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At least 127 records · Page 7

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC 71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling–intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. Finally, this work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

14 SOLAR ENERGY↗

Covalent Organic Framework (COF) Derived Ni–N–C Catalysts for Electrochemical CO 2 Reduction: Unraveling Fundamental Kinetic and Structural Parameters of the Active Sites

Electrochemical CO 2 reduction is a potential approach to convert CO 2 into valuable chemicals using electricity as feedstock. Abundant and affordable catalyst materials are needed to upscale this process in a sustainable manner. Nickel-nitrogen-doped carbon (Ni-N-C) is an efficient catalyst for CO 2 reduction to CO, and the single-site Ni-N x motif is believed to be the active site. However, critical metrics for its catalytic activity, such as active site density and intrinsic turnover frequency, so far lack systematic discussion. In this work, we prepared a set of covalent organic framework (COF)-derived Ni-N-C catalysts, for which the Ni-N x content could be adjusted by the pyrolysis temperature. The combination of high-angle annular dark-field scanning transmission electron microscopy and extended X-ray absorption fine structure evidenced the presence of Ni single-sites, and quantitative X-ray photoemission addressed the relation between active site density and turnover frequency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of a practical approach for field scale moisture flow modeling in heterogeneous media at a semiarid site

Abstract A practical approach for modeling field‐scale moisture flow in a highly heterogeneous unsaturated medium is described in this study. The validity of this approach is demonstrated through comparison of the numerical simulations with field observations at a semiarid site located in southcentral Washington State. The methodology is based on upscaling the core scale hydraulic properties and combining power‐law and tensorial connectivity‐tortuosity (PA‐TCT) approaches to derive macroscopic anisotropy parameters for each hydrostratigraphic unit (HSU) identified in the field. Each heterogeneous HSU is approximated by an equivalent homogeneous medium (EHM) model for which PA‐TCT parameters are used in the flow simulations. The available field data on moisture content and matric potential are compared with steady‐state flow simulations based on the mean form of Richards' equation. While the homogenization or averaging of heterogeneities, embedded in the EHM modeling approximation, cannot capture all of the field‐scale variability, the simulated steady‐state moisture and matric potential profiles capture well the central tendency of the field data. This approach is deemed practical for assessing the fate and transport of contaminants in highly heterogeneous unsaturated media at the transport scale of hundreds of meters.

Khaleel, Raziuddin↗

A Time-Dependent Directional Damage Theory for Brittle Rocks Considering the Kinetics of Microcrack Growth

In this work, a novel microcrack damage theory for describing the time-dependent behavior of brittle rocks is proposed. Instead of using scalar or tensorial variables to approximate the effect of microcracks, the concept of directional damage is introduced by upscaling the directional distribution density of microcracks through the noninteracting homogenization scheme. The contribution of an individual crack on global strain is first derived from the crack-opening displacements including sliding, closure, and dilation. The model is then cast in the free energy form, and the range of parameters ensuring compliance with the second law of thermodynamics is derived rigorously. Considering that the subcritical propagation of microcracks is the dominant mechanism behind the time-dependent deformation and failure of brittle rocks, the driving force for directional damage is defined as the corresponding energy release rate, and the effect of time is introduced through a damage evolution law inspired from the kinetics of subcritical crack growth. The model is applied to simulate the behavior of basalt rock under various loading conditions. In addition to predicting the stress–strain–time response, the model offers enhanced resolution in representing the anisotropic characteristics of microcrack-induced damage in brittle rocks and their time-dependent evolutions.

58 GEOSCIENCES↗

Comparison of greenhouse gas emission estimates from six hydropower reservoirs using modeling versus field surveys

