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At least 271 records · Page 15

Numerical thermal analyses of heat exchangers for the stirling engine application

The Regenerator, Cooler and Heater for the NASA Space Power Research Engine (SPRE) have been analyzed in detail for laminar, incompressible and oscillatory flow conditions. Each component has been analyzed independently and in detail with the regenerator being modeled as two-parallel-plates channel with a solid wall. The ends of the channel are exposed to two reservoir maintained at different temperature thus providing an axial temperature gradient along the channel. The cooler and heater components have been modeled as circular pipes with isothermal walls. Two different types of thermal boundary conditions have been investigated for the cooler and heater, namely, symmetric and asymmetric temperature inflow. In symmetric temperature inflow the flow enters the channel with the same temperature in throughout the velocity cycle whereas, in asymmetric temperature inflow the flow enters with a different temperature in each half cycle. The study was conducted over a wide range of Maximum Reynolds number (RE(max) varying from 75 to 60000, Valensi number (Va) from 2.5 to 800, and relative amplitude of fluid displacement (A(sub r) from 0.357 to 1.34. A two dimensional Finite volume method based on the SIMPLE algorithm was used to solve the governing partial differential equations. Post processing programs were developed to effectively describe the heat transfer mechanism under oscillatory flows. The computer code was validated by comparing with existing analytical solutions for oscillating flows. The thermal field have been studied with the help of temperature contour and three dimensional plots. The instantaneous friction factor, wall heat flux and heat transfer coefficient have been examined. It has been concluded that in general, the frictional factor and heat transfer coefficient are higher under oscillatory flow conditions when the Valensi number is high. Also, the thermal efficiency decreases for lower A(r) values. Further, the usual steady state definition for the heat transfer coefficient does not seem to be valid.

Kannapareddy, Mohan Raj↗

Fundamental Understanding of “Fresh” Lithium Nucleation and Growth in Sulfide-Based Anode-Free Solid-State Batteries: Effects of Substrate, Current Density, and Li + Supply

Understanding the electrochemical extraction and deposition of lithium (Li) from cathode is crucial for advancing anode-free solid-state batteries (AFSSBs). Herein, cryo-transmission electron microscopy (cryo-TEM) and electrochemical studies are employed to investigate how current collector surface properties, current densities, and cathode loadings influence the morphology of fresh electrochemically deposited Li and the electrochemical performance in sulfide-based AFSSBs. Cryo-TEM reveals that Cu current collectors induce irregular, dendritic Li deposits due to their lithiophobic nature and reactivity with Li 5.4 PS 4.4 Cl 1.6 (LPSC), while Ni and Au facilitate more uniform, planar-like Li growth. The morphology of the deposited Li also depends on current density: higher rates produce smaller, porous particles versus larger, denser deposits at lower rates. Importantly, for the first time, we discovered that low cathode loadings lead to poor cycling stability due to insufficient Li + supply for complete anode coverage, contrary to conventional solid-state batteries with preloaded Li metal anodes. This finding establishes a design principle where adequate cathode Li + reservoirs are essential for anode interface stability in AFSSBs. Overall, this work elucidates the interplayed effect of current collectors, current densities, and cathode loadings on Li morphology and cycle stability, offering fundamental insights into cathode-derived Li behavior and practical guidelines for optimizing AFSSBs performance through nucleation control and interface engineering.

25 ENERGY STORAGE↗

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗

An organic electrochemical transistor for multi-modal sensing, memory and processing

By integrating sensing, memory and processing functionalities, biological nervous systems are energy and area efficient. Emulating such capabilities in artificial systems is, however, challenging and is limited by the device heterogeneity of sensing and processing cores. Here we report an organic electrochemical transistor capable of sensing, memory and processing. The device has a vertical traverse architecture and a crystalline–amorphous channel that can be selectively doped by ions to enable two reconfigurable modes: a volatile receptor and a non-volatile synapse. As a volatile receptor, the device is capable of multi-modal sensing and is responsive to stimuli such as ions and light. As a non-volatile synapse, it is capable of 10-bit analogue states, low switching stochasticity and good state retention. We also show that the homogeneous integration of the devices could provide functions such as conditioned reflexes and could be used for real-time cardiac disease diagnoses via reservoir computing.

