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DOE OSTI2024

Failure Analysis for Molten Salt Thermal Energy Storage Tanks for In-Service CSP Plants

Thermal Energy Storage (TES) is a fundamental component in concentrating solar power (CSP) plants to increase the plant's dispatchability, capacity factor, while reducing the levelized cost of electricity. In central receivers CSP plants, nitrate molten salts have been used for several years for operation temperatures of up to 565 degrees C. Despite many efforts to advance nitrate salt to higher operation temperatures (even considering a replacement with molten chloride salts) to achieve higher energy conversion efficiencies, the 565 degrees C temperature is currently considered the state-of-the art. Although molten salt tanks have been broadly deployed in commercial CSP plants worldwide, several failures have been reported in these tanks after a few months or years of operation, causing significant economic loss and mistrust in CSP technologies. Most of these failures are associated with the infancy of the technology and multiple issues related to tank design, fabrication, commissioning, and aggressive operation. A technical standard dedicated to the design and fabrication of molten nitrate TES tanks does not exist today. Current in-service molten salt tanks have been generally designed based on the American Petroleum Institute's (API) 650 and ASME Section II standards. The API 650 code provides guidelines for dimensions and fabrication for oil storage tanks up to 260 degrees C. The ASME standard provides allowable stress values for various materials at a range of temperatures and conditions. Both standards seem to be limited for molten salt TES tanks where high temperatures, thermal cycling, and transient conditions are expected. In 2020, NREL released the Concentrating Solar Power Best Practices Study (NREL/TP-5500-75763) that summarized multiple issues in CSP plants, along with potential alternatives and recommendations to address those issues based on information collected from participants representing about 80% of operating CSP plants in the world. One of the recommendations from this study was the development of accurate and validated models to evaluate the plant's transient operation, capable of capturing the effect of short-term clouds and operator response, while being flexible in being adapted to various spatial and temporal resource data. The "Failure Analysis for Molten Salt Thermal Energy Tanks for In-Service CSP Plants" project was inspired on this recommendation and was focused on (1) the development and validation of a physics-based model for a representative, commercial-scale molten salt tank, (2) performing simulations to evaluate the behavior of the tank as a function of typical plant operation conditions, (3) understanding tank failures mechanisms, (4) determining the residual stress and distortion in the tank floor after welding fabrication and evaluating their impact in the stresses developed in the tank during operation, (5) assessing the impact of key operation parameters on the temperature and stress distribution, (6) conduct a preliminary evaluation of design features to reduce stress and improve tank's reliability, and (7) estimate the tank's service life based on the stress developed under diverse operation scenarios. From the analysis conducted in the project and presented in this report, it was found that maximum stresses surpassing the yield strength point of the stainless steel (SS) 347H are developed on the tank floor near the perimeter. These large stresses are strongly influenced by the initial residual stresses and distortion of the tank floor after welding fabrication. During operation, large stresses are developed in the tank floor at high operation temperatures with large salt inventory levels during transient operation. High stresses are also related to elevated temperature gradients in the tank floor that could be attributed to insufficient mixing within the salt inflow and the salt inventory. Based on the analysis, creep is the predominant failure mechanism. However, the large stress levels could favor the plastic deformation into buckles, and crack formation due to stress relaxation cracking during cycle operation. A lifetime below 3 years was estimated for the typical plant operation conditions and a specific initial residual stress and deformation distribution of the tank floor. The estimated life agrees with the service time to failure reported in several commercial molten salt tanks. Desing and operation guidelines can be extracted from the analysis presented in this report, which could be adopted by tank manufacturers and CSP operators to advance toward an ultimate solution for tank failures by reducing residual and operational stresses to achieve a tank service life of more than 30 years. Addressing failures in molten salt TES tanks is fundamental for the CSP industry's survivability, but it is also important for other industrial and power generation applications using this technology, including nuclear and concentrating solar thermal.

14 SOLAR ENERGY↗

NASA NTRS2011

Validation of Space Weather Models at Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a multiagency partnership, which aims at the creation of next generation space weather modes. CCMC goal is to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. The presentation will demonstrate the recent progress in CCMC metrics and validation activities.

