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DOE OSTI2023

Direct Measurement of Small Particle Growth and Aging at the Atmospheric Radiation Measurement Southern Great Plains Observatory Field Campaign Report

Two identical Captive Aerosol Growth and Evolution (CAGE) chambers were operated at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory in the late summer and fall of 2021. The field study was scheduled to begin in spring, 2020, but was delayed because of the pandemic. CAGE chambers are designed to expose particles to an environment that mirrors that of the surroundings with or without a controlled perturbation designed to assess a sensitivity. The analysis here focuses on roughly the last two months of the overall study period during which measurements were almost continuous and when several perturbation experiments were conducted. Though the utility of a dual-chamber system is the ability to measure the influence of a single change on top of ambient conditions, both chambers were initially operated in the same way, with ambient air pulled through the gas exchange channel in both and ammonium sulfate particles injected into both. The similar time-dependent particle growth observed in the chambers for those periods provides confidence in differences observed during the subsequent perturbation experiments. The growth rate of particles in the reference chamber into which only ammonium sulfate particles were injected and for which only ambient air was pulled through were used to describe time-of-day averages. The average growth rate was highest in the evening and in the morning after sunrise and lowest in the late afternoon. The sensitivity of particle growth to secondary aerosol precursor gases was studied by adding them at a controlled rate to the ambient air flow pulled through one of the two chambers. Addition of 5 ppb of α-pinene resulted in an average particle growth rate of 4.4 nm hr -1 , compared with that of just 0.8 nm hr -1 in the reference chamber. The added α-pinene also triggered one new particle formation (NPF) event in the early evening just before sunset and another in the morning just after sunrise. Similarly, addition of 5 ppb of SO 2 to one chamber led to a pair of NPF events and to increased particle growth rate, though unlike the impact of added α-pinene, growth was enhanced only during the daytime when OH concentration is highest. The influence of aerosol liquid water on secondary aerosol formation and particle growth was investigated by injecting ammonium sulfate seed particles into one chamber and potassium sulfate particles into the other. Particles were injected into the two chambers four times over a 1.5-day period. The chamber relative humidity (RH) history during and following each injection was used to determine whether each particle type was crystalline or aqueous. For the case when both particle types remained crystalline throughout the period, they were tracked and for the case when they remained aqueous, the magnitude and time-dependence of the growth of both were almost exactly the same. For the other two cases the ammonium sulfate particles deliquesced upon injection and remained aqueous, while the potassium sulfate particles remained crystalline. For those two cases, the aqueous particles grew substantially faster than did the crystalline particles, providing evidence of the role of aerosol liquid water on secondary aerosol formation and particle growth.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Using Geophysical Information to Investigate Subsurface Structure within the High-Hydraulic Conductivity Analysis Zone

Within the 200 East Area of the Central Plateau and southeastward toward the Columbia River, a high-hydraulic conductivity zone (HCZ) has been interpreted to extend through the 200-PO-1 and 200-BP-5 operable units on the Hanford Site. The HCZ is a controlling hydraulic feature that impacts groundwater flow out of the 200 East Area and the fate of eastwardly migrating plumes from the 200 West Area. The lateral extent of the HCZ is highly uncertain, and despite strong evidence for the existence of the HCZ based on water-level data and contaminant plume tracking, there is still a limited understanding of how to define its boundaries. To provide additional information on the nature and extent of the HCZ, three surface geophysical methods – electrical resistivity tomography (ERT), time-domain electromagnetics (TEM), and seismic methods – were used to collect data south of 200 East. In addition, existing data from 200 East, consisting of surface seismic data, a borehole check shot survey in 699-37-47A, and borehole stratigraphic interpretations, were used to aid interpretations of newly collected seismic data south of 200 East. This work presumed that the contrast in subsurface geophysical properties would be a first-order aid identifying a transmissive zone(s) within the HCZ analysis area by imaging contrasts and/or anomalies in geophysical properties. While seismic, ERT, and TEM methods have sensitivity to overlapping physical properties (porosity, moisture content, lithology), the resolution and physics used to acquire each of these datasets are different, and therefore the information can also be different. Figure S.1 shows the locations of the geophysical data considered in this report.

