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At least 847 records · Page 47

Interactions between molecular-scale processes and hyporheic exchange for understanding Fe-S-C cycling in riparian wetlands (Final Report)

Wetlands represent some of the most productive ecosystems on the planet and critically influence global environmental health. Specifically, wetlands promote water quality by transforming nutrients and organic compounds and sequestering metals and contaminants. Riparian wetland hyporheic zones, where toxic surface water and anoxic groundwater mix, exhibit dynamic conditions that drive steep redox gradients and promote hotspots of diverse and fluctuating microbial activity. Changes in climate, water quality, and water quantity can disturb hydrologic flow and biogeochemical processing in these environments. Understanding how sulfate loading, impacted by hydrologic flux and anthropogenic inputs, influences iron and carbon cycling in wetlands will be crucial for predicting water quality issues driven by iron mineral precipitation and sorption, such as the release of heavy metals and other toxic elements. We used a fully integrated multi-scale and multi-method approach to develop a mechanistic understanding of how hydrologic flow influences coupled iron and sulfur cycles in riparian wetlands. This entailed hydrological, geochemical, and microbial observations at two locations: an anthropogenic sulfate-impacted riparian wetland in northern Minnesota, and a low-sulfate Fe-rich riparian wetland in Tims Branch at the Savannah River Site (SRS). These sites were characterized by hydrologically dynamic conditions where the stream and wetland systems oscillated between gaining (upward flow) and losing (downward flow) conditions that recharged the system occasionally with oxidants that fueled a variety of biogeochemical reactions. Aqueous geochemical measurements of surface water, groundwater, and porewater samples were made alongside solid-phase geochemical analyses of sediment gravity cores. Bulk X-ray absorption spectroscopy at the Advanced Photon Source (APS; Argonne) interrogated the speciation and distribution of Fe and S mineral phases of the sediments. Interestingly, it was discovered that, despite strongly reducing conditions, Fe(III) compounds and a variety of intermediate valence S compounds were stable in the subsurface. Indeed, compounds like thiosulfate, S(0), and intermediate valence organosulfur compounds were more prevalent than FeS and pyrite. The composition of the sediments did change with changes in hydrologic flow, showing their reactivity in changing redox conditions. The abundance of these intermediate S compounds was likely formed as a result of anaerobic oxidation by aqueous and solid-phase Fe(III) compounds, fueling a cryptic S cycle that is driving the breakdown of organic matter in the hyporheic zone. Microbiome surveys showed a core community that seemed stable across the landscape, but changed with increasing depth into the sediment. The community composition did not seem to change dramatically with changes in season or hydrologic flow, except for some organisms that have the potential to contribute to S cycling. More work is needed to confirm their functional activity. These fine process-scale analyses were placed within a dynamic field context using physical flow parameters from surface water and groundwater level measurements. These data helped shed light on sulfur-driven biogeochemical processes in hydrologically dynamic riparian wetlands, addressing a gap in our understanding about the impacts of pollution and other anthropogenic changes on ecologically sensitive environments.

54 ENVIRONMENTAL SCIENCES↗

Data Validation for Hosting Capacity Analyses [Slides]

The National Renewable Energy Laboratory (NREL), in partnership with the Interstate Renewable Energy Council (IREC), has recently released a report which identifies a suite of best practices for producing trusted, validated hosting capacity analysis results reflecting real-world grid conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

2022 Component Innovation Awardee: Carter Wind Turbines

Carter Wind Turbines will develop a competitively priced, portable, ultra-lightweight, self-erecting turbine that will expand the viability of wind energy systems for commercial and residential customers in areas far from population centers. The new turbine is a taller version of the Carter Model 300, which was developed with funding from previous Competitiveness Improvement Project (CIP) awards. Compared to conventional turbines, the new assembly is cheaper to ship, can be erected in one day without any cranes or heavy excavation equipment, and is compatible with the wide range of grid configurations and site conditions found in remote areas.

CIP↗

Enhancing approximate modular Bayesian inference by emulating the conditional posterior

In modular Bayesian analyses, complex models are composed of distinct modules, each representing different aspects of the data or prior information. In this context, fully Bayesian approaches can sometimes lead to undesirable feedback between modules, compromising the integrity of the inference. The “cut-distribution” prevents unwanted influence between modules by “cutting” feedback. The direct sampling (DS) algorithm is standard practice for approximating the cut-distribution, but it can be computationally intensive, especially when the number of imputations required is large. An enhanced method is proposed, the Emulating the Conditional Posterior (ECP) algorithm, which leverages emulation to increase the number of imputations. Through numerical experiment it is demonstrated that the ECP algorithm outperforms the traditional DS approach in terms of accuracy and computational efficiency, particularly when resources are constrained. Here, it is also shown how the DS algorithm can be improved using ideas from design of experiments. Some practical recommendations are given for algorithm choice in modular Bayesian analyses.

