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At least 217 records · Page 12

Spectroscopy and electronic structure of the low-energy states of ThN

The electronic spectrum of ThN over the range 19,600–21,200 cm -1 is remarkably congested, showing at least twenty vibronic bands originating from the ground state zero-point level. Rotationally resolved spectra for eleven of these bands have been examined to probe the underlying reasons for the dense manifold of states. Dispersed fluorescence spectra and fluorescence decay lifetimes were measured to provide addition insights. Our experimental measurements were complemented by electronic structure calculations for the low-energy doublet and quartet states. The ab initio calculations yielded a density of excited states that was consistent with the congested spectrum. These states were derived from the formal configurations Th 3+ (6d)N 3- , Th 2+ (7s 2 )N 2- (2p 5 ) and Th 2+ (7s6d)N 2 -(2p 5 ). The calculations indicated that the rotational and vibrational constants would be characteristic of the electronic configurations. This prediction was not borne out by the experimental data, suggesting that the full range of inter-configurational state interactions were not captured by the computational model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Significance of ambient conditions in uranium absorption and emission features of laser ablation plasmas

This study employs laser ablation (LA) to investigate mechanisms for U optical signal variation under various environmental conditions during laser absorption spectroscopy (LAS) and optical emission spectroscopy (OES). Potential explored mechanisms for signal quenching related to ambient conditions include plasma chemistry (e.g., uranium oxide formation), ambient gas confinement effects, and other collisional interactions between plasma constituents and the ambient gas. LA-LAS studies show that the persistence of the U ground state population is significantly reduced in the presence of air ambient compared to nitrogen. LA-OES results yield congested spectra from which the U I 356.18 nm transition is prominent and serves as the basis for signal tracking. LA-OES signal and persistence vary negligibly between the test gases (air and N2), unlike the LA-LAS results. The plume hydrodynamic features and plume fundamental properties showed similar results in both air and nitrogen ambient. Investigation of U oxide formation in the laser-produced plasma suggests that low U concentration in a sample hinders consistent detection of UO molecular spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Regulating TNCs: Should Uber and Lyft set their own rules?

We evaluate the impact of three proposed regulations of transportation network companies (TNCs) like Uber, Lyft and Didi: (1) A minimum wage for drivers, (2) a cap on the number of drivers or vehicles, and (3) a per-trip congestion tax. The impact is assessed using a queuing theoretic equilibrium model which incorporates the stochastic dynamics of the app-based ride-hailing matching platform, the ride prices and driver wages established by the platform, and the incentives of passengers and drivers. We show that a floor placed under driver earnings can push the ride-hailing platform to hire more drivers and offer more rides, at the same time that passengers enjoy faster rides and lower total cost, while platform rents are reduced. Contrary to standard competitive labor market theory, enforcing a minimum wage for drivers benefits both drivers and passengers, and promotes the efficiency of the entire system. This surprising outcome holds for almost all model parameters, and it occurs because the wage floor curbs TNC labor market power. In contrast to a wage floor, imposing a cap on the number of vehicles hurts drivers, because the platform reaps all the benefits of limiting supply. The congestion tax has the expected impact: fares increase, wages and platform revenue decrease. Here, we also construct variants of the model to briefly discuss platform subsidy, platform competition, and autonomous vehicles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

What is greener than a VMT tax? The case for an indexed energy user fee to finance us surface transportation

Highway finance in the United States is perceived by many to be in a state of crisis, primarily due to the erosion of motor fuel tax revenues due to inflation, fuel economy improvement, increased use of alternative sources of energy and diversion of revenues to other purposes. Monitoring vehicle miles of travel (VMT) and charging highway users per mile has been proposed as a replacement for the motor fuel tax. A VMT user fee, however, does not encourage energy efficiency in vehicle design, purchase and operation, as would a user fee levied on all forms of commercial energy used for transportation and indexed to the average efficiency of vehicles on the road and to inflation. An indexed roadway user toll on energy (IRoUTE) would induce two to four times as much reduction in greenhouse gas (GHG) emissions and petroleum use as a pure VMT user fee. However, it is not a substitute for pricing GHG emissions and would make only a small but useful contribution to reducing petroleum dependence. An indexed energy user fee cannot adequately address the problems of traffic congestion and heavy vehicle cost responsibility. It could, however, be a key component of a comprehensive system of financing surface transportation that would eventually also include time and place specific monitoring of VMT for congestion pricing, externality charges and heavy vehicle user fees.

