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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. Here the proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

42 ENGINEERING↗
DOE OSTI2022

Determination of transition metal ions in fossil fuel associated wastewaters using chelation ion chromatography

Here, this study outlines the development and subsequent validation of a method using chelation ion chromatography (CIC) pretreatment followed by traditional ion chromatography (IC) and post column UV/vis detection to measure transition metals in fossil fuel wastewaters, such as oil & gas (O&G) brines and coal mine drainage (CMD) waters. Measurement of transition metals is often an important characterization step in the research of environmental and energy systems. IC represents one way to measure these metals with the advantages of being versatile, simple and relatively low cost compared to other analytical methods. However, high concentrations of alkali and alkaline earth metals present in fossil fuel wastewaters will decrease IC detectability of transition metals in these waters. In this study, a CIC method was developed for the analysis of transition metal ions (Fe 3+ , Cu 2+ , Ni 2+ , Zn 2+ , Co 2+ , Mn 2+ , and Fe 2+ ) in fossil fuel associated wastewaters such as Appalachian CMD and O&G wastewaters from the Permian and Bakken shale basins in the United States. CIC system incorporated an on-line chelator column (e.g., the MetPac CC-1) with high selectivity for transition metals over alkali and alkaline earth metals for salt matrix removal prior to transition metal separation and detection. Additional method developments also included acidifying all samples to 2% v/v HCl and using gradient elution rather than isocratic. The recoverability of transition metals in simple salt solutions commonly found in CMD and brine samples (e.g. NaCl, Na 2 SO 4 , CaCl 2 ) using CIC was evaluated and compared to that using traditional IC. Our results found that the CIC system significantly improved transition metal recoveries for samples in 10,000 mg/L CaCl 2 matrix, reaching 87%-108% recovery for all analytes, as opposed to 2-323% recovery in traditional IC. The limits of detection in this study achieved 10.09 – 161.2 μg/L, comparable to reported values in similar IC studies. The developed method was also verified with certified water samples, resulting in 89% - 111% recoveries in samples with higher analyte concentrations (i.e. >4x the LoDs). The developed method achieved 87% -112% recoveries for most analytes in CMD samples and 72%-138% recoveries for Bakken shale samples, relative to ICP-MS values. Overall, the current IC method can be a very good screening tool for fast and cheap analysis for transition metals at mg/L level, to facilitate selection of samples for more detailed ICP-MS analysis.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Anion and cation co-doping of Na 4 SnS 4 as sodium superionic conductors

Na based all-solid-state batteries are one of the most promising candidates for large-scale electrochemical energy storage owing to their low cost and outstanding safety properties. The key enabler of this technology is solid electrolyte with sufficiently high ionic conductivity at room temperature. In this work, the design, synthesis, characterization and testing of a series of novel fast Na-ion conductors, Na 4-x-y Sn 1-x A x S 4-y X y with aliovalent cation (P 5+ /Sb 5+ ) and anion substitutions (Cl - /Br - ) of the parent compound Na 4 SnS 4 are reported. The doped samples crystalize in a new phase with space group I4 1 /acd and show ionic conductivities that are one to four orders of magnitude higher than that of undoped Na 4 SnS 4 . R. t. conductivity of 0.64 mS cm -1 is achieved in Na 3.7 Sn 0.8 Sb 0.2 S 3.9 Cl 0.1 with a low activation energy of 0.26 eV. Furthermore, Rietveld refinement against high resolution synchrotron X-ray powder diffraction data reveals that the distribution of the doping ions and the resulted Na vacancies are underlying cause of the enhanced conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Novel fabrication technique for high-resolution spherical crystal analyzers using a microporous aluminium base

