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At least 649 records · Page 36

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗

SPARTAN and IMPROVE Comparison Experiment (SPICE) Interim Campaign Report

SPICE (the SPARTAN and IMPROVE Comparison Experiment) aims to obtain and quantify comparisons between aerosol PM 2.5 mass concentration measurements from the University of Oklahoma (OU) Surface Particulate Matter Network (SPARTAN) station and the U.S. Environmental Protection Agency (EPA) Interagency Monitoring of Protected Visual Environments (IMPROVE) station hosted by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility at ARM’s Southern Great Plains (SGP) observatory in Oklahoma. Aerosols—both natural and anthropogenic—affect human populations in multiple ways. Much of ARM’s research focuses on how aerosols influence weather and climate through their optical and radiative effects, as well as their impacts on clouds and precipitation. However, aerosols also pose direct risks to humans and other organisms through inhalation, with the severity of health impacts depending on particle size, chemical composition, and duration of exposure. The IMPROVE network was established by the U.S. EPA to monitor air quality, including visible clarity as well as total and chemically speciated aerosol mass concentrations. The ARM SGP site hosts the IMPROVE SOGP station. Separately, the SPARTAN network operates a globally distributed set of stations similar to IMPROVE but with an emphasis on remote deployment and semi-autonomous operation for use beyond the borders of the United States (IMPROVE only operates within the U.S.). The University of Oklahoma operates a SPARTAN station. To establish confidence in the OU SPARTAN instrumentation and measurement protocol relative to the EPA-certified IMPROVE station, the OU SPARTAN station is currently deployed at SGP in close proximity to the IMPROVE SOGP station. The SPICE campaign was envisioned as a contiguous calendar-year effort for 2025 to capture seasonal variation in mass loading as well as composition. However, independent of the SPICE campaign, the SPARTAN network adopted a new filter construction part-way through the year, interrupting our contiguous data set. Thus, to obtain a contiguous data set with a uniform consistent configuration, SPICE desires an extension through 2026.

54 ENVIRONMENTAL SCIENCES↗

Applications of Hyporheic Zone Sampling for Assessing VOC Plume Engineered Remediation and Natural Attenuation Effectiveness - 20414

Determining the efficacy of engineered remedial actions and/or natural attenuation as an acceptable EPA Record of Decision (ROD) must address long-term temporal and spatial variability. Since final plume downslope destinations are aquifers and related surface streams and rivers, hyporheic zone sampling is essential. Comprehensive hyporheic sampling documents plume groundwater remediation prior to upwelling into stream benthic strata and natural attenuation within this dynamic zone itself. Our intensive sampling of the Savannah River Site (SRS) Chemical, Metals, and Pesticides (CMP) Pits VOC plume-fringe from 2005 to 2018 documented PCE natural attenuation and effectiveness of In Situ Thermal Treatment (ISTT). Most plume hyporheic upwelling was delimited to a 20 m inflow reach along Pen Branch. Our study utilized corroborative sampling methodologies: ambient hole-water grab samples: passive diffusion bags (PDB); and hole-core sediment samples to confirm station to station spatial and temporal trends. VOC hot spot detections were confirmed from both groundwater and soil core samples. VOC pathways through the Pen Branch hyporheic zone were assessed at hole-installation using sequential soil samples from augered cores and grab-samples of hole-bottom water. Longer term, composite water samples were collected from PDBs deployed for a minimum two-week equilibration period. Soil samples were collected from the 15 and 65 cm core levels in December 2017 and June 2018 at six stations. Additional core depths of 40 and 85 cm were sampled in June 2018 at the highest VOC station (5DB80). All samples were analyzed in an EPA certified lab by purge and trap GC-MS. Effectiveness of previous ISTT and soil vapor extraction (SVE) for this CMP Pits PCE plume, was clearly documented by significant downward trends in VOC at hyporheic zone stations prior to December 2015. Achieving final stage conversions of PCE daughter products to ethene and CO{sub 2} may be limited depending upon suitable interactions between hyporheic zone sediment morphology, hydrology, and redox conditions. Because declines in VOC daughter products at our hyporheic stations may also be caused by physical actions of dilution and dispersion rather than true biochemical dechlorination, full quantification of natural attenuation requires the use of compound-specific isotope ratio analysis (CSIA) and microbial 16S rRNA with qPCR. To assist these next-phase efforts, a natural attenuation index (NAI) was used to help produce quicker, more cost-effective decision making for locating CSIA and microbial sampling efforts. The NAI used natural logarithm transformed GC-MS results for station VOC degradation compounds versus VOC parent compounds. Wide differences were observed between stations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Emulation of seismic-phase traveltimes with machine learning