02 PETROLEUM↗

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mono- and tri-ester hydrogenolysis using tandem catalysis. Scope and mechanism

In this work, the scope and mechanism of thermodynamically leveraged ester RC(O)O–R' bond hydrogenolysis by tandem metal triflate + supported Pd catalysts are investigated both experimentally and theoretically by DFT and energy span analysis. This catalytic system has a broad scope, with relative cleavage rates scaling as, tertiary > secondary > primary ester at 1 bar H 2 , yielding alkanes and carboxylic acids with high conversion and selectivity. Benzylic and allylic esters display the highest activity. The rate law is ν = k [M(OTf) n ] 1 [ester] 0 [H 2 ] 0 with an H/D kinetic isotope effect = 6.5 ± 0.5, implying turnover-limiting C–H scission following C–O cleavage, in agreement with theory. Intermediate alkene products are then rapidly hydrogenated. Applying this approach with the very active Hf(OTf) 4 catalyst to bio-derived triglycerides affords near-quantitative yields of C 3 hydrocarbons rather than glycerol. From model substrates, it is found that RC(O)O–R' cleavage rates are very sensitive to steric congestion and metal triflate identity. For triglycerides, primary/external glyceryl CH 2 –O cleavage predominates over secondary/internal CH–O cleavage, with the latter favored by less acidic or smaller ionic radius metal triflates, raising the diester selectivity to as high as 48% with Ce(OTf) 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computer Vision-Enabled Smart Traffic Monitoring for Sustainable Transportation Management

Transportation accounts for a significant portion of total global energy consumption. Excessive energy consumption usually occurs in urban traffic environments with congestion and travel delays. With the advancement of remote sensing and computer vision technologies, real-time traffic conditions can be monitored. Therefore, sustainable transportation management strategies can be developed to optimize the overall energy and environment performance and reduce congestion and emissions. This work presents a smart traffic monitoring system based on remote camera sensors. Real-time and historical traffic conditions at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) were monitored and analyzed to develop optimal transportation management strategies for sustainability. Computer vision algorithms were developed and applied to process the real-time camera data to obtain complete traffic information across the ORNL campus. Weeks of historical data were collected and processed to analyze the traffic and identify bottlenecks. The proposed traffic monitoring and management approach can be applied and extended to benefit other campuses or urban areas.

Shao, Yunli↗

Simulation Evaluation of a Large-Scale Implementation of Virtual-Phase Link-Based Model Predictive Control

Traffic congestion is a serious problem in the US, and traffic signal control is one of the effective solutions to congestion. Previous research on model predictive control (MPC)-based traffic signal control showed substantial benefits over conventional methods. This study focused on implementing MPC over a large-scale network with complex intersections and the impact of cycle length, network size, and imperfect state estimation on performances. This study implemented a virtual phase link (VPL)-based model predictive control method which used the number of vehicles in each VPL as input state variables and was suitable for National Electrical Manufacturing Association (NEMA) ring-barrier control. To test the impact of network size, the performance of distributed MPC (36 intersections in the network are divided into five subnetworks) was compared with that of MPC over the full network for a set of cycle lengths. To test the impact of imperfect state estimation, we synthetically infused estimation error and developed two scenarios, MPC-error and MPC-error narrow, which had higher and lower estimation errors, respectively. The performance of these MPC methods was compared with that of the existing time-of-day (TOD) method and an offline method that used Webster's method for split and MULTIBAND for cycle length and offset optimization. Trajectory and linkwise signal performance measures were collected from the simulation to evaluate performance. The distributed MPC method with perfect state estimation had the lowest delay and highest energy efficiency of all the methods. The performance of MPC decreased as the prediction inaccuracy increased. MPC-error had 7% and 11% more delay than MPC-error narrow in the morning and evening peaks, respectively. Overall, simulation results suggest that even with imperfect state estimation, MPC methods will outperform offline methods significantly.