Modern inelastic X-ray spectrometers employ curved, bent and diced analyzers to capture sufficiently large solid angles of radially emitted scattered radiation emanating from the sample. Fabricating these intricate analyzers, especially when a high energy resolution of a few millielectronvolts is required, is very time-consuming, expensive and often a hit-or-miss affair. A novel fabrication technique is introduced, utilizing a concave-spherical, microporous aluminium base to hold an assembly of a thin glass substrate with a diced crystal wafer bonded to it. Under uniform vacuum forces, the glass substrate is drawn into the aluminium base, achieving the desired bending radius, while dicing of the diffracting crystal layer prevents bending strain from being imposed on the individual crystal pixels. This technique eliminates the need for permanently bonding the crystal assembly to the concave lens, offering the opportunity for correcting figure errors, avoiding long-term degradation of the permanent bond, and making both lens and crystal reusable. Process and material costs are thus substantially decreased. Two analyzers, Si(844) and Ge(337) with intrinsic resolutions of 14.6 meV and 36.5 meV, respectively, were produced in this fashion and characterized in resonant inelastic X-ray scattering (RIXS) measurements. The achieved overall energy resolutions for both analyzers were 29.4 meV for Si(844) and 56.6 meV for Ge(337). Although the RIXS technique is veru sensitive to analyzer imperfections, the analyzers were found to be equal, if not superior, in quality to their traditional, permanently bonded counterparts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Reflective Fiber Temperature Probe Based on Localized Surface Plasmon Resonance towards Low-Cost and Wireless Interrogation

Reflection fiber temperature sensors functionalized with plasmonic nanocomposite material using intensity-based modulation are demonstrated for the first time. Characteristic temperature optical response of the reflective fiber sensor is experimentally tested using Au-incorporated nanocomposite thin films deposited on the fiber tip, and theoretically validated using a thin-film-optic-based optical waveguide model. By optimizing the Au concentration in a dielectric matrix, Au nanoparticles (NP) exhibit a localized surface plasmon resonance (LSPR) absorption band in a visible wavelength that shows a temperature sensitivity ~0.025%/°C as a result of electron–electron and electron–phonon scattering of Au NP and the surrounding matrix. Detailed optical material properties of the on-fiber sensor film are characterized using scanning electron microscopy (SEM) and focused-ion beam (FIB)-assisted transmission electron microscopy (TEM). Airy’s expression of transmission and reflection using complex optical constants of layered media is used to model the reflective optical waveguide. A low-cost wireless interrogator based on a photodiode transimpedance-amplifier (TIA) circuit with a low-pass filter is designed to integrate with the sensor. The converted analog voltage is wirelessly transmitted via 2.4 GHz Serial Peripheral Interface (SPI) protocols. Feasibility is demonstrated for portable, remotely interrogated next-generation fiber optic temperature sensors with future capability for monitoring additional parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Data for A Fluorescence-Based Transient Expression Assay for the Analysis of Upstream Open Reading Frames in Plants

Scripts for the manuscript "A fluorescence-based transient expression assay for the analysis of upstream open reading frames in plant" by Haas et al. Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome- wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild- type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost- efficient alternative to investigate transcript leaders by co- expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO2 assimilation during sun–shade transitions.

Gene Editing↗
DOE OSTI2023

Heat Transfer Characteristics of Particle and Air Flow Through Additively Manufactured Lattice Frame Material Based on Octet-Shape Topology

Particle-to-supercritical carbon dioxide (sCO 2 ) heat exchanger is a critical component in next-generation concentrating solar power (CSP) plants. The inherently low heat transfer between falling particles and sCO 2 imposes a challenge toward economic justification of levelized cost of electricity produced through solar energy. Introduction of integrated porous media with the walls bounding particle flow has the potential to enhance the overall particle-to-sCO 2 heat exchanger performance. Here, this paper presents an experimental study on heat transfer characterization of additively manufactured lattice frame material based on Octet-shaped unit cell with particles and air as working fluids. The lattice structures were additively manufactured in stainless steel (SS) 316L and SS420 (with 40% bronze infiltration) via Binder jetting process, where the lattice porosities were varied between 0.75 and 0.9. The mean particle diameters were varied from 266 μm to 966 μm. The effective thermal conductivity and averaged heat transfer coefficient were determined through steady-state experiments. It was found that the presence of lattice enhances the effective thermal conductivity by 2–4 times when compared to packed bed of particles alone. Furthermore, for gravity-assisted particle flow through lattice panel, significantly high convective heat transfer coefficients ranging from 200 W/m2K to 400 W/m2K were obtained for the range of particle diameters tested. The superior thermal transport properties of Octet-shape-based lattice frame for particle flow makes it a very promising candidate for particle-to-sCO 2 heat exchanger for CSP application.

