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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mechanical, corrosion, and wear properties of biomedical Ti–Zr–Nb–Ta–Mo high entropy alloys

The microstructures, mechanical, corrosion, and wear behaviors of the Ti x ZrNbTaMo (x = 0.5, 1, 1.5, and 2, molar ratio) high entropy alloys (HEAs) were studied in this work. It was found that the Ti–Zr–Nb–Ta–Mo HEAs showed a dendrite structure with two body-centered-cubic (BCC) solid solution phases. The Ti 0.5 ZrNbTaMo HEA exhibited a high hardness of about 500 HV, high compressive strength approaching 2,600 MPa, and large plastic strain of over 30%. Furthermore, the highly-protective oxide films formed on the surface of Ti–Zr–Nb–Ta–Mo HEAs in the phosphate buffer saline (PBS) solution, which resulted in the high corrosion resistance of the HEAs. The Ti–Zr–Nb–Ta–Mo HEAs exhibited the greater dry- and wet-wear resistance than that of the traditional biomedical Ti6Al4V alloy. The results also indicated that with the decrease in the Ti content, the wear resistance of the Ti–Zr–Nb–Ta–Mo HEAs in the PBS solution improved. Finally, the Ti 0.5 ZrNbTaMo alloy presented the highest corrosive wear resistance among the four HEAs owing to its combination of good mechanical properties and high chemical stability.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A slip-spring framework to study relaxation dynamics of entangled wormlike micelles with kinetic Monte Carlo algorithm

Hypothesis: Wormlike micelles (WLMs) formed due to the self-assembly of amphiphiles in aqueous solution have similar viscoelastic properties as polymers. Owing to this similarity, in this work, it is postulated that kinetic Monte Carlo (kMC) sampling of slip-springs dynamics, which is able to model the rheology of polymers, can also be extended to capture the relaxation dynamics of WLMs. Theory: The proposed modeling framework considers the following relaxation mechanisms: reptation, union-scission, and constraint release. Specifically, each of these relaxation mechanisms is simulated as separate kMC events that capture the relaxation dynamics while considering the living nature of WLMs within the slip-spring framework. As a case study, the model is implemented to a system of sodium oleate and sodium chloride to predict the linear rheology and the characteristic relaxation times associated with the individual relaxation mechanisms at different pH and salt concentrations. Findings: Linear rheology predictions were found to be in good agreement with experimental data. Furthermore, the calculated relaxation times highlighted that reptation contributed to a continuous increase in viscosity while union-scission contributed to the decrease in viscosity of WLM solutions at a higher salinity and pH. Finally, this manifests the proposed model’s capability to provide insights into the key processes governing WLM’s rheology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Bioinspired nonwetting surfaces for corrosion inhibition over a range of temperature and corrosivity

Applications of superhydrophobic (SHS) and lubricant infused surfaces (LIS) involve exposure to corrosive environments from the acidic to the basic, at a range of temperatures, that are not fully characterized. Here, we present for the first time a multifactorial study of the effects of surface fabrication method, surface modification, surface functionalization time, temperature and pH of the immersion medium on the corrosion performance of nonwetting copper surfaces. Bioinspired SHS and LIS fabricated using facile methods of etching and electrodeposition are systematically assessed using potentiodynamic polarization measurements for their corrosion resistance in saline solution (pH ≈7) over a temperature range 23–85°C. SHS and LIS are shown to exhibit diminished corrosion rate, by up to two orders of magnitude, compared to bare copper surface. An Arrhenius model is developed for the first time, describing the temperature- dependent corrosion rate of SHS and LIS. Electrochemical impedance spectroscopy is used to show that corrosion resistance of LIS is larger by three orders of magnitude in extremely acidic (pH = 1) and by an order magnitude in extremely alkaline (pH = 14) media compared to bare copper surface. Etched LIS are generally more resistant to corrosion compared to SHS at all temperatures with excellent microstructural durability.

