Results for “Flow Conditions” — Page 52

DOE OSTI2020

Matrix Completion Using Alternating Minimization for Distribution System State Estimation

This paper examines the problem of state estimation in power distribution systems under low-observability conditions. The recently proposed constrained matrix completion method which combines the standard matrix completion method and power flow constraints has been shown to be effective in estimating voltage phasors under low-observability conditions using single-snapshot information. However, the method requires solving a semidefinite programming (SDP) problem, which becomes computationally infeasible for large systems and if multiple-snapshot (time-series) information is used. This paper proposes an efficient algorithm to solve the constrained matrix completion problem with time-series data. This algorithm is based on reformulating the matrix completion problem as a bilinear (non-convex) optimization problem, and applying the alternating minimization algorithm to solve this problem. This paper proves the summable convergence of the proposed algorithm, and demonstrates its efficacy and scalability via IEEE 123-bus system and a real utility feeder system. This paper also explores the value of adding more data from the history in terms of computation time and estimation accuracy.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

Matrix Completion Using Alternating Minimization for Distribution System State Estimation: Preprint

This paper examines the problem of state estimation in power distribution systems under low-observability conditions. The recently proposed constrained matrix completion method which combines the standard matrix completion method and power flow constraints has been shown to be effective in estimating voltage phasors under low-observability conditions using single-snapshot information. However, the method requires solving a semidefinite programming (SDP) problem, which becomes computationally infeasible for large systems and if multiple-snapshot (time-series) information is used. This paper proposes an efficient algorithm to solve the constrained matrix completion problem with time-series data. This algorithm is based on reformulating the matrix completion problem as a bilinear (non-convex) optimization problem, and applying the alternating minimization algorithm to solve this problem. This paper proves the summable convergence of the proposed algorithm, and demonstrates its efficacy and scalability via IEEE 123-bus system and a real utility feeder system. This paper also explores the value of adding more data from the history in terms of computation time and estimation accuracy.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗

DOE OSTI2026

Measurement of the longitudinal flow-plane decorrelation using multiplane cumulants in $\sqrt{s_{NN}}$ = 200 GeV Au+Au, Ru+Ru, and Zr+Zr collisions

Measurements of the variation of anisotropic flow-plane angles (𝛹 𝑛 ) with rapidity, commonly known as the flow-plane decorrelation, provide important insights into the initial conditions of the matter produced in heavy-ion collisions. Here, in this paper, using data collected by the STAR experiment, we report the first measurement of the four-plane correlator observable 𝑇 𝑛 ⁡{𝑏⁢𝑎;𝑑⁢𝑐}=⟨⟨sin⁡[𝑛⁢(𝛹$^𝑏_𝑛$ − 𝛹$^𝑎_𝑛$)]⁢sin⁡[𝑛⁢(𝛹$^𝑑_𝑛$ − 𝛹$^𝑐_𝑛$)]⟩⟩, where superscripts 𝑎, 𝑏, 𝑐, and 𝑑 denote sequential pseudorapidity (𝜂) regions with 𝑎 corresponding to the most backward region, 𝑏 and 𝑐 close to mid-rapidity with 𝜂 𝑏 < 0 and 𝜂 𝑐 > 0, and 𝑑 being the most forward. The measurement is performed for the elliptic and triangular flow (i.e.~𝑛 = 2 and 3) in Au+Au and isobar (Ru+Ru, Zr+Zr) collisions at $\sqrt{s_{NN}}$=200~GeV. The goal of calculating the correlation of the flow-plane angle variations from backward to mid-central, and from mid-central to forward regions, is to probe the systematic variation of flow angle over a wide 𝜂 range. In mid-central collisions (10−30% centrality), we find 𝑇 2 ⁡{𝑏⁢𝑎;𝑑⁢𝑐} =−0.004 ±0.001⁢(s⁢t⁢a⁢t) ±0.002⁢(s⁢y⁢s⁢t) independent of the collision system. Such a small value of 𝑇 2 favors a random-walk'' variation of the flow-plane angles, where the rapidity correlation length is smaller than the entire region under study. These measurements provide new information on the decorrelation patterns in the system and offer a quantitative estimate of possible systematic variations in anisotropic flow angles such astwist’’ between forward and backward regions. This opens new opportunities for understanding the three-dimensional structure and the time evolution of the quark-gluon plasma created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Electrochemical CO2 conversion to formic acid through the Andora Process

