Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “DIRECTORIES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Infiltration Data Package for the E-Area Low-Level Waste Facility Performance Assessment

The infiltration data package contains the input parameters, the cap design and material properties assumptions, and the modeling results for the Hydrologic Evaluation of Landfill Performance (HELP) infiltration model simulations performed in support of the E-Area Low-Level Waste Facility Performance Assessment (PA). The infiltration estimates establish the upper boundary condition for the PORFLOW vadose-zone model and GoldSim model simulations for the following E-Area disposal unit types: Slit and Engineered Trenches, Low-Activity Waste Vault (LAWV), Intermediate-Level Vault (ILV), Componentin- Grout (CIG) special waste form trench segments, and the Naval Reactor Component Disposal Areas (NRCDAs). The infiltration data package builds upon relevant, foundational PA technical reports and memoranda from the past 15 years and is supported by three important components: the HELP model input parameter datasheets, HELP model input and output filenames and directory structure, and infiltration rates as a function of time for each scenario for each disposal unit type. For Slit and Engineered Trenches, a single best-estimate Bahia-grass case of two-percent slope and 585- foot slope length represents an upper bound on intact closure-cap infiltration rates over a 10,000-year period. Building upon the single, bounding, and intact case, two different approaches were considered for incorporating the effect of localized cap subsidence on infiltration rates in the PORFLOW flow and transport model simulations. In the first approach, a Monte Carlo probabilistic model was developed to calculate infiltration rates for 0.54%, 2%, 3.6%, and 4.9% subsidence scenariosa reflecting historical and future non-crushable content for the Slit and Engineered Trenches. The resulting blended (spatially and slope-length averaged) infiltration rates become an inflow upper boundary condition for the PORFLOW vadose zone model simulations. In the second and preferred approach, a Monte Carlo rectangle packing algorithm (Danielson, 2019) and a simplified equation for the total mass flux of water draining into a subsided compartment (Equation 1) will be employed to implement a weighted blending of radionuclide fluxes to the water table using the results of deterministic PORFLOW vadose zone simulations representative of specific subsidence cases. Finally, HELP-model results from sensitivity studies of the intact infiltration case were fit to a log-logistic function to generate infiltration profiles over a 10,000-year period for most-optimistic, more-optimistic, best-estimate, more-pessimistic, and most-pessimistic cases, for both the intact and four subsidence scenarios. For the LAWV and IL vaults, infiltration rate profiles for a 10,000-year period were developed for both an on-vault (above the concrete/metal vault roof) and an off-vault (10-foot soil zone adjacent to vault walls) scenario. The purpose of the off-vault simulations was to confirm that subsurface runoff from the concrete vault roof will adequately drain through the lowermost backfill layers adjacent to the vault walls. The LAWV and ILV infiltration profiles assume collapse of the concrete roof at relative Years 2,905 and 7,100, respectively. The identical Bahia-grass case with two-percent slope and 585-foot slope length assumed for the Slit and Engineered Trenches will represent an upper bound on intact infiltration rates for the NRCDAs and CIG special waste form as well. While the NRCDA casks are assumed to remain structurally intact (i.e., non-assumed to collapse 300 years after the end of operations. Because both rows of the existing CIG trench segments in ST23 (formerly CIG01) extend across the planned cap crest, the subsided CIG trench segments are treated conservatively in the HELP model as a 100%-subsidence case with zero subsurface run-on. The CIG special waste form trench segment infiltration profile, therefore, consists of an intact-cap period from relative Year 100 to Year 300, followed by a 100%-subsidence period from relative Year 300 to Year 10,100.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