As with most aquatic ecosystems, reservoirs play an important role in the global carbon (C) cycle and emit greenhouse gases (GHG) as carbon dioxide (CO 2 ) and methane (CH 4 ). However, GHG emissions from reservoirs are poorly quantified, especially in temperate systems, resulting in high uncertainty. We compared reservoir C emission estimates and uncertainty of diffusive, ebullitive, and degassing pathways in six hydropower reservoirs in the southeastern United States among four data sources: two field-based surveys and two models (including the GHG Reservoir “G-res” Tool). We found that CH 4 diffusion was most similar across data sources (modeled minus observed, bias = - 21 g CO 2-eq m -2 y -1 ) and had low relative uncertainty (coefficient of variation, CV = 0.98). On the other hand, CO 2 diffusion was least consistent across data sources (bias = - 518 g CO 2-eq m -2 y -1 ). Both field surveys indicated strong negative CO 2 diffusion (i.e., CO 2 uptake) at all reservoirs, while G-res estimated positive CO 2 diffusion. By extension, total C emissions showed similar discrepancies, leading to high uncertainty in upscaling and interpreting reservoir source-sink dynamics. Finally, CH 4 ebullition had the highest relative uncertainty (CV = 2.77) due to high variability across sites. We discuss limitations of field surveys and these models, including temperature-based annualization methods, varying definitions of ebullition zones, low sampling resolution, and lack of dynamism. Future field efforts focused on capturing variability in CO 2 diffusion and CH 4 ebullition will be especially valuable in reducing uncertainty and improving models to advance our understanding reservoir GHG emissions.

54 ENVIRONMENTAL SCIENCES↗

Revisiting a Drag Partition Model For Canopy-Like Roughness Elements

Turbulent flows over a large surface area (S) covered by n obstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter area A and a shelter volume V. The individual sizes of A and V without any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element to n/S elements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducing A or V with each element addition. This work demonstrates that R92’s approach results in a linear background stress reduction in A and V only when the ratio of n/S is small, due to a low probability of wake interactions. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. An alternative scaling for the shelter volume is also proposed here using thermodynamic arguments of work and dissipation though the final outcome remains similar to R92. Comparisons between R92 and available data spanning more than two decades after R92 on blocks and vegetation-like roughness elements confirm the practical utility of R92. The agreement between R92 and this updated databases of experiments and simulations confirm the potential use of R92 in large-scale models provided that the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughout S. Last, a comparison between R92 and models based on first-order closure principles with constant mixing length suggests that R92 can outperform such models when evaluated across a wide range of roughness densities.

canopy turbulence↗

Integrating continuous atmospheric boundary layer and tower-based flux measurements to advance understanding of land-atmosphere interactions

The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

54 ENVIRONMENTAL SCIENCES↗

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗

Editorial special issue: Advancing foundational sun-induced chlorophyll fluorescence science

The first research on the possibilities offered by chlorophyll-a fluorescence to track the daily course of CO 2 assimilation by leaves dates back to the last century (Kautsky and Hirsch, 1931). In the second half of the XXth Century, the development of the field of active fluorescence, which relies mainly on the pulse amplitude modulation (PAM) fluorimetry technique, allowed the unraveling of the relationship between the yield of chlorophyll-a fluorescence and photochemistry (linear electron transport), which is modulated by a third process known as non-photochemical quenching (Genty et al., 1989). Since then, active fluorescence has been regularly used in ecophysiology, forestry, and crop sciences to understand the plant response to stress (Schreiber, 2004). Since the beginning of the 2000s, the development of portable field spectrometers allows for measuring passive sun-induced fluorescence (SIF) at strong solar or telluric absorption features, which do not rely on the use of artificial excitation light (e.g., Meroni and Colombo, 2006; Meroni et al., 2009; Perez-Priego et al., 2005). Since then, the field has rapidly evolved, and now fluorescence is measurable with automated field spectrometers in the field (Grossmann et al., 2018; Gu et al., 2019b; Rossini et al., 2010), airborne platforms (Rascher et al., 2015; Zarco-Tejada et al., 2000), and satellites (Guanter et al., 2012; Sun et al., 2018). These advances offer the potential to couple ecosystem-scale measurements of CO 2 fluxes and SIF to probe new aspects related to ecosystem structural impacts on SIF andphotosynthesis processes at different time-scales and on different ecosystems (e.g., Damm et al., 2010; Magney et al., 2019; Porcar-Castell et al., 2021). While SIF has been proven as a good proxy of gross primary productivity (GPP), mainly across large spatial and temporal gradients, a series of studies showed that different factors could confound this relationship, namely different canopy structures (e.g., Dechant et al., 2020; Migliavacca et al., 2017), stress conditions (e.g., Martini et al., 2022; Wieneke et al., 2018; Wohlfahrt et al., 2018), nutritional conditions (Cendrero-Mateo et al., 2015; Martini et al., 2019), species-specific differences (e.g., Van Wittenberghe et al., 2013) and light regimes (e.g., Liu and Liu, 2018). At the same time, the modeling of SIF developed rapidly (Gu et al., 2019a; Han et al., 2022; Han et al., 2021; van der Tol et al., 2014; van der Tol et al., 2009) and with an increasing degree of realism, offering the possibility to retrieve important vegetation parameters from remote sensing (Pacheco-Labrador et al., 2019; Verrelst et al., 2015; Verrelst et al., 2016; Zhang et al., 2014). Excellent and comprehensive reviews of the field are by (Mohammed et al., 2019; Porcar-Castell et al., 2021; Porcar-Castell et al., 2014; Sun et al., 2023a; Sun et al., 2023b). Despite the exponential increase in the number of publications in the field, significant progress is still needed. Here, this special issue aims to report foundational SIF science, including theoretical modeling and measurement-based research that is urgently needed to unleash the full potential of SIF for physiological and ecological applications at scales spanning from leaf to globe. The 14 articles collected in this special issue reported on the following specific aspects: first, technical capabilities enabling spectrally resolved SIF observations and their inter-comparability in space and time; second, theoretical developments in SIF-photosynthesis relationships to correctly interpret the signal and extract mechanistic information on vegetation structure and function; third, evaluation of the potential of SIF to track process beyond photosynthesis, such as transpiration; fourth, large scale-applications of SIF observations; and finally, upscaling fluorescence from leaf to canopy scales.

