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DOE OSTI2025

Motion Dynamics of Motile Microbes in Pore-Networks and its Implications for Reactive Transport Processes

This report outlines new methods to improve simulations of microbial transport and microbially mediated reactions in porous media. A range of experimental, modeling, and machine learning tools are introduced to make these simulations faster, more reliable, and useful for real-world applications. At the microscopic level, the study investigates how different types of bacteria move through confined spaces. A new artificial intelligence tool called DeepTrackStat, is introduced to track motions dynamics as observed in videos of particles migrating through pore networks. This tool is especially helpful for studying fast-moving microbes and requires less computing power than traditional tracking methods. At larger scales, the research looks at how microbes and chemicals interact in zones where surface water and groundwater meet. To connect the small- and large-scale findings, the study presents a neural network model called STAMNet. This tool helps scale up detailed small-scale microbial motion behaviors to predict large-scale environmental changes more efficiently. By combining lab experiments, computer models, and artificial intelligence, the research presented supports smarter environmental decision-making, especially in bioremediation of contaminated groundwater and protection of water quality.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Preparing large area of thermochromic nanocomposite films for smart window application

The challenges posed by high building energy bill necessitate proactive implementation of energy-efficient strategies to minimize the uses of both electricity and heating gas and promote the use of free solar energy sources. "Smart" window films/glass, leveraging thermochromic vanadium dioxide (VO 2 ), offer an adaptive approach to harness solar energy, significantly reducing the thermal load of buildings. This is achieved by reflecting the infrared portion of the solar spectrum through a phase transition in the monoclinic M-phase (M) of VO 2 induced by heating. In this study, a scalable continuous flow synthesis process invented by Argonne was employed to explore a wide parameter space, targeting the controlled synthesis of monoclinic VO 2 (M) nanoparticles with well-controlled sizes and morphologies. Additionally, a doping strategy and surface modifications were utilized for high-throughput tuning of the metal-to-insulator transition temperature. Strategies to enhance the solar modulation properties of VO 2 nanoparticles in polymer films were investigated through (i) morphological transformation from spherical to nanorod structures, (ii) surface modification with low refractive index ligands, and (iii) incorporation of additional thermochromic materials for improved solar energy modulation and aesthetically appealing colors in smart films. Furthermore, the study outlines scaling-up synthesis methods for VO 2 nanoparticles in a continuous flow reactor using hydrazine monohydrate. This comprehensive investigation provides valuable insights into the upscaling synthesis and design of advanced VO 2 /polymer composite smart window films with enhanced functionality, solar energy modulation and visible light transmittance, driving the technology a step close for industrial application.

14 SOLAR ENERGY↗

DOE OSTI2022

ORNL Hydropower Cost Database Extract from FERC Form-1

The ORNL FERC Form 1 Hydropower Cost Database Extract is a cleaned and compiled version of the hydropower component of the Federal Energy Regulatory Commission’s (FERC) Electric Utility Annual Report, also known as Form-1. The database includes conventional and pumped storage hydropower plants owned by non-federal major utilities that submitted the Form 1 data from 1994-2020, representing about 22% of existing conventional hydropower capacity and 61% of pumped storage capacity. The database includes the escalation factors and describes the methods used to scale costs to a common data year, as well as tables of identifiers necessary to link the hydropower plants to two other relevant databases, the National Inventory of Dams and the ORNL Existing Hydropower Assets database. This database provides historical capital and operating costs for three schedules/classes defined in Form 1: Large Hydro, Pumped Storage Hydro, and Small Hydro. The Large Hydro and Pumped Storage Hydro data include cost items, such as land, structures, facilities, etc.

13 HYDRO ENERGY↗

DOE OSTI2025

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Towards Ab-Initio Simulations of Crystalline Defects at the Exascale Using Spectral Quadrature Density Functional Theory

Defects in crystalline solids play a crucial role in determining properties of materials at the nano, meso- and macroscales, such as the coalescence of vacancies at the nanoscale to form voids and prismatic dislocation loops or diffusion and segregation of solutes to nucleate precipitates, phase transitions in magnetic materials via disorder and doping. First principles Density Functional Theory (DFT) simulations can provide a detailed understanding of these phenomena. However, the number of atoms needed to correctly simulate these systems is often beyond the reach of many widely used DFT codes. The aim of this article is to discuss recent advances in first principles modeling of crystal defects using the spectral quadrature method. The spectral quadrature method is linear scaling with respect to the number of atoms, permits spatial coarse-graining, and is capable of simulating non-periodic systems embedded in a bulk environment, which allows the application of appropriate boundary conditions for simulations of crystalline defects. In this article, we discuss the state-of-the-art in ab-initio modeling of large metallic systems of the order of several thousand atoms that are suitable for utilizing exascale computing resourses.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗

DOE OSTI2021

Inpainting radar missing data regions with deep learning

Abstract. Missing and low-quality data regions are a frequent problem for weather radars. They stem from a variety of sources: beam blockage, instrument failure, near-ground blind zones, and many others. Filling in missing data regions is often useful for estimating local atmospheric properties and the application of high-level data processing schemes without the need for preprocessing and error-handling steps – feature detection and tracking, for instance. Interpolation schemes are typically used for this task, though they tend to produce unrealistically spatially smoothed results that are not representative of the atmospheric turbulence and variability that are usually resolved by weather radars. Recently, generative adversarial networks (GANs) have achieved impressive results in the area of photo inpainting. Here, they are demonstrated as a tool for infilling radar missing data regions. These neural networks are capable of extending large-scale cloud and precipitation features that border missing data regions into the regions while hallucinating plausible small-scale variability. In other words, they can inpaint missing data with accurate large-scale features and plausible local small-scale features. This method is demonstrated on a scanning C-band and vertically pointing Ka-band radar that were deployed as part of the Cloud Aerosol and Complex Terrain Interactions (CACTI) field campaign. Three missing data scenarios are explored: infilling low-level blind zones and short outage periods for the Ka-band radar and infilling beam blockage areas for the C-band radar. Two deep-learning-based approaches are tested, a convolutional neural network (CNN) and a GAN that optimize pixel-level error or combined pixel-level error and adversarial loss respectively. Both deep-learning approaches significantly outperform traditional inpainting schemes under several pixel-level and perceptual quality metrics.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1969

