of both proposed algorithms are investigated by comparing their solutions with a popular non-linear solver. Furthermore, simulation results show that the proposed methods outperform the benchmark in terms of computational cost, fuel consumption, and traffic efficiency. In particular, the proposed fuel-economy merging rule can save 57.1% fuel consumption on average on four different traffic volumes. Meanwhile, the proposed optimal control algorithms can reduce 2.2% travel time on average comparing to the “first-in-first-out” merging rule.

33 ADVANCED PROPULSION SYSTEMS↗

Optimizing on-ramp merging for connected and automated vehicles: A hierarchical approach using deep reinforcement learning and optimal control

On-ramp merging for Connected and Automated Vehicles (CAVs) presents significant challenges in dynamic traffic environments. Traditional methods and recent learning-based approaches often fail to simultaneously address decision-making complexity and execution precision under fluctuating conditions. This study introduces a novel hierarchical framework that combines: (1) a high-level Deep Reinforcement Learning (DRL) module that coordinates merging sequences through Virtual Traffic Signals (VTS) with Yield/Green phases and (2) a low-level optimal controller generating collision-free speed trajectories via pseudospectral convex optimization. A convolutional autoencoder compresses high-dimensional traffic states to enhance responsiveness. Extensive simulations demonstrate a 12.5% improvement in mainline throughput a 28% reduction in emergency braking events, and 31.66% lower fuel consumption compared to baseline methods. Furthermore, the framework’s effectiveness in coordinating CAV merges highlights its potential for real-world deployment. Future work will extend validation to multi-lane scenarios with mixed traffic and large-scale multiple merging points.

Connected and automated vehicles↗

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↗

Incentivizing Cooperative Merging Control: Insights from Multi-Agent Deep Reinforcement Learning

Cooperative driving automation enables connected and automated vehicles (CAVs) to devise cooperative merging control, introducing great potentials to alleviate traffic congestion, reduce energy consumption, and enhance safety for highway on-ramp operations. Although numerous CAV cooperative merging algorithms have been developed to improve energy and traffic performance, the agreement-seeking among CAV users and their local benefits have been understudied. This can lead to rejections of cooperative merging plans and jeopardizing CAV performance, as a cooperation may entail certain CAVs to sacrifice their local benefits to achieve a system optimum. To address this issue, the study first leverages multi-agent deep reinforcement learning (MADRL) factoring both local reward and regional reward to demonstrate the discrepancies between CAV users’ local benefits and system optimum. Next, the existence of a correlated equilibrium is proved to characterize the convergence of MADRL training. This further facilitates the incorporation of incentives (computed based on reward discrepancies) to compensate for CAV users’ local benefits and facilitate system-optimal agreements in cooperative merging operations.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗

Electron energization during merging of self-magnetized, high-beta, laser-produced plasmas

Electron energization during merging of magnetized plasmas is studied using the OMEGA and OMEGA EP laser facilities by colliding two plasma plumes, each containing a Biermann-battery self-generated magnetic field. Two neighbouring plasma plumes are produced by intense laser beams, and the anti-parallel Biermann fields merge and reconnect in the process of the plumes’ expansion and collision. To isolate the merging as an acceleration source, the electron energy spectra obtained from two-plume collision shots are compared with the spectra from single-plume shots. Single-plume shots exhibit an energized electron tail with energies up to ${\sim }250\ \textrm {keV}$ . The electrons in merging experiments are additionally accelerated by ${\sim }50\text {--}100$ keV compared to single-plume shots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Graphically Contracted Function Construction with the Recursive Pairwise Merge Algorithm

A new implementation of a recursive pairwise merge algorithm to construct a GCF from a list of CSF expansion coefficients is presented. The essential new feature is the preallocation of some work arrays used within the intermediate steps of the merge procedure. This results in roughly an order of magnitude improvement in overall efficiency and also approximately eliminates a factor of n, the molecular orbital dimension, from the original implementation. Initial application of this merge procedure to a series of H m molecules shows that the GCF wave functions can be represented well both with delocalized canonical Hartree-Fock orbitals and with localized molecular orbitals. Finally, for a given wave function complexity, as measured by the average facet count, $\bar{\text {f}}$, the delocalized Hartree-Fock orbitals show smaller errors for small $\bar{\text {f}}$ values, while the localized orbitals show smaller errors for larger $\bar{\text {f}}$ values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Merged aerosol size distribution from SMPS and OPC for SAIL

