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At least 433 records · Page 24

Geochemical and microbial characteristics of seepage water and mineral precipitates in a radwaste disposal facility impacted by seawater intrusion and high alkalinity

The construction of an underground facility can dramatically change the quality, flow direction, and level of groundwater. It may also impact subsurface microbial composition and activity. Groundwater quality was monitored over eight years in two observational wells near an underground disposal facility on the east coast of South Korea. The results showed dramatic increases in dissolved ions such as O 2 , Na, Ca, Mg, and SO 4 during facility construction. Seepage water samples downgradient from the silos and tunnels, and precipitates deposited along the seepage water flow path were collected to determine the impact inside the disposal facility. X-ray analysis (powder X-ray diffraction (pXRD) and X-ray absorption fine structure (XAFS)) were used to characterize the mineral precipitates. Microbial community composition was determined by 16S rRNA gene sequencing. The seepage water composition was of two types: Ca-Cl and Ca-Na-HCO 3 . The ratio of Cl and δ 18 O showed that the Ca-Cl type seepage water was influenced by groundwater mixed with seawater ranging from 2.7% to 15.1%. Various sulfate-reducing bacteria were identified in the Ca-Cl type seepage water, exhibiting relatively high sulfate content from seawater intrusion. Samples from the Ca-Na-HCO 3 type seepage water had an extremely high pH (>10) and abundance of Hydrogenophaga. The precipitates observed along the flow path of the seepage water included calcite, ferrihydrite, green rust, and siderite, depending on seepage water chemistry and microbial activity. This study suggests that the construction of underground structures creates distinct, localized geochemical conditions (e.g., high alkalinity, high salinity, and oxic conditions), which may impact microbial communities. These biogeochemical changes may have undesirable large-scale impacts such as water pump clogging. Overall, an understanding of the process and long-term monitoring are essential to assess the safety of underground facilities.

54 ENVIRONMENTAL SCIENCES↗

Microextraction–TQ–ICP–MS for the Direct Analysis of U and Pu from Cotton Swipes

Here, the microextraction sampling technique was integrated with triple quadrupole–inductively coupled plasma–mass spectrometry (TQ–ICP–MS) to directly sample and measure the isotopic compositions of uranium (U) and plutonium (Pu) from cotton swipes. Once extracted, the U/Pu were directed into the TQ–ICP–MS instrument for isotopic determination. Carbon dioxide (CO 2 ) and helium (He) gases were delivered to a collision reaction cell within the ICP–MS system for ion separation. The CO 2 reacts with the U + forming UO + which is ultimately separated from the Pu + ions of interest in the third quadrupole. This study demonstrates direct liquid extraction of U/Pu from a solid surface and subsequent measurement by TQ–ICP–MS in <60 s. Flow rates were optimized (0.3 mL min –1 CO 2 and 5 mL min –1 He) in the reaction cell of the ICP–MS system to maximize the Pu signal while minimizing U interferences (i.e., 238 U + tail and 238 UH + ) at m/z 239. Low levels of Pu (~2 pg) were deposited on a cotton swipe along with U at concentrations ranging from 20 to 200 ng. The 240 Pu/ 239 Pu ratio was measured with <7% relative difference from the certified value at all U concentrations. Major and minor U isotope ratios were also measured with <4% relative difference. This highlights that the microextraction–TQ–ICP–MS method can extract a mixed U/Pu sample directly from a cotton swipe and measure both isotopic systems without chemical separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Superconducting phase diagram in Bi x Ni 1 – x thin films: The effects of Bi stoichiometry on superconductivity

