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DOE OSTI2026

H2@Scale - Validating an Electrolysis System with High Output Pressure: Cooperative Research and Development Final Report, CRADA Number CRD-18-00741

Electrolysis has been a commercially available product for a while and electrolyzers have been a proven capability to provide additional benefits (e.g. controllable load for grid services) in addition to production of hydrogen. The hydrogen output is typically compressed for storage and dispensing. Compression adds cost and decreases system reliability. Honda’s electrolyzer systems have been developed to include electrochemical compression to leverage the production system itself for at least partial compression. In this project, the team will evaluate Honda’s PEM based electrochemical compression system. The system is capable of compressing hydrogen up to 70 MPa electrochemically. Validation testing is the next step to accelerate this technology into the marketplace, as the validation will provide needed data under a variety of operation conditions and controls. These operating conditions and controls are based on over a decade of NLR research and development with low-temperature electrolysis. The validation testing will include preparing NLR’s site for third party evaluation, benchmark testing of Honda’s stack and system, and simulating operation connected to renewables or in a grid service profile. NLR’s Energy System Integration Lab will be the location for the electrolyzer validation research and integrated into the Hydrogen Infrastructure Test & Research Facility (HITRF). This will build into the existing retail style hydrogen fueling station for a fully integrated experimental setup.

08 HYDROGEN↗

DOE OSTI2016

Bond breaking in epoxy systems: A combined QM/MM approach

A novel method to combine quantum mechanics (QM) and molecular mechanics has been developed to accurately and efficiently account for covalent bond breaking in polymer systems under high strain without the use of predetermined break locations. Use of this method will provide a better fundamental understanding of the mechano-chemical origins of fracture in thermosets. Since classical force fields cannot accurately account for bond breaking, and QM is too demanding to simulate large systems, a hybrid approach is required. In the method presented here, strain is applied to the system using a classical force field, and all bond lengths are monitored. When a bond is stretched past a threshold value, a zone surrounding the bond is used in a QM energy minimization to determine which, if any, bonds break. The QM results are then used to reconstitute the system to continue the classical simulation at progressively larger strain until another QM calculation is triggered. In this way, a QM calculation is only computed when and where needed, allowing for efficient simulations. A robust QM method for energy minimization has been determined, as well as appropriate values for the QM zone size and the threshold bond length. Compute times do not differ dramatically from classical molecular mechanical simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Problem-tailored Simulation of Energy Transport on Noisy Quantum Computers

The transport of conserved quantities like spin and charge is fundamental to characterizing the behavior of quantum many-body systems. Numerically simulating such dynamics is generically challenging, which motivates the consideration of quantum computing strategies. However, the relatively high gate errors and limited coherence times of today's quantum computers pose their own challenge, highlighting the need to be frugal with quantum resources. In this work we report simulations on quantum hardware of infinite-temperature energy transport in the mixed-field Ising chain, a paradigmatic many-body system that can exhibit a range of transport behaviors at intermediate times. We consider a chain with L = 12 sites and find results broadly consistent with those from ideal circuit simulators over 90 Trotter steps, containing up to 990 entangling gates. To obtain these results, we use two key problem-tailored insights. First, we identify a convenient basis – the Pauli Y basis – in which to sample the infinite-temperature trace and provide theoretical and numerical justifications for its efficiency relative to, e.g., the computational basis. Second, in addition to a variety of problem-agnostic error mitigation strategies, we employ a renormalization strategy that compensates for global nonconservation of energy due to device noise. We discuss the applicability of the proposed sampling approach beyond the mixed-field Ising chain and formulate a variational method to search for a sampling basis with small sample-to-sample fluctuations for an arbitrary Hamiltonian. This opens the door to applying these techniques in more general models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Single-view 3D reconstruction of correlated gamma-neutron sources

We describe a new method of 3D image reconstruction of neutron sources that emit correlated gammas (e.g. Cf- 252, Am-Be). This category includes a vast majority of neutron sources important in nuclear threat search, safeguards and non-proliferation. Rather than requiring multiple views of the source this technique relies on the source’s intrinsic property of coincidence gamma and neutron emission. As a result only a single-view measurement of the source is required to perform the 3D reconstruction. In principle, any scatter camera sensitive to gammas and neutrons with adequate timing and interaction location resolution can perform this reconstruction. Using a neutron double scatter technique, we can calculate a conical surface of possible source locations. By including the time to a correlated gamma we further constrain the source location in three-dimensions by solving for the source-to-detector distance along the surface of said cone. As a proof of concept we applied these reconstruction techniques on measurements taken with the the Mobile Imager of Neutrons for Emergency Responders (MINER). Two Cf-252 sources measured at 50 and 60 cm from the center of the detector were resolved in their varying depth with average radial distance relative resolution of 26%. To demonstrate the technique’s potential with an optimized system we simulated the measurement in MCNPX-PoliMi assuming timing resolution of 200 ps (from 2 ns in the current system) and source interaction location resolution of 5 mm (from 3 cm). Furthermore, these simulated improvements in scatter camera performance resulted in radial distance relative resolution decreasing to an average of 11%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Viscosity, relaxation time, and dynamics within a model asphalt of larger molecules