14 SOLAR ENERGY↗
DOE OSTI2024

Detailed Characterization of Vitrinite-Rich Subbituminous and Bituminous Coals for Utilization in Carbon Fiber Precursor Production

Chemical structures of candidate coals (one subbituminous coal from the Powder River Basin and three bituminous Eastern US coals) were examined for potential low-cost carbon fiber precursor production. Here, the structural evaluation examined the carbon skeleton ( 13 C nuclear magnetic resonance (NMR) and high-resolution transmission electron microscopy (HRTEM)), the heteroatom functionality (X-ray photoelectron spectroscopy (XPS) Fourier transform infrared spectroscopy (FTIR) and NMR), the structural ordering and distribution of PAH sizes (HRTEM), and an estimation of the molecular weight distribution (laser desorption ionization mass spectrometry, LDIMS). The molecular compositional distributions were also evaluated for a mixed solvent extract (atmospheric pressure photoionization, 21 T Fourier transform ion cyclotron resonance mass spectrometry, FT-ICR MS). Significant structural differences existed between the subbituminous and bituminous coals, as expected with coalification (with the bituminous coals having a higher carbon content, lower oxygen content, higher aromaticity values, larger cluster sizes, and so forth). While the bituminous coals were similar in structure (close in rank with Blue Gem being hvAb and the rest being hvBb), structural differences were still evident. Specifically, structural similarities were evident for the average properties of Herrin and Springfield coals: same rank, similar moisture, and volatile matter yields, along with similar aromaticity and carbon and hydrogen content. However, significant structural differences were observed at the molecular level by 21 T FT-ICR MS, which showed that the Springfield coal was structurally more complex. Specifically, 21740, 16931, 30190, and 12982 unique elemental compositions were identified for the Monarch, Herrin, Springfield, and Blue Gem coals, further illustrating the complexity of the coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Na 4 Fe 1.5 Mn 1.5 (PO 4 ) 2 (P 2 O 7 ): A low-cost and earth-abundant cathode for robust sodium storage

The mixed compounds of phosphates and pyrophosphates are attractive cathodes for sodium-ion batteries (SIBs) owing to their robust open framework structure and superior diffusion dynamics. However, most reported mixed phosphate cathodes generally suffer from low operating potential. Herein, we develop a bimetallic Na 4 Fe 1.5 Mn 1.5 (PO 4 ) 2 (P 2 O 7 )/C-rGO (NFMPP/C-rGO) cathode, which possesses two working plateaus at 2.92 and 3.95 V. The obtained NFMPP/C-rGO demonstrates a stable high capacity of over 120 mAh g −1 at 0.1 C. In-situ XRD characterization discloses a solid solution reaction for the Fe 2+/3+ redox couple and a two-phase reaction for the Mn 2+/3+ redox couple. In conclusion, first-principles calculations reveal the migration of Na + in NFMPP has low barriers. This work provides a new, low-cost, earth-abundant, and stable cathode choice for practical SIBs.

Cathode materials↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
DOE OSTI2024

Evaluating the Chemical Reactivity of DFT-Simulated Liquid Water with Hydrated Electrons via the Dual Descriptor

Modeling the various properties of liquid water, particularly its reactivity, has been a longstanding challenge for simulation methods. Recently, ab initio simulations based on density functional theory (DFT) have come to the fore as tenable methods for calculating the properties and reactivity of water, with varying degrees of success for different exchange-correlation functionals. In particular, hybrid-GGA and meta-GGA functionals have been shown to reproduce many of the structural, dynamical, and energetic properties of water to a high degree of accuracy relative to their computational cost. Here, we show that the dual descriptor (DD) measure of nucleophilicity and electrophilicity, which is sometimes used to elucidate organic chemistry reaction mechanisms, can also be used to characterize the reactivity of DFTsimulated liquid water. The DD is especially apt for understanding the reactivity of excess electrons with water as its calculation explicitly involves adding and removing an excess electron from a reference system. We use the DD to explore the reactivity of water simulated using three different DFT functionals: the LDA functional (LDA), a hybrid-GGA functional (PBE0), and a hybrid meta- GGA functional (SCAN0). Using the DD, we show that the SCAN0 functional with the standard 25% Hartree–Fock exchange produces simulated liquid water with many regions that are far more reactive than either PBE0 or LDA. To understand the implications of these highly reactive regions, we then add a strong nucleophile in the form of an excess electron and find that although PBE0 and LDA predict stable hydrated electrons, the excess electron reacts nearly instantaneously with SCAN0 water via proton abstraction to form a hydrogen atom and hydroxide ion. We show that the DD provides the ability to not only predict whether or not liquid water will react with a hydrated electron but also which particular waters will be involved solely from analyzing pure water configurations generated with each functional. We rationalize this result in terms of the known trap-seeking behavior of injected hydrated electrons, which are able to find the most electronegative region in bulk water. These results highlight the utility of the dual descriptor as a fast and interpretable method for investigating condensed-phase reactivity with excess electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals

In spite of numerous scientific and practical applications, there is still no comprehensive theoretical description of the nuclear fission process based solely on protons, neutrons and their interactions. Furthermore, the most advanced simulations of fission are currently carried out within nuclear density functional theory (DFT). In spite of being fully quantum-mechanical and rooted in the theory of nuclear forces, DFT still depends on a dozen or so parameters characterizing the energy functional. Calibrating these parameters on experimental data results in uncertainties that must be quantified for applications. This task is very challenging because of the high computational cost of DFT calculations for fission. In this paper, we use Gaussian processes to build emulators of DFT models in order to quantify and propagate statistical uncertainties of theoretical predictions for a range of nuclear deformations relevant to describing the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Instrumentation and methods for efficient time-resolved X-ray crystallography of biomolecular systems with sub-10 ms time resolution

Time-resolved X-ray crystallography has great promise to illuminate structure–function relations and key steps of enzymatic reactions with atomic resolution. The dominant methods for chemically-initiated reactions require complex instrumentation at the X-ray beamline, significant effort to operate and maintain this instrumentation, and enormous numbers (∼10 5 –10 9 ) of crystals per time point. We describe instrumentation and methods that enable high-throughput time-resolved study of biomolecular systems using standard crystallography sample supports and mail-in X-ray data collection at standard high-throughput cryocrystallography synchrotron beamlines. The instrumentation allows rapid reaction initiation by mixing of crystals and substrate/ligand solution, rapid capture of structural states via thermal quenching with no pre-cooling perturbations, and yields time resolutions in the single-millisecond range, comparable to the best achieved by any non-photo-initiated method in both crystallography and cryo-electron microscopy. Our approach to reaction initiation has the advantages of simplicity, robustness, low cost, adaptability to diverse ligand solutions and small minimum volume requirements, making it well suited to routine laboratory use and to high-throughput screening. We report the detailed characterization of instrument performance, present structures of binding of N -acetylglucosamine to lysozyme at time points from 8 ms to 2 s determined using only one crystal per time point, and discuss additional improvements that will push time resolution toward 1 ms.

Indergaard, John A. (ORCID:000000022367699X)↗
DOE OSTI2022

Material and Design Optimization of Printed Melt Wire Arrays

Recent work conducted by the Advanced Sensors and Instrumentation (ASI) program at Idaho National Laboratory resulted in the establishment of in-house capabilities for fabricating and testing new advanced manufactured sensors for measuring irradiation temperatures inside a nuclear test reactor. Though current methods of real-time temperature monitoring (e.g., thermocouples) can still be used, the complexity of the feedthroughs and attachments needed for collecting real time measurements greatly increases the experiment-related costs. On the other hand, passive monitoring techniques can be used for collecting post irradiation temperature measurements by inferring reactor temperatures, based on the melting points of well-characterized materials (i.e., standard melt wires). However, challenges have arisen due to the limited space available for including instrumentation in experiments. To resolve this issue, the ASI program expanded its temperature detection capabilities to include advance manufactured melt wires for post-irradiation temperature measurements. These melt wires can determine reactor temperatures while also accommodating space limitations in irradiation experiments. To improve performance reliability and enhance melt wire readability following irradiation, FY-22 efforts have focused on optimizing the materials used in the encapsulation and printed melt wire array. This report details the design and fabrication tasks, along with the subsequent x ray computed tomography (XCT) evaluation process. The melt wire array consisted of indium with a melting point of 157°C, indium/silver (96/4 at%) with a melting point of 219°C, and tin with a melting point of 230°C. The encapsulation disc was made of vanadium due to its low activation properties and radiation resistance when deployed in nuclear reactors. Additionally, the melt wire design consisted of a ceramic sublayer (alumina disc) to further enhance the XCT post melting images of the printed melt wires. However, when sealing the vanadium container, all three melt wires melted, reflecting the temperature limitations that must be considered when employing metal containers in the sealing process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Gumby: Quantifying multi-modal model resiliency