42 ENGINEERING↗
DOE OSTI2022

A gradient-based deep neural network model for simulating multiphase flow in porous media

We report simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO 2 storage sites, where CO 2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

42 ENGINEERING↗
DOE OSTI2021

Geochemical and microbial characteristics of seepage water and mineral precipitates in a radwaste disposal facility impacted by seawater intrusion and high alkalinity

The construction of an underground facility can dramatically change the quality, flow direction, and level of groundwater. It may also impact subsurface microbial composition and activity. Groundwater quality was monitored over eight years in two observational wells near an underground disposal facility on the east coast of South Korea. The results showed dramatic increases in dissolved ions such as O 2 , Na, Ca, Mg, and SO 4 during facility construction. Seepage water samples downgradient from the silos and tunnels, and precipitates deposited along the seepage water flow path were collected to determine the impact inside the disposal facility. X-ray analysis (powder X-ray diffraction (pXRD) and X-ray absorption fine structure (XAFS)) were used to characterize the mineral precipitates. Microbial community composition was determined by 16S rRNA gene sequencing. The seepage water composition was of two types: Ca-Cl and Ca-Na-HCO 3 . The ratio of Cl and δ 18 O showed that the Ca-Cl type seepage water was influenced by groundwater mixed with seawater ranging from 2.7% to 15.1%. Various sulfate-reducing bacteria were identified in the Ca-Cl type seepage water, exhibiting relatively high sulfate content from seawater intrusion. Samples from the Ca-Na-HCO 3 type seepage water had an extremely high pH (>10) and abundance of Hydrogenophaga. The precipitates observed along the flow path of the seepage water included calcite, ferrihydrite, green rust, and siderite, depending on seepage water chemistry and microbial activity. This study suggests that the construction of underground structures creates distinct, localized geochemical conditions (e.g., high alkalinity, high salinity, and oxic conditions), which may impact microbial communities. These biogeochemical changes may have undesirable large-scale impacts such as water pump clogging. Overall, an understanding of the process and long-term monitoring are essential to assess the safety of underground facilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A robust deep learning workflow to predict multiphase flow behavior during geological C O 2 sequestration injection and Post-Injection periods

Simulation of multiphase flow in porous media is essential to manage the geologic CO 2 sequestration (GCS) process, and physics-based simulation approaches usually take prohibitively high computational cost due to the nonlinearity of the coupled physics. This paper contributes to the development and evaluation of a deep learning workflow that accurately and efficiently predicts the temporal-spatial evolution of pressure and CO 2 plumes during injection and post-injection periods of GCS operations. Based on a Fourier Neural Operator, the deep learning workflow takes input variables or features including rock properties, well operational controls and time steps, and predicts the state variables of pressure and CO 2 saturation. To further improve the predictive fidelity, separate deep learning models are trained for CO 2 injection and post-injection periods due to the difference in primary driving force of fluid flow and transport during these two phases. We also explore different combinations of features to predict the state variables. We use a realistic example of CO 2 injection and storage in a 3D heterogeneous saline aquifer, and apply the deep learning workflow that is trained from physics-based simulation data and emulate the physics process. Through this numerical experiment, we demonstrate that using two separate deep learning models to distinguish post-injection from injection period generates the most accurate prediction of pressure, and a single deep learning model of the whole GCS process including the cumulative injection volume of CO 2 as a deep learning feature, leads to the most accurate prediction of CO 2 saturation. For the post-injection period, it is key to use cumulative CO 2 injection volume to inform the deep learning models about the total carbon storage when predicting either pressure or saturation. The deep learning workflow not only provides high predictive fidelity across temporal and spatial scales, but also offers a speedup of 250 times compared to full physics reservoir simulation, and thus will be a significant predictive tool for engineers to manage the long-term process of GCS.

58 GEOSCIENCES↗
DOE OSTI2023

Facile hyperpolarization chemistry for molecular imaging and metabolic tracking of [1– 13 C]pyruvate in vivo

Hyperpolarization chemistry based on reversible exchange of parahydrogen, also known as Signal Amplification By Reversible Exchange (SABRE), is a particularly simple approach to attain high levels of nuclear spin hyperpolarization, which can enhance NMR and MRI signals by many orders of magnitude. SABRE has received significant attention in the scientific community since its inception because of its relative experimental simplicity and its broad applicability to a wide range of molecules, however, in vivo detection of molecular probes hyperpolarized by SABRE has remained elusive. Here we describe a first demonstration of SABRE-hyperpolarized contrast detected in vivo, specifically using hyperpolarized [1– 13 C]pyruvate. Biocompatible formulations of hyperpolarized [1– 13 C]pyruvate in, both, methanol-water, and ethanol-water mixtures followed by dilution with saline and catalyst filtration were prepared and injected into healthy Sprague Dawley and Wistar rats. Effective hyperpolarization-catalyst removal was performed with silica filters without major losses in hyperpolarization. Metabolic conversion of pyruvate to lactate, alanine, and bicarbonate was detected in vivo. Pyruvate-hydrate was also observed as a minor byproduct. Measurements were performed on the liver and kidney at 4.7 T via time-resolved spectroscopy and chemical-shift-resolved MRI. In addition, whole-body metabolic measurements were obtained using a cryogen-free 1.5 T MRI system, illustrating the utility of combining lower-cost MRI systems with simple, low-cost hyperpolarization chemistry to develop safe and scalable molecular imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Methane foam performance evaluation in water-wet unconsolidated porous media: A systematic experimental investigation at elevated pressure and temperature conditions