Kuznetsova, M. M.↗

DOE OSTI2021

Experimental modal analysis of SSR1 cryomodule for numerical model tuning and validation

The present activity aims to test the Cryomodule SSR1 to validate the corresponding mixed multibody-finite element numerical model and to determine the range of frequencies in which the first natural modes of the structure lie. The experimental activity consisted of a hammer test of the cryomodule at an early assembly stage at which the internal parts, constituting the cold mass, are accessible and, thus, many accelerometers can be attached to the beam string. The comparison between the experimental results obtained for the sub-assembly and the numerical results obtained for the corresponding sub-model, derived from the previously developed complete model, allowed to assess the validity of the numerical model and to get feedback on the effectiveness of the placement of the sensors in capturing the dynamic response of the system during transportation.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Investigation of Stress Field and Fracture Development During Shale Maturation Using Analog Rock Systems

The emergence of hydrocarbons within shale as a major recoverable resource has sparked interest in fluid transport through these tight mudstones. Recent studies suggest the importance to recovery of microfracture networks that connect localized zones with large organic content to the inorganic matrix. This paper presents a joint modeling and experimental study to examine the onset, formation, and evolution of microfracture networks as shale matures. Both the stress field and fractures are simulated and imaged. A novel laboratory-scale, phase-field fracture propagation model was developed to characterize the material failure mechanisms that play a significant role during the shale maturation process. The numerical model developed consists of coupled solid deformation, pore pressure, and fracture propagation mechanisms. Benchmark tests were conducted to validate model accuracy. Laboratory-grade gelatins with varying Young’s modulus were used as scaled-rock analogs in two dimensional Hele-Shaw cell apparatus. Yeast within the gelatin generates gas in a fashion analogous to hydrocarbon formation as shale matures. These setups allow study and visualization of host rock elastic-brittle fracture and fracture network propagation mechanisms. The experimental setup was fitted to utilize photoelasticity principles coupled with birefringence properties of gelatin to explore visually the stress field of the gelatin as the fracture network developed. Stress optics image analysis and Linear Elastic Fracture Mechanics (LEFM) principles for crack propagation were used to monitor fracture growth for each gelatin type. Observed and simulated responses suggest gas diffusion within and deformation of the gelatin matrix as predominant mechanisms for energy dissipation depending on gelatin strength. LEFM, an experimental estimation of principal stress development with fracture growth, at different stages was determined for each gelatin rheology. Here, the interplay of gas diffusion and material deformation determines the resulting frequency and pattern of fractures. Results correlate with Young’s modulus. Experimental and computed stress fields reveal that fractures resulting from internal gas generation are similar to, but not identical to, type 1 opening mode.

58 GEOSCIENCES↗

DOE OSTI2026

Technical, economic, and load-following capabilities assessment of grid-connected geothermal and geothermal-solar hybrid systems

The technical and economic performance as well as the load-following capabilities of grid-connected geothermal hybrid systems were assessed in this work. The analyzed geothermal hybrid configuration is composed of a binary geothermal plant integrated with a concentrating solar-thermal system and underground thermal energy storage (UTES) through a primary heat exchanger. Physics-based models for the hybrid system for plant generation capacities of 1, 25, and 50 MW were developed from validated models for each subsystem. Also, an economic model was developed that accounts for different hybrid system capabilities, solar field sizes, and thermal storage duration. The advantage of the geothermal hybrid system was assessed by comparing the performance with the baseline benchmark geothermal plant with a similar configuration and generation capacity. It was found that hybridizing geothermal plants with concentrating solar and thermal energy storage not only improves the thermal efficiency by up to 8 percentage points when additional heat from the solar-UTES loop rises the evaporator temperatures from 70 to 125 °C, but also enhances the load-following capability for the geothermal plant, which can meet a typical residential load profile with a power rate of change 0.25 kW/s with an absolute error under 13 kW for a 1 MW plant. Other benefits of hybridization include resource preservation and a potential LCOE reduction of up to 56% for a 50 MW geothermal hybrid plant having a 50% solar share, a 1.4 solar multiple, and 24-h storage capacity. The results presented in this work demonstrate that hybridizing geothermal systems transforms them into a flexible and cost-effective solution for addressing the dynamic requirements of modern electric grids.

15 GEOTHERMAL ENERGY↗

DOE OSTI2017

Autoignition study of binary blends of n- dodecane/1-methylnaphthalene and iso- cetane/1-methylnaphthalene

An experimental study on autoignition of two binary blends, n-dodecane/1-methylnaphthalene and iso-cetane/1-methylnaphthalene, has been conducted using a rapid compression machine. Specifically, the ignition delays of the stoichiometric blend+air mixtures were measured at elevated pressures of P C = 15 bar and 30 bar, compressed temperatures of T C = 626–944 K, and varying blending ratios of the constituents. For a given set of P C and T C , a nonlinear response of the blend reactivity with respect to the relative amount of the constituents was observed. Since a comprehensive chemical kinetic model for the blends investigated here is under development, the current ignition delay datasets serve as the needed targets for model validation. For selected conditions, ignition delay simulations were conducted to highlight and discuss the deficiencies of the literature models and the potential areas for model improvements, especially at low temperatures. In conclusion, further chemical kinetic analyses were conducted to gain understanding of the blending behavior predicted by the available model.