54 ENVIRONMENTAL SCIENCES↗

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗

Control co-design of 13 MW downwind two-bladed rotors to achieve 25% reduction in levelized cost of wind energy

Wind energy is recognized worldwide as cost-effective and environmentally friendly and is among the fastest-growing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever larger scales, which is challenging due to greater structural loads and deflections. Large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. We overview a two-bladed downwind morphing rotor concept that is expected to lower the cost of energy at wind turbine sizes beyond 13 megawatts (MW) compared with continued upscaling of traditional three-bladed upwind rotor designs. We describe an aero-structural-control co-design process that we have used in designing such extreme-scale wind turbines, and we discuss how we were able to achieve a 25% reduction in levelized cost of energy for our final turbine design compared to a conventional upwind three-bladed rotor design.

17 WIND ENERGY↗

STSR-INR: Spatiotemporal super-resolution for multivariate time-varying volumetric data via implicit neural representation

Implicit neural representation (INR) has surfaced as a promising direction for solving different scientific visualization tasks due to its continuous representation and flexible input and output settings. We present STSR-INR, an INR solution for generating simultaneous spatiotemporal super-resolution for multivariate time-varying volumetric data. Inheriting the benefits of the INR-based approach, STSR-INR supports unsupervised learning and permits data upscaling with arbitrary spatial and temporal scale factors. Unlike existing GAN- or INR-based super-resolution methods, STSR-INR focuses on tackling variables or ensembles and enabling joint training across datasets of various spatiotemporal resolutions. Here we achieve this capability via a variable embedding scheme that learns latent vectors for different variables. In conjunction with a modulated structure in the network design, we employ a variational auto-decoder to optimize the learnable latent vectors to enable latent-space interpolation. To combat the slow training of INR, we leverage a multi-head strategy to improve training and inference speed with significant speedup. We demonstrate the effectiveness of STSR-INR with multiple scalar field datasets and compare it with conventional tricubic+linear interpolation and state-of-the-art deep-learning-based solutions (STNet and CoordNet).