97 MATHEMATICS AND COMPUTING↗

Hydrodynamic conditions in laser irradiated buried layer experiments

The calculation of open shell ionization level and radiative properties of materials in Non-Local Thermal Equilibrium (NLTE) is currently still a major challenge for any atomic model. The predictions of various NLTE atomic codes at these conditions still differ significantly. In recent years, a new buried layer platform was developed at the Lawrence Livermore National Laboratory and the Laboratory for Laser Energetics. This platform is used to measure ionization distribution and emission of open L-shell, mid-Z ions and open M-shell, high-Z ions at NLTE conditions that are relevant in many laser plasma applications. These experiments offer a unique chance for benchmarking the atomic models. In order to perform these experiments, a uniform well characterized plasma source is required. In this work, we present one-dimensional (1D) and two-dimensional simulations of the experimental platform. These simulations were used for both the design and the analysis of the experiments. The simulations demonstrate the different phases of hydrodynamic evolution of the target and identify the time windows in which uniform conditions can be achieved. A 1D expansion of the target was found to be adequate to describe the target's evolution for most of the experiment duration. The fast 1D simulations were compared with recent experimental results from the Omega laser facility. The sensitivity of the results to several modeling parameters such as the electron flux limiter and laser resonant absorption is reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Using Spectral Measurements to Characterize Solar Reference Cells on a Two-Axis Tracker

A study is commencing relating the spectral responsivity of reference cells in the field to changing spectral distribution during the day. Initial results indicate that measurements of the incident spectral distribution can be used to match results of reference cell measurements on a two-axis tracker with a standard deviation of ±0.25% under clear-sky conditions. Initial results are provided. As more data are obtained covering a variety of field conditions and locations, the robustness of these results will be tested. The website https://midcdmz.nrel.gov/apps/sitehome.pl?site=PVRES contains the data generated by this project.

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

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Intelligent Load Control to Manage Building Loads to Support Rapid Growth of Distributed Renewable Generation

Electricity utilities are faced with the mounting challenge of providing a stable supply of power to meet the growing demand while also integrating rapid growth in distributed variable renewable generation. Traditional means of balancing short- and long-term supply and demand imbalance will be expensive. Alternative approaches of using flexible loads in buildings are needed to mitigate the imbalance at a lower cost. This paper shows how the intelligent load control (ILC) process can be used to manage loads in buildings by dynamically prioritizing loads for curtailment using both quantitative and qualitative criteria. The ILC process can be deployed on low-cost computing platforms without the need for any additional sensing. ILC was first validated in a simulation environment to provide two grid service use cases: (1) managing monthly peak electricity demand and (2) managing buildings’ electricity consumption during a capacity bidding event. After being successfully tested in a simulation environment, ILC was deployed on real buildings to manage electricity consumption to provide two different use cases under different outdoor operating conditions. Both the simulation tests and the real building experiments were deployed using VOLTTRON™, a distributed sensing and control platform. The results from the tests and experiments showed that ILC was able to manage the controllable loads (heat pumps) in the building to maintain the electricity consumption at the desired level without a significant impact on occupant comfort. Overall, the results demonstrate that the ILC allows coordination of the controllable loads and provides a more intelligent means of load management than the traditional duty-cycling approach.

Kim, Woohyun↗

Evaluating the Collision‐Coalescence Process in Idealized Cloud Convection Using Large‐Eddy Simulations With Lagrangian Microphysics

Drizzle initiation through the collision and coalescence of cloud droplets plays a crucial role in warm cloud precipitation. Recent theoretical studies suggest that the influence of collisional growth on the droplet size distribution can be quantified by a non-dimensional drizzle number (Dz). Here, large-eddy simulations with Lagrangian microphysics are employed to evaluate the theory by simulating a tall convection-cloud chamber under various conditions. Results show that the smaller the Dz, the larger the impact of collisions on the right tail of the droplet size distribution, consistent with the theory. The simulations confirm that the collision rate can be estimated from the droplet size distribution interacting only with cloud droplets of the same size at the mode radius. This suggests that the idealized theory can be a useful tool to design a cloud chamber for drizzle investigation, as well as to represent drizzle formation in models of real atmospheric clouds.