Electrochemical utilization or conversion of CO2 can be used to convert waste CO2 into targeted high-value and cost-effective commercial products. Conventional processes for CO2 conversion to fuel sources are challenging and expensive due to their requirement for high temperatures and pressures. Electrochemically, a catalyst can be used at a fixed applied potential to reduce CO2 to form a desired product with less competition at modest operating conditions. Formic acid (FA) has recently become a product of interest for CO2 conversion due to its potential for hydrogen storage and fuel cell applications. Electrochemically, FA is produced through a direct two-electron transfer process involving CO2 with a proton source, requiring less energy input and fewer reaction steps than traditional processes. However, there remain significant obstacles for the broader-scale implementation of CO2 on the market, including competition with unwanted CO and H, the presence of molecular oxygen, and stability of the electrocatalyst. In order to overcome some of these challenges, a new continuous flow Andora Process was developed consisting of two separate cells to decouple electrochemical reduction of the charge carrier with the FA production via an engineered catalyst. Recent experimental results show that with appropriate design changes and operating conditions to the flow system, FA production above 500 mM can be achieved along with efficiencies above 80%. TEA and LCA assessments of the Andora Process show a potential for the reduction in the GWP potential and cost saving compared to the current comparative formic acid production process.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Assessment of reverse gun taylor cylinder experimental configuration

Experimental efforts for Taylor-anvil impact tests have often been limited to near room temperature. The ‘Reverse Gun’ method proposed by Gust in 1982 allows for the Taylor impact specimen to be uniformly heated without temperature losses before impact. Through the use of finite element analysis, we explore two topics in this work. First, we examine whether the reverse gun experimental configuration is comparable to the traditional Taylor-anvil setup. Second, we assess the accuracy of several commonly employed flow strength models in terms of their ability to predict the reverse gun experimental results which involve dynamic loading conditions and complex thermo-mechanical coupling. The reverse gun simulations are performed for tantalum targets at initial temperatures in the range 295 K to 1295 K and velocities from 135 m/s to 242 m/s. We show that with suitable care in the modeling of the preheated reverse gun experiments one can make valuable assessments of flow strength models. Given the conditions explored, these observations probe the thermal softening, strain hardening, and strain rate sensitivity of the material.

42 ENGINEERING↗

DOE OSTI2022

Capillary Pressure to Relative Permeability: Task 7.3.4 Relative Permeability Analysis Final Report

Surface tension affects all aspects of fluid flow in porous media. Through measurements of surface tension interaction under multiphase conditions, a relative permeability relationship can be determined. Relative permeability is a numerical description of the interplay between two or more fluids and the porous media they flow through. It is a critical parameter for various tools used to characterized subsurface multiphase flow systems, such as numerical simulation for oil and gas development, carbon sequestration, and groundwater contamination remediation. Therefore, it is critical to get a good statistic distribution of relative permeability in the porous media under study. Empirical relationships for determining relative permeability from capillary pressure are already well established but do not provide the needed flexibility required to match laboratory derive relative permeability relationships. By expanding the existing methods for calculating relative permeability from capillary pressure data, it is possible to create both two and three-phase relative permeability relationships. Existing laboratory-measured relative permeability data along with mercury intrusion capillary (MICP) data coupled with interfacial tension and contact angle measurements were used to determine the efficacy of this approach to relative permeability curve creation. The relative permeability relationships determined with this method were fit to existing laboratory data to elucidate common fitting parameters that were then used to create relative permeability relationships from MICP data that does not have an associated laboratory-measured relative permeability relationship.

58 GEOSCIENCES↗

DOE OSTI2024

Flow reversal benchmark of a one-sided heated narrow rectangular channel with CATHARE and RELAP5

Flow reversal in narrow coolant channels can be a crucial phenomenon for the safety of research reactors with a downward nominal flow direction. During a loss of forced flow accident, the downward flow stagnates briefly before transitioning into an upward natural circulation flow. The fuel may be damaged if dryout occurs and threshold fuel and/or cladding temperatures are exceeded. A comprehensive study is provided for flow reversal in narrow rectangular channels by examining experimental data and conducting software model analyses. The literature on flow reversal was reviewed, and selected experimental datasets were used to benchmark against CATHARE and RELAP5 models and also compare the code calculations with each other. The experimental data comes from flow reversal tests conducted with a narrow rectangular channel with one-sided heating. The results were compared with experimental data for successful flow reversal tests and predicted dryout power for dryout conditions. Also, the study examined the effects of the pump coastdown period, inlet liquid temperature, system pressure, and localized pressure drops. The experimental results showed that shorter coastdown periods, reduced pressure drops, and lower coolant inlet temperatures increased the dryout power. However, the system pressure did not noticeably affect the results. The simulation results showed that both CATHARE and RELAP5 agreed with experimental data, capturing the trends of the experimental results. Slight differences between each code calculation, as well as the predicted and measured dryout powers, were attributed to experimental uncertainties and the modeling of physical phenomena such as wall nucleation, interfacial heat transfer, drag coefficients, and critical heat flux. Overall, this study provides an understanding of flow reversal and the prediction capabilities of thermal-hydraulics software models. In conclusion, a future study of the flow reversal benchmark of a narrow rectangular channel with two-sided heating may provide additional valuable insights.