SUMMARY We present a machine learning (ML) method for emulating seismic-phase traveltimes that are computed using a global-scale 3-D earth model and physics-based ray tracing. Accurate traveltime predictions based on 3-D earth models are known to reduce the bias of event location estimates, increase our ability to assign phase labels to seismic detections and associate detections to events. However, practical use of 3-D models is challenged by slow computational speed and the unwieldiness of pre-computed lookup tables that are often large and have prescribed computational grids. In this work, we train a ML emulator using pre-computed traveltimes, resulting in a compact and computationally fast way to approximate traveltimes that are based on a 3-D earth model. Our model is trained using approximately 850 million P-wave traveltimes that are based on the global LLNL-G3D-JPS model, which was developed for more accurate event location. The training-set consists of traveltimes between 10 393 global seismic stations and randomly sampled event locations that provide a prescribed, distance-dependent geographic sample density for each station. Prediction accuracy is dependent on event-station distance and whether the station was included in the training set. For stations included in the training set the mean absolute deviation (MAD) of the difference between traveltimes computed using ray tracing through the 3-D model and the ML emulator for local, regional, and teleseismic distances are 0.090, 0.125 and 0.121 s, respectively. For tested station locations not included in the training set, MAD values for the three distance ranges increase to 0.173, 0.219 and 0.210 s, respectively. Empirical traveltime residuals for a global reference data are indistinguishable when ML emulation or the 3-D model is used to compute traveltimes. This result holds regardless of whether the recording station is used in ML training or not.

58 GEOSCIENCES↗

Screening IMS Seismic Detections using Dynamic Correlation Processor: Progress report for 2020

LLNL completed the FY20 workplan entailing application of the Dynamic Correlation Processor (DCP) to International Monitoring System (IMS) primary seismic data in 2019 and 2020. The effective analysis period was curtailed to January 1 through November 12, 2019 due to a data compression change that rendered later data unusable. Fixing the data compression error is a priority for our data source, and we plan to extend the period of data analysis when the fix is implemented. We found that the percentage overlap between detections generated by the International Data Centre (IDC) DFX software and detections generated by DCP varied widely by station. Overlap is 30-40% at some stations, suggesting that a large percentage of DFX detections could be screened (removed) from the detection-event association algorithm. However, detection overlap was much lower, a few percent, at many stations and the percentage overlap was low at stations known to have many mines and other local sources of seismicity. Unexpectedly low detection overlap at many stations prompted us to examine results for the ARCES station in detail. There is considerable mine activity near ARCES, but our initial FY20 analysis found only ~2% DCP/DFX detection overlap. Differences in the pre-processing (e.g. beam recipes) used by DCP and DFX appear to be the cause of low detection overlap at ARCES. DCP uses wideband filters to improve detector robustness and the IDC uses narrow-band pre-filtering to improve sensitivity. After reprocessing ARCES using the IDC beam recipe, DCP/DFX overlap increased to ~74%. This result shows that we must reprocess the IMS network using the IDC station-specific beam recipes if we are to effectively screen DFX detections and improve automatic event building performance at the IDC.