97 MATHEMATICS AND COMPUTING↗

Water-enhanced bifunctional metal-acid catalyst for C=C bond hydrogenation

Water-assisted proton shuttling can promote hydrogenation of polar functional groups, and it is generally believed that such an effect can be hardly applied to hydrogenation of C═C bonds due to the latter's weak interaction with water. Here, we report density functional theory calculations and metadynamics simulations, through which we show a dynamic bifunctional metal–acid site that can be transformed, when interacting with water, into an active configuration for unexpected water-enhanced proton shuttling to C═C bonds. In particular, we investigated B(OH)3 anchored to a Ni catalyst for hydrogenation of cyclohexene in an organic solvent, which showed in experiments an increased rate by 100 times when adding a small amount of water. Metadynamics simulations suggest that a B(OH)3–H2O cluster can form on Ni(111), which promotes the proton transfer in the first hydrogenation step, while the second hydrogenation is still driven by metal-mediated direct H-transfer. The recovery process of B(OH)3–H2O also involves a proton shuttling step. We find that the boric species on the surface serves as an electron reservoir and carries the negative charge to balance the positive charge in the proton transfer steps. This work thus provides fundamental insights into this dynamic transformation process of the metal–acid interface, which can in principle be applied to many other bifunctional systems for hydrogenating non-polar unsaturated groups by engineering the interfacial charge separation.

Sun, Shoutian↗

Engineering model 8-cm thruster subsystem

An Engineering Model (EM) 8 cm Ion Thruster Propulsion Subsystem was developed for operation at a thrust level 5 mN (1.1 mlb) at a specific impulse 1 sub sp = 2667 sec with a total system input power P sub in = 165 W. The system dry mass is 15 kg with a mercury-propellant-reservoir capacity of 8.75 kg permitting uninterrupted operation for about 12,500 hr. The subsystem can be started from a dormant condition in a time less than or equal to 15 min. The thruster has a design lifetime of 20,000 hr with 10,000 startup cycles. A gimbal unit is included to provide a thrust vector deflection capability of + or - 10 degrees in any direction from the zero position. The EM subsystem development program included thruster optimization, power-supply circuit optimization and flight packaging, subsystem integration, and subsystem acceptance testing including a cyclic test of the total propulsion package.

Herron, B. G.↗

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

Optofluidic memory and self-induced nonlinear optical phase change for reservoir computing in silicon photonics

Nanophotonics allows to employ light-matter interaction to induce nonlinear optical effects and realize non-conventional memory and computation capabilities, however to date, light-liquid interaction was not considered as a potential mechanism to achieve computation on a nanoscale. Here, we experimentally demonstrate self-induced phase change effect which relies on the coupling between geometric changes of thin liquid film to optical properties of photonic waveguide modes, and then employ it for neuromorphic computing. In our optofluidic silicon photonics system we utilize thermocapillary-based deformation of thin liquid film capable to induce nonlinear effect which is more than one order of magnitude higher compared to the more traditional heat-based thermo-optical effect, and allowing operation as a nonlinear actuator and memory element, both residing at the same compact spatial region. The resulting dynamics allows to implement Reservoir Computing at spatial region which is approximately five orders of magnitude smaller compared to state-of-the-art experimental liquid-based systems.

42 ENGINEERING↗

Impact of Polymer Rheology on Gel Treatment Performance of Horizontal Wells with Severe Channeling

Summary Gel treatment has been a cost-effective method to control the conformance of a reservoir with severe heterogeneity problems. The water channels in such reservoirs can be classified as open fractures or high permeability porous media with pore-throat network. Many simulation studies have been conducted to discuss gel treatment performance for conformance control. However, nobody considered the polymer rheology difference in open fractures and porous media in simulation. Previous simulation studies also ignored the residual resistance factor as a function of rock permeability rather than a constant parameter. In this study, a conceptual simulation model was established to simulate the linear flow system for the reservoir with horizontal wells considering the two factors mentioned above. The results demonstrate that the gel treatment always provides the better placement results in the open fracture type channel than pore-throat network type channel. Moreover, it is very necessary to consider residual resistance factor as a function of permeability, which is based on the experimental results and can provide much greater plugging efficiency in the higher permeable channels than constant residual resistance factor. Sensitivity analysis studies and multifactor analysis indicate that increasing oil viscosity and permeability ratio has a strong positive influence on conformance control results, which indicate in-situ gel treatment can be better applied in heavy or viscous oil reservoirs with fracture-like channels. Besides, the results also indicate that in reservoirs with severe channeling problem where channel velocity was high, the differences of gelant placement and profile improvement in models with two different types of channels could be enlarged greatly.

