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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Optimization models for integrated biorefinery operations

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

09 BIOMASS FUELS↗
DOE OSTI2021

Valuation of Surface Coatings in High-Energy Density Lithium-ion Battery Cathode Materials

Artificial barriers, usually with either electrochemically active or inactive coating materials, are deployed on cathode material surfaces to mitigate detrimental side reactions by suppressing direct contact of cathode and electrolyte called surface coatings. These surface coatings are commonly known to increase the wettability of liquid electrolyte and reduce the interfacial charge transfer resistance. An important caveat is the selection of appropriate coating material with appropriate thickness for achieving enhanced electrochemical performance. As modern battery materials are increasingly developed with some type of surface coating, a careful and thorough examination of their role in mitigating the cycle life issues of cathode materials is paramount. Here, this comprehensive review article extensively covers the selection criteria of coating materials based on their chemical and physical properties and electrochemical functionalities. Additionally, the article discusses the concept of critical coating thickness and methods of achieving homogeneous coating architectures that deliver desired performance benefits. Furthermore, this comprehensive article summarizes the recent advancements, effectiveness, necessity of cathode surface coatings and identifies the key aspect of structure-property correlation between coating type/thickness and lithium-ion diffusion through coating layers as the linchpin that validates surface coating approaches especially for high capacity nickel-rich cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Characterization of pitch carbon coating properties affecting the electrochemical behavior of silicon nanoparticle lithium-ion battery anodes

Silicon is an exciting material for next-generation lithium-ion battery anodes, due to its high theoretical capacity and availability, but its widespread implementation has been limited by extensive volume changes during cycling that causes mechanical damage and limits cycle life. One approach to mitigating these deleterious effects while still maintaining silicon's benefits is the addition of a pitch carbon coating to nanometer-sized silicon particles. Here, in this study, we present characterization of pitch-coated silicon electrodes without annealing and annealed at 700 °C and 1000 °C to determine the optimum temperature treatment, as well as pitch-only and silicon-only electrodes with and without annealing to elucidate the impacts of each component on early electrochemical behavior. Using Fourier transform infrared and Raman spectroscopies, atomic force and scanning spreading resistance microscopy, and electrochemical analysis, we find 700 °C to be the optimal annealing temperature, as amorphous carbon is created, which improves conductivity prior to cycling and facilitates ion storage during cycling that increases capacity. We also present in situ Raman spectroscopy data demonstrating the heterogeneous aging that occurs across the electrode surface during cycling.

25 ENERGY STORAGE↗
DOE OSTI2021

An ontology to represent synthetic building occupant characteristics and behavior

Since the introduction of the occupant behavior Drivers-Needs-Actions-Systems (DNAS) framework in 2013, researchers have used the framework or further developed it based on their case studies, which include efforts to collect new data on occupant behaviors. The effort is often costly for the relatively few new data points added. Problems emerge when the already collected data do not meet the modelers' interoperability requirements. Previous studies addressed this issue by developing more sophisticated ontologies that enable integration with other datasets and synthetic data methodologies that would meet unique research applications. This paper presents an extension of the DNAS framework for the representation of synthetic occupant data to support various applications and use cases across the building life cycle. An agent-based modeling application is one of our motivations that requires more elaborate characteristics of an occupant-agent or a group-of-agent. The extension, built upon a review of the literature, introduces new elements to the framework that fall into five categories, including socio-economic, geographical location, activities, subjective values, and individual and collective adaptive actions. On-going research includes identifying occupant datasets and developing data fusion methods to generate synthetic occupants, as well as to demonstrate its applications in agent-based modeling coupled with building performance simulation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Circular Economy Modeling Efforts at NREL: Circular Economy Lifecycle Analysis and Visualization (CELAVI) and the Circular Economy Agent-Based Model (ABM)

Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.

