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National Electric Vehicle Infrastructure Formula Program (NEVI) Brief for State Public Utility Commissions

The National Electric Vehicle Infrastructure (NEVI) Formula Program (NEVI program) is a funding opportunity for all 50 U.S. states, the District of Columbia, and Puerto Rico, established by the Bipartisan Infrastructure Law (BIL). The NEVI program instructs states to “strategically deploy electric vehicle (EV) charging infrastructure and to establish an interconnected network to facilitate data collection, access, and reliability.” The NEVI program allocates more than $\$$5 billion to states from Fiscal Year (FY) 2022 to 2026 on a formula basis. NEVI funds are available to private entities, including utilities, to build EV Supply Equipment (EVSE)1 and associated EV grid infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

National Electric Vehicle Infrastructure Formula Program (ANNUAL REPORT | PLAN YEAR 2023–2024)

The 2021 Infrastructure Investment and Jobs Act, also known as the Bipartisan Infrastructure Law (BIL), invests $\$$7.5 billion to build out a national electric vehicle (EV) charging network and created the Joint Office of Energy and Transportation (Joint Office) to “study, plan, coordinate, and implement issues of joint concern between the two agencies.” The BIL represents a historic effort to electrify the U.S. transportation system, which has significant potential to reduce U.S. greenhouse gas emissions and help tackle the climate crisis. The U.S. transportation sector accounts for one-third of the nation’s greenhouse gas emissions—the largest share of all primary sectors, including electricity production, industry, commercial and residential, and agriculture. The National Electric Vehicle Infrastructure (NEVI) Formula Program, one of the BIL funding programs, was launched in February 2022, providing nearly $\$$5 billion over 5 years to help states, the District of Columbia, and Puerto Rico (hereafter referred to as “states”) create a network of EV charging stations beginning with designated Federal Highway Administration (FHWA) Alternative Fuel Corridors (AFCs), with an emphasis on the Interstate Highway System. The funding is made available to the states in allocations each year pending FHWA certification of the state’s annual deployment plan. The NEVI program is in its third year, so there's a lot to celebrate. As of July 2024, 39 states have released solicitations for their NEVI programs and eight states have opened their first NEVI-funded stations (61 ports in total), which have already powered thousands of charging sessions for EV drivers across America. Additional stations are in the pipeline with more than 2,500 additional ports having been awarded or conditionally awarded by the states. All states released their Fiscal Year (FY) 2024 deployment plan updates to reflect the new minimum requirements and guidance, and several states added newly designated EV AFCs in their FY 2024 deployment plan updates, bringing the total AFC network of EV corridors to more than 81,000 miles.

33 ADVANCED PROPULSION SYSTEMS↗

National Electric Vehicle Infrastructure Formula Program Annual Report: Plan Year 2022-2023

The National Electric Vehicle Infrastructure (NEVI) Formula Program provides nearly $5 billion over 5 years to help states, the District of Columbia, and Puerto Rico (hereafter referred to as “states”) create a network of fast EV charging stations along designated Federal Highway Administration (FHWA) Alternative Fuel Corridors (AFCs), with emphasis along the Interstate Highway System. The first-year deployment plans were submitted to and reviewed by the Joint Office and FHWA and certified by FHWA in September 2022. To support the rollout of the NEVI Formula Program, the Joint Office has been providing technical assistance to the states since February 2022 and has developed DriveElectric.gov to serve as the front door for federal efforts to build out a national charging network. This report summarizes the key activities of the Joint Office in relation to the NEVI program and provides an individual and collective overview of the first-year deployment plans. The Joint Office will utilize the summary of these plans to inform program improvement and future technical assistance activities to support the states as they begin to implement their EV charging infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗

Soft costs and EVSE – Knowledge gaps as a barrier to successful projects

There has been a recent push to increase access to electric vehicle (EV) charging infrastructure. The National Electric Vehicle Infrastructure (NEVI) program, part of the Bipartisan Infrastructure Law (BIL) has made significant funding available for major charging infrastructure projects along state thruways, and many state and local incentives exist for EV owners to install chargers in their homes. However, deployment of these chargers has not kept up with demand, primarily due to issues in project planning, permitting processes, and unforeseen delays. This paper serves as a review of the current understanding of these and other non-hardware costs in EV charging infrastructure projects (collectively known as “soft costs”). We found that soft costs in EV charging infrastructure projects are not well understood. Specifically, there is little agreement on how soft costs should be categorized and tracked, and less agreement still on best practices for controlling these costs and lowering barriers to infrastructure deployment. A broader review of EV charging infrastructure cost analyses shows that these costs can have significant impacts on project outcomes. EV charging infrastructure projects may be able to examine the success of the solar industry in lowering soft costs, and a similar effort may lower project costs significantly. Further work on standardizing and collecting data on EV charging infrastructure costs is required to begin addressing and controlling these costs.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance (V.5.0)

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112(a)-(c)). EV-ChART provides a streamlined data submission process and an integrated set of analytic tools, connects to other data sources, and empowers data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112(a)-(c)). The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow. Per 23 CFR 680.112(a)-(c), the annual and quarterly data submissions are required of all National Electric Vehicle Infrastructure (NEVI) Formula Program projects, as well as projects for the construction of publicly accessible EV chargers that are funded with funds made available under Title 23, United States Code, including any EV charging infrastructure project funded with federal funds that is treated as a project on a federal-aid highway. One-time data submissions are required of both the NEVI Formula Program projects and grants awarded under 23 U.S.C. 151(f) for projects that are for EV charging stations located along and designed to serve the users of designated Alternative Fuel Corridors (AFCs). Other information and data required in 23 CFR 680, such as 23 CFR 680.112(d), 23 CFR 680.116(c), and 23 CFR 680.106(a), are not discussed in this guidance.

33 ADVANCED PROPULSION SYSTEMS↗

R -Matrix Analysis and Statistical Properties of Dysprosium Isotopes in the Neutron Energy Ranges Up To A Few Kev

In support of the Nuclear Criticality Safety Program, a set of evaluated resonance parameters was generated for seven dysprosium isotopes in the neutron energy range from thermal up to a few keV. The evaluation methodology used the Reich-Moore approximation to fit, with the R-matrix code SAMMY, the high-resolution capture and transmission measurements on natural and enriched samples recently performed at the Rensselaer Polytechnic Institute Gaerttner LINear ACcelerator facility. Additional transmission data measured on enriched samples by Liou at the Columbia University Nevis synchrocyclotron in the mid-seventies were used to gauge the neutron widths above 15 eV. Thermal constants such as absorption and (in)coherent scattering cross sections and corresponding scattering lengths were calibrated to the National Institute of Standards and Technology’s compilation except for 161,164 Dy isotopes.

07 ISOTOPE AND RADIATION SOURCES↗

Standardized Protocol for Real-Time APIs as Required by Title 23 CFR 680.116(c)

Improving the ability of drivers to easily locate working and available chargers is key to improving the public charging experience. Electric vehicle charging providers who are recipients of federal funds through the National Electric Vehicle Infrastructure (NEVI) Formula Program, Charging and Fueling Infrastructure (CFI) Discretionary Grant Program, and other funding programs as identified under Title 23 of the U.S. Code must deploy and maintain an application programming interface (API) to access information about charging stations they operate.1 This includes information about individual charging ports, pricing, and availability in accordance with the Federal Highway Administration’s National Electric Vehicle Infrastructure Standards and Requirements, 23 CFR 680.116(c), herein referred to as the minimum standards (Federal Highway Administration 2023). Specifically outlined in the minimum standards, states and other designated recipients are required to ensure that charging station information including location, connector type, power level, real-time status, and real-time price to charge are available free of charge to third-party software developers through an API. These requirements are intended to enable effective communication with consumers about available charging stations and help consumers make informed decisions about trip planning, including when and where to charge. This document provides a standardized protocol for how to structure data, data update frequency, and practices for making the data required to be shared via API usable for improving public transparency and the customer experience. These are recommendations only and do not modify the Federal Highway Administration’s minimum standards in any way.

