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DOE OSTI2023

Gray-Box Modeling for Distribution Systems with Inverter-Based Resources

In this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, the gray-box modeling framework is constructed by encoding prior physical knowledge of the system into a whitebox model and then embedding the output variables of the white-box model into the input vector of a black-box model. Especially, the white-box modeling component is constructed alongside the equivalent network model simplified with Kron reduction. Furthermore, case studies demonstrate that our graybox modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

Zhang, Junhui↗

DOE OSTI2023

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗

DOE OSTI2020

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation

This paper combines model-based and data-driven methods to develop a hierarchical, decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level and hence significantly speed up the computational time. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system, and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

Social scientist on board in long-term management of high level and/or long-lived radioactive waste in Belgium

In Belgium, the long-term management of radioactive waste is under the exclusive competence of the Belgian Agency for Radioactive Waste and Enriched Fissile Materials (knew as ONDRAF/NIRAS). Unlike low-level waste, no institutional policy has yet been formally approved for the long-term management of high level and/or long-lived radioactive waste (knew as B and C waste). In this context, ONDRAF/NIRAS considers the public and stakeholders' participation as an essential factor in the formulation of an effective and legitimate policy. This is why it has decided to integrate them in different ways during the elaboration of the Waste Plan (ONDRAF/NIRAS-document containing guidelines to make a principled policy decision about nuclear waste management). To do so, social scientists have been regularly mobilized either as external evaluators, follow-up committee members, or participatory observants. Hence, the Waste Plan is only the first step in a long decision-making process. For a PhD student under contract with ONDRAF/NIRAS, this mandate consists of thinking out a way to construct an inter-organizational innovative communication system that would be participative, transparent and embedded in a long-term perspective, thus integrating all the further legal steps to take throughout the decision-making process. In this regard, two paradoxical constraints must be taken into account: on the one hand, my own influence on the legal decision-making process should remain limited, because of a series of constraints, lock-ins and previous decisions which have to be respected; on the other hand, ONDRAF/NIRAS expects the research conclusions to be policy relevant and useful. In this paper, the purpose is twofold. Firstly, the issues raised by this policy mandate is an opportunity to question the per-formative dimensions of the social scientist in the decision-making process and, more specifically, to have a reflexive view on our position as PhD Student. Secondly, assuming the role of 'embarked' social scientist, numerous of answers will discuss to face the different dilemmas of the researcher 'in action'. Those reflections follow on, among others, those from previous papers discussed in Quimper in April 2013 and in Leuven in June 2013. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Demonstrating Cross-Facility Data Processing at Scale with Laue Microdiffraction

In February and April 2023 live, at-scale data processing demonstrations were conducted between the Advanced Photon Source (APS), a synchrotron light source, and the Argonne Leadership Computing Facility (ALCF). These tests were run as part of a novel beamline technique: coded aperture laue micro-diffraction. This technique requires a significant amount of compute to decode appeture patterns embedded in the detector stream. An autonomous system was able to send data to ALCF during an experiment, utilize 50 nodes of the Polaris supercomputer to process 6-12 hour scans, and return the data back to the APS within 12-15 minutes behind the detector. With scan points arriving every 72 seconds, the system kept up with the beamline, potentially enabling in-experiment analysis. The data processing system utilizes Globus infrastructure and an on-demand queue to dynamically acquire nodes on Polaris. The underlying reconstruction algorithms were parallelized via MPI and accelerated with custom CUDA kernels.

Prince, Michael↗

DOE OSTI2017

Milestone Deliverable: FY18-Q1: Deploy production sliding mesh capability with linear solver benchmarking.