The dynamics properties of a new “next generation” model asphalt system that represents SHRP AAA-1 asphalt using larger molecules than past models is studied using molecular simulation. The system contains 72 molecules distributed over 12 molecule types that range from nonpolar branched alkanes to polar resins and asphaltenes. Molecular weights range from 290 to 890 g/mol. All-atom molecular dynamics simulations conducted at six temperatures from 298.15 to 533.15 K provide a wealth of correlation data. The modified Kohlrausch-Williams-Watts equation was regressed to reorientation time correlation functions and extrapolated to calculate average rotational relaxation times for individual molecules. The rotational relaxation rate of molecules decreased significantly with increasing size and decreasing temperature. Translational self-diffusion coefficients followed an Arrhenius dependence. Similar activation energies of ∼42 kJ/mol were found for all 12 molecules in the model system, while diffusion prefactors spanned an order of magnitude. Viscosities calculated directly at 533.15 K and estimated at lower temperatures using the Debye-Stokes-Einstein relationship were consistent with experimental data for asphalts. The product of diffusion coefficient and rotational relaxation time showed only small changes with temperature above 358.15 K, indicating rotation and translation that couple self-consistently with viscosity. At lower temperatures, rotation slowed more than diffusion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

On the Green's function of the partially diffusion-controlled reversible ABCD reaction for radiation chemistry codes

Several computer codes simulating chemical reactions in particles systems are based on the Green's functions of the diffusion equation (GFDE). Indeed, many types of chemical systems have been simulated using the exact GFDE, which has also become the gold standard for validating other theoretical models. In this work, a simulation algorithm is presented to sample the interparticle distance for partially diffusion-controlled reversible ABCD reaction. This algorithm is considered exact for 2-particles systems, is faster than conventional look-up tables and uses only a few kilobytes of memory. The simulation results obtained with this method are compared with those obtained with the independent reaction times (IRT) method. This work is part of our effort in developing models to understand the role of chemical reactions in the radiation effects on cells and tissues and may eventually be included in event-based models of space radiation risks. However, as many reactions are of this type in biological systems, this algorithm might play a pivotal role in future simulation programs not only in radiation chemistry, but also in the simulation of biochemical networks in time and space as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Hardware-in-the-Loop Co-simulation of Distribution Grid for Demand Response

In modern power systems, co-simulation is proposed as an enabler for analyzing the interactions between disparate systems. This paper introduces the co-simulation platform Virtual Grid Integration Laboratory (VirGIL) including Hardware-in-the-Loop testing, and demonstrates its potential to assess demand response strategies. VirGIL is based on a modular architecture using the Functional Mock-up Interface industrial standard to integrate new simulators. VirGIL combines state-of-the-art simulators in power systems, communications, buildings, and control. In this work, VirGIL is extended with a Hardware-in-the-Loop component to control the ventilation system of a real 12-story building in Denmark. VirGIL capabilities are illustrated in three scenarios: load following, primary reserves and load following aggregation. Experimental results show that the system can track one minute changing signals and it can provide primary reserves for up-regulation. Furthermore, the potential of aggregating several ventilation systems is evaluated considering the impact at distribution grid level and the communications protocol effect.

Rotger-Griful, Sergi↗

DOE OSTI2018

Light-Duty Vehicle Attribute Projections (Years 2015-2030)

This report describes the approach and results associated with projecting vehicle attributes for future light-duty vehicle classes and powertrains, from year 2015 to 2030. The focus is the California light-duty vehicle market and the projected attributes include fuel economy, acceleration, driving range (total and all-electric), and manufacturer suggested retail price from year 2015 to year 2030. Attributes are weighted by California vehicle sales, which are projected using a historically validated consumer choice model - the Automotive Deployment Option Projection Tool (ADOPT) - integrated with a modeling framework that simulates vehicle fuel economy, cost, and acceleration performance while optimizing vehicle components - the Future Automotive Systems Technology Simulator model (FASTSim). Both models were developed at the National Renewable Energy Laboratory and have been adapted to represent the future California light-duty vehicle market for the present report. The analysis includes several scenarios pertaining to electricity and, essentially, electric vehicle demand in California, as established by the Energy Commission. Results suggest that implementation of certain policies, such as the Corporate Average Fuel Economy standards, impacts vehicle attribute projections. The results also show that standards and policy targets are not exclusively met by changes in vehicle attributes, but also through shifts in market demand and sales for certain vehicle powertrains.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

