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DOE OSTI2022

Queued Up: Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2021 [Slides]

Proposed large-scale electric generation and storage projects must apply for interconnection to the bulk power system via interconnection queues. While most projects that apply for interconnection are not subsequently built, data from these queues nonetheless provide a general indicator for mid-term trends in developer interest. Berkeley Lab compiled and analyzed data from all seven ISOs/RTOs in concert with 35 non-ISO utilities, representing an estimated 85% of all U.S. electricity load. We include all "active" projects in these generation interconnection queues through the end of 2021, as well as data on "operational" and "withdrawn" projects where those data are available. We find that the amount of new electric capacity in these queues is growing dramatically, with over 1,400 gigawatts (GW) of total generation and storage capacity now seeking connection to the grid (over 90% of which is for zero-carbon resources like solar, wind, and battery storage). Solar (676 GW) and battery storage (~420 GW) are – by far – the fastest growing resources in the queues; combined they accounted for nearly 85% of new capacity entering the queues in 2021. Substantial wind (247 GW) capacity is also seeking interconnection, 31% of which is for offshore projects (77 GW). In total, about 930 GW of zero-carbon generating capacity is currently seeking transmission access, as is 74 GW of natural gas capacity. Hybrids now comprise a large – and increasing – share of proposed projects, particularly in CAISO and the non-ISO West. 286 GW of solar hybrids (primarily solar+battery) and 19 GW of wind hybrids are currently active in the queues; nearly half of battery storage in the queues is paired with generation. However, much of this proposed capacity will be withdrawn from the queues and not built. Among a subset of queues for which data are available, only 23% of the projects seeking connection from 2000 to 2016 have subsequently been built. Completion percentages appear to be declining and are even lower for wind and solar than other resources. Additionally, wait times are on the rise: for the regions with available data, the typical duration from connection request to commercial operation increased from ~2.1 years for projects built in 2000-2010 to ~3.7 years for those built in 2011-2021.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Queued Up: Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2022 [Slides]

Proposed large-scale electric generation and storage projects must apply for interconnection to the bulk power system via interconnection queues. While most projects that apply for interconnection are not subsequently built, data from these queues nonetheless provide a general indicator for mid-term trends in developer interest. Berkeley Lab compiled and analyzed data from all seven ISOs/RTOs in concert with 35 non-ISO utilities, representing an estimated 85% of all U.S. electricity load. We include all "active" projects in these generation interconnection queues through the end of 2022, as well as data on "operational" and "withdrawn" projects where those data are available. We find that the amount of new electric capacity in these queues is growing dramatically, with over 2,000 gigawatts (GW) of total generation and storage capacity now seeking connection to the grid (over 95% of which is for zero-carbon resources like solar, wind, and battery storage). Solar (947 GW) and battery storage (~680 GW) are – by far – the fastest growing resources in the queues; combined they accounted for over 80% of new capacity entering the queues in 2022. Substantial wind (300 GW) capacity is also seeking interconnection, 38% of which is for offshore projects (113 GW). In total, about 1,250 GW of zero-carbon generating capacity is currently seeking transmission access, as is 82 GW of natural gas capacity. Hybrids projects (co-locating multiple generation and/or storage types) comprise a large – and increasing – share of proposed projects, particularly in CAISO and the non-ISO West. 457 GW of solar hybrids (primarily solar+battery) and 24 GW of wind hybrids are currently active in the queues; over half of battery storage in the queues is paired with generation. However, much of this proposed capacity will be withdrawn from the queues and not built. Among a subset of queues for which data are available, only 21% of the projects (and 14% of capacity) seeking connection from 2000 to 2017 have been built as of the end of 2022. Additionally, interconnection wait times are on the rise: The typical duration from connection request to commercial operation increased from <2 years for projects built in 2000-2007 to nearly 4 years for those built in 2018-2022 (with a median of 5 years for projects built in 2022).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Machine Learning Predicts the Timing and Shear Stress Evolution of Lab Earthquakes Using Active Seismic Monitoring of Fault Zone Processes

