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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Optical storage media data integrity studies

Optical disk-based information systems are being used in private industry and many Federal Government agencies for on-line and long-term storage of large quantities of data. The storage devices that are part of these systems are designed with powerful, but not unlimited, media error correction capacities. The integrity of data stored on optical disks does not only depend on the life expectancy specifications for the medium. Different factors, including handling and storage conditions, may result in an increase of medium errors in size and frequency. Monitoring the potential data degradation is crucial, especially for long term applications. Efforts are being made by the Association for Information and Image Management Technical Committee C21, Storage Devices and Applications, to specify methods for monitoring and reporting to the user medium errors detected by the storage device while writing, reading or verifying the data stored in that medium. The Computer Systems Laboratory (CSL) of the National Institute of Standard and Technology (NIST) has a leadership role in the development of these standard techniques. In addition, CSL is researching other data integrity issues, including the investigation of error-resilient compression algorithms. NIST has conducted care and handling experiments on optical disk media with the objective of identifying possible causes of degradation. NIST work in data integrity and related standards activities is described.

Podio, Fernando L.↗
DOE OSTI2022

Training data selection for event classification in a highly variable environment

A problem of interest for nuclear nonproliferation is monitoring activities at nuclear facilities, where proliferation events may only take place a few times and often under variable conditions. Machine learning has revolutionized data analytics by enabling the use of measurable signatures to generate predictive models of facility operations. However, traditional methods for training these models require large, reliable data sets with labeled observations, a challenge for nonproliferation. Highly variable conditions further complicate this as events from training data may have occurred in conditions quite different from the event of interest. Our hypothesis is that when events occur in a highly variable environment, careful training data selection for each test event could outperform the standard approach of using all available training data. We developed a method to optimize training data selection for the given test event and applied it to predicting the power level of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. In this study, the reactor startup exhibits variability between occurrences due to natural variability in environmental conditions and operational procedures. Using a combination of analysis techniques, a similitude assessment was performed on data collected from HFIR to isolate clusters that were optimal for training a predictive model. Concepts such as dynamic time warping and Jaccard similarity were used in conjunction with clustering analysis. In order to validate this approach, the model was trained on every combination of unique training events and the predictive performance was compared to the performance using a subset of the training data selected by isolated clusters found through the similitude assessment.

Iyer, A↗
DOE OSTI2024

Developing a Database of Bio-based Materials for Building Envelope Applications

Oak Ridge National Laboratory (ORNL) has been funded by the Department of Energy (DOE) to help accelerate the introduction of building envelope materials that would reduce the carbon footprint of the buildings sector. The DOE’s Building Technologies Office has historically sought to resolve the knowledge gaps regarding the energy efficiency and moisture durability of building envelope systems and to develop the data, guidance, and tools needed to facilitate rapid industry adoption of high-performance, moisture-managed envelope systems. This project will help accelerate the widespread acceptance of a new generation of building materials developed specifically with the intent of reducing the carbon footprint of buildings. We have produced a database of hygrothermal transport properties on low embodied carbon building materials that can be added to energy and durability simulation tools. Properties that were measured include density, heat capacity, thermal conductivity as a function of temperature and relative humidity, moisture dependent permeance, and sorption isotherms as a function of relative humidity. These data sets were measured following consensus national standards using state-of-the-art facilities. The data has been compiled and is being made available to building designers who require these data to assess these new materials in their designs. We will publish the data and seek its addition to reference databases such as the ASHRAE Handbook of Fundamentals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

In Situ Data Analysis Through Physics-informed Tensor Decompositions (LDRD Final Report)

We introduce a new low-dimensional model of high-dimensional numerical simulation data based on low-rank tensor decompositions. Our new model aims to minimize differences between the model data and simulation data as well as functions of the model data and functions of the simulation data. This novel approach to dimensionality reduction of simulation data provides a means of directly incorporating quantities of interests and invariants associated with conservation principles associated with the simulation data into the low-dimensional model, thus enabling more accurate analysis of the simulation without requiring access to the full set of high-dimensional data. Computational results of applying this approach to two standard low-rank tensor decompositions of data arising from simulation of combustion and plasma physics are presented.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

