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DOE OSTI2024

Watching the Grand Ethiopian Renaissance Dam from a distance: Implications for sustainable water management of the Nile water

Increased demands for sustainable water and energy resources in densely populated basins have led to the construction of dams, which impound waters in artificial reservoirs. In many cases, scarce field data led to the development of models that underestimated the seepage losses from reservoirs and ignored the role of extensive fault networks as preferred pathways for groundwater flow. We adopt an integrated approach (remote sensing, hydrologic modeling, and field observations) to assess the magnitude and nature of seepage from such systems using the Grand Ethiopian Renaissance Dam (GERD), Africa's largest hydropower project, as a test site. The dam was constructed on the Blue Nile within steep, highly fractured, and weathered terrain in the western Ethiopian Highlands. The GERD Gravity Recovery and Climate Experiment Terrestrial Water Storage (GRACETWS), seasonal peak difference product, reveals significant mass accumulation (43 ± 5 BCM) in the reservoir and seepage in its surroundings with progressive south-southwest mass migration along mapped structures between 2019 and 2022. Seepage, but not a decrease in inflow or increase in outflow, could explain, at least in part, the observed drop in the reservoir's water level and volume following each of the three fillings. Using mass balance calculations and GRACETWS observations, we estimate significant seepage (19.8 ± 6 BCM) comparable to the reservoir's impounded waters (19.9 ± 1.2 BCM). Investigating and addressing the seepage from the GERD will ensure sustainable development and promote regional cooperation; overlooking the seepage would compromise hydrological modeling efforts on the Nile Basin and misinform ongoing negotiations on the Nile water management.

GRACE and GRACE-FO↗

DOE OSTI2026

A New Window into the Baryon Cycle at Cosmic Noon with Line Intensity Mapping: Forecasts for auto- and cross-correlations in [CII]-158$μ$m, HI 21 cm, CO$_{J+1\rightarrow J}$, and H$α$ galaxies

Across the peak of cosmic star formation at $z\sim1-2$, inflow, processing, and feedback drive rapid changes in the spatial distribution and chemical composition of baryons in galaxies and surrounding reservoirs; this baryon cycle can be tomographically mapped by line intensity mapping (LIM) of atomic hydrogen, ionized carbon, and carbon monoxide. We present a simulation-based forecasting framework for detecting auto- and cross-power spectra between spectroscopic surveys of four such tracers at $z\sim0.5-1.7$ mapping the same deep field - TIM, EoRSpec/FYST, MeerKAT, & Euclid. We forward-model 3-D distributions for these tracers from magnetohydrodynamic simulations, directly capturing the two-halo, one-halo, and shot statistics without relying on analytical decompositions. We further detail a signal-to-noise formalism, tailored to LIM surveys with highly anisotropic geometries and Fourier-space coverage. We demonstrate that galaxy cross-correlations will be the dominant discovery channel for current-generation surveys. These instruments will detect the auto-spectra for CO and HI 21 cm and the CO $\times$ 21 cm cross-spectrum at modest S/N $\sim 1-10$, while placing upper limits on the [CII]-158$μ$m signals. [CII], CO, and HI LIM will be $\sim3-30\times$ ($0.5-1.5$ dex) more sensitive to cross-correlation with the Euclid survey, however, than their respective auto-correlations, constraining all three models of line emission at high significance (S/N $\sim 10-40$) within this decade. Finally, we formulate a staged instrumental trajectory with planned or reasonable improvements, including the as-proposed SKA-Mid. We forecast advancing the per-$k$-mode sensitivities of each auto-, galaxy-line, and line-line spectrum by several orders of magnitude, enabling new percent- and sub-percent level constraints on cosmology and the redshift evolution of star formation and the baryon cycle.

Agrawal, Shubh [Pennsylvania U., Dept. Math.]↗

NASA NTRS1982

Study of vapor flow into a capillary acquisition device

An analytical model was developed that prescribes the conditions for vapor flow through the window screen of a start basket. Several original submodels were developed as part of this model. The submodels interrelate such phenomena as the effect of internal evaporation of the liquid, the bubble point change of a screen in the presence of wicking, the conditions for drying out of a screen through a combination of evaporation and pressure difference, the vapor inflow rate across a wet screen as a function of pressure difference, and the effect on wicking of a difference between the static pressure of the liquid reservoir and the surrounding vapor. Most of these interrelations were verified by a series of separate effects tests, which were also used to determine certain empirical constants in the models. The equations of the model were solved numerically for typical start basket designs, and a simplified start basket was constructed to verify the predictions, using both volatile and nonvolatile test liquids. The test results verified the trends predicted by the model.

Dodge, F. T.↗

DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗

NASA NTRS1995

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↗

DOE OSTI2024

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗

DOE OSTI2024

Numerical Simulations in Support of a Long-Term Test of Gas Production From Hydrate Accumulations on the Alaska North Slope: Water Production and Associated Design and Management Issues

Here, we investigated numerical simulation strategies for a long-term test of depressurization-induced gas production from the B1 Sand of Unit B at the Hydrate-01 Stratigraphic Test Well. The main objective of this study was to estimate fluid production rates (with emphasis on water production) under a variety of conditions and production scenarios and contribute new insights to the design and management of the field test. In the first part of the study, we investigated the system response to a three-step depressurization process using two limiting sets of flow properties─the expected maximum and minimum intrinsic and effective permeabilities─for the very heterogeneous reservoir. In the second part, we investigated the effect of the production interval length and placement within the formation relative to the boundaries of the hydrate-bearing unit. The best performing well configuration was used in the third part of the study, which used the most representative subsurface flow properties to investigate the effect of the depressurization strategy on the production performance. The best overall performance (largest gas production with modest water production and a strong response at the observation wells) was obtained with a 10 m-long well situated 3 m below the top of the formation and a three-step depressurization scheme at 15-day intervals to a terminal bottomhole pressure of 2.8 MPa. The overall production performance was enhanced by a faster rate of depressurization. Estimated water production rates in all cases were limited and easily manageable. None of the tested well configurations or depressurization strategies significantly reduced water production without also severely reducing gas production. In all the investigated cases, 95% of the long-term fraction of produced water was replenished by inflows from the boundaries and could not be reduced. These substantial water inflows are an unavoidable feature of HU-B and cannot be easily mitigated by a hydraulic control.

02 PETROLEUM↗