CATHARE↗

DOE OSTI2021

Threshold Heat-Flux Reduction by Near-Resonant Energy Transfer

Near-resonant energy transfer to large-scale stable modes is shown to reduce transport above the linear critical gradient, contributing to the onset of transport at higher gradients. This is demonstrated for a threshold fluid theory of ion temperature gradient turbulence based on zonal-flow-catalyzed transfer. Furthermore, the heat flux is suppressed above the critical gradient by resonance in the triplet correlation time, a condition enforced by the wave numbers of the interaction of the unstable mode, zonal flow, and stable mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Experimental and Numerical Evaluation of the Thermal-Fluid Characteristics of the Helium-Cooled Modular Divertor with Multiple Jets Using a Reversed Heat Flux Approach

A single-finger unit of the Helium-Cooled Modular Divertor with Multiple Jets (HEMJ) with a plasma-facing surface (PFS) area of about 2 cm 2 has been studied in a helium (He) loop at He mass flow rates m˙ H ≤ 8 g/s and nearly prototypical conditions. Based on previous studies of the single finger of the HEMJ, our Georgia Institute of Technology group is planning to experimentally study larger divertors. Given that the HEMJ test section was heated with an induction heater and that it is impractical to scale this up to divertors with larger PFS areas, a reversed heat flux approach is being considered to measure heat transfer coefficients (HTCs). In this approach, the direction of the heat flux is reversed with water cooling and high-temperature He heating of the outer shell attached to the PFS. This work presents an initial experimental and numerical evaluation of this approach for a single HEMJ finger. Experiments with brass and copper-chromium-zirconium outer shells were conducted at dimensionless He mass flow rates or Reynolds numbers Re = 1 × 10 4 to 4.7 × 10 4 , an inlet pressure of 10 MPa, temperatures as great as 673 K, and maximum heat flux of 8.4 MW/m 2 . The experiments verify that the He-side HTCs are independent of the direction of the heat flux. Here, the results agree well with previous Nusselt number correlation and pressure loss coefficients for the HEMJ obtained using the normal heating approach.

42 ENGINEERING↗

DOE OSTI2026

Investigation of onshore wind farm wake recovery with in situ aircraft measurements during AWAKEN

The share of wind power for electricity supply is increasing worldwide. This highly variable resource requires the improved prediction of power output for network stability. The interaction between wind farm wakes and the atmospheric boundary layer (ABL) introduces uncertainties in power production that warrant detailed investigation. The flow downwind of wind farms is characterized by a reduction in wind speed and an increase in turbulence, which both vary with atmospheric conditions. During the American WAKE experimeNt (AWAKEN), the Technische Universität Braunschweig conducted measurement flights with a research aircraft upwind and downwind of onshore wind farms in the southern Great Plains in Oklahoma in the USA. This study utilizes data from 20 flights conducted at approximately hub height in September 2023 to investigate the wind field variability downwind of the wind farms and vertical profiles to observe atmospheric stratification. The flights were aligned perpendicular to the main wind direction downwind of the King Plains and Armadillo Flats wind farms. Additionally, lidar data from both upwind and downwind ground-based measurement sites and sonic anemometer data were used for comprehensive analysis. Results indicate that under stable ABL conditions, the wake persists at greater downwind distances with a higher velocity deficit in the wake relative to the undisturbed flow compared to unstable stratification. In homogeneous terrain under stable conditions, wake recovery to 95 % occurs between a distance of 4.5 and 9 km downwind of the wind farm. In the semi-complex terrain characterized by shallow hills, slopes, and valleys, the wake exhibits a higher velocity deficit compared to homogeneous terrain, while in some cases the wake was amplified by the terrain resulting in higher velocity deficit 10 km downwind of the wind farm compared to the measurements closer to the wind farm. The turbulent kinetic energy (TKE) and “TKE difference” was found to be a valuable measure in understanding wakes in a semi-complex terrain, showing a clear wake recovery and formation depending on the stratification of the ABL.

