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Results for “algorithmic differentiation”

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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562 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Genomic diversifications of five Gossypium allopolyploid species and their impact on cotton improvement

Abstract Polyploidy is an evolutionary innovation for many animals and all flowering plants, but its impact on selection and domestication remains elusive. Here we analyze genome evolution and diversification for all five allopolyploid cotton species, including economically important Upland and Pima cottons. Although these polyploid genomes are conserved in gene content and synteny, they have diversified by subgenomic transposon exchanges that equilibrate genome size, evolutionary rate heterogeneities and positive selection between homoeologs within and among lineages. These differential evolutionary trajectories are accompanied by gene-family diversification and homoeolog expression divergence among polyploid lineages. Selection and domestication drive parallel gene expression similarities in fibers of two cultivated cottons, involving coexpression networks and N 6 -methyladenosine RNA modifications. Furthermore, polyploidy induces recombination suppression, which correlates with altered epigenetic landscapes and can be overcome by wild introgression. These genomic insights will empower efforts to manipulate genetic recombination and modify epigenetic landscapes and target genes for crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2025

A Comprehensive Study of the Impact of Inverter-Based Resource (IBR) Modeling and Control on Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