54 ENVIRONMENTAL SCIENCES↗

Mitigation of distortion of Al/steel part under simulated paint baking condition: Experiment and numerical model studies

Multi-material joining of lightweight structures is essential to reduce vehicle weight for more energy savings and less greenhouse gas emission. However, mismatch of thermal expansion coefficient for dissimilar materials during the paint baking process can induce part distortion and joint failure for adhesive bonding. Here, in the present work, a thermomechanical model based on contact mechanics and large deformation theory was developed for dissimilar high-strength Al alloy and steel components to study the distortion mechanism and influential factors of the residual gap. The established model was used to optimize joint conditions, such as pitch distance and part geometry. When a weld pitch is shorter than 100 mm, the maximum gap between Al and steel part can be greatly reduced to 0.1 mm, and the local stress and plastic strain around the joint during the oven heating and cooling cycle are also substantially reduced compared with the long pitch case (900 mm). The numerical modeling results revealed that a comparable bending stiffness ratio between the steel and Al cross sections is critical to the minimization of gap and distortion under paint baking condition. Digital image correlation technique was used to measure the overall part distortion and local strain distribution that were used to validate the model prediction. Weld bonding (adhesive bonding with friction bit joining) process was successfully employed to join Al to steel component without gap opening in adhesive after the paint baking and cooling.

36 MATERIALS SCIENCE↗

Hypervelocity impact flash expansion geometry under various spacecraft surface electrical conditions

A more congested space environment due to increasing space activities introduces new threats to spacecraft operators. Among these threats include hypervelocity impacts from microparticles (< 1 µg) in the form of meteoroids and space debris. These microparticles travel at speeds between 11.2 and 72.8 km/s with respect to the Earth and can impact spacecraft forming a small (~1 µm) and dense (~ 10 26 m -3 ) plasma. This plasma can generate a strong optical emission (impact flash) and a radio frequency (RF) emission. These emissions can lead to spacecraft electrical anomalies when the impacted spacecraft surface (target) carries high electrical potential due to various space weather effects. To understand the microparticle hypervelocity impact plasma and its associated threat to spacecraft electronics, we studied the hypervelocity impact flash expansion geometry under various spacecraft surface electrical conditions. Three high-speed broadband photomultiplier tubes (PMT) are used to capture the temporal evolution of the impact flash and the temporal evolution of the angular distribution of the impact flash expansion geometry in a 3 MV electrostatic dust accelerator during a ground-based experiment. Overall, results indicate that the impact surface electrical condition has a statistically significant influence on the impact flash geometry, and a strong similarity between the impact plasma and flash expansion geometry. Thus, this paper provides new experimental support for the impact flash origin from and connection with the impact plasma, and serves as the first impact flash expansion geometry characterization under various impact surface electrical conditions in a collisionless environment (< 10 -5 Torr).

42 ENGINEERING↗

Typological representation of the offshore oceanographic environment along the Alaskan North Slope

Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III® and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ~50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (H s ) and peak period (T p ). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

54 ENVIRONMENTAL SCIENCES↗

Convex Q-Learning in Continuous Time with Application to Dispatch of Distributed Energy Resources

Convex Q-learning is a recent approach to reinforcement learning, motivated by the possibility of a firmer theory for convergence, and the possibility of making use of greater a priori knowledge regarding policy or value function structure. This paper explores algorithm design in the continuous time domain, with a finite-horizon optimal control objective. The main contributions are (i) The new Q-ODE: a model-free characterization of the Hamilton-Jacobi-Bellman equation. (ii) A formulation of Convex Q-learning that avoids approximations appearing in prior work. The Bellman error used in the algorithm is defined by filtered measurements, which is necessary in the presence of measurement noise. (iii) Convex Q-learning with linear function approximation is a convex program. It is shown that the constraint region is bounded, subject to an exploration condition on the training input. (iv) The theory is illustrated in application to resource allocation for distributed energy resources, for which the theory is ideally suited.