Engineering↗

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗

Atmospheric cloud physics laboratory project study

Engineering studies were performed for the Zero-G Cloud Physics Experiment liquid cooling and air pressure control systems. A total of four concepts for the liquid cooling system was evaluated, two of which were found to closely approach the systems requirements. Thermal insulation requirements, system hardware, and control sensor locations were established. The reservoir sizes and initial temperatures were defined as well as system power requirements. In the study of the pressure control system, fluid analyses by the Atmospheric Cloud Physics Laboratory were performed to determine flow characteristics of various orifice sizes, vacuum pump adequacy, and control systems performance. System parameters predicted in these analyses as a function of time include the following for various orifice sizes: (1) chamber and vacuum pump mass flow rates, (2) the number of valve openings or closures, (3) the maximum cloud chamber pressure deviation from the allowable, and (4) cloud chamber and accumulator pressure.

Schultz, W. E.↗

Engineering Model 8-cm Thruster System

Development of an Engineering Model 8-cm Mercury Ion Thruster System for Satellite Control has been successfully completed. This system operates at a specific impulse in excess of 2600 sec, produces a thrust of 5 mN with a total input power of 165 W; it has a dry mass of 16.6 kg and a mercury-propellant-reservoir capacity of 8.75 kg. This paper summarizes the development work, the system characteristics and performance, and the testing undertaken to verify the design.

Herron, B. G.↗

Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP) User’s Manual

This user’s manual describes version 1.0 of the SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP)) tool and provides instructions for use. The purpose of the SHASTA-HELP tool is to integrate the suite of tools developed by the SHASTA research team in a web-based framework for ease of access and more advanced, integrated analysis. This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

08 HYDROGEN↗

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

A Project Lifetime Approach to the Management of Induced Seismicity Risk at Geologic Carbon Storage Sites

The geologic storage of carbon dioxide (CO 2 ) is one method that can help reduce atmospheric CO 2 by sequestering it into the subsurface. Large-scale deployment of geologic carbon storage, however, may be accompanied by induced seismicity. We present a project lifetime approach to address the induced seismicity risk at these geologic storage sites. This approach encompasses both technical and nontechnical stakeholder issues related to induced seismicity and spans the time period from the initial consideration phase to postclosure. These recommendations are envisioned to serve as general guidelines, setting expectations for operators, regulators, and the public. They contain a set of seven actionable focus areas, the purpose of which are to deal proactively with induced seismicity issues. Although each geologic carbon storage site will be unique and will require a custom approach, these general best practice recommendations can be used as a starting point to any site-specific plan for how to systematically evaluate, communicate about, and mitigate induced seismicity at a particular reservoir.

58 GEOSCIENCES↗

Evaluation of Howard A. Hanson Dam Juvenile Fish Passage and Survival Study: Downstream Passage and Survival (Acoustic Telemetry) (Task Final Report)

The Downstream Passage and Survival (Acoustic Telemetry) task was one of several tasks for the Evaluation of Howard A. Hanson Dam (HAHD) Juvenile Fish Passage and Survival study. For this task, a juvenile fish passage and survival study was conducted at HAHD from March 10, 2024 through June 27, 2024 for arrays in the HAHD Reservoir and Green River, and through July 9, 2024 for the arrays in the Duwamish River. Fish releases occurred over four times from March through May. Active tag (acoustic telemetry) technology was used to provide biological baseline information for the passage and survival of juvenile Puget Sound (PS) Chinook salmon (Oncorhynchus tshawytscha). Results will be used by biologists, engineers, resource managers, and regional decision-makers to inform the engineering design of the new fish passage facility (FPF) at HAHD. However, hatchery sub-yearling PS Chinook salmon of the appropriate size for tag implantation during the study period (> 95 mm in fork length, Geist et al. 2018) were unavailable. Therefore, yearling Coho salmon (O. kisutch) were used as a surrogate species for this acoustic telemetry study.