With the rise of cheap data and sensors, more use cases are emerging for multi-input models. Research has shown that including multiple data modalities can improve performance, suggesting that deep learning models can successfully learn to leverage complementary information from different modalities. However, this improved predictive power comes with unanticipated costs: additional inputs change model resiliency and expand the threat space for adversarial attacks. We first provide theoretical underpinnings for how adversarial success scales with input dimension. We then characterize the performance of a suite of multispectral deep learning models with different fusion approaches, quantify their relative reliance on different input bands, and evaluate their robustness to naturalistic and adversarial image corruptions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development of Numerical Model of Metal Foam with PCM for the Estimation of Effective Thermal Conductivity

Global warming due to climate change is a threat to humankind. Nuclear energy is one of the promising solutions to reduce fossil fuel usage. Nuclear energy can handle the base load, compensating for the volatility of renewable energy. If nuclear energy could achieve load following capability, the combination with renewable energy would be more suitable. Thermal energy storage (TES) is one of the options for enabling load following of nuclear reactors. The TES makes it possible to store surplus nuclear thermal energy and release it later as needed. In Idaho National Laboratory (INL), a new concept of latent heat TES integrated with high-temperature heat pipe has been proposed and is under development, which is called Heat pipe-Integrated Thermal Battery (HITB). HITB exchanges thermal energy between the reactor system and TES via heat pipe. The heat transferred to TES medium, made of phase change material (PCM), stores energy as sensible heat and/or latent heat. As PCM typically has poor thermal conductivity, however, various heat transfer enhancement techniques are required to achieve a rapid charging cycle. There are many techniques to enhance the heat transfer ability of TES medium such as disk, fin, and metal foam. Among them, metal foam is an appropriate option to enhance the heat transfer because it maximizes the heat transfer area through metal wicks. Metal foam is a lightweight metal structure that has a high porosity of over 0.9. The typical materials for metal foam are Aluminum, Copper, Nickel, and Silicon Carbide (SiC). Metal foam not only enhances heat transfer via conduction but also increases contact surface area. In the HITB design , the metal foam is being considered as one of the options to enhance the heat transfer of TES medium (PCM) [1]. To predict the enhanced thermal performance of TES, one should properly estimate the effective thermal conductivity of metal foam combined with PCM material or calculate heat transfer in distributed model. There are many experimental works that provides effective thermal conductivity of metal foam with various PCM [2,3]. Also, many theoretical models were developed based on the unit cell model of metal foam [4,5]. With a distributed model, on the other hand, detail heat transfer characteristics between metal foam and PCM material can be analyzed considering the geometry or buoyancy effect. However, due to the complex geometry of metal foam pores, the computational cost for three-dimensional modeling highly increases. Therefore, if metal foam structure can be modeled in simple and repetitive design, the computational cost would decrease Among the various metal foam models [2], lattice model is one of the simple and extendable design. The porosity and pores per inch (PPI) can be characterized by the size and spatial distance of lattice structure. If the three-dimensional metal foam model consists of lattice structure could properly estimate the heat transfer, which is characterized by effective thermal conductivity, it would be a good option to assess the thermal performance of metal foam with PCM. In this study, a three-dimensional numerical model was developed to simulate conductive heat transfer between metal foam and PCM. The three-dimensional lattice structure of square pillars was selected as a basic structure of the metal foam. The calculation result was characterized by the effective thermal conductivity of the whole domain. A sensitivity study was conducted for mesh size, domain size, and PPI to check whether the calculation result gives a converged result or not. Lastly, the effective thermal conductivity from the lattice model was compared with existing experimental data to validate the model result

25 ENERGY STORAGE↗
DOE OSTI2021

Enabling Power System Transformation Globally: A System Operator Research Agenda for Bulk Power System Issues

The primary objective of a power system is to safely provide reliable energy services to society at an affordable cost. In many countries, this objective has been supplemented by another: meeting the energy demand with sustainable resources, which has culminated in the energy transition to low-carbon and zero-carbon energy systems. This transition, occurring rapidly around the world, is characterized by the increasing penetration of variable renewable energy (VRE), inverter-based resources (IBRs), and distributed energy resources (DERs).

costs↗
DOE OSTI2025

Velocity- and pressure-based metrics for estimating strike injuries during fish passage through hydro turbines

Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.

Biological characterization↗