New methods and results for quantification of lightning-aircraft electrodynamics

The NASA F-106 collected data on the rates of change of electromagnetic parameters on the aircraft surface during over 700 direct lightning strikes while penetrating thunderstorms at altitudes from 15,000 t0 40,000 ft (4,570 to 12,190 m). These in situ measurements provided the basis for the first statistical quantification of the lightning electromagnetic threat to aircraft appropriate for determining indirect lightning effects on aircraft. These data are used to update previous lightning criteria and standards developed over the years from ground-based measurements. The proposed standards will be the first which reflect actual aircraft responses measured at flight altitudes. Nonparametric maximum likelihood estimates of the distribution of the peak electromagnetic rates of change for consideration in the new standards are obtained based on peak recorder data for multiple-strike flights. The linear and nonlinear modeling techniques developed provide means to interpret and understand the direct-strike electromagnetic data acquired on the F-106. The reasonable results obtained with the models, compared with measured responses, provide increased confidence that the models may be credibly applied to other aircraft.

Pitts, Felix L.↗
NASA NTRSDate not supplied

Achieving Global Consensus on Acceptable Sound Levels for Overland Supersonic Flight

The National Aeronautics and Space Administration has made a commitment to deliver to the International Civil Aviation Organization’s Committee on Aviation Environmental Protection (ICAO CAEP) data defining community response to sounds from supersonic aircraft designed such that their sonic boom is replaced with a soft “thump” sound. The dataset will be a correlation of public perceptions of these sounds to the corresponding acoustic levels. The data will support efforts to develop international standards for permissible noise from supersonic overflight. NASA is planning and preparing for a series of community overflight tests with the X-59, a unique research aircraft capable of generating the “sonic thump”. NASA will begin these tests in 2024. With an eye toward achieving global consensus for noise standards, NASA’s goal is that the community response data be as broadly representative of the response of the international population as possible. As such, NASA is engaging the international regulatory and research communities in both the planning and execution of these tests, through status briefings at ICAO CAEP-sponsored meetings and through workshops with international participation. As part of this outreach NASA held a virtual workshop in December 2021 focused on strategies and considerations for estimating noise exposure levels and conducting surveys to characterize community annoyance levels relative to the “thump” sounds. This paper will present an overview of NASA’s effort, with a focus on the plans and technical goals for the community response tests. In addition, results of the recent workshop will be briefed, including considerations and approaches for ensuring broad representativeness of results and approaches for estimation of the sound levels across the test community. Participant feedback from both the workshop and previous engagements will be discussed, along with how it is being addressed in NASA’s ongoing planning efforts.

