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DOE OSTI2023

Probing liquid/liquid interfaces at and away from equilibrium using vibrational sum frequency generation

The self-assembly and transport of species at oil/aqueous interfaces represent key mechanistic steps in processes spanning from liquid extraction to soft-matter neuromorphic electrical devices. While technologically and fundamentally important, there is a notable lack of chemical understanding regarding these buried interfaces due to challenges in differentiating species located at the surface from the nearby bulk phases. In this work, we will describe some of the challenges in probing chemistry at these liquid/liquid interfaces and detail the approaches we have developed using vibrational sum frequency generation to enable studies of these complex interfaces at and away from equilibrium. From these spectroscopic developments, new insight into solvation, ion pairing, aggregation, complexation, and transport will be discussed in the context of solvent extraction chemistry. Notably, we show how the presence of both oil and aqueous phases provides an environment to drive fundamentally different phenomena from what is observed at model air/aqueous interfaces. This difference arises from key differences in solvation and bulk populations that feedback onto the surface to drive emergent and often functional molecular assemblies.

Doughty, Benjamin L↗

DOE OSTI2023

Role of aggregates and microstructure of mixed-ionic–electronic-conductors on charge transport in electrochemical transistors

Synthetic efforts have delivered a library of organic mixed ionic–electronic conductors (OMIECs) with high performance in electrochemical transistors. The most promising materials are redox-active conjugated polymers with hydrophilic side chains that reach high transconductances in aqueous electrolytes due to volumetric electrochemical charging. Current approaches to improve transconductance and device stability focus mostly on materials chemistry including backbone and side chain design. However, other parameters such as the initial microstructure and microstructural rearrangements during electrochemical charging are equally important and are influenced by backbone and side chain chemistry. In this study, we employ a polymer system to investigate the fundamental electrochemical charging mechanisms of OMIECs. We couple in situ electronic charge transport measurements and spectroelectrochemistry with ex situ X-ray scattering electrochemical charging experiments and find that polymer chains planarize during electrochemical charging. Our work shows that the most effective conductivity modulation is related to electrochemical accessibility of well-ordered, interconnected aggregates that host high mobility electronic charge carriers. Electrochemical stress cycling induces microstructural changes, but we find that these aggregates can largely maintain order, providing insights on the structural stability and reversibility of electrochemical charging in these systems. Finally, this work shows the importance of material design for creating OMIECs that undergo structural rearrangements to accommodate ions and electronic charge carriers during which percolating networks are formed for efficient electronic charge transport.

36 MATERIALS SCIENCE↗

NASA NTRS2012

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗

NASA NTRS2000

Thermocapillary Flow and Aggregation of Bubbles on a Solid Wall

During the electrolytic evolution of oxygen bubbles forming on a vertically oriented transparent tin oxide electrode, bubbles were found to be mutually attractive. The mechanism of the aggregation had never been explained satisfactorily until Guelcher et al. attributed it to thermocapillary flow. The gradient of surface tension of the liquid at the bubble's surface, which was established because of reaction heat and ohmic heat loss at the electrode wall, drives flow of the liquid adjacent to each bubble; the bubble "pumps" fluid along its surface away from the wall. Fluid flows toward the bubble to conserve mass and entrains nearby bubbles in the flow pattern. The same logic would apply when two bubbles of equal size are adjacent to each other on a warm wall. Each bubble drives thermocapillary flow and hence entrains the other in its flow pattern, which drives the aggregation. Our objective here is to perform experiments where the temperature gradient at the wall is well known and controlled. The theory can be quantitatively tested by studying aggregation of bubble pairs of equal size, and by varying system parameters such as temperature gradient, bubble size and fluid viscosity. The results are then compared with the theory in a quantitatively rigorous manner. We demonstrate that the theory without adjustable parameters is capable of quantitatively modeling the rate of aggregation of two bubbles. The equations governing the thermocapillary flow around a single stationary bubble on a heated or cooled wall in a semi-infinite domain were solved. Both Reynolds number and Marangoni number were much less than unity. The critical result is that liquid in the vicinity of a warm wall flows toward a stationary collector bubble. Consequently the thermocapillary flow around the stationary bubble entrains another bubble toward itself. The bubbles undergo hindered translation parallel to the wall with velocity U while the fluid flow field is described with u. Two velocities were equated by using a wall hindrance parameter q: U = qu [1] which shows the velocity of bubble is proportional to the entraining velocity. The hindrance parameter q can experimentally be measured independently. q can also be calculated by solving the equations of motion for a bubble translating parallel to a solid wall. The experimental cell is cylindrical with an ID of 10 cm and consists of a 1 cm deep main cell filled with silicone oil and flanked by two thermal reservoirs. The upper thermal reservoir was heated and the lower thermal reservoir was cooled so that the bubbles aggregate. Two types of silicone oil (eta = 0.02 and 0.50 Pa s) were used. Two equal sized air bubbles were injected into the cell with a syringe. The center-to-center distance of bubbles was observed through a microscope. Bubble radius ranged from 0.40 mm to 0.65 mm and the temperature gradients along with the cell ranged from 1400 to 5000 K/m. The bubbles aggregated when heat flows from the wall to the fluid. The velocities of bubbles were in the range of 1 - 10 microns/s. The separation r decreased more quickly when the temperature gradient was higher, bubble size was larger, and the oil viscosity was lower. r decreased more rapidly as the bubbles approached each other. Dimensionless time was arbitrarily set to be zero when the dimensionless center-to-center distance between the bubbles was 4. All the bubble trajectories fall onto one line, especially in the range of dimensionless distance from 4 to 3. This means the relative movement of the bubble pair is proportional to the temperature gradient and bubble size and it is inversely proportional to the viscosity of the oil. This result strongly suggests that the thermocapillary flow-based aggregation mechanism is correct. A value of q can be estimated by fitting the scaled data to Eq. [1]. A best fit value of q was obtained as q = 0.26 with a standard deviation of 0.03. Independent experimental results for q for a 0.5 mm radius bubble, give values of q in the range 0.11 to 0.23. The value of q obtained from solving the equations of motion reveals q has values in the range 0.23 - 0.30. Since the full scale of possible values of q is zero to one, the maximum deviation of independently determined values of q from the best fit value was 15% of this full scale. Thus reasonable quantitative agreement between theory and experiment has been obtained.