97 MATHEMATICS AND COMPUTING↗

Performance and economic viability assessment of a novel CO 2 adsorbent for manufacturing and integration with coal power plants

Here, this study assesses the performance and economic feasibility of a novel CO 2 adsorbent for post-combustion capture in DOE/NETL’s 650 MWnet SubC PC power plant (case B11B). Bench-scale tests showed an initial adsorption capacity of 16.3 wt%, which decreased to 12.1 wt% after 41 adsorption–desorption cycles due to induced particle aggregation by over-humidification. With a conservative adsorption capacity of 8.8 wt% and 695 adsorption–desorption cycles, an adsorbent replenishment rate of 10 tonnes/h is necessary to capture 90% of CO 2 . The breakeven sale price of the adsorbent produced at this rate is $\$$1,293/tonne, which is 40 to 80 times lower than prices for K 2 CO 3 adsorbents reported in the literature (e.g., K 2 CO 3 /TiO 2 , K 2 CO 3 /ZrO 2 ) while providing better capture performances. Sensitivity analysis reveals that increasing the plant production rate from 10 to 40 tonnes/h reduces the sale price by 8%. The study also compares the CO 2 capture cost to Cansolv, an integrated solvent-based technology. The novel adsorbent requires 2.4 GJ/tonne of CO 2 for regeneration, lower than Cansolv’s 2.7 GJ/tonne. With conservative performance estimates, the capture cost is $\$$54/tonne of CO 2 , slightly higher than Cansolv’s $\$$45/tonne. To achieve lower or comparable capture costs to Cansolv, the adsorbent should meet one of the following conditions at a commercial scale: minimum 950 cycles, 16 wt% capture capacity, 50% of the adsorbent recovery, or a reduced cost to $\$$646/tonne by upscaling the manufactury to 75 tonnes/h.

01 COAL, LIGNITE, AND PEAT↗

Development of a SnO 2 -based 44 Ti/ 44 Sc generator for medical applications

Towards application of 44 Sc for diagnostic nuclear medicine, a 44 Ti/ 44 Sc generator based on an inorganic resin has been evaluated. Unlike other radionuclide generators used for medical applications, the long-term retention of the parent 44 Ti is vital due to its long half life. In this work, tin dioxide (SnO 2 ), a robust inorganic-based resin, has been synthesized and used as the stationary phase for a 44 Ti/ 44 Sc generator. The sorption behavior of 44 Ti/ 44 Sc was tested on SnO 2 with varying acids, concentrations, and times. Preliminary batch study results showed >88 % 44 Ti retention to the resin at lower acid concentrations (0.05 M HNO 3 and 0.05 M HCl). A pilot generator was evaluated for a year, demonstrating 85.3 ± 2.8 % 44 Sc elution yields and 0.71 ± 0.14 % 44 Ti breakthrough in 5 M HNO 3 . Based on capacity studies, a 7.4 MBq (200 µCi) upscaled generator system was constructed for further evaluation of the SnO 2 resin stability and the efficacy of the eluted 44 Sc for radiolabeling. 44 Sc could be regularly eluted from this generator in 5 M HNO 3 with an overall average radiochemical yield 84.7 ± 9.5 %. Post-elution processing of the 44 Sc with DGA-normal resin removed all 44 Ti present and allowed for high 44 Sc-DOTA labeling yields of 94.2 ± 0.5 %. Overall, SnO 2 has been shown to be a viable material for a 44 Ti/ 44 Sc generator.

07 ISOTOPE AND RADIATION SOURCES↗

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37 th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H 2 ) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO 2 ) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO 2 emissions in 2050. Achieving this net-zero CO 2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO 2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $\$$250 and $\$$500 per ton CO 2 when DACCS deployed as a backstop. The average CO 2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO 2 /year, which implies a substantial upscaling of capacity to move and store CO 2 . Finally, hydrogen sensitivity scenarios showed that H 2 typically constituted a relatively small share of the overall U.S. energy system; however, H 2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Advective gas flow in bentonite: Development and comparison of enhanced multi-phase numerical approaches