Supersonic Flight↗
NASA NTRS2000

Test Cases for a Rectangular Supercritical Wing Undergoing Pitching Oscillations

Steady and unsteady measured pressures for a Rectangular Supercritical Wing (RSW) undergoing pitching oscillations have been presented. From the several hundred compiled data points, 27 static and 36 pitching oscillation cases have been proposed for computational Test Cases to illustrate the trends with Mach number, reduced frequency, and angle of attack. The wing was designed to be a simple configuration for Computational Fluid Dynamics (CFD) comparisons. The wing had an unswept rectangular planform plus a tip of revolution, a panel aspect ratio of 2.0, a twelve per cent thick supercritical airfoil section, and no twist. The model was tested over a wide range of Mach numbers, from 0.27 to 0.90, corresponding to low subsonic flows up to strong transonic flows. The higher Mach numbers are well beyond the design Mach number such as might be required for flutter verification beyond cruise conditions. The pitching oscillations covered a broad range of reduced frequencies. Some early calculations for this wing are given for lifting pressure as calculated from a linear lifting surface program and from a transonic small perturbation program. The unsteady results were given primarily for a mild transonic condition at M = 0.70. For these cases the agreement with the data was only fair, possibly resulting from the omission of viscous effects. Supercritical airfoil sections are known to be sensitive to viscous effects (for example, one case cited). Calculations using a higher level code with the full potential equations have been presented for one of the same cases, and with the Euler equations. The agreement around the leading edge was improved, but overall the agreement was not completely satisfactory. Typically for low-aspect-ratio rectangular wings, transonic shock waves on the wing tend to sweep forward from root to tip such that there are strong three-dimensional effects. It might also be noted that for most of the test, the model was tested with free transition, but a few points were taken with an added transition strip for comparison. Some unpublished results of a rigid wing of the same airfoil and planform that was tested on the pitch and plunge apparatus mount system (PAPA) showed effects of the lower surface transition Strip on flutter at the lower subsonic Mach numbers. Significant effects of a transition strip were also obtained on a wing with a thicker supercritical section on the PAPA mount system. Both of these flutter tests on the PAPA resulted in very low reduced frequencies that may be a factor in this influence of the transition strip. However, these results indicate that correlation studies for RSW may require some attention to the estimation of transition location to accurately treat viscous effects. In this report several Test Cases are selected to illustrate trends for a variety of different conditions with emphasis on transonic flow effects. An overview of the model and tests is given and the standard formulary for these data is listed. Sample data points are presented in both tabular and graphical form. A complete tabulation and plotting of all the Test Cases is given. Only the static pressures and the real and imaginary parts of the first harmonic of the unsteady pressures are available. All the data for the test are available in electronic file form. The Test Cases are also available as separate electronic files.

Bennett, Robert M.↗
DOE OSTI2023

Recombination smooths the time-signal disrupted by latency in within-host HIV phylogenies

Within-host HIV evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is re-activation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in bifurcating trees. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an Ancestral Recombination Graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time-signals or population bottlenecks. Further, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an Approximate Bayesian Computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally-sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The first Hubble diagram and cosmological constraints using superluminous supernovae

In this work, we present the first Hubble diagram of superluminous supernovae (SLSNe) out to a redshift of two, together with constraints on the matter density, Ω M , and the dark energy equation-of-state parameter, w(≡p/ρ). We build a sample of 20 cosmologically useful SLSNe I based on light curve and spectroscopy quality cuts. We confirm the robustness of the peak–decline SLSN I standardization relation with a larger data set and improved fitting techniques than previous works. We then solve the SLSN model based on the above standardization via minimization of the χ2 computed from a covariance matrix that includes statistical and systematic uncertainties. For a spatially flat Λ cold dark matter (ΛCDM) cosmological model, we find $\Omega _{\rm M}=0.38^{+0.24}_{-0.19}$, with an rms of 0.27 mag for the residuals of the distance moduli. For a w 0 w a CDM cosmological model, the addition of SLSNe I to a ‘baseline’ measurement consisting of Planck temperature together with Type Ia supernovae, results in a small improvement in the constraints of w 0 and wa of 4 per cent. We present simulations of future surveys with 868 and 492 SLSNe I (depending on the configuration used) and show that such a sample can deliver cosmological constraints in a flat ΛCDM model with the same precision (considering only statistical uncertainties) as current surveys that use Type Ia supernovae, while providing a factor of 2–3 improvement in the precision of the constraints on the time variation of dark energy, w 0 and w a . This paper represents the proof of concept for superluminous supernova cosmology, and demonstrates they can provide an independent test of cosmology in the high-redshift (z > 1) universe.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Development of display design and command usage guidelines for Spacelab experiment computer applications

Individual Spacelab experiments are responsible for developing their CRT display formats and interactive command scenarios for payload crew monitoring and control of experiment operations via the Spacelab Data Display System (DDS). In order to enhance crew training and flight operations, it was important to establish some standardization of the crew/experiment interface among different experiments by providing standard methods and techniques for data presentation and experiment commanding via the DDS. In order to establish optimum usage guidelines for the Spacelab DDS, the capabilities and limitations of the hardware and Experiment Computer Operating System design had to be considered. Since the operating system software and hardware design had already been established, the Display and Command Usage Guidelines were constrained to the capabilities of the existing system design. Empirical evaluations were conducted on a DDS simulator to determine optimum operator/system interface utilization of the system capabilities. Display parameters such as information location, display density, data organization, status presentation and dynamic update effects were evaluated in terms of response times and error rates.