Kasumi, Hiroki↗

DOE OSTI2022

Data from: Land-based climate solutions for the United States

Meeting end-of-century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature-based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature-based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the U.S. that illustrates the benefits of combining approaches. We assign a portion of non-forested former cropland to bioenergy sufficient to meet projected mid-century transportation needs, with the remainder assigned to nature-based solutions such as reforestation. Bottom-up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost-effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of reforestation. Results show a conservative end-of-century mitigation capacity of 110 (57 – 178) Gt CO2e for the U.S., ~50% higher than existing estimates that prioritize nature-based or bioenergy solutions separately. Further research is needed to shrink uncertainties but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

09 BIOMASS FUELS↗

DOE OSTI2021

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗

NASA NTRS2011

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Liu, Yi↗

NASA NTRS2016

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗

DOE OSTI2021

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

aggregates↗

DOE OSTI2021

Introducing Low-Cost Pyrazine Unit into Terpolymer Enables High-Performance Polymer Solar Cells with Efficiency of 18.23%

Recently, a random ternary copolymerization strategy has become a promising and efficient approach to develop high-performance polymer donors for polymer solar cells (PSCs). Here, in this study, a low-cost electron-withdrawing unit, 2,5-bis(4-(2-ethylhexyl)thiophen-2-yl)pyrazine (PZ-T), is incorporated into the polymer backbone of PM6 as the third component, and three D-A 1 -D-A 2 type terpolymers PMZ-10, PMZ-20, and PMZ-30 are synthesized by the random copolymerization strategy, with the PZ-T proportion of 10%, 20%, and 30%, respectively. The terpolymers exhibit downshifted highest occupied molecular orbital energy levels than PM6, which is beneficial for obtaining higher open-circuit voltage (V oc ) of the PSCs with the polymer as a donor. Importantly, the PSCs based on PMZ-10:Y6 demonstrate efficient exciton dissociation, higher and balanced electron/hole mobilities, desirable aggregation, and high power conversion efficiency of 18.23%, which is the highest efficiency among the terpolymer-based PSCs so far. The results indicate that the ternary copolymerization strategy with PZ-T as the second A-unit is an efficient approach to further improve the photovoltaic performance and reduce the synthetic cost of the D-A copolymer donors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗

DOE OSTI2023

De novo design of small beta barrel proteins

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

elm-diagnostics

elm-diagnostics is a Python package for computing diagnostic analyses and visualizations for the E3SM Land Model (ELM) component and is meant to support new feature development in ELM. The tool reads model history files and performs quantitative analyses including budget-closure checking, variable transformations, temporal aggregations, and statistical summaries to support model evaluation, validation, and scientific interpretation. The framework is designed for extensibility, with modular architecture enabling straightforward addition of new diagnostic methods, derived variables, analysis types, visualization approaches, and model-specific adaptations