circular economy↗
DOE OSTI2024

Efficient distributed continual learning for steering experiments in real-time

Deep learning has emerged as a powerful method for extracting valuable information from large volumes of data. However, when new training data arrives continuously (i.e., is not fully available from the beginning), incremental training suffers from catastrophic forgetting (i.e., new patterns are reinforced at the expense of previously acquired knowledge). Training from scratch each time new training data becomes available would result in extremely long training times and massive data accumulation. Rehearsal-based continual learning has shown promise for addressing the catastrophic forgetting challenge, but research to date has not addressed performance and scalability. To fill this gap, we propose an approach based on a distributed rehearsal buffer that efficiently complements data-parallel training on multiple GPUs to achieve high accuracy, short runtime, and scalability. It leverages a set of buffers (local to each GPU) and uses several asynchronous techniques for updating these local buffers in an embarrassingly parallel fashion, all while handling the communication overheads necessary to augment input minibatches using unbiased, global sampling. We further propose a generalization of rehearsal buffers to support both classification and generative learning tasks, as well as more advanced rehearsal strategies (notably Dark Experience Replay, leveraging knowledge distillation). We illustrate this approach with a real-life HPC streaming application from the domain of ptychographic image reconstruction. Furthermore, we run extensive experiments on up to 128 GPUs of the ThetaGPU supercomputer to compare our approach with baselines representative of training-from-scratch (the upper bound in terms of accuracy) and incremental training (the lower bound). Results show that rehearsal-based continual learning achieves a top-5 validation accuracy close to the upper bound, while simultaneously exhibiting a runtime close to the lower bound.

Asynchronous data management↗
DOE OSTI2024

An experimental process parameter study on the identification of defects in additively fabricated Al6061 with laser powder bed fusion

Additively fabricated metal parts using laser powder bed fusion (L-PBF) possess sophisticated morphology due to the recurrent use of laser-induced metal powder melting and solidification. The surface and 3D morphology of these parts often include defects in the form of protrusions, depressions, pores, voids, keyholes, or cracks that are known to be influenced by laser scanning paths and layer-to-layer processing. Such inconsistent part quality hampers the extensive adoption of L-PBF. Pores and cracks are detrimental to the fatigue life of the parts and components. Quantifying and controlling part defects and optimizing processing and scanning strategy parameters adaptively in real-time through in situ monitoring systems are highly desired. This study investigates the optimization of experimental process parameters (power, scan velocity, and hatch spacing) and their effects on the cracking and porosity of Al6061 alloy using machine learning techniques. Multi-objective optimization is formulated and conducted to determine the L-PBF parameters that minimize both porosity and crack densities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Intensification differentially affects the delivery of multiple ecosystem services in subtropical and temperate grasslands

Intensification, the process of intensifying land management to enhance agricultural goods, results in “intensive” pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO 2 and CH 4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO 2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH 4 emissions from subtropical pastures and reduced CH 4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Crossover Effects of Transition‐Metal Ions on Lithium‐Metal Anode in Localized High Concentration Electrolytes

Abstract The stability of the solid–electrolyte interphase (SEI) is critical to the cycle life of lithium‐metal batteries (LMBs). While the crossover effect of transition‐metal ions from cathode to anode is extensively studied in lithium‐ion batteries with graphite anodes, its impact on LMBs remains largely unexplored. Herein, this study investigates the electrochemical and chemical properties of SEI layers formed on lithium‐metal anodes in localized high‐concentration electrolytes (LHCEs) containing dissolved transition‐metal ions (Ni 2+ , Mn 2+ , and Co 2+ ). It is demonstrated that transition‐metal ions in LHCEs reduce the coulombic efficiency (CE) and significantly degrade the cycle life of LMBs. Time‐of‐flight secondary‐ion mass spectrometry (ToF‐SIMS) reveals that SEI structures differ depending on the dissolved TM ion, with Mn 2+ and Co 2+ inducing severe destabilization, and Ni 2+ exhibiting a less severe impact. These findings underscore the detrimental effects of transition‐metal crossover effects in LMB systems.