Abstract Machine learning (ML) techniques have become increasingly important in seismology and earthquake science. Lab‐based studies have used acoustic emission data to predict time‐to‐failure and stress state, and in a few cases, the same approach has been used for field data. However, the underlying physical mechanisms that allow lab earthquake prediction and seismic forecasting remain poorly resolved. Here, we address this knowledge gap by coupling active‐source seismic data, which probe asperity‐scale processes, with ML methods. We show that elastic waves passing through the lab fault zone contain information that can predict the full spectrum of labquakes from slow slip instabilities to highly aperiodic events. The ML methods utilize systematic changes in P‐wave amplitude and velocity to accurately predict the timing and shear stress during labquakes. The ML predictions improve in accuracy closer to fault failure, demonstrating that the predictive power of the ultrasonic signals improves as the fault approaches failure. Our results demonstrate that the relationship between the ultrasonic parameters and fault slip rate, and in turn, the systematically evolving real area of contact and asperity stiffness allow the gradient boosting algorithm to “learn” about the state of the fault and its proximity to failure. Broadly, our results demonstrate the utility of physics‐informed ML in forecasting the imminence of fault slip at the laboratory scale, which may have important implications for earthquake mechanics in nature.

58 GEOSCIENCES↗

DOE OSTI2020

Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission. A newer version of the data exists and can be found linked in the resources of this submission under "Solar-to-Grid Public Data File Updated 2021".

annual solar value↗

DOE OSTI2025

BLDAP Intro to Python/Data Science Curriculum v1

The Github repository contains the Jupyter notebooks for the intro to Python / Data Science course for Berkeley Lab Director's Apprenticeship Program (BLDAP). This course is designed for students with little to no experience in coding to learn skills in Python necessary for data science. Students utilize Jupyter notebooks throughout the course. The overall goal is for students to learn how to use Python to clean, analyze, and visualize large data sets in order to communicate effectively their conclusions about the data set. Students apply the skills they learned on actual data sets provided by researchers in Berkeley Lab.

Hales, Laurel [Lawrence Berkeley National Laborato↗

DOE OSTI2021

Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value for 2012-2020

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI, covering the years 2012-2020. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission.

annual solar value↗

DOE OSTI2023

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗

DOE OSTI2023

First results on nucleon resonance electroexcitation amplitudes from ep → e'π + π – p' cross sections at W = 1.4–1.7 GeV and Q 2 = 2.0–5.0 GeV 2

The electroexcitation amplitudes or $\gamma_vpN^*$ electrocouplings of the $N(1440)1/2^+$, $N(1520)3/2^-$, and $\Delta(1600)3/2^+$ resonances were obtained for the first time from the $ep \to e'\pi^+\pi^-p'$ differential cross sections measured with the CLAS detector at Jefferson Lab within the range of invariant mass $W$ of the final state hadrons from 1.4–1.7~GeV for photon virtualities $Q^2$ from 2.0--5.0~GeV$^2$. A good description of the nine independent one-fold differential $\gamma_v p\to \pi^+\pi^-p'$ cross sections achieved within the data-driven Jefferson Lab-Moscow State University (JM) meson-baryon reaction model in each bin of ($W$,$Q^2$) allows for separation of the resonant and non-resonant contributions. The electrocouplings were determined in the fits of the $\pi^+\pi^-p$ cross sections within three overlapping $W$ intervals with a substantial contribution from each of the three resonances listed above. Consistent results on the electrocouplings extracted from the data in these $W$ intervals provide evidence for their reliable extraction. These studies extend information on the electrocouplings of the $N(1440)1/2^+$ and $N(1520)3/2^-$ available from this channel over a broader range of $Q^2$. The electrocouplings of the $\Delta(1600)3/2^+$, which decays preferentially into $\pi\pi N$ final states, have been determined for the first time. Here, the reliable extraction of the electrocouplings for these states is also supported by the description of the $\pi^+\pi^-p$ differential cross sections with $Q^2$-independent masses and total/partial hadronic decay widths into the $\pi\Delta$ and $\rho p$ final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗

DOE OSTI2020

*-DCC: A platform to collect, annotate, and explore a large variety of sequencing experiments

Background: Over the past few years the variety of experimental designs and protocols for sequencing experiments increased greatly. To ensure the wide usability of the produced data beyond an individual project, rich and systematic annotation of the underlying experiments is crucial. Findings: We first developed an annotation structure that captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure, and the sequencing and processed files. Through various design features, such as controlled vocabularies and different field requirements, we ensured a high annotation quality, comparability, and ease of annotation. The structure can be easily adapted to a large variety of species. We then implemented the annotation strategy in a user-hosted web platform with data import, query, and export functionality. Conclusions: We present here an annotation structure and user-hosted platform for sequencing experiment data, suitable for lab-internal documentation, collaborations, and large-scale annotation efforts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Laser Diode Analysis and Verification (Professional Report)

The goal of this project at Lawrence Livermore National Laboratory (LLNL) was focused on analyzing and verifying laser diodes to ensure that the diodes meet requirements for LLNL mission applications. The different stages of this testing were documented in a process flow map which included location color coding so that each step was clearly defined in scope and location of appropriate testing facility. Data were collected and analyzed and compared to minimum acceptable values to see if requirements were met. The process map documents the initial receipt, inspection, and testing of the laser diodes. Initial inspections started with Keyence Microscope imaging and then moved on to High Potential, Ramp, and Burst Testing. Data from the diode testing were processed through MATLAB and Python codes to verify various metrics such as slope efficiency, threshold current, back irradiance, and beam divergence met requirements. These metrics were then recorded in Excel summary reports. Approximately 95% of the laser diodes passed all tests. Presentations were given to Lawrence Livermore’s internal leadership team, an external partner, and to a Lab-wide audience. The data released for this report was constrained by information protection considerations of LLNL’s national security missions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Factors Influencing Building Demand Flexibility

The U.S. Department of Energy’s National Roadmap for Grid-interactive Efficient Buildings (GEB) acknowledged that building demand flexibility (DF) is both an important strategy to decarbonizing the buildings sector and an important resource for meeting the changing needs of the electrical grid such as improving grid reliability. However, understanding the complexity and uncertainties in real building field performance of DF strategies is a large gap hindering stakeholders on both grid and buildings side to make investments on deploying such strategies. The research work in this report intended to advance understanding of the variability and influential factors in building demand flexibility. Adding such knowledge based on lab testing results and measured performance data from real buildings is an important contribution. The report uses standardized metrics and methods to quantify DF performance from field-measured DF datasets of two significant building groups of big-box retail and medium office buildings to present the challenge of building DF variability in multiple dimensions. The report presents findings related to how several key factors influence building demand flexibility from implementing a common, cost-effective DF control strategy (i.e., adjusting zone temperatures). The findings are supported by full-scale lab testing, field data analysis and simulation research. The authors also provided application-oriented recommendations to stakeholders such as building aggregators, utility program design professionals, sophisticated building portfolio owners, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Investigating high-energy proton-induced reactions on spherical nuclei: Implications for the preequilibrium exciton model