Control systems

Computationally feasible methods of large scale systems design applied to minimax algorithms and games strategies

Chen, C. I.↗

NASA NTRS1970

Parametric excitation of a plasma

Plasma waves parametric excitation by external electric field, using perturbation method of multitime scales

Chen, C. S.↗

NASA NTRS1973

Acoustic propagation in ducts with varying cross sections and sheared mean flow.

An analysis is presented of the wave propagation and attenuation in two-dimensional ducts with slowly varying cross sections which carry sheared mean flow. A uniformly valid asymptotic expansion of the acoustic waves is obtained in terms of the maximum slope of the wall by using the method of multiple scales. The result is a first-order differential equation describing the amplitude variation with the axial distance. This equation is used to evaluate the effects of variations of the duct cross section and growing boundary layers on the different acoustic modes.

Nayfeh, A. H.↗

NASA NTRS1973

Regional geology subprogram: Geological interpretation of ERTS imagery of the occidental region of Bolivia

The author has identified the following significant results. Using ERTS-1 imagery, it is possible to delimit great lithological units, folds, lineaments, faults, and in lesser degree unconformities. In the morphological aspect, the images show clearly the relief necessary for geological interpretation. The ERTS-1 images are important for the preparation of the geological and tectonic map of Bolivia, on a 1:1 million scale, if conventional methods of work are used as a base.

Brockmann, C. E.↗

NASA NTRS1973

Acoustic propagation in ducts with varying cross sections

The method of multiple scales is used to derive the equations that describe the spatial and temporal variation of the amplitudes and phases of a wave packet propagating in slowly varying hard-walled or lined ducts. The analysis is carried out for rectangular as well as circular ducts. These equations are statements of the conservation of energy. For large admittance or high-frequency modes, an approximate expression is obtained for the attenuation. This expression shows that all possible acoustic modes are attenuating. The results also show that decreasing the cross sectional area can lead to elimination of some of the acoustic modes.

Nayfeh, A. H.↗

NASA NTRS1974

Nonlinear acoustic propagation in rectangular ducts

The method of multiple scales is used to obtain a second-order uniformly valid expansion for nonlinear acoustic wave propagation in a rectangular duct whose walls are treated with a nonlinear acoustic material. The wave propagation in the duct is characterized by the unsteady nonlinear Euler equations. The results show that nonlinear materials attenuate sound more than linear materials except at high acoustic frequencies. The nonlinear materials produce higher and combination tones which have higher attenuation rates than the fundamentals. Moreover, the attenuation rates of the fundamentals increase with increasing amplitude.

Nayfeh, A. H.↗

NASA NTRS1974

Nonlinear acoustic propagation in two-dimensional ducts

The method of multiple scales is used to obtain a second-order uniformly valid expansion for the nonlinear acoustic wave propagation in a two-dimensional duct whose walls are treated with a nonlinear acoustic material. The wave propagation in the duct is characterized by the unsteady nonlinear Euler equations. The results show that nonlinear effects tend to flatten and broaden the absorption versus frequency curve, in qualitative agreement with the experimental observations. Moreover, the effect of the gas nonlinearity increases with increasing sound frequency, whereas the effect of the material nonlinearity decreases with increasing sound frequency.

Nayfeh, A. H.↗

NASA NTRS1974

Sound waves in two-dimensional ducts with sinusoidal walls

The method of multiple scales is used to analyze the wave propagation in two-dimensional hard-walled ducts with sinusoidal walls. For traveling waves, resonance occurs whenever the wall wavenumber is equal to the difference of the wavenumbers of any two duct acoustic modes. The results show that neither of these resonating modes could occur without strongly generating the other.

Nayfeh, A. H.↗

NASA NTRS1975

Nonlinear propagation of a wave packet in a hard-walled circular duct

The method of multiple scales is used to derive a nonlinear Schroedinger equation for the temporal and spatial modulation of the amplitudes and the phases of waves propagating in a hard-walled circular duct. This equation is used to show that monochromatic waves are stable and to determine the amplitude dependance of the cutoff frequencies.

Nayfeh, A. H.↗

NASA NTRS1974

Nonlinear propagation of a wave packet in a hard-walled circular duct

Nayfeh, A. H.↗

NASA NTRS1977

Non-linear analysis of vibrations of irregular plates

A numerical perturbation method is used to investigate the forced vibrations of irregular plates. Nonlinear terms associated with the midplane stretching are retained in the analysis. The numerical part of the method involves the use of linear, finite element techniques to determine the free oscillation mode shapes and frequencies and to obtain the linear midplane stress resultants caused by the midplane stretching. Representing the solution as an expansion in terms of these linear mode shapes, these modes and the resultants are used to determine the equations governing the time-dependent coefficients of this expansion. These equations are solved by using the method of multiple scales. Specific solutions are given for the main-resonant vibrations of an elliptical plate in the presence of internal resonances. The results indicate that modes other than the driven mode can be drawn into the steady state response. Though the excitation is composed of a single harmonic, the response may not be periodic. Moreover, the particular types of responses that can occur are highly dependent on the mode being excited and are sensitive to small geometrical changes.

Lobitz, D. W.↗