1-methylnaphthalene↗

DOE OSTI2023

Reducing impacts of artificial ponding in modeling salt marshes using a conductivity-formulated subgrid model

The landforms of salt marsh systems are rather complex, with meandering channel networks cutting through low-lying, extensive marsh platforms. Some small-scale topographic details are critical to flooding and draining processes but cannot be reflected in the Digital Elevation Model (DEM) due to limited measurement resolution and vegetation bias. Numerical models need a grid with high enough resolution to capture the small-scale connectivity to correctly model the small-scale flow processes, making the model computationally unaffordable. Here, in this study, we derived a subgrid model, which couples two flow components, one is the regular subgrid model for simulating the subgrid-resolved flows, and the other is a conductivity-formulated porous flow model for modeling small-scale gut flows unresolved at the subgrid level. The model validation was performed using an idealized case with a narrow slot that was unresolved in the coupled flow model. Model results were compared with a slot-resolved regular subgrid model where only surface flows are solved and suggested that, with a proper model parameterization, the coupled flow model is capable of reproducing flooding and draining processes similar to the slot-resolved subgrid model of surface flow. The model was applied to simulating flooding and draining processes in a meso-tidal salt marsh. The model results demonstrate that the coupled subgrid model can be used to reduce the impacts of artificial ponding that usually occur in numerical simulations of salt marshes with numerous narrow gullies and creeks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Artificial neural network based predictions of cetane number for furanic biofuel additives

The next generation of alternative fuels is being explored through advanced chemical and biological production techniques for the purpose of finding suitable replacements for diesel and gasoline while lowering production costs and increasing process yields. Chemical conversion of biomass to fuels offers a plethora of pathways with a variety of fuel molecules, both novel and traditional, which may be targeted. In the search for new fuels, an initial, intuition-driven evaluation of fuel compounds with desired properties is required. Due to the high cost and significant production time needed to synthesize these materials at a scale sufficient for exhaustive testing, a predictive model would allow chemists to preemptively screen fuel properties of potentially desirable fuel candidates. Current work has shown that predictive models, in this case artificial neural networks (ANN's) analyzing quantitative structure property relationships (QSPR's), can predict the cetane number (CN) of a proposed fuel molecule with relatively small error. A fuel's CN is a measure of its ignition quality, typically defined using prescribed ASTM standards and a cetane testing engine. Alternatively, the analogous derived cetane number (DCN), obtained using an Ignition Quality Tester (IQT), is a direct measurement alternative to the CN that uses an empirical inverse relationship to the ignition delay found in the constant volume combustion chamber apparatus. DCN data points acquired using an IQT were utilized for model validation and expansion of the experimental database used in this study. The present report improves on an existing model by optimizing the model architecture along with the key learning variables of the ANN and by making the model more generalizable to a wider variety of fuel candidate types, specifically the class of furans and furan derivatives, by including specific molecules for the model to incorporate. The new molecules considered include tetrahydrofuran, 2-methylfuran, 2-methyltetrahydrofuran, 5,5'-(furan-2-ylmethylene)bis(2-methylfuran), 5,5'-((tetrahydrofuran-2-yl)methylene)bis(2-methyltetrahydrofuran), tris(5-methylfuran-2-yl)methane, and tris(5-methyltetrahydrofuran-2-yl)methane. Model architecture adjustments improved the overall root-mean-square error (RMSE) of the base database predictions by 5.54%. Additionally, through the targeted database expansion, it is shown that the predicted cetane number of the furan-based molecules improves on average by 49.21% (3.74 CN units) and significantly for a few of the individual molecules. This indicates that a selected subset of representative molecules can be used to extend the model's predictive accuracy to new molecular classes. The approach, bolstered by the improvements presented in this paper, enables chemists to focus on promising molecules by eliminating less favorable candidates in relation to their ignition quality.