A simulation-based assessment of technologies to reduce heat emissions from buildings

Heat emissions from buildings are part of anthropogenic heat leading to urban overheating. This paper aims to assess how technologies (i.e., energy conservation measures - ECMs), used to decrease energy use, may also reduce heat emissions from buildings. This study employs the physics-based engine EnergyPlus to simulate the main components of heat emissions from buildings to ambient air: envelope, zone, and systems. Hourly simulations are run for IECC single- and multi-family reference models with three representative climates: Miami, Baltimore, and Chicago. The results show that the performance of ECMs varies among weather, seasons, and residential typologies. Particularly, some ECMs (i.e., cool coatings, heat pumps, additional insulation, energy-awareness occupants) show a strong decrease in heat emissions, yet they are not always correlated with proportional decreases in energy use. When all ECMs are combined, the reductions are larger on heat emissions (89%) than on site energy (65%) from the base cases. During summer in Miami, the combination of ECMs shows a decrease in heat emissions from the building surface component of 80% during daytime, 92% for the HVAC component and a counterbalanced increase in the zone component of 88%, bringing to a daily decrease in total heat emissions. The main contributions of this study are quantifying how typical ECMs influence residential building heat emissions using EnergyPlus simulations and informing urban planners and stakeholders on prioritizing measures for mitigating urban overheating problems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Operational resilience metrics for power systems with penetration of renewable resources

Abstract Modern power grid is evolving towards carbon neutrality by deploying increasing amount of renewable energy resources. However, the impact of renewable generation on power system planning and operation is not sufficiently investigated, especially the capability of renewable penetrated power systems to resist and recover from major disturbances, which is a critical concern for system operators. Novel metrics and evaluation methodologies are needed to depict systems’ ability in response to events caused by natural disasters, and quantitatively evaluate system performance in various time scales. In this paper, operational resilience metrics are proposed for power systems with penetration of renewable energy resources based on transient stability principles. A systematic methodology is proposed to quantitatively assess the evolution of system performance during various stages of the disaster process. Based on the proposed metrics, a resilience‐oriented disaster management strategy is designed and validated using the modified IEEE 39‐bus test system. The simulation results demonstrate the validity of the proposed metrics and strategy, and show that the system resilience is enhanced during the mitigation of fault conditions.

Gui, Jianzhong↗

DOE OSTI2023

Fast Frequency Response using Reinforcement Learning-Controlled Wind Turbines

To fulfill the auxiliary grid services such as load regulation, spin and non-spin reserve, and frequency support during emergencies, power system operators often require certain wind farms to operate in de-loaded modes. By leveraging the fast response capability of wind farms, the reserved power in deloaded modes can significantly enhance the stability and reliability of power grids. This paper presents a novel methodology that incorporates wind turbines into reinforcement learning-based solutions for frequency response. The proposed approach employs the state-of-the-art reinforcement learning algorithm, surrogategradient- based evolution strategy (GSES), for continuous control of the wind farm output. Our methodology is tested on a modified IEEE-39 bus system, and simulation outcomes demonstrate that the proposed approach can reliably support the frequency of the power system and prevent unnecessary load shedding.

Gao, Wei↗

DOE OSTI2017

ParSplice, Version 1

The ParSplice code implements the Parallel Trajectory Splicing algorithm described in [1]. This method is part of the Accelerated Molecular Dynamics family of techniques developed in Los Alamos National Laboratory over the last 16 years. These methods aim at generating high-quality trajectories of ensembles of atoms in materials. ParSplice uses multiple independent replicas of the system in order to parallelize the generation of such trajectories in the time domain, enabling simulations of systems of modest size over very long timescales. ParSplice includes capabilities to store configurations of the system, to generate and distribute tasks across a large number of processors, and to harvest the results of these tasks to generate long trajectories. ParSplice is a management layer that orchestrate large number of calculations, but it does not perform the actual molecular dynamics itself; this is done by external molecular dynamics engines. [1] Danny Perez, Ekin D Cubuk, Amos Waterland, Efthimios Kaxiras, Arthur F Voter, Long-time dynamics through parallel trajectory splicing, Journal of chemical theory and computation 12, 18 (2015)

Perez, Danny↗

DOE OSTI2020

Simulation of the Charge Measurements for the SuperCDMS Soudan Experiment

Astronomical observations lead us to believe that dark matter constitutes the majority of the mass of the Universe, yet it has never been directly observed experimentally. The Super Cryogenic Dark Matter Search Experiment (SuperCDMS) aims to discover the particle nature of dark matter, by developing and using some of the most sensitive detectors ever built. The SuperCDMS detectors are capable of rejecting known particles to search for dark matter interactions, but the discrimination is a complicated analysis task. Previous analyses with SuperCDMS set world leading sensitivity limits to dark matter interactions, but the analysis techniques have not been based on simulations. Now we have developed an efficient simulations infrastructure that will help better understand the detectors, develop a better background model, and optimize the next generation dark matter searches. In this thesis we present the fully-functional simulations infrastructure to produce high quality samples a s well as results for the charge system readout simulations, and comparisons to expectations from data. We show that our simulations well-reproduce dominant features of data, bringing SuperCDMS closer to a robust simulation-based analysis method, much needed for the upcoming SuperCDMS dark matter searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Scientific machine learning for closure models in multiscale problems: A review