58 GEOSCIENCES↗

Installation of Lysimeters Near Engineered Trench 3, Slit Trench 8, and Slit Trench 9

Nine new lysimeter stations were installed at the E-Area Low Level Waste Facility (ELLWF). Six lysimeter stations were installed near Engineered Trench 3 (ET3), one installed near Slit Trench 8 (ST8), and two installed near Slit Trench 9 (ST9) as shown in Figure ES-1. Two lysimeters were installed at each station at the depths shown in Table ES-1. Lysimeter placements were based on borehole lithology and were comparable to existing nearby lysimeter stations. The deepest lysimeter at each of the new lysimeter stations was designated as the action-level lysimeter. Following installation, the lysimeters were purged and placed under vacuum for sampling. Sampling occurred in April 2023. Analytical results from the sampling will be provided in the Spring 2023 Lysimeter Tritium Data technical memo and the 2023 Annual Summary Report. With the addition of the new lysimeters at ET3, ST8, and ST9, the vadose zone monitoring system is now comprised of 327 active lysimeters at 111 lysimeter stations. There are 102 action-level lysimeters at 111 stations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Auger@TA: In-situ Cross-Calibration of the World's Largest Cosmic Ray Observatories

The Pierre Auger Observatory (Auger) and the Telescope Array (TA) are the world's two largest ultra-high-energy cosmic ray (UHECR) observatories. They operate in the Southern and Northern hemispheres, respectively, at similar latitudes but with distinct surface detector (SD) designs. A significant challenge in studying UHECR physics across the full sky is the apparent discrepancy in flux measurements between the two experiments. This discrepancy could arise from astrophysical differences and/or systematic effects related to their detector designs and sensitivities to extensive air shower components. To address this, the Auger@TA working group aims to cross-calibrate the two observatories with a self-triggering micro-Auger array within the TA array. This micro-array consists of eight Auger Surface Detector (SD) stations equipped with Water Cherenkov Detectors (WCDs) and AugerPrime Surface Scintillator Detectors. Seven SD stations, configured with a centered-1-PMT design, are arranged in a hexagonal pattern with one station in the center, with 1.5 km spacing, mirroring the Auger layout. The eighth station, which features a standard 3-PMT Auger station, is located in conjunction with a TA detector at the center of the hexagon, forming a triplet for high-statistics and low-uncertainty cross-calibration. A custom communication system that uses readily available components enables seamless communication between stations and remote access to each station through a central computer. The micro-array is now fully deployed, and initial data-taking is about to start. This presentation will detail the instrumentation, communication systems, central data acquisition system, expected performance of the micro-array, and preliminary results as appropriate.

Mocellin, Adriel G.B. [Colorado School of Mines]↗

Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles

The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.

42 ENGINEERING↗

DC Fast Charging Infrastructure for Electrified Road Trips

To assess DC fast charging station network required for electrified road trips by 2030 in California, a new charging infrastructure simulation tool/model, EVI-Pro (Electric Vehicle Infrastructure Projection) RoadTrip, has been developed. In contrast to the existing EVI-Pro model that is primarily for short-distance travels, EVI-Pro RoadTrip is exclusively focused on road trips (long-distance travels, 100 or miles per day per vehicle). Also, the charging paradigm or strategy is different. EVI-Pro RoadTrip is built upon waypoint charging, in which vehicles are forced to stop to charge or replenish the on-board batteries, along the routes between origins and destinations. On the other hand, EVI-Pro is based on destination charging, in which charging is conducted when vehicles are parked in destinations (e.g., work, home). EVI-Pro RoadTrip takes coordinate-level origin and destination data for road trips (intra-state as well as domestic or international out-of-state) and estimates energy consumption and charging needs along the routes between origins and destinations on a minute-by-minute resolution. Based on charging demands for electrified road trips across the state, the optimal locations of charging stations are determined accounting for preferred land use types (e.g., commercial areas) and station service area (e.g., 5 or less miles). Based on station-by-station charging load profiles, the required number of plugs/connectors is estimated for each station and entire state. By comparing hosting capacity of the electric grid (circuit-level) and the charging load output from EVI-Pro RoadTrip, capacity deficit is also evaluated.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