This milestone was focused on deploying and verifying a “sliding-mesh interface,” and establishing baseline timings for blade-resolved simulations of a sub-MW-scale turbine. In the ExaWind project, we are developing both sliding-mesh and overset-mesh approaches for handling the rotating blades in an operating wind turbine. In the sliding-mesh approach, the turbine rotor and its immediate surrounding fluid are captured in a “disk” that is embedded in the larger fluid domain. The embedded fluid is simulated in a coordinate system that rotates with the rotor. It is important that the coupling algorithm (and its implementation) between the rotating and inertial discrete models maintains the accuracy of the numerical methods on either side of the interface, i.e., the interface is “design order.”

17 WIND ENERGY↗

DOE OSTI2017

Multi-Scale Modeling of Swelling in Accident-Tolerant U 3 Si 2 Fuel

U 3 Si 2 is a promising candidate for use as an accident-tolerant fuel for light water reactors. A multi-scale computational approach was used to calculate swelling in pellet-form U 3 Si 2 fuel. Swelling was assumed to be equal to the volume fraction of fission gas bubbles in the fuel, and the evolution of bubble volume fraction was determined from phase-field simulations. To parameterize the phase-field model, density-functional theory and molecular dynamics simulations were performed. To enable molecular dynamics simulations, a new interatomic potential for the U-Si system was developed based on the modified embedded atom method. A new phase-field model based on a grand-potential functional was also developed. The model is applicable to both intergranular and intragranular bubbles. To calculate the volume fraction of bubbles, the microstructure was decomposed into regions consisting of only intragranular or intergranular bubbles based on a truncated octahedral grain structure, and growth of the bubbles in the two regions was simulated separately. The total swelling was then calculated based on a a weighted average of bubble volume fraction in the two regions. Total swelling was of the same order of magnitude, but larger than that predicted by the existing empirical swelling model used in BISON and a rate-theory based model. Limitations of the present approach and suggestions for improvement are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Cryo-FIB for TEM Investigation of Soft Matter and Beam Sensitive Energy Materials

Primarily driven by structural biology, the rapid advances in cryogenic electron microscopy techniques are now being adopted and applied by materials scientists. Samples that inherently have electron transparency can be rapidly frozen (vitrified) in amorphous ice and imaged directly on a cryogenic transmission electron microscopy (cryo-TEM), however this is not the case for many important materials systems, which can consist of layered structures, embedded architectures, or be contained within a device. Cryogenic focused ion beam (cryo-FIB) lift-out procedures have recently been developed to extract intact regions and interfaces of interest, that can then be thinned to electron transparency and transferred to the cryo-TEM for characterization. Several detailed studies have been reported demonstrating the cryo-FIB lift-out procedure, however due to its relative infancy in materials science improvements are still required to ensure the technique becomes more accessible and routinely successful. Here, we review recent results on the preparation of cryo-TEM lamellae using cryo-FIB and show that the technique is broadly applicable to a range of soft matter and beam sensitive energy materials. We then present a tutorial that can guide the materials scientist through the cryo-FIB lift-out process, highlighting recent methodological advances that address the most common failure points of the technique, such as needle attachment, lift-out and transfer, and final thinning.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Suppression of Collisionless Magnetic Reconnection in the High Ion β, Strong Guide Field Limit

Abstract In magnetic reconnection, the ion bulk outflow speed and ion heating have been shown to be set by the available reconnecting magnetic energy, i.e., the energy stored in the reconnecting magnetic field ( B r ). However, recent simulations, observations, and theoretical works have shown that the released magnetic energy is inhibited by upstream ion plasma beta β i —the relative ion thermal pressure normalized to magnetic pressure based on the reconnecting field—for antiparallel magnetic field configurations. Using kinetic theory and hybrid particle-in-cell simulations, we investigate the effects of β i on guide field reconnection. While previous works have suggested that guide field reconnection is uninfluenced by β i , we demonstrate that the reconnection process is modified and the outflow is reduced for sufficiently large β i > ( B r 2 + B g 2 ) / B r 2 . We develop a theoretical framework that shows that this reduction is consistent with an enhanced exhaust pressure gradient, which reduces the outflow speed as v out ∝ 1 / β i . These results apply to systems in which guide field reconnection is embedded in hot plasmas, such as reconnection at the boundary of eddies in fully developed turbulence like the solar wind or the magnetosheath as well as downstream of shocks such as the heliosheath or the mergers of galaxy clusters.