CTT: Tools for Fine Alignment of Flash X-ray Systems

The CTT code is a compilation of the python code that was prototyped in the interest of making a method for fine alignment of Flash X-ray Systems at the lab. It contains python code for interacting with LTT and running optimization loops using LTT simulations or ray tracing with RaySpace. It Includes classes for creating phantom objects and modular geometry objects in the simulations. It allows one to generate a random phantom that has been optimized to stay with a certain cubic volume and maximize the minimum distance between any two ball phantom centers in all projections. It was primarily made to work on ball phantoms which were simulated as Teflon spheres. It allows the alignment from some nominal position to some displaced position to simulate recovery of a real geometry from the nominal geometry of the system. Fine alignment can be done with the projections in LTT while a rough alignment is faster using rayspace. If rayspace works well for the use case it should be preferred since it is considerably faster and less resource intensive in general. Some Notes about using this code is that one will have to edit the imports for the files to get to the correct LTT path, LTT GUI path and to the CTT path when importing. This was made by using anaconda with python 3 on windows 10. The LTT code was stored in a anaconda environment which seemed to help the python find the LTT although it shouldn’t be necessary if you append the path in your code using sys.path.append(r'add the path you want here’). The sys.path.append method is a quick way to give your python code access to a given folder when running it (such as LTT or CTT). Note that since the code was originally made with paths for a specific machine that a new user will have to edit those paths to make it work in all the files that use the old paths. This is somewhat tedious but will be required to run the code on a new machine. The methodology used to run and make these notebooks starts with opening a command prompt as administrator in windows 10. After this one would activate the anaconda environment in the appropriate directory using “conda activate myenv” in the command prompt. After this open a jupyter-notebook using the keyword “jupyter-notebook". After that a notebook should open in a browser. Note that some libraries used may not come with anaconda so those may have to be installed. There shouldn’t be much though since the main things used are scipy, numpy, matplotlib, and LTT. LTTQuicksetup also requires some paths that will be specific to the computer so that should be changed as well.

42 ENGINEERING↗
DOE OSTI2021

A New MCNP6 Electron-Photon Transport Validation Test: The Lockwood Energy Deposition Experiment (V.1.0)

This memo announces the availability of a new validation test for quantifying the accuracy of the MCNP6 electron-photon transport algorithm for use in energy-deposition calculations. Specifically, energy-deposition results are compared with the Lockwood energy-deposition experiment. The comparison includes energy-deposition profiles in a variety of different single-element materials including beryllium, aluminum, carbon, copper, iron, molybdenum, tantalum, and uranium for pencil beam electron sources with energies including 0.05-, 0.1-, 0.3-, 0.5, and 1-MeV and angles of incidence including normal, 30°, and 60° off-normal. The purpose of this memo is to discuss the contents of the Lockwood validation directory and to outline the procedure for generating the input files, running the tests, processing the results, and comparing results to the experimental and numerical benchmark. Each step is mostly automated by a makefile that executes the necessary perl script.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

LANL Nuclear Data Manager Format Specification v1.0

The LANL nuclear data manager tool is a Python utility that downloads nuclear data from the Nuclear Data Team’s website at https://nucleardata.lanl.gov, arranges it, and configures directory listings for nuclear codes such as the MCNP code to consume. In this document, the Version 1.0 API that this tool relies on will be discussed, which will show how an external provider of nuclear data could set up their website to provide a compatible implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Verification Problems for Smooth Step Amplitude Load Curves in DYNA3D/Paradyn

This report documents the addition of three new verification tests in the LOADCURVE directory of the DYNA3D/Paradyn Software Quality Assurance test suite. Each test consists of a single element, where the velocities of each node are specified by either the newly added smooth step tabular load curve or another load curve option. The first test assesses the initialization and interpolation of the newly inputted load curve option through tabulated abscissa-ordinate pairs of data. The second test uses the same set of abscissa-ordinate data points and applies offset and scaling parameters available within the load curve definition. The third test defines the smooth step load curve in an original input deck, and assesses its correct redefinition using a restart file. The simulation velocities are compared to their true values at discrete points in time, and each test is verified up to numerical precision. These results confirm that the smooth step load curve option is functioning correctly and as intended.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Electrical Power Engineering Academic Landscape (November 2011)