The cold high-pressure approach to hydrogen delivery

In view of the very expensive and wasteful nature of today's approaches to H 2 delivery, in this work we explore the possibility of transporting cold (200 K) high pressure (875 bar) H 2 in thermally insulated trailers and dispensing H 2 directly from the trailer, with the potential to eliminate station compressor, cascade, and refrigerator, leading to major reductions in station complexity, maintenance, electricity consumption, and cost, while improving functionality by enabling essentially unlimited back to back refuels, and improving safety due to reduced H 2 expansion energy at low temperature. Detailed techno-economic analysis shows promise for substantial delivery cost reductions through cold high pressure H 2 dispensed directly from the trailer. Results indicate that: (1) Terminal operations for cold high pressure H 2 delivery are $\$$0.32/kg H 2 more expensive than for 350 bar compressed gas delivery (today's lowest cost H 2 delivery technology) due to higher level of pressurization (to 1000 bar) and chilling needs (to 165 K). (2) Trailer cost drops slightly ($\$$0.73 vs. $\$$0.81/kg H 2 for a 350 bar trailer) due to increased capacity (1035 kg H 2 delivered vs. 700 kg) compensating for increased capital cost ($\$$906,900 for cold high pressure H 2 vs. $\$$634,000 for 350 bar trailer). (3) Cold hydrogen delivery presents major advantages in fueling station cost, reduced from $\$$1.27 to $\$$0.46/kg H 2 due to elimination of major system components: compressor, cascade, and chiller. (4) Total compression cost (terminal + station) drops from $\$$0.92/kg H 2 ($\$$0.32 terminal and $\$$0.60 station) for 350 bar trailers to $\$$0.55/kg H 2 (all at the terminal) for cold high pressure H 2 . (5) Elimination of small-scale station compressors is the main contributor to reduced delivery cost due to their inefficiency, capital expense, and maintenance needs. In summary, total delivery cost reduction vs. 350 bar trailer equals $\$$0.58/kg H 2 (from $\$$2.96 to 2.38/kg H 2 ), equivalent to 24% of the total delivery cost. This large cost advantage will improve the economics of H 2 vehicles facilitating the transition to a future of zero emission transportation.

08 HYDROGEN↗

Three‐Dimensional Broadband Interferometric Mapping and Polarization (BIMAP‐3D) Observations of Lightning Discharge Processes

Abstract Following on our earlier single‐station, 2‐dimensional (2D) broadband interferometric mapping and polarization (BIMAP) observations of lightning discharges, we recently deployed two BIMAP stations at Los Alamos National Laboratory to map the lightning sources and their polarization in full 3‐dimensional (3D) space (BIMAP‐3D). The two stations are separated by 11.5‐km and each station consists of four antenna sets (instead of three for the original BIMAP) that form a Y ‐shaped array for improved interferometric performance. In this paper, we report the BIMAP‐3D system design, a generalized and analytical 2D interferometry technique for noncoplanar antenna array, a two‐stage 3D mapping technique based on geometric triangulation and baseline‐based differential time of arrival, and a technique to reconstruct the polarization orientation in 3D space by combining the 2D polarization results from the two‐station observations. Along with description of the techniques, we demonstrate and discuss the initial lightning results, including 3D maps for a hybrid intracloud and cloud‐to‐ground flash and for a normal intracloud flash, development of abnormal K‐change leaders, and polarization signatures for a K‐change leader. We find that with the two‐stage 3D mapping techniques, the sources can be located to meters accuracy for a favorable event that occurs between the two stations. We also find the polarization vectors for the example K leader are mostly orthogonal to the leader channel after the full 3D polarization analysis. The main purpose of this paper is to report the BIMAP‐3D techniques and capabilities. Detailed analysis of more specific discharge processes will be reported in later studies.