In the petroleum industry, enhanced oil recovery (EOR) techniques employ foam extensively to establish conformance control in heterogeneous and fractured reservoirs in order to increase the sweep efficiency. In such applications, foam performance evaluation under complex subsurface conditions is pivotal for the effective and optimized deployment of foam treatment. However, there is a scarcity of hydrocarbon gas foam generation and evaluation studies that examine the relationships between foam performance and the critical foam parameters at high-pressure and high-temperature conditions. Here, this study aims at methodically investigating the effects of several foam parameters on methane foam performance in water-wet proppant packs under harsh operating conditions. This is in relation to the technical needs of hydrocarbon foam injection into hydraulically-induced, propped fractures in unconventional oil reservoirs. To this end, a state-of-the-art experimental foam generation apparatus was designed, fabricated, and commissioned. We performed a large number of foam flow experiments on proppant packs using methane gas and different foaming agents at 3500 psi and 115°C. Anionic and amphoteric surfactants were employed to probe the effect of their ionic nature on foam performance. Foam performance sensitivities to various foam generation parameters and operating conditions, such as surfactant concentration, gas fraction, total injection rate, operating pressure, salinity, and proppant pack length were investigated. To this end, steady-state pressure drops across the proppant packs during foam generation and foam's apparent viscosity were measured to quantify the foam performance of surfactants. The results were then analyzed to determine optimum values of the foam parameters and the interplay between these parameters are discussed here. The systematic results achieved from this work are in agreement with the trends available in the literature and provide new insights into complexities of in situ foam generation in water-wet, unconsolidated porous media at extreme reservoir conditions.

03 NATURAL GAS↗
DOE OSTI2020

Complete genome of Polaromonas vacuolata KCTC 22033 T isolated from beneath Antarctic Sea ice

Polaromonas vacuolata KCTC 22033 T is an obligate aerobic, Gram-negative, psychrophilic and rod-shaped bacterium isolated from beneath the sea ice off the coast of the Palmer Peninsula, Anvers Islands, Antarctica. P. vacuolata is the type species of Polaromonas genus and the first example of gas vacuolate Betaproteobacteria isolated from marine habitats. In this study, we report a complete genome of P. vacuolata KCTC 22033 T , which consists of 3,837,686 bp (G + C content of 52.07%) with a single chromosome, 3461 protein-coding genes, 56 tRNAs and 6 rRNA operons. Genomic analysis revealed the presence of genes involved in bacterial adaptation under saline conditions, cold adaptation via the production of gas vesicles and cell adhesion proteins, and a photoheterotrophic lifestyle when challenged by starvation. Intriguingly, several of these genes were likely acquired from species outside the Polaromonas genus. The genomic information therefore describes the unique evolution and adaptation of P. vacuolata to its extraordinary habitat, i.e., beneath the Antarctic sea ice.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluating the effectiveness of M-AMBI with other biotic indexes in a temperate estuary

Need for a scalable and widely applicable index has been increasingly important. This study evaluates the applicability of the M-AMBI, a potential comprehensive index, at small spatial scales. M-AMBI was compared to regional indices (EMAP-E and GOM B-IBI), assessing response to natural environmental gradients and low oxygen stress. Results indicate poor agreement between indices with M-AMBI and GOM B-IBI showing positive correlation but significant disagreement in habitat condition. EMAP-E had no agreement. Indices showed similar patterns of better habitat scores in higher salinities. M-AMBI also showed a negative relationship with sediment organic matter and total nitrogen. DO influenced all indices with M-AMBI the most sensitive. However, mismatches between DO and index score were observed further calibration may be needed before adoption into programs. Altogether, the M-AMBI demonstrates potential at smaller, local scales, but additional studies are needed to validate its performance in different coastal environments and under different conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Freestanding self-assembled sulfonated pentablock terpolymer membranes for high flux pervaporation desalination