Understanding the impact of repository gas, generated from degradation of waste and its interaction with the host rock, is essential when assessing the performance and safety function of long-term disposal systems for radioactive waste. Numerical models based on conventional multi-phase flow theory have historically been applied to predict the outcome and impact of gas flow on different repository components. However, they remain unable to describe the full complexity of the physical processes observed in water-saturated experiments (e.g., creation of dilatant pathways) and thus, the development of novel representations for their description is required when assessing fully saturated clay-based systems. This was the primary focus of Task A within the international cooperative project DECOVALEX-2019 (D-2019) and refinement of these approaches is the primary focus of this study (Task B in the current phase of DECOVALEX-2023). This paper summarises development of enhanced numerical representations of key processes and compares the performance of each model against high-quality laboratory test data. Experimental data reveals that gas percolation in water-saturated compacted bentonite is characterised by four key features: (i) a quiescence phase, followed by (ii) the gas breakthrough, which leads to a (iii) peak value, which is then followed by (iv) a negative decay. Three models based on the multiphase flow theory have been developed. These models can provide good initial values and reasonable responses for gas breakthrough (although some of them still predict a too-smooth response). Peak gas pressure values are in general reasonably well captured, although maximum radial stress differences are observed at 48 mm from the base of the sample. Here, numerical peak values of 12.8 MPa are predicted, whereas experimental values are about 11 MPa. These models are also capable of providing a reasonable representation of the negative pressure decay following peak pressure. However, other key specific features (such as the timing of gas breakthrough) still require a better representation. The model simulations and their comparison with experimental data show that these models need to be further improved with respect to model parameter calibration, the numerical representation of spatial heterogeneities in material properties and flow localisation, and the upscaling of the related physical processes and parameters. To further understand gas flow localisation, a new conceptual model has been developed, which shows that discrete channels can possibly be induced through the instability of gas-bentonite interface during gas injection, thus providing a new perspective for modeling gas percolation in low-permeability deformable media.

58 GEOSCIENCES↗

Discrete fracture network model benchmarks developed and applied in a DECOVALEX-2023 repository performance assessment study

This study presents newly developed benchmarks for modeling flow and transport within discrete fracture networks (DFNs) and useful methods for analyzing the results. The new benchmarks are designed to test modeling approaches for use in probabilistic performance assessment models of deep geologic repositories in fractured rock. The benchmarks simulate flow and transport through a 1 km 3 block of fractured rock. The first simulates migration of a short pulse of tracer through a simple network of four intersecting fractures. The second adds 1089 stochastically generated fractures. The third changes the pulse to a continuous point source. Evaluation of model performance relies on moment analysis and comparison of the results of different models. The expected nondimensional first moment of the conservative tracer for each benchmark is 1. The benchmarks were simulated by teams from Canada, Czechia, Germany, Korea, Sweden, Taiwan, and the United States as part of a DECOVALEX-2023 study (decovalex.org). The teams used various approaches, including explicit DFN modeling, DFN upscaling to an equivalent continuous porous medium (ECPM), and a combination of both methods. Transport mechanisms are modeled using either the advection-dispersion equation or particle tracking. Results demonstrate strong agreement among the models in breakthrough behavior up to the 75th percentile. Significant deviations in first moments and well-clustered outputs led to the identification of inaccuracies in several models. Such findings exemplify the benefit of exercising these benchmarks and using the presented methods to test DFN flow and transport models.

Benchmark↗

Reservoir-scale model of geologic hydrogen production from serpentinization: Cyclic injection in a dual-permeability fracture-matrix system

Geologic hydrogen (GeoH 2 ) from serpentinization is a promising low-carbon resource, but its reservoir-scale behavior remains poorly understood. We develop a dual-permeability reactive transport model for an injector–producer well pair in ultramafic rock that couples multiphase flow, heat transfer, geochemistry, and porosity–permeability evolution. Here, the model is calibrated to olivine flow-through experiments and upscaled to two-year long simulations with continuous injection and cyclic injection with shut-in-to-injection ratios (SIR = 1, 0.5, 0.1). Olivine reacts along high-flux pathways to form lizardite and magnetite, increasing pH; H 2 (aq) and H 2 (g) peak early and then decline as exsolution and advective export outpace local generation. Continuous injection yields the highest cumulative H 2 but the lowest water-use efficiency (1.138 x 10 –6 mol/kgw). Cyclic injection increases this ratio to 1.35 x 10 –6 , 1.377 x 10 –6 , and 1.182 x 10 –6 mol/kgw for SIR = 1, 0.5, and 0.1, respectively; SIR = 0.5 provides a ~20% improvement over continuous injection and the best compromise for pilot design.

08 HYDROGEN↗