Guo, Zezhou [Materials Science and Engineering Pro↗
DOE OSTI2021

In Situ Synthesis of Graphene-Coated Silicon Monoxide Anodes from Coa-Derived Humic Acid for High-Performance Lithium-Ion Batteries

Silicon monoxide (SiO) is attaining extensive interest amongst silicon-based materials due to its high capacity and long cycle life; however, its low intrinsic electrical conductivity and poor coulombic efficiency strictly limit its commercial applications. Here low-cost coal-derived humic acid (HA) is used as a feedstock to synthesize in-situ graphene-coated disproportionated SiO (D-SiO@G) anode with a facile method. HRTEM and XRD confirm the well-coated graphene layers on an SiO surface. Scanning Transmission X-ray Microscopy (STXM) and X-ray Absorption Near-Edge Structure (XANES) spectra analysis indicate that the graphene coating effectively hinders the side-reactions between the electrolyte and SiO particles . As a result, the D-SiO@G anode presents an initial discharge capacity of 1937.6 mAh g -1 at 0.1 A g -1 and an initial coulombic efficiency (ICE) of 78.2%. High reversible capacity (1023 mAh g -1 at 2.0 A g -1 ), excellent cycling performance ( 72.4% capacity retention after 500 cycles at 2.0 A g -1 ), and rate capability (774 mAh g -1 at 5 A g -1 ) results are substantial. Full coin cells assembled with LiFePO 4 electrodes and D-SiO@G electrodes display impressive rate performance. These results indicate a promising potential for practical use in high-performance lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Roadmapping Minigrid Innovations for Cost Reduction

Electrification of the world's rural regions is a high priority for both the private and public sectors, as it has been linked to economic development, improved education and public health. Minigrid systems, opposed to grid extension, have been identified as the favorable solution for electrification in many cases. However, the life cycle costs of minigrid systems remain too high for widespread implementation. To address this, Colorado State University (CSU) and the National Renewable Energy Laboratory (NREL) hosted a series of 3 workshops to engage a range of minigrid stakeholders to determine common issues underlying the cost of minigrid systems. The series identified numerous areas for further development in technology and business, with equal emphasis on pre-installation, capital/equipment, and operational costs. In addition, the workshop series emphasized the need for better market intelligence and a better understanding of productive use as a means of stimulating energy demand.

cost reduction↗
DOE OSTI2025

The aluminium-26 distribution in a cosmological simulation of a Milky Way-type Galaxy

Context . The 1.8 MeV γ -rays corresponding to the decay of the radioactive isotope 26 Al (with a half-life of 0.72 Myr ) have been observed by the SPI detector on the INTEGRAL spacecraft and extensively used as a tracer of star formation and current nucleosynthetic activity in the Milky Way Galaxy. Further information is encoded in the observation related to the higher 26 Al content found in regions of the Galaxy with the highest line-of-sight (LoS) velocity relative to an observer located in the Solar System. However, this feature remains unexplained. Aims . We ran a cosmological “zoom-in” chemodynamical simulation of a Milky Way-type galaxy, including the production and decays of radioactive nuclei in a fully self-consistent way. We then analyzed the results to follow the evolution of 26 Al throughout the lifetime of the simulated galaxy to provide a new method for interpreting the 26 Al observations. Methods . We included the massive star sources of 26 Al in the Galaxy and its radioactive decay into a state-of-the-art galactic chemical evolution model, coupled with cosmological growth and hydrodynamics. This approach allowed us to follow the spatial and temporal evolution of the 26 Al content in the simulated galaxy. Results . Our results are in agreement with the observations with respect to the fact that gas particles in the simulation with relatively higher 26 Al content also have the highest LoS velocities. On the other hand, gas particles with relatively lower 26 Al content (i.e., not bright enough to be observed) generally display the lowest LoS velocities. However, this result is not conclusive because the overall rotational velocity of our simulated galaxy is higher than that observed for cold CO gas in the Milky Way Galaxy. Furthermore, we found no significant correlation between gas temperature, rotational velocity, and 26 Al content at any given radius. We also found the presence of transient 26 Al-rich spots at low LoS velocities and we show that one such spot had been captured by the INTEGRAL/SPI data. Based on our model, we present a prediction for the detection of 1.8 MeV γ -rays by the future COSI mission. We find that according to our model, the new instrument will be able to observe similar 26 Al-emission patterns to those seen by INTEGRAL/SPI.