13 HYDRO ENERGY↗

X-15 hydraulic-system development

Despite the exacting requirements and conditions of the X-15 including much higher temperature, high horsepower, and extreme vibration and duty cycles, the hydraulic flight control systems compare favorably, weightwise, with preceding models. Although some items, such as the pumps, are heavier, the total system, excluding actuators, weighs approximately 195 pounds as compared with 196 pounds for the F-107A airplane. Use of the new piggy-back pump, with its low flow during most of the operating time, also permitted a reduction in fluid capacity of the hydraulic reservoirs and the total systems, even though the volume of some of the actuators is quite large. This effected a considerable saving in fluid weight. Complete ground-support equipment is available and this equipment, as well as the airplane systems, contains means for complete 5- to 15- micron filtration under controlled temperature conditions. By use of advanced engineering techniques and extensive laboratory testing, it has been possible to provide a sound, lightweight hydraulic system for this advanced, high-performance airplane. (author)

Culleton, R J↗

Evaluation of Foster Dam Juvenile Fish Passage, 2018 (Final Report)

This report presents the results of a fish passage study conducted by the Pacific Northwest National Laboratory (PNNL) for the U.S. Army Corps of Engineers Portland District (USACE) at Foster Dam (herein, Foster) during the spring (March–June) and fall (October–December) of 2018. The goal of this study was to provide biologists, engineers, resource managers, and regional decision-makers with information about passage of juvenile Chinook salmon and juvenile steelhead (or appropriate surrogates) through specific routes at Foster. The results of this study are intended to help facilitate decision-making regarding long-term measures for enhancing salmonid passage at Foster. Radio telemetry (RT) methods were instituted at low winter reservoir forebay elevation (low pool, 613 ft mean sea level (msl); spring 2018 and fall 2018) and high summer reservoir forebay elevation (high pool, 635 ft msl; late spring and early summer 2018) to accomplish the following objectives: I. Estimate the following passage metrics under typical operations (i.e., baseline conditions): a. Overall dam-passage survival and survival specific to each route of dam passage, calculated using two different methods: i. Cormack-Jolly-Seber (CJS) estimate: Probability of survival from dam passage to detection at the Primary Array, 19 river kilometers (rkm) downstream of Foster. ii. Virtual Release/Dead Fish Correction (ViRDCt) estimate: Corrects the bias that occurs from misidentifying fish that did not survive dam-passage as alive at the tailrace Egress Array, allowing an estimate of survival from dam passage to this array, 2.5 rkm downstream of Foster. b. Route distribution (passage proportions by route; also known as “passage efficiencies”). c. Efficiency metrics i. Dam-passage efficiency (DPE), the proportion of total fish passing the dam relative to the number of total fish detected in the near forebay of the dam and therefore available to pass. ii. Fish passage efficiency (FPE), the proportion of fish passing via a non-turbine route, relative to the number of total fish in the near forebay and available to pass. iii. Fish weir efficiency (FWE) and spill bay efficiency (SBE), the proportion of fish passing the weir or spill bays, respectively, relative to the total number of fish passing the dam. d. Reservoir residency time (time elapsed between release into reservoir and dam passage) and travel times through the system. II. Estimate efficiency and effectiveness of the new fish weir, compared to the turbines and the spillway. III. Under alternative operations, compare passage through each route (turbines, weir, spillway) using a block/treatment (on/off) design similar to the 2015 and 2016 studies. IV. Estimate efficiency of the new fish weir operating at a low level of discharge (< 500 cfs) and a high level of discharge (= 500 cfs), as well as dam passage survival at each weir discharge level. V. Evaluate survival and behavior of hatchery summer steelhead to wild surrogate winter steelhead for potential use of summer steelhead as a surrogate species winter steelhead. VI. Evaluate juvenile passage rates in the auxiliary water supply (AWS), forebay water supply (FWS), and hatchery water supply (HWS).

54 ENVIRONMENTAL SCIENCES↗