The Bi-Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in Bi 3 ⁢Ni crystals. While Ni acts as a ferromagnetic element in such systems, the role of the strong spin-orbit coupling element Bi in superconductivity has remained unexplored. In this work, we systematically studied the effects of Bi stoichiometry on the superconductivity of Bi x ⁢Ni 1–x thin films (x ≈ 0.5–0.9) fabricated via a composition-spread approach. Here, the superconducting phase map of Bi x ⁢Ni 1–x thin films exhibited a superconducting composition region attributable to the intermetallic Bi 3 ⁢Ni phase with different amounts of excess Bi, revealed by synchrotron x-ray diffraction analysis. Interestingly, the mixed-phase region with Bi 3 ⁢Ni and Bi showed unusual increases in the superconducting transition temperature and residual resistance ratio as more Bi impurities were included, with the maximum T c (=4.2K) observed at x ≈ 0.79. A correlation analysis of structural, electrical, and magneto-transport characteristics across the composition variation revealed that the unusual superconducting “dome” is due to two competing roles of Bi: impurity scattering and carrier doping. We found that the carrier doping effect is dominant in the mild doping regime (0.74 ≤ x ≤ 0.79), while impurity scattering becomes more pronounced at larger Bi stoichiometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Antarctic permafrost processes and antiphase dynamics of cold-based glaciers in the McMurdo Dry Valleys inferred from 10 Be and 26 Al cosmogenic nuclides

Abstract. Soil and sediment mixing and associated permafrost processes are not widely studied or understood in the McMurdo Dry Valleys of Antarctica. In this study, we investigate the stability and depositional history of near-surface permafrost sediments to ∼ 3 m depth in the Pearse and lower Wright valleys using measured cosmogenic 10Be and 26Al depth profiles. In Pearse Valley, we estimate a minimum depositional age of ∼ 74 ka for the active layer and paleoactive-layer sediments (< 0.65 m). Combined depth profile modelling of 10Be and 26Al gives a depositional age for near-surface (< 1.65 m) permafrost in Pearse Valley of 180 +20/-40 ka, implying that the deposition of permafrost sediments predates MIS 5 advances of Taylor Glacier. Deeper permafrost sediments (> 2.09 m) in Pearse Valley are thus inferred to have a depositional age of > 180 ka. At a coastal, lower-elevation site in neighbouring lower Wright Valley, 10Be and 26Al depth profiles from a second permafrost core exhibit near-constant concentrations with depth and indicate the sediments are either vertically mixed after deposition or sufficiently young so that post-depositional nuclide production is negligible relative to inheritance. 26Al/10Be concentration ratios for both depth profiles range between 4.0 and 5.2 and are all lower than the nominal surface production rate ratio of 6.75, indicating that prior to deposition, these sediments experienced complex, yet similar, exposure–burial histories. Assuming a single-cycle exposure–burial scenario, the observed 26Al/10Be ratios are equivalent to a total minimum exposure–burial history of ∼ 1.2 Myr. In proximity to the depth profile core site, we measured cosmogenic 10Be and 26Al in three granite cobbles from thin, patchy drift (Taylor 2 Drift) in Pearse Valley to constrain the timing of retreat of Taylor Glacier. Assuming simple continuous exposure, our minimum, zero-erosion exposure ages suggest Taylor Glacier partially retreated from Pearse Valley no later than 65–74 ka. The timing of retreat after 65 ka and until the Last Glacial Maximum (LGM) when Taylor Glacier was at a minimum position remains unresolved. The surface cobble ages and permafrost processes reveal Taylor Glacier advances during MIS 5 were non-erosive or mildly erosive, preserving the underlying permafrost sediments and peppering boulders and cobbles upon an older, relict surface. Our results are consistent with U/Th ages from central Taylor Valley and suggest changes in moisture delivery over Taylor Dome during MIS 5e, 5c, and 5a appear to be associated with the extent of the Ross Ice Shelf and sea ice in the Ross Sea. These data provide further evidence of antiphase behaviour through retreat of a peripheral lobe of Taylor Glacier in Pearse Valley, a region that was glaciated during MIS 5. We suggest a causal relationship of cold-based glacier advance and retreat that is controlled by an increase in moisture availability during retreat of sea ice and perhaps the Ross Ice Shelf, as well as, conversely, a decrease during times of sea ice and Ross Ice Shelf expansion in the Ross Sea.