Wehmeyer, B. (ORCID:0009000254149292)↗
DOE OSTI2022

Agent-Based Modeling for the Circular Economy: Lessons Learned From Three Case Studies

The circular economy (CE) aims at decoupling human activities from resource use, creating wealth in the process. Recently, many scholars have questioned the link between increased circularity and sustainability, resulting in many methodological approaches being developed for that purpose. This presentation summarizes the insights gained from the application of agent-based modeling (ABM) to study the techno-economic and social conditions promoting circularity and sustainability of three technologies: photovoltaic (PV) modules, hard disk drives (HDDs), and wind blades. Four main categories of agents are defined in the ABM: asset owners, service providers (e.g., refurbishers), recyclers, and manufacturers. Two main CE strategies are represented: lifetime extension (through repair or reuse) and recycling. The developed models start by projecting installed capacities and end-of-life (EOL) quantities. Then the theory of planned behavior - a social psychology model explaining behavior adoption based on attitude, peer influence, and costs - is used to model the asset owners' EOL decision (i.e., landfill, recycle or extend the lifetime of the asset). Then, the quantities of assets flowing to the recycler and service provider agents and quantities of materials flowing to manufacturers are computed. Recyclers' economies of scale are dynamically modeled, and the value generated by the CE strategies for the recyclers, service providers, and manufacturers is computed within the model. When data are available, avoided greenhouse gas emissions resulting from the CE strategies adoption are calculated exogenously from the ABM simulations. Results show that with improved used PV modules warranties, the reuse CE strategy adoption increases from 1% to 23% between 2020 and 2050. Similarly, improved standards could enhance HDDs end-users trust in data-wiping - a prerequisite to reuse - leading to a 3-fold increase in the reuse rate and avoid about 5 million tons of CO2 eq by 2050. Regarding wind blades, 5-15 years lifetime extension could reduce EOL blade quantities by 13%. High costs and logistic issues prevent blades from being recycled in greater quantities. One insight from the case studies is the necessity to have mature secondary markets for reuse to be a viable option. Interestingly, PV reuse is limited by the willingness of PV owners to purchase used modules (on the demand side), while HDDs reuse is constrained by the lack of trust toward data-wiping (limiting the supply of used HDDs). The six limits of the CE concepts presented by Korhonen et al. (2018) are finally used to interpret the results. The HDD case study is an exemplary lock-in, where the first accepted practice (shredding) retains most of the market. The PV results illustrate the technical limitation to reuse, as the growing demand cannot be supplied entirely with used PV modules. The wind case study shows the relevance of clearly defining physical flows - what type of waste should wind blades be considered, how should they be transported and landfilled? - a crucial consideration that also applies to PV modules. Finally, the three case studies highlight the relevance of studying a technology's technical, economic, and market material efficiency potentials altogether and the potential benefit of coupling ABM to life cycle assessment.

agent-based modeling↗
DOE OSTI2024

A Practical Solver for Scalar Data Topological Simplification

This paper presents a practical approach for the optimization of topological simplification, a central pre-processing step for the analysis and visualization of scalar data. Given an input scalar field f and a set of “signal” persistence pairs to maintain, our approaches produces an output field g that is close to f and which optimizes (i) the cancellation of “non-signal” pairs, while (ii) preserving the “signal” pairs. In contrast to pre-existing simplification algorithms, our approach is not restricted to persistence pairs involving extrema and can thus address a larger class of topological features, in particular saddle pairs in three-dimensional scalar data. Our approach leverages recent generic persistence optimization frameworks and extends them with tailored accelerations specific to the problem of topological simplification. Extensive experiments report substantial accelerations over these frameworks, thereby making topological simplification optimization practical for real-life datasets. Our approach enables a direct visualization and analysis of the topologically simplified data, e.g., via isosurfaces of simplified topology (fewer components and handles). We apply our approach to the extraction of prominent filament structures in three-dimensional data. Specifically, we show that our pre-simplification of the data leads to practical improvements over standard topological techniques for removing filament loops. Here, we also show how our approach can be used to repair genus defects in surface processing. Finally, we provide a C++ implementation for reproducibility purposes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Significance of Environmental Attributes as Indicators of the Life Cycle Environmental Impacts of Packaging and Food Service Ware