58 GEOSCIENCES↗

DOE OSTI2021

Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks

Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by fully distributed watershed models, estimation through inverse modeling has had a long history in subsurface hydrology. The wide availability of stream surface flow data, compared to groundwater monitoring data, provides a new data source to infer soil and geologic properties using integrated surface and subsurface hydrologic models. As most of the existing methods have shown difficulty in dealing with highly nonlinear inverse problems, we explore the use of deep neural networks for inversion owing to their successes in mapping complex, highly nonlinear relationships. We train various deep neural network (DNN) models with different architectures to predict subsurface permeability from stream discharge hydrograph at the watershed outlet. The training data are obtained from ensemble simulations of hydrographs corresponding to an permeability ensemble using a fully-distributed, integrated surface-subsurface hydrologic model. The trained model is then applied to estimate the permeability of the real watershed using its observed hydrograph at the outlet. Our study demonstrates that the permeabilities of the soil and geologic facies that make significant contributions to the outlet discharge can be more accurately estimated from the discharge data. Their estimations are also more robust with observation errors. Compared to the traditional ensemble smoother method, DNNs show stronger performance in capturing the nonlinear relationship between permeability and stream hydrograph to accurately estimate permeability. Our study sheds new light on the value of the emerging deep learning methods in assisting integrated watershed modeling by improving parameter estimation, which will eventually reduce the uncertainty in predictive watershed models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Signal Differentiation of Moving Magnetic Nanoparticles for Enhanced Biodetection and Diagnostics

Magnetic nanoparticles are extensively utilized as markers/signal labelling in various biomedical applications. Detecting and distinguishing magnetic signals from similarly sized moving magnetic nanoparticles in microfluidic systems is crucial yet challenging for biosensing. In this study, we have developed an original method to detect and differentiate magnetic signals from moving superparamagnetic (SPM) and ferrimagnetic (FM) nanoparticles of comparable sizes. Our approach utilizes a highly sensitive magnetic-coil-based sensor that harnesses the combined effects of giant magnetoimpedance (GMI) and an LC-resonance circuit, offering performance superior to that of conventional GMI sensors. Iron oxide nanoparticles, which have similar particle sizes but differing coercivities (zero for SPM and non-zero for FM) or similar zero coercivities but differing particle sizes, flow through the magnetic coil at controlled velocities. Their distinct effects are analyzed through changes in the complex impedance of the sensing system. Our findings provide a unique pathway for utilizing SPM and FM nanoparticles as innovative magnetic markers to identify specific biological entities, thereby expanding their potential applications.

Hwang, Kee Young↗

DOE OSTI2021

Impact of Lateral Alignment for Cooling Airflow during Heavy-Truck Platooning

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the thermal control/heat rejection system sensitivity to intentional lateral offsets over a range of intervehicle spacings. Previous studies have shown the following vehicle can experience elevated temperatures and reduced airflow through the cooling package as a result of close-formation platooning. Four anemometers positioned across the grille of the following trucks as well as aligned and multiple offset positions are used to evaluate the sensitivity of the impact. Straight sections of the track are isolated for the most accurate airflow impact measurements and to be most representative of on-highway driving. An intentional lateral offset in truck platooning is considered as a controls approach to mitigate reduced cooling efficacy at close following scenarios where the highest platoon savings are achieved. The truck platooning system was tested at four gap distances from 9 to 23 meters and the following truck was either aligned with the lead or offset with a 25% width (0.65 m) or 50% width (1.3 m) lateral distance. The experimental results clearly show that offset driving is effective at bringing cooling airflow from 56% with an aligned platoon back up to 75%-80% with minimal impact to fuel savings. In addition, the offset driving can also reduce the trailing truck’s engine coolant temperature by 2°C and the corresponding underhood temperature rise by 10°C. The test outcomes indicate a plausible controls strategy to mitigate reduced cooling flow during hot-weather truck platooning while still enabling the highest-energy-saving, close-following scenarios.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2020

Mega-Gauss Plasma Jet Creation Using a Ring of Laser Beams

Using 20 OMEGA laser beams at the Laboratory for Laser Energetics, University of Rochester, to irradiate a flat plastic target in a hollow ring configuration, we created supersonic cylindrical stable plasma jets with self-generated megagauss magnetic fields extending out to >4 mm. These well-collimated magnetized jets possess a number of distinct and novel properties that will allow us to study the dynamics, physical processes, and scaling properties of astrophysical jets with a dynamic range exceeding those of previous laboratory settings. The dimensionless parameters of these laboratory jets fall in the same regime as those of young stellar object jets. These jets will also provide new versatile laser-based platforms to study magnetized shocks, shear flows, and other plasma processes under controllable conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration: Preprint