58 GEOSCIENCES↗

Finite-rate entrainment effects on nitrogen oxide (NO x ) emissions in staged combustors

Axially staged combustors offer the potential for achieving low NO x emissions from gas turbines at the elevated temperatures required to achieve at least 65% combined cycle efficiencies. While there is evidence that premixing between the main burner products and secondary stream reduces NO x , it is important to characterize the specific requirements needed to achieve low emissions at gas turbine conditions. This study examines the sensitivity of NO x to finite-rate, large-scale entrainment of the main and secondary streams under the simplifying assumption of infinitely-fast small-scale mixing. Essentially, this allows us to isolate the effects of limited large-scale entrainment rates by using a homogeneous/uniform condition for the entrained and reacting gases. We use a reduced-order reactor network model to examine a generic staged-combustor whose inputs are physical time scales that embody the finite-rate entrainment characteristics. With simulations conducted over a large parameter space at typical operating conditions (25 atm, 650 K air), the results show that, even when small-scale mixing is infinitely fast and the reaction zone is uniform, entrainment significantly affects NO x emissions due to its influence on the equivalence ratio — and thus the temperature and time — at which the entrained mixture ignites. Fuel-air staging is shown to be vital to NO x reduction in most practical cases where entrainment times exceed roughly 1 ms and the secondary stream finishes entraining before the main burner products. A constrained NO x minimization indicates that using the leanest possible main burner and re-routing as much air as possible to the secondary stage is key to low NO x with finite-rate entrainment; for example, less than 10 ppm NO x can be achieved if the secondary stage contains 20% of the total mass flow.

03 NATURAL GAS↗

Heterogeneous Diels–Alder tandem catalysis for converting cellulose and polyethylene into BTX

Producing biomass-derived aromatic hydrocarbons via controllable Diels–Alder reactions is a promising approach to recover energy and chemicals from waste streams. A tandem Diels–Alder catalysis consisting of SAPO-34 and Fe/HZSM-5 (stacked catalysis or mixed catalysis) was evaluated for thermochemical conversion of cellulose and polyethylene blends into benzene, toluene, and xylenes (BTX). Aromatization catalyst type significantly affected the activity of tandem catalysis, and the BTX obtained from the HZSM-5 stacked catalysis was ~2.3 times higher than that of the USY stacked one. An introduction of Fe active promoters into HZSM-5 increased the Lewis to Brønsted acid sites molar ratio (L/B) from 0.4 to 4.1. The comparison between Fe/HZSM-5 stacked catalysis and parent HZSM-5 single catalysis indicated that the former was more effective for BTX production, obtaining a nearly two-fold increase in yield with a high selectivity of 82.8%. A close proximity between Fe/HZSM-5 and SAPO-34 in the mixed catalysis increased the BTX enhancement to 1.8. A synergistic effect was provided by the coordination of Lewis and Brønsted acid sites in the Fe/HZSM-5 mixed catalysts for facilitating BTX generation, achieving a maximum of 25.9% at a Fe/HZSM-5 to SAPO-34 mass ratio of 1:1 with a theoretical L/B of 7.2. Finally, this work provides a sustainable strategy to produce biomass-derived aromatic hydrocarbons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for direct production of low-mass dimuon resonances is performed using $ \sqrt{s} $ = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017–2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb$^{−1}$. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1–2.6 GeV and 4.2–7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world’s best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε$^{2}$ in the dark photon model above 10$^{−6}$ are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θ$_{H}$) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tan β = 0.5.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Gamma-ray spectrometry analysis methods for radioisotope dissolution and mixing for nuclear forensics applications

We report the production of surrogate nuclear explosive debris involves the dissolution of irradiated fissile material, elemental isolation, and recombination based on required fission product ratios. Gamma-ray spectrometry is used following each step to assess the radioactive fission product inventory. A high-purity germanium detector is used to measure each sample, and the detector efficiencies are determined prior to sample measurements. Through radiochemical techniques, elements are isolated and recombined into samples with specific fission product ratios. As a result, a matrix-based approach can account for imperfect chemical separations to calculate the proper mixture volumes to obtain intended volatile-to-refractory fission product ratios, or R-values.