Pervaporation desalination has several advantages over competing desalination technologies, most notably an ability to select for or against volatile organic compounds and the ability to process high salinity feeds at a low transmembrane pressure. Pervaporation has not been commercialized for desalination applications because of its energy intensity. However, emerging processes such as hydraulic fracturing produce high total dissolved solids (>30-45 g/L) byproduct streams that exceed the operational limits of traditional reverse osmosis and could be treated by pervaporation. Here, we demonstrate free-standing pervaporation membranes with excellent permeance and high salt removal based on a partially sulfonated pentablock terpolymer with the tradename Nexar™. Pervaporation membranes were easily cast from this material with desalination performances comparable or superior to commercially available membranes. We found that the polymer degree of sulfonation and casting solvent polarity had a significant impact on the membranes’ water uptake but only a modest impact on the pervaporation desalination performance. Membranes with a degree of sulfonation of 52% (2.0 meq g –1 IEC) and a casting solution composed of 50 wt% n-propanol and 50 wt% toluene achieved a water flux of 3.32 kg m -2 h -1 (permeance 135 kg m -2 h -1 bar -1 ) with 99.5% salt removal in pervaporation from a 32 g/L –1 sodium chloride feed solution at room temperature. We demonstrated that dense, non-porous NexarTM pervaporation membrane permeance and salt separation performance were superior to commercial pervaporation membranes and equivalent to commercial membrane distillation membranes, which have much larger pores. Here, this study demonstrates that commercially available sulfonated pentablock terpolymers are excellent membranes for pervaporation desalination because of their ease of casting and excellent performance.

42 ENGINEERING↗
DOE OSTI2022

Breaking $\mathrm{OER}$ and $\mathrm{CER}$ scaling relations via strain and its relaxation in $\mathrm{RuO}$ 2 (101)

Green hydrogen production from abundant water sources is an important component of renewable energy storage. Water oxidation catalysts are typically considered bound by adsorbate scaling relations, limiting their activity for the oxygen evolution reaction (OER) as well as selectivity between OER and the chlorine evolution reaction (CER) that compete in saline water streams. RuO 2 is highly active for both reactions, and recent measurements have shown the OER activity is greater on undercoordinated, high index facets compared to the lowest-energy (110) facet often studied. The growth of such orientations as epitaxial films, however, can result in appreciable strain and potential surface faceting via its relaxation. Here, we find the activity and selectivity towards OER and CER vary with thickness in epitaxial (101) RuO 2 thin films: OER activity decreases 4x as film thickness increases from 8 nm to 48 nm, while CER activity is comparable. Thus, strain and its relaxation can be used to break scaling relationships between OER and CER, highlighting the important role that defects play in selective oxidation processes on RuO 2 in chloride-containing media.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pulse-shape discrimination in water-based scintillators

This work describes a class of liquid scintillators that contain mostly water (>50 wt% of the entire composition) and can discriminate between interactions induced by neutrons and gamma rays. Here, by balancing the interface interactions between the components of the formulation, these scintillators form emulsions that can be thermodynamically stable. This approach, which considers a quantity known as the hydrophilic–lipophilic difference, requires consideration of the salinity and temperature as well as characterization of the surfactants and oil phase. Emulsions comprised of water and various oils were characterized first. Then, the effect of scintillating dyes in the oil phase was considered, followed by the construction of partial phase diagrams of the emulsions. For transparent oil-in-water emulsions with a single phase, the scintillation light yield and metrics related to pulse-shape discrimination were measured. The best performing scintillators contained 33 wt% of a scintillating oil phase and exhibited a light yield that was as high as 18% of the light yield of a commercially available liquid scintillator that does not contain water (EJ-309). These water-based liquid scintillators exhibited a figure of merit of neutron/gamma ray discrimination as high as 1.79 at about 1500 keV ee .

36 MATERIALS SCIENCE↗
DOE OSTI2021

U.S. lithium resources from geothermal and extraction feasibility

As the demand for electric vehicles (EVs) increases, demand for lithium (Li) is expected to grow over the coming decade. To satisfy the demand for rechargeable batteries, it is imperative to devise solutions for sufficient Li production. Additionally, even though commercial Li currently comes from conventional saline salar brine and spodumene ore extractions, efforts to retrieve Li from geothermal brines are increasing in popularity. In this paper, we evaluate the United States’ potential to supply Li from geothermal brines using Systems Dynamics modeling. The main goals are to assess (1) the viability of US Li supply from geothermal brines and (2) the potential supply chain impact of extracting Li from this source. Results show that Li supply from geothermal brines could (1) reach around 4% to 8% of total US Li supply and (2) be economically viable.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Closed-loop pressure retarded osmosis draw solutions and their regeneration processes: A review