17 WIND ENERGY↗

DOE OSTI2024

A Prefire Approach for Probabilistic Assessments of Postfire Debris‐Flow Inundation

Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A Prefire Approach for Probabilistic Assessments of Postfire Debris-Flow Inundation

Increases in wildfire activity and rainfall intensification are driving more postfire debris flows (PFDF) in many regions around the world. PFDFs are most common in the first postfire year and may even occur before a fire is fully controlled. This underscores the importance of assessing postfire hazards before a fire starts. Evaluation of PFDF hazards prior to fire can help strategize interventions lessening the negative effects of future fires. However, debris-flow runout and inundation analyses are not routine in PFDF hazard assessments, partially due to time constraints and substantial uncertainties in boundary conditions. Here, we propose a prefire PFDF inundation assessment framework using a debris-flow runout model based on the Herschel-Bulkley (HB) rheology (HEC-RAS v6.1). We constrain model inputs and parameters using Bayesian posterior analysis, rainfall-runoff simulations, and a debris-flow volume model. We use observations from recent PFDF incidents in northern Arizona, USA, to calibrate model components and then apply our prefire inundation assessment framework in a nearby unburned area. Specifically, we (a) identify yield stress as the most influential factor on inundation extent and arrival time in a HB model, (b) establish posterior distributions for model parameters suitable for forward modeling by leveraging uncertainties in field observations, and (c) implement a predictive forward analysis in an area that has not burned recently to evaluate PFDF inundation under several future fire scenarios. This study improves our ability to assess postfire debris-flow hazards before a fire begins and provides guidance for future applications of single-phase rheological models when assessing PFDF hazards.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Gluonic hot spot initial conditions in heavy-ion collisions

The initial conditions in heavy-ion collisions are calculated in many different frameworks. The importance of nucleon position fluctuations within the nucleus and subnucleon structure has been established when modeling initial conditions for input to hydrodynamic calculations. However, there remain outstanding puzzles regarding these initial conditions, including the measurement of the near equivalence of the elliptical v 2 and triangular v 3 flow coefficients in ultracentral 0–1% Pb + Pb collisions at the CERN Large Hadron Collider. Recently a calculation termed magma incorporating gluonic hot spots via two-point correlators in the color glass condensate framework, and no nucleons, provided a simultaneous match to these flow coefficients measured by the ATLAS experiment, including in ultracentral 0–1% collisions. Our calculations reveal that the magma initial conditions do not describe the experimental data when run through full hydrodynamic sonic simulations or when the hot spots from one nucleus resolve hot spots from the other nucleus, as predicted in the color glass condensate framework. Finally, we also explore alternative initial condition calculations and discuss their implications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Organic colloid composition in variable-redox porewaters within a mountainous floodplain

Redox gradients, often driven by changes in sediment moisture levels in porous, heterogeneous groundwater systems, create dynamic conditions that may promote the production and transport of colloids within natural waters. While much research has focused on the inorganic composition of colloids, the organic composition remains less well understood. Organic matter (OM) in colloids may associate with minerals, complex metal ions, and serve as an electron donor for microbial respiration; therefore, its composition is of high interest. We examined the composition of porewater OM along a redox gradient in a riparian soil located along the Slate River in Crested Butte, Colorado, USA as a function of depth (90, 130, 200, and 350 cm below ground surface). All depths were oxic to suboxic, except 200 cm, where the products of iron and sulfate reduction were observed concomitant with an increase in dissolved and/or colloidal OM, pH, alkalinity, and conductivity. We investigated the composition of porewater using correlated scanning transmission X-ray microscopy and transmission electron microscopy. We observed a change in the OM chemistry from carboxylate-rich at the 200 cm depth (where it was also enmeshed with non-crystalline iron) to phenol- and substituted-aromatic-rich at other depths. Radiocarbon dating revealed carbon in porewater at 200 cm was younger than depths above and below. Soil porewater can flow down into the underlaying gravel bed during baseflow conditions, thus we speculate whether riparian porewater could transport iron- and carboxylate-rich organic colloids into surrounding surface waters through the gravel bed conduit.