University Outreach Initiative Overview The GridWise ® Architecture Council (GWAC) is a team of experts with diverse, relevant industry backgrounds that has documented the guiding principles for the architecture and interoperability of a future, intelligent, transactive, energy system. One of GWAC’s goals includes sharing information about their work broadly with industry and other communities that have a need to understand smart grid architecture and interoperability. The concept of a University Outreach Initiative was developed in the spring of 2011 as a set of market research and outreach activities. These activities were developed to identify opportunities for the dissemination of information about GWAC to academic and workforce development communities. Grant recipients of the Smart Grid Workforce Training Program, funded through the American Recovery and Reinvestment Act (ARRA), were identified as initial outreach recipients. This community consists of academic and workforce program managers involved in the development of electrical power engineering or other closely related smart grid technology and business programs at two and four-year institutions, via private sector curriculum development companies, and governmental or collaborate workforce development agencies. The Outreach Initiative started with the development of the Landscape Database and Contact Directory. These documents provide descriptive project and contact information for the Smart Grid Workforce Training Program recipients. Contact information was gathered through telephone calls and Internet research. Contacts identified by telephone were introduced in conversation to the project and were asked if they wished to participate. Their knowledge of GWAC was assessed. Contacts we could not reach by phone received introductory emails explaining the Outreach Initiative and providing links to important GWAC documents for background. A survey to identify contact interest in the initiative was circulated to all contacts several weeks later.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

LCLS Undulator Quadrupole Fiducialization Plan

This note presents the fiducialization plan for the LCLS undulator quadrupoles. The note begins by summarizing the requirements for the fiducialization. A discussion of the measurement equipment is presented, followed by the methods used to perform the fiducialization and check the results. This is followed by the detailed fiducialization plan in which each step is enumerated. Finally, the measurement results and data storage formats are presented. The LCLS is made up of 33 assemblies consisting of an undulator, quadrupole, beam finder wire, and other components mounted on a girder. The components must be mounted in such a way that the beam passes down the axis of each component. In this note, we describe how the ideal beam axis is related to tooling balls on the quadrupole. This step, called fiducialization, is necessary because the ideal beam axis is determined magnetically, whereas tangible objects must be used to locate the quadrupole. The note begins with the list of fiducialization requirements. The laboratory in which the work will be performed and the relevant equipment is then briefly described. This is followed by a discussion of the methods used to perform the fiducialization and the methods used to check the results. A detailed fiducialization plan is presented in which all the steps of fiducialization are enumerated. A discussion of the resulting data files and directory structure concludes the note.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY↗
DOE OSTI2024

RectifHyd Version 2.0: Historical and counterfactual-climatological hydropower monthly generation totals for CONUS plants, 1980 – 2019

This dataset will contain the following files: - RectifHydV2.zip – the RectifHydV2 dataset, split into two files: o RectifHydV2_Actual_MWh.csv: Estimated actual monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 o RectifHydV2_Counterfactual_MWh.csv: Counterfactual (climate-only) monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 - RectifHydV2_code.zip: Full data processing pipeline, coded using R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/rectifhydv2 - RectifHydV2_inputs.zip: Complete set of input data used to create RectifHydV2, organized for direct entry into “/data/” directory of the RectifHydV2 reproducible data pipeline - RectifHydV2_misc.zip: - RectifHydV2_dailyRelease.csv

13 HYDRO ENERGY↗
DOE OSTI2020

ATOMIC Simulations and Experimental Data for Basalt-like Compounds

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [-7,-4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

ATOMIC Simulations and Experimental Data for CaCO3 Mixtures

This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [1] and are used to develop a statistical characterization of matrix effects. Our overall suite of simulations includes contains several sets of simulations: training and validation sets of simulations for three and four element mixtures of calcium, carbon, oxygen, and nitrogen (included to account for atmosphere) along with simulations of the individual elements. The 4-element simulations include the mixture of all four elements mentioned and for each of the four individual elements. The 3-element simulations include output for the mixture of calcium, carbon, oxygen and for these three individual elements. The training data were produced using a 600-run design, shown in Figure 1, that varies input parameters temperature (T), electron density (Ne), and proportion of the elements calcium, carbon, oxygen, and nitrogen (Ca; C; O; N) for the 4 element output. The 3-element output includes all parameters except for the proportion of nitrogen. The element proportions (all the variables but T and Ne) sum to one and are unused in the single-element simulations. The validation data was produced with a 80-run design shown in Figure 2. The training and validation simulation outputs for the 4-element simulations for the mixture and for the single element calcium are shown as sample simulations in Figures 3 and 4 respectively. The simulations produce spectra over a range of 190nm - 950nm that roughly mimics the range collected by the SciAps Z-300 LIBS instrument that was used for the experimental data. The measured spectra for a CaCO3 (which may include contribution from Earth's atmosphere) in the experiment is shown in in Figure 5. All files are kept in directories whose names indicate the elemental composition (CaCO3, Ca, C, O, or N), number of elements (3 or 4), and purpose (training, which is not labeled in the file name, or validation) with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file. [1] J Colgan, EJ Judge, DP Kilcrease, and JE Barefield II. Ab-initio modeling of an iron laser-induced plasma: Comparison between theoretical and experimental atomic emission spectra. Spectrochimica Acta Part B: Atomic Spectroscopy, 97:65{73}, 2014.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