Giai, Carlos A.↗

DOE OSTI2019

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation: Preprint

This paper combines model-based and data-driven methods to develop a hierarchical decentralized robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level is comprised of robust model-based decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data- driven DSE, after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level, and hence to speed up the computational time significantly. The proposed hybrid framework does not depend upon the centralized infrastructure of the control centers, thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator (PDC) locations. Also, the network model is not necessary, thus a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on a 2000-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Charged-cell periodic DFT simulations via an impurity model based on density embedding: Application to the ionization potential of liquid water

Calculations of charged systems in periodic boundary conditions (PBC) are problematic because there are spurious interactions between the charges in different periodic images that can affect the physical picture. In addition, the intuitive limit of Coulomb interactions decaying to zero as the interacting charges are placed at infinite separation no longer applies, and for example total energies become undefined. Leveraging subsystem density functional theory (also known as density embedding) we define an impurity model that embeds a finite neutral or charged subsystem within an extended (infinite) surrounding subsystem. The combination of the impurity model and a consistent choice of the Coulomb reference provides us with an algorithm for evaluating the ionization potential (IP) in extended systems. Additionally, we demonstrate our approach in a pilot calculation of the IP of liquid water, based on a configuration from a prior ab initio molecular dynamics (AIMD) simulation of liquid water (Genova et al., J. Chem. Phys. 2016, 144, 234105). The calculations with the impurity model capture the broadening on the ionization energies introduced by the interactions between the water molecules. Furthermore, the calculated average IP value (10.5 eV) compare favorably to experiments (9.9-10.06 eV) and very recent simulations based on the GW approximation (10.55 eV), while at the same time outperforming density embedding calculations carried out with a naïve handling of the electrostatic interactions (about 7 eV).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

UNCOVERING THE DEEPLY EMBEDDED ACTIVE GALACTIC NUCLEUS ACTIVITY IN THE NUCLEAR REGIONS OF THE INTERACTING GALAXY Arp 299

We present mid-infrared (MIR) 8-13 μm spectroscopy of the nuclear regions of the interacting galaxy Arp 299 (IC 694+NGC 3690) obtained with CanariCam (CC) on the 10.4 m Gran Telescopio Canarias (GTC). The high angular resolution (∼0.''3-0.''6) of the data allows us to probe nuclear physical scales between 60 and 120 pc, which is a factor of 10 improvement over previous MIR spectroscopic observations of this system. The GTC/CC spectroscopy displays evidence of deeply embedded active galactic nucleus (AGN) activity in both nuclei. The GTC/CC nuclear spectrum of NGC 3690/Arp 299-B1 can be explained as emission from AGN-heated dust in a clumpy torus with both a high covering factor and high extinction along the line of sight. The estimated bolometric luminosity of the AGN in NGC 3690 is 3.2 ± 0.6 × 10{sup 44} erg s{sup –1}. The nuclear GTC/CC spectrum of IC 694/Arp 299-A shows 11.3 μm polycyclic aromatic hydrocarbon emission stemming from a deeply embedded (A{sub V} ∼ 24 mag) region of less than 120 pc in size. There is also a continuum-emitting dust component. If associated with the putative AGN in IC 694, we estimate that it would be approximately five times less luminous than the AGN in NGC 3690. The presence of dual AGN activity makes Arp 299 a good example to study such phenomena in the early coalescence phase of interacting galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Imaging of a van der Waals spin-orbit torque system using spin ensembles in hBN