The environmental impacts of packaging and food service ware (FSW) are increasingly the subject of government policy, public discourse, and industry commitments. While some consideration is given to reducing the impacts of packaging across its entire life cycle, most of the focus is on packaging waste or feedstock substitution. Efforts typically focus on specific packaging characteristics, or material attributes, commonly perceived to be environmentally preferable. This article summarizes an extensive meta-review of existing published literature that was performed to determine whether the material attributes recyclability, recycled content, compostability, and biobased, commonly considered to be environmentally beneficial, correlate with lower net environmental impacts across the full life cycle of the packaging and FSW. Seventy-one unique life cycle assessment (LCA) studies that quantify the environmental impacts throughout the entire life cycle of packaging and FSW were analyzed. These studies included over 5000 comparisons for 13 impact categories commonly analyzed in LCA studies. The results from the meta-review identified a number of instances where material attributes do not correlate with environmental benefits for packaging and FSW. Rather, other characteristics such as material choice or mass of the packaging/FSW products can have higher influence in determining life cycle impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Evolution of LiNi 0.5 Mn 0.3 Co 0.2 O 2 Particle Damage from Fast Charging in Optimized, Full Li-Ion Cells

Fast charging batteries are critical to the widespread adoption of electric vehicles to compete with refueling times of combustion-based vehicles. In the near term, adapting current commercial battery technologies to perform better under fast charging conditions through engineering optimizations will greatly expedite the process while exploratory fast-charging electrode materials are being pursued. To do so, the degradation modes in optimized Li-ion batteries need to be completely explored to understand fast charging limits while maintaining a high energy density and a long cycle life. While lithium plating on graphite still remains a challenge, cathode degradation also plays a key role in battery performance. In this work, we used nano- and micro-X-ray computed tomography to characterize the mechanical degradation of LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) in optimized Li-ion batteries cycled at three rates, 1C, 6C, and 9C, and at different stages of cycle life, 225 and 600 cycles. We report despite using a conservative upper voltage cutoff limit aimed to minimize extensive cathode degradation, higher charging rates and increased cycling caused the polycrystalline NMC532 particles to fracture and pulverize, which likely drives cathode capacity fade and contributes to the decrease in overall cell performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Genetic variation associated with adult migration timing in lineages of Steelhead and Chinook Salmon in the Columbia River

Abstract With the discovery of a major effect region (GREB1L, ROCK1) for adult migration timing in genomes of both Chinook Salmon and Steelhead, several subsequent studies have investigated the effect size and distribution of early and late migration alleles among populations in the Columbia River. Here, we synthesize the results of these studies for the major lineages of Chinook Salmon and Steelhead that include highly distinct groups in the interior Columbia River that exhibit atypical life histories from most coastal lineage populations of these two species. Whole‐genome studies with high marker density have provided extensive insight into SNPs most associated with adult migration timing, and suites of markers for each species have been genotyped in large numbers of individuals to further validate phenotypic effects. For Steelhead, the largest phenotypic effect sizes have been observed in the coastal lineage (36% of variation for passage timing at Bonneville Dam; 43% of variation for tributary arrival timing) compared to the inland lineage (7.5% of variation for passage timing at Bonneville Dam; 8.4% of variation for tributary arrival timing) that overwinter in freshwater prior to spawning. For Chinook Salmon, large effect sizes have been observed in all three lineages for multiple adult migration phenotypes (Coastal lineage: percentage of variation of 27.9% for passage timing at Bonneville Dam, 28.7% for arrival timing for spawning; Interior ocean type: percentage of variation of 47.6% for passage timing at Bonneville Dam, 39.6% for tributary arrival timing, 77.9% for arrival timing for spawning; Interior stream type: percentage of variation of 35.3% for passage at Bonneville Dam, 9.8% for tributary arrival timing, 4.7% for arrival timing for spawning). Together, these results have extended our understanding of genetic variation associated with life history diversity in distinct populations of the Columbia River, however, much research remains necessary to determine the causal mechanism for this major effect region on migration timing in these species.

Narum, Shawn R.↗