33 ADVANCED PROPULSION SYSTEMS↗

CalderaCast User Manual Version 1.0

CalderaCast is a user-friendly web-based tool for electrical-load forecast, providing stakeholders with a fully customizable decision-support framework that estimates the likely power draw from a possible future electric-vehicle (EV) charging station at a given location on a given day along an alternative fuel corridor (AFC). These EV charging profiles are accurately modeled in CalderaCast using the Caldera software framework developed by Idaho National Laboratories (INL), reflecting the realistic charging levels observed in actual charge events. This tool was developed as part of the National Electric Vehicle Infrastructure (NEVI) program, which is quickly generating substantial interest from would-be charging station operators (CSO), large and small electric utilities, and state transportation planners, some of whom had not seriously considered EV charging previously. All these entities—with or without background in EV infrastructure—must estimate the electricity load that a proposed charging station will generate. This load forecast is critically important for a utility to properly assess the capacity of their distribution network to support the proposed station or properly size grid upgrades for potential load growth due to future EV adoption, vehicle technology improvements, or station growth. This document describes each aspect of the CalderaCast tool and provides guidance to users who are interested in utilizing the tool for their work.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. Here, this study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m 2 .K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

09 BIOMASS FUELS↗

Charged-hadron and identified-hadron (𝐾$^{0}_{𝑆}$, Λ, $Ξ$ − ) yield measurements in photonuclear Pb + Pb and 𝑝 + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with ATLAS

This paper presents the measurement of charged-hadron and identified-hadron (𝐾$^{0}_{𝑆}$, Λ, $Ξ$ − ) yields in photonuclear collisions using 1.7nb −1 of $\sqrt{s_{NN}}$ = 5.02 TeV Pb + Pb data collected in 2018 with the ATLAS detector at the Large Hadron Collider. Candidate photonuclear events are selected using a combination of tracking and calorimeter information, including the zero-degree calorimeter. The yields as a function of transverse momentum and rapidity are measured in these photonuclear collisions as a function of charged-particle multiplicity. These photonuclear results are compared with 0.1 nb −1 of $\sqrt{s_{NN}}$ = 5.02 TeV p + Pb data collected in 2016 by ATLAS using similar charged-particle multiplicity selections. These photonuclear measurements shed light on potential quark-gluon plasma formation in photonuclear collisions via observables sensitive to radial flow, enhanced baryon-to-meson ratios, and strangeness enhancement. The results are also compared with the Monte Carlo generator and hydrodynamic calculations to test whether such photonuclear collisions may produce small droplets of quark-gluon plasma that flow collectively.

H & He induced nuclear reactions↗

Disentangling Centrality Bias and Final-State Effects in the Production of High-𝑝 𝑇 Neutral Pions Using Direct Photon in 𝑑+Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV

Here, PHENIX presents a simultaneous measurement of the production of direct 𝛾 and 𝜋 0 in 𝑑 + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV over a 𝑝 𝑇 range of 7.5 to 18 GeV/𝑐 for different event samples selected by event activity, i.e., charged-particle multiplicity detected at forward rapidity. Direct-photon yields are used to empirically estimate the contribution of hard-scattering processes in the different event samples. Using this estimate, the average nuclear-modification factor, 𝑅$^{𝜋^0}_{dAu,EXP}$, is 0.925 ± 0.023⁢(stat) ± 0.15⁢(scale), consistent with unity for minimum-bias (MB) 𝑑+Au collisions. For event classes with low and moderate event activity, 𝑅$^{𝜋^0}_{dAu,EXP}$ is consistent with the MB value within 5% uncertainty. This result confirms that the previously observed enhancement of high-𝑝 𝑇 𝜋 0 production found in small-system collisions with low event activity is a result of a bias in interpreting event activity within the Glauber framework. In contrast, for the top 5% of events with the highest event activity, 𝑅$^{𝜋^0}_{dAu,EXP}$ is suppressed by 20% relative to the MB value with a significance of 4.5⁢𝜎, which may be due to final-state effects. This suppression corresponds to a 𝑝 𝑇 shift of 𝛿⁢𝑝 𝑇 = 0.213 ± 0.055 Gev/𝑐 at 9 Gev/𝑐.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analyzing Potential Greenhouse Gas Emissions Reductions from Plug-In Electric Vehicles: Report for CRC Project, "Carbon Return on Investment for Electrified Vehicles"