This dataset contains merged aerosol number size distribution data for the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign. The merged size distribution data were constructed by combining measurements from a scanning-mobility particle sizer (SMPS) and an optical particle counter (OPC), covering a size range of 0.01–35 µm. The merging methodology follows the approach described by Hand and Kreidenweis (2002) and Marinescu et al. (2019). All aerosol data from the ARM archive were corrected to standard temperature (273.15 K) and pressure (101.3 kPa).

merged size distribution↗

Cooperative Merging Speed Planning: A Vehicle-Dynamics-Free Method

Various cooperative merging control strategies at on-ramp have been proposed in the last decade. Approximated vehicle longitudinal motion models, e.g., kinematics model, have been broadly adopted for controller synthesis because of their simplicity. However, what appears problematic is that the models used for controller validation remain, in many cases, the same as the ones used for controller design. Indeed, actual vehicle dynamics contain rich behaviors that the simplified models cannot fully cover. In this paper, we first demonstrate that the actual vehicle speed can be dissimilar to the reference from a speed planner once vehicle dynamics is considered. Then, we propose two data-driven speed generators agnostic to vehicle dynamics. SUMO/Simulink joint simulations demonstrate that the proposed reference speed planners can successfully merge vehicles with distinct dynamics characteristics by following the desired sequence, speed, and intervehicle distance at the merging point while avoiding collisions.

Wang, Zejiang↗

Cooperative Merging via Online Speed Replanning: A Model-Free Approach With Vehicle-to-Vehicle Communication Packet Drop Compensation

On-ramp merging is a critical bottleneck in freeway traffic flow, contributing to congestion, accidents, and excessive fuel consumption. Although traditional ramp metering provides macroscopic control, it lacks the granularity for optimizing an individual vehicle’s trajectory. Cooperative merging, enabled by connected and automated vehicles, can potentially enhance traffic efficiency, safety, and fuel economy. However, existing research often neglects the influence of heterogeneous vehicle dynamics, unreliable vehicle-to-vehicle (V2V) communication, and real-time implementation challenges. Here, this paper introduces novel model-free online speed planners for cooperative on-ramp merging. The planners address these limitations by being agnostic to vehicle dynamics, effectively compensating for V2V communication packet drops and incurring only a light computational burden. Comprehensive evaluation, conducted on a real-time traffic-vehicle-communication co-simulation platform integrating high-fidelity vehicle dynamics, a traffic simulator, and recorded V2V communication footprints, demonstrates the effectiveness of the proposed speed planners. Simulation results reveal that the proposed method yields accurate tracking of desired speed and inter-vehicle distance, maintaining low fuel consumption even under high packet drop ratios, and demonstrating real-time implementation efficiency.

Wang, Zejiang [Univ. of Texas at Dallas, Richardso↗

Modeling Autonomous Vehicle-Targeted Aggressive Merging Behaviors in Mixed Traffic Environment

Promising advances in Autonomous Vehicle (AV) technology have fueled industry and research fields to dedicate significant effort to the study of the integration of AVs into the traffic network. This study focuses on the transition phase between all Human Driven Vehicles (HDVs) in the network to all AVs, where these different vehicle types coexist in a mixed traffic environment. This paper investigates the potential impacts of aggressive merging behaviors by human drivers on traffic performance in a mixed environment. For this, three vehicle types – AVs, HDVs, and Aggressive HDVs (AHDVs) – are modeled in an open-source microscopic traffic simulation model, SUMO. In the developed simulation, the AHDVs are modeled to emulate aggressive merging behaviors in front of AVs at a merge section of a freeway exit ramp. Several experiments are used to study the impact of such behavior. Results show travel time gains by AHDVs at the expense of AVs and HDVs.

Bae, JongIn↗

Enhanced Integer Permutation based Genetic Algorithm for Optimization of Tube-Fin Heat Exchanger Circuitry with Splits and Merges

Tube-fin heat exchangers (HXs) are widely used in air-conditioning and heat pump applications. The performance of these heat exchangers is strongly influenced by the refrigerant circuitry. Studies have proved that by optimizing the refrigerant circuitry, the performance of HXs can be significantly improved. In our previous research, an Integer Permutation based Genetic Algorithm (IPGA) was developed to obtain the optimal circuitry designs. Our previous research showed that IPGA demonstrates superior capability to obtain better refrigerant circuitries with lower computational cost than the other methods in literature. And the optimal circuitry designs obtained from IPGA are manufacturable with the available tooling. However, the IPGA developed previously cannot generate designs with splitting and merging of circuits. To remedy this limitation, a new chromosome which can represent circuitry with splitting and merging of circuits is developed. In addition to the six genetic operators implemented previously, two new genetic operators are developed to generate splits and merges. As a result, the enhanced IPGA can explore the solution space more thoroughly than the previous IPGA. A case study using an evaporator from an A-type indoor unit shows that, given the similar capacity improvements obtained from the enhanced IPGA compared with the previous IPGA, the refrigerant pressure drop reduction obtained from the enhanced IPGA is 26.5% compared against 1.0% pressure drop reduction from the previous IPGA. The benchmark of the enhanced IPGA with other methods in literature demonstrates that the enhanced IPGA can generate circuitry designs with performance superior to those obtained from other methods.