large-scale simulation↗

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗

Cold ion UV photofragmentation spectroscopy and dynamics (Invited)

Up to ten years ago, very little was known about the excited states of protonated amino acids isolated in the gas phase. From the experimental point of view, the study was hampered by the lack of ease of production of such species in sufficient density to apply photon-based techniques. With the development and widespread use of electrospray ionization sources coupled with modified or homebuilt mass spectrometers, there has been significant research into the spectroscopy of biomimetic and biologically relevant molecules. Besides, these species are floppy such that an efficient cooling is required to record clear spectroscopy. Warm protonated species display congested spectra. To extract precise spectroscopic information and avoid spectral congestion, the species need to be cooled down to less than 50 K. We present our latest results on the electronic spectroscopy of protonated phenylalanine and tyrosine on a large spectral domain (225-290 nm). These species are studied in a new simplified apparatus combining an electrospray ionization source, a cryogenically cooled quadrupole ion trap (∼10 K) and time-of-flight mass spectrometry. The role of proton transfer from the NH{sub 3}{sup +} moiety to the p-ring or to CO of the carboxylic acid group is evidenced by UV photofragment spectroscopy. This first step controls the fragmentation pathways, which strongly depend on the nature of the electronic excited states, i.e. ππ*, ππ*{sub CO} and πσ{sub NH3}.

74 ATOMIC AND MOLECULAR PHYSICS↗

Morphological biomarkers in Prochilodus lineatus (pisces, prochilodontidae) for environmental impact assessment in the region of the Baixada Maranhense, Brazil

This study aimed to identify the types of histopathological lesions found in gills of Prochilodus lineatus of the Environmental Protection Area of the Baixada Maranhense region (Brazil). Fish were collected in Mearim river. Sampling took place in October, November and December 2014. We have purchased 30 samples of fish from local fishermen. In the laboratory fish gills were removed, and then fixed in 10% formalin solution and kept into alcohol 70% to the usual histological processing. The tissue was performed by light microscopy and findings were photomicrographed in light microscope - ZEIS. The following lesions were identified: epithelial displacement, the marginal channel shift a start vascular congestion, hyperplasia and merging multiple slides; epithelial disruption, edema, vascular congestion, total fusion of lamellae and disorganization of secondary lamellae. These changes express a response of the body to some xenobiontes. Morphological changes in the gills may represent adaptive strategies for conservation of some biological functions when animals are facing changes in the water quality.

54 ENVIRONMENTAL SCIENCES↗

High resolution spectroscopy of jet cooled phenyl radical: The ν{sub 1} and ν{sub 2} a{sub 1} symmetry C–H stretching modes

A series of CH stretch modes in phenyl radical (C{sub 6}H{sub 5}) has been investigated via high resolution infrared spectroscopy at sub-Doppler resolution (∼60 MHz) in a supersonic discharge slit jet expansion. Two fundamental vibrations of a{sub 1} symmetry, ν{sub 1} and ν{sub 2}, are observed and rotationally analyzed for the first time, corresponding to in-phase and out-of-phase symmetric CH stretch excitation at the ortho/meta/para and ortho/para C atoms with respect to the radical center. The ν{sub 1} and ν{sub 2} band origins are determined to be 3073.968 50(8) cm{sup −1} and 3062.264 80(7) cm{sup −1}, respectively, which both agree within 5 cm{sup −1} with theoretical anharmonic scaling predictions based on density functional B3LYP/6-311g++(3df,3dp) calculations. Integrated band strengths for each of the CH stretch bands are analyzed, with the relative intensities agreeing remarkably well with theoretical predictions. Frequency comparison with previous low resolution Ar-matrix spectroscopy [A. V. Friderichsen et al., J. Am. Chem. Soc. 123, 1977 (2001)] reveals a nearly uniform Δν ≈ + 10-12 cm{sup −1} blue shift between gas phase and Ar matrix values for ν{sub 1} and ν{sub 2}. This differs substantially from the much smaller red shift (Δν ≈ − 1 cm{sup −1}) reported for the ν{sub 19} mode, and suggests a simple physical model in terms of vibrational mode symmetry and crowding due to the matrix environment. Finally, the infrared phenyl spectra are well described by a simple asymmetric rigid rotor Hamiltonian and show no evidence for spectral congestion due to intramolecular vibrational coupling, which bodes well for high resolution studies of other ring radicals and polycyclic aromatic hydrocarbons. In summary, the combination of slit jet discharge methods with high resolution infrared lasers enables spectroscopic investigation of even highly reactive combustion and interstellar radical intermediates under gas phase, jet-cooled (T{sub rot} ≈ 11 K) conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