07 ISOTOPE AND RADIATION SOURCES↗

Adrian Portales Coop Internship Report

Using the thesis of W.R. Nolan (cite) as a guide, Cobalt Iron (CoFe) powders were reacted with 0.1 wt.% and 0.2 wt.% phosphoric acid in a 20:1 ratio of acetone to phosphoric acid. The powders were then dried at room temperature. The resulting phosphate coated CoFe was then mixed with 0.75 wt.% of the lubricant N,N' ethylene bis-stearamide (trade name: Acrawax C) and hot pressed to form a consolidated soft magnetic material referred to as CoFeP. With an avenue of synthesis for CoFeP determined, a proper amount of stock was synthesized for continuous “brick” production. While under current optimization, these 1x1 mm magnetic bricks will ultimately be placed and secured along the inside wall of each MK Magnetics transformer core by an appropriate CoFeP dispersed epoxy. As of now each brick has been produced though a pressing and annealing process via square 2x2 cm die. Before a brick is made a pressure calculation is run to ensure the dies maximum operating pressure is not exceeded. Figure 1. ensures the user’s safety by showing that the tons-on-ram required for a 2x2 cm square die to reach 760 MPa is below the point of die failure.

36 MATERIALS SCIENCE↗

2023 American Society for Mass Spectrometry (ASMS) 71st Annual Conference on Mass Spectrometry and Allied Topics

Introduction (120 words max) Understanding metal-cluster chemistry occuring at solvent boundaries in the aqueous and organic phases has applications in environments from cellular processes to nuclear fuel reprocessing. Transport of metal ions at the boundaries from aqueous to organic phases involves forming a metal-ligand complex, and wherever the initial metal coordination environment is significantly different from the final one, the metal transitions through a series of transient species in passing from one phase to another. Here an investigation of the role of coordination in the chemistry of the transient species using gas-phase measurements that are free of solvent effects to better understand the binding of complexes of metals with triphenylphosphine chalcogenide ligands, examining metal-ligand homo- and hetero-dimers to better understand transient species. Methods (120 word max) Mass spectrometry and collision induced dissociation (CID) experiments were performed with a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer (QTOF) and Bruker amaZon speed ETD (ion trap). High resolution/high mass accuracy spectra were generated using the QTOF. External calibration was performed with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Both mass spectrometers were equipped with either the electrospray ionization source or nanospray sources. Metal samples were prepared between 40 – 60 uM of the metal-ligand complex in 25% water and 75% acetonitrile. Metal-ion clusters were isolated and subjected to collision induced dissociation. Density functional theory calculations were performed. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters with triphenylphosphine chalcogenide ligands were observed for group I metals with triphenylphosphine chalcogenide samples in the mass spectrum upon electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation spectra were acquired. We observed clusters of group I metal with triphenylphosphine oxide, triphenyl phosphine sulfide, and triphenylphosphine selenide, with homodimers and heterodimer formation. In samples where the ligands were mixed, we observed mixed sodium ligand clusters at varying amounts. These mixed ligand clusters were fragmented. Metal clusters of mixed ligand dimers containing triphenylphosphine oxide showed preferential loss of the other ligand, either triphenylphosphine sulfide or triphenyl selenide. In samples with mixed triphenylphosphine sulfide and triphenylphosphine selenium ligands, sodium bound similarly between the ligands, and losses were more evenly split, showing loss ratio upon CID with losses of triphenylphosphine sulfide:triphenylphosphine selenide 43:57 ratio observed on CID. These results suggest that the oxide binds significantly more strongly than either the selenium or sulfur triphenylphosphine ligand, and the sulfur and selenium ligands are more evenly bound. Calculations were performed using density functional theory to calculate likely structures and bond energies between the group I metal and the ligands. Novel Aspect Novel analysis of sodium bound dimers with chalcogenide triphenylphosphine ligands were investigated using mass spectrometry and theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mixed-Flux Techniques for Rational Synthesis and Structural Control in Silver Chalcogenides

The functionality of materials is intrinsically linked to their structures, an axiom encapsulated in the principle of structure-property relationships. The pinnacle of materials design is the tailoring of its structure for a specific function, which requires the ability of rational synthesis and the development of synthesis science. This idea, however, remains elusive for the synthesis of complex extended solids. A major obstacle is the difficulty in using established chemical principles selectively to control reaction paths and favor certain structural patterns over numerous other possible results. In this context, we are developing a synthesis science approach that facilitates the control of the structure and bonding to create new structures. This is achieved by employing a two-component flux consisting of mixed hydroxides and halides as the reaction medium. This enables reaction conditions that allow better control of the structure dimensionality and composition by manipulating the temperature and solvent basicity (via the flux component ratio). Here, we demonstrate the efficacy of this method in controlling their structural motifs to arrive at 23 unreported compositions and 6 unique structure types. These materials are expected to exhibit a broad range of properties, from metallic to semiconducting, with calculations suggesting the potential for emergent phenomena such as Dirac semimetals. The reaction paths afforded by these mixed fluxes establish a direct correlation between the synthetic variables and properties, providing significant insight into a broadly applicable approach for new materials.