09 BIOMASS FUELS↗

DOE OSTI2021

A crystal plasticity finite element model embedding strain-rate sensitivities inherent to deformation mechanisms: Application to alloy AZ31

We report the fundamental power-law relationship representing the flow rule in crystal visco-plasticity ensures uniqueness in the selection of slip systems accommodating imposed plastic strain-rates. The power-law relationship also introduces an artificially high strain-rate sensitivity in crystal plasticity simulations, unless a high value of the power-law exponent is used. However, the use of high values for the exponent is limited by numerical tractability. This paper presents a numerical method implemented in a crystal plasticity finite element (CPFE) model for embedding any value of the power-law exponent reflecting the true material strain-rate sensitivity. Importantly, the method does not increase computation time involved in the simulations. The enhanced CPFE model is used to interpret and predict a complex strain-rate sensitive response and microstructural evolution of AZ31 Mg alloy. Measured values of strain-rate sensitivity for slip and twinning modes are used in the simulations. Calculations show that the model successfully captures the phenomena pertaining to the effect of changing applied strain-rate on the mechanical response including flow stress and evolution of texture and twinning for a broad range of strain-rates ranging from 10 -3 s -1 to 10 3 s -1 and loading orientations in tension and compression. It is shown that such predictions are a consequence of not only relative amounts of slip and twinning activities driven by a set of accurately characterized hardening law parameters but also values of the strain-rate sensitivities inherent to individual deformation mechanisms. Besides, the model validates the measured strain-rate dependency of deformation mechanisms while accurately reproducing the mechanical data. Hence, the model can be used to verify and further refine or infer measured strain-rate sensitivity per deformation mechanism by reproducing experimental data.

36 MATERIALS SCIENCE↗

DOE OSTI2017

A Quantitative Model for the Prediction of Sooting Tendency from Molecular Structure

Particulate matter emissions negatively affect public health and global climate, yet newer fuel-efficient gasoline direct injection engines tend to produce more soot than their port-fuel injection counterparts. Fortunately, the search for sustainable biomass-based fuel blendstocks provides an opportunity to develop fuels that suppress soot formation in more efficient engine designs. However, as emissions tests are experimentally cumbersome and the search space for potential bioblendstocks is vast, new techniques are needed to estimate the sooting tendency of a diverse range of compounds. In this study, we develop a quantitative structure-activity relationship (QSAR) model of sooting tendency based on the experimental yield sooting index (YSI), which ranks molecules on a scale from n-hexane, 0, to benzene, 100. The model includes a rigorously defined applicability domain, and the predictive performance is checked using both internal and external validation. Model predictions for compounds in the external test set had a median absolute error of ~3 YSI units. An investigation of compounds that are poorly predicted by the model lends new insight into the complex mechanisms governing soot formation. Predictive models of soot formation can therefore be expected to play an increasingly important role in the screening and development of next-generation biofuels.

09 BIOMASS FUELS↗

DOE OSTI2025

Effects of Atmosphere and Ocean Horizontal Model Resolution on Tropical Cyclone and Upper-Ocean Response Forecasts in Four Major Hurricanes

A coupled atmosphere–ocean model is necessary for tropical cyclone (TC) prediction to accurately characterize ocean feedback on atmospheric processes within the TC environment. Here, the ECMWF coupled global model is run at horizontal resolutions from 9 to 1.4 km in the atmosphere, as well as 25 and 8 km in the ocean, to identify how resolution impacts forecast accuracy of four observed major TCs in the Atlantic: Irma, Florence, Teddy, and Ida. Most of the resolutions used here are unprecedented for global models. GOES-16 and synthetic aperture radar (SAR) satellite images and best track data are used for atmospheric validation. Salinity and temperature observations from Air-Launched Autonomous Micro-Observer (ALAMO) floats are used to validate modeled upper-ocean response, including mixed layer deepening, sea surface cooling, and near-inertial waves in the wakes of TCs. Increasing atmospheric resolution leads to more realistic TC structure and stronger winds, significantly improving TC intensity forecasts and modestly improving track errors. Ocean resolution impacts the upper-ocean response but does not influence atmospheric forecasts for the fast-moving TCs considered here. Stronger mixing, sea surface cooling, and near-inertial oscillations are found for both higher atmosphere and ocean resolutions, provided the initial upper-ocean state is the same for the two ocean resolutions. Whether this agrees better with the ALAMO observations also depends on the realism of the initial upper-ocean state in the model, emphasizing the importance of ocean initialization for the accurate upper-ocean response. Overall, the model at all resolutions correctly predicts stronger mixing, surface cooling, and near-inertial oscillation amplitudes to the right of a TC center, as observed by ALAMO floats.