Dodson, D. W.↗
NASA NTRS1992

Remote Sensing Data from CLARET: A Prototype Cart Data Set

A data set containing radiation, meteorological, and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of this experiment, ARM scientists requested archival of subsets or the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. The cases range from 2 to 9.5 h in length. A pyranometer, pyrgeometer, pyrheliometer, and an infrared radiometer constituted the ensemble of instruments that provided surface radiation data. A lidar, radar, and ceilometer observed the cloud geometrical structure, and visual reports and all-sky camera observations were assimilated to provide cloud cover data. Radiosondes, wind profiler, RASS (profiling virtual temperature), microwave radiometers (observing column integrated liquid water and water vapor), and standard surface measurements provided meteorological data. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory. In addition to documenting the data set, this report describes CLARET and gives a bibliography of publications associated with the project. Some preliminary results of CLARET' research are also summarized. Simultaneous CO 2 lidar and radar backscatter measurements were shown to provide estimates of the effective radius of ice particles. Simultaneous radar and infrared radiometer data appear useful for estimating column-integrated numbers and average sizes of ice cloud particles. Ice water content obtained with this method compared favorably with values from another empirical technique using radar data alone. Depolarization of the CO 2 lidar signal from ice clouds was surprisingly small, suggesting that calculation of backscatter from nonspherical particles for this lidar is a tractable problem. Examples are also cited of CO 2 lidar measurements of the effective radius of water cloud drop size distributions and of inference of the size of pristine ice crystals that assume a particular orientation in the air. These parameters are all important to radiative transfer through clouds.

Clouds (Meteorology)↗
NASA NTRS2012

Monitoring of International Space Station Telemetry Using Shewhart Control Charts

Shewhart control charts have been established as an expedient method for analyzing dynamic, trending data in order to identify anomalous subsystem performance as soon as such performance would exceed a statistically established baseline. Additionally, this leading indicator tool integrates a selection methodology that reduces false positive indications, optimizes true leading indicator events, minimizes computer processor unit duty cycles, and addresses human factor concerns (i.e., the potential for flight-controller data overload). This innovation leverages statistical process control, and provides a relatively simple way to allow flight controllers to focus their attention on subtle system changes that could lead to dramatic off-nominal system performance. Finally, this capability improves response time to potential hardware damage and/or crew injury, thereby improving space flight safety. Shewhart control charts require normalized data. However, the telemetry from the ISS Early External Thermal Control System (EETCS) was not normally distributed. A method for normalizing the data was implemented, as was a means of selecting data windows, the number of standard deviations (Sigma Level), the number of consecutive points out of limits (Sequence), and direction (increasing or decreasing trend data). By varying these options, and treating them like dial settings, the number of nuisance alerts and leading indicators were optimized. The goal was to capture all leading indicators while minimizing the number of nuisances. Lean Six Sigma (L6S) design of experiment methodologies were employed. To optimize the results, Perl programming language was used to automate the massive amounts of telemetry data, control chart plots, and the data analysis.