Hoffman, Matt [Los Alamos National Laboratory]↗

NASA NTRSDate not supplied

Application of Variable Data Rate (VDR) Towards Channel Optimization

Recognizing the vagaries of channel impediments, one way to optimize aggregate channel information throughput is to maintain a constant symbol rate but vary the modulation scheme and/or the codec rate. The CCSDS VCM and ACM standards promulgation relies upon this kind of an approach. We offer a considerably simpler alternative for spacecraft that are not parked in geo-stationary orbit, one that can rely upon conventional spacecraft housekeeping schedules to change spacecraft and ground operations and will minimize the possibility of requiring any spacecraft hardware accommodations to incorporate. We suggest the use of varying the physical symbol rate within the channel to both initiate acquisition earlier in a pass and retain the link longer as the pass tends toward loss of signal. There is nothing new in what we propose, just a recognition of what has been successful in the past and employed in multiple missions. Integrating over the periodicity of orbit repetition, we shall show that any link that is dependent primarily on a varying range from spacecraft to ground only requires a maximum of five symbol rate transitions in order to optimize total information throughput. By applying these symbol rate transitions using almost rigid rules, we anticipate doubling the information throughput for conventional LEO sun-synchronous orbits. We provide other examples as well.

variable data rate↗

NASA NTRSDate not supplied

Application of Variable Data Rate (VDR) Towards Channel Optimization

Variable Data Rate↗

DOE OSTI2021

Evaluation of a Surface Spill Operation to Return Adult Steelhead Overshoots Downstream of McNary Dam

This study, funded by the U.S. Army Corps of Engineers (USACE), was conducted by the Pacific Northwest National Laboratory to evaluate the efficacy of operating one Top Spill Weir (TSW) at McNary Dam outside the normal TSW operation dates for juvenile salmon passage. Of interest is whether the TSW is an effective downstream passage route for adult steelhead overshoots. Overshoots are fish which, having passed upstream at McNary Dam, must pass downstream to return to their natal stream to spawn. This report covers Fall (2019) and Spring (2020) study periods. The study design arranged the available 24 hours of TSW spill per week into weekly blocks with sub-blocks differentiated into day and night operations with TSW discharge periods of 4- and 8-hours duration. Hydroacoustic techniques were used to sample adult fish passage at the TSW and at turbine units 1 and 10. The experimental design contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units, were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. It is worthwhile to note that the operations data obtained for the fall study period had a greater than expected number of gaps and apparent anomalies that we believe were a result of how the data were aggregated. These problems are not particularly problematic for the present study, because the available data still provide a good indication of whether the TSW was operating at each point in time. TSW flows in both fall and spring data sets were able to be cleaned up using the established relationship between forebay elevation and TSW discharge rate. Additional cleanup of operations data would be needed, however, if more quantitative evaluation of dam-wide flow and passage relationships were needed. This study contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. Spring adult steelhead passage numbers estimated using hydroacoustics were notably lower than during the fall study period, and that was consistent with our analysis of PIT tagged fish likely to be in the vicinity during each study period. Detections of fish in BlueView sampling areas upstream of the TSW and powerhouse were not correlated with detections of fish passing hydroacoustic sampling areas, which suggests that fish approaching the face of the dam can move around the forebay before passing. Other fish detected in the forebay in large numbers, such as shad, were able to be filtered out of steelhead passage counts and did not appear to be influencing hydroacoustic passage rate estimates. A pulse of passage at the initial TSW opening was weakly evident, but trends across 4- and 8-hour operational periods did not show a distinct decline in passage over time as TSW operation continued. Our findings do not indicate a reason to choose one 8-hour period over two 4-hour periods, or vice versa. This suggests that the duration of spill periods can be chosen based on operational or other considerations. Passage rates were consistently higher during the daytime TSW discharge periods, relative to nighttime TSW discharge periods. The experimental design of the current study used start times near dawn for day periods and near dusk for night periods.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Aggregated Distributed Energy Resources in 2024: The Fundamentals

This report builds upon existing literature and leading examples of ADER pricing and programs in practice to equip commissioners and staff at Public Utilities Commissions (PUCs) and State Energy Offices with the fundamentals of ADER grid services, valuation options, and approaches to compensation. Examples, active debates, and opportunities for further reading are highlighted throughout the document for readers to explore. This report does not seek to outline a specific objective for ADERs in the electricity system nor does it recommend any specific policies for ADERs—it seeks to provide helpful information to inform policymakers’ own ADER strategies and priorities.

24 POWER TRANSMISSION AND DISTRIBUTION↗