Zhou, Xiuquan [Argonne National Laboratory (ANL), ↗

Ultra-high SERS detection of consumable coloring agents using plasmonic gold nanostars with high aspect-ratio spikes

Solution-based SERS detection by using a portable Raman instrument has emerged as an important tool due to its simplicity, and flexibility for rapid and on-site screening of analyte molecules. However, this method has several shortcomings, including poor sensitivity especially for weak-affinity analyte molecules, where there is no close contact between the plasmonic metal surface and analyte molecule. Examples of weak-affinity molecules include pigment molecules that are commonly used as a consumable coloring agent, such as allura red (AR), and sunset yellow (SY). As high consumption of colorant agents has been shown to cause adverse effects on human health, there is a strong need to develop a simple and practical sensing system with high sensitivity for these agents. Here we present a novel, highly sensitive solution-based SERS detection method for AR, and SY by using CTAC capped gold nanostars (GNS) having different aspect ratios (GNS-2, GNS-4, and GNS-5) without utilizing any aggregating agents which can enhance SERS signal however it reduces batch to batch reproducibility. The influence of the aspect ratio of GNS on SERS properties was investigated. We have achieved a limit of detection (LOD) of AR and SY as low as 0.5 and 1 ppb, respectively by using GNS-5 with the advantages of minimal sample preparation by just mixing the analyte solution into a well plate containing GNS solution. In addition, excellent colloidal stability and reproducibility have further enhanced the applicability in real-world samples. Altogether, our results evidence that the solution-based SERS detection platform using high aspect-ratio GNS can be applied for practical application to detect pigment molecules in real samples with satisfactory results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization of matrix viscosity improves polypropylene fiber dispersion and properties of engineered cementitious composites

Engineered cementitious composites (ECC) is a durable cementitious material with high tensile ductility and strain-hardening characteristics. Although considered as a cost-effective fiber for ECC, polypropylene (PP) fiber is reportedly difficult to disperse in mortar matrix due to its high aspect ratio and hydrophobicity. In this study, the matrix viscosity of a low-carbon ECC based on limestone calcined clay cement was tailored as a variable to improve PP fiber dispersion under a pre-determined mixing protocol. The effect of matrix viscosity on the composite fresh and hardened properties was investigated experimentally. Results suggested an optimal range of matrix viscosity (10.3–11.5 Pa . s) favors the composite tensile strength and strain capacity at 28 days. At the optimal state with a 0.1 % viscosity modifying admixture (VMA)-to-binder mass ratio, PP-ECC achieved 7.0 % tensile strain capacity and 3.5 MPa ultimate tensile strength. When matrix viscosity falls outside the desired range, both ultimate tensile strength and strain capacity were diminished. By tailoring the VMA dosage, the matrix viscosity can be adjusted for desired fiber dispersion, workability, and mechanical properties. Finally, the findings of this study provide a technical reference for the practical design and application of PP-ECC.

36 MATERIALS SCIENCE↗

Effects of edge-seal design on the mechanical and thermal performance of vacuum-insulated glazing