Alpine floodplain↗

DOE OSTI2026

Data from Stewart et al. 2026 "Organic Colloid Composition in Variable-Redox Porewaters within a Mountainous Floodplain"

Redox gradients, often driven by changes in sediment moisture levels in porous, heterogeneous groundwater systems, create dynamic conditions that may promote the production and transport of colloids within natural waters. While much research has focused on the inorganic composition of colloids, the organic composition remains less well understood. Organic matter (OM) in colloids may associate with minerals, complex metal ions, and serve as an electron donor for microbial respiration; therefore, its composition is of high interest. We examined the composition of porewater OM along a redox gradient in a riparian soil located along the Slate River in Crested Butte, Colorado, USA as a function of depth (90, 130, 200, and 350 cm below ground surface). All depths were oxic to suboxic, except 200 cm, where the products of iron and sulfate reduction were observed concomitant with an increase in dissolved and/or colloidal OM, pH, alkalinity, and conductivity. We investigated the composition of porewater using correlated scanning transmission X-ray microscopy and transmission electron microscopy. We observed a change in the OM chemistry from carboxylate-rich at the 200 cm depth (where it was also enmeshed with non-crystalline iron) to phenol- and substituted-aromatic-rich at other depths. Radiocarbon dating revealed carbon in porewater at 200 cm was younger than depths above and below. Soil porewater can flow down into the underlaying gravel bed during baseflow conditions, thus we speculate whether riparian porewater could transport iron- and carboxylate-rich organic colloids into surrounding surface waters through the gravel bed conduit. This data package includes geochemical data (.csv) as a function of depth from porewaters in OBJ1. Measurements included are pH, conductivity, TOC, Fe concentration, sulfate concentration, dissolved oxygen. Additionally radiocarbon dating age of carbon in samples is provided. Additionally, this dataset contains metadata files (.csv) describing the methods, file contents, and column headers.

alpine floodplain↗

DOE OSTI2026

Hybrid Cooling and Water Treatment for Resilient, Water-Self-Sufficient Data Centers

The continued growth of data center infrastructure is intensifying demand for freshwater resources, particularly in water-stressed regions, and is increasingly limiting sustainable capacity expansion. This work investigates a conceptual hybrid system that integrates freeze desalination with ultrasonic-assisted ice separation to enable on-site production of pure water from diverse sources, including seawater, brackish groundwater, and reclaimed industrial or agricultural wastewater. Simultaneously, the system produces low-temperature cooling streams that enhance heat removal in high power density computing environments. A process-level thermodynamic analysis is performed across a range of boundary and operating conditions, including variations in feed concentration, freezing temperature, and mass flow rate. The results are presented as performance curves relating feedwater concentration and target purified water output to the corresponding intake flow requirements, enabling estimation of source water demand per unit of Information Technology Equipment (ITE) energy consumption (kWh) across varying data center scales and operational scenarios. The corresponding electrical energy consumption for integrated cooling and water treatment is also evaluated as a function of system operating parameters and target water production levels. These results provide a basis for evaluating system feasibility across different conditions and for identifying parameter ranges in which integrated water treatment and cooling improve resource efficiency, thermal performance, and operational flexibility in data centers.

Elhefny, Aly [ORNL] (ORCID:0000000284907923)↗

DOE OSTI2024

Wave-powered water pump for upwelling in aquaculture: Numerical model and ocean test

Wave-powered upwelling can increase the productivity and survivability of several aquaculture species. This enhancement is due to transporting cold, nutrient-rich ocean water, typically found lower in the water column, to the surface. Macroalgaes, like kelp, exhibit increased growth from these altered conditions. The University of New Hampshire’s (UNH) wave-powered water pump (wave pump) is a point absorber wave energy converter (WEC) that uses ocean waves to create relative motion between a spar buoy and a concentric float which drives an internal pump. A numerical model of the wave pump was developed using WEC-Sim to predict device performance in the ocean. Wave pump performance was evaluated during a five day ocean test near Appledore Island in Maine in March 2023, where volumetric flow rate, relative distance between spar and float, and wave conditions were measured. These data were then used for numerical model validation. The ocean deployment recorded the device’s performance in a variety of sea states, with average significant wave heights up to 0.7 m. The ocean test data were compared to the WEC-Sim numerical model of the device with favorable results. Average values of device stroke period, stroke height, and flow rate agreed between the ocean test and model data to within approximately 16 to 22%. Furthermore, the validated numerical model provides a valuable tool for improving the design and developing a commercial-scale, wave-powered water pump for use in aquaculture.

16 TIDAL AND WAVE POWER↗