A number of accelerator-based isotope production facilities utilize $100-200$ MeV proton beams due to the high production rates enabled by high-intensity beam capabilities and the greater diversity of isotope production brought on by the long range of high-energy protons. However, nuclear reaction modeling at these energies can be challenging because of the interplay between different reaction modes and a lack of existing guiding cross section data. A Tri-lab collaboration has been formed between the Lawrence Berkeley, Los Alamos, and Brookhaven National Laboratories to address these complexities by characterizing charged-particle nuclear reactions relevant to the production of established and novel radioisotopes. In the inaugural collaboration experiments, stacked-targets of niobium foils were irradiated at the Brookhaven Linac Isotope Producer ($E_p=200$ MeV) and the Los Alamos Isotope Production Facility ($E_p=100$ MeV) to measure $^{93}$Nb(p,x) cross sections between $50-200$ MeV. The results were compared with literature data as well as the default calculations of the nuclear model codes TALYS, CoH, EMPIRE, and ALICE. The default code predictions largely failed to reproduce the measurements. Therefore, we developed a standardized procedure, which determines the reaction model parameters that best reproduce the most prominent reaction channels in a physically justifiable manner. Overall, the primary focus of the procedure was to determine the best parameterization for the pre-equilibrium two-component exciton model. This modeling study revealed a trend towards a relative decrease for internal transition rates at intermediate proton energies ($E_p=20-60$ MeV) in the current exciton model as compared to the default values. The results of this work are instrumental for the planning, execution, and analysis essential to isotope production.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Carbon dioxide (CO2) flux, amplicon sequencing and liquid chromatography–mass spectrometry (LC-MS) data for pyrogenic organic matter (PYOM) amended soil incubations in lab, Madison, WI, 2021-22

This dataset comprises soil-pyrogenic organic matter (PyOM) incubation experiments conducted in a laboratory setting. The focus was on measuring carbon dioxide (CO2) flux emitted in the headspace of incubation jars over a one-month period. The aim was to estimate carbon mineralization from two different carbon fractions in PyOM, as well as carbon mineralization from soil organic carbon (SOC). Bacterial and fungal community profiles were tracked at various time points during the incubation to observe changes in the overall community and specific responders to PyOM. LC-MS analysis of soil samples was also performed to monitor changes in the soil's chemical composition.The provided dataset includes processed CO2 flux measurements obtained from the Picarro-multiplexer measurement setup for each sample incubation jar. This data is available in the "CO2Flux.csv" file. Additionally, the dataset includes CO2 flux data partitioned to estimate mean carbon mineralization from the two PyOM carbon fractions, bulk PyOM, and SOC. The cumulative carbon mineralization data is provided in "cml_respired.csv," while the rate of carbon mineralization data is in "rate_respired.csv." The file "cml_respired_lastcyc.csv" contains cumulative carbon mineralization data for the PyOM carbon fractions, bulk PyOM, and SOC throughout the entire incubation period.For the LC-MS analysis, the raw data can be found in the "20220721_NZ_PeakHeights_FinalAnalysis.csv" file, while sample metadata is provided in "20220721_NZpilot_Metadata.csv". Processed LC-MS data is available in the file "20220721_NZ_FINAL_msdat_sub3.csv". Lastly, the dataset includes the relative abundance data for bacterial genera that exhibited a significant positive response to the addition of PyOM produced at 350 degrees Celsius, which can be found in "resp_genera_350.csv".

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Sapling bark water vapor conductance measurements from 2016-2019, Panama

This data package contains lab-based measurements of bark water vapor conductance from saplings in seasonally dry forests in the Parque Natural Metropolitano and Eugene Eisenmann Reserve, and a shadehouse in Panama. A total of 14 populations of 8 tree species were measured. The goal was to test whether bark water vapour conductance (gbark) was associated with values of stem water deficit that were published previously. In the attached zip file are two Excel metadata files with site information and descriptions of the CSV datasets included, as well as a PDF file "Sapling bvc metadata description," which describes the methods and protocol thoroughly. This data is associated with the publication Wolfe Brett T. 2020Bark water vapour conductance is associated with drought performance in tropical treesBiol. Lett.1620200263 https://doi.org/10.1098/rsbl.2020.0263.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A Measurement of the Eta Meson Radiative Decay Width via the Primakoff Effect