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices: Preprint

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗

DOE OSTI2025

Internship Presentation: Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

This study presents a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture aimed at detecting and mitigating compromised Human Machine Interface (HMI) and Instrumentation & Control (I&C) systems within the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). The approach combines network security solutions, hash-based algorithms, and blockchain technologies to verify system integrity and provide an immutable record of network activity. This integrated three-pronged strategy enhances the detection of system compromises, enabling preemptive action before significant damage occurs.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2025

Spatially programmed alignment and actuation in printed liquid crystal elastomers

Liquid crystal elastomers (LCEs) exhibit reversible shape morphing behavior when cycled above their nematic-to-isotropic transition temperature. During extrusion-based 3D printing, LCE inks are subjected to coupled shear and extensional flows that can be harnessed to spatially control the alignment of their nematic director along prescribed print paths. Here, we combine experiment and modeling to elucidate the effects of ink composition, nozzle geometry, and printing parameters on director alignment. From rheological measurements, we quantify the dimensionless Weissenberg number ( Wi ) for the flow field each ink experiences as a function of printing conditions and demonstrate that Wi is a strong predictor of LCE alignment. We find that director alignment in LCE filaments printed through a tapered nozzle varies radially when Wi < 1, while it is uniform when Wi ≫ 1. Based on COMSOL simulations and in operando X-ray measurements, we show that LCE inks printed through nozzles with an internal hyperbolic geometry exhibit a more uniform director alignment for a given Wi compared to those through tapered nozzles. Concomitantly, the stiffness along the print direction and actuation strain of printed LCEs increases substantially under such conditions. By varying Wi during printing through adjusting the flow rate “on the fly”, LCE architectures with uniform composition, yet locally encoded shape morphing transitions can be realized.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Spatial defects nanoengineering for bipolar conductivity in MoS 2

Understanding the atomistic origin of defects in two-dimensional transition metal dichalcogenides, their impact on the electronic properties, and how to control them is critical for future electronics and optoelectronics. Here, we demonstrate the integration of thermochemical scanning probe lithography (tc-SPL) with a flow-through reactive gas cell to achieve nanoscale control of defects in monolayer MoS 2 . The tc-SPL produced defects can present either p- or n-type doping on demand, depending on the used gasses, allowing the realization of field effect transistors, and p-n junctions with precise sub-μm spatial control, and a rectification ratio of over 10 4 . Doping and defects formation are elucidated by means of X-Ray photoelectron spectroscopy, scanning transmission electron microscopy, and density functional theory. We find that p-type doping in HCl/H 2 O atmosphere is related to the rearrangement of sulfur atoms, and the formation of protruding covalent S-S bonds on the surface. Alternatively, local heating MoS 2 in N 2 produces n-character.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗

DOE OSTI2023

Faster-than-real-time Simulation with Demonstration for Resilient DER Integration

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

Integrated System Model, Graph Trace Analysis, Adv↗

DOE OSTI2020

Controlled 3D nanoparticle deposition by drying of colloidal suspension in designed thin micro-porous architectures

Nanoparticle deposition by drying of colloidal suspension in thin micro-porous architectures has attracted a lot of attention in scientific research as well as industrial applications. However, the underlying mechanisms of such three-dimensional (3D) deposition are not yet fully revealed due to the complexity of the co-occurring processes of two-phase fluid flows, phase change and mass transport. Consequently, the control of 3D nanoparticle deposition remains a challenge. We use a combined experimental and numerical approach to achieve controlled 3D nanoparticle deposition by drying of colloidal suspension in two pillar-based thin micro-porous architectures. By the design of pillar layout, rectangular-spiral and circular-spiral deposition configurations are obtained globally. By varying the surface wettability, vertically symmetric and sloped nanoparticle depositions can be achieved locally. While the numerical modeling reveals the mechanisms of liquid internal flow, as well as the impact of local drying rate on nanoparticle transport, accumulation and final deposition, the experimental results of deposition configurations validate the controlling strategies. This combined experimental and numerical work provides a framework to achieve desired 3D nanoparticle deposition in thin micro-porous architectures, with a thorough understanding of the underlying mechanisms of two-phase fluid flows, phase change and mass transport.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Combustor assembly for low-emissions and alternate liquid fuels