LI, Zhenning↗

Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks

Access to metal-organic frameworks (MOFs) with enhanced mechanical stability is key to their successful deployment in practical applications. However, the high porosity of the material often affects mechanical stability. In this article, to achieve highly porous MOFs with enhanced mechanical stability, we explored the merged-net approach where two relatively fragile frameworks were merged into a robust MOF structure. We demonstrate the effectiveness of this approach by computationally evaluating mechanical properties of sph-MOFs with varying lengths of linkers. Prominently, we pinpoint the significance of triangular rigidity on the robustness of large-pore MOFs and, subsequently, designed and synthesized a rare earth (RE)-based RE-sph-MOF-5 by the reticulation of hexanuclear RE clusters, tritopic linkers, and unprecedentedly large planar hexatopic linkers containing 19 phenyl rings. The mechanical properties of sph-MOFs were characterized and quantified using amplitude-frequency modulation (AM-FM) bimodal atomic force microscopy (AFM) analyses. Markedly, the mesoporous RE-sph-MOF-5 expresses high mechanical stability despite its large mesoporous cavities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for exotic Higgs boson decays H → 𝒜𝒜 with 𝒜 → γγ in events with a semi-merged topology in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for exotic Higgs boson decays H → 𝒜𝒜, with 𝒜 → γγ is presented, using events with a semi-merged topology. One of the hypothetical particles, 𝒜, is assumed to decay promptly into a semi-merged diphoton system reconstructed as a single photon-like object, while the other 𝒜 decays into two resolved photons. The search is performed using proton-proton collision data collected by the CMS experiment at $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 138 fb −1 . The data agree with the standard model background expectation. Upper limits are set on the product of the Higgs boson production cross section and the branching fraction, σ(pp → H) ℬ(H → 𝒜𝒜 → 4γ), which range from 0.264 to 0.005 pb at 95% confidence level, for 𝒜 masses in the range 1 < m 𝒜 < 15 GeV. These limits are the most stringent to date in the 1–5 GeV m 𝒜 range.

Beyond Standard Model↗

The dynamical state of RXCJ1230.7+3439: A multi-substructured merging galaxy cluster

We analyse the kinematical and dynamical state of the galaxy cluster RXCJ1230.7+3439 (RXCJ1230), at $z$ = 0.332 using 93 new spectroscopic redshifts of galaxies acquired at the Telescopio Nazionale Galileo and from SDSS DR16 public data. We study the density galaxy distribution retrieved from photometric SDSS multiband data and find that RXCJ1230 appears as a clearly isolated peak in the redshift space, with a global line-of-sight (LOS) velocity dispersion of $σ$ v = 1004 -122 +147 km s -1 . Several tests applied to the spatial and velocity distributions reveal that RXCJ1230 is a complex system with the presence of three subclusters, located to the southwest, east, and south with respect to the main body of the cluster, containing several bright galaxies (BGs) in their respective cores. Our analyses confirm that the three substructures are in a pre-merger phase, where the main interaction takes place with the southwest subclump, almost in the plane of the sky. We compute a velocity dispersion of $σ$ v ~ 1000 and $σ$ v ~ 800 km s -1 for the main cluster and the southwest substructure, respectively. The central main body and southwest substructure differ by ~870 km s -1 in the LOS velocity. From these data, we estimate a dynamical mass of $M$ 200 = 9.0 ± 1.5 × 1014 $M$ ⊙ and 4.4 ± 3.3 × 1014 $M$ ⊙ for the RXCJ1230 main body and southwest clump, respectively, which reveals that the cluster will undergo a merger characterised by a 2:1 mass ratio impact. We solve a two-body problem for this interaction and find that the most likely solution suggests that the merging axis lies ~17° from the plane of the sky and the subcluster will fully interact in ~0.3 Gyr. However, a slight excess in the X-ray temperature observed in the southwest clump confirms a certain degree of interaction already. The comparison between the dynamical masses and those derived from X-ray data reveals good agreement within errors (differences ~15%), which suggests that the innermost regions (< r 500 ) of the galaxy clumps are almost in hydrostatical equilibrium. In summary, RXCJ1230 is a young but also massive cluster in a pre-merging phase accreting other galaxy systems from its environment.