Here, closure problems are omnipresent when simulating multiscale systems, where some quantities and processes cannot be fully prescribed despite their effects on the simulation's accuracy. Recently, scientific machine learning approaches have been proposed as a way to tackle the closure problem, combining traditional (physics-based) modeling with data-driven (machine-learned) techniques, typically through enriching differential equations with neural networks. This paper reviews the different reduced model forms, distinguished by the degree to which they include known physics, and the different objectives of a priori and a posteriori learning. The importance of adhering to physical laws (such as symmetries and conservation laws) in choosing the reduced model form and choosing the learning method is discussed. The effect of spatial and temporal discretization and recent trends toward discretization-invariant models are reviewed. In addition, we make the connections between closure problems and several other research disciplines: inverse problems, Mori-Zwanzig theory, and multi-fidelity methods. In conclusion, much progress has been made with scientific machine learning approaches for solving closure problems, but many challenges remain. In particular, the generalizability and interpretability of learned models is a major issue that needs to be addressed further.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

ParSplice, Version 1

Perez, Danny↗

DOE OSTI2022

A multisite decomposition of the tensor network path integrals

Tensor network decompositions of path integrals for simulating open quantum systems have recently been proven to be useful. However, these methods scale exponentially with the system size. This makes it challenging to simulate the non-equilibrium dynamics of extended quantum systems coupled with local dissipative environments. In this work, we extend the tensor network path integral (TNPI) framework to efficiently simulate such extended systems. The Feynman–Vernon influence functional is a popular approach used to account for the effect of environments on the dynamics of the system. In order to facilitate the incorporation of the influence functional into a multisite framework (MS-TNPI), we combine a matrix product state (MPS) decomposition of the reduced density tensor of the system along the sites with a corresponding tensor network representation of the time axis to construct an efficient 2D tensor network. The 2D MS-TNPI network, when contracted, yields the time-dependent reduced density tensor of the extended system as an MPS. The algorithm presented is independent of the system Hamiltonian. We outline an iteration scheme to take the simulation beyond the non-Markovian memory introduced by solvents. Applications to spin chains coupled to local harmonic baths are presented; we consider the Ising, XXZ, and Heisenberg models, demonstrating that the presence of local environments can often dissipate the entanglement between the sites. We discuss three factors causing the system to transition from a coherent oscillatory dynamics to a fully incoherent dynamics. The MS-TNPI method is useful for studying a variety of extended quantum systems coupled with solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Numerical simulation and optimization of red mud separation thickener with self-dilute feed

In order to acquire the flow pattern and investigate the settling behavior of the red mud in the separation thickener, computational fluid dynamics (CFD), custom subroutines and agglomerates settling theory were employed to simulate the three-dimensional flow field in an industrial scale thickener with the introduction of a self-dilute feed system. Our simulation results show good agreement with the measurement onsite and the flow patterns of the thickener are presented and discussed on both velocity and concentration field. Optimization experiments on feed well and self-dilute system were also carried out, and indicate that the optimal thickener system can dilute the solid concentration in feed well from 110 g/L to 86 g/L which would help the agglomerates’ formation and improve the red mud settling speed. The additional power of recirculation pump can be saved and flocculants dosage was reduced from 105g/t to 85g/t in the operation.

42 ENGINEERING↗

DOE OSTI2023

Two-dimensional isometric tensor networks on an infinite strip

The exact contraction of a generic two-dimensional (2D) tensor network state (TNS) is known to be exponentially hard, making simulation of 2D systems difficult. The recently introduced class of isometric TNS (isoTNS) represents a subset of TNS that allows for efficient simulation of such systems on finite square lattices. The isoTNS ansatz requires the identification of an “orthogonality column” of tensors, within which one-dimensional matrix product state (MPS) methods can be used for calculation of observables and optimization of tensors. Here we extend isoTNS to infinitely long strip geometries and introduce an infinite version of the Moses Move algorithm for moving the orthogonality column around the network. Using this algorithm, we iteratively transform an infinite MPS representation of a 2D quantum state into a strip isoTNS and investigate the entanglement properties of the resulting state. In addition, we demonstrate that the local observables can be evaluated efficiently. Lastly, we introduce an infinite time-evolving block decimation algorithm (iTEBD 2 ) and use it to approximate the ground state of the 2D transverse field Ising model on lattices of infinite strip geometry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