Implementations of a combustor assembly yield low emissions, require low power, are suitable for alternate liquid fuels, including highly viscous fuels, and are scalable for various heat release rates. The combustor assembly includes a fuel injector and a swirler. The fuel injector may include a choke portion and a spacer. The choke portion is disposed just upstream of an outlet of a liquid fuel conduit and prevents atomizing gas from interrupting continuous flow of the liquid fuel through the liquid fuel conduit. The spacer is disposed downstream of the outlet to precisely control the gap and thus, bifurcation of atomizing gas flow, between the outlet of liquid fuel conduit and an inlet of an orifice plate. The swirler is disposed radially outwardly and adjacent the fuel injector and includes a plurality of angled vanes.

42 ENGINEERING↗

DOE OSTI2026

Quantitative Analysis and Prediction of Thermal Runaway Metrics of High-Nickel Oxide Cathodes by Machine Learning Models

The pursuit of higher energy density in lithium-ion batteries has made high-nickel (Ni) layered oxides leading cathode candidates for next-generation electric vehicles. However, their poor thermal stability, particularly at Ni contents ≥ 90%, increases the risk of cathode-initiated thermal runaway. Furthermore, we present a data-driven framework combining linear and nonlinear machine learning models to predict key thermal runaway descriptors from a high-throughput differential scanning calorimetry database. With cathode composition and state of charge (SOC) as input features, the ensemble model accurately predicts peak temperature, heat release, and peak heat flow. SHAP analysis identifies Ni content and SOC as the dominant factors controlling thermal runaway temperature, while SOC primarily governs heat release and peak heat flow. Al, Mg, and Mn improve thermal stability by strengthening metal–oxygen bonding and delaying structural transformation, whereas B mainly reduces heat release through surface passivation. Validation with a new cathode composition confirms accurate prediction of SOC-dependent thermal runaway behavior and critical SOC.

25 ENERGY STORAGE↗

DOE OSTI2022

Environmental Flow Requirements from FERC Licenses Across the US

Environmental flow requirements included in Federal Energy Regulatory Commission (FERC) hydropower licenses are important for balancing natural properties and benefits of river ecosystems (e.g., healthy species, recreation, water supply, flood control) supporting hydropower production. In some cases, environmental flow requirements may limit operational flexibility given current operational schemes and make a hydropower plant less able to provide power to the electric grid on demand. Hydropower plants may gain some flexibility as hydropower scheduling time periods are made to be more responsive to the short-term needs of an energy grid increasingly reliant on intermittent renewables. However, many flow requirements focus on the daily, monthly, or seasonal flow fluctuations which matches the time scale of most paradigms linking flow alterations to the health of river ecosystems. This dataset seeks to provide a greater understanding of how flexibility in environmental requirements can be leveraged to create positive outcomes for both the power system and the environment. It contains information on environmental flow requirements from the Protection, Mitigation, and Enhancement section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The information on environmental flow requirements was extracted from the PM&E section of 50 randomly selected FERC licenses: 25 issued from 1998-2013 that were also included in the ORNL Mitigation Database (Schramm et al. 2015) and 25 issued from 2014-present. The flow requirements were then categorized into flow augmentation categories based on whether the license stated a specific water management purpose for the given requirement called augmentation categories (i.e., fisheries or habitat, recreation or boating, industry, and general or unspecified; Table B). Requirements were also grouped into flow type categories (e.g., minimum flow rate, maximum flow rate, ramping rate). Additional information related to flow requirements such as the augmentation time-period and whether the flow rate was continuous (i.e., condition must be present at all-times) or instantaneous (i.e., condition present at a point in time) was also extracted from the licenses. Some licenses had specific flow requirements based on whether the project was in a wet, dry, or normal water year. If that information was presented in the license, it was also included in the data set. The location within the project was noted, hereafter, zone, in the dataset for flow requirements relating to specific areas of hydropower projects (Dam, Powerhouse, Bypass Reach). Maximum discharge capacities of hydropower facilities were also extracted from both the Existing Hydropower Assets (EHA) data set and the National Inventory of Dams (NID) databases. Each facility was coded with project identification codes from the EHA dataset to facilitate cross-referencing between datasets.

13 HYDRO ENERGY↗