2020_Experiment_1

An early APPL experiment. Many of the RGB's are blank due to Color Segmentation issues. Partial metadata exists in the level0 directory

APPL↗
DOE OSTI2022

Sample IEEE123 Bus system for OEDI SI

Time series load and PV data from an IEEE123 bus system. An example electrical system, named the OEDI SI feeder, is used to test the workflow in a co-simulation. The system used is the IEEE123 test system, which is a well studied test system (see link below to IEEE PES Test Feeder), but some modifications were made to it to add some solar power modules and measurements on the system. The aim of this project is to create an easy-to-use platform where various types of analytics can be performed on a wide range of electrical grid datasets. The aim is to establish an open-source library of algorithms that universities, national labs and other developers can contribute to which can be used on both open-source and proprietary grid data to improve the analysis of electrical distribution systems for the grid modeling community. OEDI Systems Integration (SI) is a grid algorithms and data analytics API created to standardize how data is sent between different modules that are run as part of a co-simulation. The readme file included in the S3 bucket provides information about the directory structure and how to use the algorithms. The sensors.json file is used to define the measurement locations.

123 bus↗
DOE OSTI2018

SolarView: Georgia Solar Adoption in Context

The local-national gap is a problem currently plaguing the adoption of emerging technologies targeted at resolving energy transition issues that are characterized by disparities in the adoption of innovations and policies on a local level in response to national policy implementation. These disparities reflect a complex system of technical, economic, social, political, and ecological factors linked to the perceptions held by communities and how they see energy development and national/global policy goals. This dataset is an attempt to bridge the local-national gap regarding solar PV adoption in the State of Georgia (U.S.) by aggregating variables from seven different publicly-available sources. The objective of this activity was to design a resource that would help researchers interested in the context underlying solar adoption on the local scale of governance (e.g., the county level). The SolarView database includes information necessary for informing policy-making activities such as solar installation information, a historical county zip code directory, county-level census data, housing value indexes, renewable energy incentive totals, PV rooftop suitability percentages, and utility rates. As this is a database from multiple sources, incomplete data entries are noted.

14 SOLAR ENERGY↗
DOE OSTI2022

Centralized and Decentralized Distributed Energy Resource Access Control Implementation Considerations.

A global transition to power grids with high penetrations of renewable energy generation is being driven in part by rapid installations of distributed energy resources (DER). New DER equipment includes standardized IEEE 1547-2018 communication interfaces and proprietary communications capabilities. Interoperable DER provides new monitoring and control capabilities. The existence of multiple entities with different roles and responsibilities within the DER ecosystem makes the Access Control (AC) mechanism necessary. In this paper, we introduce and compare two novel architectures, which provide a Role-Based Access Control (RBAC) service to the DER ecosystem’s entities. Selecting an appropriate RBAC technology is important for the RBAC administrator and users who request DER access authorization. The first architecture is centralized, based on the OpenLDAP, an open source implementation of the Lightweight Directory Access Protocol (LDAP). The second approach is decentralized, based on a private Ethereum blockchain test network, where the RBAC model is stored and efficiently retrieved via the utilization of a single Smart Contract. We have implemented two end-to-end Proofs-of-Concept (PoC), respectively, to offer the RBAC service to the DER entities as web applications. Finally, an evaluation of the two approaches is presented, highlighting the key speed, cost, usability, and security features.