Pressure-Retarded Osmosis (PRO) is an osmotic process that has been used to harvest energy from salinity gradients using a semi permeable membrane. A comparison between open-loop PRO (OLPRO) and closed-loop PRO (CLPRO) was made regarding their performance and costs. In CLPRO, where the diluted draw solution is re-concentrated in the regeneration system to be reutilized in the process, has recently received an intensive focus as the most viable configuration for a standalone power plant. The choice of the PRO draw solution in CLPRO is crucial to garner a high osmotic pressure as the key for the feasibility of the process. Here, in this review, the draw solutions are critically evaluated in the literature in terms of energy output as well as the method of regeneration used to recirculate them. A set of practical criteria has been suggested to appraise the adequacy of the solution for CLPRO application. It was concluded that NH 3 – CO 2 theoretically can produce 170 W/m 2 of power density. Inorganic draw solutes such as NaCl can generate high power density up to 87 W/m 2 . Organic draw solutes with their remarkably low reverse salt flux (RSF) have promising potential for future application in PRO. Similarly, the regeneration systems of the diluted draw solutions have also been reviewed and discussed. How the energy consumption of the regeneration process affects the feasibility of CLPRO is explained. For the specific case of osmotic heat engines (OHEs), when the energy of the regeneration process is supplied by heat waste, the range of applicability of the heat waste in CLPRO in terms of efficiency is defined and compared to Organic Rankine Cycle (ORC). The results showed that CLPRO has better efficiency than ORC for temperatures T < 80 °C, which makes it a promising process or low-grade heat energy recovery. In addition, a PRO-RO hybrid system coupled with solar power can reduce the net specific energy consumption (SEC) to 0.39 kWh/m 3 . The conditions that regeneration processes should operate under to make PRO viable are discussed in the last section. Overall, the study indicates the key factors for optimizing the performance of CLPRO process.

42 ENGINEERING↗
DOE OSTI2023

Protein-activated atomic layer deposition for robust crude-oil-repellent hierarchical nano-armored membranes

Atomic layer deposition (ALD) offers unique capabilities to fabricate atomically engineered porous materials with precise pore tuning and multi-functionalization for diverse applications like advanced membrane separations towards sustainable energy-water systems. However, current ALD technique is inhibited on most non-polar polymeric membranes due to lack of accessible nucleation sites. Here, in this study, we report a facile method to efficiently promote ALD coating on hydrophobic surface of polymeric membranes via novel protein activation/sensitization. As a proof of concept, TiO 2 ALD-coated membranes activated by bovine serum albumin exhibit remarkable superhydrophilicity, ultralow underwater crude oil adhesion, and robust tolerance to rigorous environments including acid, alkali, saline, and ethanol. Most importantly, excellent cyclable crude oil-in-water emulsion separation performance can be achieved. The mechanism for activation/sensitization is rooted in reactivity for a particular set of amino acids. Furthermore, the universality of protein-sensitized ALD is demonstrated using common egg white, promising numerous potential usages in biomedical engineering, environmental remediation, lowcarbon manufacturing, catalysis, and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗
DOE OSTI2025

Autonomous sensor suite for evaluating fish-turbine interactions and environmental impacts in marine renewable energy and hydropower

Marine renewable energy (MRE) harnesses ocean-based resources such as waves, tides, currents, and thermal or salinity gradients for sustainable power generation. It has the potential to complement existing renewable resources, support remote communities, and contribute to decarbonization efforts. However, understanding the hydrodynamic forces created by MRE devices and their impacts on marine life is critical for responsible deployment. Here, to address these concerns, advanced sensor devices, including the Marine Sensor Fish (MSF), Sensor Fish Mini (SF Mini), and Flexible Sensor Fish (FSF), were developed to measure interactions between aquatic organisms and MRE systems. This paper details the design, manufacturing, calibration, and field deployment of these sensor suites, highlighting their ability to capture key physical stressors such as shear forces, pressure changes, and collision impacts. The MSF successfully evaluated turbine interactions at a tidal turbine in the Salish Sea, capturing data on turbulence, collision impact, and pressure gradients. The SF Mini validated hydrodynamic conditions in scaled hydraulic models, supporting computational fluid dynamics simulations. The FSF, with its flexible silicone body, measured species-specific impacts in turbulent environments. This research demonstrates the potential of Sensor Fish technology to advance sustainable marine energy systems by reducing biological impacts and informing environmentally sustainable designs.

Ecological impacts↗