54 ENVIRONMENTAL SCIENCES↗

Evaluating multistation phase picking algorithm phase neural operator (PhaseNO) on local seismic networks

Reliable automatic phase picking is important for many seismic applications. With the development of machine learning approaches, many algorithms are proposed, evaluated and applied to different areas. Many of these algorithms are single station based, while recent proposed methods start to combine surrounding stations into consideration in the problem of phase picking. Among these algorithms, the phase neural operator (PhaseNO) shows promising results on regional data sets comparing to existing algorithms. But there are many use cases for the local seismic networks in our community, therefore in this paper we evaluate the performance of PhaseNO on four different local data sets and compare the results to PhaseNet and EQTransformer. We used both individual phase picking metrics as well as association metrics to illustrate the performance of PhaseNO. By manually reviewing the newly detected events, we find that the PhaseNO model outperforms the single station-based approaches in the local-scale use cases due to its consideration of coherent signals from multiple stations. We also explored PhaseNO’s behaviours when only using one station, as well as gradually increasing the number of stations in the seismic network to better understand its behaviour. Overall, using the off-the-shelf machine learning based phase pickers, PhaseNO demonstrated its good performance on local-scale seismic networks.

58 GEOSCIENCES↗

Formal methods approach to the charging facility location problem for battery electric vehicles

Battery electric vehicles (BEVs) are becoming more prevalent as improvements in battery technology and energy management continue to be made. As the number of electric vehicles grows, the demand for fast-charging stations is expected to increase dramatically. Thus, building new charging station infrastructure efficiently will be key to reducing upfront costs while meeting consumer demands. In this work, we propose a method for choosing a set of charging station locations that are optimized based on a set of given common vehicle demand points. As part of this solution, we also offer a novel abstraction of the road network on which energy-efficient paths that account for charge-time delays may be found. The current algorithm chooses the optimal charging locations for a single agent which has a route objective specified using temporal logic. To demonstrate the proposed method, the running example shows how a charging station could be chosen for an electric delivery vehicle. Simulations were run on sample road networks with a given set of demand points to service and potential charging station locations to compare. The method is shown to successfully rank potential charging stations in terms of their expected average charging time cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Weather data at The Morton Arboretum 2017-2023

We have been monitoring long-term weather patterns using two weather stations at The Morton Arboretum to link environmental conditions to tree growth and other tree responses. This data package contains weather data at The Morton Arboretum from 2017-08-23 to 2023-12-31; data is located in the "MortonWeatherData2017_2023.csv" file. The two weather stations are located on each side of The Arboretum (e.g., the Nursery station on the East side and the Ware Field station on the West side; the two weather stations are 3.23 km apart and coordinates are included in the "Location_metadata.csv" file). Measured variables include rain accumulation, air temperature, relative humidity, three soil moisture/temperature measurements at various depths (10, 30, and 50 cm for the Nursery weather station, and 10, 25, and 50 cm for the Ware Field), solar radiation, saturation vapor pressure, and vapor pressure deficit.

54 ENVIRONMENTAL SCIENCES↗

Monitoring Potential Transport of Radioactive Contaminants in Shallow Ephemeral Channels: FY2019