Atmosphere-ocean interaction↗

NASA NTRS2018

High Accuracy Coronagraph Flight Model For WFIRST–CGI Raw Contrast Sensitivity Analysis

A high-accuracy high-fidelity flight wavefront control (WFC) model is developed for detailed raw contrast sensitivity analysis of WFIRST-CGI. Built upon features of recently testbed validated model, it is further refined to combine a full Fresnel propagation diffraction model for high accuracy contrast truth evaluation, and an economical compact model for WFC purposes. Extensive individual raw contrast error sensitivities are evaluated systematically, both as known imperfections and as unknown calibration errors, for both spectroscopy mode and wide field-of-view mode with shaped pupil coronagraph. More than 90 distinct error items were identified, including system aberrations, optical misalignment, component manufacturing error, telescope interface related errors, etc. The result forms the basis for raw contrast error budget flow down to a sub-system level, where detailed specifications needed to aid in component design and manufacturing, mechanical alignment and instrument integration, and verification and validation operations. Evaluations are mostly automated, making it relatively easy for repeat runs of revised design or at new desired error quantity. Top error sensitivities and contrast floor contributors are discussed and several observations are noted.

Poberezhskiy, Ilya↗

NASA NTRS1984

NTF Modeling Program

The National Transonic Facility presents a design for and assessment of a transonic wind tunnel. Among the topics covered in viewgraph format are: aerodynamic validation models, scale models of wind tunnel components, performance evaluations of various wind tunnel parameters, and drive systems.

McKinney, L. Wayne↗

DOE OSTI2021

Validation of numerical models for seismic fluid-structure-interaction analysis of nuclear, safety-related equipment

Seismic design, qualification, and risk assessment of nuclear safety-related vessels filled with liquid will have to consider the interaction between the vessel (tank), the contained liquid, and submerged components, if any. Seismic fluid-structure-interaction (FSI) analysis of nuclear vessels will rely on numerical models, which are required to be verified and validated. This study validates previously-verified numerical models using test data generated from earthquake-simulator experiments involving a cylindrical tank. Two solvers in LS-DYNA for FSI simulations are used for the numerical analysis: Arbitrary-Lagrangian-Eulerian (ALE) and Incompressible Computational Fluid Dynamics (ICFD). Numerical and test results are compared for responses critical to seismic design of advanced reactor vessels: hydrodynamic pressures on the tank wall, reactions at the support, and wave heights of the contained liquid. Analysis is performed for one-, two-, and three-directional seismic inputs with a range of intensity, and rocking motions. The accuracy of the numerical results and different methods for outputting wave heights are discussed. Recommendations for validation of seismic FSI numerical models of advanced reactors are provided. As a result, the validation exercise presented in this study is broadly applicable to cylindrical tanks, regardless of industry sector.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site‐Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH 4 ) emissions; however, no earth system model (ESM) has represented lake CH 4 dynamics. To fill this gap, we refined a process‐based lake biogeochemical model to simulate global lake CH 4 emissions, including representation of lake bathymetry, oxic methane production (OMP), the effect of water level on ebullition, new non‐linear CH 4 oxidation kinetics, and the coupling of sediment carbon pools with in‐lake primary production and terrigenous carbon loadings. We compiled a lake CH 4 data set for model validation. The model shows promising performance in capturing the seasonal and inter‐annual variabilities of CH 4 emissions at 10 representative lakes for different lake types and the variations in mean annual CH 4 emissions among 106 lakes across the globe. The model reproduces the variations of the observed surface CH 4 diffusion and ebullition along the gradients of lake latitude, depth, and surface area. The results suggest that OMP could play an important role in surface CH 4 diffusion, and its relative importance is higher in less productive and/or deeper lakes. The model performance is improved for capturing CH 4 outgassing events in non‐floodplain lakes and the seasonal variability of CH 4 ebullition in floodplain lakes by representing the effect of water level on ebullition. The model can be integrated into ESMs to constrain global lake CH 4 emissions and climate‐CH 4 feedback.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Aqueous Degradation in Harvested Medium Voltage Cables in Nuclear Power Plants

For medium voltage (MV) power cables with voltages between 5 and 35 kV that provide power to emergency and safety support systems in nuclear power plants (NPPs), degradation and failure of cables due to water exposure has occurred. Systematic studies of current NPP MV cable systems are being carried out to determine and characterize cable-aging mechanisms and provide greater accuracy to models being developed to predict MV cable field performance to support existing cable aging management and monitoring programs. To validate models based on representative laboratory specimens, samples from harvested MV cable systems are being subjected to accelerated aging and degradation from humid conditions and submergence. Degradation will be characterized via partial discharge and voltage endurance testing of the cable and induced water tree growth in insulation. The technical approach to be used for the testing harvested MV cable samples is presented.

Duckworth, Robert↗

DOE OSTI2025

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