42 ENGINEERING↗
DOE OSTI2021

DRAGraces: A Pipeline for the GRACES High-resolution Spectrograph at Gemini

This paper describes the software Data Reduction and Analysis for GRACES (DRAGraces), which is a pipeline reducing spectra from Gemini Remote Access to the CFHT ESPaDOnS Spectrograph (GRACES) at the Gemini North Telescope. The code is written in the IDL language. It is designed to find all the GRACES frames in a given directory, automatically determine the list of bias, flat, arc, and science frames, and perform the whole reduction and extraction within a few minutes. We compare the output from DRAGraces with that of the Open source Pipeline for ESPaDOnS Reduction and Analysis (OPERA), a pipeline developed at the Canada–France–Hawaii Telescope (CFHT) that also can extract GRACES spectra. Both pipelines were developed completely independently, yet they give very similar extracted spectra. They both have their advantages and disadvantages. For instance, DRAGraces is more straightforward and easy to use and is less likely to be derailed by a parameter that needs to be tweaked, while OPERA offers a more careful extraction that can be significantly superior when the highest resolution is required and when the signal-to-noise ratio is low. One should compare both before deciding which one to use for their science. Yet, both pipelines deliver a fairly comparable resolution power (R ~ 52.8k and 36.6k for DRAGraces and R ~ 58k and 40k for OPERA in high- and low-resolution spectral modes, respectively), wavelength solution, and signal-to-noise ratio per resolution element.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Abstract. Models are an important tool to predict Earth system dynamics. An accurate prediction of future states of ecosystems depends on not only model structures but also parameterizations. Model parameters can be constrained by data assimilation. However, applications of data assimilation to ecology are restricted by highly technical requirements such as model-dependent coding. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module. MIDA works in three steps including data preparation, execution of data assimilation, and visualization. The first step prepares prior ranges of parameter values, a defined number of iterations, and directory paths to access files of observations and models. The execution step calibrates parameter values to best fit the observations and estimates the parameter posterior distributions. The final step automatically visualizes the calibration performance and posterior distributions. MIDA is model independent, and modelers can use MIDA for an accurate and efficient data assimilation in a simple and interactive way without modification of their original models. We applied MIDA to four types of ecological models: the data assimilation linked ecosystem carbon (DALEC) model, a surrogate-based energy exascale earth system model: the land component (ELM), nine phenological models and a stand-alone biome ecological strategy simulator (BiomeE). The applications indicate that MIDA can effectively solve data assimilation problems for different ecological models. Additionally, the easy implementation and model-independent feature of MIDA breaks the technical barrier of applications of data–model fusion in ecology. MIDA facilitates the assimilation of various observations into models for uncertainty reduction in ecological modeling and forecasting.

58 GEOSCIENCES↗
DOE OSTI2026

Analysis of genomic signatures associated with Variovorax endosphere colonization

This repository contains the analysis code and supporting datasets associated with the study “Genomic signatures in Variovorax enabling colonization of the Populus endosphere.” Beals DG, Carper DL, Hochanadel LH, Jawdy SS, Klingeman DM, Piatkowski BT, Weston DJ, Doktycz MJ, Pelletier DA. 2026. Genomic signatures in Variovorax enabling colonization of the Populus endosphere. mSystems 11:e01605-25. https://doi.org/10.1128/msystems.01605-25 The scripts are organized sequentially (01–07) and document the workflows used for: Sequence-read alignment and feature counting Orthogroup and KEGG Ortholog annotation Count normalization Statistical analysis and aggregation Generation of manuscript figures and tables Repository contents The uncompressed files are the finalized, formatted datasets used to generate the figures and tables reported in the study, including the supplemental CSV files referenced in the manuscript. The accompanying ZIP archive contains the complete codebase and example data_input/ and data_output/ directories illustrating the organization and execution of the analytical workflow. Individual scripts identify the corresponding manuscript analyses and figure panels. Raw sequencing data Raw sequencing reads are available through the NCBI Sequence Read Archive under BioProject accession PRJNA1322484.

Beals, Delaney [ORNL] (ORCID:0000000306274574)↗