Lu, Fan↗

Inverse bremsstrahlung absorption rate for super-Gaussian electron distribution functions including plasma screening

Here we provide analytic expressions for the effective Coulomb logarithm for inverse bremsstrahlung absorption which predict significant corrections to the Langdon effect and overall absorption rate compared to previous estimates. The calculation of the collisional absorption rate of laser energy in a plasma by the inverse bremsstrahlung mechanism usually makes the approximation of a constant Coulomb logarithm. We dispense with this approximation and instead take into account the velocity dependence of the Coulomb logarithm, leading to a more accurate expression for the absorption rate valid in both classical and quantum conditions. In contrast to previous work, the laser intensity enters into the Coulomb logarithm. In most laser-plasma interactions the electron distribution function is super-Gaussian [Langdon, Phys. Rev. Lett. 44, 575 (1980)], and we find the absorption rate under these conditions is increased by as much as ≈ 30% compared to previous estimates at low density. In many cases of interest the correction to Langdon's predicted reduction in absorption is large; for example at Z = 6 and Te = 400 eV the Langdon prediction for the absorption is in error by a factor of ≈ 2. However, we also account for the additional effect of plasma screening, which predicts a reduction in absorption by a similar amount (up to ≈ 30%). These two effects compete to determine the overall absorption, which may be increased or decreased, depending on the conditions. The corrections can be incorporated into radiation-hydrodynamics simulation codes by replacing the familiar Coulomb logarithm with an analytic expression which depends on the super-Gaussian order “M” and the screening length.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reagent-Triggered Isomerization of Fluxional Cluster Catalyst via Dynamic Coupling

Metallic cluster catalysts have many thermodynamically accessible isomers with diverse active sites and low reaction barriers, and lately a strong hypothesis emerged that the many catalyst states collectively drive the catalysis. Furthermore, it remained a hypothesis that catalyst isomerization is actually kinetically feasible under the current reaction conditions. Using high-temperature dynamics simulations and sampling, a range of orientations, and vibrational energy distributions, we probe how thermal effects and molecular events affect cluster catalyst dynamics. We show that even such a delicate affair as the dissociation or scattering of a methane molecule on the heavy and thus slow Pt 13 cluster triggers substantial isomerization of the catalyst, far beyond thermal at 700 K. A kinetic coupling between the methane activity and cluster catalyst dynamics is observed. In return, the thermal dynamics of the cluster affects the methane reaction and scattering probabilities. Hence, molecular events at the surfaces of fluxional cluster catalysts should facilitate the population of an ensemble of catalyst states under the current reaction conditions, with implications for available active sites, reaction mechanisms, and apparent rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DSO+T: Transactive Energy Coordination Framework (DSO+T Study: Volume 3)

This report describes a transactive energy coordination scheme designed to integrate into existing day-ahead and real-time wholesale energy markets. This scheme was evaluated in the Distribution System Operator with Transactive (DSO+T) study to assess the engineering and economic performance of the transactive energy coordination of a large-scale deployment of distributed energy resources (DER). Transactive agents were developed for a range of DERs (heating, ventilation, and air conditioning units, water heaters, batteries, and electric vehicles) that optimize flexibility over a 48-hour horizon and adjust their strategy in response to changes in real-time prices. A transactive energy coordination scheme, executed by a DSO retail market operator, aggregates these DER bids from participating customers and clears them against a DSO supply curve using a double auction market mechanism. The process of constructing the price-quantity DSO supply curve includes distribution-level transportation constraints (for example, substation congestion limits) and forecast locational marginal price of the DSO’s connected transmission node. The resulting day-ahead and real-time quantities are then bid into a competitive wholesale market operated by an independent system operator. This report also details additional capabilities for proper marketplace simulation such as wholesale price, weather, and load forecasting. The report concludes with a discussion of lessons learned and key design features required to ensure successful operation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Novel Optical Instrument for On-Line Measurement of Particle Size Distribution—Application to Clean Coal Technologies

A flow cell is a critical measurement interface for many optical instruments. However, the flows are often sampled under harsh conditions, such as under high pressure and/or high temperature, in the presence of particles, moisture, vapors with high dew points or corrosive gases. Therefore, obtaining a high-optical-quality flow cell that does not perturb the measurement is a significant challenge. To address this challenge, we proposed a new flow cell that employs a unique laminar coaxial flow field (for the purge and sample flows). A test system was built to conduct particle size distribution (PSD) measurements with no sampling bias using a state-of-the-art analyzer (Malvern Panalytical Insitec). The results revealed that the measurement zone is well defined solely by the sample flow, and the optical windows are well protected by the purge flow, with minimal risk of any depositions from the sample flow. Using this flow cell, the Insitec can successfully measure PSD under high pressure and temperature under moist, corrosive conditions without generating any sampling bias. Importantly, we successfully applied this flow cell for on-line PSD measurement for the flue gas of a 100 kWth pressurized oxy-coal combustor operating at 15 bara.

Cheng, Mao (ORCID:0000000213273900)↗