Recently, optically active spin defects embedded in two-dimensional (2D) van der Waals (vdW) crystals have emerged as a transformative quantum sensing platform to explore cutting-edge materials science. Taking advantage of excellent solid-state integrability, this new class of spin defects can be readily arranged in nanoscale proximity to target materials, showing great promise for realizing in-situ quantum sensing of microscopic spin and charge behaviors in vdW heterostructures. Here we report hexagonal boron nitride-based quantum imaging of field-free deterministic magnetic switching and electric current distributions in an all-vdW spin-orbit torque (SOT) system. By visualizing variations of nanoscale magnetic stray field profile of room-temperature 2D magnet Fe 3 GaTe 2 under different SOT conditions, we show how the magnetic switching evolves from deterministic to stochastic behavior due to the interplay between spin orientations, anisotropy and Joule heating. Micromagnetic simulations rationalize our results well, revealing the role of field-like SOT in inhibiting thermal fluctuation driven stochastic switching and chaotic multi-domain competition. This understanding, which is otherwise difficult to access by conventional transport measurements, offers valuable insights into material design, testing, and performance evaluation of next-generation vdW spintronic devices.

Imaging techniques↗

DOE OSTI2018

NDT System for Metal Components in Concrete Structures (Final Report)

Steel reinforcements embedded within concrete can corrode and crack, leading to weakening of the structures, and existing NDT (non-destructive testing) techniques do not provide the full picture. Condition assessment is critical in evaluating these structures in order to ensure safe, long-term operation of the nuclear power plants. Improved NDT techniques are needed as the nation’s generating stations age and require action based on increasingly critical inspection data. The power industry uses eddy current test (ECT) during in-service inspections to detect and monitor defects such as cracks and corrosion in metals, particularly metal pipes. However, the detection of defects in the reinforcing steel embedded in concrete is far more challenging for numerous reasons. Primary among them is the concrete layer’s thickness, which prevents the ability to have a close proximity between sensor and metallic sample. One solution to this problem is to create a higher sensitivity technique which can inspect at depth, with good spatial resolution and excellent directional sensitivity, to isolate the metal buried deep in the concrete and characterize defects in the metal. The goal of the phase II research program was to study and develop a new reinforced concrete NDT technology based on anisotropic magnetoresistive (AMR) sensors designed specifically for ECT of steel reinforcements in concrete. The first technical objective was to demonstrate the capability of inspecting steel reinforcement structures, including metal rebar and tensioning cable at or below 6” of depth embedded in concrete. Another objective was to be able to confidently identify multiple layers of reinforcements at varying depths. In addition, the technique needed to be able to provide condition assessment of the metal, providing data on the structure and positioning of the steel members, material loss, and detection of the presence of breaks. An important part of the research and development was aimed at achieving superior performance compared to existing technology. The ability to detect corrosion breaks in unbonded multi-wire and multi-strand tendons was another important objective. The final objective that led to a successful program was to build a complete prototype portable scanning system capable of demonstrating the probe performance in the field. All of these objectives were met, which provided data for the system development work going forward. RMD worked with the engineering firm Simpson Gumpertz & Heger to develop a detailed problem definition for concrete structures and the necessary sensor specifications. In addition, we developed finite element simulation models for the eddy current based NDT system through the analysis of the electromagnetic (EM) properties of sample materials and the orientation of the transmitter, sensor array (receivers), metal, and intervening materials like concrete and air. Based on the modeling and specifications, we designed and fabricated prototype sensor modules. We then acquired and fabricated test samples to characterize and optimize the sensors. Finally, we built a complete prototype for testing on actual concrete structures. This new NDT technology has high promise for greatly improving capabilities in the inspection of steel reinforcements within concrete structures, such as rebar, liners, anchors, and prestressing cables. This method could be valuable in the maintenance of nuclear power plants, and many other structures critical to our nation’s infrastructure.