How generic is iodide-tagging photoelectron spectroscopy: An extended investigation on the Gly· X - (Gly = glycine, X = Cl or Br) complexes

We report a joint negative ion photoelectron spectroscopy (NIPES) and quantum chemical computational study on glycine-chloride/bromide complexes (denoted Gly·X - , X = Cl/Br) in close comparison to the previously studied Gly·I - cluster ion. Combining experimental NIPE spectra and theoretical calculations, various Gly·X - complexes were found to adopt the same types of low-lying isomers, albeit with different relative energies. Despite more congested spectral profiles for Gly·Cl - and Gly·Br - , spectral assignments were accomplished with the guidance of the knowledge learned from Gly·I - , where a larger spin–orbit splitting of iodine afforded well-resolved, recognizable spectral peaks. Three canonical plus one zwitterionic isomer for Gly·Cl - and four canonical conformers for Gly·Br - were experimentally identified and characterized in contrast to the five canonical ones observed for Gly·I - under similar experimental conditions. Taken together, this study investigates both genericity and variations in binding patterns for the complexes composed of glycine and various halides, demonstrating that iodide-tagging is an effective spectroscopic means to unravel diverse ion-molecule binding motifs for cluster anions with congested spectral bands by substituting the respective ion with iodide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning-based traffic signal control algorithms with neighborhood information sharing: An application for sustainable mobility

Here, this research applies R-Markov Average Reward Technique based reinforcement learning (RL) algorithm, namely RMART, for vehicular signal control problem leveraging information sharing among signal controllers in connected vehicle environment. We implemented the algorithm in a network of 18 signalized intersections and compare the performance of RMART with fixed, adaptive, and variants of the RL schemes. Results show significant improvement in system performance for RMART algorithm with information sharing over both traditional fixed signal timing plans and real time adaptive control schemes. Additionally, the comparison with reinforcement learning algorithms including Q learning and SARSA indicate that RMART performs better at higher congestion levels. Further, a multi-reward structure is proposed that dynamically adjusts the reward function with varying congestion states at the intersection. Finally, the results from test networks show significant reduction in emissions (CO, CO 2 , NO x , VOC, PM 10 ) when RL algorithms are implemented compared to fixed signal timings and adaptive schemes.

33 ADVANCED PROPULSION SYSTEMS↗

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed this issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10 .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Efficient algorithm for locating and sizing series compensation devices in large power transmission grids: II. Solutions and applications

In a companion manuscript, we developed a novel optimization method for placement, sizing, and operation of Flexible Alternating Current Transmission System (FACTS) devices to relieve transmission network congestion. Specifically, we addressed FACTS that provide Series Compensation (SC) via modification of line inductance. In this manuscript, this heuristic algorithm and its solutions are explored on a number of test cases: a 30-bus test network and a realistically-sized model of the Polish grid (~ 2700 nodes and ~ 3300 lines). The results on the 30-bus network are used to study the general properties of the solutions including non-locality and sparsity. The Polish grid is used as a demonstration of the computational efficiency of the heuristics that leverages sequential linearization of power flow constraints and cutting plane methods that take advantage of the sparse nature of the SC placement solutions. Using these approaches, the algorithm is able to solve an instance of Polish grid in tens of seconds. We explore the utility of the algorithm by analyzing transmission networks congested by (a) uniform load growth, (b) multiple overloaded configurations, and (c) sequential generator retirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