Desert Research Institute (DRI) conducted a field assessment of the potential for contaminated soil to be transported from the Smoky Site Contamination Area (CA) because of storm runoff. This activity supported U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Smoky Site Soils Corrective Action Unit (CAU) 550. The work was intended to confirm the likely mechanism of transport and determine the meteorological conditions that might cause the movement of contaminated soils, as well as determine the particle size fraction most closely associated with transported radionuclide-contaminated soils. These data will facilitate the design of the appropriate post-closure monitoring program. In 2011, DRI installed a meteorological monitoring station on the west side of the Smoky Site CA and a hydrologic (runoff) monitoring station within the CA, near the east side. The meteorological station collected air temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, and soil water content data. The maximum, minimum, and average or total values (as appropriate) for each of these parameters were recorded for each 10-minute interval. The maximum, minimum, and average water depth in the flume installed at the hydrologic station were also recorded for each 10-minute interval. This report presents the data collected from these stations during fiscal year (FY) 2019. During the FY2019 reporting period, the warmest months were June, July, and August and the coldest were December and February. The highest monthly solar radiation (i.e., sunshine) values were recorded in June, July, and August, whereas December through February had the lowest solar radiation values. Monthly mean wind speeds were highest in the spring (April) and early summer (June). Winds were predominantly from the north, except in February, July, August, and September when winds were mostly from the west. The monthly average relative humidity ranged from 17 percent to approximately 60 percent. Humidity was lowest in the summer and highest in the winter. Monthly total precipitation ranged from 0.0 during August and September to 2.22 inches (in) (56.39 millimeters [mm]) in February. Total precipitation for FY2019 was 7.83 in (198.88 mm). During the reporting period, a single, nonzero, flow event was recorded at the flume. This occurred over two days between March 6 and 7, 2019, in response to 1.16 in (29.46 mm) of precipitation falling within 9.3 hours on March 6, 2019. This event produced a peak water depth of 0.39 in (0.99 centimeters [cm]) in the flume, and runoff was measured for approximately 23.5 hours. However, the maximum recorded flow depth was less than the limit for flow discharge and velocity that can be calculated for the six-inch (15 cm) throat of a Parshall flume. The runoff event produced insufficient flow velocities through the natural channel to cause local erosion and transport of bedload materials. No bedload samples were collected for radiological analysis. Observing meteorological and environmental conditions that lead to storm runoff will help identify the parameters and threshold conditions that should be incorporated into post-closure monitoring plans for this and similar Soils CAU sites. Routine monitoring of meteorological and hydrologic parameters at the Smoky Site CA has been discontinued at the request of EM NV, effective at the conclusion of FY2019. Environmental data acquisition was completed and the meteorological and runoff monitoring stations were removed from the Smoky Site on October 15, 2019.

54 ENVIRONMENTAL SCIENCES↗

Tonopah Test Range Air Monitoring: Meteorological, Radiological, and Wind Transported Particulate Observations (CY 2019)

In 1963, the U.S. Department of Energy (DOE) (formerly the Atomic Energy Commission [AEC]), implemented Operation Roller Coaster on the Tonopah Test Range (TTR) and an adjacent area of the Nevada Test and Training Range (NTTR) (formerly the Nellis Air Force Range). This operation resulted in radionuclide-contaminated soils at the Double Tracks site and Clean Slate I, II, and III sites. This report documents observations made during ongoing monitoring of radiological, meteorological, and dust conditions at stations installed adjacent to the Clean Slate sites and at the TTR Sandia National Laboratories (SNL) Range Operations Center (ROC). The main objectives of the monitoring effort are to support the DOE Environmental Management Nevada Program (EM NV) in the safe remediation of the environmental legacy of nuclear device development and testing by determining if wind blowing across the Clean Slate sites is transporting particles of radionuclide-contaminated soil beyond the physical and administrative boundaries of the sites, and providing information for designing long-term monitoring of the sites. The monitoring program in 2019 included five stations. Station 400, located within TTR Area 3 and near the ROC, monitors conditions near the local workforce center. Stations 401 and 403 are located on the northern and southeastern perimeter fence lines, respectively, of the Clean Slate III site. Stations 404 and 405 are along the northern and eastern boundary fence, respectively, at Clean Slate II. The stations are generally downwind of the contaminated areas during either northwesterly or southerly winds, which are the predominant wind directions.

54 ENVIRONMENTAL SCIENCES↗

System and method for selective transmission and reception for stationary wireless networks

A system and methods for selective transmission and reception for stationary wireless networks. The system and method include an end user equipment, a primary base station, a core network, and a selective server. The end user equipment transmits a request for transmission to the primary base station receiver. The primary base station authenticates the end user equipment using a cellular network authentication process. The primary base station then searches for a time slot data for the end user equipment from the selective server and determines whether the time slot is open for transmission, steers a beam towards the end user equipment when time slot is open for transmission. The primary base station then enables transmission from the end user equipment, wherein the enabling is performed by the primary base station. The core network receives the transmission from the end user equipment.

Bhuyan, Arupjyoti↗

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↗