Investment in battery and electrification technologies has the potential to greatly reduce vehicular greenhouse gas (GHG) emissions, as a battery-electric vehicle (BEV) will have zero tailpipe emissions. However, there will be GHG emissions associated with production of the vehicle including its battery, and with any carbon-emitting electricity sources used to charge the vehicle. This study explores the GHG reduction benefits of different plug-in electric vehicle (PEV) designs in the context of factors such as electricity production mix, per-vehicle battery requirements, and varying battery market growth scenarios. The analyses focus on the U.S. light-duty vehicle (LDV) market, which accounts for nearly 60% of U.S. transportation sector GHG emissions - over twice as much as the next largest contributing transportation sub-sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electric Vehicle Supply Equipment and Considerations for a Reasonable Rate of Return

This white paper identifies the following recommendations for states as they consider issues related to electric vehicle supply equipment program income under the National Electric Vehicle Infrastructure program and other programs covered by National Electric Vehicle Infrastructure Standards and Requirements in the U.S. Code of Federal Regulations (23 CFR 680): 1. Conduct value analysis for better outcomes 2. Promote pricing transparency

33 ADVANCED PROPULSION SYSTEMS↗

Search for NC Delta Radiative Decay Single Photon Events In MicroBooNE

MicroBooNE, a liquid argon time projection chamber at Fermilab, is investigating the MiniBooNE anomaly, which consists of an excess of low-energy electromagnetic showers in a neutrino beam. Recent results from MicroBooNE have ruled out a 3+1 sterile neutrino explanation of the anomaly, leaving the single photon-like explanation as the most likely possibility. In this poster, we describe results of a new expanded search for the neutral current Delta radiative decay topology, a rare type of event which is by far the largest expected source of neutrino-induced single photons. Using two different reconstruction paradigms simultaneously, we study in detail events both with and without visible hadronic activity; either category of event could explain the MiniBooNE anomaly, but the two could have very different implications for underlying physics. We find that events with visible protons are excluded as an explanation of the MiniBooNE anomaly, but events without visible protons remain a possible explanation requiring further study.

Hagaman, Lee [Nevis Labs, Columbia U.] (ORCID:0000↗

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗

Electron Neutrino Selection for Neutrino Oscillation Searches in the SBN Program

The Short- Baseline Neutrino (SBN) Pprogram at Fermilab employs a near detector, SBND, and a far detector, ICARUS, to search for baseline-dependent changes to the measure muon neutrino disappearance and electron neutrino appearance and disappearance from the muon neutrino-dominated Booster Neutrino Beam flux. The use of the same liquid argon time projection chamber (LArTPC) technology in both detectors and the same neutrino beam enables a systematically well-constrained oscillation measurement, by leveraging the high statistics of O(10 million) neutrino interactions expected at SBND through 2027 to constrain flux and cross-section systematics. In this poster, we present high-statistics, high-purity electron neutrino selections in SBND and ICARUS and related electron shower energy calibration measurements in SBND enabled by the SPINE deep learning-based particle reconstruction framework. Furthermore, we discuss how these samples can enable high sensitivity to '3+1' sterile neutrino oscillations in a combined fit accounting for systematic uncertainties and correlations.

Oza, Nupur [Nevis Labs, Columbia U.; Columbia U.]↗

Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance, Version 2.0

The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Community Engagement Tips for EV Infrastructure Deployment

This Joint Office of Energy and Transportation help sheet provides tips for conducting community engagement to support electric vehicle (EV) infrastructure planning and deployment. This document is a tool and an informative resource to be used in conjunction with other guidance. It is not intended to set policy or establish or replace any standards under state or federal law applicable to public notice or community engagement.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