Fitch, Jeffery T.↗
DOE OSTI2023

Data-Driven Buy Clean: Decarbonization and Beyond

This report was compiled to provide recommendations on the availability of public background data from the U.S. Federal life cycle assessment (LCA) Data Commons to be conformant with the Association for Life Cycle Assessment (ACLCA) 2022 Product Category Rule (PCR) Open Standard to build technical tools that can assist industry in creating more comparable Type II Environmental Product Declarations (EPDs) for Federal Buy Clean and sustainability initiatives. The Federal LCA Commons is not only a public data source but also a consistently structured, self-referencing mega-repository for data developed by federal agency experts (in agency repositories) and by academia, nonprofit organizations, and industry (via the US Life Cycle Inventory Database). The Federal LCA Commons Technical Working Group is continuously improving the standardization of data documentation, formatting, and nomenclature to ensure lossless data loading and accurate data representation. This report and appendixes include the following: 1) An introduction to data-driven Buy Clean and decarbonization initiatives at the federal level; 2) The current status and associated challenges with LCA data and EPD standards and comparability; 3) Opportunities for the Federal LCA Commons to support conformance with the ACLCA 2022 PCR Open Standard and provide resources to implement the Federal Sustainability Plan, Buy Clean Program, and Inflation Reduction Act (IRA) sustainability goals and objectives. To date, the Federal LCA Commons is the result of coordinated work by National Renewable Energy Laboratory (NREL), the U.S. Department of Agriculture (USDA), the Environmental Protection Agency (EPA), the National Energy Technology Laboratory (NETL), the Argonne National Laboratory (ANL), the U.S. Army Corps of Engineers (USACE), the Federal Highway Administration (FHWA), the U.S. Forest Service (USFS), the Federal Aviation Administration (FAA), the Department of Defense (DoD) and the National Institute of Standards and Technologies (NIST). The Federal LCA Commons will continue to combine databases from the collaborating agencies while remaining a public resource. There are several initiatives among the collaborating agencies to expand the Federal LCA Commons and dedicated federal funding and resources could accelerate and strengthen these initiatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

First Plant Cell Atlas symposium report

The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

AWS Figure of Merit (FOM) Developed Parameters from Static, Transonic Model Tests

This paper provides an approach to answer the question of whether one can rely solely on static data taken during a transonic model test to provide the certainty needed that a new aircraft will or will not have Abrupt Wing Stall (AWS) events during its flight operations. By comparing traditional- and alternate-static-Figures of Merit (FOMs) with the Free-To-Roll (FTR) response data, a rational basis for assessing the merits of using standard testing techniques for the prediction of AWS events has been established. Using the FTR response data as a standard, since these results compare well with flight, the conclusion from this study is that neither traditional nor alternate FOMs can be trusted to provide an indication as to whether a configuration will or will not have AWS tendencies. Even though these FOMs may flag features which have a high degree of correlation with the FTR response data, there are as many or more of these FOM flagged features which do not correlate. Thus, one needs to use the FTR rig to assess AWS tendencies on new configurations.

Lamar, J. E.↗
DOE OSTI2025

Ultra-Fast Non-Volatile Resistive Switching Devices with Over 512 Distinct and Stable Levels for Memory and Neuromorphic Computing

Low-current multilevel programmability with inherent non-volatility and high stability of resistance states is required for both multi-bit memory storage and deep learning accelerators but is difficult to achieve. Here, in a resistive switching system, this work realizes >512 (>9 bits) distinct non-volatile conductance levels with stable retention for each state with current levels down to the nanoampere range, highly promising for potential integration with small processing nodes with ultra-low power consumption requirements. This is achieved by demonstrating a new thin film design concept that encompasses three key features: an ultra-thin epitaxial oxygen ionic switching layer that provides a tunable energy barrier at the bottom electrode, an overcoat amorphous layer that acts as an ion migration barrier for stable state retention, and a partial conductive filament as a localized electronic transport channel to the epitaxial switching layer. A large dynamic resistance range of up to seven orders of magnitude is achieved with reset-free transitions among intermediate states, and programmability is demonstrated with ultra-fast (20 ns) pulses. Artificial neural network (ANN) simulations, based on the experimental performance and its non-idealities, demonstrate close-to-ideal inference accuracies for various Modified National Institute of Standards and Technology (MNIST) data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

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