42 ENGINEERING↗

DOE OSTI2019

Time-Dependent Complete Active Space Embedded in Polarizable Force Field

Electron correlation and environmental effects play important roles in electron dynamics and spectroscopic observables of chemical systems in condensed phase. In this paper, we present a time-dependent complete active space configuration interaction (TD-CASCI) approach embedded in a polaraizable force filed, MMPol. The present implementation of TD-CASCI/MMPol utilizes a direct matrix-vector contraction, allowing studies of large systems. This scheme is used to study the solvatochromic shift of coumarin 153 in methanol. The TD-CASCI/MMPol approach captures the double excitation character in the excited state wave function and accurately predicts the solvatochromic red-shift of coumarin 153 dye within the experimental range, outperforming linear response time-dependent density functional theory. The effect of using different reference orbitals for the TD-CASCI/MMPol simulation is also investigated, highlighting the need for an unbiased treatment of all electronic states in the energy range of interest.

Liu, Hongbin↗

DOE OSTI2016

SU-F-T-345: Quasi-Dead Beams: Clinical Relevance and Implications for Automatic Planning

Purpose: Beam direction selection for fixed-beam IMRT planning is typically a manual process. Severe dose-volume limits on critical structures in the thorax often result in atypical selection of beam directions as compared to other body sites. This work demonstrates the potential consequences as well as clinical relevance. Methods: 21 thoracic cases treated with 5–7 beam directions, 6 cases including non-coplanar arrangements, with fractional doses of 150–411cGy were analyzed. Endpoints included per-beam modulation scaling factor (MSF), variation from equal weighting, and delivery QA passing rate. Results: During analysis of patient-specific delivery QA a sub-standard passing rate was found for a single 5-field plan (90.48% of pixels evaluated passing 3% dose, 3mm DTA). During investigation it was found that a single beam demonstrated a MSF of 34.7 and contributed only 2.7% to the mean dose of the target. In addition, the variation from equal weighting for this beam was 17.3% absolute resulting in another beam with a MSF of 4.6 contributing 41.9% to the mean dose to the target; a variation of 21.9% from equal weighting. The average MSF for the remaining 20 cases was 4.0 (SD 1.8) with an average absolute deviation of 2.8% from equal weighting (SD 3.1%). Conclusion: Optimization in commercial treatment planning systems typically results in relatively equally weighted beams. Extreme variation from this can result in excessively high MSFs (very small segments) and potential decreases in agreement between planned and delivered dose distributions. In addition, the resultant beam may contribute minimal dose to the target (quasi-dead beam); a byproduct being increased treatment time and associated localization uncertainties. Potential ramifications exist for automatic planning algorithms should they allow for user-defined beam directions. Additionally, these quasi-dead beams may be embedded in the libraries for model-based systems potentially resulting in inefficient and less accurate deliveries.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

INTEGRATION OF PARTICLE-GAS SYSTEMS WITH STIFF MUTUAL DRAG INTERACTION

Numerical simulation of numerous mm/cm-sized particles embedded in a gaseous disk has become an important tool in the study of planet formation and in understanding the dust distribution in observed protoplanetary disks. However, the mutual drag force between the gas and the particles can become so stiff—particularly because of small particles and/or strong local solid concentration—that an explicit integration of this system is computationally formidable. In this work, we consider the integration of the mutual drag force in a system of Eulerian gas and Lagrangian solid particles. Despite the entanglement between the gas and the particles under the particle-mesh construct, we are able to devise a numerical algorithm that effectively decomposes the globally coupled system of equations for the mutual drag force, and makes it possible to integrate this system on a cell-by-cell basis, which considerably reduces the computational task required. We use an analytical solution for the temporal evolution of each cell to relieve the time-step constraint posed by the mutual drag force, as well as to achieve the highest degree of accuracy. To validate our algorithm, we use an extensive suite of benchmarks with known solutions in one, two, and three dimensions, including the linear growth and the nonlinear saturation of the streaming instability. We demonstrate numerical convergence and satisfactory consistency in all cases. Our algorithm can, for example, be applied to model the evolution of the streaming instability with mm/cm-sized pebbles at high mass loading, which has important consequences for the formation scenarios of planetesimals.

79 ASTRONOMY AND ASTROPHYSICS↗