79 ASTRONOMY AND ASTROPHYSICS↗

Particle-in-cell modeling of plasma jet merging in the large-Hall-parameter regime

The merging process of magnetized plasma jets with parameters relevant to the plasma-jet-driven magneto-inertial fusion (PJMIF) design and the plasma liner experiment (PLX) is modeled by fully kinetic particle-in-cell (PIC) simulations in one and two spatial dimensions. Here, the modified two-stream instability is identified to be the main mechanism responsible for stopping the plasma jets and preventing species interpenetration. The electron and ion Hall parameters of the merged plasma are greater than unity, and the plasma β is close to unity, which is the desired characteristic of planned experiments at PLX. Our 2D PIC simulations validate the results of the radiation magneto-hydrodynamics code FLASH, which will be the primary tool for modeling various stages of future PJMIF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Global ion heating/transport during merging spherical tokamak formation

Here we report global ion heating/transport characteristics of magnetic reconnection during merging spherical tokamak formation experiment on TS-6 (TS-3U). Using the 96CH/320CH ultra high resolution ion Doppler tomography diagnostics, the full- 2 D imaging measurement clearly revealed that magnetic reconnection initially forms localized hot spots in the downstream region of outflow jet with inboard/outboard asymmetry (more deposition in the high field side) but the continuous accumulation of the heating coupled with transport process expands the high temperature region globally and forms characteristic poloidally ring-like structure aligned with field lines. The dynamic ion heating/transport process is also affected by the polarity of toroidal field and poloidally tilted/rotating global structure has experimentally been found both during and after merging. The characteristic poloidal asymmetry gets flipped when toroidal field direction is reversed and it was found that higher temperature appears in the positive potential side, which is opposite to the conventional understanding/prediction of guide field reconnection. Through the parallel acceleration process coupled with global heat transport, poloidally asymmetric non-classical feature has experimentally been found for the first time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The non-explosive stellar merging origin of the ultra-massive carbon-rich white dwarfs

We have investigated the origin of a sub-class of carbon-polluted white dwarfs (DQ) originally identified as the “hot DQ” white dwarfs. These objects are relatively hot ($10\, 000\lesssim T_{\rm eff}\lesssim 25\, 000$ K), have markedly higher carbon abundance (C-enriched), are more massive (M ≳ 0.8 M⊙) than ordinary DQs (M ∼ 0.6 M⊙), and display high space velocities. Hence, despite their young appearance their kinematic properties are those of an old white dwarf population. The way out of this dilemma is to assume that they formed via the merging of two white dwarfs. In this paper, we examine the observed characteristics of this population of “C-enriched” DQ white dwarfs and confirm that nearly half of the 63 known objects have kinematic properties consistent with those of the Galactic thick disc or halo. We have also conducted population synthesis studies and found that the merging hypothesis is indeed compatible with observations. Studies of this sub-class of white dwarfs have important implications for our understanding of Type Ia Supernovae (SNeIa), commonly used to determine the expansion history of the Universe, since the same formation channel applies to both kinds of objects. Hence, probing the properties of these white dwarfs that failed to explode may yield important constraints to the modelling of the mechanisms leading to a thermonuclear runaway.

79 ASTRONOMY AND ASTROPHYSICS↗

The ambiguous AT2022rze: changing-look AGN mimicking a supernova in a merging galaxy system

AT2022rze is a luminous, ambiguous transient located south-east of the geometric centre of its host galaxy at redshift $z = 0.08$. The host appears to be formed by a merging galaxy system. The observed characteristics of AT2022rze are reminiscent of active galactic nuclei (AGNs), tidal disruption events, and superluminous supernovae. The transient reached a peak absolute magnitude of $-$20.2 $\pm$ 0.2 mag, showing a sharp rise (t$_{\mathrm{rise,1/e}} = 27.5 \pm 0.6$ d) followed by a slow decline (t$_{\mathrm{dec,1/e}} = 382.9 \pm 0.6$). Its bumpy light curve and narrow Balmer lines indicate the presence of gas (and dust). Its light curve shows rather red colours, indicating that the transient could be affected by significant host extinction. The spectra reveal coronal lines, indicative of high-energy (X-ray/UV) emission. Archival data reveal no prior activity at this location, disfavouring a steady-state AGN, although an optical spectrum obtained prior to the transient is consistent with an AGN classification of the host. Based on this, we conclude that the transient most likely represents a changing-look AGN at the centre of the smallest component of the merging system.

galaxies: active↗