The ? meson is an interesting tool to study fundamental symmetries in Quantum Chromodynamics (QCD). In particular, its radiative decay width, ? p? Ñ ??q, is an important quantity that can be predicted in the framework of Chiral Perturbation Theory. A precision measurement of this quantity would provide critical inputs to understanding the mixing of the ? and ?1 mesons and extracting constants with wide-ranging applications in low-energy QCD. This decay width has been measured in the past using two different experimental techniques. The more popular technique utilized e`e´ collisions to produce ? mesons through electromagnetic interactions. Today, the Particle Data Group (PDG) averages the results of five such experiments to obtain their currently-accepted value of the decay width as: 0.515?0.018 keV. However the first measurement of this quantity was obtained from a fixed-target experiment that measured the cross section for photoproduction of ? mesons on a nuclear target via the Primakoff effect. Their result of 0.324?0.046 keV shows strong tension with the average of the collider measurements, motivating a new, high precision measurement using the Primakoff method. For this purpose, the PrimEx-eta experiment was conducted in Hall D of the Thomas Jefferson National Accelerator Facility (Jefferson Lab or JLab). The data is currently being analyzed to measure the differential cross section for the photoproduction of ? mesons on a liquid, 4He target. Preliminary results obtained from the analysis of the first phase of the PrimEx-eta experiment show reasonable agreement with the currently-accepted PDG value of the radiative decay width. However, as will be discussed, there are many challenges to this precision measurement which must be studied before any results can be finalized and compared with previous measurements. In parallel to the ? decay width measurement, the PrimEx-eta experiment measured the total cross section for the fundamental, Quantum Electrodynamics (QED) process of Compton scattering from the atomic electrons inside the target. The results obtained from this measurement are in strong agreement with the next-to-leading order QED calculations, and the total combined uncertainties are below 3% for incident photon energies between 7-10 GeV. In addition to providing the first precision measurement of the total Compton scattering cross section within this beam energy range, this measurement verifies the capability of the PrimEx-eta experimental setup to perform absolute cross section measurements at forward angles, and serves as a reference process for the calibration of systematic uncertainties.

Smith, Andrew↗

DOE OSTI2026

SIDIS Unpolarized Cross Sections from a 3 He Target with the Solenoidal Large Intensity Device at JLab

In this paper we present a detailed impact study of semi-inclusive deep inelastic scattering unpolarized cross sections' measurements using the proposed SoLID apparatus at Jefferson Lab. This type of data, collected at large Bjorken x bj , moderate values of Q 2 and small values of the transverse momentum of produced hadrons, P hT , allows to study transverse momentum dependent (TMD) parton distribution and fragmentation functions in a still poorly explored region. We present the projected results for charged light mesons based on simulated data. For the azimuthal-angle integrated cross sections we adopt the TMD framework up to the next-to-next-to-next-to-leading-logarithmic accuracy, while a simpler TMD parton model is employed for the study of azimuthal angular dependencies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Systematic Extraction of Pion Parton Distributions Using Threshold Resummation and Applications to Pion TMDs

Following our recent Monte Carlo determination of the pion?s PDFs from Drell-Yan (DY) and leading neutron electroproduction data from the Jefferson Lab Angular Momentum (JAM) collaboration, we extend the analysis by including effects from threshold resummation. At higher orders in the strong coupling, ?S, soft gluon emissions cause large logarithmic corrections, which become important in the qq¯ channel of the DY partonic cross section near threshold. These corrections can be summed over all orders of ?S. However, different prescriptions exist for how the threshold resummation is implemented, for instance, using varying levels of approximation in the Minimal Prescription with cosine, expansion, and double Mellin methods. We present the Monte Carlo results of the first simultaneous fit of the valence, sea, and gluon distributions in the pion taking into account the ambiguities in the resummation calculations. The wide ranges of valence distributions at large x and the effective behavior of the valence distribution as x approaches 1 is discussed. While the PDFs are extracted through collinear factorization, we additionally present a dedicated study to the low and large lepton pair transverse momentum distributions (TMDs) in the same DY experimental data. By adjusting the nonperturbative TMD components, we analyze the degree of compatibility between data and theory across all regions of transverse momentum dependence. We attempt to match the description of the low transverse momentum region using Collins-Soper-Sterman (CSS) formalism and the large transverse momentum region, which is best described using collinear factorization.

Sato, Nobuo↗