Although vacuum-insulated glazing (VIG) has been proposed as a promising solution towards developing energy-efficient buildings, VIGs have not become popular in the market due to several technical challenges including the complexity of the fabrication process. In particular, the edge-seal is a key component that significantly affects the thermal insulation and mechanical performance, and the development of edge-seal with adequate thermal insulation, mechanical strength, and reasonable processing cost is essential to overcome such technical issues in VIG. For this purpose, effects of edge-seal design parameters on the VIG performance should be identified. In this research, we analyzed the edge-seal for thermal transport as well as structural stresses to study the effects, and then identified and evaluated the material mixes for the edge-seal requirements. Here, the finite element simulations showed the significance of VIG corner calculation on overall thermal transmittance and the importance of seal conductivity below 1 W/m.K. The experiments with the flexible seals with different ratios of fine glass powder demonstrated that the measured shear strength values for the seal with less than 30% glass powder were more than 10 times larger than the calculated shear stress values. Based on these simulation and experimental results, a flexible sealant was developed using a proprietary mix of ceramic materials that meets the requirements of the designed VIG edge-seal, including structural as well as thermal stress resistance and a low conductivity. Moreover, the sealant is self-curing under atmospheric conditions, and thus it does not require costly inline process of laser curing or oven baking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Meta-analysis of biogas upgrading to renewable natural gas through biological CO 2 conversion

Biogas upgrading through CO 2 conversion by hydrogenotrophic methanogenesis is receiving an increasing attention worldwide because of the demand for renewable natural gas. Herein, a holistic and statistical study of the operation conditions, driving forces, performances, and potential implementation of biogas upgrading via biological CO 2 conversion was conducted. Based on a systematic review and meta-analysis of 46 existing publications that were selected from 1475 papers, we have compiled a global dataset of CO 2 bioconversion biogas upgrading, encompassing 308 study cases. Subsequently, we employed a rigorous analytical framework incorporating data processing and mixed effects linear regression analysis to examine the dataset. This analysis revealed a significant positive relationship between the H 2 :CO 2 ratio and the methane percentage in the upgraded biogas when using the study as a random effect. Furthermore, we performed meta-analysis on observations taken when the ratio was close to 4:1 and found that ex situ reactors (91.93% [88.11%, 95.75%]) can perform better than in situ reactors (84.74% [80.69%, 88.80%]). No evidence of differential performance was found based on the present dataset between different temperature regimes or operation modes. Furthermore, those findings establish a database that will contribute to a deeper understanding of the biogas upgrading via biological CO 2 conversion.

Biogas upgrading↗

Pattern formation and flocking for particles near the jamming transition on resource gradient substrates

Here, we numerically examine a bidisperse system of active and passive particles coupled to a resource substrate. The active particles deplete the resource at a fixed rate and move toward regions with higher resources, while all of the particles interact sterically with each other. We show that at high densities, this system exhibits a rich variety of pattern-forming phases along with directed motion or flocking as a function of the relative rates of resource absorption and consumption as well as the active to passive particle ratio. These include partial phase separation into rivers of active particles flowing through passive clusters, strongly phase separated states where the active particles induce crystallization of the passive particles, mixed jammed states, and fluctuating mixed fluid phases. For higher resource recovery rates, we demonstrate that the active particles can undergo motility-induced phase separation, while at high densities, there can be a coherent flock containing only active particles or a solid mixture of active and passive particles. The directed flocking motion typically shows a transient in which the flow switches among different directions before settling into one direction, and there is a critical density below which flocking does not occur. We map out the different phases as function of system density, resource absorption and recovery rates, and the ratio of active to passive particles.

97 MATHEMATICS AND COMPUTING↗

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Utilizing the maximum likelihood estimator for flow analysis

We explore the possibility of evaluating flow harmonics by employing the maximum likelihood estimator (MLE). For a given finite multiplicity, the MLE simultaneously furnishes estimations for all the parameters of the underlying distribution function while efficiently suppressing the variance of measures. Also, the method provides a means to assess a specific class of mixed harmonics, which is not straightforwardly feasible by the approaches primarily based on particle correlations. The results are analyzed using the Wald, likelihood ratio, and score tests of hypotheses. Besides, the resultant flow harmonics obtained using MLE are compared with those derived using particle correlations and event plane methods. Here, the dependencies of extracted flow harmonics on the multiplicity of individual events and the total number of events are analyzed. It is shown that the proposed approach works efficiently to deal with the deficiency in detector acceptability. Moreover, we elaborate on a fictitious scenario where the event plane is not a well-defined quantity in the distribution function. For the latter case, the MLE is shown to largely perform better than the two-particle correlation estimator. In this regard, one concludes that the MLE furnishes a meaningful alternative to the existing approaches for flow analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